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Two patients with dermatomyositis presented with violaceous lichenoid eruptions on the light exposed areas. Histology and direct immunofluorescence showed the typical features of lichen planus. The rash in dermatomyositis usually consists of a puplish-red heliotrope erythema on the face, erythematous changes on the hands and backs of the fingers with diffuse redness and shining of the nails folds (Rowell, 1979). A pathognomonic sign in dermatomyositis is the Gottron papule, a violaceous flate-topped lesion over the dorsal interphalangeal joints and occasionally a diffuse lichenoid euption occurs which may be mistaken for lichen planus (Braverman, 1983). However, there have been no previous reports of the histology and immunofluorescence finding in these patients. Two cases are reported showing clinically a violaceous lichenoid eruption of the dorsal aspect of both hands with the histology and direct immunofluorescence typical of lichen planus. The association of lichen planus and dermatomyositis is discussed. [ABSTRACT FROM AUTHOR]

Emotions are integral to human social interactions, with diverse responses elicited by various situational contexts. Particularly, the prevalence of negative emotional states has been correlated with negative outcomes for mental health, necessitating a comprehensive analysis of their occurrence and impact on individuals. In this paper, we introduce a novel dataset named DepressionEmo designed to detect 8 emotions associated with depression by 6037 examples of long Reddit user posts. This dataset was created through a majority vote over inputs by zero-shot classifications from pre-trained models and validating the quality by annotators and ChatGPT, exhibiting an acceptable level of inter-rater reliability between annotators. The correlation between emotions, and linguistic analysis are conducted on DepressionEmo. Besides, we provide several text classification methods classified into two groups: machine learning methods such as SVM, XGBoost, and LightGBM; and deep learning methods such as BERT, BART, GAN-BERT, and T5. Despite achieving the same F1 Macro score of 0.76 as BART, the pretrained BERT model, bert-base-uncased, stands out as the most efficient model in our experiments due to its lower number of parameters. Across all emotions, the highest F1 Macro value is achieved by suicide intent, indicating a certain value of our dataset in identifying emotions in individuals with depression symptoms through text analysis. The curated dataset is publicly available at: https://github.com/abuBakarSiddiqurRahman/DepressionEmo., Competing Interests: Declaration of competing interest The authors declare no conflict of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Consumers increasingly search for health information online but can become frustrated in their efforts. Here, public libraries can play an important role as trusted sources. A random sample of 200 U.S. public libraries was used to identify the availability of online consumer health information (CHI) and related characteristics. We found that 110 libraries provided online CHI. The average site provided 28 sources and required two clicks to reach the information. About a third of libraries collaborated by sharing sources or linking to existing content. Collaboration may provide a way to expand the availability and quality of online CHI on public library websites.

Objective: Recognizing that the interrelationships between chronic conditions that complicate rheumatoid arthritis (RA) are poorly understood, we aimed to identify patterns of multimorbidity and to define their prevalence in RA through machine learning., Methods: We constructed RA and age- and sex-matched (1:1) non-RA cohorts within a large commercial insurance database (MarketScan) and the Veterans Health Administration (VHA). Chronic conditions (n = 44) were identified from diagnosis codes from outpatient and inpatient encounters. Exploratory factor analysis was performed separately in both databases, stratified by RA diagnosis and sex, to identify multimorbidity patterns. The association of RA with different multimorbidity patterns was determined using conditional logistic regression., Results: We studied 226,850 patients in MarketScan (76% female) and 120,780 patients in the VHA (89% male). The primary multimorbidity patterns identified were characterized by the presence of cardiopulmonary, cardiometabolic, and mental health and chronic pain disorders. Multimorbidity patterns were similar between RA and non-RA patients, female and male patients, and patients in MarketScan and the VHA. RA patients had higher odds of each multimorbidity pattern (odds ratios [ORs] 1.17-2.96), with mental health and chronic pain disorders being the multimorbidity pattern most strongly associated with RA (ORs 2.07-2.96)., Conclusion: Cardiopulmonary, cardiometabolic, and mental health and chronic pain disorders represent predominant multimorbidity patterns, each of which is overrepresented in RA. The identification of multimorbidity patterns occurring more frequently in RA is an important first step in progressing toward a holistic approach to RA management and warrants assessment of their clinical and predictive utility., (© 2022 American College of Rheumatology. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.)

Emerging evidence suggests that AT-Rich Interaction Domain 5b (Arid5b) may play a role in energy metabolism in various tissues. To study the metabolic function of Arid5b in skeletal muscle, we generated skeletal muscle-specific Arid5b knockout (Arid5b MKO) mice. We found that Arid5b MKO skeletal muscles preferentially utilized fatty acids for energy generation with a corresponding increase in FABP4 expression. Interestingly, in Arid5b MKO mice, the adipose tissue weight decreased significantly. One possible mechanism for the decrease in adipose tissue weight could be the increase in phospho-HSL and HSL expression in white adipose tissue. While glucose uptake increased in an insulin-independent manner in Arid5b MKO skeletal muscle, glucose oxidation was reduced in conjunction with downregulation of the mitochondrial pyruvate carrier (MPC). We found that glucose was diverted into the pentose phosphate pathway as well as converted into lactate through glycolysis for export to the bloodstream, fueling the Cori cycle. Our data show that muscle-specific deletion of Arid5b leads to changes in fuel utilization in skeletal muscle that influences metabolism in other tissues. These results suggest that Arid5b regulates systemic metabolism by modulating fuel selection., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Murray, Ehsani, Najjar, Zhang and Itakura.)

Several observational studies have examined vitamin D pathway polymorphisms and their association with type 1 diabetes (T1D) susceptibility, with inconclusive results. We aimed to perform a systematic review and meta-analysis assessing associations between selected variants affecting 25-hydroxyvitamin D [25(OH)D] and T1D risk. We conducted a systematic search of Medline, Embase, Web of Science and OpenGWAS updated in April 2021. The following keywords "vitamin D" and/or "single nucleotide polymorphisms (SNPs)" and "T1D" were selected to identify relevant articles. Seven SNPs (or their proxies) in six genes were analysed: CYP2R1 rs10741657, CYP2R1 (low frequency) rs117913124, DHCR7/NADSYN1 rs12785878, GC rs3755967, CYP24A1 rs17216707, AMDHD1 rs10745742 and SEC23A rs8018720. Seven case-control and three cohort studies were eligible for quantitative synthesis ( n = 10). Meta-analysis results suggested no association with T1D (range of pooled ORs for all SNPs: 0.97-1.02; p > 0.01). Heterogeneity was found in DHCR7/NADSYN1 rs12785878 (I 2 : 64.8%, p = 0.02). Sensitivity analysis showed exclusion of any single study did not alter the overall pooled effect. No association with T1D was observed among a Caucasian subgroup. In conclusion, the evidence from the meta-analysis indicates a null association between selected variants affecting serum 25(OH)D concentrations and T1D.

Aim: The aim of this study was to evaluate current direct-to-consumer (DTC) genetic customers' ability to interpret and comprehend test results and to determine if honest brokers are needed., Method: One hundred and twenty-two customers of the DTC genetic testing company 23andMe were polled in an online survey. The subjects were asked about their personal test results and to interpret the results of two mock test cases (type 2 diabetes and multiple sclerosis), where results were translated into disease probability for an individual compared to the public., Results: When asked to evaluate the risk, 72.1% correctly assessed the first case and 77% were correct on the second case. Only 23.8% of those surveyed were able to interpret both cases correctly. x03C7;2 and logistic regression were used to interpret the results. Participants who took the time to read the DTC test-provided supplemental material were 3.93 times (p = 0.040) more likely to correctly interpret the test results than those who did not. The odds for correctly interpreting the test cases were 3.289 times (p = 0.011) higher for those who made more than USD 50,000 than those who made less. Survey results were compared to the Health Information National Trends Survey (HINTS) phase 4 cycle 3 data to evaluate national trends., Conclusions: Most of the subjects were able to correctly interpret the test cases, yet a majority did not share their results with a health-care professional. As the market for DTC genetic testing grows, test comprehension will become more critical. Involving more health professionals in this process may be necessary to ensure proper interpretations., (© 2016 S. Karger AG, Basel.)

Fertility rate is one of the most important global indexes. Past researchers found models which fit to age-specific fertility rates. For example, mixture probability density functions have been proposed for situations with bi-modal fertility patterns. This model is less useful for unimodal age-specific fertility rate patterns, so a model based on skew-symmetric (skew-normal) pdf was proposed by Mazzuco and Scarpa (2011) which was flexible for unimodal and bimodal fertility patterns. In this paper, we introduce skew-logistic probability density function as a better model: its residuals are less than those of the skew-normal model and it can more precisely estimate the parameters of the model.

Objective: To determine the relationship between anthropometric indices and the age of menarche in female students of Sabzevar, Iran., Methods: The cross-sectional study was conducted in Sabzevar, Iran, from April to September 2010, and involved girls of 11-18 years of age. The required sample size for analysing the relationship between menarche age and Body Mass Index was estimated to be 110 by correlation coefficient and Cox survival regression model and by using the NCSS_PASS software. The study had 130 students who were selected by multi-stage probability sampling. Relevant data were collected through a questionnaire as well as by measuring the anthropometric indices such as height, weight etc. Analysis of data was done by independent t-test, Pearson's correlation coefficient, Chi-square, Kaplan-Meier and Cox survival regression model using SPSS 15., Results: The mean menarche age was 12.5 +/- 1.4 years. Mean body mass index, weight and height of the menstruated girls were higher and significant than the corresponding figures of the non-menstruated girls. The correlation coefficient showed a significantly negative relation between body mass index and menarche age (r = -0.221, p = 0.025 (but correlation between menarche age and height or weight was not significant. Menarche occurrence rate was significantly higher in overweight girls than girls with normal weight. Menarche occurrence rate in girls with low weight was lower than those of normal weight., Conclusion: The menarche age and body mass index are significantly related; the higher body mass index, the lower was the menarche age, resulting in a higher menarche occurrence rate.