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

This article presents an algorithmic approach to diagnosing, staging, and treating pattern hair loss and discusses hair transplant decision-making, without reporting new clinical results.

This study describes a new treatment algorithm for alopecia areata that includes both disease severity and quality-of-life considerations, highlighting recent therapeutic advances and the need for future validation and access equity.

In this study, researchers successfully developed a 3D printed alginate-gelatin composite hydrogel scaffold characterized by high porosity and potential applications in drug delivery and screening, particularly for neurodegenerative diseases like Alzheimer's.

This case study examined a 72-year-old woman with unique hair shaft constrictions consistent with monilethrix, despite features atypical for this condition, ultimately reaching a diagnosis that led to successful improvement using oral minoxidil and reduced hair trauma.

The hydrogel improves hair growth treatment by enhancing drug delivery and promoting follicle repair.

In this study, experts propose a diagnostic and treatment guideline for folliculitis decalvans, emphasizing the role of trichoscopy and introducing a therapeutic algorithm tailored to disease activity, which is significant for clinical management given the lack of specific clinical trials.

This study found that both desmoglein-specific and non-desmoglein autoantibodies may play active roles in Pemphigus vulgaris pathogenesis, with HLA genetics influencing autoimmune specificity.

This review consolidates the opinions of top Canadian dermatologists on managing telogen effluvium, highlighting the importance of proper diagnosis, identifying triggers, and patient education.

In this study, researchers explored drug repurposing as a potential strategy for treating psoriasis and identified Pioglitazone, Trimipramine, and Dimetindene as promising candidates for this indication, based on molecular docking and predictive algorithms.

This study found that Spirulina algae extract significantly increased the differentiation of bone marrow-derived mesenchymal stem cells into neural cells without toxicity, suggesting potential as a therapeutic approach for neurodegenerative diseases in an in vitro setting.

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 study utilized the Random Forest Algorithm to create a machine learning model aimed at accurately predicting hair loss by considering complex datasets involving genetic, hormonal, lifestyle, and environmental factors, but specific outcomes were not reported.

This study developed a support vector machine model using trichoscopic patterns to accurately classify androgenic alopecia severity, with an accuracy of 94.3% in training and 90.0% in test datasets.

In this study, bond-protecting additives combined with low-volume oxidants were shown to reduce hair damage in fine hair by up to 62% compared to standard bleach methods, offering a safer bleaching approach for colorists working with this hair type.

This study found that an injectable calcium alginate-amelogenin hydrogel is biocompatible, degradable, anti-inflammatory, and promotes osteogenesis, which may enhance the bone healing process in jaw and facial bone defect areas by mediating the bone immune microenvironment.

In this study, improved hidden Markov algorithms based on Bayesian methods enhanced the resolution and segmentation accuracy of low-dose CT images significantly more than naive Bayesian methods.

This study reports that the newly developed SA-Ca(II) hydrogel has tunable mechanical properties, high biocompatibility, and potential applications in wearable protections and stimuli-responsive electronics.

This study found that a 50% ethanol extract from marine green alga Chlamydomonas sp. W80 exhibited several bioactive properties, including skin lightening and hair growth promotion effects, with potential implications for bioenergy and high-value coproducts.

This study found that polycystic ovary syndrome is the most common cause of hirsutism in premenopausal Algerian women, with recommendations for thorough endocrinologic evaluations.

This study describes characteristic trichoscopic features of various hair loss diseases and proposes an algorithmic method for diagnosing them, but reports no new clinical results.

This review highlights the diverse prognoses and limited long-term efficacy of current alopecia areata treatments, discussing existing and emerging therapies—including biologics—and proposing an algorithmic management approach based on specific disease characteristics.

This study found that the Random Forest machine learning algorithm achieved the highest accuracy, 96%, in diagnosing Polycystic Ovarian Syndrome using patients' clinical data.

A new method was developed to detect pesticide residues on apples without damage.

This study reported that newly developed quaternary ammonium chitosan/carboxymethyl starch/alginate sponges effectively inhibit bacterial growth and promote rapid hemostasis in wound management after tooth extraction in animal models, showing significant promise for clinical use in preventing complications like dry socket.

In this study, researchers used 3D printing combined with cryogenic crosslinking to develop gelatin/oxidized alginate scaffolds and found that adding 5% hydroxyapatite improved mechanical properties and osteogenic effects, enhancing bone tissue regeneration, though 10% hydroxyapatite offered no additional osteogenic benefits and reduced shape fidelity.

This study concluded that biotin, alone or combined with topical minoxidil, may effectively treat short anagen syndrome in children by enhancing anagen duration.

This paper reviews extraction methods for obtaining polysaccharides from brown macroalgae like Sargassum, highlighting their antiviral, antimicrobial, and antitumoral bioactivities in both in vivo and in vitro studies, while also discussing challenges in research and commercialization of Sargassum-based products.

This review discussed recent research on using machine learning to predict mental disorders, reporting that Adaboost could predict depression with 92.5% accuracy and 93.6% specificity, while other models like XGBoost and RNN were applied for post-stroke depression and EEG-based depression detection, respectively.