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This study observed defects in hair cuticle cross-linking in some, but not all, mouse mutants with sparse or structurally unsound hair.

This paper introduces an algorithm for using smart device-mounted microscopes to analyze scalp images and diagnose hair loss by extracting specific hair loss features.

In this study, a system was developed utilizing advanced image processing to analyze hair and scalp conditions, aiding professionals in diagnosing diseases like alopecia and monitoring treatment by extracting and comparing key parameters from microscopic images.

This study found that defective cross-linking in hair cuticles is observable in a minority of mouse hair mutants, suggesting different proteins are involved in cross-linking across cell types.

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 found that the extraction-resistant structures in hair, feathers, and hagfish teeth are due to ε-(γ-glutamyl)lysine cross-linked proteins, emphasizing their role in maintaining the integrity of these materials.

This study concluded that the process of mummification disfigures facial features, making identification challenging, but commercial shrunken heads retain more defining features compared to ceremonial ones.

Human nails contain both skin and hair keratins, each needing different extraction methods.

The study observed that patterned fibrosing alopecia, a type of scarring hair loss, appears in some patients after hair transplants, facelifts, and other surgical interventions, sharing features with lichen planopilaris and androgenetic alopecia.

This case report describes an atypical presentation of eruptive vellus hair cysts on the elbows, where standard diagnostic techniques were unreliable due to the loss of cystic structural integrity.

This study developed a model for detecting sparse hair clusters using enhanced object detection neural networks and medical images, which accurately identifies and counts sparse hair clusters with greater accuracy and efficiency than existing methods.

This review highlights the advantages of a new "Multi-Wave Punch" for follicular unit extraction in hair transplantation, noting its design reduces follicular damage and improves graft quality by effectively separating hair follicles from surrounding tissue.

This study developed a fast and sensitive ultra-high performance liquid chromatography method to quantify ketoconazole in antidandruff emulsions, showing comparable results to labeled concentrations.

The researchers developed a new follicular unit extraction system with adjustable needle lengths and precise rotation speed, which they report as being superior to existing systems for non-incisional hair transplants.

This study developed an automated image analysis framework for diagnosing hair disorders using trichoscopic images, reporting a Random Forest classifier as having an 86.67% accuracy in distinguishing between different scalp pathologies based on quantitative image features.

This article discusses hair angle manipulation using the Mega FUE® device but reports no clinical results; disclosure of the author's ownership of the manufacturing company is noted.

This review highlights recent advancements in FUE hair transplantation techniques and technologies, noting significant improvements in reducing follicle damage and increasing procedure speed, while emphasizing the need for surgeons to choose suitable devices for each patient's specific needs.

Researchers developed a quick and sensitive way to measure finasteride in blood using a small sample size.

This publication reviews articles on the aesthetic benefits of laparoscopic cholecystectomy and the dermatological effects of mask wearing during the COVID-19 pandemic, but presents no new clinical results.

In this study, trypsin digestion was found to be a faster and more efficient method than the explant technique for extracting bulge-derived keratinocytes from adult scalp biopsies.

This study introduces AlopeciaDet, a novel feature fusion technique, using camera images to detect Alopecia Areata with 99.45% accuracy, outperforming existing methods by leveraging CRSHOG and ResNet-50 features.

This review discusses the potential medicinal properties and pharmacokinetic features of nettle compounds ursolic acid and quercetin, highlighting quercetin as a promising candidate for antioxidant and anti-aging effects, but reports no new clinical results.

This study explored using large language models to automatically identify monkeypox cases from electronic medical records, finding that models based on DeepSeek features performed better than traditional methods, with logistic regression showing high accuracy in detecting key symptoms like fever and rash.

This study found that some white or grey hairs can naturally regain pigmentation, suggesting hair greying may be reversible in certain conditions linked to psychological stress.

This study used machine learning models to analyze PCOS symptoms for early diagnosis, finding Support Vector Machine and VGG16 algorithms achieved high accuracy rates of 94.44% and 98.29% respectively.

In this study, the proposed MSF-VMDNet, combining dual encoder networks with a multi-frequency domain mechanism, significantly outperformed existing methods in segmenting skin cancer tissues from histological slide images, achieving high accuracy with an MIoU of 95.37% and a Dice coefficient of 95.11%.

This study found that a pre-trained image processing technique accurately classified scalp conditions with 85% accuracy, suggesting potential for automated diagnosis and treatment selection.

This article reviews various hair abnormalities observable through trichoscopy in conditions like monilethrix, trichorrhexis nodosa, and ectodermal dysplasias, with no new clinical findings reported.

A Saudi girl was diagnosed with Loose Anagen Hair Syndrome, a rare condition causing easy hair loss without scarring.

This study found that LC-MS/MS assays provided more reliable and precise steroid measurements in human serum compared to traditional immunoassays, particularly at lower concentrations.