OBJECTIVE: To explore the application value of artificial intelligence (AI)-assisted chromosomal karyotype analysis in the diagnosis of prenatal chromosomal mosaicism. METHODS: A retrospective analysis was conducted on 172 pregnant women who underwent amniocentesis at the Department of Medical Genetics and Prenatal Diagnosis, the Third Affiliated Hospital of Zhengzhou University between January 2019 and December 2024. All cases whose fetuses were diagnosed with chromosomal mosaicism via karyotype analysis and stratified into two groups based on the analytical software employed: the conventional analysis group (n = 70), which utilized Leica analysis software for karyotype image recognition and cell counting; and the AI-assisted analysis group (n = 102), which utilized AI-assisted software for the same procedures. The clinical performance of AI-assisted karyotype analysis in diagnosing chromosomal mosaicism was comprehensively evaluated by comparing the types of mosaic karyotypes, distribution of mosaic ratios, and verification outcomes of different detection modalities between the two groups. This study was approved by the Medical Ethics Committee of the Third Affiliated Hospital of Zhengzhou University (Ethics No.: 2024-406-01). RESULTS: No statistically significant difference was observed in baseline characteristics (maternal age, gestational week, and indications for prenatal diagnosis) between the two groups. Regarding the detection efficacy for numerical and structural mosaicisms, no significant difference was found in the detection of numerical mosaicism. However, the conventional analysis group exhibited a significantly higher detection rate of autosomal structural mosaicism compared to the AI-assisted group (11.43% vs. 0.98%, P < 0.05). Numerical mosaicism cases were further verified using copy number variation sequencing (CNV-seq) and/or fluorescence in situ hybridization (FISH). The AI-assisted group demonstrated a significantly lower inconsistency rate (5.56% vs. 20.41%, P < 0.05) compared to the conventional group. For low-proportion (< 10%) chromosomal mosaicism, the AI-assisted group had a significantly lower detection rate (13.25% vs. 29.69%, P < 0.05). Subsequent validation of low-proportion mosaicism by CNV-seq and/or FISH showed a higher consistency rate in the AI-assisted group (81.82% vs. 54.55%), though the difference did not reach statistical significance (P = 0.360). CONCLUSION For the karyotyping analysis of prenatal chromosomal mosaicism, AI-assisted karyotype analysis shows high accuracy and consistency in identifying numerical chromosomal mosaicism, particularly in reducing the detection of low-proportion (< 10%) mosaicism while improving verification accuracy. AI-assisted analysis can significantly improve the detection accuracy of numerical mosaicism and mitigate the risk of misclassification for low-proportion (< 10%) mosaicism, thereby providing more precise clinical evidence for the prenatal diagnosis of chromosomal mosaicisms.
Humans ; Female ; Mosaicism ; Pregnancy ; Karyotyping/methods* ; Artificial Intelligence ; Prenatal Diagnosis/methods* ; Adult ; Retrospective Studies ; Chromosome Disorders/genetics* ; Amniocentesis

ObjectiveThis paper aims to investigate the distribution patterns of traditional Chinese medicine syndromes in patients with chronic hepatitis B （CHB） comorbid with metabolically associated fatty liver disease （MAFLD） and analyze their correlation with clinical characteristics and the progression of liver fibrosis. MethodsA cross-sectional study method was employed， and 506 patients with CHB comorbid with MAFLD who attended the Hepatology Outpatient Department of Public Health Clinical Center of Chengdu from June 2024 to December 2024 were enrolled. General information， traditional Chinese medicine syndromes information， laboratory indicators， and imaging examination results were collected using case report forms （CRF）. Tongue images of patients were acquired using a tongue diagnosis instrument， and tongue feature parameters were extracted using computer image processing technology. Frequency analysis， factor analysis， and cluster analysis， and other methods were used to explore syndrome categories and distribution patterns. Non-parametric tests were used to compare the differences in clinical characteristics among different syndromes. Univariate and multivariate logistic regression analyses were performed to investigate the correlation between traditional Chinese medicine syndromes and the progression of liver fibrosis. ResultsThe main traditional Chinese medicine syndromes in patients with CHB comorbid with MAFLD were mainly dominated by damp-heat accumulation syndrome， liver stagnation and spleen deficiency syndrome， and phlegm-blood stasis syndrome， with damp-heat accumulation syndrome accounting for the highest proportion （41.89%）. Compared with those without damp-heat accumulation syndrome， patients with damp-heat accumulation syndrome had significantly lower tongue proper H value， tongue coating H value， and tongue coating a^* value （P<0.05）， significantly higher tongue coating b^* value （P<0.05）， significantly increased levels of white blood cell （WBC）， red blood cell （RBC）， hemoglobin （HGB）， and glucose （GLU）， increased CAP values （P<0.05）， a higher proportion of males （P<0.05）， and a younger age （P<0.05）. Univariate and multivariate logistic regression analyses show that age， hepatitis B surface antigen （HBsAg）， diabetes， and damp-heat accumulation syndrome are independent risk factors for liver fibrosis （P<0.05）， and that damp-heat accumulation syndrome is predominantly distributed in liver fibrosis stage F0-F1. ConclusionDamp-heat accumulation syndrome is a typical syndrome in patients with CHB comorbid with MAFLD， which is significantly associated with enhanced inflammatory response， metabolic disorders， and early liver fibrosis， and is a key link in disease progression. Clinical attention and early intervention are needed.

Multidrug-resistant (MDR) bacterial infections have emerged as a serious challenge of global public health crisis. The overuse and misuse of conventional antibiotics have dramatically accelerated the emergence, evolution and worldwide spread of drug-resistant bacterial strains, necessitating urgent exploration of novel antibacterial strategies. Bacteriophages serve as natural bacterial predators offering distinct advantages including high host specificity, autonomous self-replication capabilities and cost-effective large-scale production. However, wild-type phages present significant clinical limitations due to their narrow host ranges, susceptibility to rapid immune clearance and poor penetration of bacterial biofilms, which severely restrict their therapeutic applications. The convergence of synthetic biology, nanotechnology and advanced gene editing technologies has accelerated the development of engineered bacteriophage platforms, providing programmable, scalable and clinically translatable pathways to overcome these inherent biological constraints. Here, we systematically delineate four fundamental strategies for engineered bacteriophage development. Chemical modification utilizes reactive functional groups such as amino, carboxyl and thiol moieties on capsid proteins through esterification, amidation or click chemistry reactions to achieve precise drug conjugation and surface functionalization. In vivo editing encompasses ultraviolet or chemical mutagenesis for random mutation induction, homologous recombination for targeted genetic alterations, recombineering methodologies including electroporation-mediated bacteriophage recombination engineering, and CRISPR-Cas systems for precise genome editing to enable exact genetic reconstruction and host range reprogramming. In vitro synthesis leverages genome engineering platforms where intact phage genomes are transferred into yeast or host bacteria to facilitate highly efficient homologous recombination, enabling large DNA fragment assembly and cross-gene host range expansion without bacterial toxicity constraints. Directed evolution combines artificial selection through mutation library screening with rational design approaches involving chimeric receptor binding protein construction or site-specific mutagenesis, effectively balancing the discovery of unknown adaptive pathways with targeted host specificity modification. Moreover, we comprehensively discuss therapeutic applications across diverse clinical scenarios. Engineered bacteriophage effectively disrupt bacterial biofilms through sophisticated functionalized delivery platforms including nanozyme-conjugated phages, phage-liposome nanoconjugates and bio-responsive hydrogels, demonstrating significantly enhanced bactericidal efficiency compared to unmodified free phages. These bioengineered vectors attenuate bacterial virulence and resensitize pathogens to antibiotics by delivering CRISPR-Cas systems or base editors to disrupt critical virulence factors such as pili, capsule synthesis machineries and quorum sensing systems, or by inactivating antibiotic resistance determinants including beta-lactamase genes. As an intelligent nanomedicine delivery platform, engineered bacteriophage enable precise pathogen elimination an through photocatalytic reactive oxygen species generation, immunomodulatory interventions, or controlled release of antibacterial drugs. Furthermore, oral administration of engineered bacteriophage facilitates microbiota modulation, which selectively eliminate intestinal pathogens while preserve beneficial commensal microbiota, thereby restoring microbial community balance and preventing complications associated with dysbiosis. Finally, we critically analyze persistent challenges including host strain matching complexity, evolution of bacterial resistance mechanisms, pharmacokinetic optimization requirements, optimal administration route selection, large-scale production quality control standards and clinical dosing determination protocols. Through multidisciplinary integration of synthetic biology, infectious disease medicine and immunology, future translational medicine studies of bacteriophage should establish comprehensive technical platforms encompassing rapid phage screening, intelligent rational design, rigorous in vivo evaluation and standardized clinical validation processes, ultimately advancing engineered bacteriophage from laboratory innovations to clinically approved therapeutics for effectively combating MDR bacterial infections.

Background/Aims: Liver cirrhosis involves chronic inflammation and progressive fibrosis.Among various immune cells, CD8+ T cells are considered a major contributor to hepatic inflammation and fibrosis. However, the exact molecular pathways governing CD8+ T-cell-mediated effects in cirrhosis remain unclear. Methods: This study analyzed transcriptomic and single-cell sequencing data to elucidate CD8+ T-cell heterogeneity and implications in cirrhosis. Results: Weighted gene co-expression analysis of bulk RNA-seq data revealed an association between cirrhosis severity and activated T-cell markers like HLA and chemokine genes. Furthermore, single-cell profiling uncovered eight CD8+ T-cell subtypes, notably, effector memory (Tem) and exhausted (Tex) T cells. Tex cells, defined by PDCD1, LAG3, and CXCL13 expression, were increased in cirrhosis, while Tem cells were decreased. Lineage tracing and differential analysis highlighted CXCL13+ Tex cells as a terminal, exhausted subtype of cells with roles in PD-1 signaling, glycolysis, and T-cell regulation. CXCL13+ Tex cells displayed T-cell exhaustion markers like PDCD1, HAVCR2, TIGIT, and TNFRSF9. Functional analysis implicated potential roles of these cells in immunosuppression. Finally, a CXCL13+ Tex-cell gene signature was found that correlated with cirrhosis severity and poorer prognosis of liver cancer. Conclusions In summary, this comprehensive study defines specialized CD8+ T-cell subpopulations in cirrhosis, with CXCL13+ Tex cells displaying an exhausted phenotype associated with immune dysregulation and advanced disease. Key genes and pathways regulating these cells present potential therapeutic targets.

Background/Aims: Liver cirrhosis involves chronic inflammation and progressive fibrosis.Among various immune cells, CD8+ T cells are considered a major contributor to hepatic inflammation and fibrosis. However, the exact molecular pathways governing CD8+ T-cell-mediated effects in cirrhosis remain unclear. Methods: This study analyzed transcriptomic and single-cell sequencing data to elucidate CD8+ T-cell heterogeneity and implications in cirrhosis. Results: Weighted gene co-expression analysis of bulk RNA-seq data revealed an association between cirrhosis severity and activated T-cell markers like HLA and chemokine genes. Furthermore, single-cell profiling uncovered eight CD8+ T-cell subtypes, notably, effector memory (Tem) and exhausted (Tex) T cells. Tex cells, defined by PDCD1, LAG3, and CXCL13 expression, were increased in cirrhosis, while Tem cells were decreased. Lineage tracing and differential analysis highlighted CXCL13+ Tex cells as a terminal, exhausted subtype of cells with roles in PD-1 signaling, glycolysis, and T-cell regulation. CXCL13+ Tex cells displayed T-cell exhaustion markers like PDCD1, HAVCR2, TIGIT, and TNFRSF9. Functional analysis implicated potential roles of these cells in immunosuppression. Finally, a CXCL13+ Tex-cell gene signature was found that correlated with cirrhosis severity and poorer prognosis of liver cancer. Conclusions In summary, this comprehensive study defines specialized CD8+ T-cell subpopulations in cirrhosis, with CXCL13+ Tex cells displaying an exhausted phenotype associated with immune dysregulation and advanced disease. Key genes and pathways regulating these cells present potential therapeutic targets.

BACKGROUND: Valvular heart disease (VHD) has become increasingly common with the aging in China. This study aimed to evaluate regional differences in the clinical features, management strategies, and outcomes of patients with VHD across different regions in China. METHODS: Data were collected from the China-VHD Study. From April 2018 to June 2018, 12,347 patients who presented with moderate or severe native VHD with a median of 2 years of follow-up from 46 centers at certified tertiary hospitals across 31 provinces, autonomous regions, and municipalities in Chinese mainland were included in this study. According to the locations of the research centers, patients were divided into five regional groups: eastern, southern, western, northern, and central China. The clinical features of VHD patients were compared among the five geographical regions. The primary outcome was all-cause mortality or rehospitalization for heart failure. Kaplan-Meier survival analysis was used to compare the cumulative incidence rate. RESULTS: Among the enrolled patients (mean age, 61.96 years; 6877 [55.70%] male), multiple VHD was the most frequent type (4042, 32.74%), which was mainly found in eastern China, followed by isolated mitral regurgitation (3044, 24.65%), which was mainly found in northern China. The etiology of VHD varied significantly across different regions of China. The overall rate of valve interventions was 32.67% (4008/12,268), with the highest rate in southern China at 48.46% (205/423). In terms of procedure, the proportion of transcatheter valve intervention was relatively low compared to that of surgical treatment. Patients with VHD in western China had the highest incidence of all-cause mortality or rehospitalization for heart failure. Valve intervention significantly improved the outcome of patients with VHD in all five regions (all P  <0.05). CONCLUSIONS: This study revealed that patients with VHD in China are characterized by significant geographic disparities in clinical features, treatment, and clinical outcomes. Targeted efforts are needed to improve the management and prognosis of patients with VHD in China according to differences in geographical characteristics. REGISTRATION ClinicalTrials.gov , NCT03484806.
Aged ; Female ; Humans ; Male ; Middle Aged ; China/epidemiology* ; Heart Valve Diseases/therapy* ; Kaplan-Meier Estimate ; Tertiary Care Centers ; Treatment Outcome

Under the background of carbon peaking and carbon neutrality goals, the Ministry of Ecology and Environment, together with 15 national ministries and commissions, has formulated the Implementation Plan on Establishing a Carbon Footprint Management System, and it is urgent for traditional Chinese medicine(TCM) pharmaceutical enterprises to carry out research on carbon footprint accounting methods of related products. Based on the life cycle assessment(LCA) theory, taking mulberry leaf extract produced by a certain enterprise as an example, this study analyzed the carbon footprint of TCM extracts during the life cycle. The results show that for every 1 kg of product produced, the carbon emissions from the stages of raw material acquisition, transportation, and extract production are-20.569, 1.205, and 173.577 kgCO_2eq(CO_2 equivalent), respectively. The carbon footprint of the product is 154.213 kgCO_2eq·kg~(-1). In addition, the carbon emission is the highest in the production stage, in which the consumption of ethanol solvents makes the greatest contribution to the carbon footprint, accounting for 25.71%, more than one-fourth of the total carbon footprint. The second contribution was from the treatment process of TCM residues, accounting for 19.67%, closely followed by wastewater treatment(17.71%), the consumption of hot steam(17.43%), and drinking water(16.90%). The consumption of electric power and packaging materials has a smaller carbon emission of 2.58%. In particular, the carbon emission caused by the consumption of packaging materials is only 0.04%, which is negligible. The results of the study are expected to provide a reference for TCM enterprises to carry out research on the carbon footprint of products, offer ideas for collaborative innovation in reducing pollution and carbon emissions throughout the entire industry chain of TCM, and develop new quality productivity of modern TCM industry based on green and low-carbon manufacturing.
Morus/chemistry* ; Plant Leaves/chemistry* ; Carbon Footprint ; Drugs, Chinese Herbal/chemistry* ; Plant Extracts/analysis* ; Medicine, Chinese Traditional

This study aims to investigate the potential effect of the water extract of fresh Rehmanniae Radix on hypercholesterolemia in mice that was induced by a high-fat and high-cholesterol diet and explore its possible mechanism from bile acid reabsorption. Male C57BL/6 mice were randomly assigned into the following groups: control, model, low-and high-dose(4 and 8 g·kg~(-1), respectively) fresh Rehmanniae Radix, and positive drug(simvastatin, 0.05 g·kg~(-1)). Other groups except the control group were fed with a high-fat and high-cholesterol diet for 6 consecutive weeks to induce hypercholesterolemia. From the 6th week, mice were administrated with corresponding drugs daily via gavage for additional 6 weeks, while continuing to be fed with a high-fat and high-cholesterol diet. Serum levels of total cholesterol(TC), triglycerides(TG), low density lipoprotein-cholesterol(LDL-c), high density lipoprotein-cholesterol(HDL-c), and total bile acid(TBA), as well as liver TC and TG levels and fecal TBA level, were determined by commercial assay kits. Hematoxylin-eosin(HE) staining, oil red O staining, and transmission electron microscopy were performed to observe the pathological changes in the liver. Three livers samples were randomly selected from each of the control, model, and high-dose fresh Rehmanniae Radix groups for high-throughput transcriptome sequencing. Differentially expressed genes were mined and KEGG pathway enrichment analysis was performed to predict the key pathways and target genes of the water extract of fresh Rehmanniae Radix in the treatment of hypercholesterolemia. RT-qPCR was employed to measure the mRNA levels of cholesterol 7α-hydroxylase(CYP7A1) and cholesterol 27α-hydroxylase(CYP27A1) in the liver. Western blot was employed to determine the protein levels of CYP7A1 and CYP27A1 in the liver as well as farnesoid X receptor(FXR), apical sodium-dependent bile acid transporter(ASBT), and ileum bile acid-binding protein(I-BABP) in the ileum. The results showed that the water extract of fresh Rehmanniae Radix significantly lowered the levels of TC and TG in the serum and liver, as well as the level of LDL-c in the serum. Conversely, it elevated the level of HDL-c in the serum and TBA in feces. No significant difference was observed in the level of TBA in the serum among groups. HE staining, oil red O staining, and transmission electron microscopy showed that the water extract reduced the accumulation of lipid droplets in the liver. Further mechanism studies revealed that the water extract of fresh Rehmanniae Radix significantly down-regulated the protein levels of FXR and bile acid reabsorption-related proteins ASBT and I-BABP. Additionally, it enhanced CYP7A1 and CYP27A1, the key enzymes involved in bile acid synthesis. Therefore, it is hypothesized that the water extract of fresh Rehmanniae Radix may exert an anti-hypercholesterolemic effect by regulating FXR/ASBT/I-BABP signaling, inhibiting bile acid reabsorption, and increasing bile acid excretion, thus facilitating the conversion of cholesterol to bile acids.
Animals ; Male ; Bile Acids and Salts/metabolism* ; Mice, Inbred C57BL ; Mice ; Diet, High-Fat/adverse effects* ; Cholesterol/metabolism* ; Drugs, Chinese Herbal/administration & dosage* ; Hypercholesterolemia/genetics* ; Receptors, Cytoplasmic and Nuclear/genetics* ; Rehmannia/chemistry* ; Liver/drug effects* ; Humans ; Cholesterol 7-alpha-Hydroxylase/genetics* ; Plant Extracts

The traditional Chinese medicine(TCM) industry is a crucial part of China's pharmaceutical sector and plays a strategic role in ensuring public health and promoting economic and social development. In response to the practical demand for high-quality development of the TCM industry, this paper focused on the bottlenecks encountered during the digital and intelligent transformation of TCM production systems. Specifically, it explored technical strategies and methodologies for constructing the best TCM production mode. An innovative artificial intelligence(AI)-centered technical architecture for TCM production was proposed, focusing on key aspects of production management including process modeling, state evaluation, and decision optimization. Furthermore, a series of critical technologies were developed to realize the best TCM production mode. Finally, a novel AI-driven TCM production mode characterized by a closed-loop system of "measurement-modeling-decision-execution" was presented through engineering case studies. This study is expected to provide a technological pathway for developing new quality productive forces within the TCM industry.
Artificial Intelligence ; Drugs, Chinese Herbal ; Medicine, Chinese Traditional/methods* ; Humans