Based on the theory of "disease of both blood and water" in Essentials from the Golden Cabinet （《金匮要略》）， and in combination with the dynamic syndrome evolution of heart failure with preserved ejection fraction （HFpEF）， this paper systematically clarifies the pathomechanism of HFpEF， characterized by yang deficiency as the root， blood stasis as the pivotal factor and water retention as the manifestation. Accordingly， the therapeutic principles have been proposed， which are warming yang and banking up original qi to consolidate the root， activating blood and unblocking collaterals to smooth the mechanism， and promoting urination and regulating pivot to remove the branch. On this basis， a compound formula structure of "one monarch， one minister and one assistant" is established， forming an integrated intervention strategy that synergistically combines the three methods of warming yang， activating blood， and promoting urination through combined classical formulas. Zhenwu Decoction （真武汤）， which warms yang and dissolves rheum， is used to consolidate the root and directly target the source of yang deficiency， serving as the monarch； Guizhi Fuling Pills （桂枝茯苓丸）， which activates blood， promotes urination and unblocks the pivot， assists in interrupting the binding of blood stasis and water retention， serving as the minister； Tingli Dazao Xiefei Decoction （葶苈大枣泻肺汤）， which regulates qi， disperses retained fluids， and eliminates the manifestation， alleviates acute water-retention symptoms， serving as the assistant. This compound formula is warming without being drying， diuretic without being drastic， and dispels stasis without consuming blood， thereby achieving the therapeutic effects of warming yang， activating blood， and promoting urination.

ObjectiveDonkey hide is the sole legally designated raw material for the preparation of the traditional Chinese medicine Ejiao. The quality stability of donkey hide during preservation directly determines the efficacy and safety of Ejiao. This study focuses on the dynamic succession of microbial communities during the preservation of donkey hides from different origins, aiming to clarify the correlation between microbial biodiversity difference and the degradation profiles of hide collagen and critical biochemical components, thereby providing a theoretical foundation for developing targeted preservation strategies based on microbial regulation. MethodsDonkey hides originating from four different regions were subjected to an accelerated microbial aging assay to simulate the spoilage process. The microbial community succession was analyzed using high-throughput sequencing. Microstructure changes and pore structure characteristics were assessed by scanning electron microscopy and mercury intrusion porosimetry, respectively. Additionally, the content of major components, including lipids, proteins, and sugars were determined by biochemical methods. ResultsAfter 96 h of aging, the collagen fiber structure in Africa donkey hides (ADH) exhibited significant degradation and collapse, followed by Xinjiang donkey hides (XDH). Instead, the microstructure of Dong’e black donkey hides (DDH) and Peru donkey hides (PDH) remained relatively intact. The porosities of DDH, XDH, PDH, and ADH increased from 27.9%, 15.7%, 30.3%, and 46.2% to 36.5%, 52.6%, 42.8%, and 57.7%, respectively, during the aging process, which suggested that the originally compact fiber structure was disrupted by microbial aging. Fourier transform infrared spectrometer analysis revealed the amide bands in XDH exhibited relatively weak intensity, and no collagen amide I band was observed in ADH. Meanwhile, the lipid and protein contents decreased in all four types of donkey hides, indicating that these components served as the primary nutrient sources for the growth of microorganism. Notably, the most severe collagen degradation was observed in XDH and ADH. A substantial increase was detected in the total soluble sugar in PDH aging solution and hydroxyproline in the ADH aging solution, respectively. These results indicated that donkey hides exhibit distinct patterns of structural degradation and nutrient utilization. Furthermore, the viable cells number of donkey hides increased sharply after 48 h of aging. Metagenomic analysis revealed that the relative abundance of Euryarchaeota in ADH, PDH and XDH declining from initial 93.19%, 97.73% and 30.08% to 0.79%, 1.43% and 0.02% after 96 h, respectively. Conversely, a significantly increase was observed in the abundance of Bacillota, with a marked increase in ADH, peaking at 92.75%. Additionally, the abundance of Pseudomonadota in PDH increased from 0.10% to 87.84%, suggesting that Bacillota and Pseudomonadota may be key factors exacerbating donkey hide spoilage. Unlike the other three types of donkey hides, the dominant bacterial phylum in DDH shifted from Pseudomonadota to Bacteroidota, characterized by a substantial abundance increase of Bacteroidota from 0.13% to 44.22%. ConclusionRegional variation in origin significantly influence the microbial aging of donkey hides, leading to distinct patterns of structural deterioration and differential nutrient utilization. Therefore, implementing origin-specific preservation strategies, through the precisely controlling environmental factors to suppress harmful phyla such as Bacillota and Pseudomonadota, is crucial for enhancing the storage quality of donkey hides.

ObjectiveINF2 is a member of the formins family. Abnormal expression and regulation of INF2 have been associated with the progression of various tumors, but the expression and role of INF2 in hepatocellular carcinoma (HCC) remain unclear. HCC is a highly lethal malignant tumor. Given the limitations of traditional treatments, this study explored the expression level, clinical value and potential mechanism of INF2 in HCC in order to seek new therapeutic targets. MethodsIn this study, we used public databases to analyze the expression of INF2 in pan-cancer and HCC, as well as the impact of INF2 expression levels on HCC prognosis. Quantitative real time polymerase chain reaction (RT-qPCR), Western blot, and immunohistochemistry were used to detect the expression level of INF2 in liver cancer cells and human HCC tissues. The correlation between INF2 expression and clinical pathological features was analyzed using public databases and clinical data of human HCC samples. Subsequently, the effects of INF2 expression on the biological function and Drp1 phosphorylation of liver cancer cells were elucidated through in vitro and in vivo experiments. Finally, the predictive value and potential mechanism of INF2 in HCC were further analyzed through database and immunohistochemical experiments. ResultsINF2 is aberrantly high expression in HCC samples and the high expression of INF2 is correlated with overall survival, liver cirrhosis and pathological differentiation of HCC patients. The expression level of INF2 has certain diagnostic value in predicting the prognosis and pathological differentiation of HCC. In vivo and in vitro HCC models, upregulated expression of INF2 triggers the proliferation and migration of the HCC cell, while knockdown of INF2 could counteract this effect. INF2 in liver cancer cells may affect mitochondrial division by inducing Drp1 phosphorylation and mediate immune escape by up-regulating PD-L1 expression, thus promoting tumor progression. ConclusionINF2 is highly expressed in HCC and is associated with poor prognosis. High expression of INF2 may promote HCC progression by inducing Drp1 phosphorylation and up-regulation of PD-L1 expression, and targeting INF2 may be beneficial for HCC patients with high expression of INF2.

BACKGROUND:Osteosarcoma has a complex pathogenesis and a poor prognosis.While advancements in medical technology have led to some improvements in the 5-year survival rate,substantial progress in its treatment has not yet been achieved. OBJECTIVE:To screen key molecular markers in osteosarcoma,analyze their relationship with osteosarcoma treatment drugs,and explore the potential disease mechanisms of osteosarcoma at the molecular level. METHODS:GSE99671 and GSE284259(miRNA)datasets were obtained from the Gene Expression Omnibus database.Differential gene expression analysis and Weighted Gene Co-expression Network Analysis(WGCNA)on GSE99671 were performed.Functional enrichment analysis was conducted using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes separately for the differentially expressed genes and the module genes with the highest positive correlation to the disease.The intersection of these module genes and differentially expressed genes was taken as key genes.A Protein-Protein Interaction network was constructed,and correlation analysis on the key genes was performed using CytoScape software,and hub genes were identified.Hub genes were externally validated using the GSE28425 dataset and text validation was conducted.The drug sensitivity of hub genes was analyzed using the CellMiner database,with a threshold of absolute value of correlation coefficient|R|>0.3 and P<0.05. RESULTS AND CONCLUSION:(1)Differential gene expression analysis identified 529 differentially expressed genes,comprising 177 upregulated and 352 downregulated genes.WGCNA analysis yielded a total of 592 genes with the highest correlation to osteosarcoma.(2)Gene Ontology enrichment results indicated that the development of osteosarcoma may be associated with extracellular matrix,bone cell differentiation and development,human immune regulation,and collagen synthesis and degradation.Kyoto Encyclopedia of Genes and Genomes enrichment results showed the involvement of pathways such as PI3K-Akt signaling pathway,focal adhesion signaling pathway,and immune response in the onset of osteosarcoma.(3)The intersection analysis revealed a total of 59 key genes.Through Protein-Protein Interaction network analysis,8 hub genes were selected,which were LUM,PLOD1,PLOD2,MMP14,COL11A1,THBS2,LEPRE1,and TGFB1,all of which were upregulated.(4)External validation revealed significantly downregulated miRNAs that regulate the hub genes,with hsa-miR-144-3p and hsa-miR-150-5p showing the most significant downregulation.Text validation results demonstrated that the expression of hub genes was consistent with previous research.(5)Drug sensitivity analysis indicated a negative correlation between the activity of methotrexate,6-mercaptopurine,and pazopanib with the mRNA expression of PLOD1,PLOD2,and MMP14.Moreover,zoledronic acid and lapatinib showed a positive correlation with the mRNA expression of PLOD1,LUM,MMP14,PLOD2,and TGFB1.This suggests that zoledronic acid and lapatinib may be potential therapeutic drugs for osteosarcoma,but further validation is required through additional basic experiments and clinical studies.

OBJECTIVES: This study aimed to investigate the impact of foam macrophages (FMs) on the intracellular survival of Mycobacterium tuberculosis (MTB) and identify the molecular mechanisms influencing MTB survival. METHODS: An in vitro FM model was established using oleic acid induction. Transcriptomic and metabolomic analyses were conducted to identify the key molecular pathways involved in FM-mediated MTB survival. RESULTS: Induced FMs effectively restricted MTB survival. Transcriptomic and metabolomic profiling revealed distinct changes in gene and metabolite expression in FMs during MTB infection compared with normal macrophages. Integrated analyses identified significant alterations in the cyclic adenosine monophosphate (cAMP) signaling pathway, indicating that its activation contributes to the FM-mediated restriction of MTB survival. CONCLUSIONS FMs inhibit MTB survival. The cAMP signaling pathway is a key contributor. These findings enhance the understanding of the role of FMs in tuberculosis progression, suggest potential targets for host-directed therapies, and offer new directions for developing diagnostic and therapeutic strategies against tuberculosis.
Mycobacterium tuberculosis/physiology* ; Transcriptome ; Metabolomics ; Foam Cells/microbiology* ; Humans ; Metabolome ; Tuberculosis/microbiology* ; Gene Expression Profiling

OBJECTIVE: To assess the independent and combined effects of air pollutants, meteorological factors, and greenspace exposure on new tuberculosis (TB) cases. METHODS: TB case data from Shanghai (2013-2018) were obtained from the Shanghai Center for Disease Control and Prevention. Environmental data on air pollutants, meteorological variables, and greenspace exposure were obtained from the National Tibetan Plateau Data Center. We employed a distributed-lag nonlinear model to assess the effects of these environmental factors on TB cases. RESULTS: Increased TB risk was linked to PM _2.5, PM ₁₀, and rainfall, whereas NO ₂, SO ₂, and air pressure were associated with a reduced risk. Specifically, the strongest cumulative effects occurred at various lags: PM _2.5 ( RR = 1.166, 95% CI: 1.026-1.325) at 0-19 weeks; PM ₁₀ ( RR = 1.167, 95% CI: 1.028-1.324) at 0-18 weeks; NO ₂ ( RR = 0.968, 95% CI: 0.938-0.999) at 0-1 weeks; SO ₂ ( RR = 0.945, 95% CI: 0.894-0.999) at 0-2 weeks; air pressure ( RR = 0.604, 95% CI: 0.447-0.816) at 0-8 weeks; and rainfall ( RR = 1.404, 95% CI: 1.076-1.833) at 0-22 weeks. Green space exposure did not significantly impact TB cases. Additionally, low temperatures amplified the effect of PM _2.5 on TB. CONCLUSION Exposure to PM _2.5, PM ₁₀, and rainfall increased the risk of TB, highlighting the need to address air pollutants for the prevention of TB in Shanghai.
China/epidemiology* ; Humans ; Air Pollutants/analysis* ; Tuberculosis/epidemiology* ; Incidence ; Meteorological Concepts ; Particulate Matter/adverse effects* ; Environmental Exposure ; Male ; Female ; Adult ; Air Pollution ; Middle Aged

Objective To analyze the influencing factors of death in the elderly with coronavirus disease 2019(COVID-19).Methods The case data of death caused by COVID-19 in West China Fourth Hospital from January 1 to July 8,2023 were collected,and surviving cases from the West China Elderly Health Cohort infected with COVID-19 during the same period were selected as the control.LASSO-Logistic regression was adopted to analyze the data after propensity score matching and the validity of the model was verified by drawing the receiver operating characteristic curve.Results A total of 3 239 COVID-19 survivors and 142 deaths with COVID-19 were included.The results of LASSO-Logistic regression showed that smoking(OR=3.33,95%CI=1.46-7.59,P=0.004),stroke(OR=3.55,95%CI=1.15-10.30,P=0.022),malignant tumors(OR=19.93, 95%CI=8.52-49.23, P<0.001),coronary heart disease(OR=7.68, 95%CI=3.52-17.07, P<0.001),fever(OR=0.51, 95%CI=0.26-0.96, P=0.042),difficulty breathing or asthma symptoms(OR=21.48, 95%CI=9.44-51.95, P<0.001),and vomiting(OR=8.19,95%CI=2.87-23.58, P<0.001)increased the risk of death with COVID-19.The prediction model constructed based on the influencing factors achieved an area under the curve of 0.889 in the test set.Conclusions Smoking,stroke,malignant tumors,coronary heart disease,fever,breathing difficulty or asthma symptoms,and vomiting were identified as key factors influencing the death risk in COVID-19.
Humans ; COVID-19/mortality* ; Aged ; Propensity Score ; China/epidemiology* ; Risk Factors ; Logistic Models ; Smoking ; SARS-CoV-2 ; Male ; Female ; Stroke ; Neoplasms

Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91％of the total clinical isolates and 4.07％of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89％were isolated from children and 33.11％were isolated from adults.More than 90％of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79％in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06％were isolated from children and 19.94％isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0％.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.

Objective To understand the changing composition and antibiotic resistance of bacterial species in the clinical isolates from outpatient and emergency department(hereinafter referred to as outpatients)and inpatient children over time in various hospitals,and to provide laboratory evidence for rational antibiotic use.Methods The data on clinically isolated pathogenic bacteria and antimicrobial susceptibility of isolates from outpatients and inpatient children in the CHINET program from 2015 to 2021 were collected and analyzed.Results A total of 278 471 isolates were isolated from pediatric patients in the CHINET program from 2015 to 2021.About 17.1％of the strains were isolated from outpatients,primarily group A β-hemolytic Streptococcus,Escherichia coli,and Staphylococcus aureus.Most of the strains(82.9％)were isolated from inpatients,mainly SS.aureus,E.coli,and H.influenzae.The prevalence of methicillin-resistant S.aureus(MRSA)in outpatients(24.5％)was lower than that in inpatient children(31.5％).The MRSA isolates from outpatients showed lower resistance rates to the antibiotics tested than the strains isolated from inpatient children.The prevalence of vancomycin-resistant Enterococcus faecalis or E.faecium and penicillin-resistant S.pneumoniae was low in either outpatients or inpatient children.S.pneumoniae,β-hemolytic Streptococcus and S.viridans showed high resistance rates to erythromycin.The prevalence of erythromycin-resistant group A β-hemolytic Streptococcus was higher in outpatients than that in inpatient children.The prevalence of β-lactamase-producing H.influenzae showed an overall upward trend in children,but lower in outpatients(45.1％)than in inpatient children(59.4％).The prevalence of carbapenem-resistant Klebsiella pneumoniae(CRKpn),carbapenem-resistant Pseudomonas aeruginosa(CRPae)and carbapenem-resistant Acinetobacter baumannii(CRAba)was 14％,11.7％,47.8％in outpatients,but 24.2％,20.6％,and 52.8％in inpatient children,respectively.The prevalence of multidrug-resistant E.coli,K.pneumoniae,Proteus mirabilis,P.aeruginosa and A.baumannii strains was lower in outpatients than in inpatient children.The prevalence of fluoroquinolone-resistant E.coli,ESBLs-producing K.pneumoniae,ESBLs-producing P.mirabilis,carbapenem-resistant E.coli(CREco),CRKpn,and CRPae was lower in children in outpatients than in inpatient children,but the prevalence of CRAba in 2021 was higher than in inpatient children.Conclusions The distribution of clinical isolates from children is different between outpatients and inpatients.The prevalence of MRSA,ESBL,and CRO was higher in inpatient children than in outpatients.Antibiotics should be used rationally in clinical practice based on etiological diagnosis and antimicrobial susceptibility test results.Ongoing antimicrobial resistance surveillance and prevention and control of hospital infections are crucial to curbing bacterial resistance.