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PubMed2026

Structural complexity and mechanistic diversity of MECOM rearrangements in myeloid neoplasms.

Rearrangements involving MECOM at chromosome 3q26.2 are recurrent in myeloid neoplasms, classically represented by inv(3)(q21q26.2) and t(3;3)(q21;q26.2), which reposition the GATA2-distal haematopoietic enhancer and drive aberrant EVI1 overexpression. However, the full structural and mechanistic diversity of MECOM rearrangements (MECOM-r) is yet to be explored. We retrospectively analysed 97 cases with cytogenetically defined MECOM-r and identified 12 with complex rearrangements using GTG-banded karyotyping and tri-colour interphase/metaphase fluorescence in situ hybridisation analyses. These 12 cases demonstrated remarkable structural heterogeneity. The abnormalities encompassed translocations, inversions, insertions, duplications, and deletions, which often coexisted within the same specimen as multiple rearranged subclones. Insertional events emerged as a distinct mechanism of MECOM activation. These encompassed insertions of MYNN and/or MECOM into chromosomes 1 and 6, insertion of chromosome 8 segment into MECOM, and inverted insertions between homologous chromosome 3 segments. Recurrent breakpoints at 3q21 across multiple cases, together with localised copy number imbalances frequently involving the MYNN and GOLIM4 loci at 3q26.2, underscore the architectural fragility of these two regions. Co-occurring abnormalities such as -5/del(5q), -7/del(7q), and TP53 loss were common, reflecting a permissive genomic background for chromosomal reassembly. Our findings expand the mechanistic landscape of MECOM-r beyond canonical inv(3)/t(3;3), establishing 3q21 and 3q26.2 as structural 'hotspots' and genomic instability hubs. Distinct from fusion-driven oncogenes such as KMT2A, MECOM activation results from enhancer hijacking and regional structural remodelling, leading to EVI1 overexpression and clonal evolution in myeloid malignancies.

Humans↗
PubMed2026

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↗
PubMed2026

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↗
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

Azacitidine-Venetoclax or Induction Chemotherapy for Acute Myeloid Leukemia.

BACKGROUND: Induction chemotherapy has long been a key component of curative therapy for fit patients with acute myeloid leukemia (AML), despite its frequently severe side effects and substantial health care utilization. For patients who are ineligible for induction chemotherapy, hypomethylating therapy plus venetoclax is the standard treatment owing to its efficacy and side-effect profile. METHODS: In this multicenter, phase 2 trial, we randomly assigned, in a 1:1 ratio, previously untreated adults with AML who were eligible for induction chemotherapy to receive either azacitidine plus venetoclax or induction chemotherapy. Patients with core binding factor fusions, mutations in the gene encoding FMS-like tyrosine kinase 3 (FLT3), or mutations in the gene encoding nucleophosmin-1 (NPM1; unless the patient was ≥60 years of age) were excluded. The primary end point was event-free survival. RESULTS: A total of 172 patients underwent randomization, with 86 patients assigned to each group. The median age of the patients was 64 years. A total of 72% of the patients had adverse-risk disease according to the European LeukemiaNet 2022 classification. At a median follow-up of 21.9 months, the median event-free survival was 14.5 months (95% confidence interval [CI], 10.4 to 24.4) in the azacitidine-venetoclax group, as compared with 6.2 months (95% CI, 4.1 to 10.1) in the induction chemotherapy group, corresponding to a hazard ratio for event or death of 0.57 (95% CI, 0.39 to 0.84; P = 0.002 by the stratified log-rank test). Infection of grade 3 or higher occurred in 28% of the patients (95% CI, 19 to 39) receiving azacitidine-venetoclax and in 41% of those (95% CI, 30 to 52) receiving induction chemotherapy; hemorrhage of grade 3 or higher occurred in 2% (95% CI, 0.3 to 8) and 12% (95% CI, 6 to 20), respectively. CONCLUSIONS: In this phase 2, randomized trial, azacitidine-venetoclax therapy led to significantly longer event-free survival than induction chemotherapy among induction-eligible patients with AML. (Funded by AbbVie and others; PARADIGM ClinicalTrials.gov number, NCT04801797.).

Adult↗