Complete Platysma Muscle Suspension in Deep Plane Facelift Surgery.

SUMMARY: Deep plane facelift surgery is not new, having originally been described over 30 years ago, however the technique has seen a recent surge in popularity. While proponents emphasize its ability to deliver very natural results, critics often cite the possibility of additional risk of the procedure due to its technically challenging dissection in proximity to branches of the facial nerve and other critical structures. These risks are perhaps greatest when operating in what have historically been described as the "danger zones," particularly when releasing the zygomatic retaining ligaments, when performing the medial deep plane dissection in the midface, and when extending the platysma flap over the angle of the mandible into the neck. The senior author (DBR) has performed deep plane facelift surgery for over 20 years, training many novice surgeons to perform this procedure safely and incrementally. Herein, we illustrate surgical techniques to optimize safety when performing deep plane dissections. A novel vertical midline platysmaplasty combined with extended release of the low cervical platysma provide rejuvenation of the neck that extends to the clavicles.

VASCilia (Vision Analysis StereoCilia): A Napari Plugin for Deep Learning-Based 3D Analysis of Cochlear Hair Cell Stereocilia Bundles.

Cochlear hair cell stereocilia bundles are key organelles required for normal hearing. Often, deafness mutations cause aberrant stereocilia heights or morphology that are visually apparent but challenging to quantify. Actin-based structures, stereocilia are easily and most often labeled with phalloidin then imaged with 3D confocal microscopy. Unfortunately, phalloidin non-specifically labels all the actin in the tissue and cells and therefore results in a challenging segmentation task wherein the stereocilia phalloidin signal must be separated from the rest of the tissue. This can require many hours of manual human effort for each 3D confocal image stack. Currently, there are no existing software pipelines that provide an end-to-end automated solution for 3D stereocilia bundle instance segmentation. Here we introduce VASCilia, a Napari plugin designed to automatically generate 3D instance segmentation and analysis of 3D confocal images of cochlear hair cell stereocilia bundles stained with phalloidin. This plugin combines user-friendly manual controls with advanced deep learning-based features to streamline analyses. With VASCilia, users can begin their analysis by loading image stacks. The software automatically preprocesses these samples and displays them in Napari. At this stage, users can select their desired range of z-slices, adjust their orientation, and initiate 3D instance segmentation. After segmentation, users can remove any undesired regions and obtain measurements including volume, centroids, and surface area. VASCilia introduces unique features that measures bundle heights, determines their orientation with respect to planar polarity axis, and quantifies the fluorescence intensity within each bundle. The plugin is also equipped with trained deep learning models that differentiate between inner hair cells and outer hair cells and predicts their tonotopic position within the cochlea spiral. Additionally, the plugin includes a training section that allows other laboratories to fine-tune our model with their own data, provides responsive mechanisms for manual corrections through event-handlers that check user actions, and allows users to share their analyses by uploading a pickle file containing all intermediate results. We believe this software will become a valuable resource for the cochlea research community, which has traditionally lacked specialized deep learning-based tools for obtaining high-throughput image quantitation. Furthermore, we plan to release our code along with a manually annotated dataset that includes approximately 55 3D stacks featuring instance segmentation. This dataset comprises a total of 1,870 instances of hair cells, distributed between 410 inner hair cells and 1,460 outer hair cells, all annotated in 3D. As the first open-source dataset of its kind, we aim to establish a foundational resource for constructing a comprehensive atlas of cochlea hair cell images. Together, this open-source tool will greatly accelerate the analysis of stereocilia bundles and demonstrates the power of deep learning-based algorithms for challenging segmentation tasks in biological imaging research. Ultimately, this initiative will support the development of foundational models adaptable to various species, markers, and imaging scales to advance and accelerate research within the cochlea research community.

Large-scale annotated dataset for cochlear hair cell detection and classification.

Our sense of hearing is mediated by cochlear hair cells, of which there are two types organized in one row of inner hair cells and three rows of outer hair cells. Each cochlea contains 5-15 thousand terminally differentiated hair cells, and their survival is essential for hearing as they do not regenerate after insult. It is often desirable in hearing research to quantify the number of hair cells within cochlear samples, in both pathological conditions, and in response to treatment. Machine learning can be used to automate the quantification process but requires a vast and diverse dataset for effective training. In this study, we present a large collection of annotated cochlear hair-cell datasets, labeled with commonly used hair-cell markers and imaged using various fluorescence microscopy techniques. The collection includes samples from mouse, rat, guinea pig, pig, primate, and human cochlear tissue, from normal conditions and following in-vivo and in-vitro ototoxic drug application. The dataset includes over 107,000 hair cells which have been identified and annotated as either inner or outer hair cells. This dataset is the result of a collaborative effort from multiple laboratories and has been carefully curated to represent a variety of imaging techniques. With suggested usage parameters and a well-described annotation procedure, this collection can facilitate the development of generalizable cochlear hair-cell detection models or serve as a starting point for fine-tuning models for other analysis tasks. By providing this dataset, we aim to give other hearing research groups the opportunity to develop their own tools with which to analyze cochlear imaging data more fully, accurately, and with greater ease.

Supporting education with ips: Advancing a career-oriented model for integrating work and study support for young adults in sweden.

OBJECTIVE: Supported education (SEd) provides individualized support to people with mental health problems to achieve their educational goals. Individual placement and support (IPS) has emerged as a model through which SEd may be efficiently delivered. However, the components and characteristics of educational support for these employment-focused services have not been fully explored. Building on earlier studies, we constructed a preliminary model of SEd components that integrated with the IPS model. The SEd model included the eight original principles of IPS, developed to reflect the SEd component, and two new principles were suggested. The aim of the study is to investigate these adapted principles by exploring the feasibility of applying them within established IPS programs providing both employment and educational services. METHODS: An organizational learning approach was taken, involving five IPS programs providing both employment and educational services to young adults with mental health problems. Data were collected through focus groups, interviews, and workshops with 19 IPS specialists. RESULTS: The results suggest that while the IPS principles provide a feasible and relevant structure for the development and provision of integrated services, adaptations that reflect the educational context were considered valuable when supporting young adults in pursuing their career-related goals. CONCLUSIONS AND IMPLICATIONS FOR PRACTICE: The respondents confirmed that the SEd principles and the focus on support in educational contexts helped them to further develop their knowledge and strategies. While challenging, integrating SEd in IPS models shows good potential for supporting young adults as they struggle to reach longer term career-oriented goals. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Topological Data Analysis Captures Task-Driven fMRI Profiles in Individual Participants: A Classification Pipeline Based on Persistence.

BOLD-based fMRI is the most widely used method for studying brain function. The BOLD signal while valuable, is beset with unique vulnerabilities. The most notable of these is the modest signal to noise ratio, and the relatively low temporal and spatial resolution. However, the high dimensional complexity of the BOLD signal also presents unique opportunities for functional discovery. Topological Data Analyses (TDA), a branch of mathematics optimized to search for specific classes of structure within high dimensional data may provide particularly valuable applications. In this investigation, we acquired fMRI data in the anterior cingulate cortex (ACC) using a basic motor control paradigm. Then, for each participant and each of three task conditions, fMRI signals in the ACC were summarized using two methods: a) TDA based methods of persistent homology and persistence landscapes and b) non-TDA based methods using a standard vectorization scheme. Finally, using machine learning (with support vector classifiers), classification accuracy of TDA and non-TDA vectorized data was tested across participants. In each participant, TDA-based classification out-performed the non-TDA based counterpart, suggesting that our TDA analytic pipeline better characterized task- and condition-induced structure in fMRI data in the ACC. Our results emphasize the value of TDA in characterizing task- and condition-induced structure in regional fMRI signals. In addition to providing our analytical tools for other users to emulate, we also discuss the unique role that TDA-based methods can play in the study of individual differences in the structure of functional brain signals in the healthy and the clinical brain.

Developing sustainable service user involvement practices in mental health services in Sweden: the "Userinvolve" research program protocol.

Background: The purpose of this paper is to outline the protocol for the research program "UserInvolve," with the aim of developing sustainable, service user involvement practices in mental health services in Sweden. Methods: This protocol outlines the knowledge gap and aim of the UserInvolve-program. It further provides an overview of the research infrastructure, with specific focus on the organization and management of the program as well as the design of the six underlying research projects. These six research projects form the core of the UserInvolve-program and will be carried out during a six-year period (2022-2027). The projects are focused on examining articulations of experiential knowledge in user collectives, on four specific user involvement interventions (shared decision-making, peer support, user-focused monitoring, and systemic involvement methods) and on developing theory and method on co-production in mental health research and practice. Results or conclusion: The knowledge gained through the co-production approach will be disseminated throughout the program years, targeting service users, welfare actors and the research community. Based on these research activities, our impact goals relate to strengthening the legitimacy of and methods for co-production in the mental health research and practice field.

Large-scale annotated dataset for cochlear hair cell detection and classification.

Our sense of hearing is mediated by cochlear hair cells, localized within the sensory epithelium called the organ of Corti. There are two types of hair cells in the cochlea, which are organized in one row of inner hair cells and three rows of outer hair cells. Each cochlea contains a few thousands of hair cells, and their survival is essential for our perception of sound because they are terminally differentiated and do not regenerate after insult. It is often desirable in hearing research to quantify the number of hair cells within cochlear samples, in both pathological conditions, and in response to treatment. However, the sheer number of cells along the cochlea makes manual quantification impractical. Machine learning can be used to overcome this challenge by automating the quantification process but requires a vast and diverse dataset for effective training. In this study, we present a large collection of annotated cochlear hair-cell datasets, labeled with commonly used hair-cell markers and imaged using various fluorescence microscopy techniques. The collection includes samples from mouse, human, pig and guinea pig cochlear tissue, from normal conditions and following in-vivo and in-vitro ototoxic drug application. The dataset includes over 90'000 hair cells, all of which have been manually identified and annotated as one of two cell types: inner hair cells and outer hair cells. This dataset is the result of a collaborative effort from multiple laboratories and has been carefully curated to represent a variety of imaging techniques. With suggested usage parameters and a well-described annotation procedure, this collection can facilitate the development of generalizable cochlear hair cell detection models or serve as a starting point for fine-tuning models for other analysis tasks. By providing this dataset, we aim to supply other groups within the hearing research community with the opportunity to develop their own tools with which to analyze cochlear imaging data more fully, accurately, and with greater ease.

Predicting Complicated Mild Traumatic Brain Injury in Adolescent Trauma to Enhance Clinical Decisions in Imaging.

BACKGROUND: The Pediatric Emergency Care Applied Research Network (PECARN) traumatic brain injury algorithm is used to identify children at low risk of clinically significant traumatic brain injuries to reduce computed tomography (CT) exposure. Adapting PECARN rules based on population-specific risk stratification has been suggested to improve diagnostic accuracy. OBJECTIVE: This study sought to identify center-specific patient variables, beyond PECARN rules, that may enhance the identification of patients requiring neuroimaging. METHODS: This single-center, retrospective cohort study was conducted from July 1, 2016, to July 1, 2020, in a Southwestern U.S. Level II pediatric trauma center. The inclusion criteria were adolescents (10-15 years), Glasgow Coma Scale (13-15), with a confirmed mechanical blow to the head. Patients without a head CT were excluded. Logistic regression was performed to identify additional complicated mild traumatic brain injury predictor variables beyond the PECARN. RESULTS: There were 136 patients studied; 21 (15%) presented with a complicated mild traumatic brain injury. Relative to motorcycle collision or all-terrain vehicle trauma (odds ratio [OR] 211.75, 95% confidence interval, CI [4.51, 9931.41], p < .001), an unspecified mechanism (OR 42.0, 95% CI [1.30, 1350.97], p = .03) and consult activation (OR 17.44, 95% CI [1.75, 173.31], p = .01) were significantly associated with complicated mild traumatic brain injury. CONCLUSIONS: We identified additional factors associated with complex mild traumatic brain injury, including motorcycle collision and all-terrain vehicle trauma, unspecified mechanism, and consult activation that are not in the PECARN imaging decision rule. Adding these variables may aid in determining the need for appropriate CT scanning.

White matter volume and myelin oligodendrocyte glycoprotein (MOG) microsatellites in pediatric obsessive-compulsive disorder.

The myelin oligodendrocyte glycoprotein ( MOG ) gene plays an important role in myelination and has been implicated in the genetics of white matter changes in obsessive-compulsive disorder (OCD). We examined the association between variations of two microsatellite markers across MOG for association and total white matter volume as measured using volumetric MRI in 37 pediatric OCD patients 7-18 years. We compared white matter volumes between microsatellite allele groups using analysis of covariance with covariates of age, gender, and total intracranial volume. After controlling for multiple comparisons, a significant relationship was detected between MOG (TAAA)n and increased total white matter volume ( P  = 0.018-0.028). Although preliminary, our findings provide further support for the involvement of MOG in OCD.

The hair cell analysis toolbox is a precise and fully automated pipeline for whole cochlea hair cell quantification.

Our sense of hearing is mediated by sensory hair cells, precisely arranged and highly specialized cells subdivided into outer hair cells (OHCs) and inner hair cells (IHCs). Light microscopy tools allow for imaging of auditory hair cells along the full length of the cochlea, often yielding more data than feasible to manually analyze. Currently, there are no widely applicable tools for fast, unsupervised, unbiased, and comprehensive image analysis of auditory hair cells that work well either with imaging datasets containing an entire cochlea or smaller sampled regions. Here, we present a highly accurate machine learning-based hair cell analysis toolbox (HCAT) for the comprehensive analysis of whole cochleae (or smaller regions of interest) across light microscopy imaging modalities and species. The HCAT is a software that automates common image analysis tasks such as counting hair cells, classifying them by subtype (IHCs versus OHCs), determining their best frequency based on their location along the cochlea, and generating cochleograms. These automated tools remove a considerable barrier in cochlear image analysis, allowing for faster, unbiased, and more comprehensive data analysis practices. Furthermore, HCAT can serve as a template for deep learning-based detection tasks in other types of biological tissue: With some training data, HCAT's core codebase can be trained to develop a custom deep learning detection model for any object on an image.

A prototype closed-loop brain-machine interface for the study and treatment of pain.

Chronic pain is characterized by discrete pain episodes of unpredictable frequency and duration. This hinders the study of pain mechanisms and contributes to the use of pharmacological treatments associated with side effects, addiction and drug tolerance. Here, we show that a closed-loop brain-machine interface (BMI) can modulate sensory-affective experiences in real time in freely behaving rats by coupling neural codes for nociception directly with therapeutic cortical stimulation. The BMI decodes the onset of nociception via a state-space model on the basis of the analysis of online-sorted spikes recorded from the anterior cingulate cortex (which is critical for pain processing) and couples real-time pain detection with optogenetic activation of the prelimbic prefrontal cortex (which exerts top-down nociceptive regulation). In rats, the BMI effectively inhibited sensory and affective behaviours caused by acute mechanical or thermal pain, and by chronic inflammatory or neuropathic pain. The approach provides a blueprint for demand-based neuromodulation to treat sensory-affective disorders, and could be further leveraged for nociceptive control and to study pain mechanisms.

Provider Response to a Venous Thromboembolism Risk Assessment and Prophylaxis Ordering Tool: Observational Study.

OBJECTIVES: Our health system launched an initiative to regulate venous thromboembolism (VTE) risk assessment and prophylaxis with electronically embedded risk assessment models based on validated clinical prediction rules. Prior to system-wide implementation, usability testing was conducted on the VTE clinical decision support system (CDSS) to assess provider perceptions, facilitate adoption, and usage of the tool. The objective of this study was to conduct usability testing with end users on the CDSS' risk assessment model and prophylaxis ordering components. METHODS: This laboratory usability testing study was conducted with 24 health care providers. Participants were given two case scenarios that mirrored real-world scenarios to assess likelihood of use and adoption. During each case scenario, participants engaged in a think-aloud session, verbalizing their decision-making process while interacting with the tool. Following each case scenario, participants completed the System Usability Scale (SUS) and a posttask interview. Participants' comments and interactions with the VTE CDSS were placed into coding categories and analyzed for generalizable themes by three independent coders. RESULTS: Of the 24 participants, 50% were female and the mean age of all participants was 32.76 years. The average SUS across the different services lines was 72.39 (C grade). Each participant's comments were grouped into three overarching themes: functionality, visibility/navigation, and content. Comments included personalizing workflow for each service line, minimizing the number of clicks, clearly defining risk models, including background on risk scores, and providing treatment guidelines for order sets. CONCLUSION: An important step toward providing quality health care to patients at risk of developing a VTE event is providing user-friendly tools to providers. Following usability testing, our study revealed opportunities to positively impact provider behavior and acceptance. The rigor and breadth of this usability testing study and adoption of the optimizations should increase provider adoption and retention of the VTE CDSS.

Clinical relevance of the use of Dentoxol® for oral mucositis induced by radiotherapy: A phase II clinical trial.

BACKGROUND: Severe oral mucositis associated with cancer therapy is a frequent complication that may affect a patient's systemic condition, resulting in interruption and/or prolongation of cancer therapy. Dentoxol® is a medical solution in the form of a mouthwash that has been shown to result in statistically significant improvement in the prevention of severe oral mucositis. However, knowing the measures of the clinical significance of this therapy is important for accurate decision-making. AIM: To describe the clinical impact of Dentoxol® use in severe oral mucositis. METHODS: Clinical significance was measured using the results obtained in a randomized controlled clinical trial previously conducted by the same group of researchers. The measures of clinical significance evaluated were the absolute risk or incidence, relative risk, absolute risk reduction, relative risk reduction, number needed to treat, and odds ratio. RESULTS: The data obtained show that the impact of Dentoxol® on reducing the severity of oral mucositis has important clinical relevance. CONCLUSION: The results of this study justify the incorporation of Dentoxol® mouth rinse into clinical protocols as a complement to cancer therapy to prevent and/or treat oral mucositis secondary to radiotherapy.

Legitimizing user knowledge in mental health services: Epistemic (in)justice and barriers to knowledge integration.

Including the voices and knowledge of service users is essential for developing recovery-oriented and evidence-based mental health services. Recent studies have however, suggested that challenges remain to the legitimization of user knowledge in practice. To further explore such challenges, a co-production study was conducted by a team of researchers and representatives from user organizations in Sweden. The aim of the study was to explore the barriers and facilitators to the legitimacy of user knowledge, as a central factor in sustainably implementing user influence in mental health practice. A series of workshops, with representatives of mental health services and user organizations were conducted by the research team to explore these issues. The analysis built on the theoretical framework of epistemic injustice, and the underlying aspects, testimonial, hermeneutic and participation-based injustice, were utilized as a framework for a deductive analysis. Results suggest that this is a useful model for exploring the complex dynamics related to the legitimacy of user knowledge in mental health systems. The analysis suggests that the legitimacy of user knowledge is related to the representativeness of the knowledge base, the systematic formulation of this knowledge in applicable methods, access to resources and positions within the mental health system and participation in the process of integrating this knowledge-base in mental health contexts. Legitimizing user knowledge in practice additionally challenges mental health systems to support readiness for change in working environments and to address the power and role issues that these changes involve.

Sustained attention induces altered effective connectivity of the ascending thalamo-cortical relay in obsessive-compulsive disorder.

Abnormal function of the thalamo-cortical relay is considered a hallmark of obsessive-compulsive disorder (OCD) and aberrant network interactions may underpin many of the clinical and cognitive symptoms that characterize the disorder. Several statistical approaches have been applied to in vivo fMRI data to support the general loss of thalamo-cortical connectivity in OCD. However, (a) few studies have assessed the contextual constraints under which abnormal network interactions arise or (b) have used methods of effective connectivity to understand abnormal network interactions. Effective connectivity is a particularly valuable method as it describes the putative causal influences that brain regions exert over each other, as opposed to the largely statistical consistencies captured in functional connectivity techniques. Here, using dynamic causal modeling (DCM), we evaluated how attention demand induced inter-group differences (HC ≠ OCD) in effective connectivity within a motivated thalamo-cortical network. Of interest was whether these effects were observed on the ascending thalamo-cortical relay, essential for the sensory innervation of the cortex. fMRI time series data from sixty-two participants (OCD, 30; HC, 32) collected using an established sustained attention task were submitted to a space of 162 competing models. Across the space, models distinguished between competing hypotheses of thalamo-cortical interactions. Bayesian model selection (BMS) identified marginally differing likely generative model architectures in OCD and HC groups. Bayesian model averaging (BMA), was used to weight connectivity parameter estimates across all models, with each parameter weighted by each model's posterior probability, thus providing more stable estimates of effective connectivity. Inferential statistical analyses of estimated parameters revealed two principal results: (1) Significantly reduced intrinsic connectivity of the V1 → SPC pathway in OCD, suggested connective weakness in the early constituents of the dorsal visual pathway; (2) More pertinent with the discovery possibilities afforded by DCM, sustained attention in OCD patients induced significantly reduced contextual modulation of the ascending relay from the thalamus to the prefrontal cortex. These results form an important complement to our understanding of the contextual bases of thalamo-cortical network deficits in OCD, emphasizing vulnerability of the ascending relay.

An ultra-brief screening scale for pediatric obsessive-compulsive disorder: The OCI-CV-5.

BACKGROUND: Obsessive-compulsive disorder (OCD) is an often disabling and chronic condition that is normally assessed using diagnostic interviews or lengthy self-report questionnaires. This makes routine screening in general health settings impractical, and as a result OCD is often under-(or mis-)recognized. The present study reports on the development of an ultra-brief version of the Obsessive-Compulsive Inventory-Child Version (OCI-CV) which may be administered routinely as a screener for pediatric OCD. METHOD: A total of 489 youth diagnosed with OCD, 259 non-clinical controls, and 299 youth with other disorders completed the OCI-CV and other indices of psychopathology. Using item analyses, we extracted five items and examined the measure's factor structure, sensitivity and specificity, and convergent and discriminant validity. RESULTS: We extracted five items that assess different dimensions of OCD (washing, checking, ordering, obsessing, neutralizing/counting), termed the OCI-CV-5. Results revealed that the measure possesses good to excellent psychometric properties, and a cutoff off (≥2) yielded optimal sensitivity and specificity. LIMITATIONS: Participants were predominantly White. In addition, more research is needed to examine the OCI-CV-5's test-retest reliability and sensitivity to treatment. CONCLUSIONS: The OCI-CV-5 shows promise as an ultra-brief self-report screener for identifying OCD in youth when in-depth assessment is unfeasible.

40-years of Lake Urmia restoration research: Review, synthesis and next steps.

Public concern over environmental issues such as ecosystem degradation is high. However, restoring coupled human-natural systems requires integration across many science, technology, engineering, management, and governance topics that are presently fragmented. Here, we synthesized 544 peer-reviewed articles published through September 2020 on the desiccation and nascent recovery of Lake Urmia in northwest Iran. We answered nine questions of scientific and popular interest about causes, impacts, stabilization, recovery, and next steps. We find: (1) Expansion of irrigated agriculture, dam construction, and mismanagement impacted the lake more than temperature increases and precipitation decreases. (2) Aerosols from Lake Urmia's exposed lakebed are negatively impacting human health. (3) Researchers disagree on how a new causeway breach will impact salinity, evaporation, and ecosystems in the lake's north and south arms. (4) Most researchers tried to restore to a single, uniform, government specified lake level of 1274.1 m intended to recover Artemia. (5) The Iranian government motivated and funded a large and growing body of lake research. (6) Ecological and limnological studies mostly focused on salinity, Artemia, and Flamingos. (7) Few studies shared data, and only three studies reported engagement with stakeholders or managers. (8) Researchers focused on an integration pathway of climate downscaling, reservoirs, agricultural water releases, and lake level. (9) Numerous suggestions to improve farmer livelihoods and governance require implementation. We see an overarching next step for lake recovery is to couple human and natural system components. Examples include: (a) describe and monitor the system food webs, hydrologic, and human components; (b) adapt management to monitored conditions such as lake level, lake evaporation, lake salinity, and migratory bird populations; (c) improve livelihoods for poor, chronically stressed farmers beyond agriculture; (d) manage for diverse ecosystem services and lake levels; (e) engage all segments of society; (f) integrate across restoration topics while building capacity to share data, models, and code; and (g) cultivate longer-term two-way exchanges and public support. These restoration steps apply in different degrees to other Iranian ecosystems and lakes worldwide.

The OCI-CV-R: A Revision of the Obsessive-Compulsive Inventory - Child Version.

BACKGROUND: The Obsessive-Compulsive Inventory-Children's Version (OCI-CV) was developed to assess obsessive-compulsive symptoms in youth. Recent changes in the Diagnostic and Statistical Manual (DSM-5) exclude hoarding from inclusion in the diagnosis of obsessive-compulsive disorder (OCD). Accordingly, the present study examined the reliability, validity, factorial structure, and diagnostic sensitivity of a revised version of the scale - the OCI-CV-R- that excludes items assessing hoarding. METHODS: Participant were 1047 youth, including 489 meeting DSM criteria for primary OCD, 298 clinical controls, and 260 nonclinical controls, who completed the OCI-CV and measures of obsessive-compulsive symptom severity, depression, and anxiety at various treatment and research centers. RESULTS: Findings support a five-factor structure (doubting/checking, obsessing, washing, ordering, and neutralizing), with a higher order factor. Factorial invariance was found for older (12-17 years) and younger (7-11 years) children. Internal consistency of the OCI-CV-R was acceptable, and discriminant and convergent validity were adequate and akin to that of its progenitor. Diagnostic sensitivity and specificity were found for a total score of 8 and higher. CONCLUSION: It is recommended that the OCI-CV-R replace the former version, and that this measure serve as part of a comprehensive clinical assessment of youth with OCD. Recommendations for further research with ethnically and racially diverse samples, as well as the need to establish benchmark scores are discussed.

Radiation Oncology Education Collaborative Study Group Annual Spring Symposium: Initial Impact and Feedback.

The Radiation Oncology Education Collaborative Study Group (ROECSG) is an international collaborative network of radiation oncology (RO) professionals with the goal of improving RO education. This report summarizes the first two ROECSG annual symposia including an overview of presentations and analysis of participant feedback. One-day symposia were held in June 2018 and May 2019. Programs included oral and poster presentations, RO education leadership perspectives, and keynote addresses. Post-symposia surveys were collected. Research presentations were recorded and made available online. The 2018 symposium was had 36 attendees from 25 institutions in three countries. The 2019 symposium had 76 individuals from 41 institutions in five countries. Attendees represented diverse backgrounds including attending physicians (46%), residents (13%), medical students (14%), physicists (2%), nurses (1%), and program coordinators (1%). Fifty-five oral presentations were given with 53 released online. Ninety percent of attendees rated the symposium as improving their knowledge of RO educational scholarship, 98% felt the symposium provided the opportunity to receive feedback on RO education scholarship, and 99% felt that the symposium fostered the development of collaborative RO education projects. ROECSG was rated higher than professional organizations in fostering educational scholarship (p<0.001). All attendees felt that the symposium produced new RO education scholarship ideas and provided unique networking opportunities. The first two ROECSG symposia drew a diverse population of attendees and provided unique opportunities for presentation of RO education scholarship. Future ROECSG symposia will be designed to enhance opportunities to present RO education scholarship and to facilitate networking.

Interaction between Different Implant Surfaces and Liquid Fibrinogen: A Pilot In Vitro Experiment.

BACKGROUND: Platelet concentrates like leucocyte- and platelet-rich fibrin (L-PRF) have been widely evaluated in different oral surgical procedures to promote the healing process. However, liquid L-PRF products such as liquid fibrinogen have been poorly explored, especially in the biomimetic functionalization of dental implants. The aim of this in vitro study is to evaluate the interaction between 5 different dental implant surfaces and liquid fibrinogen. METHODS: Five commercially available dental implants with different surfaces (Osseospeed™, TiUnite™, SLActive®, Ossean®, and Plenum®) were immersed for 60 minutes in liquid fibrinogen obtained from healthy donors. After this period, the implants were removed and fixed for scanning electron microscopy (SEM). RESULTS: All dental implants were covered by a fibrin mesh. However, noticeable noncontact areas were observed for the Osseospeed™, TiUnite™, and SLActive® surfaces. On the other hand, Ossean® and Plenum® surfaces showed a dense and uniform layer of fibrin covering almost the entire implant surface. The Osseospeed™, TiUnite™, and SLActive® surfaces presented with lower blood cell numbers inside the fibrin mesh compared with the others. Moreover, at higher magnification, thicker fibrin fibers were observed in contact with Ossean® and Plenum® surfaces. The Plenum ®surface showed the thickest fibers which also inserted and interconnect to the microroughness. CONCLUSION: The initial contact between an implant surface and the fibrin network differs significantly among different implant brands. Further studies are necessary to explore the clinical impact of these observations in the osseointegration process of dental implants.