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Inositol Metabolism Modulates Inflammatory Injury in Acute Pancreatitis via the ISYNA1-NETs Axis

J Inflamm Res. 2026 Sep 22;19:606503. doi: 10.2147/JIR.S606503. eCollection 2026.

ABSTRACT

BACKGROUND: Neutrophil extracellular traps (NETs) were key factors mediating inflammatory injury in acute pancreatitis (AP). To this end, there was an urgent need to identify precise and effective therapeutic targets that modulate NETs formation, providing new ideas for the prevention and treatment of AP pancreatitis injury.

GAP: To address this gap, we investigated the potential involvement of the myo-inositol metabolism in modulating NETs and inflammatory damage during AP.

METHODS: Multi-omics analysis identified myo-inositol metabolism as critical. We then established the in vitro NETs model using phorbol-12-myristate-13-acetate (PMA) to investigate the role and regulatory mechanism of inositol-3-phosphate synthase 1 (ISYNA1) on NETs formation. Finally, the findings were validated in the classic AP mouse model to verify the correlation between myo-inositol metabolism and AP pathogenesis.

RESULTS: Multiple omics analyses showed that the myo-inositol metabolic pathway is the most significant, and the key enzyme ISYNA1 involved in myo-inositol synthesis was significantly reduced. ISYNA1 was significantly downregulated in both the in vitro NETs model and in neutrophils infiltrating the pancreatic tissue of AP mice. Meanwhile, exogenous supplementation of ISYNA1 or myo-inositol significantly inhibited the NETs formation in vitro and inflammatory injury in AP mice. Mechanistically, downregulation of ISYNA1 led to reduced myo-inositol synthesis, thereby promoting NETs formation via modulation of the PI3K/AKT pathway.

CONCLUSION: ISYNA1 and myo-inositol metabolism were among the key links that regulated NETs formation and inflammatory injury in AP. Therefore, enhancing ISYNA1 and myo-inositol metabolism might serve as a potential intervention target for treating acute organ injury in AP.

PMID:42801157 | PMC:PMC13615823 | DOI:10.2147/JIR.S606503

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Genomics and social practices at Mogou and other Gansu sites during prehistoric trans-Eurasian exchange

Ancient DNA from 149 individuals at 11 sites in Gansu, China, dated to around 4,700–3,000 years ago, reveals human population history during early transcontinental exchanges of agriculture and technology, as well as contemporary social practices, at the large Mogou cemetery.
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Unmasking FCGR2B as a high-grade serous ovarian cancer specific marker of immune suppression and tumor progression through multi-omics mining

Transl Oncol. 2026 Apr 3;67:102748. doi: 10.1016/j.tranon.2026.102748. Online ahead of print.

ABSTRACT

BACKGROUND: Epithelial ovarian cancer (EOC) encompasses five major histological subtypes with marked genetic, immunological, and clinical heterogeneity. While genome-wide association studies (GWAS) have identified subtype-specific risk loci, a critical gap remains in understanding how plasma proteins influence immune-cell traits and contribute to EOC pathogenesis.

METHODS: We integrated subtype-stratified GWAS data from two EOC cohorts with plasma proteomics and immune-cell traits to construct protein-immune-EOC regulatory landscapes using a three-stage Mendelian randomization framework. Single-cell RNA-seq and multiplex immunofluorescence were employed to delineate the cellular distribution and spatial context of causal proteins. Subsequent analyses characterized immune infiltration, macrophage polarization, and clinicopathological associations. Drug-gene correlations were used to identify potential therapeutic targets, and transcriptomic analyses were applied to delineate the underlying transcriptional landscape.

RESULTS: We identified 20 subtype-specific protein-immune-EOC regulatory axes, with FCGR2B emerging as a causal plasma protein in immune regulation and high-grade serous ovarian cancer (HGSOC) progression. FCGR2B was highly expressed in tumor-associated macrophages and was associated with an M2-like polarization phenotype. Functional characterization revealed that FCGR2B was associated with shorter progression-free survival and an immunosuppressive tumor microenvironment. Transcriptomic analyses revealed altered NF-κB signaling upon FCGR2B knockdown, and drug-response data suggested a potential association between high FCGR2B expression and sensitivity to NF-κB inhibitors.

CONCLUSIONS: These findings delineate subtype-specific genetically informed protein-immune regulatory landscapes in EOC and identify FCGR2B as a key immunoregulatory and prognostic biomarker in HGSOC, suggesting FCGR2B as a potential therapeutic vulnerability that warrants further investigation.

PMID:41934917 | DOI:10.1016/j.tranon.2026.102748

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Electric dipole moment drives the dynamics of the TNFR1 complex I signalosome

Nature, Published online: 01 April 2026; doi:10.1038/s41586-026-10304-1

Long-range interactions mediated by protein electric dipole moments have a role in driving the assembly and disassembly of super-signalling complex I for promoting NF-κB signalling.
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SkillsBench: Benchmarking How Well Agent Skills Work Across Diverse Tasks

arXiv:2602.12670v3 Announce Type: replace Abstract: Agent Skills are structured packages of procedural knowledge that augment LLM agents at inference time. Despite rapid adoption, there is no standard way to measure whether they actually help. We present SkillsBench, a benchmark of 86 tasks across 11 domains paired with curated Skills and deterministic verifiers. Each task is evaluated under three conditions: no Skills, curated Skills, and self-generated Skills. We test 7 agent-model configurations over 7,308 trajectories. Curated Skills raise average pass rate by 16.2 percentage points(pp), but effects vary widely by domain (+4.5pp for Software Engineering to +51.9pp for Healthcare) and 16 of 84 tasks show negative deltas. Self-generated Skills provide no benefit on average, showing that models cannot reliably author the procedural knowledge they benefit from consuming. Focused Skills with 2--3 modules outperform comprehensive documentation, and smaller models with Skills can match larger models without them.
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SkillsBench: Benchmarking How Well Agent Skills Work Across Diverse Tasks

arXiv:2602.12670v2 Announce Type: replace Abstract: Agent Skills are structured packages of procedural knowledge that augment LLM agents at inference time. Despite rapid adoption, there is no standard way to measure whether they actually help. We present SkillsBench, a benchmark of 86 tasks across 11 domains paired with curated Skills and deterministic verifiers. Each task is evaluated under three conditions: no Skills, curated Skills, and self-generated Skills. We test 7 agent-model configurations over 7,308 trajectories. Curated Skills raise average pass rate by 16.2 percentage points(pp), but effects vary widely by domain (+4.5pp for Software Engineering to +51.9pp for Healthcare) and 16 of 84 tasks show negative deltas. Self-generated Skills provide no benefit on average, showing that models cannot reliably author the procedural knowledge they benefit from consuming. Focused Skills with 2--3 modules outperform comprehensive documentation, and smaller models with Skills can match larger models without them.
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