Notes

PhyliCS: the Python collection to explore scCNA info and also measure spatial cancer heterogeneity.
Short cervical length is a predictor of preterm birth. We evaluated if there were racial differences in variables associated with cervical length in pregnant Brazilian women.

Cervical length was determined by vaginal ultrasound in 414 women at 21weeks gestation. All women were seen at the same clinic and analyzed by the same investigators. Women found to have a short cervix (≤25mm) received vaginal progesterone throughout gestation. Composition of the vaginal microbiome was determined by analysis of the V1-V3 region of the gene coding for bacterial 16S ribosomal RNA. Demographic, clinical and outcome variables were determined by chart review. Subjects were 53.4% White, 37.2% mixed race and 9.4% Black.

Pregnancy, medical history and education level were similar in all groups. Mean cervical length was shorter in Black women (28.4mm) than in White (32.4mm) or mixed race (32.8mm) women (p≤0.016) as was the percentage of women with a short cervix (23.1, 12.2, 7.8% in Black, White, mixed race respectively) (p≤0.026). Mean cervical length increased with maternal age in White (p=0.001) and mixed race (p=0.045) women but not Black women. There were no differences in bacterial dominance in the vaginal microbiota between groups. Most women with a short cervix delivered at term.

We conclude that Black women in Brazil have a shorter cervical length than White or mixed race women independent of maternal age, pregnancy and demographic history or composition of the vaginal microbiome.
We conclude that Black women in Brazil have a shorter cervical length than White or mixed race women independent of maternal age, pregnancy and demographic history or composition of the vaginal microbiome.Background Associations between mental health and dermatology have generated a new branch of study called psychodermatology, which includes relevant conditions to the adolescent population. However, there is limited research focusing on this field and this specific population. Objective To estimate the prevalence of dermatological pathologies in the Colombian adolescent population and their possible associations with mental health conditions. Methods We performed a secondary analysis of the Colombian National Mental Health Survey results. A representative sample of the adolescent Colombian population answered questions regarding dermatological conditions and mental health disorders. We estimated the prevalence and evaluated associations using the chi squared independence test. Results Of 1753 adolescents, 8.3% (CI95%=[6.8-10.1]) had dermatitis or skin allergies and 4.5% (CI95%=[3.3-6.1]) acne. For dermatitis, we found associations with age, education, and family dysfunction (p-Values=0.024; less then 0.001; 0.046 respectively). Acne was associated with age, sex, educational level, the number of social groups involved in, alcohol consumption, psychoactive substances use and previous violent experiences (respective p-Values=0.007; 0.004; 0.005; 0.036; 0.002; 0.003; 0.044). Regarding mental health, dermatological conditions were associated with depression, affective disorders, suicide attempt and suicide ideation. Conclusion Our results are the first to describe the prevalence of these disorders in Colombia. This is an exploratory study; nonetheless, it is of great value since it is the first to describe these associations in adolescents in a middle-income country, which should be considered during clinical examinations. Further longitudinal studies evaluating possible causal relationship between psychiatric and dermatological conditions are fundamental to establish causal links.Iron is a highly important metal ion cofactor within the human body, necessary for haemoglobin synthesis, and required by a wide range of enzymes for essential metabolic processes. Iron deficiency and overload both pose significant health concerns and are relatively common world-wide health hazards. Effective measurement of total iron stores is a primary tool for both identifying abnormal iron levels and tracking changes in clinical settings. Population based data is also essential for tracking nutritional trends. This review article provides an overview of the strengths and limitations associated with current techniques for diagnosing iron status, which sets a basis to discuss the potential of a new serum marker - ferritin-bound iron - and the improvement it could offer to iron assessment.
Many factors involved in the onset and clinical course of the ongoing COVID-19 pandemic are still unknown. Although big data analytics and artificial intelligence are widely used in the realms of health and medicine, researchers are only beginning to use these tools to explore the clinical characteristics and predictive factors of patients with COVID-19.

Our primary objectives are to describe the clinical characteristics and determine the factors that predict intensive care unit (ICU) admission of patients with COVID-19. Determining these factors using a well-defined population can increase our understanding of the real-world epidemiology of the disease.

We used a combination of classic epidemiological methods, natural language processing (NLP), and machine learning (for predictive modeling) to analyze the electronic health records (EHRs) of patients with COVID-19. We explored the unstructured free text in the EHRs within the Servicio de Salud de Castilla-La Mancha (SESCAM) Health Care Network (Castillare likely to be admitted to the ICU if they had tachypnea and delayed their visit to the emergency department after being seen in primary care.

Our results show that a combination of easily obtainable clinical variables (age, fever, and tachypnea with or without respiratory crackles) predicts whether patients with COVID-19 will require ICU admission.
Our results show that a combination of easily obtainable clinical variables (age, fever, and tachypnea with or without respiratory crackles) predicts whether patients with COVID-19 will require ICU admission.Corticomuscular coupling reflects nonlinear interactions and multi-layer neural information transmission between the motor cortex and effector muscle in the sensorimotor system. Transfer spectral entropy (TSE) analysis has been used to describe corticomuscular coupling within single scale. As an extension of TSE, multiscale transfer spectral entropy (MSTSE) is proposed in this paper to depict multi-layer of neural information transfer between two coupling signals. EGFR inhibitor The reliability and effectiveness of MSTSE were verified on data generated by nonlinear numerical models and those of a force tracking task. Compared with TSE, MSTSE is more robust to the embedding dimension and performs optimally in the detection of the coupling properties. Further analysis of the physiological signals showed that the MSTSE provided more detailed band characteristics than the single scale TSE measurement. MSTSE indicates significant coupling scattered in alpha, beta and low gamma bands during the force tracking task. Besides, the coupling strength in the descending direction of the beta band was significantly higher than that in the ascending direction.
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