West China Second University Hospital of Sichuan University

Summary What is already known about this topic? What does this study add?

Neonatal hypoxic-ischemic encephalopathy (HIE) may induce substantial neuronal damage. In particular, an overactivation of microglia following HIE represents a pathogenically important process. Previous studies have shown that microglial inhibitors can exert neuroprotective effects in HIE; however, the specific mechanisms underlying these effects have not yet been elucidated. Ligation of the left common carotid artery and exposure to 5% O2 were utilized to produce an HIE model in rats. A number of experimental approaches were then used to determine the effect of a microglial inhibition, achieved via the administration of GW2580, a Csf1r inhibitor, and investigate the mechanisms involved. Our HIE models exhibited substantial brain infarction and were significantly impaired in motor functions (p < 0.01-0.001, in all tests examined). In the infarction areas, the number of microglia, macrophages, and neural stem cells (NSCs) was all dramatically increased over that in sham-injured rats, respectively (p < 0.05-0.001). The administration of GW2580 significantly reduced the numbers of microglia and macrophages, but increased the number of NSCs when compared to those in vehicle-treated HIE models (p < 0.05-0.001). Furthermore, GW2580 significantly ameliorated both the histological and behavioral phenotypes in HIE rats and increased STAT phosphorylation (p < 0.05-0.001). Finally, the inhibition or activation of STAT3 respectively decreased or increased the neuroprotective effects of GW2580 (p < 0.05-0.001). Collectively, our findings demonstrate that the STAT3 signaling pathway plays a critical role in the neuroprotective effects of microglial inhibition and may facilitate the development of novel therapeutic strategies to treat stroke.

Neurological complications are a major contributor to morbidity in neonatal patients supported with extracorporeal membrane oxygenation (ECMO). Adequate neurological monitoring during ECMO enables the early recognition and management of neurological injury. In addition, long-term neurodevelopmental follow-up after ECMO allows for the early identification of neurodevelopmental delay and the timely initiation of interventions. Therefore, standardized neurological monitoring and structured long-term follow-up in neonatal patients receiving ECMO support are essential to reduce the incidence and severity of neurological complications, improve prognosis, and enhance the quality of life of affected children. This is a Protocol for a Systematic Review and GRADE-Based Expert Consensus. This protocol outlines the methodology and process for developing the "Chinese Expert Consensus for Neurological Monitoring and Long-term Follow-Up in Neonatal Patients Supported on extracorporeal membrane oxygenation (ECMO) (2025)." It details the purpose, target patient population, composition of the consensus working group, presentation and collection of clinical questions, rigorous evaluation and summarization of evidence, and formulation of expert recommendations. This structured approach enhances the standardization and transparency of the consensus development process. This expert consensus has been registered bilingually with the International Practice Guidelines Registry Platform (IPGRP) under the registration number PREPARE-2024CN1051. The final recommendations will be disseminated through publication in peer-reviewed journals, presentations at national and international conferences, educational workshops, and postings on widely used medical platforms in China. The aim is to support healthcare professionals, improve clinical outcomes, and inform health policy development in neonatal critical care.

With the advancement of GPU architecture, matrix computation engines such as NVIDIA Tensor Cores now support double-precision (FP64) General matrix multiplications (GEMMs) with the same efficiency as single-precision (FP32) GEMMs. However, the adoption of this enhanced FP64 capability remains limited, primarily restricted to applications that involve multiple FP64 BLAS3 operations. Singular Value Decomposition (SVD), a fundamental decomposition in numerical linear algebra with numerous applications, can greatly benefit from exploiting this hardware feature. In this article, for FP32 SVD, we propose a novel algorithm, FP64 precision eigenvalue decomposition (EVD) based SVD, specifically designed to leverage the latest GPU architectural features. We provide a theoretical analysis demonstrating the feasibility of our approach on emerging GPU architectures and evaluate it from both accuracy and performance perspectives. Moreover, for FP64 SVD, we introduce a double-blocking band reduction technique combined with a GPU-based bulge chasing algorithm to further accelerate the overall SVD process. Experimental results show that, for FP32 SVD, our EVD-based SVD implementation achieves higher numerical accuracy and delivers speedups of up to 6.1× on H100 and 5.0× on A100 over the state-of-the-art cuSOLVER SVD solver. In the case of FP64 SVD, our method also achieves 4.9× and 4.8× speedups on H100 and A100, respectively. These results highlight the potential of our approach as a highly efficient and accurate solution for SVD on modern GPU platforms.

Rationale:Glycogen storage disease type Ia (GSD Ia) typically presents with fasting hypoglycemia and hyperlipidemia. Atypical infantile presentations can delay diagnosis. We report an infant with extreme hypertriglyceridemia ultimately diagnosed as GSD Ia.Patient concerns:A 5-month-old girl presented with poor appetite, growth retardation, hepatomegaly, and extreme hypertriglyceridemia (72 mmol/L), hypercholesterolemia, elevated transaminases, hyperuricemia, and hyperlactatemia, but initial normal blood glucose.Diagnoses:Initial differentials included familial hypertriglyceridemia, but metabolic screening was normal. Whole-exome sequencing confirmed GSD Ia with compound heterozygous G6PC mutations (c.648G>T and c.814G>T).Interventions:Initial lipid-lowering (low-fat diet, fenofibrate, omega-3, plasma exchange) reduced triglyceride. Post-diagnosis, she received lactose-free formula with frequent feeds and nocturnal nutrition; uncooked cornstarch was introduced at 6 months, though adherence was initially poor.Outcomes:Metabolic control was unstable until age 2 due to poor adherence. After 24 months of structured cornstarch therapy, fasting glucose normalized (4.2–6.6 mmol/L), triglycerides decreased (1.8–6.7 mmol/L), and catch-up growth occurred (height Z-score from -3.9 to -2.2 by 36 months).Lessons:GSD Ia should be considered in infantile extreme hypertriglyceridemia with growth retardation, even without classic hypoglycemia. Sustained metabolic control requires multidisciplinary strategies addressing both biochemical and adherence barriers.

Abstract Background Preimplantation genetic testing for monogenic disorders (PGT-M) represents a critical clinical strategy for preventing the transmission of hereditary diseases from carriers to offspring, with its diagnostic efficacy heavily dependent on the accuracy and coverage of detection platforms. Genome-wide SNP array such as the Asian Screening Array (ASA), has demonstrated favorable performance in haplotype analysis for PGT-M. Here, we systematically evaluated the efficiency of the Asian Screening Array-based PGT workflow in PGT application for different genetic disorders. Methods We conducted a retrospective analysis by reviewing 377 pedigrees underwent PGT-M preclinical work-up and 367 PGT-M clinical cycles (1677 embryos in total) based on the Asian Screening Array. We established detection strategies combining ASA haplotyping analysis and individualized direct mutation detection based on different genetic patterns. Long-read sequencing or single-sperm haplotyping strategy was applied for families with de novo pathogenic variants or lacking family member samples. Individualized direct mutation detection methods such as Gap-PCR, RP-PCR, PCR-RFLP were adopted for different cases. Results Results indicated the clinical validity of our ASA-based PGT workflow, integrating linkage analysis, direct mutation detection, and chromosomal CNV screening. The number of SNPs available for linkage analysis in the upstream and downstream regions of target genes/regions is sufficient for most of the cases. Individualized direct mutation detection methods for different cases also validated the ASA haplotyping results. In haplotype analysis, the method based on long-read sequencing is more effective than single-sperm haplotyping strategy. Detailed haplotyping strategy for families with microdeletions and tandem duplications was established based on ASA. A total of 636 embryos were ultimately deemed suitable for transfer after undergoing linkage analysis and CNV detection. Conclusion This study validated the feasibility and superiority of ASA-based approach in PGT, also provided a standardized and reliable technical solution for the clinical prevention of different genetic disorders.