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This study evaluated AI chatbots' responses to scabies-related questions, finding DeepSeek had the highest accuracy despite higher hallucination rates, while ChatGPT-5.2 provided more readable and reliable information, highlighting variability and the need for cautious use of AI in health queries.

This study reports that structural and biochemical analysis of steroid 5α-reductases clarifies how they mediate steroid reduction with NADPH, potentially aiding in designing targeted therapies.

This study observed that COVID-19 infection in cancer patients may worsen lung damage, leading to over a 50% reduction in lung volume and increased lung density due to scar tissue formation.

This study found that altering neonatal neurosteroid levels affected anxiety and aversive learning in adult rats, possibly through changes in hippocampal GABAergic functions.

This source analyzes linguistic difficulties faced by speakers of East Slavic languages learning Polish, emphasizing challenges in pronunciation, vocabulary, and grammar. It suggests that tailored educational materials comparing linguistic nuances can improve learning outcomes by highlighting important differences between the languages.

This study identified key trends and influential contributors in skin microbiome research from the past decade, highlighting the growing publication rates, major players like the USA, and prominent researchers such as Gallo RL.

In this study, researchers introduced a machine learning approach to discover new nanozymes through the DiZyme platform, enabling the accurate prediction of multiple catalytic activities, and providing a comprehensive database and assistant resources for users.

This research introduces WomenCare, a web-based system using a machine learning model to predict PCOD risk by evaluating factors like age, BMI, and lifestyle habits; it aims to help women monitor their health but is not a substitute for a professional diagnosis.

This review, sourced from expert panel discussions and literature analysis, suggests Tianmeng oral liquid may improve sleep, reduce anxiety and depression, and enhance well-being in psychosomatic disorder patients, though further research is necessary.

This research explores the impact of advanced technologies, such as machine learning and robotics, on cardiothoracic surgery, noting that innovations like artificial hearts and enhanced circulatory support systems may improve patient outcomes by aiding diagnostics, surgery planning, and postoperative care.

This review suggests that integrating artificial intelligence in diabetic foot management could significantly improve early diagnosis and wound healing by facilitating thermographic analysis and developing "smart dressings," though challenges in training, legal, and ethical aspects remain.

In this review of autonomous robotic surgery, the authors explore the integration of AI and machine learning in surgical procedures, detailing both the advancements and challenges of these technologies, including ethical concerns and current regulatory frameworks.

This review discusses the applications and potential of Bioengineered Artificial Skin Substitutes in cosmetics and pharmacology research, with no new clinical findings reported.

This study found that dynamic resilient hyaluronic acid fillers were effective and well-tolerated for correcting moderate-to-severe nasolabial folds in people of color, with improvements in wrinkle severity and fewer adverse events compared to non-people of color.

This study evaluates a framework using neural networks and machine learning techniques to classify and detect Alopecia Areata from hair images, aiming for accurate differentiation between healthy hair and the condition.

This study discusses the potential of advanced imaging technologies in dermatology to improve diagnostic accuracy and reduce the need for invasive procedures like biopsies, while noting significant barriers in adoption and accessibility in India due to costs and infrastructure constraints.

This study highlights emerging regenerative strategies, such as stem cell-derived therapies and machine learning tools, that may advance hair loss treatment beyond traditional methods by promoting follicle regeneration and offering personalized care.

This scoping review describes the current use of artificial intelligence in alopecia research, highlighting AI's evolution from diagnostic to prognostic applications in dermatology and identifying gaps in multimodal integration and fairness across demographics.

In this retrospective cohort study, researchers found that exposure to 5-alpha reductase inhibitors and spironolactone in female alopecia patients was not linked to an increased risk of developing malignant or benign gynecologic tumors when compared to minoxidil use.

This review highlights new perspectives in genomics and epigenomics for skin rejuvenation, comparing innovative strategies like senolytics and DNA repair modulators with classical treatments, and emphasizing the importance of tailoring therapies using individual genomic profiles for personalized anti-ageing approaches.

This review discusses advancements in skin microphysiological systems, such as 3D bioprinting, skin organoids, and skin-on-a-chip, and their effectiveness in emulating human skin functions for research and preclinical applications, highlighting the potential for replacing animal testing with these innovative technologies.

This review discusses the integration of omics analyses in androgenetic alopecia research, reporting no new clinical results but suggesting that collaborative multi-omics studies may enhance understanding of AGA's pathomechanisms.

In this study, researchers are constructing a comprehensive data set from 997 adult participants in Japan to develop a statistical model that explores the relationships among various health parameters, aiming to enable personalized and preventive health care interventions based on empirical data.

This study highlights the potential benefits and current limitations of robotic systems in nipple-sparing mastectomies, noting their promise in reducing surgeon fatigue but pointing out challenges such as longer operating times, high costs, and limited haptic feedback.

This study developed a hat-shaped device with wearable sensors to estimate scalp moisture content using machine learning, demonstrating that it can provide accurate measurements comparable to professional scalp analyzers without the need for high-cost equipment.

This study identified a proliferative intermediate transcriptional state associated with the transition from secondary hair germ cells to lower hair follicle-associated cells during early hair follicle regeneration in mice.

This review suggests that hyperspectral and terahertz imaging show promise in non-invasively assessing scalp changes associated with hair loss, but further validation is needed for clinical application.

This study used a probabilistic framework to show that platelet-rich plasma preparation results in significant variability in platelet dose due to factors like injected volume and concentration factor.

In this study, the authors identified and characterized the Get3d protein, conserved across plants and photosynthetic bacteria, which localizes to the chloroplast in Arabidopsis thaliana and potentially plays a role in tail-anchored protein targeting, linked to photosynthesis homeostasis.