Explore the vast range of titles available.

Background Neuroinflammation-induced injury is intimately associated with poor prognosis in patients with cerebral venous sinus thrombosis (CVST). The cyclic GMP-AMP synthase–stimulator of interferon gene (cGAS–STING) axis is a cytoplasmic double-stranded DNA (dsDNA) sensing pathway has recently emerged as a crucial mediator of neuroinflammation in ischemic stroke. However, the role of the cGAS–STING pathway in modulating post-CVST inflammation and the underlying mechanisms involved remain unclear. Methods A CVST model was induced by ferric chloride in male C57BL/6J mice. The selective cGAS inhibitor RU.521, STING agonist 2′3′-cGAMP, and STING siRNA were delivered by intranasal administration or intraventricular injection. Post-CVST assessments included rotarod test, TUNEL staining, Fluoro-Jade C staining, dihydroethidium staining, western blotting, qPCR, immunofluorescence, immunohistochemistry, ELISA and flow cytometry. Results cGAS, STING, NLRP3 and GSDMD were significantly upregulated after CVST and mostly in the microglia of the mouse brain. CVST triggered the release of dsDNA into the cytoplasm and elicited an inflammatory response via activating the cGAS–STING axis. RU.521 decreased the levels of 2′3′-cGAMP, STING and downstream inflammatory cytokines, and suppressed the expressions of NLRP3 inflammasome and pyroptosis-pertinent components containing cleaved caspase-1, GSDMD, GSDMD-C, pro- and cleaved IL-1β, and cleaved IL-1β/pro-IL-1β. Besides, RU.521 treatment also reduced oxidative stress, lessened the numbers of microglia and neutrophils, and ameliorated neuronal apoptosis, degeneration along with neurological deficits post-CVST. 2′3'-cGAMP delivery enhanced the expressions of STING and related inflammatory mediators, NLRP3 inflammasome and pyroptosis-relevant proteins, whereas these alterations were significantly abrogated by the silencing of STING by siRNA. Conclusions Our data demonstrate that repression of the cGAS–STING pathway diminishes the neuroinflammatory burden of CVST and highlight this approach as a potential therapeutic tactic in CVST-mediated pathologies.

Background Decompressive craniectomy (DC) is performed conventionally for large putaminal intracerebral hemorrhage (ICH). However, DC causes local skull defect and leads to post-surgical cranioplasty. The aim of this study is to investigate the effectiveness and safety of an endoscopic procedure to treat large putaminal ICH without DC. Methods This retrospective study included 112 large putaminal ICH patients who underwent hematoma evacuations with either an endoscopic procedure (group A) or with DC (group B) between January 2009 and June 2017. The efficacy was evaluated by mean modified Rankin Scale (mRS) three months after surgery. Safety was evaluated by mortality rate and postoperative complications. Univariate and multivariate logistic regression analyses were performed to determine the risk factors for clinical outcomes. Results The study included 49 patients in group A and 63 in group B. The mRS scores in both groups were similar after 3 months’ follow-up ( p  = 0.709). There was no difference in the mortality rate between the two groups ( p  = 0.538). The rate of complications was lower in group A than that in group B ( p  = 0.024). Smaller preoperative midline shift ( p  = 0.008) and absent intraventricular extension ( p  = 0.044) have contributed significantly to better outcomes. Conclusion Endoscopic hematoma evacuation without DC is safe and effective for patients with large putaminal ICH and deserves further investigation, preferably in a randomized controlled setting.

Ischemic stroke is one of the leading causes of mortality and disability worldwide. Following stroke, there is secondary neuroinflammation that promotes further injury. Identifying the long non-coding RNA (lncRNA) involved in neuroinflammation after cerebral ischemic stroke will promote the discovery of potential therapeutic targets. We identified differentially expressed genes from genome-wide RNA-seq profiles of mice with focal ischemia using Gene Ontology Term Enrichment, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment analyses. Immune cell infiltration deconvolution, protein-protein interaction network construction, and co-expression network analyses were also used to screen lncRNAs. In further experiments, lncRNA knockdown animal models were developed by intraventricular injection of the antisense oligonucleotide before performing middle cerebral artery occlusion (MCAO). An enzyme-linked immunosorbent assay was performed to measure the level of cytokines. Hematoxylin-eosin staining and immunohistochemical staining were used to observe the changes in morphology. Enrichment analysis revealed that differential mRNAs induced neuroinflammation after MCAO. Immune deconvolution showed that the proportion of microglia gradually increased while monocytes decreased within 24 h. We identified six hub lncRNAs ( , , , , , and ) that were highly correlated with activated-microglia mRNAs (cor > 0.8). We found that Neat1 had the highest correlation coefficient with pro-inflammatory factor mRNA levels. In vivo experiments demonstrated that had abnormally high expression after MCAO. Knockdown of could significantly alleviate brain damage by reducing the number of activated microglia and reducing their release of proinflammatory cytokines. We identified inflammation-associated lncRNA as crucial, which means it is a potential target for ischemic stroke treatment.

Superconducting quantum computing is one of the most mature solid-state platforms for quantum computation, with processors exceeding one hundred qubits. Yet further scaling toward fault-tolerant quantum computing is increasingly constrained by calibration complexity. Conventional scripts are brittle to anomalous signals, and expert judgment is bounded by cognitive bandwidth and serial operation time, failing to keep pace with system scale. Here we report Vibe Calibration, an autonomous calibration system orchestrated by large language model agents, which distills expert tacit knowledge into reusable Skills. Each Skill is organized as a decision tree that packages parameterized measurement commands, quantitative acceptance criteria, and audit records, enabling autonomous execution and self-healing. We capture this knowledge through a three-phase human-in-the-loop distillation process and fine-tune a large language model on validated trajectories. On a 112-qubit processor with frequency-tunable transmons, the system autonomously completes calibration of 108 out of 112 qubits in 4.7 hours, achieving a 4--5\\(\\) speedup over manual calibration of the full 112 qubits. A cross-validated comparison with expert manual calibration on a 16-qubit subset shows agreement on 14 out of 16 qubits. More importantly, the model demonstrates transferable calibration workflows across devices. While low-level control scripts require minor interface adaptation for different hardware platforms, the core decision logic and task orchestration generalize to new processors, demonstrating a reusable laboratory interface rather than a memorized script.This work demonstrates, for the first time, fully autonomous calibration of a hundred-qubit superconducting processor through reusable and auditable Skills, removing a critical barrier to scalable quantum hardware operation.

The stabilizer (additive) method and non-additive method for constructing asymmetric quantum codes have been established. In this paper, these methods are generalized to inhomogeneous quantum codes.