Artificial intelligence-driven multiomics predictive model for abdominal aortic aneurysm subtypes to identify heterogeneous immune cell infiltration and predict disease progression.

BACKGROUND: Abdominal aortic aneurysm (AAA) poses a significant health risk and is influenced by various compositional features. This study aimed to develop an artificial intelligence-driven multiomics predictive model for AAA subtypes to identify heterogeneous immune cell infiltration and predict disease progression. Additionally, we investigated neutrophil heterogeneity in patients with different AAA subtypes to elucidate the relationship between the immune microenvironment and AAA pathogenesis. METHODS: This study enrolled 517 patients with AAA, who were clustered using k-means algorithm to identify AAA subtypes and stratify the risk. We utilized residual convolutional neural network 200 to annotate and extract contrast-enhanced computed tomography angiography images of AAA. A precise predictive model for AAA subtypes was established using clinical, imaging, and immunological data. We performed a comparative analysis of neutrophil levels in the different subgroups and immune cell infiltration analysis to explore the associations between neutrophil levels and AAA. Quantitative polymerase chain reaction, Western blotting, and enzyme-linked immunosorbent assay were performed to elucidate the interplay between CXCL1, neutrophil activation, and the nuclear factor (NF)-κB pathway in AAA pathogenesis. Furthermore, the effect of CXCL1 silencing with small interfering RNA was investigated. RESULTS: Two distinct AAA subtypes were identified, one clinically more severe and more likely to require surgical intervention. The CNN effectively detected AAA-associated lesion regions on computed tomography angiography, and the predictive model demonstrated excellent ability to discriminate between patients with the two identified AAA subtypes (area under the curve, 0.927). Neutrophil activation, AAA pathology, CXCL1 expression, and the NF-κB pathway were significantly correlated. CXCL1, NF-κB, IL-1ß, and IL-8 were upregulated in AAA. CXCL1 silencing downregulated NF-κB, interleukin-1ß, and interleukin-8. CONCLUSION: The predictive model for AAA subtypes demonstrated accurate and reliable risk stratification and clinical management. CXCL1 overexpression activated neutrophils through the NF-κB pathway, contributing to AAA development. This pathway may, therefore, be a therapeutic target in AAA.

Construction of prediction models for novel subtypes in patients with arteriosclerosis obliterans undergoing endovascular therapy: an unsupervised machine learning study.

BACKGROUND: Arteriosclerosis obliterans (ASO) is a chronic arterial disease that can lead to critical limb ischemia. Endovascular therapy is increasingly used for limb salvage in ASO patients, but the outcomes vary. The development of prediction models using unsupervised machine learning may lead to the identification of novel subtypes to guide patient prognosis and treatment. METHODS: This retrospective study analyzed clinical data from 448 patients with ASOs who underwent endovascular therapy. Unsupervised machine learning algorithms were employed to identify subgroups. To validate the precision of the clustering outcomes, an analysis of the postoperative results of the clusters was conducted. A prediction model was constructed using binary logistic regression. RESULTS: Two distinct subgroups were identified by unsupervised machine learning and characterized by differing patterns of clinical features. Patients in Cluster 2 had significantly worse conditions and prognoses than those in Cluster 1. For the novel ASO subtypes, a nomogram was developed using six predictive factors, namely, platelet count, ankle brachial index, Rutherford category, operation method, hypertension, and diabetes status. The nomogram achieved excellent discrimination for predicting membership in the two identified clusters, with an area under the curve of 0.96 and 0.95 in training cohort and internal test cohort. CONCLUSION: This study demonstrated that unsupervised machine learning can reveal novel phenotypic subgroups of patients with varying prognostic risk who underwent endovascular therapy. The prediction model developed could support clinical decision-making and risk counseling for this complex patient population. Further external validation is warranted to assess the generalizability of the findings.

Large-scale comparative analysis reveals phylogenomic preference of blaNDM-1 and blaKPC-2 transmission among Klebsiella pneumoniae.

blaNDM-1 and blaKPC-2 are responsible for the global increase in carbapenem-resistant Klebsiella pneumoniae, posing a great challenge to public health. However, the impact of phylogenetic factors on the dissemination of blaNDM-1 and blaKPC-2 is not yet fully understood. This study established a global dataset of 4051 blaNDM-1+ and 10,223 blaKPC-2+ K. pneumoniae genomes, and compared their transmission modes on a global scale. The results showed that blaNDM-1+ K. pneumoniae genomes exhibited a broader geographical distribution and higher sequence type (ST) richness than blaKPC-2+ genomes, indicating higher transmissibility of the blaNDM-1 gene. Furthermore, blaNDM-1+ genomes displayed significant differences in ST lineage, antibiotic resistance gene composition, virulence gene composition and genetic environments compared with blaKPC-2+ genomes, suggesting distinct dissemination mechanisms. blaNDM-1+ genomes were predominantly associated with ST147 and ST16, whereas blaKPC-2+ genomes were mainly found in ST11 and ST258. Significantly different accessory genes were identified between blaNDM-1+ and blaKPC-2+ genomes. The preference for blaKPC-2 distribution across certain countries, ST lineages and genetic environments underscores vertical spread as the primary mechanism driving the expansion of blaKPC-2. In contrast, blaNDM-1+ genomes did not display such a strong preference, confirming that the dissemination of blaNDM-1 mainly depends on horizontal gene transfer. Overall, this study demonstrates different phylogenetic drivers for the dissemination of blaNDM-1 and blaKPC-2, providing new insights into their global transmission dynamics.

Construction of a novel lower-extremity peripheral artery disease subtype prediction model using unsupervised machine learning and neutrophil-related biomarkers.

Lower-extremity peripheral artery disease (LE-PAD) is a prevalent circulatory disorder with risks of critical limb ischemia and amputation. This study aimed to develop a prediction model for a novel LE-PAD subtype to predict the severity of the disease and guide personalized interventions. Additionally, LE-PAD pathogenesis involves altered immune microenvironment, we examined the immune differences to elucidate LE-PAD pathogenesis. A total of 460 patients with LE-PAD were enrolled and clustered using unsupervised machine learning algorithms (UMLAs). Logistic regression analyses were performed to screen and identify predictive factors for the novel subtype of LE-PAD and a prediction model was built. We performed a comparative analysis regarding neutrophil levels in different subgroups of patients and an immune cell infiltration analysis to explore the associations between neutrophil levels and LE-PAD. Through hematoxylin and eosin (H&E) staining of lower-extremity arteries, neutrophil infiltration in patients with and without LE-PAD was compared. We found that UMLAs can helped in constructing a prediction model for patients with novel LE-PAD subtypes which enabled risk stratification for patients with LE-PAD using routinely available clinical data to assist clinical decision-making and improve personalized management for patients with LE-PAD. Additionally, the results indicated the critical role of neutrophil infiltration in LE-PAD pathogenesis.

Identification of Clinical Heterogeneity and Construction of Prediction Models for Novel Subtypes in Patients with Abdominal Aortic Aneurysm: An Unsupervised Machine Learning Study.

BACKGROUND: Abdominal aortic aneurysm (AAA) is one of the most common diseases in vascular surgery. Endovascular aneurysm repair (EVAR) can effectively treat AAA. It is essential to accurately classify patients with AAA who need EVAR. METHODS: We enrolled 266 patients with AAA who underwent EVAR. Unsupervised machine learning algorithms (UMLAs) were used to cluster subjects according to similar clinical characteristics. To verify UMLA's accuracy, the operative and postoperative results of the 2 clusters were analyzed. Finally, a prediction model was developed using binary logistic regression analysis. RESULTS: UMLAs could correctly classify patients based on their clinical characteristics. Patients in Cluster 1 were older, had a higher BMI, and were more likely than patients in Cluster 2 to develop pneumonia, chronic obstructive pulmonary disease, and cerebrovascular disease. The aneurysm diameter, neck angulation, diameter and angulation of bilateral common iliac arteries, and incidence of iliac artery aneurysm were significantly higher in cluster 1 patients than in cluster 2. Cluster 1 had a longer operative time, a longer length of stay in the intensive care unit and hospital, a higher medical expense, and a higher incidence of reintervention. A nomogram was established based on the BMI, neck angulation, left common iliac artery (LCIA) diameter and angulation, and right common iliac artery (RCIA) diameter and angulation. The nomogram was evaluated using receiver operating characteristic curve analysis, with an area under the curve of 0.933 (95% confidence interval, 0.902-0.963) and a C-index of 0.927. CONCLUSIONS: Our findings demonstrate that UMLAs can be used to rationally classify a heterogeneous cohort of patients with AAA effectively, and the analysis of postoperative variables also verified the accuracy of UMLAs. We established a prediction model for new subtypes of AAA, which can improve the quality of management of patients with AAA.

Risk Factors and Outcomes for Isolation with Polymyxin B-Resistant Enterobacterales from 2018-2022: A Case-Control Study.

Purpose: To analyze the risk factors and clinical outcomes of patients isolated with polymyxin B-resistant (PR) Enterobacterales from various clinical specimens to prevent and control the spread of these strains. Methods: This retrospective case-control study included 72 PR Enterobacterales-positive cases and 144 polymyxin B-susceptible (PS) Enterobacterales controls from 2018 to 2022. Patients with PR Enterobacterales isolated in various clinical cultures were defined as cases. Patients with PS Enterobacterales cultures at similar anatomic sites during the same period were randomly selected as controls. Data were collected from clinical and laboratory test records. Bivariable logistic regression and Pearson's chi-square tests were used to assess risk factors. Results: PR strains were predominantly Klebsiella pneumoniae (72.2%) and Salmonella enteritidis (8.3%). Of the patients, 66.04% were admitted to an intensive care unit (ICU). Risk factors for isolation with PR strains included chronic heart disease (P = 0.012; odds ratio [OR] 1.15; 95% confidence interval [CI] 1.03-1.28), immunosuppressant use (P = 0.016; OR 1.04 [1.0-1.07), drainage tube [head] (P = 0.006; OR 1.1 [1.0-1.1]), and polymyxin B exposure (P = 0.007; OR 1.03 [1.0-1.06]. With respect to outcomes, admission to an ICU (P = 0.003; OR 7.1 [1.9-25.4]), hypertension (P = 0.035; OR 1.4 [1.02-1.83]), and drainage tube [head] (P = 0.044; OR 1.1 [1.0-1.15]) were associated with treatment failure. Additionally, treatment failure was more frequent in patients (45.83%) than in controls (14.58%). Conclusion: The major risk factors for isolation with PR strains were chronic heart disease, exposure to immunosuppressants, use of drainage tubes, and polymyxin B exposure. The isolation of PR strains in patients was a predictor of unfavorable outcomes. These findings provide a basis for monitoring the spread of PR Enterobacterales.

Analysis of the features of 105 confirmed CRISPR loci in 487 Klebsiella variicola.

Klebsiella variicola, an emerging human pathogen, poses a threat to public health. The horizontal gene transfer (HGT) of plasmids is an important driver of the emergence of multiple antibiotic-resistant K. variicola. Clustered regularly interspersed short palindromic repeats (CRISPR) coupled with CRISPR-associated genes (CRISPR/Cas) constitute an adaptive immune system in bacteria, and can provide acquired immunity against HGT. However, the information about the CRISPR/Cas system in K. variicola is still limited. In this study, 487 genomes of K. variicola obtained from the National Center for Biotechnology Information database were used to analyze the characteristics of CRISPR/Cas systems. Approximately 21.56% of genomes (105/487) harbor at least one confirmed CRISPR array. Three types of CRISPR/Cas systems, namely the type I-E, I-E*, and IV-A systems, were identified among 105 strains. Spacer origin analysis further revealed that approximately one-third of spacers significantly match plasmids or phages, which demonstrates the implication of CRISPR/Cas systems in controlling HGT. Moreover, spacers in K. variicola tend to target mobile genetic elements from K. pneumoniae. This finding provides new evidence of the interaction of K. variicola and K. pneumoniae during their evolution. Collectively, our results provide valuable insights into the role of CRISPR/Cas systems in K. variicola.

Characterization and diversity of CRISPR/Cas systems in Klebsiella oxytoca.

CRISPR (clustered regularly interspaced short palindromic repeats)/Cas (CRISPR-associated protein) system is a crucial adaptive immune system for bacteria to resist foreign DNA infection. In this study, we investigated the prevalence and diversity of CRISPR/Cas systems in 175 Klebsiella oxytoca (K. oxytoca) strains. Specifically, 58.86% (103/175) of these strains possessed at least one confirmed CRISPR locus. Two CRISPR/Cas system types, I-F and IV-A3, were identified in 69 strains. Type I-F system was the most prevalent in this species, which correlated well with MLST. Differently, type IV-A3 system was randomly distributed. Moreover, the type IV-A3 system was separated into two subgroups, with subgroup-specific cas genes and repeat sequences. In addition, spacer origin analysis revealed that approximately one-fifth of type I-F spacers and one-third of type IV-A3 spacers had a significant match to MGEs. The phage tail tape measure protein and conjunctive transfer system protein were important targets of type I-F and IV-A3 systems in K. oxytoca, respectively. PAM sequences were inferred to be 5'-NCC-3' for type I-F, 5'-AAG-3' for subgroup IV-A3-a, and 5'-AAN-3' for subgroup IV-A3-b. Collectively, our findings will shed light on the prevalence, diversity, and functional effects of the CRISPR/Cas system in K. oxytoca.

Immune-dysregulated neutrophils characterized by upregulation of CXCL1 may be a potential factor in the pathogenesis of abdominal aortic aneurysm and systemic lupus erythematosus.

Background: The abdominal aortic aneurysm (AAA) incidence is closely related to systemic lupus erythematosus (SLE). However, the common mechanisms between AAA and SLE are still unknown. The purpose of this research was to examine the main molecules and pathways involved in the immunization process that lead to the co-occurrence of AAA and SLE through the utilization of quantitative bioinformatics analysis of publicly available RNA sequencing databases. Moreover, routine blood test information was gathered from 460 patients to validate the findings. Materials and methods: Datasets of both AAA (GSE57691 and GSE205071) and SLE (GSE50772 and GSE154851) were downloaded from the Gene Expression Omnibus (GEO) database, and differentially expressed genes (DEGs) were analyzed using bioinformatic tools. To determine the functions of the common differentially expressed genes (DEGs), Gene Ontology (GO) and Kyoto Encyclopedia analyses were conducted. Subsequently, the hub gene was identified through cytoHubba, and its validation was carried out in GSE47472 for AAA and GSE81622 for SLE. Immune cell infiltration analysis was performed to identify the key immune cells correlated with AAA and SLE, and to evaluate the correlation between key immune cells and the hub gene. Subsequently, the routine blood test data of 460 patients were collected, and the result of the immune cell infiltration analysis was further validated by univariate and multivariate logistic regression analysis. Results: A total of 25 common DEGs were obtained, and three genes were screened by cytoHubba algorithms. Upon validation of the datasets, CXCL1 emerged as the hub gene with strong predictive capabilities, as evidenced by an area under the curve (AUC) > 0.7 for both AAA and SLE. The infiltration of immune cells was also validated, revealing a significant upregulation of neutrophils in the AAA and SLE datasets, along with a correlation between neutrophil infiltration and CXCL1 upregulation. Clinical data analysis revealed a significant increase in neutrophils in both AAA and SLE patients (p < 0.05). Neutrophils were found to be an independent factor in the diagnosis of AAA and SLE, exhibiting good diagnostic accuracy with AUC >0.7. Conclusion: This study elucidates CXCL1 as a hub gene for the co-occurrence of AAA and SLE. Neutrophil infiltration plays a central role in the development of AAA and SLE and may serve to be a potential diagnostic and therapeutic target.

Factors affecting distal false lumen enlargement after thoracic endovascular aortic repair for type B aortic dissection.

Objective: To investigate the factors influencing distal false lumen enlargement after thoracic endovascular aortic repair (TEVAR) for type B aortic dissection. Materials and methods: Data were collected on patients with type B aortic dissection who underwent TEVAR from January 2008 to August 2022. Patients were divided into a distal aortic segmental enlargement (DSAE) group and a non-DSAE group based on whether the distal false lumen was dilated more than 5 mm on computed tomographic angiography (CTA) images. To analyze the independent influences on distal false lumen dilatation after TEVAR, the variables with a P value < 0.05 during univariate analysis were included in the binary logistic regression analysis model. Results: A total of 335 patients were included in this study, with 85 in the DSAE group and 250 in the non-DSAE group. The mean age was 52.40 ± 11.34 years, 289 (86.27%) were male patients, and the median follow-up time was 6.41 (11.99-29.99) months. There were significant differences in Marfan syndrome, chronic obstructive pulmonary disease (COPD), and follow-up time between the two groups. In terms of morphology, there were statistically significant differences in the number of tears, the size of the primary tear, and the length of dissection between the two groups. Binary logistic regression analysis indicated that Marfan syndrome, COPD, and the primary tear size were associated with distal false lumen dilatation. Conclusions: Marfan syndrome, COPD, and the primary tear size influence distal aortic segmental enlargement after TEVAR in type B aortic dissection patients.

Characteristics of humoral and cellular responses to coronavirus disease 2019 (COVID-19) inactivated vaccine in central China: A prospective, multicenter, longitudinal study.

Introduction: In China, the long-term immunogenicity and adverse effects of inactivated vaccines produced by different or the same manufacturer remain unclear. Therefore, the objective of this study was to evaluate the cellular immune responses and neutralizing antibody kinetics of homologous and heterologous administrations of an inactivated coronavirus disease 2019 (COVID-19) vaccine 240 days after the second vaccination. Methods: This prospective, multicenter, observational, longitudinal study involved 595 participants with a negative SARS-CoV-2 polymerase chain reaction result who were serologically tested and followed for 8 months after vaccination. Neutralizing antibodies, interferon-gamma (IFN-γ), interleukin (IL)-6, CD4+ T-lymphocyte, and B-lymphocyte counts were evaluated in serum samples after stimulation with 2 µg/mL SARS-CoV-2 spike protein for 16 h at follow-up intervals of 2 months. Results: Most participants [582/595; 146 male participants, 449 female participants; mean age 35 (26-50 years)] rapidly developed neutralizing antibodies after two doses of the vaccine administered 3-weeks apart. The positive rate of neutralizing antibodies peaked at 97.7% at 60-90 days, decreased, and stabilized at 82.9% at 181-240 days post-vaccination. Lower antibody concentrations were correlated with older age, longer duration after vaccination, non-health care workers, mixed-manufacturer vaccinations, and intervals of less than 40 days between two doses of vaccination, whereas lower IFN-γ levels and B-lymphocyte counts were associated with older age, blood type A, and non-health care workers. A higher IL-6 level was associated with older age, mixed-manufacturer vaccinations, intervals of less than 40 days between two doses of vaccination, and medical staff. Adverse reactions were mild or moderate and self-limited, with no serious events reported. Discussion: Two doses of the Chinese inactivated vaccine induced robust and rapid antibody expression and cellular immune responses. Boosting vaccination is considered important, as antibodies and cellular immune responses were reduced in susceptible populations.

Evaluation of Commercial Products for Colistin and Polymyxin B Susceptibility Testing for mcr-Positive and Negative Escherichia coli and Klebsiella pneumoniae in China.

Purpose: To evaluate the performance of five widespread commercial products for colistin and polymyxin B susceptibility testing in China for mcr-positive and -negative Escherichia coli and Klebsiella pneumoniae. Methods: A total of 132 E. coli and 83 K. pneumoniae strains (including 68 mcr-1-positive E. coli and 28 mcr-8-positive K. pneumoniae) were collected. We analysed the performance of colistin susceptibility (with Vitek 2 and Phoenix M50) and the performance of polymyxin B susceptibility (with DL-96II, MA120, and a Polymyxin B Susceptibility Test strip; POL E-strip). Broth microdilution was used as the gold standard. Categorical agreement (CA), essential agreement (EA), major error (ME), and very major error (VME) were calculated for comparisons. Results: For E. coli, the total CA, EA, ME, and VME to colistin were as follows: Vitek 2, 98.5%/98.5%/0%/2.9%; and Phoenix M50, 98.5%/97.7%/0%/2.9%. The total CA, EA, ME, and VME to polymyxin B were as follows: POL E-strip, 99.2%/63.6%/1.6%/0%; MA120, 70.0%/-/0%/58.8%; and DL-96II, 80.2%/-/1.6%/36.8%. Only Vitek 2 and Phoenix M50 presented satisfactory performances for mcr-1-positive E. coli. For K. pneumoniae, the total CA, EA, ME, and VME to colistin were as follows: Vitek 2, 73.2%/72.0%/0%/61.6%; and Phoenix M50, 74.7%/74.7%/0%/58.3%. The total CA, EA, ME, and VME to polymyxin B were as follows: POL E-strip, 91.6%/74.7%/2.1%/16.7%; MA120, 92.8%/-/2.1%/13.9%; and DL-96II, 92.2%/-/2.1%/8.3%. All systems were unsatisfactory for mcr-8-positive K. pneumoniae. When the susceptibility of mcr-negative strains was tested, all systems presented excellent performance. Conclusion: Vitek 2 and Phoenix M50 with colistin for E. coli showed acceptable performance regardless of mcr-1 expression, while DL-96II, MA120, and the POL E-strip performed worse for mcr-1-positive strains. Furthermore, mcr-8 greatly affected the performance of all systems with both colistin and polymyxin B for K. pneumoniae isolates.

Genomic Insights into CRISPR-Harboring Plasmids in the Klebsiella Genus: Distribution, Backbone Structures, Antibiotic Resistance, and Virulence Determinant Profiles.

CRISPR systems are often encoded by many prokaryotes as adaptive defense against mobile genetic elements (MGEs), but several MGEs also recruit CRISPR components to perform additional biological functions. Type IV-A systems are identified in Klebsiella plasmids, yet the distribution, characterization, and role of these plasmids carrying CRISPR systems in the whole Klebsiella genus remain unclear. Here, we performed large-scale comparative analysis of these plasmids using publicly available plasmid genomes. CRISPR-harboring plasmids were mainly distributed in Klebsiella pneumoniae (9.09%), covering 19.23% of sequence types, but sparse in Klebsiella species outside Klebsiella pneumoniae (3.92%). Plasmid genome comparison reiterated that these plasmids often carried the cointegrates of IncFIB and IncHI1B replicons, occasionally linked to other replicons, such as IncFIA, IncFII, IncR, IncQ, and IncU. Comparative genome analysis showed that CRISPR-carrying Klebsiella plasmids shared a conserved pNDM-MAR-like conjugation module as their backbones and served as an important vector for the accretion of antibiotic resistance genes (ARGs) and even virulence genes (VGs). Moreover, compared with CRISPR-negative IncFIB/IncHIB plasmids, CRISPR-positive IncFIB/IncHIB plasmids displayed high divergences in terms of ARGs, VGs, GC content, plasmid length, and backbone structures, suggesting their divergent evolutionary paths. The network analysis revealed that CRISPR-positive plasmids yielded fierce competitions with other plasmid types, especially conjugative plasmids, thereby affecting the dynamics of plasmid transmission. Overall, our study provides valuable insights into the role of CRISPR-positive plasmids in the spread of ARGs and VGs in Klebsiella genus.

A distributed and integrated control strategy for an islanded microgrid considering line loss and communication interruption.

To improve the stability and economic operation performance of multi-distributed energy resources in networked islanded microgrid, a distributed and integrated control strategy is designed in this study. The strategy is based on the communication network in an islanded microgrid, which is able to achieve minimal generation cost, reliable communication, and stable voltage and frequency. These targets are achieved through the following methods. Firstly, a power regulation part is combined with droop controller to constitute an improved primary control, which can take the line loss factor into account and adjust the output power of each distributed energy resource to its optimal value. Secondly, an optimal path reconstruction method and a Kalman filter estimation method with sliding mode controller are developed to address the communication interruption problem in communication channels and output channels, respectively. In the end, the secondary controller is used to regulate voltage and frequency, and a small signal model method is applied to analyze the impact on the whole system when these designs are applied. The effect of the proposed strategies has been verified by the related case studies.

MiR-7a-5p Attenuates Hypoxia/Reoxygenation-Induced Cardiomyocyte Apoptosis by Targeting VDAC1.

MicroRNA-7a-5p (miR-7a-5p) is closely related to apoptosis and plays an important role in ischemia/reperfusion (I/R) injury. Whether miR-7a-5p is involved in hypoxia/reoxygenation (H/R)-induced cardiomyocyte apoptosis is unknown. Therefore, this study aims to evaluate the role of miR-7a-5p in cardiomyocyte H9C2 cells in response to H/R stimulation. The results of RT-qPCR demonstrated that the expression level of miR-7a-5p was significantly down-regulated in H/R-treated H9C2 cells. MTT assay revealed that the cell viability was notably decreased in H/R group. Flow cytometric analysis found that the ratio of apoptotic cells was increased markedly following H/R. Enforced miR-7a-5p expression increased cell viability and decreased the apoptotic rate. Western blot analysis revealed that the expressions of pro-apoptotic proteins cleaved caspase-3 and Bax were down-regulated, while the expression of anti-apoptotic protein Bcl-2 was up-regulated in H/R-treated H9C2 cells transfected with miR-7a-5p mimic. On the contrary, miR-7a-5p downexpressing promoted apoptosis in H/R-treated H9C2 cells. Furthermore, the bioinformatics prediction manifested voltage-dependent anion channel 1 (VDAC1) was a potential target for miR-7a-5p, and dual-luciferase reporter assay confirmed that miR-7a-5p targeted VDAC1 3' untranslated regions, which leads to the repressed expressions of VDAC1 mRNA and protein. Knockdown of VDAC1 potentiated the protective effects of miR-7a-5p against H/R-induced cell injury. In conclusion, our results demonstrated that miR-7a-5p is involved in H/R-induced cardiomyocyte apoptosis through targeting VDAC1. MiR-7a-5p/VDAC1 axis might be utilized as hopeful biomarkers to reveal the potential mechanism of myocardial I/R injury.

Early predictors of severe COVID-19 among hospitalized patients.

BACKGROUND: Limited research has been conducted on early laboratory biomarkers to identify patients with severe coronavirus disease (COVID-19). This study fills this gap to ensure appropriate treatment delivery and optimal resource utilization. METHODS: In this retrospective, multicentre, cohort study, 52 and 64 participants with severe and mild cases of COVID-19, respectively, were enrolled during January-March 2020. Least absolute shrinkage and selection operator and binary forward stepwise logistic regression were used to construct a predictive risk score. A prediction model was then developed and verified using data from four hospitals. RESULTS: Of the 50 variables assessed, eight were independent predictors of COVID-19 and used to calculate risk scores for severe COVID-19: age (odds ratio (OR = 14.01, 95% confidence interval (CI) 2.1-22.7), number of comorbidities (OR = 7.8, 95% CI 1.4-15.5), abnormal bilateral chest computed tomography images (OR = 8.5, 95% CI 4.5-10), neutrophil count (OR = 10.1, 95% CI 1.88-21.1), lactate dehydrogenase (OR = 4.6, 95% CI 1.2-19.2), C-reactive protein OR = 16.7, 95% CI 2.9-18.9), haemoglobin (OR = 16.8, 95% CI 2.4-19.1) and D-dimer levels (OR = 5.2, 95% CI 1.2-23.1). The model was effective, with an area under the receiver-operating characteristic curve of 0.944 (95% CI 0.89-0.99, p < 0.001) in the derived cohort and 0.8152 (95% CI 0.803-0.97; p < 0.001) in the validation cohort. CONCLUSION: Predictors based on the characteristics of patients with COVID-19 at hospital admission may help predict the risk of subsequent critical illness.

Prevalence and Genetic Diversity of Clostridium perfringens Isolates in Hospitalized Diarrheal Patients from Central China.

OBJECTIVE: This study aimed to investigate the prevalence, genetic diversity and clinical characteristics of Clostridium perfringens isolates from hospitalized clinical diarrheal patients. METHODS: A prospective study was conducted on 1108 patients with diarrhea during hospitalization. Stool samples were cultured for C. perfringens, and the toxin genes were detected by PCR. The available clinical data of 112 patients were analyzed to study the clinical features of various isolates. Multi-locus sequence typing (MLST) was performed to assess phylogenetic relationship between different isolates. RESULTS: A total of 153 (13.8%) isolates were obtained from patients' stools. C. perfringens type F (49.0%) was the major toxin type in the isolates, followed by type A (n = 59, 38.6%) and type C (n = 14, 9.2%). Patients older than 50 years and those with underlying diseases of cancer, hepatobiliary system, and ulcerative colitis (UC) were more predisposed to C. perfringens type F and type A infection than to type C. The patients infected with type C experienced more severe clinical symptoms compared to those with type A infection. There was a significant association between type FC and foodborne gastrointestinal (GI) diseases (p = 0.018), between type FP and antibiotic-associated diarrhea (AAD) (p < 0.001), and between type A and sporadic diarrhea (SD) (p < 0.001). Phylogenetic analysis indicated that type F isolates carrying a chromosomal cpe gene mainly belonged to ST77 (6/15 isolates). Type F isolates with cpe gene on a plasmid exhibited high genetic diversity. CONCLUSION: High prevalence and considerable genetic diversity of C. perfringens type F were found in clinical diarrheal patients. Elderly people and patients with cancer, hepatobiliary diseases or UC, or suspected of having food poisoning (FP) may be targeted for routine testing of C. perfringens toxin genes and may benefit from early detection of C. perfringens type C isolates that cause more severe clinical symptoms.

Severe Acute Respiratory Syndrome Coronavirus 2 Viral RNA Load Status and Antibody Distribution Among Patients and Asymptomatic Carriers in Central China.

This study aimed to monitor severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral loads and specific serum-antibodies (immunoglobulin [Ig] G and M) among confirmed patients and asymptomatic carriers from returning healthy travelers. The throat swabs, sputum, and stool samples from 57 hospitalized coronavirus disease (COVID-19) patients and 8 asymptomatic carriers, among 170 returning healthy travelers were tested using reverse-transcription real-time polymerase chain reaction. SARS-CoV-2 IgM/IgG antibodies were detected via serum chemiluminescence assay. Sequential results showed higher viral RNA loads in the throat, sputum, and stool samples at 3-12 and 6-21 days after symptom onset among severely ill COVID-19 patients. Shorter viral habitation time (1-8 days) was observed in the oropharyngeal site and intestinal tract of asymptomatic carriers. The IgG and IgM response rates were 19/37 (51.4%) and 23/37 (62.6%) among the 29 confirmed patients and 8 asymptomatic carriers, respectively, within 66 days from symptom or detection onset. The median duration between symptom onset and positive IgG and IgM results was 30 (n=23; interquartile range [IQR]=20-66) and 23 (n=19; IQR=12-28) days, respectively. Of 170 returning healthy-travelers to China, 4.7% were asymptomatic carriers (8/170) within 2 weeks, and the IgG and IgM positivity rate was 12.8% (12/94). IgM/IgG-positivity confirmed 3 suspected SARS-CoV-2 cases, despite negative results for SARS-CoV-2 RNA. Compared with other respiratory viral infectious diseases, COVID-19 has fewer asymptomatic carriers, lower antibody response rates, and a longer antibody production duration in recovered patients and the contacted healthy population. This is an indication of the complexity of COVID-19 transmission.

Arborinine, a potential LSD1 inhibitor, inhibits epithelial-mesenchymal transition of SGC-7901 cells and adriamycin-resistant gastric cancer SGC-7901/ADR cells.

Arborinine is a natural product isolated from G. parva leaf extracts, which displays potentially antiproliferative activity against human cervical cancer cells. In contrast, its anticancer effects against gastric cancer cells and drug-resistant gastric cancer cells remain unknown. In this work, arborinine was evaluated as a broad-spectrum antiproliferative agent, and it exhibited potently inhibitory activity against NCI-N87 (IC50 = 5.67 µM), BGC-823 (IC50 = 7.26 µM), MGC803 (IC50 = 4.75 µM), SGC-7901 (IC50 = 1.96 µM), HGC-27 (IC50 = 5.70 µM), SGC-7901/ADR (IC50 = 0.24 µM), SGC-7901/VCR (IC50 = 1.09 µM), and MGC803/PTX (IC50 = 1.32 µM) cell lines. Subsequent target verification experiments demonstrated that arborinine selectively and reversibly inhibited LSD1 in a time-dependent manner. Furthermore, it was found that arborinine suppressed the epithelial-mesenchymal transition of gastric cancer cell line SGC-7901 and adriamycin-resistant gastric cancer cell line SGC-7901/ADR in a dose-dependent manner. The in vivo antitumor study further indicated that arborinine can significantly reduce the growth of tumors both in SGC-7901 and SGC-7901/ADR xenograft mouse models. Overall, we demonstrated the potential of arborinine as an effective treatment for gastric cancer and adriamycin-resistant gastric cancer.