Search

everythingexperts & clinicslearnfaqsresearchcommunity

for

Search:↓

This study found that using spanlastics, a nano, surfactant-based drug delivery system, improved the bioavailability, drug release characteristics, and pharmacokinetic behavior of famotidine, a poorly soluble drug, by enhancing its dissolution and membrane permeation.

This study found that a cedrol nanoemulsion improved hair growth and bioavailability compared to an ointment, demonstrating enhanced efficacy in vitro and in vivo.

This study concluded that incorporating the percentage of free PSA and urinary markers improves the accuracy of determining the need for prostate biopsy.

This study observed that female mice with disrupted 5α-reductase 1 showed increased insulin resistance and hepatic steatosis, suggesting altered glucocorticoid metabolism contributes to metabolic disorders.

In this study, the researchers compared the pharmacokinetics and tissue distribution of dihydroartemisinin in nanostructured lipid carriers versus in solution, finding longer mean residence times and variable organ accumulation with the nanostructured lipid carriers.

The researchers reported that several m6A-related genes, particularly IGF2BP3, were differentially expressed in keloid tissue compared to normal skin, indicating potential targets for understanding keloid pathogenesis and treatment.

This study found that the WNMFDDA model effectively predicts drug-disease associations, achieving high accuracy in cross-validation and confirming most candidate associations through existing databases.

This study presents a computational approach, CATNIP, which repurposes drugs using only their biological and chemical information, predicting new uses like adrenergic uptake inhibitors for Parkinson's and vandetanib for Type 2 Diabetes.

This study demonstrated that genetic markers can predict human ear morphology with moderate to good accuracy, potentially aiding forensic identification in crime scene investigations where traditional DNA matches are unavailable.

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.

DNA can predict physical traits like eye and hair color accurately, especially in Europeans, but predicting other traits and in diverse populations needs more research.

In this study, ritlecitinib was generally well tolerated in pediatric alopecia areata patients aged 6 to <12 years, with no severe or serious adverse events reported, and the drug's pharmacokinetic parameters were successfully characterized.

HGF combined with ADA is highly accurate for diagnosing tuberculous pleural effusion, especially in younger females.

This study suggests that novel diagnostic, preventive, and treatment approaches for autoimmune diseases like alopecia areata may be developed by identifying hub genes, and highlights the usefulness of machine learning and bioinformatics in finding new disease biomarkers.

Repaglinide-loaded liponiosomal hybrids improve blood sugar control and insulin release better than regular Repaglinide.

This study constructed a model using serum levels of BMP2, CD8A, PRF1, and XCL1 as a non-invasive biomarker to accurately predict recurrence in patients with alopecia areata.

The two finasteride formulations are bioequivalent.

This study found that combining diagonal earlobe crease with lipoprotein(a) provides strong diagnostic value for coronary heart disease.

In this study, researchers investigated genetic variants in pharmacogenes affecting tadalafil and finasteride pharmacokinetics, finding fed volunteers had higher drug exposure than fasting individuals, but genetic variation did not significantly impact pharmacokinetics after correcting for multiple comparisons.

In this study, a machine learning framework incorporating the CatBoost algorithm accurately predicted Systemic Lupus Erythematosus in Omani patients, suggesting potential for early clinical intervention.

This study developed a sensitive HPLC-MS/MS method for determining cyproterone acetate levels in human plasma and found no significant difference in its concentration between two oral formulations in bioequivalence testing.

This study identified two key epigenetic-related genes, HR and SMYD4, which may act as potential biomarkers in keloid disease, suggesting new therapeutic avenues for further research.

This study found that women with female pattern hair loss exhibited hormonal imbalances, with the Free Androgen Index being a particularly effective diagnostic marker.

In this study, women with PCOS exhibited a significantly elevated low-grade inflammatory profile through salivary cytokines, with IL-1β and TNF-α demonstrating strong potential as non-invasive diagnostic markers, alongside traditional androgen measures like FAI.

In this study, the rs4541843 G > A variant was found to be significantly associated with increased risk and severity of alopecia areata, as well as elevated expression of hsa-miR-182-5p, suggesting their potential as molecular markers for diagnosis and severity assessment.

This study found that women with PCOS had higher levels of serum phoenixin isoforms, which correlated with reproductive and metabolic markers, suggesting these isoforms may have a potential diagnostic role.

This study developed a leakage-resistant machine learning framework for classifying hair loss types, emphasizing transparency through explainable AI. Among tested models, Extreme Gradient Boosting excelled, achieving high accuracy and stability on both cross-validation and holdout datasets.

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 study found that the 4Kscore model, when adjusted for kallikrein marker changes due to finasteride use, improved the prediction of high-grade prostate cancer compared to adjusted total PSA alone in men taking 5-α-reductase inhibitors.

This study found distinct hair metal profiles in Parkinson's disease patients, with lower iron and copper, higher manganese and arsenic, and explored their link to gut dysfunction and microbiota dysbiosis, suggesting hair metal analysis as a promising diagnostic tool.