Postoperative gastrointestinal (GI) bleeding is a serious complication after hip fracture surgery in older adults, yet perioperative risk stratification remains limited because commonly used GI-bleeding scores are not tailored to orthopedic settings. This study aimed to develop and internally validate an interpretable model to predict postoperative GI bleeding risk in elderly hip fracture patients, using data routinely available during the perioperative period. We retrospectively included 342 elderly patients who underwent hip fracture surgery at the Third Hospital of Hebei Medical University from January to December 2023. The outcome was GI bleeding within 1 month after surgery, confirmed by medical records and/or telephone follow-up. Patients were randomly split into a training set (n = 242) and a validation set (n = 100). Predictors were screened using LASSO with 10-fold cross-validation, followed by multivariable logistic regression to identify independent risk factors. Ten prediction algorithms were trained and compared. Model performance was assessed by AUC, calibration, and decision curve analysis, and interpretability was evaluated using SHAP. GI bleeding occurred in 38 patients (11.1%). Multivariable analysis identified four independent predictors: alcohol consumption history (OR 8.109, 95% CI 2.463-26.69), glucocorticoid use (OR 4.922, 95% CI 1.055-22.97), NSAID use (OR 6.851, 95% CI 1.811-25.915), and higher systemic immune-inflammation index (SII) (OR 1.001, 95% CI 1.000-1.002). Among the tested models, LightGBM showed the best overall performance, with AUCs of 0.843 (training) and 0.817 (validation), good calibration, and the highest net benefit on decision curve analysis. SHAP results ranked feature importance as SII, NSAID use, alcohol consumption history, and glucocorticoid use, consistent with regression findings. We developed and validated an interpretable LightGBM model that predicts postoperative GI bleeding risk in elderly hip fracture patients using routinely available clinical data. The final model incorporates only preoperative variables, systemic inflammation, NSAID use, alcohol history, and glucocorticoid use, supporting its application for early risk stratification prior to surgery.
Breast cancer patients often experience significant psychological distress. This study examined distress trajectories from diagnosis to 6 months post-treatment and explored differences across demographic, medical, and psychosocial subgroups. In this prospective cohort study, 528 patients with breast cancer were recruited between 1 December 2023 and 31 December 2024. Assessments were conducted at baseline (at diagnosis, T0), after the first treatment (T1), mid-treatment (T2), at treatment completion (T3), and at three (T4) and six months (T5) post-treatment. Growth mixture modeling (GMM) was used to identify distinct trajectories of psychological distress. Multinomial logistic regression analysis was performed to examine associations between patient-related factors and trajectory membership. Three psychological distress trajectories were identified: a high-distress remission group (17.05%), a moderate-stable distress group (11.93%), and a low-fluctuating distress group (71.02%). Multivariable analyses showed that higher educational attainment, breast-conserving surgery, early disease stage, partial self-management ability, and strong social support were associated with membership in the moderate-stable or low-fluctuating groups (p < 0.05). Employment, health insurance coverage, avoidant medical coping style, and higher baseline anxiety and depression scores were concurrently associated with membership in the high-distress remission group (p < 0.05). Although psychological distress generally decreased over time, 71.02% of patients followed a low-fluctuating trajectory, 11.93% maintained moderate distress with potential risk of persistence, and 17.05% showed high initial distress that remitted substantially within 6 months. Continuous monitoring and early psychosocial support are recommended, particularly for patients with moderate- or high-risk trajectories.
To compare perioperative outcomes between the 48-h short-stay pathway and traditional inpatient management for patients undergoing robot-assisted partial nephrectomy (RAPN), and to evaluate the feasibility, safety, recovery efficiency, and economic benefits of the 48-h short-stay pathway. This retrospective study included 175 patients who underwent RAPN between February 2022 and June 2024. Patients were assigned to a 48-h short-stay group (n = 60) or a traditional inpatient group (n = 115). A 1:1 propensity score matching (PSM) was conducted to balance baseline characteristics, including age, sex, BMI, comorbidities, tumor features, surgeon identity, and surgical year. Perioperative outcomes, recovery indicators, complications, and medical costs were compared. After PSM, 53 matched pairs were analyzed. The short-stay group showed significantly shorter operative time, less intraoperative blood loss, shorter warm ischemia time, earlier mobilization, earlier oral intake, faster bowel function recovery, and shorter bed rest (all P < 0.05). The short-stay group had 71.7% of patients discharged on postoperative day (POD) 1 and 100% within 48 h, while the traditional group had 22.6% on POD1, 33.96% on POD2, and 43.4% on POD ≥ 3 (P < 0.001). Both total and postoperative hospital stays were significantly shorter in the short-stay group (2.00 vs. 6.00 days, P < 0.001), with lower hospitalization costs (P < 0.001). Postoperative creatinine was lower in the short-stay group (P = 0.023), while creatinine change was comparable (P = 0.063). Complication rates, emergency department visits, and 30-day readmission rates were similar between groups (all P > 0.05). The short-stay group had a significantly lower drain placement rate (P = 0.002) without increased adverse events. The 48-h short-stay pathway for selected patients undergoing RAPN is feasible and safe. It accelerates postoperative recovery, shortens hospital stay, reduces medical costs, and optimizes healthcare resource utilization, without compromising safety or oncological early outcomes.
The Clinical Genome Resource (ClinGen) Von Hippel-Lindau (VHL) Variant Curation Expert Panel (VCEP) has created variant classification specifications tailored to the VHL gene, including phenotype-driven and evidence-based criteria, utilizing somatic and germline mutational hotspots, along with functional and in-silico data. Using the American College of Medical Genetics and Genomics (ACMG) guidance and the ClinGen Sequence Variant Interpretation (SVI) recommendations, the VCEP made substantial modifications to 8 evidence codes (PVS1, PS3, PS4, PM1, BS2, BS3, BS4, BP5), while 14 had minor changes, and 6 were not used (PM3, PP2, BP1, PP4, PP5/BP6). The VHL VCEP applied two literature sets of over >428 papers in Clinical Interpretations of Variants in Cancer (CIViC) and >8700 structured annotations using Hypothesis. From 31 pilot variants, 15 remained pathogenic/likely pathogenic, 9 resolved to benign through the stand-alone benign evidence code while 7 variants with initial uncertain classifications lacking additional evidence, remained uncertain. The versioned VHL VCEP specifications are publicly available in the ClinGen Criteria Specifications Registry and will enhance the transparency and consistency of variant classifications for this highly sequenced hereditary cancer gene.
Tanzania has adopted artificial intelligence (AI)-assisted chest X-ray screening for tuberculosis (TB), including the use of CAD4TB version 6, which is registered by the Tanzania Medicines and Medical Devices Authority (TMDA). While GeneXpert, practical reference standard used in routine practice, remains the primary bacteriological confirmatory test in routine practice, there is currently no established national threshold for CAD4TB use in either active case finding (ACF) or passive case finding (PCF) settings. This study evaluates the implementation and operational use of CAD4TB version 6 within mobile TB screening units in Tanzania and highlights challenges affecting its effective use. We conducted a retrospective analysis of screening data from 11,923 individuals collected from mobile clinics equipped with digital X-ray, CAD4TB version 6, and GeneXpert systems. Comparisons were made between manual chest X-ray interpretation, CAD4TB scores, and GeneXpert results within the subset of individuals who underwent confirmatory testing. The findings reveal substantial inconsistencies in screening workflows, including non-uniform use of CAD4TB prior to GeneXpert testing, missing radiological records, and deviations from intended protocols across sites. Descriptive analysis showed that CAD4TB scores generally aligned with GeneXpert-positive cases within the tested subset; however, due to selective application of GeneXpert and incomplete data, these observations cannot be interpreted as measures of diagnostic accuracy. This study should be interpreted as an implementation and operational assessment of AI-assisted TB screening rather than a diagnostic accuracy or threshold-setting study. The findings highlight important gaps in protocol adherence, data completeness, and workflow standardization, underscoring the need for prospective, protocol-driven studies to establish validated national thresholds for CAD4TB use in Tanzania.
Perivascular epithelioid cell tumors (PEComas) are rare mesenchymal tumors composed of cells exhibiting an epithelioid morphology. These cells typically arrange around small blood vessels (perivascular spaces) and display dual differentiation characteristics of smooth muscle cells and melanocytes. Diagnosis is challenging due to the absence of specific symptoms or tumor markers. This case features a young male patient with a large hepatic PEComa, whose imaging findings resemble those of hepatocellular carcinoma. We have detailed the entire process from diagnosis to treatment to aid in differential diagnosis and surgical planning. A 31-year-old male patient with no prior medical history underwent a routine health examination 20 days prior to presentation. Although the patient was asymptomatic, ultrasound revealed an incidental hepatic lesion measuring 58 × 50 × 45 mm (maximum diameter 58 mm, or 5.8 cm). The screening center suspected a hemangioma. Subsequently, he presented to our hospital. Comprehensive imaging studies, including ultrasound, computed tomography (CT), and magnetic resonance imaging (MRI), revealed a 58 mm-diameter space-occupying lesion in segments V and VIII of the right hepatic lobe. Imaging findings initially raised suspicion for hepatocellular carcinoma. To minimize surgical trauma and preserve liver function, our team discussed surgical approaches and ultimately decided on a laparoscopic partial hepatectomy. During the procedure, we obtained a specimen for pathological examination. The final histopathological analysis confirmed the diagnosis of a PEComa with undetermined malignant potential. The patient recovered smoothly postoperatively and was successfully discharged. PEComa has an insidious onset and is rare. Early diagnosis is often challenging, and imaging studies typically show no highly specific findings. Clinical diagnosis frequently relies on biopsy. In terms of treatment, radical resection (R0 resection, i.e., negative margins) represents the definitive therapeutic approach.
Work in eating disorder (ED) services presents unique challenges and rewards that may affect clinicians' work-related and personal wellbeing. However, research on ED clinician needs, views, and experiences is still sparse, despite major service changes since the COVID pandemic. This study aims to explore and conceptualise NHS ED clinicians' work-related experiences, challenges, and needs, in order to inform future clinicians wellbeing and service improvement strategies. Clinicians working in ED services (N = 19) were interviewed using a semi-structured interview guide that probed their professional experiences, work-related needs, and views. Interviews were analysed using NVivo, following guidance from Braun and Clarke (2006) for reflexive thematic analysis. A holistic ecological systems framework for ED services was created, comprised of five levels of influence: intrinsic, intra-personal, departmental, systemic, and societal. These levels contain nine themes: [1] clinician motivation for working in ED services [2], complexities of ED management [3], clinician personality and emotional disposition [4], team dynamics [5], supervision, management, and organizational support [6], service-level concerns [7], macro-level systemic concerns [8], broader societal challenges in ED care, and [9] COVID-related challenges. Key concerns included the chronic nature and risk of EDs, growing service demands amid limited resources, and regulation through guidelines and commissioning targets. This presented framework illustrates the multifaceted array of complexities faced by ED clinicians. The interplay of personal, inter-personal, and systemic factors is explored, with clinicians' interest in and commitment to ED care at the core of the framework. These areas can be targeted to improve clinician job satisfaction and reduce burnout risk, with the goal to provide optimal patient care. This study explores the experiences and wellbeing of clinicians working in NHS eating disorder (ED) services. Through interviews with clinicians, the research explored both the positive and difficult parts of their job. While staff felt strongly committed to helping people with EDs, many also described feeling emotionally drained and frustrated. This was often due to high workloads, not enough resources, and long waiting lists. Clinicians found it especially hard when they had to follow strict service rules that didn’t work well for individual patients, and when they had to manage complex medical risks. Supportive teams and good supervision helped some staff cope. Wider problems like staff shortages, poor communication between services, and lack of funding compounded emotional strain. The findings show that ED clinicians urgently need more support, including better resources, more flexible ways of working, and proper training, to give safe, effective care without burning out.
Hidradenitis suppurativa (HS), an inflammatory skin disorder characterized by painful nodules and abscesses, has varying prevalence among different races/ethnicities. This study explored the social drivers of health, burden, and impact of HS among different racial and ethnic groups. An online, cross-sectional survey was conducted among adult patients with HS (September 2023-December 2023) in the USA. Patients were recruited through HS Connect (patient advocacy group) and AmeriSpeak (US national sample panel). Descriptive data were collected using patient-reported outcome measures and de novo questions about patients' disease knowledge and perception, healthcare access and utilization, impact on quality of life (QoL), and social impact. All analyses were descriptive and stratified by racial/ethnic groups. The study included 583 patients (mean age, 34.8 years; 95.5% female) representing a range of racial backgrounds: Black or African American (n = 273; 46.8%), white (n = 236; 40.5%), Two or More Races (n = 47; 8.1%), American Indian or Alaska Native (n = 18; 3.1%), Asian (n = 7; 1.2%), and Native Hawaiian and Other Pacific Islander (n = 2; 0.3%). Ethnic representation also varied (Hispanic/Latino = n = 76; 13.0%). Patients of all races and ethnicities reported considerable QoL impact (Dermatology Life Quality Index, EQ-5D-5L), with results for smaller subgroups (n < 10) included for descriptive completeness only and not intended for comparison with other groups. During flaring, most patients used over-the-counter products/medications (54.2%) or nonmedical intervention/home remedy (56.9%) Up to 36.5% of patients reported challenges in procuring food, utilities, medicine/healthcare, phone, clothing, or childcare when needed in the past year. Among those who paid out-of-pocket for their HS treatment, 55.6% reported that it stopped them from visiting a healthcare provider for treatment. The findings indicate a high burden and impact of HS across all races and ethnicities. Patients reported social drivers of health and challenges with healthcare utilization, indicating the need for integrating social workers and care management teams in dermatology practice, which could facilitate improved care of patients with HS. Hidradenitis suppurativa is a painful skin condition that causes lumps and abscesses. It affects people of all races and ethnicities but is more common in Black or African American individuals. This study surveyed 583 adults in the USA to understand how hidradenitis suppurativa affects people from different racial and ethnic backgrounds. Our focus was on how the disease impacts their daily lives, their ability to access healthcare, how often they visit doctors, their quality of life, and their mental and emotional well-being. Most people said that hidradenitis suppurativa lowers their quality of life and makes daily activities harder. During flaring, many used home remedies instead of seeing a doctor. People suffering from hidradenitis suppurativa also reported trouble getting basic needs such as food, medicine, and transportation. These challenges occurred among patients from different racial and ethnic groups; results for very small subgroups (Asian, Native Hawaiian/Other Pacific Islander) are reported descriptively only and should not be interpreted as representative of these groups or compared with other groups. The research underscores the importance of improving awareness and tailoring care for people with hidradenitis suppurativa, particularly those facing barriers to healthcare.
The progressive skeletal muscle degeneration observed in Duchenne Muscular Dystrophy (DMD) patients requires multiple cycles of satellite cells (SCs) activation to promote tissue regeneration. Dystrophic SCs present intrinsic defects, and the disrupting fibrotic niche hinders appropriate muscle recovery. Traditional 2D culture systems face challenges in modeling the DMD muscle niche and SCs behavior. Our aim was to validate a 3D culture of skeletal muscle spheroids (iSMS) for DMD modeling, as compared to the traditional 2D culture, while investigating the pathophysiological mechanisms of dystrophin deficiency in vitro. To compare iSMS with traditional 2D myogenic differentiation, we differentiated wild-type (WT), dystrophic (DMD) isogenic induced pluripotent stem cells (iPSCs), as well as iPSCs derived from DMD patients, characterized myogenic markers levels and assessed differences in proliferation and differentiation using RT-qPCR, immunofluorescence, and flow cytometry. Our data showed that iSMS improved PAX7 expression in vitro, while MYOD1, MYOG, MYF5, and MYH3 expression were significantly reduced. These findings suggest that, at three weeks of myogenic differentiation, iSMS cultures retained satellite-like cells in a less activated, progenitor-like state. Accordingly, we identified higher expression of canonical Notch signaling genes such as JAG1 and NOTCH1 in iSMS compared to 2D. We also characterized the response of 2D and iSMS to terminal differentiation medium, providing a valuable comparison with muscle fibers derived from human adult myoblasts. Additionally, we showed that DMD iSMS-derived progenitors proliferated at reduced levels compared with WT, a characteristic not observed in progenitors derived from 2D cultures. Finally, we performed iSMS and 2D myogenic differentiation of iPSC lines from three patients with DMD. Our results highlight important advantages of using the iSMS differentiation platform over 2D for DMD in vitro modeling. Exploring these 3D systems may help to gain a deeper understanding of SCs behavior to advance in novel treatments for DMD, which might be applicable to other forms of muscular disorders.
Mental health conditions account for 18% of years lived with disability worldwide. 1-in-6 adults are affected in England, with most mental health conditions beginning in childhood and adolescence. Mental distress and ill health are unequally distributed in the UK, with strong associations with wider determinants of health, and higher prevalence among systemically disadvantaged groups. Currently, there is a lack of evidence to inform effective and timely policymaking for primary prevention in the UK. In recognition of these challenges, a national Population Mental Health (PMH) Consortium was established, as part of Population Health Improvement UK (PHIUK). PHIUK is a national research network which works to transform health and reduce inequalities through change at the population level. Our aim is to establish an interdisciplinary PMH Consortium, focussing on upstream determinants and the prevention of risks and onset of mental health conditions through interdisciplinary stakeholder engagement, to create new opportunities for population-based improvement of mental health in the UK.The PMH Consortium brings together leading interdisciplinary representation in population mental health, spanning from sciences to the arts, across the UK. Membership includes six academic institutions, third sector organisations, lived experience expertise, and strong links with national bodies to ensure integrated cross-national and regional policy impact. The PMH Consortium comprises four cross-cutting platforms (Partners in policy, implementation, and lived experience; Data, linkages, and causal inference; Narrowing inequalities; Training and capacity building) and three challenge areas (Children and young people's mental health; Prevention of suicide and self-harm; Multiple long-term conditions) which are highly integrated and interdependent. The work will be underpinned by a Theory of Change across an initial four-year life cycle. This paper describes the aim, objectives, and approach of the PMH Consortium, as well as anticipated challenges and strengths. The goal of the PMH Consortium is to develop a model for population mental health research and policy translation that is both scalable and sustainable. It is critical to ensure continued impact and viability beyond the initial four years, contributing to the prevention of mental health conditions in the UK, with personal, economic, social, and health benefits.
Therapeutic plasma exchange (TPE) is being increasingly utilized in the clinical management of severe rheumatic immune diseases, providing an effective means for rapidly removing pathogenic autoantibodies and inflammatory mediators. However, the non-selective nature of this technique can also lead to the unintended clearance of concomitantly administered antirheumatic drugs, potentially compromising therapeutic efficacy and disease control. Therefore, effective management of potential drug removal process during TPE and the implementation of individualized risk assessment are crucial for optimizing treatment outcomes in patients undergoing TPE. The variability in the extent of drug removal during TPE is primarily determined by their distinct pharmacokinetic characteristics, necessitating the establishment of a systematic, evidence-based strategy for adjusting drug administration regimens in patients receiving TPE treatment. This review synthesizes current evidence from 65 studies on the removal of antirheumatic drugs during TPE, identifying key determinants influencing clearance rates, including volume of distribution, protein binding, molecular size, and elimination half-life. Our analysis reveals that the risk of drug removal exists as a continuous spectrum: large monoclonal antibodies (e.g., rituximab, natalizumab), characterized by a large molecule size, low volume of distribution, with which mostly confined to the vascular space, are cleared with high efficiency. This finding supports the clinical recommendation of administering such drugs after TPE. For drugs with limited direct evidence, we propose a predictive model based on fundamental pharmacokinetic parameters to estimate their removal risk and guide clinical decision-making. Based on this evidence, we have constructed a stratified clinical management framework. It aims to maintain effective therapeutic drug exposure levels during chronic TPE therapy and to provide a rationale for the judicious application of TPE in overdose scenarios. Implementing this pharmacokinetic-informed, risk-adapted individualized strategy is important for ensuring treatment continuity, enhancing patient safety, and advancing empiricism-based therapy towards precision medicine.
The association between preoperative peripheral nerve block (PNB), major adverse cardiovascular events (MACE), and postoperative length of hospital stay (LOS) in elderly patients who underwent major thoracic and abdominal surgery remains unclear. This study aims to explore the potential mediating effect of MACE on the association between preoperative PNB and postoperative LOS using a statistical mediation framework. In this retrospective cohort study, perioperative data were collected from elderly patients (aged over 65 years) who underwent major thoracic and abdominal surgery. Mediation analysis was employed to examine the relationships between PNB, MACE, and postoperative LOS. A total of 1915 patients were included in the analysis, with 68.7% (1316/1915) receiving preoperative PNB. Compared to patients who did not receive PNB, those who did had a significantly lower incidence of MACE (P < 0.001) and a shorter postoperative LOS (P < 0.001). The adjusted total and direct associations of PNB with postoperative LOS were - 0.809 days (95% confidence interval [CI], -1.236 to -0.390; P < 0.001) and - 0.661 days (95% CI, -1.077 to -0.250; P = 0.003), respectively. A statistically significant indirect association via MACE was observed (adjusted β=-0.149 days; 95% CI, -0.271 to -0.060; P < 0.001), indicating that 18.1% (95% CI, 6.7% to 41.0%) of the total association was statistically attributable to the indirect pathway through MACE under the model assumptions. A sensitivity analysis excluding postoperative covariates yielded consistent results (proportion mediated: 25.3%). Our findings suggest that the observed association between preoperative PNB and reduced postoperative LOS in elderly patients following major thoracic and abdominal surgery may be partly explained by a statistically significant indirect pathway through a reduction in MACE, potentially accounting for approximately 18% of the total effect. These findings are hypothesis-generating and represent statistical associations rather than demonstrated causal mechanisms. ChiCTR2400087610; https://www.chictr.org.cn.
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Healthcare-seeking behavior is a key factor in how well a health system performs and how fair it is. In Saudi Arabia, public healthcare services are free, yet many people still choose private healthcare, especially in cities like Riyadh. It is important to understand why people seek care from private clinics to help shape health policies, distribute resources better, and improve services across the healthcare system. This study aimed to examine the frequency of private healthcare use, defined as the reported usual or concurrent use of private healthcare services, and to identify sociodemographic, behavioral, and health-related factors associated with this choice among adults in Riyadh, Saudi Arabia. A cross-sectional study was carried out in Riyadh from March to July 2023 using a multistage cluster sampling method. We randomly selected 48 government primary healthcare centers and invited adults aged 18 and older who visited these centers to participate. We collected data electronically with a validated questionnaire that covered sociodemographic details, patterns of healthcare use, reasons for choosing private healthcare, behavioral risk factors, and existing health conditions. We used multivariate logistic regression analysis to find independent predictors of private healthcare use, reporting adjusted odds ratios (AORs) and 95% confidence intervals (CIs). Of 14,239 participants, 72.4% reported using private healthcare services either as a usual source of care or alongside public services. The multivariable analysis revealed several factors to be positively related to private healthcare utilization. Those who were married were more likely to use private healthcare services (AOR 1.23, 95% CI 1.11-1.36). Those with insurance coverage were threefold higher odds of private healthcare use (AOR 3.51, 95% CI 3.13-3.94). Smokers were more likely to seek private healthcare (AOR 1.60, 95% CI 1.45-1.77) than non-smokers, and those who exercised reported increased utilization (AOR 1.83, 95% CI 1.67-2.00). Obesity was also positively related to private healthcare utilization (AOR 1.38, 95% CI 1.12-1.71), and those with heart disease had substantially higher odds of using private healthcare services (AOR 2.09, 95% CI 1.59-2.76). Private healthcare use in Riyadh is common and associated with insurance coverage, marital status, behavioral factors, and certain chronic conditions. These findings provide descriptive insights into factors related to private healthcare utilization among public PHC attendees in Riyadh, without implying causal effects or policy recommendations beyond the scope of the data.
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The gut microbiome supports digestion, immunity, and metabolism; its imbalance (dysbiosis) drives inflammation and metabolic dysfunction, contributing to chronic diseases such as diabetes, cardiovascular disease, inflammatory bowel disease, and autoimmune disorders. Medicinal plants provide a wide range of phytochemicals (such as polyphenols, flavonoids, alkaloids, saponins), which reach the colon and undergo two-sided interactions with microbes in the gut, acting as potential microbiome modulators and substrates of biotransformation into bioactive metabolites. This structured narrative review synthesises evidence from peer-reviewed studies indexed in PubMed, Scopus, and Web of Science over the last 10 years on the role of medicinal plants in microbiome-mediated chronic disease modulation. This literature is organised into three mechanistic axes: (i) perturbations, defined here as measurable shifts in microbial diversity or taxonomic composition relative to a baseline or healthy reference state, together with beneficial taxa enrichment; (ii) alterations in microbial metabolite output, especially short-chain fatty acids (SCFAs) and other immunometabolic mediators; and (iii) downstream host metabolic and immune signalling. Rather than broad descriptive summaries, the literature is organised using an axis-based mechanistic framework, highlighting key translational constraints such as botanical heterogeneity, dose/formulation variability, and inconsistent microbiome endpoint standardisation, that must be addressed to strengthen human evidence and clinical relevance. Illustrative microbiome-mediated processes involve botanicals such as turmeric (curcumin), ginseng (ginsenosides), and green tea (catechins), though evidence strength varies by study design. Future progress requires standardised phytochemical characterisation, microbiome-stratified trials, and integration of multi-omics with artificial intelligence analytics to enhance mechanistic insight, identify responders, and enable personalised plant-based microbiome therapies.
RNA modifications regulate post transcriptional gene expression, yet most computational methods model each modification independently and overlook competition among modification types at a single site. We present EvoRMD, a biologically contextualized and interpretable framework for RNA modification prediction. EvoRMD combines RNA language model embeddings with structured metadata, including species, organ, cell type, and subcellular localization, and uses attention to identify informative sequence positions. A shared multiclass classifier produces context conditioned predictions across 11 modification types. EvoRMD achieves strong performance and provides interpretable insights through attention patterns and motif analyses, supporting biologically grounded prioritization of candidate RNA modifications.
Chronic low back pain (CLBP) is a prevalent condition with unclear pathophysiology and substantial socioeconomic burden. Cerebral blood flow (CBF) alterations have been implicated in CLBP, yet previous arterial spin labeling (ASL) studies using single post-labeling delay (PLD) have yielded inconsistent results. In this study, multi-PLD ASL was combined with machine learning to characterize CBF alterations in CLBP and to explore their classification feasibility. Seventy-eight patients with CLBP and seventy-eight age- and sex-matched healthy controls underwent multi-PLD ASL scanning. Voxel-wise comparisons of normalized CBF were performed, followed by correlation analyses with clinical measures. Radiomics features extracted from brain regions showing significant CBF differences were used to construct machine learning classification models via a rigorous nested cross-validation and LASSO feature selection framework. Compared with healthy controls, patients with CLBP exhibited significant hyperperfusion in the right lingual gyrus and right thalamus. CBF values in the right lingual gyrus were positively correlated with Oswestry Disability Index scores, while thalamic CBF was positively correlated with pain intensity. Among the evaluated models, the XGBoost classifier achieved the best performance, with an area under the curve of 0.842 (95% CI: 0.774-0.901). These findings indicate that region-specific CBF alterations are closely associated with pain severity and functional impairment in CLBP. Machine learning analysis of CBF radiomic features shows potential discriminative performance in identifying patients with CLBP.
Cutaneous gene therapy has the potential to treat a wide range of skin disorders, but effective delivery remains limited by the skin's barrier properties and immune surveillance. Here, we identify AAVrh32.33 as a potent vector for targeting dermal stromal compartments. Following systemic administration in mice, AAVrh32.33 mediated robust and durable transgene expression, with preferential targeting of dermal fibroblasts and hair follicle bulge cells. Expression peaked at one month and persisted for up to two years, highlighting its suitability for chronic conditions. To reduce immunogenicity, a dominant CD8+ T cell epitope was disrupted, generating the IDPΔ variant. This modification attenuated peptide-specific T cell responses while preserving stromal transduction. In human skin explants, IDPΔ achieved high levels of gene expression, primarily in dermal fibroblasts and precursors, confirming translational relevance. Finally, vectors encoding CCL17, CCL20, and CCL22 demonstrated localized targeted therapeutic gene delivery in both healthy and inflamed skin, underscoring the feasibility of using this platform to reshape local immune responses. Together, these findings establish AAVrh32.33 and IDPΔ as promising platforms for durable cutaneous gene therapy, with direct applications in diseases such as vitiligo where long-term modulation of the dermal microenvironment is essential.
Osteosarcoma typically arises during adolescence, posing a significant challenge. Despite comprehensive treatment strategies encompassing surgery, radiation therapy, and chemotherapy, which can notably enhance long-term survival rates among osteosarcoma patients, the 5-year survival rate for metastatic cases remains discouragingly low. Consequently, early diagnosis and prompt intervention are paramount in improving the prognosis of patients afflicted with this condition. Metabolic reprogramming holds paramount significance in the initiation and progression of tumors. In this meticulous investigation, we devised a risk prediction model that encompasses seven pivotal nucleotide metabolism-related genes: MYC, MUC1, IMPDH1, SAMHD1, NUDT13, UCK2, and NUDT16. This model was formulated leveraging six advanced machine learning algorithms. The results demonstrated that the risk prediction model exhibited robust prognostic predictive capability. Notably, patients identified with a high-risk phenotype exhibited a significantly lower long-term survival rate, coupled with elevated expression of immunosuppressive genes, highlighting the importance of metabolic reprogramming in influencing both survival outcomes and immune status. The multivariate Cox regression analysis confirmed that our model serves as an independent prognostic indicator, significantly impacting the long-term prognosis of osteosarcoma patients. Subsequently, we developed and validated a nomogram, which accurately predicts 1-, 3-, and 5-year survival rates for these patients. Furthermore, we compared chemosensitivity between high- and low-risk groups, gaining valuable insights into potential therapeutic differences. In conclusion, this model demonstrates superior prognostic predictive capability and holds promise in guiding chemotherapy treatment strategies for osteosarcoma patients, thereby enhancing treatment outcomes.