The global mental health crisis has led to increased substance abuse among youth. Prescription drug abuse causes approximately 115 American deaths daily. Understanding intergenerational transmission of substance abuse is complex due to lengthy human studies and socioeconomic variables. Recent FDA guidelines mandate abuse liability testing for neuro-active drugs but overlook intergenerational transfer. Brown planaria, due to their nervous system development similarities with mammals, offer a novel model.
The study explored the role of testosterone beyond its well-established effects on male sex characteristics, focusing on its association with non-communicable diseases (NCDs) like obesity and type 2 diabetes (T2D), using Mendelian randomization (MR) analysis on genomic data.
Wolbachia pipientis (Wolbachia) is a maternally inherited endosymbiotic bacterium that infects over 50% of arthropods, including pillbugs, and acts as a reproductive parasite in the host. In the common terrestrial pillbug Armadillidium vulgare (A. vulgare), Wolbachia alters the sex ratio of offspring through a phenomenon called feminization, where genetic males develop into reproductive females. Previous studies have focused on the presence or absence of Wolbachia as a sex ratio distorter in laboratory cultured and natural populations mainly from sites in Europe and Japan. Our three-year study is the first to evaluate the effects of the Wolbachia sex ratio distorter in cultured A. vulgare offspring in North America. We asked whether Wolbachia bacteria feminize A. vulgare isopod male offspring from infected mothers and if this effect can be detected in F1 offspring by comparing the male/female offspring ratios. If so, the F1 offspring ratio should show a higher number of females than males compared to the offspring of uninfected mothers. Over three years, pillbug offspring were cultured from pregnant A. vulgare females and developed into adults. We determined the Wolbachia status of mothers and counted the ratios of male and female F1 progeny to determine feminization effects. In each year sampled, significantly more female offspring were born to Wolbachia-infected mothers than those from uninfected mothers. These ratio differences suggest that the Wolbachia infection status of mothers directly impacts the A. vulgare population through the production of reproductive feminized males, which in turn provides an advantage for further Wolbachia transmission.
Skin cancer is a common and potentially deadly form of cancer. This study’s purpose was to develop an automated approach for early detection for skin cancer. We hypothesized that convolutional neural network-based models using transfer learning could accurately differentiate between benign and malignant moles using natural images of human skin.
Autism spectrum disorder (ASD) is hard to correctly diagnose due to the very subjective nature of diagnosing it: behavior analysis. Due to this issue, we sought to find a machine learning-based method that diagnoses ASD without behavior analysis or helps reduce misdiagnosis.
Authors emphasize the challenges of manual tumor segmentation and the potential of deep learning models to enhance accuracy by automatically analyzing MRI scans.
Authors address the gender disparity in STEM fields, examining changes in gender diversity across male-dominated undergraduate programs over 19 years at 24 top universities. Analyzing data from NCES IPEDS, it identifies STEM as persistently male-dominated but notes increasing gender diversity in many disciplines, particularly in recent years. Results indicate that higher-ranked universities in disciplines like computer science and mechanical engineering show a weak correlation with improved gender diversity, suggesting effective initiatives can mitigate the gender gap in STEM, despite ongoing challenges.
The authors use molecular modeling to test analogs of the stearoyl-coenzyme A desaturase 1 (SCD1) inhibitor MF-438 with implications for future development of Parkinson's disease therapeutics.
Artificial sweeteners are rising in popularity, in part due to the influence of social media platforms like YouTube. However, YouTube commenters often repeat information about artificial sweeteners that is not supported by scientific research. To investigate how misinformation about sweeteners spreads through social media, Kim and Yoo conduct a content analysis of YouTube comments to reveal how many comments repeat misinformation about artificial sweeteners' effects.
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