Rethinking BCC diagnosis: Automating concept-specific detection of BCC in dermatoscopic images.

Background: Basal cell carcinoma (BCC) is a prevalent type of skin cancer in which the inherent subjectivity of dermoscopy poses diagnostic challenges. Existing AI systems, which provide mainly image-level insights, lack the interpretability that is crucial for effective clinical decisions and patient education.

Patients And Methods: Our study developed a refined BCC dataset from the Human‒Machine Adversarial Model (HAM10000), which was annotated by clinicians to identify key diagnostic features.

Topical riboflavin versus 5-aminolevulinic acid photodynamic therapy for the treatment of mild to moderate acne: A split-face randomized study.

Background: ALA-PDT has been widely used in mild to moderate acne vulgaris worldwide. However, very few studies used riboflavin-PDT to treat acne vulgaris.

Objective: To investigate the efficacy and adverse events of riboflavin-PDT to treat mild to moderate facial acne, and compare it with ALA-PDT on a non-inferiority basis.

Evaluating diurnal rhythms of host responses to enteric norovirus infection in mouse models.

Norovirus is a leading cause of gastroenteritis worldwide. The factors required for the life cycle and pathogenesis of norovirus in humans remain unclear. Mouse models of norovirus infection have been widely used to explore the crosstalk between norovirus and the host.

Melatonin treatment increases skin microbiota-derived propionic acid to alleviate atopic dermatitis.

Background: Melatonin has been reported to relieve the inflammatory symptoms and improve sleep disturbance in patients with atopic dermatitis (AD). Recent studies showed that melatonin produced beneficial effects by remodeling intestinal microbiota composition; however, whether the beneficial effects of melatonin in AD were mediated by the modulation of skin microbiota remains unclear.

Objective: We sought to investigate the mechanism by which melatonin treatment-induced changes in the skin microbiota composition further alleviated AD.

Enhancing Epstein-Barr virus detection in IBD patients with XAI and clinical data integration.

Background: There is increasing evidence of a link between Epstein-Barr virus (EBV) and gastrointestinal cancers, particularly in immunocompromised patients and those on thiopurines. Traditional endoscopic techniques have limitations in diagnosing EBV, whereas standard methods for diagnosing EBV have practical challenges in regular clinical settings related to their invasiveness and high costs.

Methods: An explainable AI (XAI) model was developed to analyze 1598 endoscopic images from 287 patients with inflammatory bowel disease (IBD), with a focus on detecting EBV infection.

Influence of hair presence on dermoscopic image analysis by AI in skin lesion diagnosis.

The escalating rates of melanoma and non-melanoma skin cancers highlight the urgent need for enhanced diagnostic tools. This study evaluates the effect of hair presence in dermoscopic images on AI-driven skin lesion recognition, using 10,015 images from the HAM10000 collection. Images were categorized based on the extent of hair occlusions to assess their impact on AI performance.

AI fusion of multisource data identifies key features of vitiligo.

Vitiligo is a skin disorder that is associated with a decreased risk of skin cancer, but it can lead to increased susceptibility to sunburn, psychological distress, and disruptions in daily life, consists of two primary subtypes: segmental and nonsegmental vitiligo, each with distinct underlying mechanisms. However, the reliable identification of diagnostic markers and the ability to differentiate between these subtypes have remained elusive challenges. This study aims to pioneer predictive algorithms for vitiligo diagnosis, harnessing the capabilities of AI (Artificial Intelligence) to amalgamate multisource data and uncover essential features for distinguishing vitiligo subtypes.

CD74 fibroblasts proliferate upon mechanical stretching to promote angiogenesis in keloids.

The healing of human skin wounds is susceptible to perturbation caused by excessive mechanical stretching, resulting in enlarged scars, hypertrophic scars, or even keloids in predisposed individuals. Keloids are fibro-proliferative scar tissues that extend beyond the initial wound boundary, consisting of the actively progressing periphery and the quiescent center. The stretch-associated outgrowth and enhanced angiogenesis are two features of the periphery of keloids.

HDAC3 integrates TGF-β and microbial cues to program tuft cell biogenesis and diurnal rhythms in mucosal immune surveillance.

The intestinal mucosal surface is directly exposed to daily fluctuations in food and microbes driven by 24-hour light and feeding cycles. Intestinal epithelial tuft cells are key sentinels that surveil the gut luminal environment, but how these cells are diurnally programmed remains unknown. Here, we show that histone deacetylase 3 (HDAC3) controls tuft cell specification and the diurnal rhythm of its biogenesis, which is regulated by the gut microbiota and feeding schedule.

Retrosynthetic analysis via deep learning to improve pilomatricoma diagnoses.

Background: Pilomatricoma, a benign childhood skin tumor, presents diagnostic challenges due to its manifestation variations and requires surgical excision upon histological confirmation of its characteristic cellular features. Recent artificial intelligence (AI) advancements in pathology promise enhanced diagnostic accuracy and treatment approaches for this neoplasm.

Methods: We employed a multiscale transfer learning model, initiating the training process at high resolutions and adapting to broader scales.

Radiomics-based machine learning model to phenotype hip involvement in ankylosing spondylitis: a pilot study.

Objectives: Hip involvement is an important reason of disability in patients with ankylosing spondylitis (AS). Unveiling the potential phenotype of hip involvement in AS remains an unmet need to understand its biological mechanisms and improve clinical decision-making. Radiomics, a promising quantitative image analysis method that had been successfully used to describe the phenotype of a wide variety of diseases, while it was less reported in AS.

Radiomic and deep learning analysis of dermoscopic images for skin lesion pattern decoding.

This study aims to explore the efficacy of a hybrid deep learning and radiomics approach, supplemented with patient metadata, in the noninvasive dermoscopic imaging-based diagnosis of skin lesions. We analyzed dermoscopic images from the International Skin Imaging Collaboration (ISIC) dataset, spanning 2016-2020, encompassing a variety of skin lesions. Our approach integrates deep learning with a comprehensive radiomics analysis, utilizing a vast array of quantitative image features to precisely quantify skin lesion patterns.

Anti-inflammatory and antioxidant effects on skin based on supramolecular hyaluronic acid-ectoin.

We addressed the damage caused by internal and external factors on the skin, as well as the aging phenomenon caused by delayed repair after damage. We prepared supramolecular hyaluronic acid-ectoin (HA-ECT) by combining theoretical calculations and experimental research, using intermolecular forces between hyaluronic acid and ectoin. This supramolecule has good stability, safety, and skin permeability and can penetrate the stratum corneum of the skin, reaching the epidermis and dermis of the skin.

promotes hair-follicle recovery via FGF2-PI3K/Akt signal pathway.

Unlabelled: A previous study indicated that patients with androgenic alopecia (AGA) have significantly reduced levels of . This study investigates whether promotes hair-follicle recovery and its possible mechanism. Hair alteration and cutaneous histopathological changes induced by testosterone propionate were observed by H&E and bromodeoxyuridinc (BrdU) stain to evaluate the therapeutic effect of in C57BL/6 J mice.

joint infections: A case series.

Tuberculosis is a chronic infectious disease, caused by , that seriously endangers human health. Skeletal tuberculosis is the most common type of extrapulmonary tuberculosis and tuberculous arthritis is the second most common type of skeletal tuberculosis. We report a case series of patients with tuberculous arthritis, two of whom had no joint disease in the past and presented as monoarthritis.

Enhancing phosphorus transformation in typical reddish paddy soil from China: Insights on long-term straw return and pig manure application via microbial mechanisms.

Effective utilization of organic resources to activate residual phosphorus (P) in soil and enhance its availability is crucial for mitigating P resource scarcity and assessing the sustainable use of P in agricultural practices. However, the mechanisms through which organic resources affect soil P conversion via microorganisms and functional genes remain unknown, particularly in long-term organic-inorganic agricultural systems. In this study, we examined the impact of combined organic-inorganic fertilizer application on P availability, carbon (C) and P cycling genes, and microbial communities (bacterial and fungal) in reddish paddy soil based on a 42-year field experiment.

SIRT7 promotes mitochondrial biogenesis to render the adaptive resistance to MAPK inhibition in melanoma.

Melanoma, arising from the malignant transformation of melanocytes, stands as the most lethal type of skin cancer. While significant strides have been made in targeted therapy and immunotherapy, substantially enhancing therapeutic efficacy, the prognosis for melanoma patients remains unoptimistic. SIRT7, a nuclear-localized deacetylase, plays a pivotal role in maintaining cellular homeostasis and adapting to external stressors in melanoma, with its activity closely tied to intracellular nicotinamide adenine dinucleotide (NAD).

Soil Cd bioavailability response characteristics to microbes in paddy fields with co-incorporation of milk vetch, rice straw and amendments.

Excessive heavy metals in soils can threaten food security and soil health. New practical technology is urgently needed to remediate cadmium (Cd) contaminated paddies in many parts of the world. Chinese milk vetch (M), rice straw (R), and soil amendments can reduce Cd activity in soil; however, the mechanism underlying this reduction is not well understood.

Smart diabetic foot ulcer scoring system.

Current assessment methods for diabetic foot ulcers (DFUs) lack objectivity and consistency, posing a significant risk to diabetes patients, including the potential for amputations, highlighting the urgent need for improved diagnostic tools and care standards in the field. To address this issue, the objective of this study was to develop and evaluate the Smart Diabetic Foot Ulcer Scoring System, ScoreDFUNet, which incorporates artificial intelligence (AI) and image analysis techniques, aiming to enhance the precision and consistency of diabetic foot ulcer assessment. ScoreDFUNet demonstrates precise categorization of DFU images into "ulcer," "infection," "normal," and "gangrene" areas, achieving a noteworthy accuracy rate of 95.