Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

With the development of education and technology, the construction of research public platforms has emerged as a critical initiative for many universities and top-tier public hospitals. The core and most fundamental function of a basic public platform is to aggregate large instruments and specific resources, providing open services for instrumental analysis and sample testing. Optimized management and high-quality, efficient services are essential for such platforms. This article elucidates the construction of a research public platform in West China Hospital, focusing on the adoption of hierarchical management and precise services. The core of the hierarchical management lies in building a multi-level service platform composed of routine support platforms, advanced technology platforms, and specially qualification platforms, while establishing a talent hierarchy that differentiates between core and routine positions. This structure is designed to accurately meet the diverse needs of users and enhance resource efficiency. By implementing user access control with differentiated permissions for internal and external users and a dynamic credit-based review system, the laboratory can ensure safe and efficient operations. The four service modes-instrument usage, in-lab experiments, sample testing, and collaborative projects-are precisely aligned with various research scenarios. Proactive engagement with grant-funded projects, customized services for research groups, and a multidimensional training system further strengthen the platform's support for major scientific research tasks. Through systematic management and service innovation, this model achieves efficient integration and sustainable development of platform resources, providing a valuable reference for the construction of public platforms in similar medical institutions.
China ; Research ; Laboratories/organization & administration*

OBJECTIVES: To investigate the molecular epidemiology of children with phenylketonuria (PKU) in Gansu, China, providing foundational data for intervention strategies. METHODS: A retrospective analysis was conducted on 1 159 PKU families who attended Gansu Provincial Maternity and Child Care Hospital from January 2012 to December 2024. Sanger sequencing, multiplex ligation-dependent probe amplification, whole exome sequencing, and deep intronic variant analysis were used to analyze the PAH gene. RESULTS: For the 1 159 children with PKU, 2 295 variants were identified in 2 318 alleles, resulting in a detection rate of 99.01%. The detection rates were 100% (914/914) in 457 classic PKU families, 99.45% (907/912) in 456 mild PKU families, and 96.34% (474/492) in 246 mild hyperphenylalaninemia families. The 2 295 variants detected comprised 208 distinct mutation types, among which c.728G>A (14.95%, 343/2 295) had the highest frequency, followed by c.611A>G (4.88%, 112/2 295) and c.721C>T (4.79%, 110/2 295). The cumulative frequency of the top 23 hotspot variants reached 70.28% (1 613/2 295), and most variant alleles were detected in exon 7 (29.19%, 670/2 295). CONCLUSIONS Deep intronic variant analysis of the PAH gene can improve the genetic diagnostic rate of PKU. The development of targeted detection kits for PAH hotspot variants may enable precision screening programs and enhance preventive strategies for PKU.
Humans ; Phenylketonurias/epidemiology* ; Female ; Male ; Retrospective Studies ; Phenylalanine Hydroxylase/genetics* ; Mutation ; Child, Preschool ; China/epidemiology* ; Child ; Infant

BACKGROUND: Lung cancer is one of the leading causes of cancer-related mortality worldwide, with above 80% of cases be non-small cell lung cancer (NSCLC), among which lung squamous cell carcinoma (LUSC) occupies a significant proportion. Although comprehensive cancer therapies have considerably improved the overall survival of patients, patients with advanced LUSC have a poorer prognosis. Therefore, there is a need for a biomarker to predict the progress of advanced LUSC in order to improve prognosis through early diagnosis. Previous studies have shown that miRNAs are differentially expressed in lung cancer tissues and play roles as potential oncogenes or tumor suppressors. The aim of this study is to identify differentially expressed miRNAs between early-stage and advanced-stage LUSC, and to establish a set of miRNAs that can predict the progress of advanced LUSC. METHODS: Clinical data and miRNA-related data of LUSC patients were downloaded from The Cancer Genome Atlas (TCGA) database. Bioinformatic methods were applied to analyze the data. Receiver operating characteristic (ROC) curves were plotted, and various online tools were used to predict target genes, with subsequent analysis of the potential biological mechanisms of these genes. RESULTS: A total of 58 differentially expressed miRNAs were identified between the experiment group and the control group. Seven miRNAs were selected for potential construction of a miRNA biomarker through LASSO regression, and based on the area under the curve (AUC) values of each miRNA, four of these miRNAs (miR-377-3p, miR-4779, miR-6803-5p, miR-3960) were ultimately chosen as biomarkers for predicting advanced LUSC. The AUC under the ROC curve for the combined four miRNAs was 0.865. Enrichment analysis showed that these target genes were involved in several pathways, including cancer-related pathways, mitogen-activated protein kinase (MAPK) signaling pathway, serine/threonine kinase, and tyrosine kinase signaling pathways. CONCLUSIONS The combined use of miR-377-3p, miR-4779, miR-6803-5p and miR-3960 provides a good predictive ability for the progress of advanced LUSC patients, with an AUC of 0.865.
Humans ; MicroRNAs/metabolism* ; Lung Neoplasms/metabolism* ; Biomarkers, Tumor/metabolism* ; Carcinoma, Squamous Cell/pathology* ; Gene Expression Regulation, Neoplastic ; Male ; Female ; Prognosis ; ROC Curve ; Middle Aged

OBJECTIVE: To explore and quantify the association of hot night exposure during the sperm development period (0-90 lag days) with semen quality. METHODS: A total of 6,640 male sperm donors from 6 human sperm banks in China during 2014-2020 were recruited in this multicenter study. Two indices (i.e., hot night excess [HNE] and hot night duration [HND]) were used to estimate the heat intensity and duration during nighttime. Linear mixed models were used to examine the association between hot nights and semen quality parameters. RESULTS: The exposure-response relationship revealed that HNE and HND during 0-90 days before semen collection had a significantly inverse association with sperm motility. Specifically, a 1 °C increase in HNE was associated with decreased sperm progressive motility of 0.0090 (95% confidence interval [ CI]: -0.0147, -0.0033) and decreased total motility of 0.0094 (95% CI: -0.0160, -0.0029). HND was significantly associated with reduced sperm progressive motility and total motility of 0.0021 (95% CI: -0.0040, -0.0003) and 0.0023 (95% CI: -0.0043, -0.0002), respectively. Consistent results were observed at different temperature thresholds on hot nights. CONCLUSION Our findings highlight the need to mitigate nocturnal heat exposure during spermatogenesis to maintain optimal semen quality.
Humans ; Male ; Semen Analysis ; Adult ; Sperm Motility ; Hot Temperature/adverse effects* ; China ; Middle Aged ; Spermatozoa/physiology* ; Young Adult

Objective: To investigate the differences and diversity changes in gut microbiota between children and adolescents with constipation and diarrhea, and healthy individuals, and to explore the correlation between changes in stool consistency and gut microbiota, in order to provide a scientific reference for the research on intestinal microecology among children and adolescents. Methods: From October 2021 to March 2022, a total of 42 children and adolescents with constipation and 37 with diarrhea from a tertiary hospital in Hangzhou City, and 43 healthy individuals from 3 primary and secondary schools were included in this study. Fecal samples of children and adolescents were collected and then stool genomic DNA was extracted for 16S rRNA gene high throughput sequencing, and the sequencing results were analyzed. In the analysis of alpha diversity, the Kruskal-Wallis rank sum test was used to compare the differences between the three groups, and the FDR multiple testing correction was used for pairwise comparisons. In the analysis of beta diversity, the Adonis test was used to compare the overall differences between the three groups, and the ANOSIM test was used for pairwise comparisons. In the LEfSe analysis, the LDA scores obtained through LDA analysis (linear regression analysis). Results: Alpha diversity analysis showed that there were statistically significant differences in the Shannon index (4.01, 3.81, 4.19) and Simpson index (0.05, 0.06, 0.04) between the diarrhea group, constipation group, and healthy group ( H=6.05, 6.35, P <0.1). Further pairwise comparison showed that the Shannon index and Simpson index of the healthy group were higher than those of the constipation group ( P <0.1). Beta diversity analysis showed that the impact of grouping factors on inter group differences was statistically significant ( R 2=0.045, P <0.1). Community composition analysis showed that there were 234 species in total among the three groups, and 36 unique species in the healthy group, 36 species in the diarrhea group, and 48 species in the constipation group. Species difference analysis showed significant differences in species composition at the genus level among the three groups ( H=0.000 05, 0.000 16, 0.000 20, 0.000 21, 0.000 53, 0.001 39, P <0.1), including Lachnospiraceae of Firmicutes phylum, Eubacterium hallii, Veillonellaceae, Qscillospiraceae, Butyricicoccaceae and Staphylococcaceae, respectively. KEGG abundance statistics and COG functional analysis showed that there were no significant differences in gene expression abundance of the same function among the three groups ( P >0.1). Conclusions The different stool consistency of children and adolescents is related to changes in gut microbiota composition. Compared to the healthy group, children with constipation or diarrhea have disrupted gut microbiota balance, with a shift in dominant bacteria and a higher abundance of opportunistic pathogens.

Objective To explore the changes of metabonomics in blood of mice after high-voltage electric shock,then screen out the significantly changed differential metabolites and metabolic pathways.Methods The head of C57BL/6J mice was subjected to high-voltage electric shock(electric shock group)or exposed to acoustic and optical stimulation of high-voltage electric(control group),then the whole blood from mice were collected to separate serum.The dual platform combined metabonomic analysis based on gas chromatography-mass spectrometer(GC-MS)and liquid chromatography-mass spectrometer(LC-MS)was performed and orthogonal partial least squares discriminant analysis(OPLS-DA)was used to screen the differential metabolites and related metabolic pathways.Results A total of 415 differential metabolites were screened out in metabonomics in blood of mice after high-voltage electric shock,including 187 up-regulated and 228 down-regulated metabolites.These differentially metabolites were significantly enriched in metabolic pathways including central carbon metabolism in cancer,glucagon signaling pathway,etc.Conclusion By establishing the model of high-voltage electrical injury on experimental mice,this study reveals the significant change of metabolite content and metabolic pathway in blood by high-voltage electrical injury.Which provides a basis for the damage of blood metabolic activity by high-voltage electrical injury,and suggests the potential harm of high-voltage electrical injury to blood metabolic activity in the whole body.

Objective To study the change of lipidomics in chronic cadmium-exposed mice,thereby screening out lipid subclasses,lipid molecules and enriched metabolic pathways with significant differences.Methods Twelve SPF male C57BL/6J mice(8 weeks old)were randomly divided into the control group(normal water feeding)and the experimental group[cadmium water(0.6 mg/L of CdCl2)feeding],with 6 mice in each group.Mice were sacrificed after 6 months of cadmium exposure,and fresh liver tissues were collected immediately.Lipid oil red O staining and lipidomics analysis were performed on liver tissue.Results Compared with the control group,the liver tissue of mice in the experimental group did not appear red after lipid oil red O staining.Seventeen lipid subclasses with significant differences and 144 lipid molecules with significant differences were screened out by lipidomics.These lipid molecules with significant differences were enriched in glycerophospholipid metabolism,linoleic acid metabolism,alpha-linolenic acid metabolism,glycosylphosphati-dylinositol biosynthesis,glycerolipid metabolism and arachidonic acid metabolism by KEGG.Conclusion This study reveals that chronic cadmium exposure can induce the disorder of lipid subclasses and lipid metabolites in the liver of mice,which provides a basis for understanding the non-alcoholic fatty liver disease caused by chronic cadmium exposure.