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In silico identification of DNMT1 inhibitors from the PlantCyc database through computational approach to assess the anti-cancer potential of nutraceutical compounds in breast cancer.

Breast cancer accounts for a disproportionate share of global cancer-related deaths, with 670,000 fatalities and 2.3 million new diagnoses recorded in women during 2022 alone. Existing treatment modalities carry considerable toxicity burdens, and resistance to available agents remains an unresolved clinical problem. DNA methyltransferase 1 (DNMT1), the enzyme chiefly responsible for maintaining genome-wide methylation patterns during DNA replication, has been mapped out as a high-value target in breast cancer because its dysregulation silences tumour suppressor genes through promoter hypermethylation. The present work involves hierarchical in silico workflow to screen 4549 plant-derived compounds from the PlantCyc database (v16.0.3) against the human DNMT1 catalytic domain (PDB ID: 4WXX). Ten top-scoring compounds were taken forward for molecular docking via AutoDock Vina; Quercetin and Kaempferol both recorded the highest binding affinities at -9.5 kcal/mol, Wogonin (-9.3 kcal/mol) and Xanthohumol (-8.1 kcal/mol) also emerged as strong binders. Pharmacokinetic evaluation using ADMET-AI confirmed that all 10 compounds met Lipinski's rule of five, with human intestinal absorption values at or above 0.98. Wogonin and Xanthohumol were selected for a 100 ns all-atom molecular dynamics (MD) simulation in GROMACS due to their well-rounded ADMET profiles and limited existing data on their specific interactions with DNMT1 in breast cancer. Across all measured trajectory metrics, backbone RMSD, residue fluctuation, radius of gyration, solvent-accessible surface area, and intermolecular hydrogen bond count, Wogonin formed a more stable, compact complex. These findings suggest that Wogonin and Xanthohumol are non-toxic nutraceutical candidates suitable for DNMT1 targeted epigenetic therapy, with computational foundation strong enough to facilitate future in vitro and in vivo validation work.

Humans

Contact tracing for hepatitis C: perspectives of people with experience of substance use and hepatitis C on intervention acceptability.

INTRODUCTION: Chronic hepatitis C (HCV) is a major cause of cirrhosis and hepatocellular carcinoma. In the UK, the principal risk factor for HCV is injecting drug use. The introduction of direct acting anti-virals (DAA's) have transformed HCV care, with cure rates of over 95%. However, HCV is often asymptomatic, and reinfection is a concern. Modelling and real-life studies demonstrate the potential effectiveness of a contact tracing approach for finding people who have acquired HCV through injecting drug use. However, it is not used routinely in the UK. This qualitative study was undertaken to assess the acceptability of a contact tracing approach to identify people who have injected drugs with an index patient recently diagnosed with HCV. METHODS: Twelve people with lived or living experience of injecting drug use and an HCV diagnosis were interviewed using semi-structured interview topic guides. Participants were purposefully selected according to the inclusion criteria and to ensure there was an even spread of male and female participants. Sekhon's Theoretical Framework of Acceptability, incorporating seven components (affective attitude, burden, ethicality, intervention coherence, opportunity cost, perceived effectiveness, and self-efficacy) was used to analyse data from interview transcripts. RESULTS: A sample of 12 people who inject drugs in the UK indicated that a contact tracing approach was acceptable across two components of Sekhon's acceptability framework: affective attitude and ethicality. Participants broadly found the idea of tracing people who may be at risk of contracting HCV acceptable, and the approach aligned with their value systems. A contact tracing approach would help alleviate concerns about putting other people's lives at risk through HCV transmission and was seen as a 'sensible' way of finding people at risk. However, there were caveats to this acceptability. Contact tracing approaches delivered by mainstream health, or governmental organisations increased burden, opportunity costs and perceived effectiveness of a contact tracing approach for HCV, particularly within contexts of exclusion and criminalisation of people who inject drugs. Burden and opportunity costs were also affected by individual experiences and risks of violence, sexual violence and abuse. There was a lack of knowledge of contact tracing approaches amongst respondents, leading to a lack of intervention coherence and misunderstandings of what contact tracing was and how it would work. Trusted relationships with NGOs and HCV specialist nurses reduced burden and increased confidence and ability (self-efficacy) to engage with a contact tracing approach. CONCLUSION: People who inject drugs broadly perceive contact tracing as an acceptable method of finding people who are at risk of HCV. However, this acceptability is based on specific modes of delivery through trusted organisations. Findings further highlight the importance of naming and describing contact tracing approaches appropriately, as well as assessing and mitigating against potential risk to index patients, to increase self-efficacy and capacity to engage. Considering these findings, the potential for expanding existing contact tracing approaches should be explored to ensure the UK reaches and maintains its elimination targets.

Humans

A systematic approach to standardizing the visual appearance of endometriotic lesions for artificial intelligence recognition.

INTRODUCTION: Numerous studies have shown that the diagnostic performance and reproducibility of visual recognition of endometriosis during laparoscopy are poor. The use of artificial intelligence (AI) seems relevant for exhaustive lesion recognition. Standardization of the visual classification of lesions, in the form of an ontology, is an essential prerequisite to enable medical experts to annotate surgical data consistently and subsequently allow engineers to train and build an artificial intelligence tool for endometriosis recognition. MATERIAL AND METHODS: A systematic search was conducted in the MEDLINE (via PubMed), EMBASE, and the Cochrane Library databases up to May 2022, aiming to identify studies describing the laparoscopic visual appearance of superficial endometriosis, endometriomas, and deep infiltrating endometriosis. The accumulated data in the literature concerning the visual appearance of the different forms of endometriosis were used to create an ontology that could be used for artificial intelligence applications. RESULTS: Out of 932 articles screened, 35 studies were selected based on the inclusion criteria of human subjects with histologically confirmed endometriosis lesions visualized via laparoscopy. The selected studies were reviewed to develop a visual ontology of endometriosis lesions observed via laparoscopy. The lesions were categorized into 4 classes and further subdivided into 11 subclasses: superficial (black, red, white, or subtle), adhesions (dense or filmy), deep (obliteration, retraction, or deformation), and ovarian (endometrioma or chocolate fluid). The positive predictive value (PPV) varied across lesion types: black lesions (PPV 47%-97%), red lesions (PPV 33%-100%), white lesions (PPV 20%-81%), and ovarian endometriosis (PPV 42%-98%). Nonspecific lesions such as adhesions (PPV 16%-50%) and subtle superficial lesions (PPV 0%-67%) presented lower PPVs. Deep endometriosis lesions, often buried within organs, required indirect signs (obliteration, retraction, deformation) for identification. CONCLUSIONS: The visual ontology proposed in this systematic search could facilitate the detection and classification of endometriosis lesions using artificial intelligence. This study highlights the challenges of reaching a consensus on lesion recognition and classification in AI projects due to the diverse visual presentations of endometriosis.

Humans

Clinical Performance of Bulk-Fill Versus Incremental Composite Placement Approaches in Vital Posterior Teeth: A 24 Months Randomized Controlled Trial.

BACKGROUND: Composite resin placement technique may influence marginal integrity, polymerization stress distribution, and long-term clinical performance of posterior restorations. This randomized controlled clinical trial evaluated the 24-month clinical performance of four different placement techniques in Class I posterior composite restorations. METHODS: Fifty patients aged 20-35&#x2009;years presenting with four occlusal carious lesions each were enrolled, resulting in 200 restorations. Cavities (4-5&#x2009;mm depth) were prepared according to caries extension. Restorations were randomly allocated into four equal groups (n&#x2009;=&#x2009;50) according to placement technique: stamp technique, snowplow technique, modified incremental "pizza" technique, and bulk-fill technique. All materials were applied following manufacturers' instructions. Clinical evaluation was performed at baseline and after 6, 12, and 24&#x2009;months using FDI criteria. Functional (fracture/retention, marginal adaptation), esthetic (marginal staining, anatomical form), and biological (postoperative sensitivity, secondary caries) properties were assessed by two calibrated evaluators. Statistical analysis was performed at a significance level of &#x3b1;&#x2009;=&#x2009;0.05. RESULTS: Thirty-eight patients with a total of 152 restorations were evaluated at the end of the 24&#x2009;months in line with FDI at the end of the study with 76% recall rates. No statistically significant differences were observed among groups regarding fracture/retention or secondary caries (p&#x2009;>&#x2009;0.05). Marginal adaptation and marginal staining demonstrated minor deterioration over time across all groups, with statistically significant intergroup differences found (p&#x2009;<&#x2009;0.05). Postoperative sensitivity was minimal and transient in all groups with no significant difference (p&#x2009;=&#x2009;0.181). CONCLUSIONS: Within the limitations of this 24-month follow-up, the four placement techniques demonstrated comparable clinical performance in Class I posterior composite restorations. Selection of technique may therefore be guided by clinical preference and procedural efficiency rather than differences in short-term clinical outcomes. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT07415317.

Humans

Exploring Immersive Virtual Reality as an Approach to Improve School Participation-Related Constructs in Children With ADHD.

BACKGROUND: School participation is frequency and involvement from person-environment transactions, not diagnosis, per the International Classification of Functioning, Disability and Health (ICF) and the family of participation-related constructs (fPRC). In this framework, the environmental and child determinants of school participation (e.g., school routines and peer/teacher context; self-regulation, activity competence and preferences) interact bidirectionally to shape everyday participation. However, many interventions still target isolated impairments, overlooking coordinated changes in capacities and context. Grounded in this contemporary view, this study aimed to investigate the impact of an immersive virtual reality (IVR) intervention on school participation-related constructs in children with ADHD. METHODS: The study included 92 children aged between 7 and 12&#x2009;years diagnosed with ADHD. Participants were randomly assigned into intervention (n&#x2009;=&#x2009;46) and control (n&#x2009;=&#x2009;46) groups. Both groups completed the School Participation Questionnaire (SPQ) and Bruininks-Oseretsky Test of Motor Proficiency Test 2 Brief Form (BOT2-BF) assessment prior to the intervention. The intervention group received an IVR intervention program twice a week for 8 weeks. During this period, the control group did not receive additional therapy. At the end of the 8 weeks, the SPQ was readministered to both groups. RESULTS: Baseline characteristics showed no significant differences in SPQ and BOT2-BF results between groups, confirming homogeneity prior to intervention. Following the intervention, the study group demonstrated significant improvements across all domains of the SPQ (doing, being, symptoms and environment), with large effect sizes for SPQ total score (d&#x2009;=&#x2009;0.978) and subdomains (d&#x2009;=&#x2009;0.452-0.910). In contrast, the control group showed no improvements and even declines in subdomains. Post-intervention, between-group comparisons revealed significant differences favouring the study group across all domains (p&#x2009;<&#x2009;0.001), with large effect sizes (d&#x2009;=&#x2009;0.878-1.165). CONCLUSIONS: Findings suggest that the IVR program was associated with improvements in teacher-rated environmental and child determinants of school participation (SPQ domains) in children with ADHD.

Humans

Integration of ear and hearing care services in low- and middle-income health systems: a systematic review and qualitative synthesis.

Hearing loss is a global public health burden and mostly affects those living in low- and middle-income countries (LMICs). One approach to address ongoing challenges is the World Health Organization's recommendation for the integration of ear and hearing care (EHC) services into healthcare packages. However, little is known about EHC integration approaches, particularly in LMICs additionally, these approaches have not been investigated through a health systems lens. This qualitative review aimed to describe the various approaches to the EHC service integration in LMICs and to identify enabling and constraining factors. We reviewed 17 studies, with a focus on LMICs, using adaptations of the Valentijn integration and World Health Organization EHC frameworks, following the PRISMA guidelines. Our investigation showed that most integration approaches were at micro or individual level. Enabling factors for integration of EHC services were training, mentorship, collaboration, technology, inclusion of EHC in healthcare packages and investment in EHC services. Barriers were challenges with training, facilities and equipment, policy implementation and resourcing of EHC services. We further described factors influencing healthcare seeking behaviour and the use of integrated EHC services, such as access and ability to pay, referral systems and communication and awareness. This study describes the complex nature of EHC integration and ways to support integration. Key considerations are the level of integration, training to address workforce issues and factors influencing service utilisation as we work towards health system strengthening.

Humans

Review of regulatory requirements for benefit-risk assessment for medical devices: uncovering existing methodologies.

INTRODUCTION: A positive benefit-risk profile is a prerequisite for the market approval of medical devices. However, regulations are often criticized for providing limited information on benefit-risk assessment (BRA) despite growing expectations for quantitative methods. A clearer understanding of regulatory requirements, existing methodologies, and unresolved issues is needed. AREAS COVERED: Relevant regulatory documents referencing BRA for medical devices were systematically identified, with a primary focus on the European regulation followed by screening to extract BRA&#x2011;related requirements and any explicitly or implicitly described methods. The findings were analyzed and consolidated by BRA context, type, objective, methodological description, and implementation, thereby establishing a basis for the BRA methodological landscape. EXPERT OPINION: BRA is not a single concept, but a set of context&#x2011;dependent assessments across lifecycle of a medical device. BRA within clinical evaluation framed into BRAs of risk management holds a pivotal role and is supported by the most detailed methodological guidance, although BRAs in other contexts are important. A structured overview of existing BRA requirements clarifies their treatment across regulatory documents. By differentiating BRA contexts, types, objectives, and required methodological detail, the analysis supports a more transparent understanding of BRA and helps identify priorities for methodological refinement and interface clarification.

Risk Assessment

Effectiveness of the DASH diet versus alternative dietary interventions for hypertension management: A systematic review and meta-analysis.

BACKGROUND: The Dietary Approaches to Stop Hypertension (DASH) diet is widely recommended for blood pressure control; however, its comparative effectiveness relative to other structured dietary interventions remains uncertain. OBJECTIVE: To evaluate the comparative effectiveness of the DASH diet versus alternative dietary interventions on blood pressure and cardiometabolic outcomes in adults. METHODS: A systematic review and meta-analysis of randomized controlled trials was conducted in accordance with PRISMA guidelines. Multiple databases were searched from inception to February 2026. Eligible studies included adults with elevated blood pressure or hypertension comparing the DASH diet with other dietary interventions or usual care. Continuous outcomes were pooled using random-effects models and expressed as mean differences (MD) or standardized mean differences (SMD). Risk of bias was assessed using the Cochrane RoB 2 tool, and certainty of evidence was evaluated using the GRADE approach. RESULTS: A total of 22 randomized controlled trials were included in the qualitative synthesis, of which 10 were included in the meta-analysis. The DASH diet did not demonstrate a statistically significant advantage over comparator diets in reducing systolic blood pressure (MD = 1.30; 95% CI: -1.54 to 4.14) or diastolic blood pressure (MD = 0.21; 95% CI: -3.72 to 4.14), with substantial heterogeneity observed across studies. Significant effects were identified for selected cardiometabolic outcomes, including reductions in urinary sodium excretion (MD = -32.89; 95% CI: -62.76 to -3.01), LDL cholesterol (MD = -8.59; 95% CI: -14.64 to -2.54), and glycated hemoglobin (HbA1c) (MD = -0.49; 95% CI: -0.52 to -0.46), as well as an increase in urinary potassium excretion (MD = 11.76; 95% CI: 4.08 to 19.44). The certainty of evidence ranged from moderate to very low across outcomes. CONCLUSIONS: The DASH diet was not superior to other dietary interventions in reducing blood pressure; however, it demonstrated consistent benefits in selected cardiometabolic parameters. Given the overall low certainty of evidence and substantial heterogeneity, these findings should be interpreted cautiously. Future research should focus on well-designed trials with standardized outcomes and longer follow-up to clarify comparative effectiveness.

Humans

Multi-omic biomarkers in cardiovascular disease: Discovery to clinical translation.

Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, necessitating improved risk stratification and early detection strategies. Multiomics approaches that integrate genomics, transcriptomics, proteomics, metabolomics, and epigenomics offer unprecedented opportunities for biomarker discovery and precision medicine in cardiovascular care. This narrative review examines the current landscape of multiomics biomarkers for CVD, tracing their evolution from discovery to clinical translation. We synthesize evidence from recent studies evaluating the clinical utility of integrated omics approaches across diverse cardiovascular conditions, including atherosclerotic cardiovascular disease, heart failure, and atrial fibrillation. High-throughput proteomics has identified novel protein signatures that enhance cardiovascular risk prediction beyond traditional risk factors. Metabolomics has revealed pathway-specific biomarkers, including trimethylamine N-oxide and lipid species, associated with atherogenesis. Polygenic risk scores derived from genomic data demonstrate incremental value when combined with clinical risk scores. Multiomics biomarkers represent a transformative approach to cardiovascular risk assessment and disease management.

Humans

Utility of Dynamic MRI in Surgical Outcome of Patients With Degenerative Cervical Myelopathy: A Single-Center, Randomized Controlled Trial.

BACKGROUND AND OBJECTIVES: The utility of dynamic MRI (dMRI) in surgical planning and outcomes for degenerative cervical myelopathy (DCM) has not been validated in any prospective randomized trials. METHODS: In this hospital-based randomized controlled trial conducted between February 2023 and December 2024, patients with DCM were randomized into 2 groups: the Static MRI Group, where surgery was guided by conventional static MRI alone, and the dMRI Group, in which dMRI was performed, with the potential to alter the surgical approach. The primary outcome was recovery rate (RR) at 3 months. Secondary outcomes included postoperative changes in modified Japanese Orthopaedic Association scores and Nurick grades, surgical plan alterations, comparison of surgical approaches, and complication rates. RESULTS: Seventy-four patients were analyzed at a 3-month follow-up. The dMRI group had a significantly higher mean RR (55.42% &#xb1; 29.05%) than the Static group (46.76% &#xb1; 29.51%) ( P = .044). A RR of &#x2265;50% was observed in 91.9% of patients in the dMRI group, compared with 59.4% in the static MRI group ( P = .002). Modified Japanese Orthopaedic Association scores improved more in the dMRI group (15.47 &#xb1; 2.62 vs 13.77 &#xb1; 2.66, P = .007). While Nurick grades improved in both groups, the intergroup difference was not statistically significant ( P = .151). dMRI altered the surgical plan in 59.5% of cases. Anterior approaches yielded better RR but had more complications. By contrast, posterior approaches had fewer but more severe complications including mortality. CONCLUSION: dMRI enhances the detection of clinically significant cord compression and may aid in surgical decision-making, potentially contributing to superior functional outcomes in DCM. Further studies are required to determine its impact on long-term functional outcomes.

Humans

An Assessment of Reliability Estimation Methods for Binomial Health Care Quality Measures.

We evaluated the performance of commonly used methods for estimating the reliability of binomial health care quality measures using simulated datasets spanning a range of performance score means and variances, numbers of entities, and patient sample sizes. For each simulation, reliability was estimated for all selected methods and compared with the known true reliability derived from the simulation parameters, with methods assessed on their accuracy and precision. Logistic regression with reliability estimated on the outcome scale demonstrated the highest accuracy and precision among all methods evaluated. The widely used Adams beta-binomial method performed poorly, although a modification recommended by Nieser and Harris substantially improved its performance. These approaches are applicable only to binomial measures. Among methods that can be applied to both binomial and continuous measures, permutation resampling of the Spearman rank correlation coefficient was the most accurate and precise, outperforming other commonly used approaches. Overall, for binomial quality measures, logistic regression on the outcome scale is the preferred method for reliability estimation, followed closely by the modified beta-binomial approach, while for non-binomial measures, permutation-based Spearman rank correlation appears to be the most suitable method.

Reproducibility of Results

Predictive evolutionary genomics: principles, validation, and practice.

Climate change and habitat loss are driving rapid evolutionary responses in populations world-wide, which creates an urgent need for evolutionary forecasting in conservation and agriculture. Such forecasting can be categorized into three time scales: trait-based models that use multivariate quantitative genetic equations to project correlated phenotypic responses up to c.&#xa0;20 generations, allele-based analyses that model allele frequency dynamics up to 100 generations, and composite adaptation scores that aggregate many small effects to yield predictions across longer horizons. However, these approaches have remained largely disconnected. Here, we present a Bayesian framework that integrates these three complementary approaches for evolutionary prediction. Our framework combines genomic, phenotypic, and environmental data to yield probabilistic predictions with explicit uncertainty. We show how predictive evolutionary forecasts can be validated with experimental evolution, field experimentation, historical specimens, and reciprocal transplants. These validated forecasts can help advance conservation and agricultural programmes by helping predict which populations are at risk of future extinction, optimizing breeding programmes for future climates, and planning ecosystem management under environmental change. By supporting a shift towards more predictive approaches in evolutionary biology, this framework may help improve our ability to manage biodiversity and food security in a changing world.

Genomics

Understanding and Usefulness of Effect Size and Certainty of Evidence: A Cross-Sectional Survey of Evidence-Based Practice Competencies Among US Registered Dietitians.

INTRODUCTION: Understanding of absolute and relative effect estimates, and determining effect size and certainty of evidence corresponding to effect estimates, represent fundamental evidence-based practice competencies that promote informed clinical decision-making. While research has been conducted in the medical profession, based on our literature review there is no published research on these competencies in the nutrition and dietetics profession. METHODS: Among registered dietitians, our main objectives were to assess (1) their understanding and perceived usefulness of three absolute and two relative effect estimate approaches to determine effect size, (2) their perceived usefulness of certainty of evidence, and (3) factors influencing their understanding and perceived usefulness. We conducted a web-based, cross-sectional survey by recruiting dietitians from the Academy of Nutrition and Dietetics (United States). Participants received effect estimates based on hypothetical dietary interventions vs. usual diet for reducing myocardial infarction risk. RESULTS: Of the 11,050 dietitians who received the survey link, 210 participated, and only completers (n&#x2009;=&#x2009;114) were included in our analysis. Participants demonstrated a similar understanding of the relative (27.6%) and absolute (27.5%) effect estimates, with Risk Difference being the best understood approach and Number Needed to Treat being the least (30.7% vs. 24.6% correct responses). While perceived usefulness scores were similar between five approaches, they were highest when data was presented as Relative Risk [mean (SD): 4.82 (1.50)]. Dietitians rated the usefulness of certainty of evidence favorably [mean (SD): 5.07 (1.83), on a 7-point scale], and no factors were associated with correct understanding. CONCLUSION: Dietitians may have limited understanding of effect size thresholds presented in our survey, a finding mostly consistent with surveys of other health professionals. To optimize informed decision-making between dietitians and clients, dietetic programs and continuing education platforms should consider additional training on effect estimate approaches (relative and absolute), and determining effect sizes and certainty of evidence for effect estimates.

Clinical nutrition

Comparison of conventional and micro-surgical techniques for gingival recession using collagen matrix: Randomised controlled split-mouth clinical trial.

BACKGROUND: The present study aimed to determine the effectiveness of the microsurgical approach in treating gingival recession with collagen matrix by comparing it with Conventional surgery in terms of clinical and patient-centered outcomes. METHODS: A total of 29 patients with bilateral gingival recession in the maxillary canine and/or premolar region were selected. After randomisation, bilateral recession sites were grouped into the test group (Microsurgery under 3.5 X magnification) and the control group (Conventional surgery). All the clinical and patient-reported parameters were recorded at baseline, 1, 3 and 6 months. RESULTS: Both groups showed statistically significant differences in terms of reduction in gingival recession height (GRH), gingival recession width (GRW), clinical attachment level gain (CAL gain), increase in keratinized tissue thickness (KTT) and keratinized tissue width (KTW) after 6 months. But intergroup comparison showed no significant difference in terms of clinical parameters. The only significant difference was noted in terms of patient-centred parameters (Patient satisfactory score, Hypersensitivity score, Root aesthetic scores), which favoured the microsurgical group. CONCLUSIONS: Both groups demonstrated comparable clinical improvement; However, Patient-centred parameters were significantly better with the Microsurgical approach. Selection of the surgical approach should balance patient needs with practical considerations like cost, time, and clinician proficiency.

Adult

Pricing Combination Therapies: A Systematic Review of Value Attribution, Cost-Sharing Mechanisms and Policy Frameworks.

BACKGROUND: Combination therapies are increasingly central to modern pharmacotherapy, particularly in oncology and other high-burden diseases. However, pharmaceutical pricing and reimbursement systems remain largely designed for single-product-single-indication interventions. When multiple patented medicines are used together, especially when owned by different manufacturers, conventional pricing frameworks may struggle to align prices with the value of the combination while preserving incentives for innovation and timely patient access. OBJECTIVE: To identify, describe, and critically assess the methods, models, and policy frameworks proposed in the literature to establish prices for combination therapies, with particular attention to value attribution mechanisms, cost-sharing arrangements between manufacturers, and budget impact considerations. METHODS: A systematic literature review was conducted in accordance with PRISMA guidelines and a pre-registered Open Science Framework protocol. Searches were performed in MEDLINE, Scopus, Web of Science, EconLit, CRD databases, and grey literature sources for publications up to July 2025. Eligible studies analysed pricing approaches, economic models, reimbursement mechanisms, or policy frameworks relevant to combination therapies, including more recent multi-indication pricing literature. Given the heterogeneity of the literature, findings were synthesized using a structured narrative and thematic approach. RESULTS: Sixty-nine studies met the inclusion criteria. The literature was dominated by conceptual and policy analyses, with relatively few empirical or implementation-oriented studies. Value attribution emerged as the central methodological challenge in pricing combination therapies. Several complementary approaches were proposed to operationalise value attribution, including adaptations of indication- or pathway-based pricing, manufacturer cost-sharing arrangements, managed entry agreements, and outcome-based reimbursement mechanisms. Empirical evidence suggests that health systems continue to rely primarily on pragmatic and often partial solutions rather than fully specified pricing frameworks. A complementary review of the multi-indication pricing literature indicates that, although the two fields address different pricing problems, they share important methodological and institutional lessons that can inform the development of pricing frameworks for combination therapies. CONCLUSIONS: The literature provides a growing repertoire of conceptual approaches for pricing combination therapies but limited empirical evidence on implementation. Pricing frameworks should place value attribution at their core while combining complementary policy mechanisms adapted to national pricing and reimbursement systems. Lessons from multi-indication pricing provide a valuable foundation but require additional governance mechanisms to address value attribution, multi-manufacturer negotiation, and implementation challenges specific to combination therapies.

Journal Article

Single-cell RNA sequencing provides further insights into the immunostimulatory action of freeze-dried Lactiplantibacillus plantarum on Penaeus vannamei shrimp.

Immunostimulation through dietary interventions opened new avenues in developing disease control and prevention tools for shrimp aquaculture. We have previously shown that feeding with freeze-dried Lactiplantibacillus plantarum (LAB) increased disease resistance of Penaeus vannamei against both Vibrio parahaemolyticus and white spot syndrome virus (WSSV) based on bulk RNA sequencing of shrimp gills. This tissue participates in ion transport and serves as a first line of defense against environmental stressors and pathogenic infections. However, characterization of their cell composition and functions remains limited. Here, we implemented a single-cell RNA sequencing approach to further gather insights into how feeding with freeze-dried LAB modulates host immunity which may not be evident with bulk RNA sequencing approach. A total of five clusters with unique transcriptional signatures were identified, corresponding to pillar cells, septal cells, and sessile hemocytes. Pseudo-bulk analyses at global- and cluster-levels showed differential expression of genes related to host immunity and metabolism. We further revealed how overall transcriptomic changes are not exclusively caused by gene expression changes but may also be driven by cell population dynamics. This study highlighted how single-cell RNA sequencing approach may shed light on the mechanisms of action of immunostimulants which may be masked in bulk transcriptome analyses.

Animals

Comparison of paralog identification methods and their impact on species tree topologies in target capture phylogenomics within the Sindora clade (Detarioideae: Leguminosae).

Target capture is a common method of generating high throughput DNA sequencing data for phylogenetic reconstruction of species relationships, for which single copy genes are usually most informative. However, a pervasive problem with target capture is that putatively single copy genes may in fact be paralogs resulting from gene duplication, which are problematic for phylogenetic inference because their evolutionary history may differ from the divergence history of species. Here, we use as a case study a target enrichment dataset of 88 species of Detarioideae (Leguminosae) with a focus on the Sindora clade to examine approaches for handling paralogs, including the built-in paralog handling functions in HybPiper and CAPTUS, plus subsequent steps using Putative Paralog Detection and the tree-based Yang & Smith orthology inference approach. We compare the paralogs flagged using these methods and verify their performance with BLAST mapping against a reference genome sequence of Sindora glabra, and then subsequently compare the species tree topologies produced across these methods. Our comparisons of paralogs flagged across the Sindora clade show that the Putative Paralog Detection pipeline was the most accurate in identifying paralogs in terms of its similarity to the BLAST mapping, followed by the built-in paralog identification function of CAPTUS. However, the results we recovered for the Detarioideae subfamily suggest that the largest differences in species tree topology resulted from the use of paralog-filtered alignments (such as with the Putative Paralog Detection pipeline and the Yang & Smith orthology inference approaches) rather than just by removing the sequences of identified paralogous genes. This was the true for HybPiper-assembled datasets but was not seen in CAPTUS-assembled datasets. In all comparisons, the topological differences caused by different paralog handling methods tended to be confined to clades where processes such as hybridisation and introgression are prevalent. Our study provides a roadmap to establish the best approach to identify, eliminate or separate paralogs in the absence of a chromosomally contiguous reference genome for a study group, and highlights the importance of careful data inspection and processing in addition to understanding the extent of paralogy and paralog characteristics (e.g. sequence divergence between copies) for their study group.

Phylogeny

Reliability-aware hierarchical learning for Chagas disease screening from 12-lead ECGs: tackling label uncertainty and class imbalance.

Objective.Chagas disease, a neglected tropical disease (NTD) with significant cardiovascular impact, remains underdiagnosed in resource-limited regions. Electrocardiogram (ECG) screening offers a low-cost tool for detecting cardiac involvement, yet algorithm development is challenged by label noise, data scarcity, and the latent nature of infection. This study proposes a robust ECG-based screening framework that explicitly addresses these constraints.Approach.We introduce aReliability-Aware Hierarchical Learningstrategy that calibrates supervision according to data provenance, prioritizing serology-confirmed labels over noisy self-reports. To mitigate data scarcity, we compare a specialized convolutional neural network (CNN) trained from scratch with a transfer learning approach based on a Spatio-Temporal ECG foundation Model (FM). Performance is evaluated across varying data scales, and the representation structure is analyzed to interpret model behavior.Main results.On the official hidden test set of the George B. Moody PhysioNet/Computing in Cardiology Challenge 2025, our approach achieved a Challenge Score of 0.163. We observe that while the specialized CNN performs competitively in data-rich regimes, the FM exhibits superior robustness in extreme low-resource settings. Furthermore, performance reaches a plateau imposed by underlying disease physiology. Bimodal score distributions suggest that models distinguish established cardiomyopathy from indeterminate infection, which remains electrophysiologically indistinguishable from healthy controls.Significance.These findings clarify both the potential and intrinsic limits of ECG-based AI screening for NTD-associated cardiac involvement. Reliability-aware supervision and data-efficient transfer learning provide a practical framework toward scalable and clinically meaningful ECG screening systems in resource-constrained environments.

Humans