The Janus kinase/signal transducers and activators of transcription (JAK-STAT) control natural killer (NK) cells development and cytotoxic functions, however, whether long non-coding RNAs (lncRNAs) are involved in this pathway remains unknown. We found that miR155HG was elevated in activated NK cells and promoted their proliferation and effector functions in both NK92 and induced-pluripotent stem cells (iPSCs)-derived NK (iPSC-NK) cells, without reliance on its derived miR-155 and micropeptide P155. Mechanistically, miR155HG bound to miR-6756 and relieved its repression of JAK3 expression, thereby promoting the JAK-STAT pathway and enhancing NK cell proliferation and function. Further investigations disclosed that upon cytokine stimulation, STAT3 directly interacts with miR155HG promoter and induces miR155HG transcription. Collectively, we identify a miR155HG-mediated positive feedback loop of the JAK-STAT signaling. Our study will also provide a power target regarding miR155HG for improving NK cell generation and effector function in the field of NK cell adoptive transfer therapy against cancer, especially iPSC-derived NK cells.

Objective:To develop CNN-Dinov2, a deep learning-based automatic classification model for Gram-stained images, enabling rapid diagnosis of three prevalent Gram-negative bacilli in bloodstream infections: Escherichia coli ( E.coli), Klebsiella pneumoniae ( K.pneumoniae), and Pseudomonas aeruginosa ( P.aeruginosa). Methods:This evaluation study analyzed 1 425 Gram-stained microscopic images from patients with bloodstream infections at Houjie Hospital, in Dongguan City, collected between January 2023 and January 2024. The images, all positive for blood culture and identified as target strains, were categorized into Escherichia coli (419 images), Klebsiella pneumoniae (411 images), Pseudomonas aeruginosa (413 images), and other Gram-negative bacilli (182 images). They were randomly split into a training set (1 141 images), a validation set (141 images), and a test set (143 images) in an 8∶1∶1 ratio. A hybrid CNN-Dinov2 model was developed by integrating ResNet′s local feature extraction with Dinov2′s global pre-trained features, followed by a fully connected layer. The model was optimized by inputting the preprocessed images and adjusting parameters through loss calculation and backpropagation. AlexNet, Dinov2, and ResNet18 served as control models. The models′ classification performance was assessed using accuracy, precision, weighted F1 score, and recall rate, derived from the confusion matrix. The PR curve and AP value further evaluated each model′s classification capability across the four image categories. Results:The CNN-Dinov2 model achieved a training accuracy of 99.74%, a validation accuracy of 98.12%, and a validation loss of 0.070 6, demonstrating robust generalization without overfitting. Validation metrics revealed superior performance with an accuracy of 98.60%, precision of 98.65%, a weighted F1 score of 98.60%, and a recall rate of 98.60%, outperforming other models. The confusion matrix confirmed its strong classification capability, with the highest sum of diagonal values for identifying four types of bacteria. The macro average precision (AP) values under the precision-recall (PR) curves were all 1, indicating excellent discrimination across all categories. Overall, the CNN-Dinov2 model exhibited the best performance among the four models evaluated.Conclusion:This study successfully developed CNN-Dinov2, an automated classification model for Gram staining images. It offers valuable support for the rapid diagnosis of bloodstream infections caused by Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa, demonstrating practical utility.

Objective:To develop CNN-Dinov2, a deep learning-based automatic classification model for Gram-stained images, enabling rapid diagnosis of three prevalent Gram-negative bacilli in bloodstream infections: Escherichia coli ( E.coli), Klebsiella pneumoniae ( K.pneumoniae), and Pseudomonas aeruginosa ( P.aeruginosa). Methods:This evaluation study analyzed 1 425 Gram-stained microscopic images from patients with bloodstream infections at Houjie Hospital, in Dongguan City, collected between January 2023 and January 2024. The images, all positive for blood culture and identified as target strains, were categorized into Escherichia coli (419 images), Klebsiella pneumoniae (411 images), Pseudomonas aeruginosa (413 images), and other Gram-negative bacilli (182 images). They were randomly split into a training set (1 141 images), a validation set (141 images), and a test set (143 images) in an 8∶1∶1 ratio. A hybrid CNN-Dinov2 model was developed by integrating ResNet′s local feature extraction with Dinov2′s global pre-trained features, followed by a fully connected layer. The model was optimized by inputting the preprocessed images and adjusting parameters through loss calculation and backpropagation. AlexNet, Dinov2, and ResNet18 served as control models. The models′ classification performance was assessed using accuracy, precision, weighted F1 score, and recall rate, derived from the confusion matrix. The PR curve and AP value further evaluated each model′s classification capability across the four image categories. Results:The CNN-Dinov2 model achieved a training accuracy of 99.74%, a validation accuracy of 98.12%, and a validation loss of 0.070 6, demonstrating robust generalization without overfitting. Validation metrics revealed superior performance with an accuracy of 98.60%, precision of 98.65%, a weighted F1 score of 98.60%, and a recall rate of 98.60%, outperforming other models. The confusion matrix confirmed its strong classification capability, with the highest sum of diagonal values for identifying four types of bacteria. The macro average precision (AP) values under the precision-recall (PR) curves were all 1, indicating excellent discrimination across all categories. Overall, the CNN-Dinov2 model exhibited the best performance among the four models evaluated.Conclusion:This study successfully developed CNN-Dinov2, an automated classification model for Gram staining images. It offers valuable support for the rapid diagnosis of bloodstream infections caused by Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa, demonstrating practical utility.

Objective This study aimed to investigate the potential relationship between urinary metals copper (Cu), arsenic (As), strontium (Sr), barium (Ba), iron (Fe), lead (Pb) and manganese (Mn) and grip strength. Methods We used linear regression models, quantile g-computation and Bayesian kernel machine regression (BKMR) to assess the relationship between metals and grip strength.Results In the multimetal linear regression, Cu (β=-2.119), As (β=-1.318), Sr (β=-2.480), Ba (β=0.781), Fe (β= 1.130) and Mn (β=-0.404) were significantly correlated with grip strength (P < 0.05). The results of the quantile g-computation showed that the risk of occurrence of grip strength reduction was -1.007 (95％ confidence interval:-1.362, -0.652; P < 0.001) when each quartile of the mixture of the seven metals was increased. Bayesian kernel function regression model analysis showed that mixtures of the seven metals had a negative overall effect on grip strength, with Cu, As and Sr being negatively associated with grip strength levels. In the total population, potential interactions were observed between As and Mn and between Cu and Mn (Pinteractions of 0.003 and 0.018, respectively).Conclusion In summary, this study suggests that combined exposure to metal mixtures is negatively associated with grip strength. Cu, Sr and As were negatively correlated with grip strength levels, and there were potential interactions between As and Mn and between Cu and Mn.

Objective:To examine the burden and trends of acute viral hepatitis in Guangdong Province from 1990 to 2019, and provide reference evidences for hepatitis prevention and control in the province.Methods:Data on acute viral hepatitis (hepatitis A, B, C, and E) in Guangdong from 1990 to 2019 were extracted from the Global Burden of Disease Study 2019 database. The incidence, prevalence, mortality, and disability-adjusted life years (DALY) data were analyzed by age and gender, and the estimated annual percentage change (EAPC) was calculated to describe the changing trends in disease burden.Results:From 1999 to 2019, the standardized incidence, prevalence, mortality, and DALY of acute viral hepatitis in Guangdong were higher than the national averages. In 2019, 51.43% (2 245 087/4 365 221) of acute viral hepatitis cases in Guangdong Province were mainly attributed to hepatitis B, and 77.18% (106/138) of deaths were due to acute hepatitis B. In different age groups, except for acute hepatitis B, which was more common in adults, the incidence rates of other types of viral hepatitis such as hepatitis A, B, and E showed an overall decreasing trend with age. The mortality rates of different types of acute viral hepatitis, except for the <5 age group, increased with age. The overall incidence and mortality rates of acute viral hepatitis were higher in men than in women.Conclusions:The overall burden of acute viral hepatitis in Guangdong declined in 2019, but remained higher than the national level. Further efforts are needed to strengthen hepatitis prevention and screening in different population in Guangdong Province, especially in children and the elderly.

"Global cancer statistics 2022" based on the latest GLOBCAN data from the International Agency for Research on Cancer (IARC) was recently released, providing a systematic analysis of the incidence and mortality of 36 types of cancer across 185 countries worldwide. The international burden of cancer is expected to continue to increase over the next 30 years, posing a severe public health and social challenge for many countries, including China. This article offers a key point interpretation of the "Global cancer statistics 2022", focusing on the evolution of cancer epidemiology and future development trends. The aim is to broaden the international perspective on cancer prevention and treatment, with the hope of providing reference and guidance for cancer prevention and treatment efforts in our country.

The occurrence of benign prostate hyperplasia(BPH)was related to disrupted sex steroid hormones,and metformin(Met)had a clinical response to sex steroid hormone-related gynaecological disease.How-ever,whether Met exerts an antiproliferative effect on BPH via sex steroid hormones remains unclear.Here,our clinical study showed that along with prostatic epithelial cell(PEC)proliferation,sex steroid hormones were dysregulated in the serum and prostate of BPH patients.As the major contributor to dysregulated sex steroid hormones,elevated dihydrotestosterone(DHT)had a significant positive rela-tionship with the clinical characteristics of BPH patients.Activation of adenosine 5'-monophosphate(AMP)-activated protein kinase(AMPK)by Met restored dysregulated sex steroid hormone homeostasis and exerted antiproliferative effects against DHT-induced proliferation by inhibiting the formation of androgen receptor(AR)-mediated Yes-associated protein(YAP1)-TEA domain transcription factor(TEAD4)heterodimers.Met's anti-proliferative effects were blocked by AMPK inhibitor or YAP1 over-expression in DHT-cultured BPH-1 cells.Our findings indicated that Met would be a promising clinical therapeutic approach for BPH by inhibiting dysregulated steroid hormone-induced PEC proliferation.

OBJECTIVE: To explore the clinical characteristics and genetic basis of a child with autism spectrum disorder (ASD) in conjunct with congenital heart disease (CHD). METHODS: A child who was hospitalized at the Third People's Hospital of Chengdu on April 13, 2021 was selected as the study subject. Clinical data of the child were collected. Peripheral blood samples of the child and his parents were collected and subjected to whole exome sequencing (WES). A GTX genetic analysis system was used to analyze the WES data and screen candidate variants for ASD. Candidate variant was verified by Sanger sequencing and bioinformatics analysis. Real-time fluorescent quantitative PCR (qPCR) was carried out to compare the expression of mRNA of the NSD1 gene between this child and 3 healthy controls and 5 other children with ASD. RESULTS: The patient, an 8-year-old male, has manifested with ASD, mental retardation and CHD. WES analysis revealed that he has harbored a heterozygous c.3385+2T>C variant in the NSD1 gene, which may affect the function of its protein product. Sanger sequencing showed that neither of his parent has carried the same variant. By bioinformatic analysis, the variant has not been recorded in the ESP, 1000 Genomes and ExAC databases. Analysis with Mutation Taster online software indicated it to be disease causing. Based on the guidelines from the American College of Medical Genetics and Genomics (ACMG), the variant was predicted to be pathogenic. By qPCR analysis, the expression level of mRNA of the NSD1 gene in this child and 5 other children with ASD was significantly lower than that of the healthy controls (P < 0.001). CONCLUSION The c.3385+2T>C variant of the NSD1 gene can significantly reduce its expression, which may predispose to ASD. Above finding has enriched the mutational spectrum the NSD1 gene.
Male ; Child ; Humans ; Autism Spectrum Disorder/genetics* ; Heart Defects, Congenital/genetics* ; Computational Biology ; Genomics ; Mutation ; RNA, Messenger/genetics* ; Histone-Lysine N-Methyltransferase/genetics*

The many-banded krait, Bungarus multicinctus, has been recorded as the animal resource of JinQianBaiHuaShe in the Chinese Pharmacopoeia. Characterization of its venoms classified chief phyla of modern animal neurotoxins. However, the evolutionary origin and diversification of its neurotoxins as well as biosynthesis of its active compounds remain largely unknown due to the lack of its high-quality genome. Here, we present the 1.58 Gbp genome of B. multicinctus assembled into 18 chromosomes with contig/scaffold N50 of 7.53 Mbp/149.8 Mbp. Major bungarotoxin-coding genes were clustered within genome by family and found to be associated with ancient local duplications. The truncation of glycosylphosphatidylinositol anchor in the 3'-terminal of a LY6E paralog released modern three-finger toxins (3FTxs) from membrane tethering before the Colubroidea divergence. Subsequent expansion and mutations diversified and recruited these 3FTxs. After the cobra/krait divergence, the modern unit-B of β-bungarotoxin emerged with an extra cysteine residue. A subsequent point substitution in unit-A enabled the β-bungarotoxin covalent linkage. The B. multicinctus gene expression, chromatin topological organization, and histone modification characteristics were featured by transcriptome, proteome, chromatin conformation capture sequencing, and ChIP-seq. The results highlighted that venom production was under a sophisticated regulation. Our findings provide new insights into snake neurotoxin research, meanwhile will facilitate antivenom development, toxin-driven drug discovery and the quality control of JinQianBaiHuaShe.

Objective: To investigate the specificity of endogenous metabolic profile in plasma of patients with occupational acute methyl acetate poisoning using non-targeted metabolomics. Methods: A total of six patients with occupational acute methyl acetate poisoning were selected as the poisoning group, while 10 healthy workers without occupational exposure history of chemical hazards in the same industry were selected as the control group using the judgment sampling method. Metabolites in patient plasma of the two groups were detected using ultra-high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry, and non-targeted metabolomics analysis was performed. Principal component analysis and partial least squares discriminant analysis were used to identify differential metabolites and analyze their metabolic pathways. Results: There were significant differences in metabolite profiles in patient plasma between poisoning group and control group. A total of 195 differentially expressed metabolites were screened in plasma of patients in poisoning group, including 119 upregulated and 76 downregulated metabolites. Lipid substances (lipids and lipid-like molecules) accounted for the highest proportion (21.5%). The differential metabolites of poisoning group were related to folate biosynthesis, amino acid metabolism, pyrimidine metabolism, sphingolipid biosynthesis and other metabolic pathways in plasma compared with the control group (all P<0.05). Conclusion: Occupational acute methyl acetate poisoning affects metabolism of the body. The folic acid biosynthesis, amino acid and lipid metabolism and other pathways may be involved in the occurrence and development of poisoning.