143174 research outputs found
Sort by
Lifestyle medicine in medical education: benefits for patients, communities, and our future medical workforce
No full textLifestyle Medicine (LM) is an increasingly important aspect of modern medical practice. LM focuses on sleep, healthy eating, physical activity, mental wellbeing, and the socioeconomic determinants of health. In 2019, Imperial College London introduced the ‘Lifestyle Medicine and Prevention’ (LMAP) module to educate medical students on these areas within a broader framework of public health ethics and practice. We hypothesised that early LM education may enhance students’ insight into their own health and wellbeing. Of 364 first-year medical students invited to complete an end-of-module survey, 278 consented to share their data and 239 responded to the open-ended question analysed: ‘Has your LMAP learning encouraged you to change any of your health behaviours? Please explain how’. Responses were analysed thematically. Of 239 responses, 155 students (66%) reported changes in their health behaviours after the LMAP module, 57 (24%) reported no change, and 27 (10%) described early contemplation of change. Lifestyle Medicine education may encourage reflection and positive health behaviour change amongst medical students
Protocol for a biomarker discovery study to identify correlates of risk for future tuberculosis disease progression in South African children (INTREPID)
No full textIntroduction
Young children and children living with HIV are at high risk of progressing to tuberculosis (TB) disease following Mycobacterium tuberculosis (Mtb) exposure and infection, and also of developing severe forms of disease and TB-related mortality. Identifying children who have very early (sub-clinical) TB disease, prior to progression to clinically apparent TB, would mean that TB preventive treatment (TPT) could be more efficiently targeted to this group. Identifying biomarker changes on drug therapy in children with Mtb infection or very early disease could pave the way for the development of tests that can identify which children have viable bacilli and are therefore at increased risk of disease progression.
Methods and analysis
The INTREPID study will utilize already collected samples taken from well-phenotyped paediatric cohorts in three clinical studies conducted in South Africa in children <5 years, including a drug-resistant TPT trial (TB-CHAMP), an observational household contact study (IGRA studies), and a prospective diagnostic study (Umoya), all conducted in a setting with a high burden of TB and HIV. We will employ transcriptomic, proteomic, metabolomic, and serology approaches to analyse changes in host blood profiles at every stage along the TB continuum, from Mtb exposure to disease and from children treated for Mtb infection and early TB disease, as well as targeted Mtb antibody analysis. Data on viral co-infections and relevant clinical and epidemiological parameters will be integrated and evaluated to identify the optimal biosignatures that can predict future progression to clinically overt disease in children below 5 years of age, including those living with HIV.
Ethics and dissemination
The study protocol received ethical approval from the Stellenbosch University Health Research Ethics Committee (N23/03/025). The study findings will be disseminated through peer-reviewed publications, scientific conferences, and formal presentations to healthcare professionals and to local communities, in collaboration with the Desmond Tutu TB Centre Community Advisory Board (DTTC CAB)
Multi-Level Monte Carlo training of neural operators
No full textOperator learning is a rapidly growing field that aims to approximate nonlinear operators related to partial differential equations (PDEs) using neural operators. These rely on discretization of input and output functions and are, usually, expensive to train for large-scale problems at
high-resolution. Motivated by this, we present a Multi-Level Monte Carlo (MLMC) approach to train neural operators by leveraging a hierarchy of resolutions of function dicretization. Our framework relies on using gradient corrections from fewer samples of fine-resolution data to decrease the computational cost of training while
maintaining a high level accuracy. The proposed MLMC training procedure can be applied to any architecture accepting multi-resolution data. Our numerical experiments on a range of state-of-the-art models and test-cases
demonstrate improved computational efficiency compared to traditional single-resolution training approaches, and highlight the existence of a Pareto curve between accuracy and computational time, related to the number of samples
per resolution
The influence of the Casimir effect on the binding potential for 3D wetting
No full textWe provide comprehensive details of how a previously overlooked entropic, or low temperature Casimir contribution, WC , to the total binding potential for 3D short-ranged wetting may be determined from a microscopic Landau-Ginzburg-Wilson Hamiltonian. The entropic contribution comes from the many microscopic configurations corresponding to a given interfacial one, which arise from bulk-like fluctuations about the mean-field (MF) constrained profile, and adds to the usual MF con-
tribution WM F . We determine the functional dependence of WC on the interface (and wall) shape using a boundary integral method which can be cast as a diagrammatic expansion with each diagram corresponding to successively higher-order exponentially decaying contributions. The decay of WC is qualitatively different for first-order and critical wetting with the change in form occurring at the MF tricritical point. Including the Casimir contribution to the binding potential preserves the
global surface phase diagram but changes, radically, predictions for fluctuation effects at first-order and tricritical wetting, even when capillary-wave fluctuations are not considered
Structure-based virtual screening for TRPM8 modulators
No full textTransient receptor potential melastatin 8 (TRPM8) is an emerging therapeutic target, yet the performance of available structural models for docking and optimal docking protocols for virtual screening (VS) remains unclear. Here, we benchmarked two available TRPM8 structural conformations (agonist-bound TRPM87WRE and antagonist-bound TRPM89B6G) using docking tools, Smina and rDock, using known TRPM8 inhibitors and property-matched decoys. rDock achieved the highest hit rates and outperformed Smina in ranking true actives at first-ranks than their corresponding decoys, whereas Smina showed a target-structure dependence on docking performance but delivered superior overall ranking quality across both target structures. Both docking tools displayed considerable overlap between active and decoy score distributions, indicating only moderate discriminatory power of docking scores alone. When prioritizing a small subset of top-ranked compounds, integrated screening approaches, particularly the consensus protocol, improved the recovery of true actives, while the hierarchical protocol achieved comparable performance at a substantially lower computational cost. Collectively, this work establishes a reproducible VS benchmark for TRPM8 and supports the use of different screening protocols to improve early hit identification
Clinical characteristics and outcomes associated with preserved ratio impaired spirometry (PRISm) in Saudi Arabia
No full textBackground: Preserved ratio impaired spirometry (PRISm) is an abnormal spirometric pattern associated with increased morbidity and mortality. However, its psychological and symptomatic burden remains poorly characterized. This study aimed to: (1) assess the prevalence of anxiety, depression, breathlessness, impaired health status, and reduced quality of life; (2) evaluate the impact of psychological and respiratory symptoms on clinical outcomes; and (3) explore the associations of psychological and respiratory symptoms with clinical outcomes among patients with PRISm in Saudi Arabia.
Methods: Breathlessness was assessed using the modified Medical Research Council (mMRC) Dyspnea Scale. Symptoms of anxiety and depression were evaluated using the Hospital Anxiety and Depression Scale (HADS). Quality of life was measured using the St. George’s Respiratory Questionnaire (SGRQ). Overall health status and the impact of respiratory symptoms on daily activities were assessed using the Chronic Airways Assessment Test (CAAT).
Results: A total of 101 patients with PRISm met our inclusion criteria and were included in the analysis. Of these patients, 38 (37.6%) exhibited symptoms of anxiety, and 27 (26.7%) exhibited symptoms of depression. Furthermore, 45 (44.5%) demonstrated impacts in association with PRISm on their health status, 37 (36.6%) had increased levels of breathlessness, and 67 (66.3%) had impaired quality of life. PRISm subjects with uncontrolled respiratory symptoms have reduced health status and increased levels of psychological symptoms compared with those with controlled symptoms. In addition, quality of life, health status, and respiratory symptoms were significantly impaired in subjects with depressive or anxious symptoms compared with those without depression or anxiety. Although no associations were observed with hospital-based outcomes, depression was associated with a higher number of comorbidities.
Conclusions: Our study demonstrates that individuals with PRISm face substantial respiratory and psychological difficulties, including elevated anxiety and depression levels, as well as frequent hospitalizations. Given that PRISm is underdiagnosed and underappreciated with no clear guidelines on treatment plans, these findings underscore the critical need for routine assessments and comprehensive management strategies to enhance quality of life for PRISm patient
Optimizing ChemBL-derived QSAR models for natural flavonoid screening: chemotype-specific predictive reliability in α-glucosidase inhibition
No full textα-Glucosidase inhibitors (AGIs) are therapeutic agents for postprandial glucose regulation, where flavonoids represent a major class of natural AGIs. Existing QSAR models often fail to generalize to natural compounds due to limited chemical space overlap. This study aimed to construct and evaluate Random Forest–based QSAR models trained on ChEMBL-derived α-glucosidase inhibitors and to determine their applicability natural flavonoids. All inhibitors from ChEMBL were curated into two datasets, one containing all scaffolds and another containing flavonoid-only. A custom RDKit-based classification pipeline automatically identified flavonoid chemotypes using SMARTS pattern recognition and fingerprint similarity, excluding nonphenolic compounds. Molecular descriptors were computed via Mordred, and regression and classification models were developed using 10-fold cross-validation. External validation employed 15 natural flavonoids from literature, categorized into four structural groups: (1) flavones/flavonols (aglycones), (2) flavonol glycosides (1–2 sugars), (3) isoflavones, and (4) flavan-3-ols. The general model trained on 563 diverse compounds achieved high regression (R2 = 0.837), while the flavonoid-specific model showed moderate regression performance (R2 = 0.564). The classification performance was higher for the general model than the flavonoid-specific model (accuracies of 0.915 and 0.880, respectively). When validated with external dataset, the flavonoid-specific model showed better predictive performance than the general model. The flavonoid-specific model is the most suitable for predicting pIC50 of catechins and aglycones (MAE = 0.182 and 0.233, respectively). The optimized QSAR model reliably predicts the inhibitory potential of natural flavones and flavonols (aglycones) but should be used cautiously for glycosides and isoflavones. The trained model is available online on https://github.com/bryangervais/QSAR-Predictor
Comparative cross-species transcriptomics during RSV infection identifies targets to treat RSV disease
No full textRespiratory syncytial virus (RSV) remains a health threat to young children worldwide. The host immune response plays a key role in disease following infection. Infection models advance our understanding of respiratory viruses, but individual models have gaps, which overlapping complementary systems can fill. We compared disease signatures in mice, adults and children; combining transcriptomic data collected from blood, nasal mucosa and lung biopsy following RSV infection. We identified both shared and species-specific pathways triggered by RSV. While systemic responses in children’s blood were more similar to those in RSV-challenged adults, mucosal responses during primary infection in mice more closely resembled those in children. We identified an association between IL-17 pathways and RSV pathogenesis and with over-expression of the downstream effectors S100A8 and S100A9. Inhibiting these with the anti-inflammatory drug Paquinimod reduced disease. Here we demonstrate that integrating mouse and human transcriptomic data can identify novel targets to treat RSV disease
HISTONCHO: A dataset of intervention histories for onchocerciasis control & elimination in sub-Saharan Africa
No full textIn sub-Saharan Africa (SSA), onchocerciasis control has been implemented for many decades, beginning in 1974 under the Onchocerciasis Control Programme in West Africa (OCP) and in 1995 in Central and East Africa (plus Liberia) under the African Programme for Onchocerciasis Control (APOC). Since the establishment of the Expanded Special Project for Elimination of Neglected Tropical Diseases (ESPEN) in 2016, data on mass drug administration (MDA) with ivermectin has been centrally compiled for all endemic countries at implementation unit (IU) level, beginning in 2013. This paper presents HISTONCHO, a dataset collating detailed information on interventions, including vector control, from 1975 through to 2022, using the ESPEN portal (2013-2022), regional and country reports, implementation partners’ records, and published literature. Reconstructing such intervention histories is crucial for an understanding of their evolution, modelling their impact, and tailoring future interventions. We discuss strengths and limitations associated with the ESPEN database, and how HISTONCHO can be improved to support modelling of intervention strategies as well as onchocerciasis control and elimination efforts by endemic country programmes
Patient organizations involvement in healthcare: a rapid review and conceptual framework
No full textBackground: Patient organizations have become increasingly influential in the healthcare sector, offering unique insights into unmet health needs, disease impact, and patients’ quality of life. These groups have evolved from advocates for access to treatment, as seen during the HIV/AIDS crisis, to active participants in the research and policy-making processes. Despite growing recognition of their critical role, a comprehensive understanding of their interactions with various healthcare actors remains limited.
Main Body: This rapid review aims to map the landscape of patient organization involvement in healthcare, particularly in high-income settings. We conducted a systematic search of MEDLINE, focusing on literature published between 2000 and 2024, and identified 61 relevant articles. The analysis revealed that patient organizations interact with a range of actors, including pharmaceutical companies, healthcare professionals, payers, health technology assessment bodies, and regulatory agencies. Key themes were identified around conflicts of interest, especially with regards to the pharmaceutical industry, where concerns about transparency and independence were prevalent. The review also highlighted the vital role patient organizations play in research and development, regulatory approval processes, and reimbursement decisions. The conceptual framework developed from this review outlines these interactions across the pharmaceutical lifecycle, emphasizing the varied and significant contributions of patient organizations.
Conclusion: This review underscores the need for more transparency and meaningful engagement of patient organizations in healthcare decision-making. While their involvement has been primarily studied in the context of pharmaceutical industry relations, further research is needed to explore their interactions with other relevant actors. Addressing funding challenges and expanding research beyond well-studied regions are crucial for fully understanding and optimizing the role of patient organizations in healthcare