text:
Sexual Misconduct FAQ
What is Title IX?
Title IX of the Education Amendments of 1972 is a law that forbids exclusion or discrimination on the basis of sex in any education program or activity receiving federal financial assistance. This includes conventional forms of discrimination, such as differential treatment in academic programs. It also includes discrimination in the form of sexual harassment or violence.
How does Mississippi State University ensure compliance with Title IX?
The university is committed to maintaining an educational environment free from sex discrimination, sexual violence, or sexual misconduct of any type. The Title IX Coordinator oversees MSU’s efforts to prevent discrimination and misconduct, and to respond effectively when they occur.
The university strongly encourages reporting all forms of sexual misconduct. MSU’s policy is to investigate reports promptly, thoroughly and fairly, in order to ensure the safety of students, employees, and others who participate in our programs. Retaliation against those who report misconduct is not tolerated.
All members of the university community should take time to familiarize themselves with the Sexual Misconduct Policy, which can be found here.
Does Title IX apply to employees as well as students? Men as well as women?
Yes and yes. Title IX prohibits sex discrimination in “any education program or activity.” MSU’s Sexual Misconduct Policy therefore applies to all members of the university community, including students, faculty and staff. It also applies to independent contractors, visitors on campus, and those participating in university programs such as summer camps and conferences. It applies regardless of a person’s sex, sexual orientation, or gender identity.
Who is the university’s Title IX Coordinator?
The university’s Title IX Coordinator is:
The Title IX Coordinator is responsible for overseeing the university’s efforts to prevent sexual misconduct, and to respond effectively when it occurs. This includes overseeing training and awareness efforts, investigations, disciplinary proceedings, and other matters. If you have questions about university policy or other matters relating to Title IX, please feel free to contact the Office of Civil Rights Compliance.
What is sexual misconduct?
For purposes of university policy, the term “sexual misconduct” refers to unwelcome behavior of a sexual nature committed without effective consent. This includes but is not limited to the following:
- Sexual Harassment is unwelcome conduct of a sexual nature that is severe, pervasive, or persistent enough to impair a person's ability to participate in university programs or activities. It can include verbal or non-verbal communication or physical conduct. Examples of prohibited sexual harassment include, but are not limited to (a) repeated sexual solicitations toward a person who has not indicated they are welcome; (b) conditioning favorable treatment in connection with any university program upon sexual favors; (c) threats of a sexual nature that do not rise to the level of sexual assault or domestic violence; and (d) severe, pervasive, or persistent insults or derisive comments related to sex, gender, or sexual orientation directed at a specific individual.
- Sexual Assault refers to rape or other physical sexual acts perpetrated against a person without their consent. Sexual assault includes sexual penetration or intercourse or any other physical contact of a sexual nature that occurs without consent.
- Sexual Exploitation is taking sexual advantage of another person in a way that deliberately infringes on their reasonable expectation of privacy and/or security, but does not involve actual or attempted physical contact. An example of sexual exploitation would be recording images, video or audio of another person engaged in sexual activity or in a state of undress without that person’s consent, even if the sexual activity itself is consensual.
- Stalking means engaging in a course of conduct directed at a specific person that would cause a reasonable person to fear for their safety or suffer substantial emotional distress. Examples of stalking include but are not limited to physically pursuing a person against their wishes, or sending repeated, unwanted messages by electronic or other means.
- Domestic/Dating Violence refers to acts of physical violence, or threats of physical violence, committed by a person who is or has been in a social relationship of a romantic or intimate nature with the victim. The violent act itself may or may not be sexual in nature.
The university’s Sexual Misconduct Policy is interpreted in accordance with the rights to free expression held by members of the university community. Thus, the mere expression of opinions, ideas, words or symbols that another person finds objectionable will not, without more, constitute sexual misconduct.
What is consent to sexual activity?
Consent refers to words or actions that clearly show an active, knowing and voluntary agreement to engage in a particular sexual activity. Consent is determined objectively. This means that an individual is deemed to have given consent when a reasonable person, under the particular circumstances of the encounter, would understand the individual’s words and/or actions as indicating the required agreement.
Consent may be withdrawn at any time by words and/or actions that clearly show the individual no longer wishes to participate. Silence and/or the absence of resistance by themselves are not consent. Consent to engage in sexual activity in the past by itself is not consent to future sexual activity. Consent to engage in sexual activity with one person is not consent to engage in sexual activity with another person.
Other factors that may preclude consent are:
- Force or coercion. There is no consent when a person submits to sexual activity due to physical force, the threat of physical force, or coercion. Coercion refers to threatening an adverse consequence that would prevent a reasonable person from exercising free will in the decision whether to consent. Coercion is not merely words of persuasion one might reasonably use to seek voluntary consent.
- Incapacity or impairment. There is no consent if a person is mentally or physically incapacitated or impaired such that they cannot understand the fact, nature, or extent of the sexual situation. This includes impairment or incapacitation due to alcohol or drug consumption if it prevents the person from having such an understanding, as well as being asleep or unconscious. It also includes instances in which a person lacks the required understanding due to medical conditions, or cognitive or other disabilities.
- Age. There is no consent for purposes of university policy where a person is too young to give effective consent under applicable law. Under Mississippi law, persons under fourteen cannot give effective consent to sexual activity with any person who is more than twenty-four months older. Persons between fourteen and sixteen cannot give consent to anyone who is more than thirty-six months older.
What should I do if I have experienced sexual assault or other sexual misconduct?
First, you need to ensure your physical safety. Go to a safe place. If you are in danger or need emergency assistance, call 911. Once you are not in danger, you can either report the matter to MSU or contact a confidential advisor. Regardless of which option you choose—or if you choose neither—you are always free to report the matter to law enforcement.
To report the matter to MSU, contact the Title IX Coordinator at 662-325-5839 or at email@example.com. The Coordinator or their designee will assist you in obtaining supportive measures and will provide you with information on how to proceed under university policies, including submitting a formal complaint.
Alternatively, to seek confidential assistance, you have two options. First, you can contact the MSU Safeline at 662-325-3333. The Safeline is available 24 hours per day, 7 days per week. You will talk to a trained counselor, who will assist you in getting the help you need, including seeking advocacy, counseling, and/or medical care.
Second, you can contact MSU’s Office of Survivor Support Services at 662-325-3045. This office can provide direct, in-person support, including assistance in seeking counseling or medical care, navigating MSU’s investigation process, and/or filing a report with law enforcement.
Conversations with Safeline or the Office of Survivor Support Services are confidential and do not constitute a report to MSU. In either case, you are not required to submit a formal report to the university, although both can provide information on how to report if you choose to do so. Even after you have reported to MSU and/or to law enforcement, you are still free to make use of these confidential resources at any time.
Reporting to Law Enforcement
Sexual misconduct may involve violations of criminal laws. Members of the university community always retain the right to report sexual misconduct to the police, but are not required to do so. Reporting to law enforcement is separate and independent from reporting to the university. If requested, the university can assist you in contacting law enforcement to file a report.
In an emergency, the MSU and Starkville Police Departments can be reached by calling 911. Non-emergency contact information for these agencies is as follows:
|MSU Police Department
|Starkville Police Department
|Oktibbeha County Sherriff’s Office
|U.S. Dep't of Education Office of Civil Rights
Reporting to the MSU Police Department will constitute a report the university and will result in a response by the Title IX Coordinator. Reporting to other law enforcement agencies will not trigger these responses unless and until that agency or the complainant elects to share that information with the university.
There are other people at MSU who can provide confidential assistance that may be helpful to individuals who have experienced sexual assault or harassment. However, these are not considered primary responders. Reporting to them will not put the university on notice of sexual assault, and will not result in an investigation.
Consequently, the university strongly recommends that initial reports be submitted to the Title IX Coordinator or via the confidential resources listed above first. Once that has occurred, other resources include:
Student Counseling Services (662-325-2091) allows students to meet confidentially with mental health counselors. Additionally, Counseling Services can provide a Sexual Assault Advocate, who can offer confidential assistance, including (1) explaining reporting options; (2) providing accompaniment and assistance in seeking medical care or police protection; and (3) seeking other assistance without disclosing the victim’s identity.
The Longest Student Health Center (662-325-2431) provides medical care, including emergency care, to members of the university community. Health Center staff also are able to perform a Physical Evidence Recovery Kit (PERK) in cases of rape or sexual assault. Information shared with Health Center staff, including information pertaining to sexual assault or other misconduct, is confidential.
The Employee Assistance Program (1-866-219-1232) provides confidential assistance to employees covering a wide range of family, marital, and other issues. The EAP offers telephone counseling and can refer employees for in-person counseling sessions.
Anonymous complaints of discrimination, sexual misconduct, or other unethical or unlawful behavior can be made through the MSU Ethics Line, a comprehensive and confidential online reporting tool. An online report can be completed via the Ethics Line web page. To submit a report by telephone, dial 877-310-0424.
The MSU Ethics Line is not a 911 or emergency service. If your situation involves any immediate threat, call the MSU Police Department, not the Ethics Line.
Also, please note that the Ethics Line is not equivalent to reporting sexual misconduct to the Title IX coordinator. While the university will take appropriate steps to address threats to safety or other ongoing problems identified by anonymous disclosures, its ability to respond, impose discipline, and/or assist the complainant normally will be significantly limited. Members of the community are therefore strongly encouraged to consider the other options for reporting.
Is there anything I can do to preserve evidence of a sexual assault?
In many cases, yes. The following steps will help to preserve evidence of a rape or other sexual assault:
- Do not shower or douche.
- Try not to urinate. Urinating may reduce the ability to detect “date rape” drugs.
- If there was oral contact, do not smoke, eat, or brush your teeth.
- Do not change clothes. If you have already changed your clothes, place them in a paper bag, as plastic may destroy evidence. If you haven’t changed, keep the original clothes on and bring an extra set to wear home.
- If there is written or electronic evidence—such as text messages, social media, messages, or emails—in which the incident is discussed, do not delete them. Both the complainant and respondent should consider taking screenshots of any correspondence with the other party around the time of the incident. This may be important to questions concerning consent.
What will happen when I report sexual misconduct to the university?
The Title IX Coordinator or a designee will contact you to learn more about what you have reported. They will inform you of your options for seeking supportive measures, such as interim housing accommodations, or changes to class or work schedules. They will provide you with information on MSU’s policies and procedures, including how to submit a formal complaint.
The university may also take other interim steps, such as entering a no-contact order between the reporting person and the accused person. The person who contacts you also will explain the investigation and adjudication process.
Under normal circumstances, the university will strive to complete a full investigation within sixty days of a report of sexual misconduct. Depending on the results of the investigation, the university may hold a disciplinary hearing. If at the hearing the respondent is found to have committed an offense, disciplinary action will be taken.
Will information I convey to the university remain confidential?
The university will strive to keep reported information about sexual misconduct private to the greatest extent possible, but cannot guarantee that all information will be kept confidential. Once a report is submitted to a Mandatory Reporter, the university has a duty to investigate the matter and ensure the safety of all members of the community. In some instances, this means that certain information must be provided to individuals involved in an investigation.
If complainant makes a report of sexual misconduct to MSU but then declines to submit a formal complaint, the university generally will not pursue further investigation. However, there may be instances in which the Title IX Coordinator determines that the factual circumstances require the university to investigate further and/or initiate disciplinary proceedings on its own initiative.
In cases where a complainant expressly asks that no information be shared with an accused person, disciplinary action is not possible. The university will consider whether that request can be granted while still maintaining the safety of the institution and in either case will provide supportive measures to the complainant as appropriate.
What if someone attempts to retaliate against me for reporting sexual misconduct?
Retaliation against those who report sex discrimination or sexual misconduct, or who cooperate with an investigation of alleged discrimination or misconduct, whether conducted by the university or any law enforcement agency, is strictly prohibited.
Retaliation is an independent basis for disciplinary action, regardless of the outcome of the underlying complaint. Retaliation includes any adverse action that would deter a reasonable person from reporting, testifying, or otherwise cooperating with an investigation or proceeding. Any such retaliation should be reported immediately to the Title IX Coordinator or the Dean of Students.
What types of assistance can the university provide if I report sexual misconduct?
The university will take steps to assist and protect individuals who report sexual misconduct or seek confidential assistance. The Title IX Coordinator or a designee will discuss potential assistance during an initial meeting with the complaining party. Persons who wish to remain confidential should contact Student Counseling Services, which can refer them to a Sexual Assault Advocate, who can help obtain assistance without triggering a formal investigation.
Assistance may include, but is not limited to:
- Modifying class or work schedules as necessary;
- Making alternate housing or workplace arrangements;
- Addressing other academic or workplace concerns (e.g. assignments, leaves of absence, and withdrawal); and
- Providing additional and/or targeted educational programming and training.
The university may also issue orders prohibiting contact between the complainant, the accused, and/or any other member of the university community. While these accommodations are most commonly provided to complainants, the university may also make accommodations for the accused or any other person, where it deems them necessary for a prompt, fair, and impartial resolution.
What will happen if the university goes forward with disciplinary proceedings?
All investigations and disciplinary proceedings concerning alleged sexual misconduct or sex discrimination will be conducted in a prompt, fair, and impartial manner by individuals who have received appropriate training on domestic violence, sexual assault and related issues. Procedures for investigation and adjudication are included in the Sexual Misconduct Policy.
Briefly, the Title IX Coordinator will select an appropriately trained person or persons to conduct an investigation. The parties will be advised of the nature of the charges, their rights, and the procedures to be followed at any hearing. The parties will have equal rights throughout the resolution process, and will have an equal opportunity to inspect evidence present relevant witnesses and other evidence if a hearing is necessary.
Parties may be assisted by an advisor of their choosing throughout the process, who may be but is not required to be an attorney. If a party does not have an advisor, the university will appoint one upon request at no charge.
Hearings will be conducted by appropriately-trained adjudicators. The standard of proof for adjudicating any sexual misconduct charge is a preponderance of the evidence standard. In other words, the evidence must show that it is more likely than not that the alleged sexual misconduct occurred. Unless and until that standard is met, respondents are presumed not responsible for alleged misconduct.
Both the complainant and the respondent will be informed simultaneously and in writing of the outcome of any disciplinary proceeding and the procedures to appeal.
What sanctions may be imposed if a person is found responsible for sexual misconduct?
Sanctions for violations of the Sexual Misconduct Policy must be determined based on the facts of each individual case. Sanctions are distinct from non-punitive interventions—such as no-contact orders or changes in housing assignments—which the university may impose to insure the safety of community members.
Sanctions may include, but are not limited to, expulsion, suspension, conduct probation, loss of campus housing, community service, restrictions on privileges, termination of employment, reassignment of employment, restitution, educational requirements, or a formal warning.
What happens if a deliberately false report of sexual misconduct is submitted?
Submitting a deliberately false report or providing false information in bad faith is prohibited and is grounds for disciplinary action. A report is made in bad faith when the person making it actually knew it was false or made it with reckless disregard for the truth. A report is not made in bad faith merely because the facts asserted later turn out not to be accurate.
Can a complaint of sexual misconduct be resolved by informal agreement?
It depends on the nature of the misconduct. Informal resolution is appropriate only where all parties to a sexual misconduct matter request it. Even when a request is made, the university may determine that other alleged violations are sufficiently serious that informal resolution would be inappropriate. In such cases, the matter will be resolved through formal adjudication.
If the complainant and respondent both request informal resolution under circumstances in which it would be appropriate, the university will make reasonable efforts to facilitate it.
Informal resolution is strictly voluntary. No one, whether complainant or accused, will be compelled to participate in any mediation or other informal resolution. Further, informal resolution efforts always will be supervised by a properly-trained person with no conflict of interest—that is, not by an investigator or potential formal adjudicator.
Who are MSU’s Mandatory Reporters?
Most MSU employees are considered Mandatory Reporters for all matters involving sexual assault, harassment, or other forms of sexual misconduct.
If you are employed by MSU in any capacity—full time or part time—you should assume that reporting is mandatory for you unless you fall into one of the exceptions listed in MSU’s Sexual Misconduct Policy (e.g., counselors and medical staff) or have been explicitly informed by your supervisor that you are not required to report.
If you are a student employee such as a Resident Assistant or Grad Assistant, your Mandatory Reporting duties apply to the extent you are performing your job duties. For example, a Resident Assistant would be required to report sexual harassment they learned about from a resident, but not necessarily from a non-resident personal friend during a private conversation. This limitation does not apply to full time faculty or staff.
What about employees with jobs involving confidentiality, like counselors?
Certain employees are specifically exempted from Responsible Employee status. These include (1) licensed counselors, such as those at Student Counseling Services, and their staff members; and (2) health care providers and staff, such as those at the Longest Student Health Center.
University policy does not require these employees to relay any information about sexual misconduct that is reported to them. Conferring with these employees is not considered a report to the university, and will not put the university on notice of alleged sexual misconduct or trigger any university investigation or disciplinary proceedings.
What are my reporting obligations as a Mandatory Reporter?
Mandatory Reporters are required to notify the university’s Title IX Coordinator when they learn of (1) sexual misconduct involving any member of the university community, or (2) any other sexual misconduct on campus or involving any MSU program or activity. To that end, Mandatory Reporters should keep the following in mind:
- Reporting should be prompt. A Mandatory Reporter should report an incident of sexual misconduct to the Title IX Coordinator as soon as is practical under the circumstances.
- Reporting is not discretionary. The obligation to report sexual misconduct is not discretionary. A Mandatory Reporter may not, for example, decide that a matter is not sufficiently serious to report. That is a decision for the Title IX Coordinator and appropriate university officials to make.
- Mandatory reporting is not limited to matters involving students. Mandatory Reporters who learn of alleged sexual harassment or other sexual misconduct involving employees—regardless of where they occur—as well as incidents involving guests and other non-student/non-employees if they occur on campus or in connection with an MSU activity.
- Independent responses are prohibited. Under no circumstances may any employee, department, organization, or division of the university attempt to resolve unilaterally a complaint of sexual misconduct that is required to be reported under university policy. The Mandatory Reporter must always notify the Title IX Coordinator, who will determine the correct response after consultation with appropriate officials.
- Inform students of your obligations. Many Mandatory Reporters can reasonably anticipate students reporting sexual misconduct to them. The university encourages these employees to inform students of their reporting obligations in advance. When sexual misconduct is actually reported, the employee should tell the reporting person as early in the conversation as possible that any information provided will have to be relayed to the Title IX Coordinator, and that if the reporting person prefers to keep the information confidential, the university has resources such as the Student Counseling Center and Longest Health Center that can provide confidential assistance.
- Tell the reporting person what will happen next. A Mandatory Reporter should tell the person reporting sexual misconduct (1) that they will be informing the Title IX Coordinator of the incident; (2) why they are sharing this information—that is, they have an obligation to inform those on campus in a position to respond; and (3) that the university will contact them to provide additional information and support.
- Do not share the information with others. Once you have informed the Title IX Coordinator, your reporting duties are complete. You may not share the information with anyone else. If your supervisor expects to be notified of such reports, you may inform them that you have relayed a complaint to the Title IX Coordinator, and that they may contact the coordinator directly with questions or concerns.
What information about Title IX should course syllabi contain?
All course syllabi should contain the university’s standardized statement on Title IX and sexual misconduct. The statement is:
MSU is committed to complying with Title IX, a federal law that prohibits discrimination, including violence and harassment, based on sex. This means that MSU’s educational programs and activities must be free from sex discrimination, sexual harassment, and other forms of sexual misconduct. If you or someone you know has experienced sex discrimination, sexual violence and/or harassment by any member of the university community, you are encouraged to report the conduct to MSU’s Director of Civil Rights Compliance at 662-325-5839 or by e-mail to firstname.lastname@example.org.
Additional resources are available at http://students.msstate.edu/sexualmisconduct/.


The biggest acts snubbed by the Country Music Hall of Fame
On August 12, the Country Music Hall of Fame announced that it would induct Marty Stewart, Hank Williams Jr., and songwriter Dean Dillon into its ranks. Since the Hall of Fame was created in 1961, it has inducted the genre’s biggest legends throughout the decades, from Loretta Lynn and Waylon Jennings to Brooks and Dunn and George Strait.
But of course, throughout the years, the Hall of Fame has failed to recognize the contributions of some true legends. Flip through the slideshow below and look at the biggest acts snubbed by the Country Music Hall of Fame, ranging from Bobbie Gentry, the singer-songwriter behind Reba McEntire’s smash-hit “Fancy,” to Tejano legend Freddy Fender.
With a career that’s spanned nearly 50 years, it’s easy to forget that Tanya Tucker recorded her legendary hit “Delta Dawn” at the ridiculously young age of 13. In the years since, Tucker’s distinctive voice and incredible performances have made her a staple of the genre, even with her most recent release While I’m Livin, which took home the Grammy Award in 2019 for Best Country Album.


Inspiring pillowcase to prompt praying the powerful Blessing from scripture before bed.
The blessing is straight from scripture and having it easily accessible on the pillowcase makes it that much easier to start this habit of prayer.
-Pillow Size: Standard 30” x 20”
-Material: 100% Polyester; Silky Smooth Micro-Fiber
-Care: Machine Wash Cold; Tumble Dry Low
-Insert NOT included


text:
From the Editor’s Desk: The madness of March
For me, not only does the month of March mean winter is coming to an end but it means it’s time for March Madness and the NCAA college basketball tournament.
Basketball, by far, is my favorite sport. It’s all I played as a kid and continue to play today (that is before a recent roller skating disaster and injured shoulder put me out of commission). I grew up on a cattle feedlot in Johnstown, Colo. We had a dirt driveway, but that didn’t stop my dad from putting up a telephone pole-style hoop for us.
I’d sweep away any loose dirt and rocks and my dad, siblings and I enjoyed many a game of hoops on that dirt court. I wasn’t much into video games back then, so I either spent my free time playing drums or shooting baskets.
Basketball has always been a meditation for me in that respect. Even today, there’s nothing more calming than shooting a few hoops. Nowadays, I get to enjoy that with my son Jaxson, who’s already becoming a great shooter himself at age 7.
Each year, my wife and I have our own NCAA bracket competition. I’m pretty sure she’s beat me most years. Jaxson even got in on the action last year, filling out his own bracket. Three years ago, he watched us fill out our brackets and decided to create his own. A preschooler at the time, he made the most adorable bracket with made up college names.
You might say that basketball has always been one of my passions.
You can read about two others with a passion for art in this issue. Read about sculptor Michael Garman on page 4. His detailed sculptures are well-known worldwide. You can also read about Jean Bevsek on page 13. She’s a self-taught artist and author.
Also, if you’d like to join me in filling out an NCAA bracket, I’ve created a Life After 50 contest. Copy the following link into your web browser and sign up: https://tournament.fantasysports.yahoo.com/t1/group/5510/invitation?key=09abe866e993b1f4&soc_trk=lnk.
Hello from Asheville, NC. My family is big into March Madness as well. Many generations of Tarheel supporters in my family. I like that you and your wife compete with the bracket. Sounds very fun. My mom is 85 loves her Tarheels and The Hornets. The sound of a dribbling basketball takes me back to my childhood. I played in Elementary. My brother played from the time he could walk.

domain: artistic


text:
By Isaac Butler
Perhaps this is a no-brainer, but what is called intergroup contact (hanging out with people who aren’t like you) is often touted as an important way to mitigate implicit bias and lower racial anxiety. We even briefly brought up intergroup contact earlier when discussing implicit bias.
Since we talk about it so often in the news (and on this site) let’s go ahead and discuss intergroup contact in terms of white and black people. Positive intergroup contact is actually of great benefit to both. Not only does it reduce both black and white racial anxiety, but it also helps create resilience. That is to say, the next time that people are in mixed-race groups, it makes contact easier, even when those situations are fraught. Positive intergroup contact also makes future contact more likely.
Obviously, the struggle is making sure that intergroup contact remains positive. Fraught, stressful, and negative interracial interaction is only going to reinforce people’s bias, anxiety and reluctance. It’s not always guaranteed that hanging out with people is going to go well. This is as true for interracial interaction as anything else.
So here’s some things that can help facilitate positive intergroup contact:
These all apply to direct contact. But there is another kind of intergroup contact, generally called indirect contact or extended contact.
We live in a time of increased racial segregation in many areas of our lives. Because of that, sustained interracial interaction may not always be easy to achieve. Yet sustained interracial interaction is what we need.
As a result, researchers have started developing strategies that can facilitate positive interracial dynamics even among racially homogenous groups. The goal here is to enhance attitudes towards other racial groups and to lower anxiety about potential interaction with people of other races.
Thus, the extended contact effect. How extended contact works is this: Let’s say you’re white and you don’t really know a lot of black people. Your friend Terry, who is also white, has black friends. It turns out that knowing this can help positively shift your attitudes and expectations about hanging out with black people and make that interaction easier when it actually happens.
One study in California, for example, found that the extended contact effect helped reduce prejudice towards Mexican Americans amongst white subjects. In other words, simply knowing white people who had Mexican American friends made white people less prejudiced towards Mexican Americans even when they had very little actual direct contact.
Two things become clear from this body of research. First, extended contact helps reduce racial anxiety. To use a somewhat ridiculous simile, it’s kind of like when you’re a kid and you see a friend of yours successful nail some physical feat you’ve been frightened to try. If they can do it, so can you.
Second, this shows how important norms are to governing behavior, expectations and attitudes. If you’re white and know other white people with friends who aren’t white, that normalizes interracial friendships, and makes interracial contact more acceptable. This provides some interesting options for addressing prejudice and racial anxiety in racially homogenous environments, which, given the high rates of segregation in k-12 education, is vital.

domain: psychology


text:
Comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites
© Betel et al; licensee BioMed Central Ltd. 2010
Received: 26 April 2010
Accepted: 27 August 2010
Published: 27 August 2010
mirSVR is a new machine learning method for ranking microRNA target sites by a down-regulation score. The algorithm trains a regression model on sequence and contextual features extracted from miRanda-predicted target sites. In a large-scale evaluation, miRanda-mirSVR is competitive with other target prediction methods in identifying target genes and predicting the extent of their downregulation at the mRNA or protein levels. Importantly, the method identifies a significant number of experimentally determined non-canonical and non-conserved sites.
microRNAs are a class of small regulatory RNAs that are involved in post-transcriptional gene silencing. These small (approximately 22 nucleotide) single-strand RNAs guide a gene silencing complex to an mRNA by complementary base pairing, mostly at the 3' untranslated region (3' UTR). The association of the RNA-induced silencing complex (RISC) to the conjugate mRNA results in silencing the gene either by translational repression or by degradation of the mRNA . Reliable microRNA target prediction is an important and still unsolved computational challenge, hampered both by insufficient knowledge of microRNA biology as well as the limited number of experimentally validated targets.
Early studies of target recognition revealed that near-perfect complementarity at the 5' end of the microRNA, the so-called "seed region" at positions 2 to 7, is a primary determinant of target specificity . However, a perfect seed match by itself is a poor predictor for microRNA regulation due to the large number of random occurrences of any given hexamer in 3' UTRs.
Conversely, a number of studies have shown that some target sites with a mismatch or a G:U wobble in the seed region confer a noticeable regulatory effect [3–5], and a recent study using a cross-linking and immunoprecipitation (CLIP) method to study in vivo microRNA targets found a significant number of non-canonical sites [6, 7]. Therefore, perfect seed complementarity is neither necessary nor sufficient for microRNA regulation.
Most computational methods require sites to have perfect seed complementarity ("canonical" sites) [8–10], with only a few methods allowing for G:U wobbles or mismatches in the seed region [11, 12] ("non-canonical" sites). Other approaches consider predicted mRNA secondary structure and require energetically favorable hybridization between microRNA and target mRNA [13–15]. However, for the most part, all these target prediction methods generate a large number of predictions, many of which are presumed to be false. To address this problem, virtually all computational methods filter predictions by conservation, which eliminates poorly conserved candidate sites from consideration.
Several studies have used genome-wide mRNA expression changes following microRNA transfection to elucidate microRNA target specificity rules [8, 9, 16]. Grimson et al. defined a four-class hierarchy of canonical seed types of differing efficiencies and identified additional "context" features of target sites that correlate (but only weakly) with reduced expression levels, in particular the AU content flanking the target site. Using univariate regression between feature scores and expression change, they developed a seed-class-dependent scoring system called "context score", which has been incorporated into the TargetScan prediction program. Nielsen et al. assessed the significance of similar features by the shift in the cumulative distribution of log expression ratios using the same four-class seed hierarchy. Recently, proteomics studies of protein expression changes in response to microRNA transfection and knockdown [17, 18] corroborated a number of these specificity features. Importantly, these studies showed that most targets with significantly reduced protein levels also experienced detectable reduction in mRNA levels, indicating that changes in mRNA expression are reasonable indicators for microRNA regulation.
Here we present a new algorithm called mirSVR for scoring and ranking the efficiency of miRanda-predicted microRNA target sites by using supervised learning on mRNA expression changes following microRNA transfections. mirSVR incorporates target site information and contextual features into a single integrated model, without the need to define seed subclasses. We use support vector regression (SVR) to train on a wide range of features, including secondary structure accessibility of the site and conservation.
We first compared mirSVR against a number of existing target prediction algorithms using a large panel of independent microRNA transfection and inhibition experiments as test data. For a fair comparison, we limited consideration to sites with canonical seed pairing in this analysis. mirSVR performs as well as, and often better than, existing methods for the task of predicting the extent of downregulation of genes at the mRNA or protein level. The miRanda-mirSVR approach effectively broadens target prediction beyond the standard notion of seed hierarchy and strict conservation without introducing a large number of spurious predictions. In particular, we found that the mirSVR scoring model correctly identified functional but poorly conserved target sites, and that imposing a conversation filter results in a reduced rate of detection of true targets.
mirSVR downregulation scores are calibrated to correlate linearly with the extent of downregulation and therefore enable accurate scoring of genes with multiple target sites by simple addition of the individual target scores. Furthermore, the scores can be interpreted as an empirical probability of downregulation, which provides a meaningful guide for selecting a score cutoff. We found that the model can correctly identify genes that are regulated by multiple endogenous microRNAs - rather than transfected microRNAs whose concentrations are above physiological levels - by analyzing targets bound to human Argonaute (AGO) proteins as identified by AGO immunoprecipitation . We also revisited the idea of the seed hierarchy, and found that different seed types had wide and overlapping ranges of efficiencies. Finally, we tested the usefulness of including non-canonical sites in the model by evaluating performance on biochemically determined sites from recent Photo Activatable Ribonucleoside enhanced CLIP experiments (PAR-CLIP). In this data set approximately 7% of the detected sites do not contain perfect microRNA seed match to the expressed microRNAs . We found that miRanda-mirSVR indeed correctly identified a significant number of these experimentally verified non-canonical sites. miRanda target sites and mirSVR scores are available at http://www.microRNA.org.
Results and discussion
mirSVR performance: efficiency of canonical sites and the role of conservation
Training the mirSVR scoring model
For all results reported below, we trained mirSVR on a set of nine microRNA transfection experiments performed on HeLa cells from Grimson et al. . We evaluated two different training modes for our model: (1) training only on genes containing a single canonical site in the 3' UTR, called the "canonical-only" model; (2) training on genes containing a single canonical or non-canonical site in the 3' UTR, where we allow non-canonical sites with exactly one G:U wobble or mismatch in the 6-mer seed region, called the "all-sites" model. The first mode produces a model that is readily compared with most existing target prediction methods, which largely assume at least a 6-mer seed match, while the second mode allows us to assess whether we can achieve statistically significant prediction results on non-canonical sites. Consistent with previous studies [8, 9], the most significant features are base-pairings at the seed region and the sequence composition flanking to the seed region (Additional file 1, Figure S1). Additional features such as conservation, position in the UTR, and UTR length are weakly correlated with the extent of downregulation.
mirSVR scores improve ranking of canonical sites over existing target prediction methods
We first tested the canonical-only mirSVR prediction model, where we restricted consideration to genes with single canonical target sites, that is, sites with perfect complementarity to positions 2 to 7 of the microRNA. The test data consists of 17 independent microRNA transfection experiments followed by mRNA expression profiling from Linsley et al. , five microRNA transfection experiments followed by protein expression measurements from Selbach et al. , and three microRNA inhibition experiments followed by mRNA expression profiling [21–23].
We compared the performance of the mirSVR model against well-known existing target prediction methods that were representative of the different methodologies, namely: TargetScan's context score , which incorporates contextual feature scores estimated from expression data from transfection experiments and, like mirSVR, was optimized to predict the expression changes of the target genes; miRanda's alignment score [11, 24], which was designed to score the quality of the miRNA::site duplex using dynamic programming and was the first method to incorporate binding at the 3' end of the microRNA; and PITA's energy score , derived from a secondary structure based method which computes the difference between the free energy of the predicted microRNA-target duplex and the energetic cost of unpairing the local secondary structure of the target site. For a general performance measure, we computed the Spearman rank correlation between the observed log expression change and the prediction score, which gives a general measure of the overall ranking performance of the algorithm. It is important to note that for this analysis, we did not filter the potential canonical target sites for conservation: mirSVR and comparison methods were required to rank all sites with seed matches, whether or not the sites are conserved. In this sense, we are not performing a typical method comparison of existing target prediction programs as they are implemented through various web servers. Instead, we are assessing the intrinsic value of different target site scoring systems to predict the extent of microRNA regulation.
In addition to the Spearman rank correlation, we compared the performance of mirSVR and context score by an ROC analysis where the true positive and true negative sets are defined as the top and bottom 20% of candidate target genes based on their expression changes following microRNA transfection (or inhibition) (Figure 2b). Consistent with the rank correlation results, mirSVR has a larger AUC (area under the ROC curve) than context score in 19 out of the 25 test cases (P < 0.006, Figure 2c). The results from both the rank correlation and ROC analysis indicate that mirSVR improves target ranking over the context score method for both reduction of mRNA levels and reduction of protein levels.
We also did a more limited comparison of mirSVR against context score, miRanda, PITA and two additional methods for which we could obtain published target site predictions but had no access to source code: PicTar  and Diana-microT . In contrast to our main method comparison (Figure 2), here we were restricted to a limited number of target sites that were predicted by both additional algorithms, and in particular all sites were required to pass the conservation filter imposed by PicTar. For statistically meaningful results, we considered only experiments for which ≥ 50 targets were scored by all methods. Even when limited to a small set of conserved targets, mirSVR improves over all other methods in 8 out of 11 experiments in the Linsley et al. data set when evaluated in terms of rank correlation with extent of downregulation (Additional file 1, Figure S2a); for the other test sets, no experiments contained enough scored targets to make a comparison. Moreover, when assessing the mean log expression change of the top 50 predictions of each method, mirSVR's top predictions exhibit greater downregulation than those of any other method (Additional file 1, Figure S2b).
mirSVR detects genes with effective but non-conserved sites
However, for the task of detecting the most downregulated targets with single canonical sites in the Linsley et al. and Selbach et al. test sets, we found that the detection rate as a function of the number of predictions did not improve at any point by imposing a more stringent conservation filter (Figure 3b). If it were a good idea to filter mirSVR results for conservation, we would expect to see the detection curve for more conserved sites to climb more steeply than the detection curve for less conserved sites; instead, the detection curves for conservation filters all initially climb at the same rate. Eventually, as we run out of conserved sites that are in the 5% most downregulated set, the more conserved detection curves plateau at a lower detection rate, showing that a substantial number of downregulated targets are missed. We note that this effect is not restricted to our particular choice of conservation measure or even to the mirSVR scoring system. We repeated the analysis with context scores downloaded from TargetScan and using their associated conservation scores (P CT )  and similarly found no improvement in detection rates of the most downregulated targets with increased P CT threshold (Additional file 1, Figure S3). These results, which are consistent with previous work , suggest that conservation should be used in combination with other informative features to score target sites and not as hard filter, which leads to a substantial loss of bona fide targets.
A unified scoring model for microRNA target sites
Interpreting mirSVR scores in terms of downregulation
The analysis so far has focused on genes with single canonical microRNA target sites for a straightforward comparison to existing methods. To obtain a unified model for a wider range of sites, we retrained mirSVR on all genes in the Grimson et al. data set containing either a single canonical target site or a single non-canonical site with at most a single G:U wobble or mismatch in the seed region. We confirmed that the "all-sites" mirSVR model performed similarly to our "canonical-only" mirSVR model for the task of predicting downregulation of canonical target genes (Additional file 1, Figure S4).
Seed classes have broad ranges of efficiencies
Previous reports identified four seed types that roughly correlate with extent of downregulation (8 mer > 7(m8) > 7(A1) > 6 mer) . After rescaling mirSVR scores to correlate linearly with downregulation, we reexamined the notion of seed hierarchy in terms of mirSVR scores. Consistent with previous observations, we found that the mean mirSVR score by seed type generally agreed with the reported class hierarchy, namely, that longer seed matches correlate with extent of downregulation. However, each seed type had a broad distribution of scores, with considerable overlap between the different seed types (Figure 5b). In particular, there is a large overlap between score ranges for 8-mer sites and the 7(m8) sites and only a subtle difference between the 7(A1) and 6-mer distributions. Therefore, the distinction between seed classes and the subsequent rules used to rank their efficiency do not correctly capture the range of regulatory effect, and the assumption that longer complementarity in the seed region gives stronger inhibition does not always hold. We propose that our score-based method, which is independent of seed classification, provides a more meaningful ranking of target sites efficiency.
Predicting the targets of endogenous microRNAs
mirSVR correctly extends to genes regulated by multiple endogenous microRNAs
So far we have measured mirSVR performance using expression data from microRNA transfection experiments. However, overexpression of microRNAs by transfection experiments may lead to stronger or more widespread downregulation than observed under physiological conditions and also appears to perturb endogenous microRNA regulation in the cell by out-competing the endogenous microRNAs for the silencing machinery . In addition, the majority of cells express multiple microRNAs at significant levels  and most 3' UTRs have multiple predicted target sites for different microRNAs. It is therefore likely that under physiological conditions many genes are subjected to concurrent regulation by multiple microRNAs, and several target prediction methods model regulation by multiple microRNA sites [10, 25]. To test the performance of the mirSVR all-site model on more physiological relevant targets, we generated another test set from published microarray data from AGO IP experiments . RNA extracted from AGO1-4 immunoprecipitation was analyzed on a microarray platform and compared to RNA extracted from the washed lysate. The endogenous microRNA targets are identified as the set of genes that are enriched in the AGO-IP relative to the cleared lysate and contained a predicted microRNA target site for the endogenously expressed microRNAs.
We included in our prediction set genes with target sites for any or all of the top six endogenously expressed microRNAs (miR-16, miR-19b, miR-30e-5p, miR-32, miR-20a, miR-21). An ROC analysis where the true sites are the 20% most AGO-IP enriched genes and false predictions are the top 20% most enriched in the washed lysate achieved an AUC of 0.72. Moreover, of the top 20% most enriched genes in the AGO-IP, mirSVR correctly detected approximately 85% of these genes as targets of one or more of the endogenous microRNAs using a gene-level mirSVR score threshold of -0.1. In addition, we compared the mirSVR canonical-only model to context score using this AGO IP test set. Similarly to the transfection experiments, we found that mirSVR improves over context score both when comparing the rank correlation of the prediction scores with the enrichment in the AGO IP and by ROC analysis (Additional file 1, Figure S6). Therefore, although mirSVR was trained on data from microRNA overexpression experiments, which may include non-physiological targets, it makes meaningful target predictions for endogenous microRNAs expressed at regular cellular concentrations.
mirSVR identifies functional non-canonical sites
A number of studies have shown that non-canonical sites can lead to downregulation of target genes [3, 30–32], although it is unclear whether these examples represent a widespread pattern of microRNA regulation. Recent large-scale biochemical identification of mammalian microRNA targets have shown that approximately 7% of the target sites are non-canonical [6, 7] confirming that non-canonical sites account for an appreciable part of microRNA-mediated silencing. The correlation between mirSVR scores and downregulation shows that while canonical sites are generally more effective than non-canonical sites, canonical and non-canonical sites with similar mirSVR scores exert a similar regulatory effect on genes (Figure 4a). However, we still need to assess whether inclusion of non-canonical sites improves detection of microRNA-regulated genes or simply increases the fraction of false predictions.
To further evaluate the performance of mirSVR on non-canonical sites, we used a new data set of biochemically verified microRNA target sites from PAR-CLIP experiments . In this assay, the targeted mRNAs are covalently linked to AGO proteins and are identified by high-throughput sequencing after immunoprecipitation of the AGO protein. We focused the analysis on the approximately 7% of CLIP-identified sites that had no perfect 6-mer seed matches to any of the endogenous microRNAs, thus constituting a set of biochemically identified non-canonical sites. These sites were found both in coding regions and UTRs. To be consistent with how our model was trained, we further restricted the analysis to CLIP-identified non-canonical sites in the 3' UTRs that contained exactly one mismatch or G:U wobble in the 6-mer seed. We compared the mirSVR scores of the non-canonical candidate sites detected by CLIP (true sites) to those of non-canonical candidates in the same 3' UTRs that were not detected (false sites, see Methods). The distribution of mirSVR scores of the true non-canonical sites is shifted significantly downwards (indicating more confident predictions) relative to the false sites (P < 1.7e-36, one-sided KS test, Figure 6b). In addition, at a score cutoff of -0.1, mirSVR precision is 0.24 and the sensitivity is 0.09, significantly better than random prediction (P < 1.0e-4, Additional file 1, Figure S7), indicating that mirSVR scores are meaningful in discriminating non-canonical sites. However, the low sensitivity indicates that many of the functional non-canonical sites are not identified at this threshold. Future progress in identifying functional non-canonical sites is likely to require a more focused approach that includes training on additional experimental data.
Taken together, these results suggest that certain non-canonical sites are bona fide microRNA target sites that contribute, either in addition to canonical sites or independently, to gene silencing and that careful inclusion of such sites in the prediction model results in a more comprehensive target identification.
We have presented a comprehensive microRNA target prediction and ranking algorithm that accurately predicts target site efficiency as measured by gene expression arrays, mass spectroscopy, enrichment in AGO-IP, and CLIP-based experiments. Evaluation by a variety of measures shows that miRanda-mirSVR is competitive with other methods when tested on mRNA and protein expression changes. We reexamined the use of conservation as a selection criteria for effective target sites to establish that site conservation is best used as a feature, not a filter. mirSVR scores are calibrated to correlate with downregulation and can be interpreted as an empirical probability of target inhibition, leading to an intuitive choice of score threshold. Finally, we have shown that non-canonical sites, as determined by the miRanda weighted alignment algorithm, can be judiciously included into the prediction method without inflating the number of false predictions, leading to detection of functional non-canonical sites as assessed on data from microRNA transfections and from CLIP experiments. mirSVR's improved performance can be attributed to a number of modeling choices and careful statistical analysis: using a representation that allows variability in seed region binding, including non-canonical seed base pairing; incorporating a wide range of microRNA::site duplex and contextual features; training with an algorithm that avoids overfitting; and correctly calibrating the contributions of individual sites in order to properly score multi-site targets. Our statistical analysis raises some questions regarding the common notion that extent of seed complementarity and conservation are primary determinants of functional sites and suggests that multiple features, some of which exert subtle effects, determine the efficacy of target sites.
Future directions for microRNA target prediction
Although mirSVR scores incorporate many features important for microRNA-mediated inhibition, other potential aspects of target specificity are not included in the model. New data from high-throughput microRNA target identification experiments, such as cross-linking methods (HITS-CLIP , PAR-CLIP ) and Ago-IP pulldowns [19, 33], reveals that, contrary to common belief, a significant portion of target sites are found in coding regions of mRNAs, which are not considered by most current target prediction methods. Predicting and scoring target sites in the coding region will likely require a specific model that accounts for features that are unique to these regions, such as polyribosome occupancy and translation rates. microRNA target specificity may vary substantially between organisms, given the diversity of RNAi pathways and the different constituents of RISC complexes. Moreover, it is entirely plausible that target specificity for a given microRNA could change substantially between different cell types. Likewise, additional non-specific sequence determinants that are currently unknown could influence microRNA-mediated regulation. For example, the inhibition of cog-1 by the nematode-specific lsy-6 microRNA is mediated by two target sites that are dependent on additional non-sequence-specific context features . While it remains to be seen if such mechanisms are common, it is clear that one model may not account for all types of microRNA regulation. A number of RNA-binding proteins are known to be important post-transcriptional regulators that may have substantial effect on microRNA regulation, either through cis acting mechanisms, for example, by blocking target sites , or in trans, for example, by changing the secondary structure in the vicinity of the target site. In addition, a number of RNA-binding motifs have been linked to modulating microRNA-mediated regulation . Finally, the balance between the abundance of microRNAs and of RISC is likely a critical determinant in microRNA-mediated regulation. Our recent study has shown that offsetting the balance between microRNA levels and RISCs by exogenous transfection of small RNAs can lead to a noticeable loss on endogenous microRNA regulations, presumably by out-competing the endogenous microRNAs for the limited RISC .
Therefore, integrating both microRNA and RISC expression levels into target prediction is an important goal towards more accurate modeling of microRNA regulation in a physiological context.
Materials and methods
Training and test data sets
The mRNA expression training data was taken from the Grimson et al.  [GEO:GSE8501] data set, containing expression arrays from HeLa cells transfected by miR-122a, miR-128a, miR-132, miR-133a, miR-142, miR-148b, miR-181a, miR-7, miR-9. Although mRNA expression was measured at 12 h and 24 h post-transfection, we used only the 24 h measurements since they gave stronger enrichment for downregulated targets with canonical seed matches (data not shown). Similar to the Grimson et al. study, we restricted our analysis to probes with signal intensities above median in the control transfection experiments. This filter is motivated by the fact that genes must be endogenously expressed at a reasonable level in order to be able to observe microRNA-induced silencing; moreover, this reduces the number of genes whose expression changes are induced by the introduction of the transfection vector. For training the mirSVR model, we included only genes that contained a single target site for the transfected microRNA, allowing only canonical sites for the canonical-only model and including restricted kinds of non-canonical sites for the all-sites model, as described below. We did not exclude single-site genes whose log expression change after transfection was positive.
Test data of microRNA transfection with mRNA expression measurements
The mRNA expression test data set was taken from the Linsley et al. study  [GEO:GSE6838], which comprised expression data from let-7c, miR-103, miR-106b, miR-141, miR-15a, miR-16, miR-17-5p, miR-192, miR-20, miR-200a, and miR-215 transfection experiments (all measured after 24 h), and was processed in a similar fashion to training set.
Test data of microRNA transfection with proteomics expression measurements
Protein expression test data set consisting of let-7b, miR-155, miR-16, miR-1, and miR-30a transfection experiments was taken from the Selbach et al. study . Protein expression changes were computed as the median of the log 2 expression changes of its measured peptides between transfection and control experiments. Only proteins with unique peptide count ≥ 10 were used to ensure unique protein identification.
Test data of microRNA inhibition with mRNA expression measurements
Inhibition test sets were collected from three sources: the first is miR-106b 2'-O-methyl inhibition from [GEO:GSM155605] , the second is A172 glioma cells treated with anti-miR-21 [GEO:GSM298113]  and the third is LNA inhibition of miR-122 , where expression levels from multiple probes per genes were averaged.
AGO IP test data
To generate a test set of mRNA targets for endogenously expressed microRNAs, we used a recent study by Landthaler et al.  that identified the mRNA profiles of immunoprecipitates (IP) of the four AGO1-4 proteins in HEK293 cells. To identify the genes associated with FLAG/HA-tagged AGO proteins complexes, the transcripts isolated from the IPs were analyzed by microarrays and compared to the mRNA from the cleared lysate. The gene set that is enriched in the IP samples in comparison the lysate defines the complement of gene targets of the endogenously expressed microRNAs. The microRNA profile in HEK293 cells includes a number of microRNAs which can be grouped by their seed sequence similarity. To generate the test set, we selected the most abundant microRNAs from the six most common seed families (hsa-miR-16, hsa-miR-30e-5p, hsa-miR-19b, hsa-miR-32, hsa-miR-20a and hsa-miR-21) and searched for their target sites in genes that are enriched in the AGO1-4 IPs. Microarray data from the IP experiments was downloaded from  and normalized using the GCRMA R package; log enrichment values were computed using the limma package.
Data was provided by private communication from the authors. Non-canonical sites were defined as sequence traces determined by the CLIP method that did not contain perfect seed matches to any of the top 100 endogenous microRNAs expressed in HEK293 cells. Sequence traces that matched coding regions or 5' UTRs were discarded and those that matched 3' UTRs were used to predict non-canonical target sites; in the latter case, the endogenously expressed microRNA with closest seed to the sequence trace was assigned to the site. Within each identified 3' UTR, non-canonical sites that overlap with the CLIP-bound sequences were considered as true sites and all other non-canonical candidate sites for the same microRNAs were labeled as false predictions. This procedure generated a data set of 4,692 negative sites and 883 positive sites for 54 microRNAs.
Predicting target sites
In order to search for canonical seed matches and restricted non-canonical sites and to obtain predicted miRNA::target duplexes, we used a modified version of the miRanda algorithm , miRanda 2.0, using a score cutoff (-sc) of 120, gap opening and gap extension (-go -ge) of -9 and -4 respectively. The modified version excludes the first 5' base and last two 3' bases of the microRNA from the alignment and allows for only a single G:U or mismatch in the seed region (positions 2 to 7). The algorithm computes an optimal sequence complementarity alignment between the microRNA and mRNA using a weighted dynamic programming approach where matches in the seed regions have higher position-specific weights, resulting in alignments that strongly favor 5' base-pairing. 3' UTR sequences were downloaded from UCSC genome browser, with the longest UTR chosen from afilternative isoforms. "Canonical target" sites are defined as sites that contain minimally a 6-mer perfect match at positions 2 to 7 of the microRNA.
Target site features
Each target site is represented by a feature vector that encodes binary descriptors of the microRNA::mRNA duplex, extracted from miRanda alignment outputs, and additional contextual information such as the UTR length, AU composition, conservation and secondary structure accessibility scores. The predicted miRNA::site is represented by a seed bit vector denoting matches at positions 2 to 8 of the microRNA and presence of nucleotide 'A' across from position 1; an additional bit for a match at microRNA position 9; and a feature for binding at the 3' end of the microRNA. The seed bit vector represents different types of canonical seeds as well as non-canonical seeds in a uniform manner.
AU composition scores and 3' binding were computed as previously described . Briefly, AU scores are defined as the sum of the adenosine or uridine bases over a window of 30 bases flanking the target sites, inversely weighted by their distance from the target site. 3' binding is defined as the number of perfect base pairs between positions 12 to 17.
Accessibility scores were computed using RNAplfold  with the following parameters: w = 80, L = 40 and u = 8 on a window of 160 bases around the target site. In practice, the accessibility scores for positions -20 to +20 averaged over a window of two bases were used for the SVR model. We used phastCons scores  for target site conservation, which measures the conservation of nucleotide positions across multiple vertebrates. The features and expression values (that is, log expression changes for training data and Linsley et al. test set, proteomics expression for Selbach et al. test set, and IP enrichment for Landthaler et al. test set) were Z-score transformed.
Context score and PITA scores
Context scores values were computed using the source code downloaded from  that implements the regression model described in Grimson et al. 2007. Briefly, context score is composed of three regression values, which are specific to each seed class, that model the correlation between the AU composition, 3'-binding and distance from the nearer end of the UTR with mRNA downregulation. Target sites are first classified into one of the four seed classes: 6-mer, T1A 7-mer, m8 7-mer and 8-mer; the context score is computed as the sum of the three regression values specific to the seed class. The computed context scores are highly correlated with the scores downloaded from TargetScan release 5.0 (0.96 average Pearson correlation, see Additional file 1, Table S1). PITA scores were computed with code downloaded from  using default parameters. Target sites that did not match the position of our miRanda predicted sites (up to three bases) were discarded.
Support vector regression
so that the optimization problem only penalizes examples whose outputs fall outside an "epsilon tube" around the prediction function; here ϵ is a parameter chosen prior to training. SVR training was performed using the libsvm package with the following parameters: -s 4 -t 0 -c 1.0e-1 -n 5e-1 (that is, v SVR with a linear kernel).
Non-linear transformation of prediction scores
mirSVR scores were transformed using the sigmoid function . To learn the a, b, c parameters we performed five-fold cross-validation on the training data (single-site genes from Grimson et al. data set) and assembled the mirSVR prediction scores computed on each of the held-out sets. We then fit the parameters of the sigmoid function using MATLAB nlinfit function which performs a non-linear regression of mirSVR scores from the five-fold cross validation against their (Z-transformed) log expression changes. Finally, we retrained mirSVR on all the Grimson et al. data and transformed mirSVR prediction scores on test data using the sigmoid transfer function.
3' untranslated region
area under the curve
cross-linking and immunoprecipitation
Photo Activatable Ribonucleoside enhanced CLIP
RNA-induced silencing complex
receiver operating characteristic
support vector machine
support vector regression.
We thank Debora Marks for helpful discussions; Aly Khan for technical assistance; Rob Sheridan, Manda Wilson and Aaron Gabow for adaptation of mirSVR scores to miRanda sites at the http://www.microRNA.org target prediction resource; and Markus Hafner and Tom Tuschl for providing the PAR-CLIP data. This work was supported by NIH grants PO1GM073047 and 1U24CA143840.
- Filipowicz W, Bhattacharyya SN, Sonenberg N: Mechanisms of post-transcriptional regulation by microRNAs: are the answers in sight?. Nat Rev Genet. 2008, 9: 102-14. 10.1038/nrg2290.PubMedView ArticleGoogle Scholar
- Lai EC: MicroRNAs are complementary to 3' UTR sequence motifs that mediate negative post-transcriptional regulation. Nat Genet. 2002, 30: 363-4. 10.1038/ng865.PubMedView ArticleGoogle Scholar
- Didiano D, Hobert O: Perfect seed pairing is not a generally reliable predictor for miRNA-target interactions. Nat Struct Mol Biol. 2006, 13: 849-51. 10.1038/nsmb1138.PubMedView ArticleGoogle Scholar
- Didiano D, Hobert O: Molecular architecture of a miRNA-regulated 3' UTR. RNA. 2008, 14: 1297-317. 10.1261/rna.1082708.PubMedPubMed CentralView ArticleGoogle Scholar
- Lal A, Navarro F, Maher CA, Maliszewski LE, Yan N, O'Day E, Chowdhury D, Dykxhoorn DM, Tsai P, Hofmann O, Becker KG, Gorospe M, Hide W, Lieberman J: miR-24 Inhibits cell proliferation by targeting E2F2, MYC, and other cell-cycle genes via binding to "seedless" 3' UTR microRNA recognition elements. Mol Cell. 2009, 35: 610-25. 10.1016/j.molcel.2009.08.020.PubMedPubMed CentralView ArticleGoogle Scholar
- Chi SW, Zang JB, Mele A, Darnell RB: Argonaute HITS-CLIP decodes microRNA-mRNA interaction maps. Nature. 2009, 460: 479-486.PubMedPubMed CentralGoogle Scholar
- Hafner M, Landthaler M, Burger L, Khorshid M, Hausser J, Berninger P, Rothballer A, Ascano M, Jungkamp AC, Munschauer M, Ulrich A, Wardle GS, Dewell S, Zavolan M, Tuschl T: Transcriptome-wide identification of RNA-binding protein and microRNA target sites by PAR-CLIP. Cell. 2010, 141: 129-41. 10.1016/j.cell.2010.03.009.PubMedPubMed CentralView ArticleGoogle Scholar
- Grimson A, Farh KK, Johnston WK, Garrett-Engele P, Lim LP, Bartel DP: MicroRNA targeting specificity in mammals: determinants beyond seed pairing. Mol Cell. 2007, 27: 91-105. 10.1016/j.molcel.2007.06.017.PubMedPubMed CentralView ArticleGoogle Scholar
- Nielsen CB, Shomron N, Sandberg R, Hornstein E, Kitzman J, Burge CB: Determinants of targeting by endogenous and exogenous microRNAs and siRNAs. RNA. 2007, 13: 1894-910. 10.1261/rna.768207.PubMedPubMed CentralView ArticleGoogle Scholar
- Krek A, Grün D, Poy MN, Wolf R, Rosenberg L, Epstein EJ, MacMenamin P, da Piedade I, Gunsalus KC, Stoffel M, Rajewsky N: Combinatorial microRNA target predictions. Nat Genet. 2005, 37: 495-500. 10.1038/ng1536.PubMedView ArticleGoogle Scholar
- John B, Enright AJ, Aravin A, Tuschl T, Sander C, Marks DS: Human MicroRNA targets. PLoS Biol. 2004, 2: e363-10.1371/journal.pbio.0020363.PubMedPubMed CentralView ArticleGoogle Scholar
- Lall S, Grun D, Krek A, Chen K, Wang YL, Dewey CN, Sood P, Colombo T, Bray N, Macmenamin P, Kao HL, Gunsalus KC, Pachter L, Piano F, Rajewsky N: A genome-wide map of conserved microRNA targets in C. elegans. Curr Biol. 2006, 16: 460-71. 10.1016/j.cub.2006.01.050.PubMedView ArticleGoogle Scholar
- Kruger J, Rehmsmeier M: RNAhybrid: microRNA target prediction easy, fast and flexible. Nucleic Acids Res. 2006, 34: W451-4. 10.1093/nar/gkl243.PubMedPubMed CentralView ArticleGoogle Scholar
- Hammell M, Long D, Zhang L, Lee A, Carmack CS, Han M, Ding Y, Ambros V: mirWIP: microRNA target prediction based on microRNA-containing ribonucleoprotein-enriched transcripts. Nat Methods. 2008, 5: 813-9. 10.1038/nmeth.1247.PubMedPubMed CentralView ArticleGoogle Scholar
- Kertesz M, Iovino N, Unnerstall U, Gaul U, Segal E: The role of site accessibility in microRNA target recognition. Nat Genet. 2007, 39: 1278-84. 10.1038/ng2135.PubMedView ArticleGoogle Scholar
- Hausser J, Landthaler M, Jaskiewicz L, Gaidatzis D, Zavolan M: Relative contribution of sequence and structure features to the mRNA binding of Argonaute/EIF2C-miRNA complexes and the degradation of miRNA targets. Genome Res. 2009, 19: 2009-20. 10.1101/gr.091181.109.PubMedPubMed CentralView ArticleGoogle Scholar
- Selbach M, Schwanhausser B, Thierfelder N, Fang Z, Khanin R, Rajewsky N: Widespread changes in protein synthesis induced by microRNAs. Nature. 2008, 455: 58-63. 10.1038/nature07228.PubMedView ArticleGoogle Scholar
- Baek D, Villén J, Shin C, Camargo FD, Gygi SP, Bartel DP: The impact of microRNAs on protein output. Nature. 2008, 455: 64-71. 10.1038/nature07242.PubMedPubMed CentralView ArticleGoogle Scholar
- Landthaler M, Gaidatzis D, Rothballer A, Chen PY, Soll SJ, Dinic L, Ojo T, Hafner M, Zavolan M, Tuschl T: Molecular characterization of human Argonaute-containing ribonucleoprotein complexes and their bound target mRNAs. RNA. 2008, 14: 2580-96. 10.1261/rna.1351608.PubMedPubMed CentralView ArticleGoogle Scholar
- Smola A, Scholkopf B: A tutorial on support vector regression. Statistics and Computing. 2004, 14: 199-222. 10.1023/B:STCO.0000035301.49549.88.View ArticleGoogle Scholar
- Linsley PS, Schelter J, Burchard J, Kibukawa M, Martin MM, Bartz SR, Johnson JM, Cummins JM, Raymond CK, Dai H, Chau N, Cleary M, Jackson AL, Carleton M, Lim L: Transcripts targeted by the microRNA-16 family cooperatively regulate cell cycle progression. Mol Cell Biol. 2007, 27: 2240-52. 10.1128/MCB.02005-06.PubMedPubMed CentralView ArticleGoogle Scholar
- Elmén J, Lindow M, Silahtaroglu A, Bak M, Christensen M, Lind-Thomsen A, Hedtjärn M, Hansen JB, Hansen HF, Straarup EM, McCullagh K, Kearney P, Kauppinen S: Antagonism of microRNA-122 in mice by systemically administered LNA-antimiR leads to up-regulation of a large set of predicted target mRNAs in the liver. Nucleic Acids Res. 2008, 36: 1153-62. 10.1093/nar/gkm1113.PubMedPubMed CentralView ArticleGoogle Scholar
- Gabriely G, Wurdinger T, Kesari S, Esau CC, Burchard J, Linsley PS, Krichevsky AM: MicroRNA 21 promotes glioma invasion by targeting matrix metalloproteinase regulators. Mol Cell Biol. 2008, 28: 5369-80. 10.1128/MCB.00479-08.PubMedPubMed CentralView ArticleGoogle Scholar
- Enright AJ, John B, Gaul U, Tuschl T, Sander C, Marks DS: MicroRNA targets in Drosophila. Genome Biol. 2003, 5: R1-10.1186/gb-2003-5-1-r1.PubMedPubMed CentralView ArticleGoogle Scholar
- Maragkakis M, Alexiou P, Papadopoulos GL, Reczko M, Dalamagas T, Giannopoulos G, Goumas G, Koukis E, Kourtis K, Simossis VA, Sethupathy P, Vergoulis T, Koziris N, Sellis T, Tsanakas P, Hatzigeorgiou AG: Accurate microRNA target prediction correlates with protein repression levels. BMC Bioinformatics. 2009, 10: 295-10.1186/1471-2105-10-295.PubMedPubMed CentralView ArticleGoogle Scholar
- Friedman RC, Farh KK, Burge CB, Bartel DP: Most mammalian mRNAs are conserved targets of microRNAs. Genome Res. 2009, 19: 92-105. 10.1101/gr.082701.108.PubMedPubMed CentralView ArticleGoogle Scholar
- Bartel DP: MicroRNAs: target recognition and regulatory functions. Cell. 2009, 136: 215-33. 10.1016/j.cell.2009.01.002.PubMedPubMed CentralView ArticleGoogle Scholar
- Khan AA, Betel D, Miller ML, Sander C, Leslie CS, Marks DS: Transfection of small RNAs globally perturbs gene regulation by endogenous microRNAs. Nat Biotechnol. 2009, 27: 549-55. 10.1038/nbt0709-671a.PubMedPubMed CentralGoogle Scholar
- Landgraf P, Rusu M, Sheridan R, Sewer A, Iovino N, Aravin A, Pfeffer S, Rice A, Kamphofirst AO, Landthaler M, Lin C, Socci ND, Hermida L, Fulci V, Chiaretti S, Foà R, Schliwka J, Fuchs U, Novosel A, Müller RU, Schermer B, Bissels U, Inman J, Phan Q, Chien M, Weir DB, Choksi R, De Vita G, Frezzetti D, Trompeter HI, et al: A Mammalian microRNA Expression Atlas Based on Small RNA Library Sequencing. Cell. 2007, 129: 1401-1414. 10.1016/j.cell.2007.04.040.PubMedPubMed CentralView ArticleGoogle Scholar
- Vella MC, Choi EY, Lin SY, Reinert K, Slack FJ: The C. elegans microRNA let-7 binds to imperfect let-7 complementary sites from the lin-41 3' UTR. Genes Dev. 2004, 18: 132-7. 10.1101/gad.1165404.PubMedPubMed CentralView ArticleGoogle Scholar
- Wu L, Belasco JG: Micro-RNA regulation of the mammalian lin-28 gene during neuronal differentiation of embryonal carcinoma cells. Mol Cell Biol. 2005, 25: 9198-208. 10.1128/MCB.25.21.9198-9208.2005.PubMedPubMed CentralView ArticleGoogle Scholar
- Yekta S, Shih IH, Bartel DP: MicroRNA-directed cleavage of HOXB8 mRNA. Science. 2004, 304: 594-6. 10.1126/science.1097434.PubMedView ArticleGoogle Scholar
- Hendrickson DG, Hogan DJ, Herschlag D, Ferrell JE, Brown PO: Systematic identification of mRNAs recruited to argonaute 2 by specific microRNAs and corresponding changes in transcript abundance. PLoS One. 2008, 3: e2126-10.1371/journal.pone.0002126.PubMedPubMed CentralView ArticleGoogle Scholar
- Kedde M, Strasser MJ, Boldajipour B, Oude Vrielink JAF, Slanchev K, le Sage C, Nagel R, Voorhoeve PM, van Duijse J, Ørom UA, Lund AH, Perrakis A, Raz E, Agami R: RNA-binding protein Dnd1 inhibits microRNA access to target mRNA. Cell. 2007, 131: 1273-86. 10.1016/j.cell.2007.11.034.PubMedView ArticleGoogle Scholar
- Jacobsen A, Wen J, Marks DS, Krogh A: Signatures of RNA binding proteins globally coupled to effective microRNA target sites. Genome Res. 2010, 20: 1010-9. 10.1101/gr.103259.109.PubMedPubMed CentralView ArticleGoogle Scholar
- RNA regulatory networks, Zavolan Lab. [http://www.mirz.unibas.ch/]
- Tafer H, Ameres SL, Obernosterer G, Gebeshuber CA, Schroeder R, Martinez J, Hofacker IL: The impact of target site accessibility on the design of effective siRNAs. Nat Biotechnol. 2008, 26: 578-83. 10.1038/nbt1404.PubMedView ArticleGoogle Scholar
- Siepel A, Bejerano G, Pedersen JS, Hinrichs AS, Hou M, Rosenbloom K, Clawson H, Spieth J, Hillier LW, Richards S, Weinstock GM, Wilson RK, Gibbs RA, Kent WJ, Miller W, Haussler D: Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes. Genome Res. 2005, 15: 1034-50. 10.1101/gr.3715005.PubMedPubMed CentralView ArticleGoogle Scholar
- TargetScan. [http://www.targetscan.org]
- PITA source code. [http://genie.weizmann.ac.il/pubs/mir07/mir07_exe.html]
- Elmén J, Lindow M, Schütz S, Lawrence M, Petri A, Obad S, Lindholm M, Hedtjärn M, Hansen HF, Berger U, Gullans S, Kearney P, Sarnow P, Straarup EM, Kauppinen S: LNA-mediated microRNA silencing in non-human primates. Nature. 2008, 452: 896-9. 10.1038/nature06783.PubMedView ArticleGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

domain: biology


Programs that track the purchase of cold medicine that may be used to make meth is not stopping the meth trade. In fact, it’s creating more criminals.
That’s what the Associated Press found in a recent investigation. The programs are designed to keep individuals from purchasing enough over the counter drugs to make meth. For years, manufacturers sidestepped these laws by recruiting smurfs (sometimes called smurfers). The AP reveals that not only does smurfing increase several years after a tracking system is put in place in a state, but the smurfs have created a sizeable illegal market for legal drugs.
The stricter alternative is to make certain cold medicines prescription-only. But scheduling drugs creates a new set of problems:
Oregon began requiring a prescription for pseudoephedrine products in 2006. Mississippi became the second state to do so in July, and Missouri’s governor is asking lawmakers to follow suit in 2011.
If more states do the same, it could be devastating for makers of cold and sinus pills. The pseudoephedrine market is estimated at more than $550 million annually.
Opponents of prescription laws say they punish mostly law-abiding consumers for the crimes of a relative few.
But many law enforcement officials say it’s hard to argue with Oregon’s success. The state had 191 meth incidents in 2005, the year before the prescription-only law. By 2009, it had 12.


text:
Today, in the process of getting ready for guests arriving tomorrow, and in preparing for the upcoming retreat, I have moved mountains!!! There are those days when there is just no time for day dreaming, and it's all about performance.
Bruce's wing span is not long enough to stretch out this quilt top while holding it. However, it is ready to go to the quilters to be completed. On one of the corners I've appliqued the date and on the other bottom corner, I've appliqued my initials. I have chosen the name offered by Marty Toale, Square Dance Among Flowers.
Marty, please send me your address, so that when the pattern is completed, I will be able to send you a free pattern. Thank you everyone for the ideas you offered.
This pattern is called Love Birds, and will be the pattern
given away tomorrow to the early bird. Email me at - firstname.lastname@example.org Please do not forget your address.
"We quilt for so many reasons. To escape the stresses of life, to create something beautiful to cherish, or to make a gift for future generations. Yet for me the greatest joy comes from those quiet moments every quilter knows. This is the time that is my own, when I can relax, reflect, and gently sew my memories into cloth." - Jinny Beyer
I will hopefully have great things to share with you after I return. I leave on Monday morning. Enjoy the week end.


text:
THE HOME Office has denied dozens of Afrobeats stars visas to perform in Britain.
Artists and producers warn the hostile environment against the world’s fastest-growing music genre risks top names boycotting the UK.
An investigation by The Voice found that Suella Braverman’s department stopped at least 20 artists from entering the UK to perform at Afrobeat festivals.
Music insiders say West African artists are treated with more suspicion despite being part of a multi-million dollar industry, and when visas are granted to stars, their dancers have been turned down.
Afrobeat stars fume that Britain is the hardest embassy in the world to deal with, and they are routinely given short stays of just two weeks which prevents them from making the most of their visit.
Music-lovers say this is the biggest attack on a Black music genre by British authorities since dancehall in the 1990s.
Ghanaian singer Ishmael Nii Arday Ankrah, known as Nii Funny, who had a visa application refused in 2021, told The Voice: “It is not fair for them to treat us that way because the UK is our former enslavers so if we are going there to play a show, I think they have to support us.”
Mr Ankrah’s management team insists they “submitted all the right documents” but Home Office officials turned the application down after questioning why his UK-based sponsor had so much money when they were so young.
The singer was aware of numerous African artists having their visa applications denied but are not willing to publicly speak about it as there is a stigma attached to visa refusals from Britain – which many believe will tarnish their brand and reputation.
Being refused entry to the UK can also have a negative impact on other overseas trips.
He said he was only given two weeks on his last visa which put limitations on his plans.
He said: “When I got to the UK, I performed at the Kente Festival and the way the crowd were responding to my songs, I loved it and I feel like I could stay more than the two weeks.
“People have been calling me for shows here and there but my time was limited.”
Mr Ankrah wants artists granted a minimum of three months stay, so they are able to build on the momentum and excitement surrounding African music.
Christian Borquaye, who manages three prominent African artists and is based in Birmingham, said he personally knows at least 20 artists who have been refused visas and had “their money taken by the Home Office.”
“The criteria that they are giving the artists to come here is quite demanding. An artist who is trying to climb the ladder has to pay visa fees and there is no guarantee is going to get that visa.”
Mr Borquaye, whose showbiz name is Hunta, said he now plans to shoot the majority of his music videos in Ghana instead of the UK.
Emmanuel Boakye Bidewtey, is the CEO of Livenewsgh Creative Hub, and is also an artist and event manager based in Ghana.
He told The Voice Ghanaian artists want to travel to Britain for festivals and concerts but says the British embassy has been dubbed “the most difficult embassy to work with.”
He says he knows of five African artists who have recently had their UK visa applications denied and, since the start of 2023, one artist has been prohibited from travelling to Britain.
“We had a collaboration with an artist in the UK and there was a show that we really wanted to be on, but the process was like hell.”
Mr Bidewtey, known as Zolla Nie, said three of the recording artists he works with were nominated for awards at the UK Ghana Music Awards last year and wanted to perform and thank their UK fans for nominating them, but their visas were not issued, which left them “devastated”.
He says it is no secret that “Afrobeats artists go through a lot of stress to acquire a visa to the UK” and believes applications from African artists are treated with more suspicion with their documents double-checked.
Mr Bidewtey said that “Afrobeats is the music that sells Africa”, which pop stars now freely tap into, but West African artists are losing out financially by not being able to travel to the UK.
Renowned African artists like Burna Boy, Davido, Fuse ODG, Wizkid, Yemi Alade, Stonebwoy, Rema, Asake and Shatta Wale all have a huge international fanbases, appeal and acclaim, which is helping to propel African music genres to the top.
In the UK, the rise of African music has directly resulted in the launch of the landmark official Afrobeats music chart.
Each week, the UK’s 20 most popular Afrobeats songs – based on sales and streams across a seven-day period – are compiled by the Official Charts Company (OCC).
The chart was launched for the first time in 2020, with the first chart being revealed on BBC Radio 1Xtra on 26 July 2020.
With a buzzing African music scene now on British shores – which has been undoubtedly driven by Britain’s African and Caribbean community – the UK is now being seen as a key market for artists to tap into.
West African singers say their applications for visas to come to the UK are being unreasonably scrutinised and they are required to submit endless amounts of proof that they are really recording artists – which they say is unfair and discriminatory.
Many are calling for a reform of the current regulations to ensure African singers have the same rights as American and European Union artists to travel and enter Britain to perform at concerts.
Three-time Grammy-nominated musician Rocky Dawuni called for the easing of regulations once artists can prove they are “credible” and “established in their own country.”
He said: “They are coming to the UK to play, I think there should be a fast-track of helping these artists to be able to come and do what they do.”
Speaking to The Voice from Costa Rica ahead of a performance, he said: “Obviously living in Ghana, I’ve had musicians who have tried to travel and some members would get visas and others would be denied.
“It’s a really complicated process and system because every embassy has their rules, regulations and requirements about how artists can get visas and also work permits to be able to perform.”
Mr Dawuni is currently working on a new album and his new single Never Bow Down, which features Jamaican artist Blvk H3ro.
He told The Voice, he is unsure if there is a “bigger plan to suppress” African music and “keep it at bay” but whatever is driving the difficulties in artists getting to perform abroad is a “misplaced policy.”
“It is diminishing the music at a time when African music is on the rise, African music is breaking new boundaries and African music is connecting with new audiences.”
Afrobeats and Afro-dancehall artist Article Wan said that while he has never been denied a UK visa many of his musical peers have experienced problems.
He said: “The artist maybe travelling with five dancers going for a show and most of the time three dancers are going to be given a visa and two are going to be denied.”
The Accra-based musician says this makes things difficult and “destroys their craft” and creativity.
Article Wan, real name Bright Homenya, told The Voice he knows of several artists who have had their applications denied, but said many don’t want to make it public for “their brands sake.”
He said: “The embassy will give you their reasons, which you can’t do anything about. You need to reapply again or wait for some time, and if you have to perform within a particular time you cannot even go, it will stop you.
“Music is broad, people want to travel, go and shoot music videos, and go and link up with other artists and promoters and spread their wings.”
He added that so much money is being wasted on applications which have no chance of being approved.
Article Wan said he has an assistant to help him with his applications but is aware other Afrobeats artists do not have the same support.
A Home Office spokesperson said: “Musicians and performers are a valued and important part of UK culture with the country attracting world class entertainers and musicians from around the globe.
“This is why we offer a dedicated immigration route for creative workers.
“All visa applications are carefully considered on their individual merits in accordance with the immigration rules.
“The application process is designed to ensure that all visa decisions can be made using the most accurate information and is fair for all applicants.”

domain: news


text:
Ferns Gathering Saturday 8th of June 2013This is a day packed with something for everyone - from strolling musicians, gaelic games events, children's workshops, medieval costumes and more........ You can walk in the footsteps of Knights, Kings and Saints, you never know who you'll bump into as you walk in the Ancient Capital of Leinster. We plan to make this a special day. See bottom page for list of fringe activities.
1798 Bus Tour
9a.m. - 2.15p.m.This bus tour will bring you to nearby locations associated with the 1798 rebellion. Visit the former home of Lieutenant Bookey (leader of the Yeoman Cavalry); the Fr. Murphy Centre (one of the leaders of the 1798 Rebellion) and a site of a Rebel Camp. Lead by historians Brian Cleary and Denis Kinsella, this is a tour worth taking. 1798 Bus Tour Details The cost of the tour is €15 which includes entry to locations and lunch. Meet at the church car park at 9am. If you would like to register your interest in taking this tour, email email@example.com
Genealogy Workshops & Lectures
10 - 12noon and 2 - 4p.m.Sponsored and conducted by the award winning genealogy company Eneclann, these workshops will enable participants to access Eneclann’s vast databases. Two workshops are planned, one in the morning from 10a.m. - 12 noon and the second in the afternoon from 2p.m. - 4p.m. A 20 minutes talk on 'Getting started on Irish family history' will start at 11a.m and another on 'Online Research' will start at 3p.m.
Interested in taking part? If you would like to take part in these workshops, bring a little information about the family you want to research i.e. names, date of birth, marriage, any information you think might help in your search. Thanks to Scoil Naomh Maodhóg who have given the location and computers for the day and if you are not familiar with IT, members of the local community will be on hand to give you individual assistance. There is no charge for these workshops as they are sponsored by Eneclann. To register your interest, email firstname.lastname@example.org
Guided walking tours of Ferns Heritage TrailFerns is fortunate to have a number of national monuments, reflecting its rich medieval/christian heritage. If you would like a free guided tour of the various sites, we have a number of local volunteers who would love to show you around. Guided tours are available at: Saturday 10a.m. and 12 and 2p.m. and 4p.m. in the afterrnoon. On Sunday tours at 10a.m. and 2p.m. can be arranged. Just get on touch on email@example.com
Lecture by Dr. Stephen Harrison.
4.30 - 6p.m.Dr. Stephen Harrison of Trinity College researched and wrote all the battles of the Anglo-Norman invasion for the Irish Battlefields Project.The modern county of Wexford was the scene of some of the earliest and fiercest fighting of the Anglo-Norman Invasion. From Baginbun to Wexford town, these events are unusually well-documented and vividly described, and the ensuing settlement was to have an even more profound impact on the county. Join Stephen Harrison as he examines invasions, incursions, sieges and settlements across south-east Ireland. Entry to this event is free, and on a first come first served basis.
INHP WorkshopsLocated in the Castle grounds, these workshops will be conducted by Irish National Heritage Park guides. There is no booking necessary for these workshops, timings are as follows:
- 3pm - 4 pm Shield Making
- 4pm - 4.30pm Brass Rubbing
- 4.30pm - 5.30pm Daily Life
- 5.30pm - 6.30pm Shield Making
- 6.30pm - 7.30pm Daily Life
- 7.30pm - 8pm Brass Rubbing
Brass Rubbing:This workshop will be of particular interest to children. It allows individuals to select a brass template inscribed with a historical or nature themed image and using a wax stem, translate the image onto paper.
Norman Shield Making:Another workshop suitable for children. In keeping with Norman tradition in the 12th century, make and decorate your own Norman shield using history inspired design.
Daily Life:An interactive exploration of medieval life in Ireland. It focuses on clothing, weapons and culture before the arrival of the Vikings during the Viking period and into the Norman era. It includes a detailed presentation and a display of weapons, armour and clothing from each period.
Display of building materialsused in buildings such as Ferns Castle. This demonstration will be given by Paddy Byrne, Period Conservationist.
3p.m. - 8.30p.m.The grounds of Ferns Castle will be transformed into amedieval village. Montague Heritage Services will set up their medieval style tents in the afternoon with a extensive range of displays. The public can see at close range many activities of medieval times, children can have take part in combat school and try their hand at archery.
Monier & SilversmithMonier stamps coins from the Viking & Norman period – examples of finds and discussion around the changes in coinage right through to 16th century. The Silversmith has a full working forge and mobile workshop and can cast on site.
Textiles & Daily Life:You will see women and children turning fleece into fibre and making clothes.In this area there is also a nursery, a space where children from a wealthy family would learn manners, basic reading and writing and some of the games they might have played.
Food & Medicine:Food is prepared and displayed on site in the appropriate ware with dedicated personnel discussing the various cooking techniques as well as the methods of preservation and recipes. Medicine, folklore, healing herbs, bloodletting, the Barber and the Physic are all discussed.
Armoury & Maille Making:In the Armoury there are various types of helmets, shields, swords and other weapons which can be handled and photographed. The Armourer explains the types of weapons used at various times during our history. The Maille Maker sits making ‘chain-maille’ and intricate and equally awkward skill, knitting iron links together with specialised tools where members of the public get the opportunity to handle and in some cases try out the technique.
Horn/Bone Worker & Wood Worker:These individuals display their skill at crafting everyday items from horn, bone, antler and wood, giving a little insight into the skills required for everyday living in times past.
Combatants & Children’s Combat School:Costumed Heritage Specialists put the children through their paces. This is an opportunity for children to hone their skill at arms. Using ‘wasters’ (wooden practise swords) the young squires are put through their paces and taught how to parry and block. Suitable for ages 5 – 12. Groups of 20 at a time with lessons lasting approximately 20 minutes each time.
‘Have a Go Archery’:This is a great opportunity for children to practice archery in a safe and fun setting.
7p.m. til lateThe grand finale to a great day will consist of a banquet in the grounds of Ferns Castle. Don't forget Diarmuid MacMurrough has renewed his invitation to Strongbow to come to Ferns for the Gathering and Strongbow accepted........ Of course Strongbow isn't the only celebrity coming to the Banquet, Anne Doyle will also be there. Who knows what news will break over the weekend. This gives great cause for celebration, come along and join the fun.
This is a ticketed event. Tickets are €20 for an evening of great food, music and craic - if you are interested in attending, please contact us on firstname.lastname@example.org
Ferns Fringe EventsWe have lots more activities planned around this special weekend - see Ferns Gathering Fringe Events 2013 to check them out! Events include: Stitch with Ferns Tapestry Group in Ferns Castle; GAA - Cumán Abu; Speed Test & Street Leagues; strolling musicians; medieval characters on the streets, music in local pubs and more........
We will be updating these events as we add to the programme.
Times of events are subject to slight change - please check website for updates.
For more information on the Ferns Gathering Sunday the 8th of June Events 2013 contact us directly

domain: history