SEARCH · Search PubMed

Results for “Robust optimisation”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

191 recordsLinked to original sources

PubMed2026

Robust optimisation for photon radiotherapy: A scoping review of models, paradigms, and reporting.

BACKGROUND AND PURPOSE: Robust optimisation offers an alternative to conventional margin-based photon radiotherapy planning by explicitly modelling uncertainty, but practice is variable and not standardised. MATERIALS AND METHODS: A scoping review was conducted to map robust optimisation for photon external beam radiotherapy. Electronic searches of Scopus, PubMed and Google Scholar (2000-2025, English language) identified planning studies that incorporated modelled uncertainties into the optimisation process and reported at least one robustness-related outcome. Data were charted on clinical context, uncertainty models, optimisation paradigms, robustness metrics and evidence for clinical implementation. RESULTS: Seventy-one studies were included. Most investigated prostate, breast or lung cancer and used intensity-modulated radiotherapy or volumetric-modulated arc therapy in commercial or research treatment planning systems. Scenario-based worst-case (minimax) optimisation was the dominant paradigm in clinically oriented work, while chance-constrained, conditional value at-risk, distributionally robust and adaptive formulations were confined to small methodological series. Uncertainty modelling focused mainly on rigid set-up error; fewer studies incorporated respiratory motion, inter-fraction anatomical change, dose-calculation uncertainty or biological variation. Robustness was evaluated with diverse scenario-based dose-volume metrics, probabilistic coverage measures, composite robustness indices and, less often, biological endpoints. Direct clinical implementation reports were scarce. CONCLUSION: Robust photon planning is technically feasible and generally maintains or improves target coverage and organ sparing compared with margin-based planning. However, heterogeneity in uncertainty models, optimisation configuration and robustness reporting limits comparison and synthesis. Pragmatic minimum standards are proposed to support future consensus and wider clinical adoption.

Humans↗

PubMed2026

Response-optimised training improves learning of a complex motor task and closely related motor tasks.

Regular physical exercise is essential for promoting healthy aging and longevity. In older adults with varying physical and cognitive decline, optimising exercise interventions is crucial to maximise benefits. A promising approach to achieve this goal is by adjusting task demands to individual abilities in turn preventing over- or underloading their abilities. In the field of motor learning, it is currently unclear whether such an optimised training improves not only performance on the trained task but also transfers to untrained motor and cognitive tasks. We conducted a randomized, single-blinded, 6-week dynamic balance training (DBT) with healthy older adults (n = 30). Training was tailored to individual balance ability. Participants were assigned to either suboptimal (high or low difficulty) or optimal (moderate difficulty) training groups. Transfer effects were assessed via cognitive tasks (memory and executive) and motor tasks (untrained DBT variations and other balance tasks) measured pre-, mid- and post-intervention. Multivariate longitudinal statistical analysis showed higher performance gains in the optimal training group in three out of six sessions compared to the suboptimal groups, especially under testing conditions with high task demands. The optimal group also showed greater improvements in near motor transfer tasks mid- and post-intervention, while no significant differences were observed in the cognitive tasks. Within-group DBT learning positively correlated with transfer gains, highlighting the role of training response in achieving transfer. In conclusion, optimised task difficulty in balance training enhances both task-specific performance and related motor skills, supporting the use of personalised interventions to maintain function and independence in older adults.

Humans↗

PubMed2026

Optimising Exercise Prescription: A Meta-Analysis Examining the Dose Response of Exercise Duration on Cardiorespiratory Fitness Following HIIT and MICT.

BACKGROUND: High-intensity interval training (HIIT) is often promoted as a time-efficient alternative to moderate-intensity continuous training (MICT) for improving cardiorespiratory fitness, yet the duration of HIIT sessions varies considerably across studies. OBJECTIVE: We aimed to characterise the dose-response relationship between exercise session duration and the improvement in cardiorespiratory fitness for HIIT and MICT. METHODS: A dose-response meta-analysis of randomised controlled trials comparing exercise duration in HIIT and MICT, following Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines and registered in PROSPERO (CRD42022335590). Effect sizes were calculated using a random-effects meta-analysis. The primary outcome was maximal oxygen uptake (VO2max). Secondary outcomes included blood pressure, lipid profiles, glucose metabolism markers and body composition measures. A one-stage random-effects dose-response meta-analysis was performed to examine the relationship between exercise duration and adaptations. We searched PubMed and Google Scholar; eligibility criteria for selecting studies were randomised controlled trials in humans, published in English and exercise interventions lasting at least 4 weeks. RESULTS: We identified 69 randomised controlled trials (2387 participants). High-intensity interval training elicited greater improvements in VO2max than MICT (d = 0.38, 95% confidence interval 0.27-0.49, p < 0.001). High-intensity interval training demonstrated a non-linear dose-response relationship between exercise session duration and VO2max, with 80% of maximal effect (changes in VO2max = 3.45 mL/kg/min) achieved with only ~11 min/session (95% confidence interval 9.5-40.2). Moderate-intensity interval training showed a linear dose-response relationship between exercise session duration and VO2max, requiring ~52 min/session to achieve 80% of the maximal observed effect (95% confidence interval 30.4-55.8). The dose-response relationship was consistent across populations. High-intensity interval training and MICT had comparable effects in improving cardiometabolic risk factors. CONCLUSIONS: High-intensity interval training demonstrated a non-linear dose response, with 80% of maximal effect on VO2max in ~11 min/session, whilst MICT required four to five times longer to reach similar responses. The different types of training had comparable effects on cardiometabolic risk factors.

Journal Article↗

PubMed2026

Behaviourally informed text message reminders to increase cervical screening attendance in people with severe mental illness: the OPTIMISE pilot randomised controlled trial.

OBJECTIVES: This study assessed the feasibility of both the delivery and evaluation of 'enhanced' (behaviourally informed) text message reminders containing links to existing co-designed resources supporting decision-making for people with severe mental illness (SMI) regarding attendance of cervical screening. DESIGN: A pilot randomised controlled trial (RCT). SETTING: 13 General Practice (GP) practices in London were recruited. PARTICIPANTS: GP practices identified people with SMI aged 24-64 years who were overdue cervical screening. Target sample size was 120 participants (60 per arm) based on existing guidance for pilot trials. INTERVENTION: In March 2025, participants were randomised (1:1) to receive either the enhanced (intervention) or the standard (control) SMS reminder. PRIMARY AND SECONDARY OUTCOME MEASURES: 18 weeks later, feasibility outcomes were collected (primary outcomes) and data analysis for a definitive RCT was rehearsed (secondary outcome). RESULTS: Of the 150 participants across 13 GP practices that were randomised (n=75 per arm), 132 (88%) texts delivered (intervention n=64/75 (85%), control n=68/75 (91%)). 10 practices (76.9%) provided follow-up data for 102 participants (intervention n=50, control n=52). Five participants (intervention n=4, control n=1) attended screening within the trial period. Participant survey response rate was low (9/132 (7%), intervention n=5, control n=4). Both SMS messages were low cost, with the intervention SMS a 50% higher cost to deliver (7.5p vs 5p per SMS). Primary feasibility measures of recruitment rate of GP practices (27%), retention of GP practices (77%) and participants (100%), SMS delivery (88%) and data completeness (64%) indicated viability, although survey response rate (7%) did not. CONCLUSIONS: Achieving adequate recruitment and retention, data completeness and comparable groups is viable with some amendments, although an alternative method is required to assess fidelity. Behaviourally informed SMS reminders are feasible to deliver to people with SMI, although it is uncertain if the extra resources are accessed and used. With changes to data collection, a definitive trial could be feasible. Given the low observed cervical screening attendance, additional intervention is needed for this group. TRIAL REGISTRATION NUMBER: ISRCTN12558681.

Humans↗

PubMed2026

Retrosigmoid craniotomy surgical guide: The way forward for precise exposure of the transverse-sigmoid sinuses.

INTRODUCTION: The retrosigmoid craniotomy is the workhorse approach to the cerebellopontine angle. Accurate localisation of the transverse-sigmoid junction (TSJ) is key for optimised exposure and cerebellar retraction. Various methods, both anatomical and navigational, have been used but with suboptimal results. We utilised a 3D-printed retrosigmoid surgical guide in an attempt to overcome this and report our early outcomes and experiences in the design, production and utilisation of the guide. METHODS: This is a prospective cohort study of the patients with retrosigmoid craniotomies performed using the surgical guides. Patient demographics and diagnoses, along with the accuracy of the planned burrhole and craniotomy, need for craniotomy extension, presence of venous sinus injury, set-up time, and cost were reported. RESULTS: There were ten cerebellopontine angle cases in which the surgical guides were utilised, three petrous meningiomas, two trigeminal neuralgias, two metastasis, and three other tumours. The planned burrhole and craniotomy were precise in all cases with accurate exposure of the TSJ and no requirement for craniotomy extension. The mean set up time was 3.9 min, and the mean cost of the surgical guides was USD 470.90. One elderly patient had an intraoperative transverse sinus injury related to adherent dura that was planned for exposure. CONCLUSION: The 3D-printed surgical guide is a potential solution to the rapid, precise and consistent identification of the TSJ when performing a retrosigmoid craniotomy. We present our early experience and discuss nuances in the designing, production, and intraoperative phases to optimise the precision of this guide. We suggest two methods to avoid sinus injury in elderly patients: either to plan the craniotomy to the edge of the sinus, or to plan sinus exposure but to use burr drills rather than the osteotome, as in our case, to expose the sinus.

Humans↗

PubMed2026

Precision targeting of teacher burnout using network-informed ecological momentary interventions.

Teacher well-being affects classroom functioning and workforce stability, yet generic digital programs rarely use person-specific affect dynamics to select support. This cluster-randomised trial evaluated whether micro-interventions selected from high expected influence (EI) nodes in teachers' contemporaneous affect networks produced larger changes in burnout-related EI and everyday happiness than content-matched random allocation. The objectives were to estimate allocation effects on changes in estimated network summaries and happiness, evaluate network change as a statistical mediator, examine personality moderation, and benchmark simpler allocation rules. A two-arm cluster randomised platform trial was conducted in 84 public schools across four urban districts in H Province. After a 14 day baseline of ecological momentary assessment (EMA), person specific partial correlation networks were estimated for happiness, exhaustion, detachment, efficacy and rumination. An optimisation engine prioritised three brief micro-intervention types per teacher according to baseline EI, while the active control received the same library without network information. EMA continued for 8 weeks; Bayesian multilevel models, permutation-based mediation, and benchmarking analyses were applied. EI-based targeting produced larger reductions in the composite EI-change index than active control (mean difference 0.11, 95% credible interval 0.08 to 0.14) and higher week 7 EMA happiness (4.4 points on a 0 to 100 scale, 95% credible interval 2.7 to 6.0), with a positive arm by week slope difference of 0.62 points per week (95% credible interval 0.39 to 0.85). Model-based mediation estimates were consistent with approximately one half of the happiness difference being statistically associated with change in the composite EI-change index (average conditional mediation estimate 3.5 points, 95% credible interval 2.0 to 5.2). Benchmarking showed smaller gains under severity, threshold, or group-level centrality rules. Effects were stronger among teachers higher in conscientiousness. The findings indicate that integrating EMA, network modelling, and EI-driven optimisation yields measurable gains beyond content-matched exposure, providing a proof of concept for district-scale precision mental health that requires prospective implementation testing. Replication in additional regions, expanded node sets, and longer follow up are warranted to assess durability and generalisability.

Female↗

PubMed2026

Flavoromics-based profiling reveals taste and aroma differences between infant formula and breast milk.

Flavor differences between infant formula (IF) and breast milk (BM) are considered a potential factor affecting infants' acceptance of IF. This experiment employs flavoromics combined with multivariate statistical analysis to systematically compare the flavor profiles of IF and BM. Electronic tongue analysis and amino acid correlation revealed that IF was characterised by pronounced saltiness and umami richness, whereas BM exhibited greater bitterness and astringency. Volatile compound profiling identified five key flavor constituents in IF, predominantly aldehydes such as hexanal and pentanal. In contrast, BM contained a broader array of compounds-including acids, aldehydes, and esters-resulting in a more complex flavor profile. Kyoto Encyclopedia of Genes and Genomes (KEGG)-based metabolic pathway annotation, together with fatty acid profiling, suggested that some volatiles may be associated with lipid oxidation, Maillard reaction and sulfur-containing amino acid degradation pathways, offering a theoretical basis for the targeted optimisation of IF flavor.

Humans↗

PubMed2026

Orbital involvement in sickle cell disease: A systematic review.

Orbital involvement in sickle cell disease (SCD) is rare but potentially vision-threatening and is often misdiagnosed due to overlap with infectious orbital disease. We conducted a systematic review of case reports and series describing orbital complications in patients with confirmed SCD, following PRISMA and MOOSE guidelines. Across 53 studies, 76 cases were identified. Patients were predominantly male (77.6%), with an average age of 13.2 years. Orbital disease was the initial SCD manifestation in 6.6%. Presentations included periorbital edema in all, proptosis in 64.1%, restricted ocular motility in 56.5%, reduced visual acuity in 28.1%, and bilateral involvement in 38.2%. Laboratory findings commonly included leukocytosis (73%) and raised inflammatory markers (86.7%). Radiologically, orbital subperiosteal hematoma were observed in 70%, combined orbital bone infarction and hematoma in 38.2%, and orbital bone infarction alone in 19.7%. Magnetic resonance imaging is critical for accurate diagnosis. Intracranial hemorrhage was present in 9.2%. Less frequent manifestations included orbital apex syndrome, lacrimal gland disease, and nonspecific soft tissue swelling. Management was primarily conservative (82.9%), and surgery was reserved for vision-threatening or intracranial complications. Complete recovery was achieved in 93.1% of cases. While severe vision-threatening complications are uncommon, early recognition remains critical to optimising outcomes in sickle cell orbitopathy.

Humans↗

PubMed2026

Continuous Intraperitoneal Insulin Infusion for People With Type 1 Diabetes: A Literature Review and International Position Statement.

Achieving glucose targets without hypoglycaemia is the treatment goal in type 1 diabetes. Structured education, intensified insulin injection regimens, continuous glucose monitoring, automated insulin delivery, and ongoing support from a multidisciplinary team all support people with type 1 diabetes to achieve this goal. Despite these advances, significant barriers to achieving optimal management remain. Continuous intraperitoneal insulin infusion has comparable or better glucose outcomes to continuous subcutaneous insulin infusion and may reduce the frequency of hypoglycaemia, including severe episodes. Intraperitoneal insulin may be considered as a treatment modality for children and adults with type 1 diabetes using optimised intensive insulin therapy for whom subcutaneous insulin has failed due to lipoatrophy, -dystrophy or -hypertrophy, local allergy, subcutaneous insulin resistance or co-existing skin conditions. Failure of subcutaneous insulin may result in recurrent or unexplained severe hypoglycaemia or hyperglycaemia. Intraperitoneal insulin may also be considered as a treatment modality for people with type 1 diabetes with severe needle-phobia, and for those being considered for islet cell or pancreatic transplantation, or where transplantation is not available. This paper summarises current intraperitoneal insulin delivery technology, its potential risks and benefits, and an expert position statement. It is intended for use by diabetes specialist healthcare professionals, and as a reference for other healthcare professionals, commissioners, payors, people with diabetes, their carers, and advocates.

Humans↗

PubMed2026

Strategies to improve recruitment to randomised trials.

BACKGROUND: Recruiting participants to randomised controlled trials (RCTs) is challenging. Identifying effective recruitment strategies would benefit health research: poor recruitment leads to underpowered trials, reducing the reliability of findings and increasing the risk of wasted resources, ethical concerns, and trial failure. Evidence to inform recruitment strategies is increasingly generated through Studies Within A Trial (SWATs), which are methodological studies embedded within host RCTs. This is an update of a review last published in 2018. OBJECTIVES: Primary: to quantify the effects of strategies to improve recruitment of participants to RCTs. Secondary: to evaluate recruitment strategies' cost-effectiveness and impact on retention, and the equity, diversity, and inclusion (EDI) characteristics of recruited participants. SEARCH METHODS: We used MEDLINE, Embase, and six other databases to identify the studies included in the review. We also sought unpublished recruitment SWATs through social media and targeted email dissemination to trial methodology networks. The latest search date was 16 February 2023. SELECTION CRITERIA: We included randomised SWATs evaluating trial recruitment strategies embedded in healthcare and non-healthcare trials. We excluded quasi-randomised, hypothetical, questionnaire-only, retention-only, or clinician incentive studies. DATA COLLECTION AND ANALYSIS: Primary outcome: proportion of eligible participants or centres recruited. SECONDARY OUTCOMES: cost-effectiveness, retention rates, and EDI characteristics of included participants. We conducted random-effects meta-analysis for strategies evaluated in at least two studies; otherwise, we synthesised results narratively. We reported effects as risk differences (RDs) with 95% confidence intervals (CIs), and assessed between-trial heterogeneity. We used GRADE to assess the certainty of evidence for the primary outcome. We expressed cost-effectiveness as the incremental cost per additional participant recruited in pounds sterling (GBP). MAIN RESULTS: We identified 91 eligible studies (53 new to this update), providing 94 comparisons and involving at least 176,747 participants. Eighty-one studies involved strategies aimed at trial participants, while 10 evaluated strategies aimed at recruiters. All were healthcare studies. We found 65 recruitment strategies; 49 were evaluated in a single study. Only five strategies were supported by high-certainty evidence according to GRADE criteria, and we focus on these strategies in the summary below. Open-label trials versus blinded, placebo trials. Open-label trials recruited more participants than blinded trials (RD 10%, 95% CI 8% to 12%; 3 studies, 9004 participants), corresponding to approximately 10 additional participants per 100 approached. The studies involved mostly women in the UK and Estonia. No cost or retention data were reported. Telephone reminder versus no telephone reminder. Telephone reminders to people who did not respond to an initial postal invitation boosted recruitment by 6% (95% CI 3% to 9%; 2 studies, 1450 participants), in trials with low underlying recruitment (we are less certain for trials with over 10% recruitment). The studies involved people with a mean age of 58 years in Canada and Norway. No cost or retention data were reported. Recruitment primer letter versus no letter. Pre-recruitment letters and leaflets designed to encourage participation made little or no difference to recruitment (absolute improvement 1%, 95% CI -1% to 2%; 2 studies, 5376 participants), and were associated with increased costs compared to not sending a primer (incremental cost: GBP 2.08). The studies involved mostly older white people in the UK and Ireland. Multimedia information via a digital link/QR code plus paper participant information leaflet (PIL) versus paper PIL alone. This made little or no difference to recruitment (absolute improvement 0%, 95% CI -1% to 1%; 7 studies, 11,612 participants) and retention (absolute improvement 0%, 95% CI -2% to 3%; 5 studies, 7403 participants), and increased costs compared to not including multimedia information (incremental cost: GBP 0.78). The studies involved people in the UK. Optimised, user-tested PIL versus standard PIL. Optimising participant information leaflets (e.g. through user-testing the leaflet with the target population to shape its content, format, and appearance) made little or no difference to recruitment: absolute improvement was 0% (95% CI 0% to 1%; 6 studies, 27,805 participants). The studies involved people in the UK. Only one study reported EDI data; participants were mostly older women. No cost or retention data were reported. We had moderate-certainty evidence for 13 other strategies; confidence was often reduced because the results came from single studies. Seven strategies involved changes to how potential participants received information; four involved changes to trial conduct; one targeted the recruiter or recruitment site; and one tested non-monetary incentives. We had much less confidence in the other 47 comparisons because the studies had design flaws, were single studies, or had very uncertain results. Costs were reported in only 17 of 91 studies. Strategy impact on retention was reported in 15 studies. All but one study (99%) were from high-income countries. The most reported demographics were age (49 studies), sex (32 studies), gender (27 studies), and education level (16 studies). AUTHORS' CONCLUSIONS: The evidence on strategies to improve trial recruitment remains broad but lacks depth. Of 65 strategies evaluated, only five were supported by high-certainty evidence. Open-label trial designs and telephone reminders to non-responders increased recruitment, while optimised participant information leaflets, recruitment primer letters, and multimedia information provided alongside a paper participant information leaflet had little or no effect. Reporting of participant characteristics was poor, limiting assessment of equity, diversity, and inclusion across most studies. Evidence is heavily skewed toward high-income countries. Future research must prioritise evaluations in low-to-middle-income settings and consistently report cost, retention, and EDI outcomes. We strongly urge the methodology research community to strengthen the evidence base by prioritising replications of existing strategies over the development and testing of new ones. FUNDING: National Institute for Health and Care Research (Advanced Fellowship, Adwoa Parker, reference:NIHR302256). Health Research Board, Republic of Ireland, Evidence Synthesis Ireland (grant ESI-2021-001) REGISTRATION: This review updates an earlier Cochrane review, which was first published in 2002 and subsequently updated in 2007, 2010, and 2018. Previous versions of the review and their protocols are available at: https://doi.org/10.1002/14651858.MR000013.pub2 https://doi.org/10.1002/14651858.MR000013.pub3 https://doi.org/10.1002/14651858.MR000013.pub4 https://doi.org/10.1002/14651858.MR000013.pub5 https://doi.org/10.1002/14651858.MR000013.pub6.

Randomized Controlled Trials as Topic↗

PubMed2026

Mitigating pH-induced instability in deruxtecan-based ADCs: an onboard-mixing icIEF approach for robust charge heterogeneity characterization.

Accurate charge variant analysis of antibody-drug conjugates (ADCs) is essential for understanding product heterogeneity and ensuring quality control. However, Deruxtecan (DXd)-based ADCs present a unique analytical challenge due to the intrinsic instability of the payload, where the lactone ring readily undergoes hydrolysis under alkaline conditions, resulting in time-dependent shifts in charge distribution during imaged capillary isoelectric focusing (icIEF). In this study, we describe the development of an onboard-mixing icIEF method designed to minimize pH-induced degradation during sample preparation. By separating ADC samples from carrier ampholytes (CAs) prior to injection and enabling real-time mixing within the instrument, this approach effectively suppresses premature lactone ring opening and stabilizes charge variant profiles. Comparative studies between conventional premixing and onboard-mixing approach demonstrated that the latter significantly enhances reproducibility, particularly for acidic variants that are highly sensitive to structural conversion. Comprehensive method validation confirmed excellent precision, linearity, and sensitivity, with consistent performance across run-to-run and intra-day analyses. The results underscore the importance of controlling microenvironmental pH exposure in the analysis of chemically instable ADCs. The proposed onboard-mixing strategy provides a robust and efficient solution for icIEF-based characterization, reducing analytical artifacts while simplifying method development. This approach is broadly applicable to ADCs and other biotherapeutics containing pH-sensitive functional groups.

Hydrogen-Ion Concentration↗

PubMed2026

Mul-PheG2P: decoupled learning and prediction-space fusion enables robust and interpretable multi-phenotype genomic prediction.

Genomic prediction of multiple phenotypes is crucial in modern plant breeding; however, existing methods struggle with negative transfer and lack interpretability, particularly across high-dimensional small-sample data and diverse species. To address this, we propose Mul-PheG2P, a novel paradigm based on decoupled learning and predictive space fusion. It employs a two-stage design: first training phenotype-specific encoders using genetic data, then decoupling phenotype-specific learning from cross-phenotype aggregation via an interpretable prediction layer. Mul-PheG2P outperforms existing methods across diverse crop datasets, including maize (Zea mays), wheat (Triticum aestivum), and tomato (Solanum lycopersicum). It provides a multi-scale interpretability chain: at the macro level, it quantifies phenotypic contributions via attention-based weighting; at the micro level, Integrated Gradients reveal the genetic basis of predictions. Notably, the model successfully identified the CCT (CONSTANS, CO-like, and TOC) motif regulating photoperiodism and the SQUAMOSA (SQUAMOSA promoter binding protein) promoter for inflorescence development, confirming its ability to capture functional biological mechanisms. These results highlight the high performance and interpretability of Mul-PheG2P, showcasing its value for low-cost, large-scale screening to advance precision breeding.

Phenotype↗

PubMed2026

Data-centric, robust, and explainable multimodal deep learning for clinical decision support: A systematic review.

PURPOSE: Multimodal deep learning is increasingly proposed for clinical decision support (CDS) under a "data-centric" framing that prioritizes label quality, missing-modality robustness, distribution shift, calibration, and explainability. Prior reviews have examined multimodal medical AI, CDS, and data-centric methods separately, but none address their intersection. We mapped the modalities, fusion strategies, and data-centric and explainability techniques used in this recent literature, quantified how often each is implemented rather than merely mentioned, assessed deployment-relevant evidence (external validation, clinical-outcome measurement, equity), and formally appraised study-level risk of bias. METHODS: Following the PRISMA 2020 statement (PROSPERO CRD420261427815; registered retrospectively), we screened 150 records and included primary, clinical, multimodal studies that applied machine or deep learning to a decision-support task and reported at least one quantitative result. Two reviewers screened and extracted data with consensus adjudication. Each study was coded against pre-specified operational definitions, separating implemented or empirically evaluated techniques from those only mentioned. Study-level risk of bias was assessed with PROBAST + AI. Synthesis was narrative. RESULTS: Thirty-one studies met inclusion; 30 (97%) were published between 2024 and 2026, with a median of three modalities (range 2-6), most commonly structured EHR (71%) and imaging (39%). Data-centric techniques were frequently reported (74-84% across label-noise, distribution-shift, calibration, missing-modality and class-imbalance handling; equity 61%). However, external validation was reported in only 4/31 studies (13%), a clinical or provider outcome in 3/31 (10%), and no study reported routine deployment. Overall risk of bias was high in 27/31 studies (87%), driven by the analysis domain. CONCLUSION: Within this recent, self-selected slice of the field, technical robustness and explainability techniques are widely reported but rarely validated out-of-distribution or against clinical outcomes, and the underlying evidence is at high risk of bias. Progress requires external multi-site validation, clinical-outcome measurement, formal bias appraisal, and adherence to AI reporting standards (e.g., TRIPOD + AI) before deployment can be justified.

Deep Learning↗

PubMed2026

Predicting training outcomes for developmental dyslexia from EEG data.

Developmental dyslexia (DD) is characterised by lower-than-average reading abilities and is diagnosed in approximately 10% of individuals. The societal barriers may limit professional fulfilment and psychological wellbeing of individuals with DD, calling for the development of effective interventions to counteract them. As DD is associated with challenges in both phonological and visuo-attentional domains, different longitudinal training approaches were developed to strengthen them. However, they require a considerable amount of personal, social and economic resources and the outcomes may vary depending on individual differences in behavioural and neurophysiological functionality. Hence, predicting training outcomes might help in developing personalised treatment protocols and optimising the use of resources. In the present work we applied machine learning to resting-state EEG to predict longitudinal training outcomes in adults with DD enrolled in a randomized clinical trial. In particular, one group received a visuo-attentional training combined with transcranial alternating current stimulation (tACS), another group received visuo-attentional training with sham/placebo stimulation, and the third group received a phonological training with sham/placebo stimulation. The improvement in text reading speed was associated with spectral power in low-beta and individual frequencies in the alpha (IAF) and beta (IBF) bands, while the improvement in pseudoword reading was associated with IBF. The findings highlight the potential of capturing neural markers of treatment responsiveness in DD. Future studies should focus on the generalisability of predictive models to real-world settings, while investigating whether specific EEG markers predict responsiveness to distinct remediation protocols, thus supporting the development of personalised interventions.

Humans↗

PubMed2026

Germline variants and impact on lung cancer outcomes following chemotherapy: A systematic review.

BACKGROUND: Lung cancer is the primary cause of cancer deaths in the UK and globally, and the main subtypes are non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC). Many treatment options are available, with platinum-based chemotherapy being a key component for many patients. However, variation in survival outcomes exists among individuals of European ancestry, which makes it important to identify germline genetic variants that help guide decision-making and optimise patient treatment and outcomes. METHOD: A systematic literature search was conducted in PubMed and Web of Science for lung cancer studies investigating the impact of germline genetic variants on systemic anti-cancer therapy (SACT) outcomes in populations of European ancestry. The review was conducted according to the Preferred Reporting Items of Systematic Review and Meta-Analysis (PRISMA) and Synthesis without Meta-Analysis (SWiM) guidelines. RESULTS: A total of 20 studies were included in the review out of 4469 on NSCLC and SCLC, encompassing 3639 patients. The most thoroughly investigated area was NSCLC treated with platinum-based chemotherapy. Genetic variants associated with overall survival and/or progression-free survival included XPD Lys751Gln, XPD Asp312Asn, ERCC1 C118T, and XRCC1 Arg399Gln. For non-platinum-treated NSCLC and SCLC, there was insufficient evidence to conduct a meaningful investigation. CONCLUSION: The XPD Lys751Gln, XPD Asp312Asn, ERCC1 C118T, and XRCC1 Arg399Gln variants showed potential associations with survival outcomes among patients of European ancestry with NSCLC after platinum-based chemotherapy. To support clinical implementation, large real-world pharmacogenomics studies stratified by ancestry are needed to overcome statistical power and heterogeneity limitations.

Humans↗

PubMed2026

Meta-PseU: A meta-classifier for robust prediction of RNA pseudouridine modification sites from long sequences.

BACKGROUND AND OBJECTIVES: Pseudouridine (Ψ) represents one of the most abundant and conserved RNA modifications. Ψ provides an additional hydrogen-bond donor that enhances RNA structural stability and modulates translation. It participates in diverse biological processes, including RNA-protein interactions, splicing, translational control, and stress responses. Aberrant pseudouridylation is implicated in cancer, neurodegenerative disorders, and autoimmune diseases. Despite its biological importance, experimental identification of Ψ sites remains time-consuming and costly, limiting the feasibility of transcriptome-wide profiling. Computational approaches have therefore become essential complements to experimental techniques. However, state-of-the-art machine-learning and deep-learning predictors often suffer from limited generalizability due to small training datasets. To overcome these issues, we aim at constructing new long-sequence datasets and developing a novel Ψ site predictor. METHODS: New long-sequence datasets were constructed as benchmarks for RNA Ψ-site prediction. The Ψ modification sites in RMBase 3.0 were mapped to the reference genomes across three species of human, mouse, and yeast, and the RNA sequences with a length of 201 were generated by extending the upstream and downstream from the mapped, central sites. To eliminate sequence redundancy, the sequences were clustered using CD-HIT with a 70% sequence identity threshold. We developed Meta-PseU, a logistic regression-based meta-classifier that considered 118 machine learning and deep learning classifiers. The datasets and programs are freely accessible at https://github.com/kuratahiroyuki/MetaPseU. RESULTS: By optimizing model configuration, we proposed the Meta-PseU model stacking 32 machine learning and deep learning classifiers out of 118 classifiers. Meta-PseU substantially improved model generalizability, overcoming a key limitation of existing approaches. It greatly outperformed state-of-the-art predictors and achieved increasing accuracy with increasing sequence length. CONCLUSIONS: Long-sequence datasets were newly constructed as benchmarks for RNA Ψ-site prediction. Meta-PseU offers a new framework for robust Ψ-site identification by using long sequences.

Pseudouridine↗

PubMed2026

Robust error-minimization in the genetic code across physicochemical metrics and variant codes: A graph-theoretic analysis in GF(2)6.

The standard genetic code reduces the impact of point mutations, but the robustness of this property across physicochemical metrics, naturally occurring variant codes, and codon-reassignment mechanisms remains incompletely quantified. Embedding the 64 codons in GF(2)6 represents the hypercube Q6 as a coordinate-dependent subgraph of the encoding-independent single-nucleotide mutation graph H(3,4), and enables continuous ρ-interpolation between the two. Under a quartet-pattern shuffle null (n=10,000), the standard code is significantly low-cost across four established, code-independent physicochemical distance metrics with partially overlapping content (Grant ham p=0.0062; Miyata p<0.001; Woese polar requirement p=0.003; Kyte-Doolittle hydropathy p=0.001), and the signal strengthens monotonically as ρ moves Q6→H(3,4). A structure-aware sensitivity analysis under the alignment-derived ProtSub matrix (Jia & Jernigan 2021) yields the most extreme percentile of any measure tested (p=0.0004; all five p-values pass Bonferroni at α=0.05). Across the 27 NCBI translation tables, near-optimality is preserved: 11 of 12 informative-distance variants retain top-5% placement after BH-FDR correction. Natural codon reassignments avoid disrupting codon-family connectivity: under the encoding-independent H(3,4) adjacency, observed events are topology-breaking at relative risk 0.32 versus the candidate landscape (permutation p≤10-4). The H(3,4) result is stable by construction; the Q6 decomposition is representation-specific and fails to show depletion under 8 of 24 base-to-bit encodings, so we report H(3,4) as the primary test and Q6 as a sensitivity. Event-level conditional-logit modelling shows that topology avoidance and local physicochemical cost provide complementary, only weakly correlated signal (rs=0.15), and that topology adds explanatory value beyond physicochemistry under both Q6 and encoding-independent H(3,4) adjacency. Retrospective reanalysis of nine genome-recoding datasets is consistent with codon-family topology operating as an evolutionary-trajectory constraint distinct from acute engineering fitness. The contribution is the second axis: code evolution is jointly constrained by physicochemical smoothness and codon-family topological integrity, and these two constraints are partly independent.

Codon reassignment↗

PubMed2026

Pre-transport dietary chitosan improves the physiological robustness of juvenile largemouth bass (Micropterus salmoides) by modulating antioxidant and inflammatory responses.

The acute stress caused by long-distance transport can lead to oxidative damage, immune dysfunction, and health deterioration in fish. This study evaluated dietary chitosan as a pre-transport nutritional strategy for juvenile largemouth bass (Micropterus salmoides). Five experimental diets contained chitosan at 0, 2.5, 5.0, 7.5, or 10.0 g/kg, designated as p0, p25, p50, p75, and p100, respectively, for 56 d. The effects of dietary chitosan were evaluated using growth performance, feed utilization, digestive function, antioxidant capacity, nonspecific immunity, and resistance to Aeromonas hydrophila infection. Then, fish from the p0 and p50 groups underwent a 12-h transport stress test, with samples collected before, during, and 7 d after transport. Dietary chitosan improved most of these parameters. Among the treatment groups, p50 and p75 showed the best overall performance. The dose-response analysis further indicated that the appropriate dietary inclusion range was 5.0-7.5 g/kg. Under transport stress, fish in the p50 group exhibited more stable antioxidant enzyme responses and lower lipid peroxidation, as indicated by reduced MDA levels. Consistent with these enzyme responses, antioxidant-related genes remained relatively stable. At the same time, expression patterns related to the Nrf2-Keap1 and NF-κB signaling pathways suggested that 5.0 g/kg chitosan alleviated transport-induced oxidative damage and inflammation. Dietary chitosan also attenuated pro-inflammatory gene induction and altered the temporal expression patterns of anti-inflammatory genes. Overall, 5.0-7.5 g/kg dietary chitosan is suitable for juvenile largemouth bass, and 5.0 g/kg may serve as an effective pre-transport dietary inclusion level.

Animals↗