The SocialVidStim: a video database of positive and negative social evaluation stimuli for use in social cognitive neuroscience paradigms.

This paper describes the SocialVidStim-a database of video stimuli available to the scientific community depicting positive and negative social evaluative and neutral statements. The SocialVidStim comprises 53 diverse individuals reflecting the demographic makeup of the USA, ranging from 9 to 41 years old, saying 20-60 positive and 20-60 negative social evaluative statements (e.g. 'You are a very trustworthy/annoying person'), and 20-60 neutral statements (e.g. 'The sky is blue'), totaling 5793 videos post-production. The SocialVidStim are designed for use in behavioral and functional magetic resonance imaging paradigms, across developmental stages, in diverse populations. This study describes stimuli development and reports initial validity and reliability data on a subset videos (N = 1890) depicting individuals aged 18-41 years. Raters perceive videos as expected: positive videos elicit positively valenced ratings, negative videos elicit negatively valenced ratings and neutral videos are rated as neutral. Test-retest reliability data demonstrate intraclass correlations in the good-to-excellent range for negative and positive videos and the moderate range for neutral videos. We also report small effects on valence and arousal that should be considered during stimuli selection, including match between rater and actor sex and actor believability. The SocialVidStim is a resource for researchers and we offer suggestions for using the SocialVidStim in future research.

Method for cycle detection in sparse, irregularly sampled, long-term neuro-behavioral timeseries: Basis pursuit denoising with polynomial detrending of long-term, inter-ictal epileptiform activity.

Numerous physiological processes are cyclical, but sampling these processes densely enough to perform frequency decomposition and subsequent analyses can be challenging. Mathematical approaches for decomposition and reconstruction of sparsely and irregularly sampled signals are well established but have been under-utilized in physiological applications. We developed a basis pursuit denoising with polynomial detrending (BPWP) model that recovers oscillations and trends from sparse and irregularly sampled timeseries. We validated this model on a unique dataset of long-term inter-ictal epileptiform discharge (IED) rates from human hippocampus recorded with a novel investigational device with continuous local field potential sensing. IED rates have well established circadian and multiday cycles related to sleep, wakefulness, and seizure clusters. Given sparse and irregular samples of IED rates from multi-month intracranial EEG recordings from ambulatory humans, we used BPWP to compute narrowband spectral power and polynomial trend coefficients and identify IED rate cycles in three subjects. In select cases, we propose that random and irregular sampling may be leveraged for frequency decomposition of physiological signals. Trial Registration: NCT03946618.

Clinicopathological and cellular senescence biomarkers in chronic stalled wounds.

BACKGROUND: Chronic wounds have been associated with an elevated burden of cellular senescence, a state of essentially irreversible cell cycle arrest, resistance to apoptosis, and a secretory phenotype. However, whether senescent cells contribute to wound chronicity in humans remains unclear. The objective of this article is to assess the role of clinicopathological characteristics and cellular senescence in the time-to-healing of chronic wounds. METHODS: A cohort of 79 patients with chronic wounds was evaluated in a single-center academic practice from February 1, 2005, to February 28, 2015, and followed for up to 36 months. Clinical characteristics and wound biopsies were obtained at baseline, and time-to-healing was assessed. Wound biopsies were analyzed histologically for pathological characteristics and molecularly for markers of cellular senescence. In addition, biopsy slides were stained for p16INK4a expression. RESULTS: No clinical or pathological characteristics were found to have significant associations with time-to-healing. A Cox proportional hazard ratio model revealed increased CDKN1A (p21CIP1/WAF1 ) expression to predict longer time-to-healing, and a model adjusted for gender and epidermal hyperplasia revealed increased CDKN1A expression and decreased PAPPA expression to predict longer time-to-healing. Increased p16INK4a staining was observed in diabetic wounds compared to non-diabetic wounds, and the same association was observed in the context of high dermal fibrosis. CONCLUSIONS: The findings of this pilot study suggest that senescent cells contribute to wound chronicity in humans, especially in diabetic wounds.

Mapping cellular senescence networks in human diabetic foot ulcers.

Cellular senescence, a cell fate defined by irreversible cell cycle arrest, has been observed to contribute to chronic age-related conditions including non-healing wounds, such as diabetic foot ulcers. However, the role of cellular senescence in the pathogenesis of diabetic foot ulcers remains unclear. To examine the contribution of senescent phenotypes to these chronic wounds, differential gene and network analyses were performed on publicly available bulk RNA sequencing of whole skin biopsies of wound edge diabetic foot ulcers and uninvolved diabetic foot skin. Wald tests with Benjamini-Hochberg correction were used to evaluate differential gene expression. Results showed that cellular senescence markers, CDKN1A, CXCL8, IGFBP2, IL1A, MMP10, SERPINE1, and TGFA, were upregulated, while TP53 was downregulated in diabetic foot ulcers compared to uninvolved diabetic foot skin. NetDecoder was then used to identify and compare context-specific protein-protein interaction networks using known cellular senescence markers as pathway sources. The diabetic foot ulcer protein-protein interaction network demonstrated significant perturbations with decreased inhibitory interactions and increased senescence markers compared to uninvolved diabetic foot skin. Indeed, TP53 (p53) and CDKN1A (p21) appeared to be key regulators in diabetic foot ulcer formation. These findings suggest that cellular senescence is an important mediator of diabetic foot ulcer pathogenesis.

Cellular Senescence in Human Skin Aging: Leveraging Senotherapeutics.

BACKGROUND: As the largest organ in the human body, the skin is continuously exposed to intrinsic and extrinsic stimuli that impact its functionality and morphology with aging. Skin aging entails dysregulation of skin cells and loss, fragmentation, or fragility of extracellular matrix fibers that are manifested macroscopically by wrinkling, laxity, and pigmentary abnormalities. Age-related skin changes are the focus of many surgical and nonsurgical treatments aimed at improving overall skin appearance and health. SUMMARY: As a hallmark of aging, cellular senescence, an essentially irreversible cell cycle arrest with apoptosis resistance and a secretory phenotype, manifests across skin layers by affecting epidermal and dermal cells. Knowledge of skin-specific senescent cells, such as melanocytes (epidermal aging) and fibroblasts (dermal aging), will promote our understanding of age-related skin changes and how to optimize patient outcomes in esthetic procedures. KEY MESSAGES: This review provides an overview of skin aging in the context of cellular senescence and discusses senolytic intervention strategies to selectively target skin senescent cells that contribute to premature skin aging.

Sex disparities in outcomes after carotid artery interventions: A systematic review.

This systematic review aimed to identify sex-specific outcomes in men and women after carotid endarterectomy (CEA) and carotid artery stenting (CAS), including transfemoral and transcarotid. A search of literature published from January 2000 through December 2022 was conducted using key terms attributed to carotid interventions on PubMed. Studies comparing outcome metrics post intervention (ie, myocardial infarction [MI], cerebral vascular accident [CVA] or stroke, and long-term mortality) among male and female patients were reviewed. Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed. Overall, all studies reported low rates of perioperative complications. Among the studies that did not stratify outcomes by the preoperative symptom status, there were no significant sex differences in rates of perioperative strokes or MIs. Two studies, however, noted a higher rate of 30-day mortality in male patients undergoing CEA than in female patients. Analysis of asymptomatic patients undergoing CEA revealed no difference in perioperative MIs (female: 0% to 1.8% v male: 0.4% to 4.3%), similar rates of CVAs (female: 0.8% to 5% v male: 0.8% to 4.9%), and no significant differences in the long-term mortality outcomes. Alternatively, symptomatic patients undergoing CEA reported a higher rate of CVAs in female patients vs. male patients (7.7% v 6.2%) and showed a higher rate of death in female patients (1% v 0.7%). Among studies that did not stratify outcome by symptomatology, there was no difference in the 30-day outcomes between sexes for patients undergoing CAS. Asymptomatic patients undergoing CAS demonstrated similar incident rates across perioperative MIs (female: 0% to 5.9% v male: 0.28% to 3.3%), CVAs (female: 0.5% to 4.1% v male: 0.4% to 6.2%), and long-term mortality outcomes (female: 0% to 1.75% v male: 0.2% to 1.5%). Symptomatic patients undergoing CAS similarly reported higher incidences of perioperative MIs (female: 0.3% to 7.1% v male: 0% to 5.5%), CVAs (female: 0% to 9.9% v male: 0% to 7.6%), and long-term mortality outcomes (female: 0.6% to 7.1% v male: 0.5% to 8.2%). Sex-specific differences in outcomes after major vascular procedures are well recognized. Our review suggests that symptomatic female patients have a higher incidence of neurologic and cardiac events after carotid interventions, but that asymptomatic patients do not.

Loss of RREB1 in pancreatic beta cells reduces cellular insulin content and affects endocrine cell gene expression.

AIMS/HYPOTHESIS: Genome-wide studies have uncovered multiple independent signals at the RREB1 locus associated with altered type 2 diabetes risk and related glycaemic traits. However, little is known about the function of the zinc finger transcription factor Ras-responsive element binding protein 1 (RREB1) in glucose homeostasis or how changes in its expression and/or function influence diabetes risk. METHODS: A zebrafish model lacking rreb1a and rreb1b was used to study the effect of RREB1 loss in vivo. Using transcriptomic and cellular phenotyping of a human beta cell model (EndoC-ßH1) and human induced pluripotent stem cell (hiPSC)-derived beta-like cells, we investigated how loss of RREB1 expression and activity affects pancreatic endocrine cell development and function. Ex vivo measurements of human islet function were performed in donor islets from carriers of RREB1 type 2 diabetes risk alleles. RESULTS: CRISPR/Cas9-mediated loss of rreb1a and rreb1b function in zebrafish supports an in vivo role for the transcription factor in beta cell mass, beta cell insulin expression and glucose levels. Loss of RREB1 also reduced insulin gene expression and cellular insulin content in EndoC-ßH1 cells and impaired insulin secretion under prolonged stimulation. Transcriptomic analysis of RREB1 knockdown and knockout EndoC-ßH1 cells supports RREB1 as a novel regulator of genes involved in insulin secretion. In vitro differentiation of RREB1KO/KO hiPSCs revealed dysregulation of pro-endocrine cell genes, including RFX family members, suggesting that RREB1 also regulates genes involved in endocrine cell development. Human donor islets from carriers of type 2 diabetes risk alleles in RREB1 have altered glucose-stimulated insulin secretion ex vivo, consistent with a role for RREB1 in regulating islet cell function. CONCLUSIONS/INTERPRETATION: Together, our results indicate that RREB1 regulates beta cell function by transcriptionally regulating the expression of genes involved in beta cell development and function.

A Knowledge-Based Discovery Approach Couples Artificial Neural Networks With Weight Engineering to Uncover Immune-Related Processes Underpinning Clinical Traits of Breast Cancer.

Immune-related processes are important in underpinning the properties of clinical traits such as prognosis and drug response in cancer. The possibility to extract knowledge learned by artificial neural networks (ANNs) from omics data to explain cancer clinical traits is a very attractive subject for novel discovery. Recent studies using a version of ANNs called autoencoders revealed their capability to store biologically meaningful information indicating that autoencoders can be utilized as knowledge discovery platforms aside from their initial assigned use for dimensionality reduction. Here, we devise an innovative weight engineering approach and ANN platform called artificial neural network encoder (ANNE) using an autoencoder and apply it to a breast cancer dataset to extract knowledge learned by the autoencoder model that explains clinical traits. Intriguingly, the extracted biological knowledge in the form of gene-gene associations from ANNE shows immune-related components such as chemokines, carbonic anhydrase, and iron metabolism that modulate immune-related processes and the tumor microenvironment play important roles in underpinning breast cancer clinical traits. Our work shows that biological "knowledge" learned by an ANN model is indeed encoded as weights throughout its neuronal connections, and it is possible to extract learned knowledge via a novel weight engineering approach to uncover important biological insights.

Prenatal Diagnosis and Fetal Outcome with Mosaic Genome-Wide Uniparental Disomy.

INTRODUCTION: While non-mosaic genome-wide paternal uniparental disomy (patUPD) is consistent with complete hydatidiform mole, the prenatal presentation of mosaic genome-wide patUPD is not well defined. This report adds another case to the small cohort of patients with the rare genetic disorder of mosaic genome-wide patUPD and provides one of the few examples of a prenatal presentation of this disease. We discuss ultrasound findings and prenatal analysis to review predominant genetic and clinical features associated with mosaic genome-wide patUPD. CASE PRESENTATION: A 30-year-old gravida 1 para 0 woman was referred at 10 weeks gestation due to an abnormal first-trimester ultrasound suggesting a partial molar pregnancy. The patient undertook genetic counseling and reviewed possible genetic etiologies and testing options. Karyotype analysis demonstrated a female fetus (46, XX). The BWS methylation pattern suggested the absence of maternally derived copies of IC1 (H19) and IC2 (LIT1) critical regions, which could result from patUPD of chromosome 11. CMA of cultured amniocytes was significant for arr(1-22,X)x2 hmz, consistent with genome-wide absence of heterozygosity (shown in Fig. 3). DISCUSSION/CONCLUSION: This case report is intended to add to the limited knowledge regarding prenatal diagnosis of mosaic genome-wide patUPD by highlighting the ultrasound findings, the genetic testing performed, and fetal outcome. The fetal karyotype was normal. CMA was consistent with a molecular diagnosis of GWUPD. Low-level mosaicism in our sample was inferred given the clinical presentation of a developing fetus. Methylation studies were consistent with a diagnosis of BWS. The diagnosis of genome-wide patUPD using CMA provides further knowledge of UPD and its functional relevance. In a prenatal setting, a CMA profile without heterozygosity is typical of a complete molar pregnancy. However, in the presence of a fetus, it likely represents mosaic GWUPD, a rare condition that is usually of paternal origin.

Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation.

We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 × 10-9), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background.

Endothelial GTPCH (GTP Cyclohydrolase 1) and Tetrahydrobiopterin Regulate Gestational Blood Pressure, Uteroplacental Remodeling, and Fetal Growth.

[Figure: see text].

The Trifecta of Single-Cell, Systems-Biology, and Machine-Learning Approaches.

Together, single-cell technologies and systems biology have been used to investigate previously unanswerable questions in biomedicine with unparalleled detail. Despite these advances, gaps in analytical capacity remain. Machine learning, which has revolutionized biomedical imaging analysis, drug discovery, and systems biology, is an ideal strategy to fill these gaps in single-cell studies. Machine learning additionally has proven to be remarkably synergistic with single-cell data because it remedies unique challenges while capitalizing on the positive aspects of single-cell data. In this review, we describe how systems-biology algorithms have layered machine learning with biological components to provide systems level analyses of single-cell omics data, thus elucidating complex biological mechanisms. Accordingly, we highlight the trifecta of single-cell, systems-biology, and machine-learning approaches and illustrate how this trifecta can significantly contribute to five key areas of scientific research: cell trajectory and identity, individualized medicine, pharmacology, spatial omics, and multi-omics. Given its success to date, the systems-biology, single-cell omics, and machine-learning trifecta has proven to be a potent combination that will further advance biomedical research.

Proteomic Signature of Dysfunctional Circulating Endothelial Colony-Forming Cells of Young Adults.

Background A subpopulation of endothelial progenitor cells called endothelial colony-forming cells (ECFCs) may offer a platform for cellular assessment in clinical studies because of their remarkable angiogenic and expansion potentials in vitro. Despite endothelial cell function being influenced by cardiovascular risk factors, no studies have yet provided a comprehensive proteomic profile to distinguish functional (ie, more angiogenic and expansive cells) versus dysfunctional circulating ECFCs of young adults. The aim of this study was to provide a detailed proteomic comparison between functional and dysfunctional ECFCs. Methods and Results Peripheral blood ECFCs were isolated from 11 subjects (45% men, aged 27±5 years) using Ficoll density gradient centrifugation. ECFCs expressed endothelial and progenitor surface markers and displayed cobblestone-patterned morphology with clonal and angiogenic capacities in vitro. ECFCs were deemed dysfunctional if <1 closed tube formed during the in vitro tube formation assay and proliferation rate was <20%. Hierarchical functional clustering revealed distinct ECFC proteomic signatures between functional and dysfunctional ECFCs with changes in cellular mechanisms involved in exocytosis, vesicle transport, extracellular matrix organization, cell metabolism, and apoptosis. Targeted antiangiogenic proteins in dysfunctional ECFCs included SPARC (secreted protein acidic and rich in cysteine), CD36 (cluster of differentiation 36), LUM (lumican), and PTX3 (pentraxin-related protein PYX3). Conclusions Circulating ECFCs with impaired angiogenesis and expansion capacities have a distinct proteomic profile and significant phenotype changes compared with highly angiogenic endothelial cells. Impaired angiogenesis in dysfunctional ECFCs may underlie the link between endothelial dysfunction and cardiovascular disease risks in young adults.

In-home vascular testing program during the COVID-19 pandemic.

This is a retrospective review of a pilot program to provide in home vascular testing to patients during the COVID-19 Pandemic. Results: Eighty-four patients underwent a total of 105 vascular imaging tests as part of the program. Two patients required hospitalization secondary to imaging findings. A description of the program, the results of the testing and patient experience with in-home vascular testing is discussed.

A Preliminary Study of Deep-Learning Algorithm for Analyzing Multiplex Immunofluorescence Biomarkers in Body Fluid Cytology Specimens.

INTRODUCTION: Multiplex biomarker analysis of cytological body fluid specimens is often used to assist cytologists in distiguishing metastatic cancer cells from reactive mesothelial cells. However, evaluating biomarker expression visually may be challenging, especially when the cells of interest are scant. Deep-learning algorithms (DLAs) may be able to assist cytologists in analyzing multiple biomarker expression at the single cell level in the multiplex fluorescence imaging (MFI) setting. This preliminary study was performed to test the feasibility of using DLAs to identify immunofluorescence-stained metastatic adenocarcinoma cells in body fluid cytology samples. METHODS: A DLA was developed to analyze MFI-stained cells in body fluid cytological samples. A total of 41 pleural fluid samples, comprising of 20 positives and 21 negatives, were retrospectively collected. Multiplex immunofluorescence labeling for MOC31, BerEP4, and calretinin, were performed on cell block sections, and results were analyzed by manual analysis (manual MFI) and DLA analysis (MFI-DLA) independently. RESULTS: All cases with positive original cytological diagnoses showed positive results either by manual MFI or MFI-DLA, but 2 of the 14 (14.3%) original cytologically negative cases had rare cells with positive MOC31 and/or BerEP4 staining in addition to calretinin. Manual MFI analysis and MFI-DLA showed 100% concordance. CONCLUSION: MFI combined with DLA provides a potential tool to assist in cytological diagnosis of metastatic malignancy in body fluid samples. Larger studies are warranted to test the clinical validity of the approach.

Magna ease bioprosthetic aortic valve: mid-term haemodynamic outcomes in 1126 patients.

OBJECTIVES: The Magna Ease aortic valve (Edwards Lifesciences, Irvine, CA) is a third-generation bioprosthetic valve developed as a modification of the well-studied Perimount and Magna valve designs. This study's objective is to evaluate a large, single-centre experience with Magna Ease aortic valve replacement (AVR) focusing on clinical outcomes and haemodynamic performance. METHODS: All patients undergoing AVR between 8/2010 and 10/2018 at our institution implanted with the Magna Ease valve were included except those undergoing ventricular assist device or congenital aortic surgery. Primary outcomes were overall survival and freedom from reoperation. Mean transprosthetic gradient (mTPG) and structural valve deterioration (SVD) served as secondary outcomes. RESULTS: Totally 1126 consecutive implantations of Magna Ease valves were included. Concomitant procedures were performed in 56.5% (n = 636). No severe patient-prosthesis mismatch (PPM) was present at implantation. Overall survival at 30 days, 1 year, 5 years and 9 years was 97.2%, 95.0%, 86.1% and 78.2%, respectively, with improved survival for isolated AVR. Total of 2.4% (n = 27) of patients required reoperation with 0.3% (n = 4) for SVD. Echocardiographic follow-up data revealed low mTPG throughout the study period. SVD occurred in 28.7% of patients at a mean of 3.9 years post implantation. CONCLUSIONS: Magna Ease AVR maintained low mean transprosthetic gradients throughout mid-term evaluation and was associated with excellent overall survival and freedom from reoperation at nine years post implantation.

Developing a Telemedicine Curriculum for a Family Medicine Residency.

INTRODUCTION: Telemedicine has rapidly become an essential part of primary care due to the COVID-19 pandemic. However, formal training in telemedicine during residency is lacking. We developed and implemented a telemedicine curriculum for a family medicine residency program and investigated its effect on resident confidence levels in practicing telemedicine. METHODS: We designed a process map of the telemedicine visit workflow at the residency clinic to identify key topics to cover in the curriculum. We created a live 50-minute didactic lecture on best practices in telemedicine, along with a quick-reference handout. We distributed pre- and postintervention surveys to current residents (N=24) to assess the effect of the educational intervention on their confidence in practicing telemedicine. RESULTS: Fourteen residents (58% response rate) completed all aspects of the study including both surveys and participation in the educational intervention. Confidence levels in conducting telemedicine visits increased in three of five domains: (1) virtual physical exam ( P=.04), (2) visit documentation (P=.03), and (3) virtually staffing with an attending ( P=.04). Resident interest in using telemedicine after residency also increased following the educational intervention. CONCLUSION: Telemedicine requires a unique skill set. Formal education on best practices improves resident confidence levels and interest in practicing telemedicine. Primary care residency programs should incorporate telemedicine training to adequately prepare their graduates for clinical practice.