Social isolation in geriatric institutions is a real threat to older adults' (OAs) well-being. Visits from family members, when they are not impacted by geographical distance or illness, sometimes fail to provide sufficient opportunities for social connectedness and interaction to prevent and/or combat OAs' loneliness and social isolation. Information and Communication Technologies (ICTs) offer promising solutions to this problem. Video calls provide a quick and convenient way for remote communication between OAs and their families, and a complement to face-to-face visits in geriatric settings. Over the last months, during the several confinements imposed to stop the transmission of COVID-19 over the world, several care homes and long-care facilities have equipped themselves with laptops, tablets and video call applications to help OAs remain in contact with their relatives. However, numerous technical and human-related factors may hinder the use of video calls in these settings. The complexity of technological devices, as well as OAs limited digital skills, low confidence and experience in the use of technology are some examples. Furthermore, the specific context of use and the required implication of multiple actors  should also be considered when examining the use and implementation of video calls in geriatric institutions. We conducted a narrative review of literature describing the use of video calls in geriatric institutions between 2000 and 2021, especially because of the little information related to OAs' use of video calls in geriatric settings. One thousand one hundred ninety-seven references were screened and 15 studies focusing on the usability, acceptability and effectiveness of video calls were included. A qualitative, deductive thematic analysis inspired by a Health Technology Assessment (HTA) multidimensional model was used to identify barriers, enablers and solutions to video calls implementation in geriatric institutions. The results from the HTA-based analysis provide encouraging evidence for the feasibility of video call use in geriatric settings, and its efficacy on reducing social isolation among residents. However, numerous technical, human-related, ethical and organizational barriers persist and should be addressed in future works. The present analysis has also allowed the identification of potential solutions to overcome these barriers, which are discussed in this publication. Social isolation and loneliness represent a serious issue among older adults living in geriatric institutions. Current literature shows that the prevalence of loneliness among nursing home residents is estimated between 50 and 55% –3. IndeeVideo calls are a remote communication service offered by several software programs such as Skype , Zoom 1 or WhatsLee and Coughlin  identifiUnderstanding the barriers and enablers to using video calls in a specific context, such as geriatric care institutions, requires conducting a multidimensional analysis considering, for instance, human, organizational, technological and ethical aspects. However, a few articles in this field have tackled those aspects using a comprehensive approach , 31. A rIn this sense, the multidimensional analysis models used in the field of Health Technology Assessment (HTA) could provide an analysis grid that questions the clinical, human, technological, medico-economic, ethical and legal aspects of an intervention. This analytical framework makes it possible to assess the global value of a health technology  . It coulThe objective of this review was first to identify barriers, enablers, as well as solutions for the implementation of video calls in elderly care institutions, using a multidimensional HTA approach for the analysis of experimental results presented in publications in the literature, and second to explore the benefits of this service on the maintenance of OAs' social interactions.What are the barriers, enablers and benefits for the use of video calls by OAs in elderly care institutions and what solutions could be considered to overcome those barriers and take advantage of those enablers?.” The keywords for conducting the search were grouped into three categories: elderly, nursing homes and video calls. A systematic search was first conducted consulting the following databases: PsycINFO, PubMed/Medline, Web of Science and Scopus. The search was carried out between March and June 2021. We reviewed studies published between January 2000 and June 2021. As with Schuster and Hunter  method , we deved Hunter , we alloThe criteria for the inclusion of studies in the review were as follows: (a) experimental studies involving OAs using video call technologies and functionalities, (b) studies describing a video call intervention or activity conducted in a geriatric care institution , (c) publications describing an experimental study regardless of the study design , (d) studies written in English or French. Publications were excluded if: (a) participants gave their opinions only based on photos or videos of video call technologies, without actually using them, (b) studies described experimentations using mobile telepresence robots as a support for video calls.To guide the literature selection process, the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA)  was usedWe examined barriers, enablers, as well as solutions to the implementation and use of video calls in geriatric care institutions, as reported in the publications, using the European Health Technology Assessment model  created by the European Network of HTA . Althouglevel 1), “Topic” (level 2), and “Issue” (level 3). The combination of a domain, topic and issue is linked to an assessment element ID, which can be identified using a specific code for standardization purposes . An example of this combination is presented in The EUnetHTA core model® version 3.0, is composed of nine domains, each one including several topics, each topic includes as well different issues . The model is thus structured into three levels: “Domain”  the intervention objectives, (b) the participants' characteristics, (c) the conditions of the experimentations , (d) the methodology of the study , (e) the barriers and enablers to the implementation of the technology (if described), (f) the benefits of the intervention on social interactions (if described), (g) the solutions to overcome barriers to the implementation of the technology (if described).level 1). We proceeded then to a first coding cycle . A subsequent exploration of the data coded (sentences or set of statements) was made to get a more analytical identification and defined at the topic level (level 2) or at the issue level (level 3); corresponding coding was then made using the HTA nomenclature. A semantic approach was used to identify themes and codes using the explicit or surface meaning of the data and not the underlying assumptions or ideas  was identified and assigned, then the topic “Patient satisfaction” (level 2) and the issue “Were patients satisfied with the technology?” (level 3) were also identified and coded. Finally, the assessment element ID for the corresponding combination Domain, Topic and Issue was added (D0017). Those examples are presented in Following the same methodology, in the following excerpt from another one of the studies selected: “ending” n = 5) followed by a “videophone” (n = 4), with the remainder using either a “laptop” (n = 2), a “smartphone” (n = 1), a “tabletop” (n =1), or a “TV” (n = 2). Three different software programs, such as “Skype” (n = 8), “Line” (n = 2) and “MSN ” (n = 2) were used on tablet, laptop, smartphone or TV. The length of experimentation reported in the studies ranged from 1 day to 18 months. A general description of the included articles is presented in A total of 15 studies were included in this analysis. The studies were published between November 2002 and December 2020. They were conducted in different world regions: North-America (United-States of America) , 39, 40,, “Line”  (n = 2) senger)”  (n = 2) n = 5), “randomized trial” (n = 3) or “ethnographic and a part of a Collaborative Action Research (CAR)” (n = 2), the remaining ones were a “case study” (n = 1), a “randomized longitudinal trial” (n = 1), an “exploratory mixed-methods study” (n = 1), a “cross-sectional study” (n = 1), or a “quasi experimental study” (n = 1). Regarding the main objective of the assessment described in the studies, more than half addressed the feasibility and acceptance of video calls technologies, notably through the study of their usability and usefulness, the other half studied the clinical impact of video calls on loneliness or depression. Finally, the majority of the studies involved both healthy OAs and OAs with cognitive impairments (n = 12). However, the severity of the impairments remained unclear. Only a few publications reported explicitly involving OAs with severe cognitive decline (dementia) (n = 3). A summary of the methodological features of the studies is presented in Concerning the methodological aspects, the majority of the study designs were “exploratory qualitative studies” . Then, data that refers to the next two EUnetHTA analysis levels “Topics” and “Issues” are described. The EUnetHTA core model® version 3.0 assessment element ID is provided for each issue described.A summary of the distribution of HTA domains by articles is shown in n = 15), the target population for the interventions using video calls was “OAs living in elderly care facilities.” These institutions were: nursing homes (Issue: “What Is the Target Population in This Assessment?” ID (A0007).In all the studies included .The aim of video calls interventions was to target socialization need of OAs living in institutional settings. OAs living in elderly care institutions frequently experienced loneliness, infrequent social contact with their relatives or friends, a lack of meaningful relationships, and/or difficulties in forming new relationships , 45, 46.Issue: “What are the Other Typical or Common Alternatives to the Current Technology?” ID (A0018). Before the implementation of video calls in elderly care institutions, OAs already had their own habits, like regular in-visits or telephone calls. Several studies refer to existing modes of socialization with relatives that may compete with video calls. Most of the studies mentioned face-to-face visits , 25, 26,Issue 1: “For Which Health Conditions and Populations, and For What Purposes Is the Technology Used?” ID (A0001). Video call interventions were offered to OAs living in geriatric care facilities to reconnect with families, facilitate interactions, or maintain social connectedness –42, 45. Issue 2: “Is the Technology a New, Innovative Mode of Care, an Add-on to or Modification of a Standard Mode of Care or Replacement of a Standard Mode of Care?” ID (F0001). In two studies, video calls were considered to be an additional means of long-distance communication , 47, andIssue 1: “What is This Technology and the Comparator(s)?” ID (B0001). Studies experimented and assessed video calling technology. Video calls allow face-to-face contact during a call (associating audio and video) and can be used on different technological supports. Among the 15 studies reviewed, six different video calling technologies were used, as well as three different freeware programs. Two of them are instant messaging and video calling applications , while the other one provides only video calls services . Detailed descriptions of these technologies, how they were used, and in which settings are presented in Issue 2: “Who Administers the Technology and the Comparators and in What Context and Level of Care are They Provided?” ID (B0004). For the use of video calling technology, OAs were either independent , 42, 44,Issue 3: “What Is the Claimed Benefit of the Technology in Relation to the Comparators?” ID (B0002). After introducing video calling technology and services in the geriatric facilities, residents, families and care staffs reported different benefits. Among them, the most cited was the fact of being able to have richer and more emotional conversations, compared to traditional calls, by the addition of the video dimension , 44–46. Issue: “What Material Investments are Needed to Use the Technology?” ID (B0007). Video calling intervention implies some material investments . What Kind of Training Resources and Information Should be Provided to the Patient Who Uses the Technology, or For his Family?” ID (B0014). In order to correctly use video call technology and services, training or information sessions may be necessary for users. Among the selected studies, six did not specify this information . Regarding the safety of OAs who took part in the video call intervention, some staff members expressed concerns about physical risks linked to the use of video call technologies  . In addishe grew concerned that her family did not want to speak to her” ?” ID (C0062). To reduce the risk of confusion and anxiety about the video call technology, some care staff suggested “disguising” the video call equipment. The goal was to make it more user-friendly . As far Issue: “How Does the Technology Affect Symptoms and Findings  of the Disease or Health Condition?” ID (D0005). The use of video calls in an elderly care facility can have an effect on health outcomes of the target population. Two studies found a decrease in depressive symptoms experienced by most residents , 19, 34.Issue: “What Is the Effect of the Technology on Generic Health-related Quality of Life?” ID (D0012). The use of video calls can also affect the health-related quality of life. The main reported benefits of its use were the improvement of the users' well-being , 41, 46,still [being] part of the family” . Studies that reported users' feedback (OAs and family members) described a good level of satisfaction of using video calls to communicate with their loved ones . The implementation of video calls in geriatric institutions may require the involvement of facility staff members, which impacts their work and the care process. In eight studies, staff members assisted , 42, 44,he care” . Dependihe care” , once a he care” , 42, or he care” , 46.Issue 2: “What Kind of Process Ensures Proper Education and Training of Staff?” (G0003). To ensure proper assistance to OAs with the use of video conferencing technology, researchers trained staff members , 25, helpart of the time I [family member] get an update from her [staff member] on what is going on with regard to my husband” (Issue: “What Are the Processes Ensuring Access to the New Technology For Patients/Participants?” ID (G0101). In cases where facility staffs were directly involved in the use of video calls, different processes were implemented. Some facilities practiced up-front appointment setting between the family and the resident , 42, 44.husband” . Staff mSometimes, the use of video calls was considered as another social activity and therefore was presented on regular communication supports of the institution (newsletter to the families) . In the Issue: “What Management Problems and Opportunities are Attached to the Technology?” ID (G0008). The integration of a new technology into an elderly care institution often raised management issues. When facility staff was asked to implement video calls, understaffing and an already heavy workload were recurring organizational issues , 26, 46.Issue: “How Is the Technology Accepted?” ID (G0010). The success of the integration of a new technology, activity, or intervention depends partly on its acceptance by facility staffs. In two studies reviewed, professionals showed no interest in ICT technologies and did not understand their usefulness in an OAs facility , 45. Thilink up [with other residences] and become more connected with each other to provide a more 'close knit' unit” . The introduction of video calling technologies in an elderly care institution needs, at the very least, an investment in the basic video calling equipment . This kind of intervention may create other needs in terms of technology  but also resources (provision of user guides).I would definitely need someone to help” . When implementing a new mode of remote communication involving the use of a technology, it is important to study the balance between the benefits and harms that it generates. First, there is the risk of reducing, or even completely replacing, traditional visits by relatives in the institution . Some faHowever, no studies reported a decrease in the frequency of traditional visits after the introduction of video calls. On the contrary, several times, video calls were shown to increase social interactions between residents and their relatives, especially when the latter was unable to travel due to health reasons or geographical distance , 40, 44.Issue: “What are the Known and Estimated Benefits and Harms For Patients When Implementing or Not Implementing the Technology?” ID (F0010). The use of video calls raised the issue of privacy. Indeed, the facility staff members were often requested to ensure proper video calls functioning. This constant supervision raised the question of the privacy of exchanges between family members and OAs . In addiIssue 1: “Is the Technology Used for Individuals That are Especially Vulnerable?” ID (F0005). Some studies included OAs living with dementia or other advanced cognitive disorders , 44–46. Issue: “Are There Factors That Could Prevent a Group or Person From Gaining Access to the Technology?” ID (H0012). Some factors may prevent some OAs living in geriatric institutions from taking advantage of or even using video calls. In a few studies, staff members decided which OAs were eligible  for video calls intervention, without giving OAs the opportunity to try or to give their opinions on the video calling technology , 25, 47.for me at 90, it is going to be difficult” . Many factors limited access to technology for all facility residents, or only for a group of vulnerable OAs. Their self-perception, their abilities, but also the complexity of the tool are limiting factors to video calls use. Some OAs expressed insecurity about the image they projected of themselves through the use of video calls , 46, or fficult” , “Too olcation]” , “she woo calls” . Anothero calls” , a feelio calls” , a poor o calls” , and a lo calls”  were baro calls” . Some OAo calls” , 27, 45.Some OAs did not dare ask their relatives to participate, thinking that they would be too busy to do so anyway , 24. TheIssue 1: “What Expectations and Wishes Do Patients Have With Regard to the Technology and What Do They Expect to Gain From the Technology?” ID (H0100). No study mentioned the expectations and wishes of OAs toward video conferencing technologies. They only evaluated their opinions during or after the interventions.it would feel like you were talking to the caller in-person and be more in contact” (Issue 2: “How Do Patients Perceive the Technology Under Assessment?” ID (H0006). Several OAs considered video calls as a way of reconnecting with their family and renewing social ties , 26, 47.contact” . Howevercontact” . Howevercontact” , compliccontact” , and eveAspects related to rules and regulations were not described in the publications reviewed.The purpose of this research was to compile and review existing literature on video calls involving OAs in elderly care institutions from January 2000 to June 2021. Our search identified 15 studies, with a wide variety of intervention designs, study settings, and sample characteristics. The objective of this review was first to identify barriers, enablers, as well as solutions to the implementation of video calls in elderly care institutions using a multidimensional perspective, and second to explore the benefits of this service on the maintenance of OAs' social interactions. The EUnetHTA multidimensional framework  was usedAmong the enablers of video calls interventions, it is important to underline that most of the authors showed the feasibility of the implementation of video calls in elderly care institutions. Evidence of this is that, at the end of each study, despite the barriers encountered , several OAs continued to benefit from video calls with their relatives. This can be explained by the fact that the participants found the benefits more important than the obstacles.It is interesting to note that videophones did not elicit strong rejection from residents, as their ergonomics were similar to those of traditional landline telephones, which are widely used among this population. Furthermore, using video calls instead of telephone calls was more a change in the means of communication than a change in the habits of communication for the OAs. Video calls interventions were also considered feasible because devices employed were available for a general public and were also low cost.As emphasized by all the studies in this review, video calls are useful since they enable OAs to have more meaningful remote communication  with their relatives, especially those who live far away. Furthermore, the several COVID-19 confinements particularly highlighted the usefulness of video calls, as reported in two studies , 46. ThuAnother strong enabler to video calls use was OAs' interest in video calls service. However, as their environment played a central role, OA's motivation was closely related to family and staff members' motivation itself. Indeed, those two stakeholders played an active role in facilitating the use of video calling technology by OAs. However, family and staff members' implication and interest on the service mostly depended on their capacity of using it, on their tolerance of technical and operating difficulties , as wellsocial facilitation interventions generally presume a degree of reciprocity, and strive to provide mutual benefits to all participants involved” , or by choosing technology more tailored to OAs' needs such as a mobile telepresence robot , or a TVApart from videophones, most of the OAs seemed to need training in the basic knowledge of video calling technologies. These training programs need to be adapted to OAs' cognitive capacities. Quillion-Dupré  created However, although training may resolve several usage problems, some OAs may still face usability issues. In this case, additional support by skilled staff members during video calls sessions should be provided to ensure proper use of the video calling technology.The implementation of video calls in geriatric institutions requires considering OAs' socialization needs, as they already have their habits with telephone calls or in-person visits. Thus, OAs could be reluctant to use an additional communication technology. Moreover, OAs' physical, cognitive and sensory disorders may increase their fatigability, which in turn could impact their perceived vulnerability, their self-esteem and their self-efficacy toward video calling technology. Combined with OAs' lack of experience and negative attitude toward technology, those factors may affect video calls use.Families' motivation was identified as an enabler in video calls use. However, when family members are more reluctant about video calls, or have a low tolerance for operating and technical difficulties, the resident/family member dyad tends to have a low potential of video calls use . Mickus A possible solution to better take into account OAs' vulnerabilities and disorders could be to embed video calls use into regular activities such as meals, or entertainments. This solution has the advantage of not adding extra fatigue to the day, as well as to ‘dress-up' the video calling technology , allowinIn addition, it could be interesting to add a purpose to those video calls sessions . The feFinally, training and regular support by staff members appeared to be crucial for OAs to understand the video calling technology, as well as to reassure them about their own capacity in using it. In order to include families more easily into video calls use, it could be interesting to provide a similar kind of training and technical support to family members in need of assistance.As stated in the literature review by Schuster and Hunter , professHowever, the shortage of personnel, the frequent turnover, and their high workload were major obstacles to the implementation of video calls in geriatric settings. Indeed, video calls implied additional tasks such as scheduling appointments, or providing technical support to OAs or even to family members. This supplementary workload, together with staff members' lack of experience and low self-efficacy could negatively impact their motivation for video calls sessions.That is why, in order to counter those barriers, it is important to study the capacity of staff members to use video calls considering their current working conditions . ProvidiFinally, actively involving staff members into video calls activities could increase their motivation to use this service. In the study by Zamir et al. , video cAs stated above, video calls use could be hindered by numerous barriers, which were sometimes difficult to overcome. First, there is the question of providing equal and non-discriminatory access to the service.a priori that the OA, because of physical and/or cognitive limitations, would be unable to use the technology, without giving him/her the opportunity to try it out, resulting in the exclusion of some people from the intervention. For instance, in one institution, residents with hearing impairments were not recruited by staff members to take part in the video call activity, and thus, missed the opportunity to try and potentially benefit from the intervention .- Define an individual plan of socializing activities for each resident who will benefit from video calls, ensuring a balance between remote and direct social contacts.- Set up a training program for the residents who will participate in the video call activity that is adapted to their needs and abilities. This may be the opportunity to conduct some usability tests and define the necessary adaptations to ensure the accessibility of the activity .- Offer to professionals and members of the resident's family or friends, interested in the activity, specific training on the use of the device. The availability of pedagogical material adapted to this objective  can help to improve the understanding of the use of the system and its adoption.- Define a mode of use of video calls that will allow for the privacy of the participants .- Define with the professionals who will manage the activity a strategy for the handling of technical problems that will allow, on the one hand a quick resolution, and on the other hand to calm and reassure the residents and their family members.- Solicit family members and members of the resident's entourage interested in using the video calling device early enough to schedule an accurate time for the call.- Respect the schedule that has been agreed upon for the video call with residents and their family members or friends to avoid frustrations or unrealistic expectations .- Before initiating a video calls session explain again how to use the device and how the session is going to run.- Monitor the use of the system during the video call session to make the necessary technical or ergonomic adaptations .- Monitor resident's behavior during the video call to identify any signs of confusion or stress and adapt the activity accordingly.- Define a way of monitoring the activity at the individual and at the institution scale to identify the necessary modifications, whether at the technical, training or psychosocial impact level. A follow-up activity sheet can be used for this purpose.- Include the video call activity in the team debriefings and evaluation sessions to allow professionals to discuss, on the one hand, about individual and organizational impacts of the intervention, and to define ways to improve the implementation of the device, on the other hand.- Keep a regular check on the updates of the technologies and applications allowing the conduct of video calls in order to always have a stable, robust and secure system at disposal.In this review, the thematic analysis was based on the EUnetHTA Core Model® . Thus, dAnother limitation encountered refers to the selection of publications for the review. First, only publications in English and French were selected. Second, it is also possible that studies that did not mention video calls or elderly care institutions in the key words or in the abstract were not included. Third, the literature review did not take into account the quality of the intervention, or the study described, since we gave priority to include as many relevant publications as possible. Thus, some factors that we know are important for the understanding of the interventions or for the appreciation of their impact were not considered in our analysis . These aspects limit the generalizability of our results.The isolation and loneliness of OAs in institutions are a problem that has been particularly discussed lately with the successive confinements and restrictions due to the COVID-19 epidemic. Video calls have been one of the solutions proposed by several geriatric institutions to maintain the social link between residents and their families. This literature review has shown that this technology can help connect OAs with their loved ones who are unable to travel. Generally speaking, when the family and the resident perceive the usefulness of video calls, such as having richer exchanges, this service reduces the feeling of loneliness in the OAs and improves the quality of social interactions within the family.However, the level of acceptance of video calls by the residents, their families and the facility staff varies according to the studies. Various organizational, human-related, ethical and technological barriers and proposed solutions were also identified. Future research must better take into account the family and the facility staff perspectives and needs in the implementation and the study of the acceptance of video calls in institutions. In the future, health economics, organizational, ethical and legal aspects should be better described and addressed. Finally, we highlight the importance of conducting small pilot tests before the implementation of video call services in geriatric institutions that can be helpful to identify technical, human-related, organizational or ethical requirements at the institutional and the individual level.The original contributions presented in the study are included in the article/BN, A-SR, and MP: conceptualization and methodology, writing—original draft preparation, and writing—review and editing. BN: formal analysis and investigation and project administration. All authors have read and agreed to the published version of the manuscript.This work was supported by Technosens (Grenoble), CIFRE funding (2021/0344), Assistance Publique-Hôpitaux de Paris (AP-HP) and Université de Paris.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Recently, the field of face and facial features has been progressively studied. The features of facial expression have gained increasing attention for related applications. The wrinkle is the most representative feature, and its research and applications have been topics of high interest. Wrinkles play an important role in face feature analysis. They have been widely used in applications, such as age estimation, skin texture classification, expression recognition, and simulation.Existing approaches to the image‐based analysis of wrinkles as texture not as curvilinear discontinuity and wrinkle detection mainly have focused on detecting wrinkles on forehead position, which is usually horizontal linear shapes, while the detection of the nasolabial wrinkle is not well understood due to their variety of shapes and complexity.In this paper, we present a nasolabial wrinkle line detecting effective algorithm based on the Active appearance model and Hessian filter to improve localization results by creating unique initial shapes of the wrinkle lines for each input face image.Experimental results show that the proposed method is capable of tracking curve wrinkle lines, thus allowing to detect complexly structured wrinkle lines. This work demonstrates results illustrated the competitiveness of the proposed method in detecting nasolabial wrinkle lines.In our study, this was introduced the effectiveness of changing the structure of AAM and successfully applied in wrinkle line localizing, although competitive results are achieved by the proposed wrinkle detection method. Current wrinkle detection methods focused on detecting active wrinkle positions as forehead wrinkles,Detecting initial position of wrinkle line by Hessian filter: To make wrinkle detection method more effective and common was detected candidate wrinkle position by applying a ridge detection algorithm.Apply initial wrinkle line to Active Appearance Model as individual mean shape: Create an active shape model and localize the wrinkle line using initial shape of wrinkle line.To make nasolabial wrinkle detection method more efficient, this work is divided into two main parts:The main contribution of this work is summarized as follows: The information about related works on the wrinkle area was introduced in section 2In this section, we introduce related work based on wrinkle line detection. We divided the section into three parts rely on methods that were used in the wrinkle research area: texture based, filters based, and shape model‐based.2.1The automated location of wrinkles from images is an important step in age estimation. Ng et al2.2Localization wrinkle is a line or ridge detection problem. Only a few methods have been proposed in the previous. Ng et al2.3Facial shape detection has received a lot of attention over the past decade and successfully applied in many research areas and have been topics of high interest using shape models to detect wrinkle line. The Active Shape Model (ASM) was used by training and locating 81 face feature points, including several points in the nasolabial region.Current wrinkle detectors rely on a bold boundary pattern of the wrinkle line.Texture and geometrical information around the wrinkle line not used completely.Above methods mainly suitable for detecting forehead wrinkle lines, wherein nasolabial wrinkle lines remain unexplored.Current algorithms leave many opportunities to improve wrinkle detection method and introduced by the following drawbacks:3The proposed detector Figure 3.1The first and most important step is to detect face and face feature points from the input image. In this step, using general AAM localized detect face and face features. The shape of the face represented as a sequence of 88 points Figure , in whicChin region is initially extracted using points coordinates in Table H of the input image I, if image function is g in this case for small values x and y consisting of second‐order derivatives at scale σ, is given as:To extract the initial position of wrinkle lines in cheek area using edge detection operator is not effective, as edge detection operators detect borders between areas of high and low gray values, it could not detect wrinkle position. An edge detector is a first derivative operator, an edge detector measures the steepness of the slope at each point of the landscape. Our aim is thin lines are darker or brighter than their neighbors, this can be reached using second‐order derivatives. To localize wrinkles pixels by second‐order derivatives, we applied a Hessian filter. The Hessian filter is a matrix of second‐order derivative and is capable of capturing local structures in images. The eigenvalues of the Hessian filter evaluated at each image point quantify the rate of change of the gradient field in various directions. A small eigenvalue indicates a low rate of change in the field in the corresponding Eigen direction. The Hessian matrix 1, λ2λ of the Hessian matrix:In order to extract the Eigen direction in which a local structure of the image is decomposed, Equation  is transUsing these values for areas, where the major eigenvalue of the Hessian is large. To localize the wrinkle line positions, we calculate the major eigenvalue at each pixel:xx, Hxy, and HyyH are the second derivative.Then:3.2The wrinkle line structure of different persons might appear different and the wrinkle line might be weak or strong, as the cheek region is a passive part of the face in some cases just using second‐order derivatives is not enough to detect the whole line position. Detecting wrinkle with filters leads to losing some weak parts of the whole line, and an active appearance model (AAM) is applied to prevent such outcome and to find all of the candidate wrinkle lines. Active Appearance Model (AAM) introduced by Cootes et al.AAM was trained using the FACES datasetThe vector of labeled points Equation  used to x¯ is the mean shape of Equation  LLT = 100.Discard some short and distorted lines less than Line Angle Threshold (LAT) less than LAT = π.Remain wrinkle line with n=x1,y1,⋯,xn,ynT represented as:E represents the Eigen vectors of shape, and msh represents new unique mean shape.AAM consists of shape and texture modelsW is a vectorization of wrinkle structure after Procrustes transformation, s is the spars coefficient corresponding to the wrinkle structure database, vecvec is the vectorization of the input shape, and λ is the regularization parameter 1e−6.To apply the AAM algorithm for sets of points with unique initial shape under Procrustes transformation and reduce the error between input image and model using the relationship between the shape and texture model was applied:l. Algorithm 2. AAM Iteration with created unique mean shape.4This research investigates the effectiveness of detecting nasolabial wrinkle lines based on AAM using a unique initial shape. The proposed algorithm successfully detected the wrinkle line in the nasolabial region, which compares with the performance of the proposed algorithm with state‐of‐the‐art algorithms. Figure 4.1The FACES dataset4.2Our research is based on skin patterns that is why we were faced with problems such as noise and illumination. To overcome the skin pattern noise, illumination, shadow problems Gaussian blurring, and automatic histogram equalization methods were applied Figure .4.3The wrinkle initial position was detected by calculating Eigenvalues. The idea of the Hessian filter centers on the utilization of second‐order partial derivatives for edge detection. Eigenvalues of the Hessian filter were applied to extract principal directions into which the local second‐order structure of the image can be analyzed Figure Despite the fact that the Hessian filter benefits from the presence of the curve and valley extraction, a significant drawback is its omnidirectional nature. The vertical and horizontal discontinuities are detected as wrinkles; however, some of them are actually non‐wrinkles. To remain only wrinkle lines, the Equation  was impl4.4In this research, for detecting the cheek wrinkle position was used for each input image unique initial shape based on edges of wrinkle line and AAM. Figure 4.5To compare the proposed method with state‐of‐the‐art algorithms, ASM‐basedThe ASM‐based methodA the number of pixels on manually labeled wrinkle line, and B the number of pixels on detected wrinkle line. To validate the accuracy of the similarity between ground truth and the detected shape is defined as:N is the total number of images 100, and J is output from Equation (In this paper, JSI was applied to calculate the error metric of detected wrinkle lines by calculating the similarity between manually labeled and detected wrinkle lines. An expansion of 20 points is applied to the assumed line when calculating the JSI. The Jaccard index:JA,B=A∩BATable 5The structure of wrinkles varies greatly in width, length, and pattern in different images, making it difficult to develop automatic wrinkle detection. Related works on the area of wrinkle line detection are mainly focused on detecting forehead and another part of the face based on filter and operators. Therefore, an efficient active appearance model has been proposed. This method is based on effective active appearance nasolabial wrinkle detection model, which apply the unique initial shape based on the wrinkle line structure.In our study, was introduced the effectiveness of changing the structure of AAM and successfully applied in wrinkle line localizing. Although competitive results are achieved by the proposed wrinkle detection method, in the future, we planned to pay attention to skin texture information that can be used to achieve to create a wrinkle mapping model. In addition to wrinkle line structure, the effects of variation of color, face alignment, and illumination shall be studied in the future works.


The COVID-19 pandemic has caused major disruptions in people’s lives around the globe. Sleep habits and emotional balance have been disturbed in a way that could be comparable to the havoc caused by a deep personal crisis or a traumatic experience. This unfortunate situation provides a unique context in which to study the impact of these imbalances on cognitive processes. In particular, the field of eyewitness science could benefit from these conditions, since they are also often present in crime victims, but can only be generated in the laboratory up to a certain ethical and practical limit. For several decades, eyewitness studies have tried to discover what variables affect people’s ability to properly recognize faces. However, the disparity of experimental designs and the limitations of laboratory work could be contributing to the lack of consensus around several factors, such as sleep, anxiety, and depression. Therefore, the possibility of observing the influence of these agents in natural contexts could shed light on this discussion. Here, we perform simple and repeated lineups with witnesses of mock-crime, considering the conditions related to the COVID-19 pandemic, which to some extent allow emulating the deterioration in general well-being that often afflicts crime victims. For this, 72 participants completed symptomatology scales, and watched a video portraying a staged violent episode. Subsequently, they gave testimony and participated in two lineups, in which we manipulated the presence/absence of the perpetrator, to recreate critical scenarios for the appearance of false recognitions. We found an increase in recognition errors in those individuals who did not have access to the perpetrator during the Initial lineup. Additionally, the conditions of the pandemic appear to have adversely affected the ability to witness and accurately perform lineups. These results reaffirm the need to move toward the standardization of research practices and methods for assessing testimonial evidence, especially in relation to the results of the lineups. Considering the degree of fallibility of these processes can lead to a reduction of wrongful convictions. Since the beginning of the COVID-19 pandemic, mental health surveys have been conducted consistently around the world. The concern arises from the fact that social isolation, confinement, and sedentary lifestyle are directly associated with a broad range of mental disorders . The resA difficulty that constantly appears throughout most of the background in eyewitness science is the limitation  to produce ecological conditions in the laboratory , that is1, 72% of wrongful convictions in the United States are strongly determined by incorrect identifications in lineups. Even acting in good faith, people may misrecognize an individual in a lineup, due to various environmental and personal factors. In order to understand this, we must understand memory as highly malleable and subject to distortion and not as a video camera that faithfully reproduces the past . Given the influence that these variables seem to have on simple identifications, and the fact that repeated lineups are still practiced in some countries, it is of interest to contemplate this case from an exploratory perspective.In this exploratory study, we will analyze the impact on performance in simple and repeated lineups, of emotional states and sleep habits during the lockdown related to the COVID-19 pandemic.Finally, the influence of the same variables in tasks of free recall and chronological order of images will be studied, seeking to determine if the relationships are repeated through different memory modalities.To this end, two groups of subjects completed psychometric scales, watched a video of an incident at a conference, and gave their oral testimony (day 1). 24 h later, they tried to identify the perpetrator in a photographic lineup, in the presence (With perpetrator group) or absence (Without perpetrator group) of the perpetrator (day 2). On day 8 both groups carried out a definitive lineup in present condition. Additionally, they gave a final testimony, and were tested for the episodic temporal order of the event.The participants were 78 Argentines recruited online through the official social networks of the Sleep and Memory Lab. Applicants underwent a prior online interview with the experimenter, to ensure that they met the inclusion criteria. They also had to demonstrate that they had the appropriate technical resources (PC and fast enough Internet etc.), and basic knowledge of how to use them. The sample size was decided according to previous studies sharing similar designs . These sM = 29 ± 6, years, For the collection of sociodemographic data and symptomatological scales, the Google Forms platform was used. This form of data collection has been shown to be equivalent to traditional forms of collection . Then, tThe entire study was conducted online, at the beginning of each session, the participants entered a video call with the experimenter, who provided instructions, showed the stimuli through streaming, and supervised the tasks.On day 1, after signing the informed consent, they completed the first part of the sociodemographic questionnaire, State-Trait Anxiety Inventory (STAI-Y), and Beck Depression Inventory (BDI-II). Immediately after, they watched a video called “The Incident,” featuring an individual acting aggressively in front of a crowd, and after that, the Initial free recall was performed. 24 h later (day 2), the participants completed the Stanford Sleepiness Scale (SSS), the State Anxiety Inventory, and carried out the Initial lineup. On day 8, the participants performed the Final lineup. Immediately after, a Final free recall of the video watched on day 1 was executed. Finally, they completed the Chronological order task, the Pittsburgh Sleep Quality Index (PSQI), the STAI-Y, and the second part of the sociodemographic questionnaire .The video showed a conference in a room with numerous people. After about 30 s, a young man broke into the meeting to deliver a message. At that moment he argued with the main speaker of the talk, and became violent, yelling, and throwing objects to the ground. After this, he withdraws muttering. The speaker tried to retake the talk, and the video ended. It was filmed in high definition, by three cameras that alternated presenting a general panorama of the front of the room. It took 90 s.Subjects were presented with an image, simultaneously showing the photographs of 6 bearded males of similar ages and builds, randomly ordered, in black and white, numbered from left to right from one to six, in the form of a typical six-person lineup (lineup consisted of 5 foils and the perpetrator). For the Without perpetrator group, the perpetrator was extracted and another man with similar characteristics was added (lineup consisted of 6 foils). The participants were asked to observe the image for as long as necessary, noting the number that accompanies each photo. It was instructed that they had to identify the person who had broken into the talk or reject the lineup. The subjects received an unbiased instruction, which indicates the possibility of the absence of the perpetrator . In response, they provided a number, or rejected the lineup. Immediately afterward, they were asked for an estimate of the degree of confidence in their own decision, with a number between zero and one hundred, representing with zero the absolute lack of confidence.A total of 40 participants were recruited to assess an online fairness test of the with perpetrator six-persons lineup (lineup consisted of 5 foils and the perpetrator), and 64 participants for the six-person lineup that had no perpetrator, via a mock witness paradigm (lineup consisted of 6 foils) . A groupIn the lineup that included the perpetrator, an ALM of 3.40 and a Functional Size of 5 were obtained. In the lineup without the perpetrator an ALM of 2.50 was obtained.The participants were instructed to describe in as much detail as possible what they had watched in the video, mentioning that it might include dialogues, characteristics of the people  and the place, among other elements. The free recall was recorded, and the total number of details was counted and classified according to their veracity in correct and incorrect details. When counting the number of details, we considered actions, persons, objects, and elements of the environment. Every detail was counted only once, no matter how many times it was repeated in history. The instruction was “Now I’m going to ask you to describe, in as much detail as possible, what you have watched in the video. You can include dialogues, characteristics of the people  and the place. I am going to record everything you say with the recorder.During this test, the lineups of both groups included the perpetrator. It was similar to the Initial lineup, but the set of photographs was personalized, so that each subject could repeat their previous choice. Within the group of 6 photos, there were 3 new faces, and 3 previously seen . On this occasion, both groups had access to the perpetrator and 5 foils, and the order of the photos was semi-randomized, so that none of the previously seen individuals occupied the same place. The fairness control of this lineup was carried out in the same way as in the Initial lineup and 40 mock witnesses were used. It obtained an ALM of 4.13 and a Functional Size of 5.It included contact information, sex, age, educational level, occupation, cohabitation group, intake of medication, and presence of sleep disorders.Based on a 4-point Likert scale, it contains 40 questions that are used to estimate two types of anxiety: state anxiety (the level of anxiety experienced at the time of performing the task) and trait anxiety  . The adaIt is a multiple-choice inventory used to measure severity of depressive symptoms during the past 2 weeks. It is made up of 21 items that cover emotional, cognitive, and behavioral aspects BDI-II; .The participants were provided with 5 images semi-randomly extracted from the video, and they were asked to order them chronologically, starting with the one that was observed first. The five images were presented simultaneously and the time to respond was unlimited. The task was scored considering the performance in terms of two factors: absolute location (that the first observed image was assigned to place 1) and relative location (that the first observed image was assigned to a position prior to the second observed image). The result obtained varies between 0 and 5, a higher score represents a better performance.It is a self-administered questionnaire that assesses the quality of sleep integrating several factors, such as its latency, duration, and efficiency. Each component receives a score between 0 and 3, and is subsequently added to the others, having a result of between 0 and 21 points. Higher scores represent poorer quality of sleep .Statistical analyzes were carried out in the statistical software IBM SPSS Statistics 25, and RStudio Version 1.3.1073. The scores of the three symptomatology scales  were transformed into categories above and below average (low/high) in a similar way to the procedure of The frequency of target selection for the With/Without perpetrator groups, in the Initial and Final lineup, was analyzed with Pearson’s chi-squared test. We further calculated the Odds ratio. Additionally, chi-squared was used to compare the frequency of target selections of the subgroups (within With/Without perpetrator) of high or low anxiety, depression and quality of sleep, both in the Initial lineup and in the Final lineup, between them and against the chance level.The recall variables were analyzed with two-tailed T-test comparing the high and low level of the symptomatology variables. The score of the chronological order task was related to symptomatology variables in the same way.t-test was used to compare recall variables between Initial and Final free recall. For the non-parametric variables, we used the Wilcoxon Signed-Ranks Test.A paired All tests were performed with a fixed alpha of 5%.Additionally, to evaluate the relationship between the accuracy of the elections and the confidence attributed to them, two types of analysis were carried out. Initially, Point Biserial Correlation was applied  and thenN = 17) of the participants selected the target on Day 8, significantly higher than the 22% (N = 7) selected by the Without perpetrator group . Thus, the target selection was alarmingly low for both groups. However, if we consider that by chance 17% (one sixth) of the subjects would select the target, we observed that the With perpetrator group was significantly higher than the chance level . This difference was not observed for the Without perpetrator group . Furthermore, based on the odds ratio, the odds that a subject would recognize the target on Day 8 would be 2.96 times higher if the perpetrator had been available during recognition on Day 2.Regarding the repetition of the lineup, we observed that in the With perpetrator group 43% (2(2) = 1.01, p = 0.32]. However, within these repeated identifications, the rate of correct choices was different for both groups. While the With perpetrator group showed that 46% (N = 13) of their repeated choices were correct (target selection-target selection), the Without perpetrator group showed that only one of their maintained choices was correct  = 9.69, p < 0.01). It is important to consider that in the case of the Without perpetrator group a maintained correct identification would imply that the participant would have rejected the foils on Day 2 and have chosen the perpetrator on Day 8 while participants in the With perpetrator group have access to the perpetrator in both tests. We further analyzed the incorrectly maintained choices of the Without perpetrator group. We observed that 39% (N = 12) of the participants did not repeat the same choice in the Final lineup. However, 61% (N = 19) chose the same foil twice, significantly different to the choice level .There were no significant differences between groups for the maintained choices between the recognition at Day 2 and the test at Day 8 (choose the same photo in both lineups) (N = 2) of the Without perpetrator group correctly rejected the lineup.Regarding the Initial lineup, 36% (14) of the participants in the With perpetrator group achieved a target selection in the Initial lineup, while only 6% (p = 0.140). In the Final lineup no significant relationships were found, both for the With perpetrator group , and for the Without perpetrator group . In addition, the CAC curves were performed to comprehensively evaluate the confidence-precision relationship. Confidence was divided into low confidence (0–50%), medium confidence (60–80%) and high confidence (90–100%). To calculate the value of the correct proportion corresponding to each confidence level, the following formula was used: # Correct identifications/# Correct identifications + # Incorrect identifications (N = 4), 0.23 (N = 8), and 0.05 (N = 2) were obtained for low, medium, and high confidence, respectively (N = 3), 0.38 (N = 13), and 0.11 (N = 4) in low, medium and high confidence, respectively. The Without perpetrator group presented at low confidence an incorrect proportion of 0.71 (N = 7), at medium confidence 0.78 (N = 23), and in high confidence an incorrect proportion of 0.66 (N = 1) was found (N = 3), 0.28 (N = 11), and 0.07 (N = 3) in low, medium, and high confidence, respectively. The Without perpetrator group presented correct proportions of 0.12 (N = 4), 0.09 (N = 3), and 0 (N = 0) in low, medium, and high confidence, respectively (N = 7), 0.28 (N = 11), and 0.10 (N = 4) in low, medium and high confidence, respectively. The Without perpetrator group presented incorrect proportions of 0.25 (N = 8), 0.46 (N = 15), and 0.06 (N = 2) in low, medium, and high confidence, respectively  = 0.14, p = 0.91, V = 0.14], anxiety at day 8 , and quality of sleep . A summary of the symptomatology scale scores (divided by groups) can be found in We divided the symptomatology scales into high and low scores . No significant differences were found between the With and Without perpetrator groups in terms of levels of depression , depression  and sleep quality . None of the high/low subgroups of the three symptom scales achieved target selections above the chance level in the Final lineup.No significant associations were found between the performance of the With perpetrator group on the Initial lineup, and levels of anxiety at day 1 , high and low anxiety score on day 1 , high and low depression score , high and low sleep quality score . However, we find that the target selection for the low anxiety at day 8 were significantly above the chance level , also for high anxiety at day 1 , high depression  and high sleep quality condition . No other subgroup achieved target selections significantly above the chance level (1.11 < (χ2(2) < 2.13, all ps > 0.29).We further differentiated the identifications made in the Final lineup for the With perpetrator group, dividing the participants in high and low symptomatology scores. We observed no significant differences for the target selection between high and low anxiety score on day 8 , high and low anxiety score on day 1 , high and low depression score , high and low sleep quality score . None of the high/low subgroups of the three symptom scales achieved target selections above the chance level in the Final lineup .The same analysis was applied to the Without perpetrator group. We observed no significant differences for the target selection between high and low anxiety score on day 8 [χ2(1) = 0.001, U-test, U = 501.50, p = 0.03, RB = 0.23).We found that those participants with high sleep quality, perform better in the chronological order task than those with low sleep quality . We further found that those subjects who exhibited a high degree of depressive symptoms, reported a smaller drop in the number of details, between the Initial recall and the Final recall with respect to those who showed a low depressive level  = 2.25, p = 0.02, d = 0.26). No other significant differences were found for the recall variables grouped by the levels of the symptom scales (−1.31 < t (70) < 1.29, all ps > 0.08).In addition, we observed that those participants with high sleep quality, provide a greater number of incorrect details during the Initial recall than those with low sleep quality (This study was a first step toward understanding how lockdown by COVID-19 pandemic context may influence eyewitness identifications and episodic memory formation. We first found that participants in the With perpetrator group who exhibited high anxiety on the first day, selected the target in the Final lineup above the chance level. On the contrary, those who showed a low degree of anxiety on day 8, selected the target in the Final lineup above the chance level. These results go in line with the model proposed by Regarding the recall variables, we observed no significant differences between the anxiety level for neither the free recall nor for the Chronological order task. The differences shown by our data in the anxiety modulation between target selection in the lineup and the episodic memory could be due to the influence of uncontrolled variables such as cognitive overload and test expectancy which could be impacting in a different way the different types of recall .We further observed that those participants within the With perpetrator group who showed a high degree of depression selected the target above the chance level, but participants with low depression did not. A similar result was obtained for the recall variables, where those participants with a high degree of depressive symptoms had a lower decay in memory change between the Initial recall and the Final recall, than those with low depression. Taken together, these results could be explained as the product of a biased processing in favor of negative content . Thus, tRegarding the temporal order, it has been shown that patients with depressive disorder showed an impairment in the temporal order of their episodic memories . HoweverIn addition, we found that those participants within the With perpetrator group who had high quality of sleep selected the target significantly above change in the Final lineup but this result was not found for the participants in the low condition. This is supported by several studies showing that sleep improves memory acquisition and consolidation . HoweverRegarding the recall variables, we observed that participants with high sleep quality recalled more incorrect details on day 1 than participants with low quality. We would expect that a low quality of sleep will be related to a decrease in source monitoring inducing more false memories . HoweverIn addition, we found that those subjects with high sleep quality obtained better results in the Chronological order task. This highlights the widely accepted fact that adequate sleep is conducive to learning . Both, sThe results suggest that simply being exposed to an innocent suspect in an intervening lineup, whether that innocent suspect is identified by the witness or not, increases the probability of misidentifying the innocent suspect and decreases the probability of correctly identifying the true perpetrator in a subsequent test lineup.It has been largely demonstrated that multiple lineups would increase the chance to identify an innocent as a suspect and decrease the probability of correctly identifying the true perpetrator . Here weWhen considering the low overall performance of both groups, the possibility of explaining the results because of low encoding level, derived from contextual conditions, should also be considered. It has been extensively documented how an individual’s state at the time of learning can affect their ability to acquire new information, both positively and negatively . In thisConcerning the confidence-accuracy relationship, the curve did not seem to follow a clear trend . AlthougAmong the limitations of our study, it stands out that the size of the sample could have prevented a more detailed and reliable analysis that would take advantage of more subdivisions of the variables. The approach in real context, offered us a more ecological model, but a less controlled environment. As a result, the intervention of variables not contemplated should not be completely ruled out when considering the results. Additionally, unlike our experimental situation, in a real-life episode, where an individual experiences a violent crime, the sleep disturbances are not likely to appear until after the event, so they would not have an impact on the encoding. Finally, not having pre-lockdown measures in our specific population forces us to speculate based on the trend observed in other populations, and although there are strong reasons to think that anxiety, depression, and the quality of sleep were modified during this period, it is not possible to prove it undoubtedly.The phenomenon of false memories is complex and multi-determined. It is possible that this work has been able to reflect a portion of that complexity, by showing how different contextual and individual variables interact dynamically to end up in a complex result. From this point, it is essential to move toward a more careful handling of each of the multiple factors mentioned. In particular, regarding identification performance, the variation of the exposure times to the initial stimulus, as well as the manipulation of the degree of similarity between the faces that makes up the lineup, would be a promising horizon toward which to advance in future experiments.https://zenodo.org/record/5548028#.YVsjLJrMLIV.The raw data supporting the conclusions of this article is available in The studies involving human participants were reviewed and approved by Ethics Committee of Institute of Translational Medicine Research Alberto C. Taquini Buenos Aires University. The patients/participants provided their written informed consent to participate in this study.FU, CL, MB, and CF made substantial contributions to the conception and design of the work. FU ran the experiments. FU and PF-K performed the statistical analyses. FU, CL and CF contributed by drafting the work. FU, CL, MB, PF-K, and CF contributed to revising it critically. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Using single-cell RNA sequencing (scRNA-Seq) to identify T cell receptors (TCRs) in IAR T cells, we have identified a class of TCRs that share TCRα chains between individuals (“public” chains). We isolated IAR T cells from blood of healthy, new-onset T1D and established T1D donors using multiplexed CD154 enrichment and identified paired TCRαβ sequences from 2767 individual cells. More than a quarter of cells shared TCR junctions between 2 or more cells (“expanded”), and 29/47 (~62%) of expanded TCRs tested showed specificity for islet antigen epitopes. Public TCRs sharing TCRα junctions were most prominent in new-onset T1D. Public TCR sequences were more germline like than expanded unique, or “private,” TCRs, and had shorter junction sequences, suggestive of fewer random nucleotide insertions. Public TCRα junctions were often paired with mismatched TCRβ junctions in TCRs; remarkably, a subset of these TCRs exhibited cross-reactivity toward distinct islet antigen peptides. Our findings demonstrate a prevalent population of IAR T cells with diverse specificities determined by TCRs with restricted TCRα junctions and germline-constrained antigen recognition properties. Since these “innate-like” TCRs differ from previously described immunodominant TCRβ chains in autoimmunity, they have implications for fundamental studies of disease mechanisms. Self-reactive restricted TCRα chains and their associated epitopes should be considered in fundamental and translational investigations of TCRs in T1D.Human islet antigen reactive CD4  This process has the potential to be extremely diverse, with a vast potential repertoire size  to recognize antigenic peptides presented in the context of major histocompatibility (MHC) molecules. Each T cell expresses a distinct TCR clonotype, most commonly comprising TCRα and β chains  utilized restricted TRA chains  and established T1D (T1D) donors. We also found extensive TCR clonotype sharing in IAR T cells from T1D subjects, consistent with in vivo T cell expansion during disease progression. Here we examined IAR T cells from a broader cohort of HC, new-onset T1D (newT1D), and established T1D patients. We demonstrate that public and private TCRs from IAR T cells have different properties and change in proportion as T1D progresses.Increasingly, phenotypic and TCR diversity of T cells are being explored by genome-wide single-cell RNA sequencing (scRNA-Seq) , 30–37. https://doi.org/10.1172/jci.insight.151349DS1 Age did not differ significantly between groups , and another pool for newT1D patients, containing 7 additional peptides to accommodate the DRB1*0301 patients (0401/0301/DQ8 pool). The peptides we used represent consensus immunodominant epitopes recognized by CD4+ T cells in DRB1*0401, DRB1*0301, and DQ8 T1D patients over many published  (+ plus CD45RO+), to increase cell yield. Unless noted otherwise, analyses reported here utilized memory cells because they are antigen experienced and more likely involved in ongoing autoimmunity.Following peptide stimulation, cells with upregulated CD154 were enriched using magnetic bead separation , then soCD45RO+) , though n = 2767 cells (profiles) from individual IAR T cells . This corresponds to means of 38, 62, and 68 profiles/person from each disease group. By amino acid sequences, these cells expressed 4296 unique TCR junctions, corresponding to 2160 and 2136 TRA and TRB junctions, respectively. These TCR sequences are listed in Sorted cells that were subjected to scRNA-Seq and RNA-Seq reads were processed to identify rearranged TCR chains . After initial quality control filtering, we identified TCRs in + T cells, followed by functional analysis of antigen specificity  were then transduced with recombinant lentiviruses, and cells that had or had not been transduced were identified by staining for the murine Tcrb constant region encoded by the recombinant TCR (+ 8.84% (mean + SD).Key islet epitope(s) driving in vivo expansion of IAR T cells have not been identified. To demonstrate the specificity of expanded TCRs, we ascertained the specific cognate peptide(s) recognized by individual TCRs from the pools used to stimulate T cell activation. To accomplish this, we used recombinant lentiviral transduction methods to ectopically express TCR sequences in primary CD4cificity . We focunant TCR  44). Th. Th+ T cSpecificity of TCRs was determined by testing transduced T cells for proliferation in response to islet peptides . Cell di50) values are included in DRB1*0401-restricted TCR (50 was less than the lowest concentration of peptide tested (EC50 < 0.01 μg/mL). Most IAR TCRs yielded dose-response curves shifted to the right  when compared with the HA reactive TCR, with EC50 values ranging from 0.01 to >10 g/mL , showing greater avidity than other IAR TCRs. It may be important that these expanded, high-avidity TCRs were found only in single individuals. EC50 values were not clearly related to TCR transduction efficiency, suggesting that they were intrinsic to each TCR. In this small data set, EC50 values were not obviously related to disease status.We found that measurable proliferation above background was dose-dependent upon peptide concentration, as shown for a subset of 23 expanded IAR TCRs in cted TCR . Prolife>10 g/mL . One of + cells triggered islet peptide-specific proliferation: 18/47 TCRs (~38%) did not proliferate in response to specific peptides  identified a perfect match with an iNKT receptor , but public junctions were more variable in length than private TRA junctions (TRB junctions were significantly longer than public junctions (median lengths of 15 versus 14 amino acids)  of junction sequences during TCR recombination J recombination. Conversely, sequences with lower (more negative) pgen values have a lower probability of generation. We calculated pgen values for public and private TCRs and compared them for both TRA and TRB junctions . Higher pgen scores and shorter chain lengths seen in public IAR TCRs are interrelated properties of sequences common to many repertoires  . These dbination . Junctiounctions . As expeunctions , indicat+), T1D, and control donors collected through the Network for Pancreatic Organ Donors with Diabetes (nPOD)  and disease state  gave qualitatively similar overlaps with IAR T cell TRB junctions.To further characterize public and private TCRs from IAR T cells, we determined whether their junction amino acid sequences were represented in other TCR databases. One such database comprises TCR sequences from different T cell subsets isolated from spleen and pancreatic lymph nodes from autoantibody positive at risk (AAbs (nPOD) , 51. TCRunctions . Among pVDJdb is another curated TCR database of TCR sequences with known antigen specificities, comprising both TRA and TRB junctions  had perfect matches with VDJdb junctions, significantly more than private TRA junctions  epitopes, identified by multiplex class I peptide–MHC multimer binding , that utilizes single-cell TCR chain sequence data to construct an undirected graph representing the TCR clonotype landscape for a given data set (tcrGraph defines a TCR “clone” as a maximum number of chains that are paired with one another but not with other chains. We used tcrGraph to assign unique identifiers (cloneIDs) to each TCR clone  based on amino acid sequences   (TRA-TRB pairs (1 TRA-1 TRB)  (We then used  T cells . Using tA-1 TRB) . In contB, etc.) . TabulatA-1 TRB) . Chain pimmunity , but freB, etc.) .TRB and TRA junctions . Breaking down these results by disease group showed that the fraction of TRA junctions associated with multiple TRB junctions  was greatest in newT1D patients . Notably, none of the public TRA junctions from patients with T1D were associated with multiple TRB junctions  than private TRB junctions , consistent with biological specificity rather than randomly assorting technical factors.To ensure that the different chain pairing between public and private IAR TCRs was not biased by technical factors unrelated to disease state, we performed similar tabulations for the reverse pairings, i.e., numbers of unctions . Thus, tTRB junctions with an identical TRA chain in public IAR TCRs, we performed junction amino acid sequence comparisons. We identified the complete set of TRB junctions sharing TRA junctions  among all TCRs in our study and performed pairwise sequence comparisons. As a metric, we utilized Levenshtein distance, the minimum number of single amino acid residue changes  required to change one TRB sequence into the other. We then plotted the distribution of pairwise Levenshtein distances of unique TRB junctions associated with a single TRA chain compared with the distribution of distances between randomly selected TRB junctions from nonexpanded IAR TCRs  (TRA-sharing TRB junctions was shifted significantly lower (more similarity) compared with the random sets , this was not true of all pairwise combinations. Thus, while some TRA-sharing TRB junctions from IAR T cells were similar in sequence, others were quite different.To better understand pairing of multiple Methods) . While tTRB junctions associated with a single TRA chain, we performed sequence alignments for pairs with lowest Levenshtein distance . To resolve this question, we tested islet antigen specificity for public TCR clones with identical TRA chains and mismatched TRB junctions to determine if they recognized the same peptide   . In othectively)  showed sunctions . Thus, s epitope .P value = 0.0392, Fisher’s exact test). Examining the public multispecific TCRs in more detail, we noted that Clone_81 TCR was triggered by multiple peptides from GAD65. GAD 377–396 showed the strongest activity, while 2 additional peptides, GAD 273–292 and GAD 281–300, which overlapped each other but were noncontiguous with GAD 377–396, showed weaker activity  showed specificity for multiple islet peptides . Multispactivity . This saactivity . The patactivity . GAD 273e tested . SequencUsing scRNA-Seq on a wider number of HCs and patients with T1D and broader duration of disease than we examined previously , we repoThe frequency of public TCRs in IAR T cells was increased in newT1D relative to established T1D. This perhaps reflects dilution of specificities as epitope spreading occurs in established T1D –58. It iTRA chains . The figure is likely to be an underestimate, as our methods detected relatively low numbers of cells. In addition, the use of combinations of restricted public clones may allow coverage of an even larger and more useful fraction of newT1D/T1D patients. However, we recognize that unless most or all drivers of disease are among the public clones, targeting cells expressing these public clones is not likely to modify disease. Another caveat to translational uses of shared TRA public chains from IAR T cells is potential cross-reactivity of these TCRs with CMV or other microbes. Using such cross-reactive public TCRs as targets for T cell depletion might introduce holes in the host antimicrobial repertoire, although it is not known how consequential any such holes would be for the overall antimicrobial repertoire. Finally, the predominance of public TRA chains in IAR T cells indicates the need for additional translational studies to evaluate TRA chains as well as TRB chains. This is especially true because TRB chains have been the focus of most studies investigating TCRs as biomarkers and therapeutic targets . Code and data for generating the figures are provided at https://github.com/BenaroyaResearch/Shared-germline-like-TCR-alpha-chains-in-type-1-diabetes (commit ID: fb926c7aaf8f72203eb72f4bb0cb4c9481e233be). Profiles yielding TCRs were deposited in the National Center for Biotechnology Information Gene Expression Omnibus repository .Code for Protocols for these studies were approved by the Institutional Review Board of Benaroya Research Institute (IRB7109-332). Protocols for the T1DAL clinical trial were approved under the auspices of NCT00965458, as described previously .tcrGraph software; PSL directed and PSL, EB, HAD, KJF, and AKH analyzed RNA-Seq data; CO performed EC50 analysis; WWK, CS, CJG, GTN, ES, KM, HRS, and TMB provided materials; PSL, KC, FBW, EB, HAD, KJF, and HKU interpreted data; PSL and KC conceived the experiments; and PSL and KC wrote the manuscript. All authors made contributions to the final manuscript.EB, JC, and FBW performed and KC directed laboratory experiments; VHG directed RNA-Seq profiling; MGR performed pipeline analysis of the RNA-Seq data and developed the


WNT10A. A HaploReg database research for regulatory annotations revealed that the association signal at 2q35 maps to a binding site for the transcription factor EBF1, whose gene is located at a second MPB risk locus on chr. 5q33.3. To investigate a potential interaction between EBF1 and WNT10A during MPB development, we performed in vitro luciferase reporter assays as well as expression analyses and immunofluorescence co-stainings in microdissected human hair follicles. Our experiments confirm that EBF1 activates the WNT10A promoter and that the WNT10A/EBF1 interaction is impacted by the allelic expression of the MPB risk allele at 2q35. Expression analyses across different hair cycle phases and immunhistochemical (co)stainings against WNT10A and EBF1 suggest a predominant relevance of EBF1/WNT10A interaction for hair shaft formation during anagen. Based on these findings we suggest a functional mechanism at the 2q35 risk locus for MPB, where an MPB-risk allele associated reduction in WNT10A promoter activation via EBF1 results in a decrease in WNT10A expression that eventually results in anagen shortening, that is frequently observed in MPB affected hair follicles. To our knowledge, this study is the first follow-up study on MPB that proves functional interaction between two MPB risk loci and sheds light on the underlying pathophysiological mechanism at these loci.More than 300 genetic risk loci have been identified for male pattern baldness (MPB) but little is known about the exact molecular mechanisms through which the associated variants exert their effects on MPB pathophysiology. Here, we aimed at further elucidating the regulatory architecture of the MPB risk locus on chromosome (chr.) 2q35, where we have previously reported a regulatory effect of the MPB lead variant on the expression of  Male-pattern baldness (MPB) is the most common form of heritable hair loss in men. The phenotype is characterized by an androgen-dependent progressive hair loss in distinct areas of the scalp. While the pathophysiological signs have been well described (reviewed elsewhere ), the moPcombined = 3.55×10−15, effect allele (EA) = T, odds ratio (OR) = 1.34, 95% confidence interval (CI) = [1.27–1.42]) ) . The ass 606268) . Moreoveollicles , 17. Howin silico and in vitro experiments localization of EBF1 and WNT10A across hair follicle compartments we performed immunofluorescence stainings in microdissected human scalp hair follicles. We demonstrate that WNT10A and EBF1 are expressed in the same human hair follicle compartments suggesting a co-expression in vivo. Together, our data provide not only novel insights into the regulatory architecture of the 2q35 risk locus but also yield the first functional evidence for a regulatory interaction between candidate genes at different MPB risk loci.Therefore, we aimed at further elucidating the underlying biological mechanism at the 2q35 risk locus and its role in MPB by means of eriments . To thisr2 >0.6). The database research identified rs3856551-C/T, a second MPB associated variant located 10.2 kb upstream of and in strong LD with rs7349332 . According to HaploReg annotations, rs3856551 is located intronically in WNT10A and within a transcription factor binding site for EBF1   = 71%) compared to the non-risk allele   . Based oWNT10A expression and whether (ii) this interaction is influenced by the 2q35 MPB risk allele, we performed luciferase reporter assays. To this end, we transiently co-transfected HEK-293T cells with (i) luciferase vectors that contained a predicted WNT10A promoter sequence as well as the 2q35-EBF1 binding site, harboring either the MPB risk (rs3856551-T) or the alternate allele (rs3856551-C); or the empty reporter vector pGL-3-basic as a control and (ii) an EBF1 expression vector. Here, the sequence of the functional elements within the luciferase vectors (pWNT10A-FL-EBF1) was specifically designed to reflect the genomic architecture at the 2q35 risk locus  with increasing amounts of transfected EBF1 vector (5–20 ng) across all experiments. Without high EBF1 stimulation (<20 ng), no significant differences in promoter activity were observed, however stimulation at the highest EBF1 concentration (20 ng) consistently resulted in a significant (P<0.05) preferential promoter activation with the WNT10A promoter carrying the MPB non-risk allele  EBF1 acts as a regulator of in vitro model, the detection of co-expression of genes or their protein products in phenotypically relevant tissue can provide additional evidence for a functional interaction. Therefore, the expression of the candidate genes WNT10A and EBF1 and their resulting protein products were investigated in microdissected human temporal scalp hair follicle specimen  = 71% vs MSS [rs3856551-C] = 66%). However, the experimental data are in line with the assumption that EBF1 acts as a transcriptional activator of WNT10A expression and the previous mRNA expression data that revealed a reduced expression of WNT10A in hair follicles of 2q35 risk allele carriers -FL) containing the putative Mycoplasma contamination using Venor®GeM Advance, Minerva Biolabs, Berlin Germany) were grown in DMEM  supplemented with 10% vol/vol fetal bovine serum  at 37°C in an atmosphere of 5% CO2. In 48-well plates, 5.2×104 cells per well were seeded in 250 μl DMEM 24 h prior to transient transfection. Transfection was carried out using Lipofectamine® 2000  according to the manufacturer’s protocol. In brief, for each well of the 48-well plate 25 μl OptiMEM  was mixed with 0.5 μl Lipofectamine, 5 ng pRL-CMV , 50 ng reporter plasmid and 5–20 ng of pCMV5 or 5–20 ng pCMV-EBF1. The mixture was incubated for 5 min at room temperature and then added to the appropriate wells. Transfected cells were grown for 48 h at 37°C and 5% CO2 level and afterwards used for luciferase reporter assays. Each transfection was carried out in triplicate  in at least three independent experiments .HEK-293T cells . Each measurement was done in at least three independent experiments. Since the addition of the EBF1 expression vector led to a significant decrease in Renilla luminescence in the present experiments  and were directly equated to the activity of the examined WNT10A promoter.Forty-eight hours post-transfection, cells were carefully washed with 1×PBS  and the Dual-Luciferase® Reporter Assay System  was used according to the manufactures’ protocol to measure eriments  it couldHuman hair follicles from temporal “clinically healthy” scalp skin were obtained from patients during routine face-lift surgery. For the immunofluorescence analyses, anagen hair follicles derived from three different individuals were microdissected  one day WNT10A: Hs00228741_m1, EBF1: Hs01092694_m1, GAPDH: Hs02786624_g1, ACTB: Hs01060665_g1, all Applied Biosystems, Foster City, CA, USA) were mixed. The samples were analyzed in triplicates  on a QuantStudio 3 Real-Time PCR System  using the following conditions: 95°C for 10 min, followed by 45 cycles of 95°C for 15 s and 60°C for 1 min. Relative expression of WNT10A and EBF1 in relation to the housekeeping genes GAPDH and ACTB was calculated based on the calculated Δ-Cp values using the 2-ΔΔCp-method [Total RNA from 12 human scalp hair follicles (anagen and early catagen stadium) of four donors  each was isolated using the RNeasy Mini Kit  according to the manufactures’ instructions. 500 ng of RNA were reverse transcribed into cDNA using the Tetro™ cDNA Synthesis Kit . For the gene expression assay 0.5 μl cDNA, 5 μl TaqMan® Fast Advanced Master Mix , 0.5 μl TaqMan® Gene Expression Assay .All data are expressed as mean ±SEM. To evaluate statistical differences in luciferase assays, two-way analysis of variance (ANOVA) followed by Tuckey’s post-hoc test was applied to account for multiple comparisons. Given the exploratory design and moderate statistical power of this study, no correction for multiple testing was performed. For the statistical analysis of the qPCR results, the mean ±SEM of the measurements were calculated. Immunohistochemical staining was used to analyze the expression pattern and localization of WNT10A and EBF1 in the human hair follicle. The cryosections were first air dried for 10 min at room temperature and then fixed for 10 min in acetone at -20°C (WNT10A) or 4% paraformaldehyde at room temperature (EBF1). After air drying for 10 min at room temperature the slides were washed three times for 5 min in wash buffer . Cryosections for the WNT10A staining were blocked at room temperature for 60 min with a mixture of 20% normal goat serum, 1% bovine serum albumin (BSA) and 0.1% Tween20 in TBS. The WNT10A primary antibody  diluted 1:25 in TBS was applied overnight at 4° C. After washing the sections three times for 5 min in TBS, the sections were stained with a goat anti-rabbit IgG secondary antibody conjugated with Alexa Fluor 488  for 45 min at room temperature. Cryosections for the EBF1 staining were pre-incubated at room temperature for 30 min with a mixture of 0.1% Triton-X, 1% BSA in PBS. The EBF1 primary antibody  diluted 1:20 in 1% BSA/PBS was applied overnight at 4°C. After washing the cryosections three times for 5 min in PBS, the sections were stained for 45 min with a goat anti-rabbit IgG secondary antibody conjugated with fluorescein . To enhance the fluorescence signal the sections were incubated with a tertiary antibody directed against fluorescein conjugated to Alexa Fluor 488  for 30 min at room temperature. After washing the cryosections three times for 5 min in their respective wash buffer, the sections were counterstained with DAPI  for 1 min, washed three times for 5 min in their wash buffer and mounted with Fluoromount-G™ . For all immunostainings primary antibodies were omitted for negative controls. The sections were dried for 30 min at room temperature and stored at -20°C until fluorescence microscopy. For fluorescence microscopy and photographs a BZ-9000  fluorescence microscope maintaining a constant set exposure time throughout imaging was used.S1 FigSchematic representation of the study background, the key scientifc questions, the experimental workflow, and the key findings and conclusion of the present study.(TIF)Click here for additional data file.S2 FigWNT10A promoter with respect to EBF1 and rs3856551 in five separate experiments. (F-J) Renilla (RL) values of the five luciferase assays. The number in brackets marks correlating experiemnts. B and G belong to (A-E) Activity of (TIF)Click here for additional data file.S3 FigRepresentative pictures of WNT10A (A) and EBF1  stainings in hair follicle samples from two additional independent individuals. For (C) Alexa Fluor 555  was used as the secondary antibody. Orignal magificaiton x 200.(TIF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.