Artificial Intelligence for Mohs and Dermatologic Surgery: A Systematic Review and Meta-Analysis.

BACKGROUND: Over the past decade, several studies have shown that potential of artificial intelligence (AI) in dermatology. However, there has yet to be a systematic review evaluating the usage of AI specifically within the field of Mohs micrographic surgery (MMS). OBJECTIVE: In this review, we aimed to comprehensively evaluate the current state, efficacy, and future implications of AI when applied to MMS for the treatment of nonmelanoma skin cancers (NMSC). MATERIALS AND METHODS: A systematic review and meta-analysis was conducted following PRISMA guidelines across several databases, including PubMed/MEDLINE, Embase, and Cochrane libraries. A predefined protocol was registered in PROSPERO, with literature search involving specific keywords related to AI and Mohs surgery for NMSC. RESULTS: From 23 studies evaluated, our results find that AI shows promise as a prediction tool for precisely identifying NMSC in tissue sections during MMS. Furthermore, high AUC and concordance values were also found across the various usages of AI in MMS, including margin control, surgical recommendations, similarity metrics, and in the prediction of stage and construction complexity. CONCLUSION: The findings of this review suggest promising potential for AI to enhance the accuracy and efficiency of Mohs surgery, particularly for NMSC.

Assessing the Feasibility and Effectiveness of Screening for Indoor Tanning in the Primary Care Setting: A Report of Preliminary Findings.

Introduction: Indoor tanning is a major modifiable risk factor in the development of both melanoma and nonmelanoma skin cancers. Investigation of behavior-altering interventions is an area of active research. As with other preventive measures, screening of high-risk populations can be an important aspect of a multimodality public health intervention. This study sought to further the limited understanding of indoor tanning screening practices in the primary care setting. Methods: Physicians practicing within the scope of primary care in the northeast were surveyed in 2022 on practice patterns around the frequency of indoor tanning screening, barriers encountered with implementing screening, and actions taken with a positive screen. Research methodology adhered to the Joanna Briggs Institute critical appraisal checklist. Results: Of 26 primary care physicians, only 7.7% routinely screened for indoor tanning. Barriers identified included time limitations (76.9%) and prioritization of other health concerns (96.2%). All primary care physicians (100%) reacted to reports of indoor tanning with an intervention, most commonly counseling on the risks of indoor tanning (92.6%). Conclusions: This data suggest that screening for indoor tanning use could be improved. The authors recommend the incorporation of a standardized screening question regarding indoor tanning in intake forms.

Patterns of physical activity of people with COPD during participation in a pulmonary rehabilitation program.

INTRODUCTION: Very few studies have examined patterns of physical activity (PA) during a pulmonary rehabilitation (PR) program in people with COPD. AIMS: To compare the patterns of PA in: 1) the week before commencing PR (pre-PR) with a week during PR (PR week); 2) PR days and non-PR days during a PR week; 3) pre-PR and the week following PR completion (post-PR). METHODS: This was a multicenter, prospective cohort study. Participants attended twice weekly supervised PR for 8-12 weeks. Daily step count (primary outcome), time in light activities, time in moderate to vigorous PA (MVPA), total sedentary time and sit-to-stand (STS) transitions were measured using a thigh worn accelerometer for seven days, at each assessment time point: pre-PR, PR week and post-PR. RESULTS: 29 participants, mean age (SD) 69years(7), FEV1 53%pred(16). The PR week compared to pre-PR, showed higher daily: step count (mean difference (95%CI)), 941steps(388-1494); and MVPA, 11mins(6-15), with no difference in: time in light activities, -1min(-6-5); total sedentary time, 7mins(-21-36); or STS transitions, 0(-5-6). PR days compared to non-PR days showed higher: step count, 2810steps(1706-3913); time in light activities 11mins(1-20); time in MVPA, 27mins(17-35) and STS transitions, 8(4-12), with no difference in total sedentary time: -33mins(-80-15). There were no differences in any PA measures post-PR compared to pre-PR (p < 0.05). CONCLUSION: Daily step count and time spent in MVPA increased significantly during the PR week, solely due to increased PA on days participants attended PR.

Evaluating the accuracy of automated processing of child and adult language production in preschool classrooms.

Young children's language and social development is influenced by the linguistic environment of their classrooms, including their interactions with teachers and peers. Measurement of the classroom linguistic environment typically relies on observational methods, often providing limited 'snapshots' of children's interactions, from which broad generalizations are made. Recent technological advances, including artificial intelligence, provide opportunities to capture children's interactions using continuous recordings representing much longer durations of time. The goal of the present study was to evaluate the accuracy of the Interaction Detection in Early Childhood Settings (IDEAS) system on 13 automated indices of language output using recordings collected from 19 children and three teachers over two weeks in an urban preschool classroom. The accuracy of language outputs processed via IDEAS were compared to ground truth via linear correlations and median absolute relative error. Findings indicate high correlations between IDEAS and ground truth data on measures of teacher and child speech, and relatively low error rates on the majority of IDEAS language output measures. Study findings indicate that IDEAS may provide a useful measurement tool for advancing knowledge about children's classroom experiences and their role in shaping development.

Association of post-COVID phenotypic manifestations with new-onset psychiatric disease.

Acute COVID-19 infection can be followed by diverse clinical manifestations referred to as Post Acute Sequelae of SARS-CoV2 Infection (PASC). Studies have shown an increased risk of being diagnosed with new-onset psychiatric disease following a diagnosis of acute COVID-19. However, it was unclear whether non-psychiatric PASC-associated manifestations (PASC-AMs) are associated with an increased risk of new-onset psychiatric disease following COVID-19. A retrospective electronic health record (EHR) cohort study of 2,391,006 individuals with acute COVID-19 was performed to evaluate whether non-psychiatric PASC-AMs are associated with new-onset psychiatric disease. Data were obtained from the National COVID Cohort Collaborative (N3C), which has EHR data from 76 clinical organizations. EHR codes were mapped to 151 non-psychiatric PASC-AMs recorded 28-120 days following SARS-CoV-2 diagnosis and before diagnosis of new-onset psychiatric disease. Association of newly diagnosed psychiatric disease with age, sex, race, pre-existing comorbidities, and PASC-AMs in seven categories was assessed by logistic regression. There were significant associations between a diagnosis of any psychiatric disease and five categories of PASC-AMs with odds ratios highest for neurological, cardiovascular, and constitutional PASC-AMs with odds ratios of 1.31, 1.29, and 1.23 respectively. Secondary analysis revealed that the proportions of 50 individual clinical features significantly differed between patients diagnosed with different psychiatric diseases. Our study provides evidence for association between non-psychiatric PASC-AMs and the incidence of newly diagnosed psychiatric disease. Significant associations were found for features related to multiple organ systems. This information could prove useful in understanding risk stratification for new-onset psychiatric disease following COVID-19. Prospective studies are needed to corroborate these findings.

Converting OMOP CDM to phenopackets: A model alignment and patient data representation evaluation.

OBJECTIVE: This study aims to promote interoperability in precision medicine and translational research by aligning the Observational Medical Outcomes Partnership (OMOP) and Phenopackets data models. Phenopackets is an expert knowledge-driven schema designed to facilitate the storage and exchange of multimodal patient data, and support downstream analysis. The first goal of this paper is to explore model alignment by characterizing the common data models using a newly developed data transformation process and evaluation method. Second, using OMOP normalized clinical data, we evaluate the mapping of real-world patient data to Phenopackets. We evaluate the suitability of Phenopackets as a patient data representation for real-world clinical cases. METHODS: We identified mappings between OMOP and Phenopackets and applied them to a real patient dataset to assess the transformation's success. We analyzed gaps between the models and identified key considerations for transforming data between them. Further, to improve ambiguous alignment, we incorporated Unified Medical Language System (UMLS) semantic type-based filtering to direct individual concepts to their most appropriate domain and conducted a domain-expert evaluation of the mapping's clinical utility. RESULTS: The OMOP to Phenopacket transformation pipeline was executed for 1,000 Alzheimer's disease patients and successfully mapped all required entities. However, due to missing values in OMOP for required Phenopacket attributes, 10.2 % of records were lost. The use of UMLS-semantic type filtering for ambiguous alignment of individual concepts resulted in 96 % agreement with clinical thinking, increased from 68 % when mapping exclusively by domain correspondence. CONCLUSION: This study presents a pipeline to transform data from OMOP to Phenopackets. We identified considerations for the transformation to ensure data quality, handling restrictions for successful Phenopacket validation and discrepant data formats. We identified unmappable Phenopacket attributes that focus on specialty use cases, such as genomics or oncology, which OMOP does not currently support. We introduce UMLS semantic type filtering to resolve ambiguous alignment to Phenopacket entities to be most appropriate for real-world interpretation. We provide a systematic approach to align OMOP and Phenopackets schemas. Our work facilitates future use of Phenopackets in clinical applications by addressing key barriers to interoperability when deriving a Phenopacket from real-world patient data.

COVID-19 Vaccine Information and Infertility Posts on X: Insights on a Misinformation Pandemic.

OBJECTIVE: This study aimed to evaluate misinformation surrounding infertility and the COVID-19 vaccine on X (formerly known as Twitter) by analyzing the prevalence and content of this misinformation across a sample of posts on X. METHODS: This study is a retrospective review of posts on X (formerly known as tweets) from the COVID-19-TweetIDs dataset from July 2021 and November 2021. Included posts were from crucial time points in the COVID-19 vaccine discourse and contained at least one word related to COVID-19 vaccination and fertility. Posts were analyzed and categorized based on factuality, common words, and hashtags. Descriptive statistics on total followers, account verification status, and engagement were obtained. Differences between posts on X classified as factual and misinformation were examined using analysis of variance or χ2 tests. Sentiment analysis determined if post content was generally positive, neutral, or negative. RESULTS: A total of 17,418 relevant posts on X were reviewed: 11,436 from timeframe 1 (July 2021) and 5982 from timeframe 2 (December 2021). Misinformation posts rose from 29.9% in July 2021 to 45.1% in November 2021. In both timeframes, accounts sharing factual information had more followers (p < 0.001), and verified users were more likely to share accurate posts (p ≤ 0.001). Factual and misinformation posts had similar engagement. Sentiment analysis identified that real posts were more positive and misinformation posts were more negative (p < 0.001). CONCLUSIONS AND RELEVANCE: Misinformation about the COVID-19 vaccine and fertility is highly prevalent on X and threatens vaccine uptake in patients desiring future fertility. Accounts sharing factual information were likely to have more followers and be verified; therefore, verifying more physicians sharing accurate information is critical.

Astrocytic Slc4a4 regulates blood-brain barrier integrity in healthy and stroke brains via a CCL2-CCR2 pathway and NO dysregulation.

Astrocytes play vital roles in blood-brain barrier (BBB) maintenance, yet how they support BBB integrity under normal or pathological conditions remains poorly defined. Recent evidence suggests that ion homeostasis is a cellular mechanism important for BBB integrity. In the current study, we investigated the function of an astrocyte-specific pH regulator, Slc4a4, in BBB maintenance and repair. We show that astrocytic Slc4a4 is required for normal astrocyte morphological complexity and BBB function. Multi-omics analyses identified increased astrocytic secretion of CCL2 coupled with dysregulated arginine-NO metabolism after Slc4a4 deletion. Using a model of ischemic stroke, we found that loss of Slc4a4 exacerbates BBB disruption, which was rescued by pharmacological or genetic inhibition of the CCL2-CCR2 pathway in vivo. Together, our study identifies the astrocytic Slc4a4-CCL2 and endothelial CCR2 axis as a mechanism controlling BBB integrity and repair, while providing insights for a therapeutic approach against BBB-related CNS disorders.

Effect of Peanut Butter Intake on Sleep Health in Firefighters: A Randomized Controlled Trial.

Sleep is often impaired in firefighters due to the psychologically and physiologically intense nature of their work and working shift schedules. Peanut butter is affordable and a substantial source of monounsaturated fatty acids, which may aid sleep health. Thus, this study sought to determine if a daily serving of peanut butter consumed before bedtime for seven weeks altered sleep quality and quantity among full-time firefighters. Forty firefighters (peanut butter group = 20; control group = 20) participated in this eight-week randomized controlled trial. All participants completed a subjective questionnaire on mood, focus, and alertness twice daily and wore an Actigraph wristwatch to measure sleep variables, including latency, efficiency, time in bed, time asleep, wake after sleep onset, number of awakenings, and time spent awake. After a baseline week, the peanut butter group consumed two tablespoons of peanut butter two hours prior to bedtime for seven weeks. Compared to the control group, the peanut butter group did not demonstrate significant changes (p > 0.05) in sleep measures or subjective feelings of mood, focus, or alertness after consuming peanut butter for seven weeks. Therefore, peanut butter as a source of peanuts did not alter sleep quality or quantity in this group of firefighters.

Investigating disparities in smoking cessation treatment for veterans with multiple sclerosis: A national analysis.

BACKGROUND AND AIMS: Smoking is a risk factor for multiple sclerosis (MS) development, symptom burden, decreased medication efficacy, and increased disease-related mortality. Veterans with MS (VwMS) smoke at critically high rates; however, treatment rates and possible disparities are unknown. To promote equitable treatment, we aim to investigate smoking cessation prescription practices for VwMS across social determinant factors. METHODS: We extracted data from the national Veterans Health Administration electronic health records between October 1, 2017, and September 30, 2018. To derive marginal estimates of the association of MS with receipt of smoking-cessation pharmacotherapy, we used propensity score matching through the extreme gradient boosting machine learning model. VwMS who smoke were matched with veterans without MS who smoke on factors including age, race, depression, and healthcare visits. To assess the marginal association of MS with different cessation treatments, we used logistic regression and conducted stratified analyses by sex, race, and ethnicity. RESULTS: The matched sample achieved a good balance across most covariates, compared to the pre-match sample. VwMS (n = 3320) had decreased odds of receiving prescriptions for nicotine patches ([Odds Ratio]OR = 0.86, p < .01), non-patch nicotine replacement therapy (NRT; OR = 0.81, p < .001), and standard practice dual NRT (OR = 0.77, p < .01), compared to matches without MS (n = 13,280). Men with MS had lower odds of receiving prescriptions for nicotine patches (OR = 0.88, p = .05), non-patch NRT (OR = 0.77, p < .001), and dual NRT (OR = 0.72, p < .001). Similarly, Black VwMS had lower odds of receiving prescriptions for patches (OR = 0.62, p < .001), non-patch NRT (OR = 0.75, p < .05), and dual NRT (OR = 0.52, p < .01). The odds of receiving prescriptions for bupropion or varenicline did not differ between VwMS and matches without MS. CONCLUSION: VwMS received significantly less smoking cessation treatment, compared to matched controls without MS, showing a critical gap in health services as VwMS are not receiving dual NRT as the standard of care. Prescription rates were especially lower for male and Black VwMS, suggesting that under-represented demographic groups outside of the white female category, most often considered as the "traditional MS" group, could be under-treated regarding smoking cessation support. This foundational work will help inform future work to promote equitable treatment and implementation of cessation interventions for people living with MS.

An open source knowledge graph ecosystem for the life sciences.

Translational research requires data at multiple scales of biological organization. Advancements in sequencing and multi-omics technologies have increased the availability of these data, but researchers face significant integration challenges. Knowledge graphs (KGs) are used to model complex phenomena, and methods exist to construct them automatically. However, tackling complex biomedical integration problems requires flexibility in the way knowledge is modeled. Moreover, existing KG construction methods provide robust tooling at the cost of fixed or limited choices among knowledge representation models. PheKnowLator (Phenotype Knowledge Translator) is a semantic ecosystem for automating the FAIR (Findable, Accessible, Interoperable, and Reusable) construction of ontologically grounded KGs with fully customizable knowledge representation. The ecosystem includes KG construction resources (e.g., data preparation APIs), analysis tools (e.g., SPARQL endpoint resources and abstraction algorithms), and benchmarks (e.g., prebuilt KGs). We evaluated the ecosystem by systematically comparing it to existing open-source KG construction methods and by analyzing its computational performance when used to construct 12 different large-scale KGs. With flexible knowledge representation, PheKnowLator enables fully customizable KGs without compromising performance or usability.

Propensity weighted analysis of chemical venous thromboembolism prophylaxis agents in isolated severe traumatic brain injury: An EAST sponsored multicenter study.

BACKGROUND: In patients with severe traumatic brain injury (TBI), clinicians must balance preventing venous thromboembolism (VTE) with the risk of intracranial hemorrhagic expansion (ICHE). We hypothesized that low molecular weight heparin (LMWH) would not increase risk of ICHE or VTE as compared to unfractionated heparin (UH) in patients with severe TBI. METHODS: Patients ≥ 18 years of age with isolated severe TBI (AIS ≥ 3), admitted to 24 level I and II trauma centers between January 1, 2014 to December 31, 2020 and who received subcutaneous UH and LMWH injections for chemical venous thromboembolism prophylaxis (VTEP) were included. Primary outcomes were VTE and ICHE after VTEP initiation. Secondary outcomes were mortality and neurosurgical interventions. Entropy balancing (EBAL) weighted competing risk or logistic regression models were estimated for all outcomes with chemical VTEP agent as the predictor of interest. RESULTS: 984 patients received chemical VTEP, 482 UH and 502 LMWH. Patients on LMWH more often had pre-existing conditions such as liver disease (UH vs LMWH 1.7 % vs. 4.4 %, p = 0.01), and coagulopathy (UH vs LMWH 0.4 % vs. 4.2 %, p < 0.001). There were no differences in VTE or ICHE after VTEP initiation. There were no differences in neurosurgical interventions performed. There were a total of 29 VTE events (3 %) in the cohort who received VTEP. A Cox proportional hazards model with a random effect for facility demonstrated no statistically significant differences in time to VTE across the two agents (p = 0.44). The LMWH group had a 43 % lower risk of overall ICHE compared to the UH group (HR = 0.57: 95 % CI = 0.32-1.03, p = 0.062), however was not statistically significant. CONCLUSION: In this multi-center analysis, patients who received LMWH had a decreased risk of ICHE, with no differences in VTE, ICHE after VTEP initiation and neurosurgical interventions compared to those who received UH. There were no safety concerns when using LMWH compared to UH. LEVEL OF EVIDENCE: Level III, Therapeutic Care Management.

The Cyclical Battle of Insomnia and Mental Health Impairment in Firefighters: A Narrative Review.

The occupational requirements of full-time non-administrative firefighters include shift-work schedules and chronic exposure to alerting emergency alarms, hazardous working conditions, and psychologically traumatic events that they must attend and respond to. These compiling and enduring aspects of the career increase the firefighter's risk for insomnia and mental health conditions compared to the general population. Poor sleep quality and mental health impairments are known to coincide with and contribute to the symptom severity of one another. Thus, it is important to determine approaches that may improve sleep and/or mental health specifically for firefighters, as their occupation varies in many aspects from any other occupation. This review will discuss symptoms of insomnia and mental health conditions such as PTSD, anxiety, depression, substance abuse, and suicide in firefighters. The influencing factors of sleep and mental health will be examined including anxiety sensitivity, emotional regulation, and distress tolerance. Current sleep and mental health interventions specific to full-time firefighters are limited in number; however, the existing experimental studies will be outlined. Lastly, this review will provide support for exploring exercise as a possible intervention that may benefit the sleep and mental health of this population.

Altered tongue muscle contractile properties coincide with altered swallow function in the adult Ts65Dn mouse model of down syndrome.

Purpose: Down syndrome (DS) is a developmental disability associated with difficulties in deglutition. The adult Ts65Dn mouse model of DS has been previously shown to have differences in measures of swallowing compared with euploid controls. However, the putative mechanisms of these differences in swallowing function are unclear. This study tested the hypothesis that the Ts65Dn genotype is associated with atypical measures of tongue muscle contractile properties, coinciding with atypical swallow function. Methods: Adult (5-month-old) Ts65Dn (n = 15 female, 14 male) and euploid sibling controls (n = 16 female, 14 male) were evaluated through videofluoroscopy swallow studies (VFSS) to quantify measures of swallowing performance including swallow rate and inter-swallow interval (ISI). After VFSS, retrusive tongue muscle contractile properties, including measures of muscle fatigue, were determined using bilateral hypoglossal nerve stimulation. Results: The Ts65Dn group had significantly slower swallow rates, significantly greater ISI times, significantly slower rates of tongue force development, and significantly greater levels of tongue muscle fatigue, with lower retrusive tongue forces than controls in fatigue conditions. Conclusion: Tongue muscle contractile properties are altered in adult Ts65Dn and coincide with altered swallow function.

Bridging the literacy gap for surgical consents: an AI-human expert collaborative approach.

Despite the importance of informed consent in healthcare, the readability and specificity of consent forms often impede patients' comprehension. This study investigates the use of GPT-4 to simplify surgical consent forms and introduces an AI-human expert collaborative approach to validate content appropriateness. Consent forms from multiple institutions were assessed for readability and simplified using GPT-4, with pre- and post-simplification readability metrics compared using nonparametric tests. Independent reviews by medical authors and a malpractice defense attorney were conducted. Finally, GPT-4's potential for generating de novo procedure-specific consent forms was assessed, with forms evaluated using a validated 8-item rubric and expert subspecialty surgeon review. Analysis of 15 academic medical centers' consent forms revealed significant reductions in average reading time, word rarity, and passive sentence frequency (all P < 0.05) following GPT-4-faciliated simplification. Readability improved from an average college freshman to an 8th-grade level (P = 0.004), matching the average American's reading level. Medical and legal sufficiency consistency was confirmed. GPT-4 generated procedure-specific consent forms for five varied surgical procedures at an average 6th-grade reading level. These forms received perfect scores on a standardized consent form rubric and withstood scrutiny upon expert subspeciality surgeon review. This study demonstrates the first AI-human expert collaboration to enhance surgical consent forms, significantly improving readability without sacrificing clinical detail. Our framework could be extended to other patient communication materials, emphasizing clear communication and mitigating disparities related to health literacy barriers.

BECLIN1 is essential for intestinal homeostasis involving autophagy-independent mechanisms through its function in endocytic trafficking.

Autophagy-related genes have been closely associated with intestinal homeostasis. BECLIN1 is a component of Class III phosphatidylinositol 3-kinase complexes that orchestrate autophagy initiation and endocytic trafficking. Here we show intestinal epithelium-specific BECLIN1 deletion in adult mice leads to rapid fatal enteritis with compromised gut barrier integrity, highlighting its intrinsic critical role in gut maintenance. BECLIN1-deficient intestinal epithelial cells exhibit extensive apoptosis, impaired autophagy, and stressed endoplasmic reticulum and mitochondria. Remaining absorptive enterocytes and secretory cells display morphological abnormalities. Deletion of the autophagy regulator, ATG7, fails to elicit similar effects, suggesting additional novel autophagy-independent functions of BECLIN1 distinct from ATG7. Indeed, organoids derived from BECLIN1 KO mice show E-CADHERIN mislocalisation associated with abnormalities in the endocytic trafficking pathway. This provides a mechanism linking endocytic trafficking mediated by BECLIN1 and loss of intestinal barrier integrity. Our findings establish an indispensable role of BECLIN1 in maintaining mammalian intestinal homeostasis and uncover its involvement in endocytic trafficking in this process. Hence, this study has important implications for our understanding of intestinal pathophysiology.

Differential role of fusiform gyrus coupling in depressive and anxiety symptoms during emotion perception.

Anxiety and depression co-occur; the neural substrates of shared and unique components of these symptoms are not understood. Given emotional alterations in internalizing disorders, we hypothesized that function of regions associated with emotion processing/regulation, including the anterior cingulate cortex (ACC), amygdala and fusiform gyrus (FG), would differentiate these symptoms. Forty-three adults with depression completed an emotional functional magnetic resonance imaging task and the Hamilton Depression and Anxiety Scales. We transformed these scales to examine two orthogonal components, one representing internalizing symptom severity and the other the type of internalizing symptoms (anxiety vs depression). We extracted blood oxygen level dependent signal from FG subregions, ACC, and amygdala and performed generalized psychophysiological interaction analyses to assess relationships between symptoms and brain function. Type of internalizing symptoms was associated with FG3-FG1 coupling (F = 8.14, P = 0.007). More coupling was associated with a higher concentration of depression, demonstrating that intra-fusiform coupling is differentially associated with internalizing symptom type (anxiety vs depression). We found an interaction between task condition and internalizing symptoms and dorsal (F = 4.51, P = 0.014) and rostral ACC activity (F = 4.27, P = 0.012). Post hoc comparisons revealed that less activity was associated with greater symptom severity during emotional regulation. Functional coupling differences during emotional processing are associated with depressive relative to anxiety symptoms and internalizing symptom severity. These findings could inform future treatments for depression.