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Acne is caused by genetics, diet, hormones, and bacteria, with treatments not yet curative.

In this review, the researchers highlight LED therapy as an emerging and safe treatment for skin inflammatory conditions, aging, and hair growth disorders, noting its integration into dermatological practice but emphasizing the need for more controlled studies to confirm its efficacy.

This review suggests that platelet-rich plasma may be effective in increasing hair density in patients with androgenetic alopecia, but more research is needed to determine the best treatment protocol.

This study found that ancient and modern Chinese goats share close genetic ties, originating from the Fertile Crescent, with genetic divergence influenced by China's climatic divisions.

This study reviewed the physiological and psychological impacts of acne vulgaris, highlighting its complex interactions with endocrine issues, sebum production, and immune response, while suggesting that a multidisciplinary approach can inform future treatments and improve quality of life for those affected.

This article discusses the importance of oral and maxillofacial surgeons understanding the pathogenesis and treatment of acne vulgaris, but it presents no new research findings.

This review discusses the similarities in clinical, endocrine, and ultrasonographic features between PCOS and other disorders with excessive androgen secretion, emphasizing the importance of accurate diagnosis but reports no new clinical results.

This review discusses the role of HPV vaccination and early screening in reducing cervical cancer incidence but reports no new clinical results.

This review outlines the major health consequences of anabolic-androgenic steroid abuse, with a focus on sexual and reproductive issues, and suggests management prioritizes cessation and relapse prevention due to lack of robust randomized trials.

This source provides a comprehensive review of acne vulgaris, highlighting its pathophysiology, epidemiology, molecular mechanisms, and treatment options, emphasizing the significance of addressing acne's psychosocial burden for adolescents and beyond.

This review discusses potential biomarkers for alopecia and their significance, and while it highlights areas for future research, it reports no new clinical results.

This study found that while genetic variants contribute minimally to predicting hair greying in a Polish population, age remains the primary predictor, underscoring the complexity of hair greying as a genetic trait.

This study found that abdominal obesity was the primary predictive factor for nonalcoholic fatty liver disease in women, rather than the presence of polycystic ovary syndrome.

This study developed a mathematical model and online tool using serum AMH, androstenedione levels, UML, and BMI to screen for undiagnosed PCOS, particularly useful for Asian populations.

Among a Han Chinese cohort, this study found that a higher genetic risk score was linked to increased susceptibility to BPH, larger prostate size, reduced effectiveness of 5ARI treatment, and a higher risk of undergoing TURP.

This study introduced the KRDQN predictive framework, which outperformed existing methods in predicting adverse drug reactions and provided interpretable insights into drug mechanisms, aiding pharmacovigilance and clinical decision-making.

This study evaluated novel steroids' potential as future hormonal therapies for neuroprotection in glucose disorders, but emphasized that further research is needed to optimize androgen antagonist use in the context of COVID-19 progression.

This article reviews the therapeutic use of carnitine derivatives for re-establishing mitochondrial functionality in aging and reports no new clinical results.

This study observed that gerbils exhibit a different wound healing mechanism compared to mice, with lower TGF-B1 expression and distinct tissue responses, yet achieve similar healing outcomes.

This study observed that cutaneous microwounds created by fractional photothermolysis heal differently from typical wounds, displaying rapid re-epithelialization and limited inflammation, which may help reduce scar formation by delaying collagen remodeling and minimizing myofibroblast activation.

This review discusses selection signatures and selective sweeps in fiber-producing animals and recommends further genomic investigations to identify genes related to important fiber traits, without providing new results.

This study evaluated a new AI-linked imaging device for grading dandruff severity, finding high correlation with expert assessments and suggesting its potential application in other skincare areas due to its versatility and ease of use.

This retrospective cohort study reported that oral tofacitinib was effective in treating alopecia areata, with 83.2% of patients showing improvement and 16.0% achieving complete remission. Earlier intervention and previous hair regrowth were linked to better outcomes, and no severe adverse events were observed.

In this study, a novel GAN-based image translation method focusing on regions of interest showed improved predictive performance for post-hair transplant images compared to existing methods, using an ensemble approach to enhance robustness and detection accuracy.

This study reviewed the potential of Lupeol, a natural triterpenoid, in promoting hair growth and reducing inflammation related to alopecia, revealing promising molecular pathways and favorable pharmacokinetics while suggesting further research to validate these findings.

This study found that higher Dietary Inflammatory Index scores were significantly associated with an increase in both the occurrence and severity of alopecia areata.

In this study, hair loss after laparoscopic sleeve gastrectomy was associated with zinc and iron levels, even within normal ranges, and a combined variable of zinc and iron predicted susceptibility to hair loss.

This study found that long-lived proteins in mice, identified across various tissues, may be linked to neurodegenerative and cardiovascular diseases due to their low renewal rate and increased risk of damage.

In this study, researchers evaluated various machine learning models for predicting type 2 diabetes risk, finding that Random Forest and K-NN models performed best in terms of precision, recall, accuracy, and other metrics using common symptoms as features.

This study identified 12 potential candidate biomarkers associated with hair loss by analyzing the differential expression of genes, suggesting possible therapeutic targets for alopecia.