Metabolic dysfunction-associated fatty liver disease, representing a spectrum of liver disorders from simple steatosis to metabolic dysfunction-associated steatohepatitis, fibrosis, and cirrhosis, has emerged as one of the most prevalent chronic liver conditions globally, affecting an estimated approximately 30% of the world's population. Its pathogenesis is highly complex, involving intricate interactions between genetic predisposition, metabolic dysregulation, inflammation, and cellular stress responses. Within this complex landscape, orphan nuclear receptors (ONRs) have gained significant attention. Defined by the lack of identified endogenous ligands, ONRs function as master transcriptional regulators controlling diverse biological processes. Crucially, they play pivotal roles in the development and progression of numerous diseases, including metabolic disorders.This review specifically focuses on elucidating the critical contributions of various ONRs to the pathogenesis of metabolic dysfunction-associated fatty liver disease. We examined how these receptors modulate key pathological drivers: lipid metabolism, inflammation,and autophagy.

The importance of putative folate-biopterin metabolic interactions lies in the role they may play in the expression of several clinically relevant phenotypes. However, to date, clinical studies on folate-biopterin interactions have been limited. The purpose of this article was to highlight the close relationship between these two cofactors, which share structural similarities and exhibit overlapping metabolic pathways. This folate-biopterin crosstalk has generated several ideas and hypotheses that are critical to advancing the biochemical understanding of several important and seemingly disparate clinical and/or biologically important phenotypes. These phenotypes include melanization/pigmentation, phenylketonuria, autism, neural tube defects, affective disorders, and vascular disease. This review provides a timely, integrated overview of this important area of biochemistry, which is under-represented in the literature and would benefit from further scientific and clinical investigation using improved metabolite-specific analytical methodologies applied to clinically relevant questions.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a leading cause of hepatic fibrosis, yet its prevalence in asymptomatic populations remains unclear. This study aimed to assess the prevalence of steatosis and significant fibrosis in asymptomatic individuals without known liver disease in the Greater Vancouver Area.

Interested individuals voluntarily registered online via the Canadian Liver Foundation website or by telephone. Inclusion criteria included age ≥ 19 years, no known liver disease, and low alcohol intake (<30 g/day for men, <20 g/day for women). Demographic and clinical data were collected, and all participants underwent transient elastography after a 3-h fast. The study aimed to collect 4,500 analyzable scans while reflecting the region’s ethnic diversity.

A total of 4,193 participants were analyzed. The median age was 62 years, the median body mass index was 25.4, and 45% were male. Asian individuals comprised 42% of the cohort. Steatosis was present in 59.6% of participants, and 45.7% met diagnostic criteria for MASLD. Significant fibrosis (F2–F4) was found in 8.6%. Age, male sex, ethnicity, cardiac disease, diabetes, hypertension, and obesity were significantly associated with fibrosis. Logistic regression analysis confirmed age, weight, diabetes, dyslipidemia, hypertension, and obesity as independent predictors.

A substantial proportion of asymptomatic individuals in Greater Vancouver have undetected MASLD and significant fibrosis. Early identification of high-risk groups may support broader implementation of transient elastography screening. This study provides one of the first North American population-based estimates of MASLD and fibrosis stratified by ethnicity, offering new insights into liver disease distribution among Caucasian, Chinese, and South Asian populations.

Shenqi Fuzheng (SQ) is a widely used Chinese medicine formula known for its immune-enhancing and Qi-supplementing properties. However, the blood-absorbed components of SQ and their pharmacokinetics remain underexplored. This study aimed to comprehensively analyze the chemical constituents of SQ and investigate their absorption and pharmacokinetic behavior in rat plasma.

Ultra-performance liquid chromatography-triple quadrupole time-of-flight mass spectrometry (hereinafter referred to as UPLC-Triple-TOF/MS) is employed to identify the chemical components in SQ extract and quantify the components absorbed into the blood after oral administration in rats. This method provides fragmentation patterns of compounds and key pharmacokinetic profiles of blood-absorbed compounds.

A total of 105 compounds are identified from the SQ extract, and 40 are detected in the blood following oral administration. Organic acids and amino acids are found at higher concentrations in the bloodstream. Compounds such as Astragalosides promptly enter the bloodstream within 5 m after administration, with levels declining after 15 m. Flavonoids are absorbed within 15–30 m, and the peak of alkaloids occurs approximately 1 h after administration.

This study provides new insights into the chemical composition and pharmacokinetics of SQ, highlighting the dynamic changes in the content of absorbed compounds in the blood. It further promotes the comprehensive characterization of traditional Chinese medicine formulations through UPLC-Triple-TOF/MS. Future research should focus on elucidating the pharmacological activities of the identified compounds and investigating their potential synergistic effects within the formulation.

Huo Xue Tong Luo Capsule (HXTL) has been clinically used to treat osteonecrosis of the femoral head, osteoporosis, and other bone and joint diseases with promising effects. Our previous study has shown that HXTL can promote osteogenesis in mesenchymal stem cells by inhibiting lncRNA-Miat expression through histone modifications. However, the mechanism by which HXTL treats postmenopausal osteoporosis (PMOP) remains unclear. In this study, we used network pharmacology-based mechanism prediction, molecular docking, and pharmacological validation to investigate the mechanism of HXTL in treating PMOP.

The key candidate targets and relevant signaling pathways of HXTL for PMOP treatment were predicted using network pharmacology and molecular docking analysis. RAW264.7 cells were used for Western blot to validate the predicted mechanistic pathways. The ovaries of mice were surgically removed to simulate PMOP. The effect of HXTL on PMOP was evaluated using tartrate-resistant acid phosphatase staining and immunohistochemical assays in vivo.

Network pharmacology analysis suggested that HXTL interacted with 215 key targets linked to PMOP, primarily affecting the PI3K-AKT signaling pathway. Molecular docking showed that the main components of HXTL exhibited strong binding affinity to NFATc1, p-PI3K, and p-AKT1. Furthermore, our in vitro results confirmed that HXTL suppressed the PI3K-AKT signaling pathway. In vivo, HE and tartrate-resistant acid phosphatase staining results showed that HXTL inhibited osteoclast formation and protected bone mass.

This research demonstrated that HXTL could inhibit osteoclast formation and prevent bone loss induced by ovariectomy in mice by inhibiting the PI3K-AKT signaling pathway. These findings provide important evidence for the clinical application of HXTL in treating PMOP.

Prostate cancer is the second most diagnosed cancer in men worldwide and a significant cause of cancer-related death. Proteogenomic analysis offers insights into how genomic mutations influence protein expression and can identify novel biomarkers. This study aimed to investigate the impact of missense mutations on protein abundance in prostate cancer versus healthy tissues using SILAC-based quantitative proteomics.

Mass spectrometry data from prostate tumors and adjacent healthy tissues were analyzed using stable isotope labeling. Peptides were classified based on their abundance into RefSeq and Variant Abundant groups. Missense mutations were mapped via RefSeq and dbPepVar databases. Protein intensity metrics were compared, and Spearman’s correlation was used to evaluate the relationship between mutation presence and protein abundance.

Functional enrichment revealed that RefSeq Abundant proteins are involved in normal metabolic and structural functions, while Variant Abundant proteins are enriched in tumor-related pathways such as immune evasion and apoptosis suppression. A significant negative correlation was found between protein intensity difference and ratio (p < 0.05), indicating that missense mutations contribute to altered protein expression. Mutation hotspot analysis identified recurrent alterations in genes such as PPIF and ACTB. PROVEAN was used to evaluate the functional impact of variants, identifying several as deleterious to protein stability and function.

Missense mutations are associated with altered protein abundance and may promote oncogenic processes in prostate cancer. These findings enhance the understanding of genome-proteome interactions and could support the development of targeted biomarkers and therapies.

Leishmaniasis is a dangerous yet neglected tropical disease affecting a vast population of the world. Several medicinal plants and their constituents (natural products/phytochemicals) have been considered of prime importance for the management of leishmaniasis over the years. The present review sheds light on the molecular mechanisms of the constituents obtained from medicinal plants that are pre-clinically effective against leishmaniasis. Various mechanisms by which medicinal plant-derived natural products elicit their action against leishmaniasis are illustrated in the literature. The mechanisms identified include: disruption of cytoplasmic and mitochondrial membranes, induction of apoptosis and autophagy, modulation of gene expression and immunological pathways, pro-oxidant effects (disrupting redox balance) with mitochondrial dysfunction, cell cycle arrest, impaired cellular bioenergetics, i.e., adenosine triphosphate production and coagulation of cellular contents within Leishmania parasites. Future phytochemical and pharmacological (especially clinical) studies are necessary to further understand the mechanistic details of medicinal plant-derived natural compounds and to develop new phytotherapeutic entities from nature against leishmaniasis.

Human papillomavirus (HPV) infection is the primary cause of cervical, anogenital, and oropharyngeal cancers in the United States. These cancers are preventable through HPV vaccination. Research is critically needed to identify effective strategies for promoting HPV vaccination among high-risk groups. This study develops a risk prediction model to identify patients who are unlikely to complete HPV vaccination, with the goal of using the model to direct resources and increase vaccination rates.

We assessed vaccination status along with patient, provider, and clinic characteristics that predict vaccination completion. We then developed a predictive model to assess the likelihood of completing HPV vaccination, which can be used to target interventions based on patient needs. We used a retrospective cohort from a large integrated delivery system in Oregon. Using logistic regression with data available in the electronic health record, we created a risk model to determine the likelihood of vaccination completion among patients aged 11–17 years.

In a cohort of 61,788 patients, 40,570 (65.7%) had received at least one dose of the HPV vaccine. The full model included 17 demographic, clinical, provider, and community characteristics, achieving a bootstrap-corrected C-statistic of 0.67 with adequate calibration. The reduced model, which retained five demographic and clinical characteristics (age, language, race, ethnicity, and prior vaccinations), had a bootstrap-corrected C-statistic of 0.65 and adequate calibration.

Our findings suggest that a risk prediction model can guide the implementation of targeted interventions and the intensity of those interventions based on the likelihood of vaccination completion.