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Contemporary surgical decision-making for hallux valgus and hallux rigidus in Switzerland: A national cross-sectional survey using standardized clinical scenarios.

BACKGROUND: Surgical management of hallux valgus and hallux rigidus is influenced by deformity severity, surgeon training, and evolving techniques. Previous surveys in Australia (2012), Switzerland (2015), and Israel (2023) using identical hypothetical cases demonstrated marked regional differences and a recent rise in minimally invasive Chevron-Akin (MICA). Whether these advances have altered contemporary Swiss practice remains unclear. METHODS: An electronic survey replicating the original questionnaire was distributed to members of the Swiss Foot and Ankle Society. Three standardized clinical cases were presented: mild hallux valgus, severe hallux valgus, and hallux valgus et rigidus. Respondents selected nonoperative versus operative management and specified procedures and fixation methods. Demographics, subspecialty training, and surgical volume were recorded. Current results were compared with prior Swiss data to assess temporal change. RESULTS: Eighty surgeons completed the survey (94% foot and ankle specialists). For mild hallux valgus, 87.7% recommended surgery; Scarf osteotomy remained most common (49.4%), followed by Chevron (21.0%) and Minimally Invasive Hallux Valgus correction (14.8%). Minimally Invasive adopters were predominantly mid-career (83% aged 41-50), high-volume surgeons. For severe hallux valgus, 95.1% favoured surgery; MTPJ arthrodesis was preferred (50.6% isolated; 11.1% with Lapidus), while Minimally Invasive Hallux Valgus correction was rarely chosen (2.5%). In hallux valgus et rigidus, 96% selected MTPJ fusion, most commonly plate-and-screw fixation (45.1%). Compared with 2015, fixation strategies evolved, yet procedure selection remained largely unchanged. CONCLUSION: Despite global expansion of minimally invasive bunion surgery, Swiss surgeons continue to favour established open techniques, particularly Scarf osteotomy and fusion-based strategies. Adoption of MIS remains limited and concentrated among high-volume, mid-career specialists, indicating a cautious national diffusion pattern. LEVEL OF EVIDENCE: IV, survey study.

Hallux Valgus

Is ophthalmology a pain-free career? A systematic review and meta-analysis of musculoskeletal pain among ophthalmologists.

OBJECTIVE: To estimate the pooled prevalence, anatomical distribution, and occupational impact of work-related musculoskeletal (MSK) pain among ophthalmologists, and to identify modifiable ergonomic risk factors. DESIGN: A systematic review and meta-analysis of published data. The protocol was preregistered (PROSPERO CRD42023422368) and reported in accordance with PRISMA. PARTICIPANTS: The participants were 6691 ophthalmologists from 21 studies. METHODS: Electronic databases (MEDLINE, Embase, Cochrane, and PubMed) were searched for peer-reviewed quantitative studies reporting MSK pain prevalence in ophthalmologists. Pooled estimates with 95% CI were calculated using random-effects models; heterogeneity was quantified using I². MAIN OUTCOME MEASURES: Prevalence of overall and site-specific MSK pain; effects on workload and productivity; prevalence of treatment or mitigation strategies. RESULTS: The pooled prevalence of any MSK pain was 70% (95% CI: 65%-75%; I² = 92%); neck (41%; 95% CI: 35%-47%; I² = 95%), lower back (36%; 95% CI: 32%-39%; I² = 87%), and shoulder pain (28%; 95% CI: 22%-35%; I² = 91%) were most common. Pain led to workload modification in up to 44% and contributed to reduced clinical volume, sick leave, or contemplation of early retirement. Forty-six percent (95% CI: 22%-71%) pursued no treatment; 39% (95% CI: 30%-49%) used medical therapy; and 29% (95% CI: 20%-41%) sought physiotherapy. Heterogeneity was high across studies, reflecting differing case definitions and self-reported measures. CONCLUSIONS: MSK pain affects most ophthalmologists, particularly in the cervical and lumbar regions and frequently alters practice patterns. These findings underscore the need for early ergonomic training, structured micro-breaks, and workspace redesign. Prospective intervention trials are required to establish causality and quantify benefit.

Humans

Peptide molecular lock-engineered nanobodies enable an oriented dual-modal immunoassay for reliable detection of Cronobacter sakazakii.

Conventional nanobody ELISAs for trace Cronobacter sakazakii in powdered infant formula suffer from random orientation and low signal output. We developed an oriented dual-modal immunoassay that combines site-specific biotinylation via a C-terminal AviTag and a peptide molecular lock, enabling controlled surface orientation while preserving nanobody structural integrity. This strategy was further integrated with phage-displayed nanobodies for multivalent amplification and both fluorescent and colorimetric readouts. The assay exhibited a broad linear range of 103-106 CFU/mL, with limits of detection (LODs) of 6.70 × 102 CFU/mL for fluorescence and 1.55 × 103 CFU/mL for colorimetry, showing improved sensitivity compared with the conventional passive adsorption-based Nb-ELISA evaluated in this study. XGBoost-based multimodal fusion improved quantitative accuracy, and SHAP analysis elucidated modality contributions. In spiked powdered infant formula samples, recoveries ranged from 92.1% to 118% with coefficients of variation below 5.98%, confirming acceptable matrix tolerance and analytical reliability.

Cronobacter sakazakii

Ensemble DNA methylation clock demonstrates Immune-metabolic aging signatures associated with mortality.

Aging is a multifactorial process that is best described in terms of the progressive acquisition of multiple layers of phenotypic changes, such as epigenetic modifications, inflammation, and metabolic dysregulation. DNA methylation clocks have been extensively used to construct epigenetic clocks based on the DNAm profiles that can be used to estimate biological age and predict age-associated outcomes. Nevertheless, the vast majority of clocks constructed so far have been based on linear models, which are unlikely to fully account for the heterogeneity and non-linearity of survival-related DNAm signatures. In this work, we constructed a heterogeneous stacked ensemble survival model based on DNAm data obtained from the Framingham Heart Study. We first identified 190 CpG loci using elastic net Cox regression and subsequently constructed a survival prediction model based on the fusion of five complementary survival models by means of a neural network meta-learner. The prediction power of the survival model was evaluated in an external validation cohort, where we observed strong performance for predicting all-cause mortality that significantly exceeded PhenoAge and was statistically comparable to GrimAge. These performance estimates were derived in cohorts of European ancestry and externally validated in postmenopausal women aged 50-79 years, and should therefore be interpreted as applicable only to demographically similar populations.

Humans

Early radiographic loss of intermetatarsal angle correction after single first TMT arthrodesis (Modified Lapidus) versus three-corner TMT arthrodesis.

INTRODUCTION: The Lapidus procedure treats hallux valgus with first-ray hypermobility. It can be performed as a single first tarsometatarsal (TMT) arthrodesis or a three-corner TMT construct with additional intermetatarsal fusion. Early loss of correction remains a concern. This study compared early radiographic stability between techniques. METHODS: Fifty patients (15 three-corner TMT arthrodesis, 35 single first TMT arthrodesis) treated between 2014 and 2023 were retrospectively reviewed. Hallux valgus angle (HVA), intermetatarsal angle (IMA), Méary's angle, and tibial sesamoid position were measured on weight-bearing radiographs at 6 weeks and 6 months postoperatively. RESULTS: Both techniques achieved significant correction. The three-corner TMT arthrodesis group showed greater initial IMA correction at 6 weeks (p = 0.020) and maintained a lower IMA at 6 months (p = 0.001). Early IMA loss was greater after single first TMT arthrodesis (1.5°±1.7° vs 0.6°±0.8°, p = 0.013). CONCLUSION: Three-corner TMT arthrodesis was associated with greater early intermetatarsal stability than single first TMT arthrodesis.

Humans

Reinforcement learning-based dynamic ensemble for missense variant effect prediction and tiered prioritization of VUS.

BACKGROUND: Accurate classification of missense variants remains a challenging task despite major advances in genomics. Numerous computational models have been developed to assist in variant classification, but often require repeated integration and benchmarking efforts. Ensemble methods have been proposed to overcome the limitations of single predictors, but mostly rely on fixed, predefined weights that constrain their ability to capture interactions among predictive signals. METHODS: We present GenixRL, a dynamic ensemble framework that reformulates model fusion as a reinforcement learning optimization problem. GenixRL uses a Q-learning agent to learn a policy that dynamically weights the probabilistic outputs of complementary predictors, including BayesDel (addAF and noAF), ClinPred, and MetaRNN. Replacing static weighting with policy learning allows GenixRL to adaptively identify optimal weightings and substantially improve classification accuracy. RESULTS: In benchmark evaluation against 25 state-of-the-art predictors, GenixRL achieved an AUROC of 0.9644 on an independent ClinVar dataset. On saturation genome editing assays for BRCA1 and BRCA2, GenixRL achieved the best performance and ranked highest on 14 of 17 clinically significant genes in a zero-shot evaluation. Applied to uncertain and conflicting ClinVar variants, GenixRL enabled tiered, evidence-based prioritization of hundreds of thousands of variants as likely pathogenic or pathogenic with high confidence, supported by orthogonal population evidence from gnomAD. CONCLUSION: GenixRL advances pathogenicity prediction for missense variants and provides an adaptive ensemble that sorts variants of uncertain significance into tiered candidates for expert curation and functional validation.

Mutation, Missense

Diagnostic accuracy of nuclear STAT6 immunohistochemistry for solitary fibrous tumour: a systematic review and meta-analysis.

Nuclear STAT6 immunohistochemistry is the diagnostic surrogate for the NAB2::STAT6 fusion of solitary fibrous tumour (SFT); its sensitivity is established, but specificity varies for unexamined reasons. This review quantified pooled accuracy and tested whether antibody clone and nuclear threshold govern specificity. PubMed, Scopus and Web of Science were searched to 29 June 2026 for studies reporting nuclear STAT6 immunohistochemistry against a reference standard (NAB2::STAT6 confirmation and/or expert consensus) in SFT and comparators, with extractable two-by-two data. Two reviewers screened, extracted data and applied QUADAS-2. A bivariate generalised linear mixed model gave summary sensitivity and specificity, and exploratory subgroup analysis and meta-regression tested antibody clone, anatomical site and reference-standard type. Twenty-three studies (1216 SFT and 4715 comparators) were included. Summary sensitivity was 98.7% (95% confidence interval 96.7-99.5) and specificity 99.1% (97.8-99.6); the diagnostic odds ratio was approximately 8656. The monoclonal YE361 subgroup (8 studies) reached specificity 99.9% (99.3-100), with one false positive among 861 comparators, versus 98.1% (96.0-99.1) for polyclonal and other antibodies. False positives concentrated in dedifferentiated liposarcoma and prostatic stromal tumours. Estimates were stable after removing studies at higher risk of bias (98.9%/99.1%) and on leave-one-out analysis; the Deeks test was non-significant (p = 0.08). Nuclear STAT6 immunohistochemistry is therefore highly sensitive and specific for SFT, and the residual specificity loss is structured and largely avoidable: the monoclonal YE361 read at a strict nuclear threshold is preferred, with MDM2 and CDK4 applied to exclude dedifferentiated liposarcoma when nuclear STAT6 is unexpectedly positive.

Humans

Transcriptomic insights into temperature regulation of proliferation and differentiation in skeletal muscle cells of Nibea albiflora.

Myogenesis involves sequential stages of muscle satellite cell activation, myoblast proliferation, differentiation, and fusion into multinucleated myotubes. Teleost muscle exhibits indeterminate growth and is highly sensitive to environmental temperature, yet the underlying mechanisms by which temperature regulate proliferation and differentiation remain poorly understood. In this study, we established a primary skeletal muscle cell culture from the yellow drum (Nibea albiflora), an economically important marine fish, and integrated morphological observations with comparative transcriptomics analysis to characterize cellular and molecular responses at 28 °C and 20 °C during both proliferation and differentiation stages. Phenotypic analysis revealed that 28 °C significantly enhanced both myoblast proliferation and myogenic differentiation ability compared with 20 °C. Transcriptomic profiling revealed that at 28 °C, differentiation upregulated extracellular matrix(ECM) organization, calcium signaling, and sarcomere assembly, while proliferation enhanced focal adhesion, growth factor signaling, and lipid metabolism. At 20 °C, differentiation was characterized by glutathione metabolism, and ferroptosis, while proliferation involved cytokine-cytokine receptor interaction and negative regulation of signal transduction. Core myogenic regulatory factors (MRFs), particularly myogenin, were strongly upregulated at 28 °C during the differentiation stage, serving as an internal control. Based on these findings, we propose a testable model that elevated temperature coordinates Ca2+-dependent MRF activation with ECM-integrin signaling to drive sarcomere assembly and muscle growth. Key differentially expressed genes (DEGs) regulating myogenesis in N. albiflora were also identified. This study provides a mechanistic framework for temperature adaptation in teleost skeletal muscle and identifies candidate genes for functional validation and marker-assisted selection, as well as a rationale for temperature management strategies to improve aquaculture yield of N. albiflora.

Animals

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