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Resting-state fMRI reveals brain functional alterations linked to balance disorders in vestibular migraine patients

AI for research: the ultimate guide to choosing the right tool

Targetable Mutations in <i>BRAF</i> V600E–Negative Hairy-Cell Leukemia

Genetically druggable targets for MAPK-activated colorectal cancer by a two-sample mendelian randomization analysis

Why an overreliance on AI-driven modelling is bad for science

Assessment of a Polygenic Risk Score in Screening for Prostate Cancer

Strong evidence for the evolution of decreasing compositional heterogeneity in SARS-CoV-2 genomes during the pandemic

Abstract The rapid evolution of SARS-CoV-2 during the pandemic was characterized by the fixation of a plethora of mutations, many of which enable the virus to evade host resistance, likely altering the virus’ genome compositional structure (i.e., the arrangement of compositional domains of varying lengths and nucleotide frequencies within the genome). To explore this hypothesis, we summarize the evolutionary effects of these mutations by computing the Sequence Compositional Complexity (SCC) in random stratified datasets of fully sequenced genomes. Phylogenetic ridge regression of SCC against time reveals a striking downward evolutionary trend, suggesting the ongoing adaptation of the virus’s genome structure to the human host. Other genomic features, such as strand asymmetry, the effective number of K-mers, and the depletion of CpG dinucleotides, each linked to the virus’s adaptation to its human host, also exhibit decreasing phylogenetic trends throughout the pandemic, along with strong phylogenetic correlations to SCC. We hypothesize that viral CpG depletion (throughout C➔U changes), promoted by directional mutational pressures exerted on the genome by the host antiviral defense systems, may play a key role in the decrease of SARS-CoV-2 genome compositional heterogeneity, with specific adaptation to the human host occurring as a form of genetic mimicry. Overall, our findings suggest a decelerating evolution of reduced compositional complexity in SCC, whereas the number of K-mers and the depletion of CpG dinucleotides are still increasing. These results indicate a genome-wide evolutionary trend toward a more symmetric and homogeneous genome compositional structure in SARS-CoV-2, which is partly still ongoing.

Advancing Health Equity in the Climate Crisis — A Climate Justice Curriculum for Resident Physicians

Analysis and validation of hub genes for atherosclerosis and AIDS and immune infiltration characteristics based on bioinformatics and machine learning

Why more AI researchers should collaborate with governments

Otitis Media in Young Children

Prevalence and underdiagnosis of diabetes mellitus in a food insecure population

Studying seabirds with a cactus as a research assistant

Extensive mutual influences of SMC complexes shape 3D genome folding

Endovascular Treatment for Stroke Due to Occlusion of Medium or Distal Vessels

D2D assisted cooperative computational offloading strategy in edge cloud computing networks

Ensuring Inclusive, Affirming Care for LGBTQ+ Patients — Scaling Up Cultural Competency Training

Effect of modified materials on the hydraulic conductivity of loess soil

Challenges to the Future of a Robust Physician Workforce

A scoping review and modelling of predictors of an abnormal Thompson score in term neonates in low-resource settings

Abstract Clinical risk scores, such as Thompson score, are useful alternatives to identify neonatal encephalopathy in low-resource settings where adequate training and equipment are often unavailable. An understanding of the clinical predictors of abnormally high Thompson score values would be beneficial to identify term neonates with suspected neonatal encephalopathy. A scoping review was conducted to identify a set of a priori neonatal and maternal variables associated with neonatal encephalopathy. Next, a prospective study of all term neonates admitted to Sally Mugabe Central Hospital in Zimbabwe between October 2020 and December 2022 was conducted to develop a predictive statistical model of abnormal (&gt; 10) Thompson score. In total 45 articles were identified from searching Medline, Scopus and Web of Science and 10 articles were selected. Five studies were conducted in countries in Asia and five in Africa. Of 6,054 neonates who met the inclusion criteria, 4.06% (n = 246) had an abnormal Thompson score at admission with a case fatality rate of 589 per 1000 admissions. Among these neonates, 90.65% (n = 223) had a low Apgar score (p &lt; 0.001). 40 candidate predictors were identified, of which 20 predictors were selected as the most important. Six risk factors were predictive of neonates at risk of abnormal Thompson score, including low neonatal heart rate (aOR = 0.97), temperature lower than 36.5 °C (aOR = 2.24), head swelling (aOR = 2.19), other maternal risk factors of sepsis excluding offensive liquor and premature rupture of membranes (aOR = 1.97), meconium-stained umbilicus (aOR = 1.79), and not crying at birth (aOR = 2.58). These identified risk factors should be prioritised before conducting a Thompson score assessment in resource-poor settings, and local clinical guidelines should incorporate these into the clinical management of at-risk neonates.