Molecular Subtypes Defined by Cuproptosis-Associated Genes, Prognostic Model Development, and Tumor Immune Microenvironment Characterization in Adrenocortical Carcinoma.

Introduction: This study aims to explore the role of cuproptosis-related genes in ACC, utilizing data from TCGA and GEO repositories, and to develop a predictive model for patient stratification. Methods: A cohort of 123 ACC patients with survival data was analyzed. RNA-seq data of 17 CRGs were examined, and univariate Cox regression identified prognostic CRGs. A cuproptosis-related network was constructed to show interactions between CRGs. Consensus clustering classified ACC into three subtypes, with transcriptional and survival differences assessed by PCA and survival analysis. Gene set variation analysis (GSVA) and ssGSEA evaluated functional and immune infiltration characteristics across subtypes. Differentially expressed genes (DEGs) were identified, and gene clusters were established. A risk score (CRG_score) was generated using LASSO and multivariate Cox regression, validated across datasets. Tumor microenvironment, stem cell index, mutation status, drug sensitivity, and hormone synthesis were examined in relation to the CRG_score. Protein expression of key genes was validated, and functional studies on ASF1B and NDRG4 were performed. Results: Three ACC subtypes were identified with distinct survival outcomes. Subtype B showed the worst prognosis, while subtype C had the best. We identified 214 DEGs linked to cell proliferation and classified patients into three gene clusters, confirming their prognostic value. The CRG_score predicted patient outcomes, with high-risk patients demonstrating worse survival and possible resistance to immunotherapy. Drug sensitivity analysis suggested higher responsiveness to doxorubicin and etoposide in high-risk patients. Conclusion: This study suggests the potential prognostic value of CRGs in ACC. The CRG_score model provides a robust tool for risk stratification, with implications for treatment strategies.

High-Order Topological Pumping on a Superconducting Quantum Processor.

High-order topological phases of matter refer to the systems of n-dimensional bulk with the topology of m-th order, exhibiting (n-m)-dimensional boundary modes and can be characterized by topological pumping. Here, we experimentally demonstrate two types of second-order topological pumps, forming four 0-dimensional corner localized states on a 4×4 square lattice array of 16 superconducting qubits. The initial ground state of the system at half-filling, as a product of four identical entangled 4-qubit states, is prepared using an adiabatic scheme. During the pumping procedure, we adiabatically modulate the superlattice Bose-Hubbard Hamiltonian by precisely controlling both the hopping strengths and on-site potentials. At the half pumping period, the system evolves to a corner-localized state in a quadrupole configuration. The robustness of the second-order topological pump is also investigated by introducing different on-site disorder. Our Letter studies the topological properties of high-order topological phases from the dynamical transport picture using superconducting qubits, which would inspire further research on high-order topological phases.

Empirical evidence and theoretical understanding of ecosystem carbon and nitrogen cycle interactions.

Interactions between carbon (C) and nitrogen (N) cycles in terrestrial ecosystems are simulated in advanced vegetation models, yet methodologies vary widely, leading to divergent simulations of past land C balance trends. This underscores the need to reassess our understanding of ecosystem processes, given recent theoretical advancements and empirical data. We review current knowledge, emphasising evidence from experiments and trait data compilations for vegetation responses to CO2 and N input, alongside theoretical and ecological principles for modelling. N fertilisation increases leaf N content but inconsistently enhances leaf-level photosynthetic capacity. Whole-plant responses include increased leaf area and biomass, with reduced root allocation and increased aboveground biomass. Elevated atmospheric CO2 also boosts leaf area and biomass but intensifies belowground allocation, depleting soil N and likely reducing N losses. Global leaf traits data confirm these findings, indicating that soil N availability influences leaf N content more than photosynthetic capacity. A demonstration model based on the functional balance hypothesis accurately predicts responses to N and CO2 fertilisation on tissue allocation, growth and biomass, offering a path to reduce uncertainty in global C cycle projections.

Hinokiflavone from Platycladi cacumen as a potent broad-spectrum inhibitor of gut microbial Loop-1 ß-glucuronidases: Inhibition kinetics and molecular simulation.

Gut microbial Loop-1 ß-glucuronidases (gmGUS) played an important role in irinotecan-induced gastrointestinal toxicity by regulating the level of its active metabolite SN38 through enterohepatic recirculation. gmGUS inhibition has emerged as a promising approach to relieve its dose-limiting intestinal toxicity and improve its medication efficacy. This study aims to investigate the inhibitory effects and mechanisms of Platycladi cacumen and its main constituent hinokiflavone against four different types of Loop-1 gmGUS (EeGUS, SaGUS, CpGUS and EcGUS). Our results showed that the ethanol extract of Platycladi cacumen displayed strong broad-spectrum inhibition against four gmGUS, and hinokiflavone could potently inhibit EeGUS, SaGUS, CpGUS and EcGUS with IC50 values of 0.09 ± 0.01 µM, 0.44 ± 0.01 µM, 0.20 ± 0.01 µM and 0.69 ± 0.10 µM, respectively. Inhibition kinetic analyses demonstrated that hinokiflavone acted as a strong competitive inhibitor of EeGUS with Ki value of 0.13 µM, while it displayed non-competitive inhibition against SaGUS, CpGUS and EcGUS, with the Ki values of 0.43 µM, 0.33 µM and 0.76 µM, respectively. Docking simulations revealed that hinokiflavone could tightly bind with Tyr-485 and Glu-516 in catalytic sites of EeGUS, as well it created strong interactions with amino acids in loop structures of SaGUS (Asn-362), CpGUS (Phe-363, Met-364, Ala-365 and Arg-375) and EcGUS (Leu-361) to interfere the substrate entry into the catalytic pocket. Collectively, these results confirmed that hinokiflavone from Platycladi cacumen is a potent naturally occurring inhibitor of gmGUS with broad efficiency, suggesting hinokiflavone will be helpful for alleviating intestinal toxicity in irinotecan therapy.

Disulfidptosis-related subtype and prognostic signature in prostate cancer.

BACKGROUND: Disulfidptosis refers to cell death caused by the accumulation and bonding of disulfide in the cytoskeleton protein of SLC7A11-high level cells under glucose deprivation. However, the role of disulfidptosis-related genes (DRGs) in prostate cancer (PCa) classification and regulation of the tumor microenvironment remains unclear. METHODS: Firstly, we analyzed the expression and mutation landscape of DRGs in PCa. We observed the expression levels of SLC7A11 in PCa cells through in vitro experiments and assessed the inhibitory effect of the glucose transporter inhibitor BAY-876 on SLC7A11-high cells using CCK-8 assay. Subsequently, we performed unsupervised clustering of the PCa population and analyzed the differentially expressed genes (DEGs) between clusters. Using machine learning techniques to select a minimal gene set and developed disulfidoptosis-related risk signatures for PCa. We analyzed the tumor immune microenvironment and the sensitivity to immunotherapy in different risk groups. Finally, we validated the accuracy of the prognostic signatures genes using single-cell sequencing, qPCR, and western blot. RESULTS: Although SLC7A11 can increase the migration ability of tumor cells, BAY-876 effectively suppressed the viability of prostate cancer cells, particularly those with high SLC7A11 expression. Based on the DRGs, PCa patients were categorized into two clusters (A and B). The risk label, consisting of a minimal gene set derived from DEGs, included four genes. The expression levels of these genes in PCa were initially validated through in vitro experiments, and the accuracy of the risk label was confirmed in an external dataset. Cluster-B exhibited higher expression levels of DRG, representing lower risk, better prognosis, higher immune cell infiltration, and greater sensitivity to immune checkpoint blockade, whereas Cluster A showed the opposite results. These findings suggest that DRGs may serve as targets for PCa classification and treatment. Additionally, we constructed a nomogram that incorporates DRGs and clinical pathological features, providing clinicians with a quantitative method to assess the prognosis of PCa patients. CONCLUSION: This study analyzed the potential connection between disulfidptosis and PCa, and established a prognostic model related to disulfidptosis, which holds promise as a valuable tool for the management and treatment of PCa patients.

[Effect of Tumor Suppressor Gene Kmt2c Heterozygous Deletion on Hematopoietic System in Mice].

OBJECTIVE: To explore the effect of heterozygous deletion of histone methyltransferase Kmt2c gene on the hematological system of mice. METHODS: CRISPR/Cas9 technology was used to construct mice model of Kmt2c heterozygous deletion (Kmt2c+/-) and the changes of whole blood cell count in mice were continuously monitored by blood routine test. The clonal expansion ability of bone marrow cells was explored by colony formation assay in vitro and the proportion of primitive hematopoietic cells, including long-term hematopoietic stem cell (LT-HSC), short-term hematopoietic stem cell (ST-HSC), and multipotent progenitor cell in mutant mice was analyzed by flow cytometry. RESULTS: Kmt2c+/- mice model was successfully constructed, and the mRNA expression level of Kmt2c was 28% of that of C57BL/6J mice. The colony formation ability of bone marrow cells of Kmt2c+/- mice in vitro increased with the passage times, and the colony number in the fourth generation was significantly higher than that of control group (P <0.05). The proportions of LT-HSC and ST-HSC in the primitive hematopoietic cell population of Kmt2c+/- mice was 19.6%±3.3% and 28.9%±4.9%, respectively, which showed an increasing trend compared with 16.9%±2.6% and 18.9%±2.5% in control group, but the difference was not statistically significant (P >0.05). The white blood cell count of Kmt2c+/- mice gradually increased after 12 weeks of monitoring and reached (9.8±1.0)×109/L at the 14th week, which was significantly higher than (7.3±1.4)×109/L of control group (P < 0.05). CONCLUSION: The bone marrow cells of Kmt2c+/- mice have potential of clonal expansion.

ECG arrhythmia classification based on the fast ant colony clustering algorithm with improved spatiotemporal feature perception ability.

Electrocardiograph (ECG) is one of the most critical physiological signals used for arrhythmia diagnosis. In recent years, ECG arrhythmia classification devices consisting of multi-module sensors, clustering algorithms and neural networks play an important role in monitoring and diagnosing cardiovascular diseases. However, the commonly used ECG arrhythmia classification methods are still facing some problems such as the complex model structure and long running time. To address the above problems, this paper proposes an ECG arrhythmia classification method based on the fast ant colony clustering algorithm with improved spatiotemporal feature perception ability (SFP-FACC), which uses LSTM to fit the cluster centers and avoids the time consumption of updating the cluster centers during the classification process. The spatiotemporal feature perception ability of this model with the dynamic time warping (DTW) algorithm is improved. The classification is achieved by applying the combination of Euclidean distance and DTW. The convergence speed of the model is improved by using dynamic pheromone volatility coefficient; and finally the optimal solution of the model is determined by using radix sort. Based on the MIT-BIH arrhythmia dataset, the overall accuracy of the proposed classification method in this paper achieves 99.04 %, and even the accuracy of certain types of classification achieves 100 %, and the running time is about 3.5 times faster than that of the basic models. The experiments show that the method proposed in this paper has certain advantages.

Short-term outcomes of totally robotic versus robotic-assisted distal gastrectomy for gastric cancer: a single-center retrospective study.

BACKGROUND: Totally robotic distal gastrectomy (TRDG) is being used more and more in gastric cancer (GC) patients. The study aims to evaluate the short-term efficacy of TRDG and robotic-assisted distal gastrectomy (RADG) in the treatment of GC. METHODS: We retrospectively collected the clinical data of patients who underwent TRDG or RADG, of which 60 patients were included in the study: 30 cases of totally robotic and 30 cases of robotic-assisted. The short-term efficacy of the two groups was compared. RESULTS: There was no significant difference in the clinicopathological data between the two groups. Compared to RADG, TRDG had less intraoperative blood loss(P = 0.019), less postoperative abdominal drainage(P = 0.031), shorter time of exhaust( P = 0.001) and liquid diet(P = 0.001), shorter length of incision(P<0.01), shorter postoperative hospital stays(P = 0.033), lower postoperative C-reactive protein(CRP)(P = 0.024) and lower postoperative Visual Analogue Scale(VAS) scores(P = 0.048). However, no significant statistical differences were found in terms of total operation time(P = 0.108), number of lymph nodes retrieved(P = 0.307), time for anastomosis(P = 0.450), proximal resection margin(P = 0.210), distal resection margin(P = 0.202), postoperative complication(P = 0.506), total hospital cost(P = 0.286) and postoperative white blood cell(WBC)(P = 0.113). CONCLUSIONS: In terms of security and technology, TRDG could serve as a better treatment method for GC.

Machine Learning of Laboratory Data in Predicting 30-Day Mortality for Adult Hemophagocytic Lymphohistiocytosis.

BACKGROUND: Hemophagocytic Lymphohistiocytosis (HLH) carries a high mortality rate. Current existing risk-evaluation methodologies fall short and improved predictive methods are needed. This study aimed to forecast 30-day mortality in adult HLH patients using 11 distinct machine learning (ML) algorithms. METHODS: A retrospective analysis on 431 adult HLH patients from January 2015 to September 2021 was conducted. Feature selection was executed using the least absolute shrinkage and selection operator. We employed 11 ML algorithms to create prediction models. The area under the curve (AUC), sensitivity, specificity, positive predictive value, negative predictive value, F1 score, calibration curve and decision curve analysis were used to evaluate these models. We assessed feature importance using the SHapley Additive exPlanation (SHAP) approach. RESULTS: Seven independent predictors emerged as the most valuable features. An AUC between 0.65 and 1.00 was noted among the eleven ML algorithms. The gradient boosting decision tree (GBDT) algorithms demonstrated the most optimal performance (1.00 in the training cohort and 0.80 in the validation cohort). By employing the SHAP method, we identified the variables that contributed to the model and their correlation with 30-day mortality. The AUC of the GBDT algorithms was the highest when using the top 4 (ferritin, UREA, age and thrombin time (TT)) features, reaching 0.99 in the training cohort and 0.83 in the validation cohort. Additionally, we developed a web-based calculator to estimate the risk of 30-day mortality. CONCLUSIONS: With GBDT algorithms applied to laboratory data, accurate prediction of 30-day mortality is achievable. Integrating these algorithms into clinical practice could potentially improve 30-day outcomes.

Valnemulin restores colistin sensitivity against multidrug-resistant gram-negative pathogens.

Colistin is one of the last-resort antibiotics in treating infections caused by multidrug-resistant (MDR) pathogens. Unfortunately, the emergence of colistin-resistant gram-negative strains limit its clinical application. Here, we identify an FDA-approved drug, valnemulin (Val), exhibit a synergistic effect with colistin in eradicating both colistin-resistant and colistin-susceptible gram-negative pathogens both in vitro and in the mouse infection model. Furthermore, Val acts synergistically with colistin in eliminating intracellular bacteria in vitro. Functional studies and transcriptional analysis confirm that the combinational use of Val and colistin could cause membrane permeabilization, proton motive force dissipation, reduction in intracellular ATP level, and suppression in bacterial motility, which result in bacterial membrane disruption and finally cell death. Our findings reveal the potential of Val as a colistin adjuvant to combat MDR bacterial pathogens and treat recalcitrant infections.

Epigallocatechin-3-gallate attenuates fluoride induced apoptosis via PI3K/FoxO1 pathway in ameloblast-like cells.

Fluoride is a double-edged sword. It was widely used for early caries prevention while excessive intake caused a toxicology effect, affected enamel development, and resulted in dental fluorosis. The study aimed to evaluate the protective effect and mechanism of Epigallocatechin-3-gallate (EGCG) on the apoptosis induced by fluoride in ameloblast-like cells. We observed that NaF triggered apoptotic alterations in cell morphology, excessive NaF arrested cell cycle at the G1, and induced apoptosis by up-regulating Bax and down-regulating Bcl-2. NaF activated the insulin-like growth factor receptor (IGFR), and phosphatidylinositol-3-hydroxylase (p-PI3K), while dose-dependently down-regulating the expression of Forkhead box O1 (FoxO1). EGCG supplements reversed the changes in LS8 morphology, the cell cycle, and apoptosis induced by fluoride. These results indicated that EGCG possesses a protective effect against fluoride toxicity. Furthermore, EGCG suppressed the activation of p-PI3K and the down-regulation of FoxO1 caused by fluoride. Collectively, our findings suggested that EGCG attenuated fluoride-induced apoptosis by inhibiting the PI3K/FoxO1 signaling pathway. EGCG may serve as a new alternative method for dental fluorosis prevention, control, and treatment.

Environmental explanation of prostate cancer progression based on the comprehensive analysis of polychlorinated biphenyls.

OBJECTIVE: Polychlorinated biphenyls (PCBs) have caused great environmental concerns. The study aims to investigate underlying molecular mechanisms between PCBs exposure and prostate cancer (PCa). METHODS: To investigate the association between PCBs exposure and prostate cancer by using CTD, TCGA, and GEO datasets. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to explore pathways associated with PCBs-related genes (PRGs). Using Lasso regression analysis, a novel PCBs-related prognostic model was developed. Both internal and external validations were conducted to assess the model's validity. Molecular docking was utilized to assess the binding capacity of PCBs to crucial genes. At last, preliminary experimental validations were conducted to confirm the biological roles of Aroclor 1254 in PCa cells. RESULTS: The GO enrichment analysis of PRGs revealed that the biological processes were most enriched in the regulation of transcription from the RNA polymerase II promoter and signal transduction. The KEGG enrichment analysis showed that of the pathways in cancer is the most significantly enriched. Next, a PCBs-related model was constructed. In the training, test, GSE70770, and GSE116918 cohorts, the biochemical recurrences free survival of the patients with high-risk scores was considerably lower. The AUCs at 5 years were 0.691, 0.718, 0.714, and 0.672 in the four cohorts, demonstrating the modest predictive ability. A nomogram that incorporated clinical characteristics was constructed. The results of the anti-cancer drug sensitivity analysis show chemotherapy might be more beneficial for patients at low risk. The molecular docking analysis demonstrated PCBs' ability to bind to crucial genes. PCa cells exposed to Aroclor 1254 at a concentration of 1 µM showed increased proliferation and invasion capabilities. CONCLUSIONS: This study provides new insights into the function of PCBs in PCa and accentuates the need for deeper exploration into the mechanistic links between PCBs exposure and PCa progression.

Machine learning-based autophagy-related prognostic signature for personalized risk stratification and therapeutic approaches in bladder cancer.

OBJECTIVE: Bladder cancer (BCa) is a highly lethal urological malignancy characterized by its notable histological heterogeneity. Autophagy has swiftly emerged as a diagnostic and prognostic biomarker in diverse cancer types. Nonetheless, the currently accessible autophagy-related signature specific to BCa remains limited. METHODS: A refined autophagy-related signature was developed through a 10-fold cross-validation framework, incorporating 101 combinations of machine learning algorithms. The performance of this signature in predicting prognosis and response to immunotherapy was thoroughly evaluated, along with an exploration of potential drug targets and compounds. In vitro and in vivo experiments were conducted to verify the regulatory mechanism of hub gene. RESULTS: The autophagy-related prognostic signature (ARPS) has exhibited superior performance in predicting the prognosis of BCa compared to the majority of clinical features and other developed markers. Higher ARPS is associated with poorer prognosis and reduced sensitivity to immunotherapy. Four potential targets and five therapeutic agents were screened for patients in the high-ARPS group. In vitro and vivo experiments have confirmed that FKBP9 promotes the proliferation, invasion, and metastasis of BCa. CONCLUSIONS: Overall, our study developed a valuable tool to optimize risk stratification and decision-making for BCa patients.

Magnetic resonance imaging-based radiomics nomogram for the evaluation of therapeutic responses to neoadjuvant chemohormonal therapy in high-risk non-metastatic prostate cancer.

PURPOSE: The aim of this study was to assess the potential application of a radiomics features-based nomogram for predicting therapeutic responses to neoadjuvant chemohormonal therapy (NCHT) in patients with high-risk non-metastatic prostate cancer (PCa). METHODS: Clinicopathologic information was retrospectively collected from 162 patients with high-risk non-metastatic PCa receiving NCHT and radical prostatectomy at our center. The postoperative pathological findings were used as the gold standard for evaluating the efficacy of NCHT. The least absolute shrinkage and selection operator (LASSO) was conducted to develop radiomics signature. Multivariate logistic regression analyses were conducted to identify the predictors of a positive pathological response to NCHT, and a nomogram was constructed based on these predictors. RESULTS: Sixty-three patients (38.89%) experienced positive pathological response to NCHT. Receiver operating characteristic analyses showed that the area under the curve (AUC) of periprostatic fat (PPF) radiomics signature was 0.835 (95% CI, 0.754-0.898), while the AUC of intratumoral radiomics signature was 0.822 (95% CI, 0.739-0.888). Multivariate logistic regression analysis revealed that PSA level, PPF radiomics signature and intratumoral radiomics signature were independent predictors of positive pathological response. A nomogram based on these three predictors was constructed. The AUC was 0.908 (95% CI, 0.839-0.954). The Hosmer-Lemeshow goodness-of-fit test showed that the nomogram was well calibrated. Decision curve analysis revealed the favorable clinical practicability of the nomogram. The nomogram was successfully validated in the validation cohort. Kaplan-Meier analyses showed that nomogram and positive pathological response were significantly related with survival of PCa. CONCLUSION: The radiomics-clinical nomogram based on mpMRI radiomics features exhibited superior predictive ability for positive pathological response to NCHT in high-risk non-metastatic PCa.

Genomic analysis of foodborne Staphylococcus aureus obtained from unannounced food inspections between 2012 and 2021 in East China.

Staphylococcus aureus is a significant cause of foodborne illness in China. Our investigation concentrated on the genetic characterization of foodborne S. aureus identified during unannounced inspections conducted in Suzhou from 2012 to 2021. Dominant clones included clonal complex (CC) 1, CC398, CC188, and CC7, with CC398 notably increasing in 2020-2021. The isolates commonly contained 1-3 plasmids, with rep5a (48.55%) and rep16 (44.51%) predominating. A concerning 24.3% showed multidrug resistance, particularly to penam (blaZ and mecA) and fosfomycin (fosB), with resistance rates rising from 32.7% to 53.3%, potentially linked to the increase in CC types like CC5, CC20, and CC25. Most isolates carried genes for virulence factors such as aureolysin, hemolysin, staphylokinase, and staphylococcal complement inhibitor. A significant increase in virulence genes, especially the enterotoxin gene sea, was observed, possibly associated with shifts in CC1 and CC7 prevalence. This underscores the necessity for ongoing surveillance to understand the genomic traits of S. aureus in ensuring food safety.

Hederagenol improves multiple sclerosis by modulating Th17 cell differentiation.

Multiple sclerosis (MS) is a common autoimmune illness that is difficult to treat. The upregulation of Th17 cells is critical in the pathological process of MS. Hederagenol (Hed) has been shown to lower IL-17 levels, although its role in MS pathophysiology is uncertain. In this study, we explore whether Hed could ameliorate MS by modulating Th17 cell differentiation, with the goal of identifying new treatment targets for MS. The experimental autoimmune encephalomyelitis (EAE) mouse model was conducted and Hed was intraperitoneally injected into mice. The weight was recorded and the clinical symptom grade was assessed. Hematoxylin-eosin staining was carried out to determine the extent of inflammation in the spinal cord and liver. The luxol Fast Blue staining was performed to detect the pathological changes in the myelin sheath. Nerve damage was detected using NeuN immunofluorescence staining and terminal deoxynucleotidyl transferase dUTP nick-end labeling staining. Immunohistology approaches were used to study alterations in immune cells in the spinal cord. The proportions of T cell subsets in the spleens were analyzed by flow cytometry. RORγt levels were measured using quantitative real-time PCR or Western blot. The activity of the RORγt promoter was analyzed by Chromatin immunoprecipitation. Hed administration reduced the clinical symptom grade of EAE mice, as well as the inflammatory infiltration, demyelination, and cell disorder of the spinal cord, while having no discernible effect on the mouse weight. In addition, Hed treatment significantly reduced the number of T cells, particularly Th17 cells in the spinal cord and spleen-isolated CD4+ T cells. Hed lowered the RORγt levels in spleens and CD4+ T cells and overexpression of RORγt reversed the inhibitory effect of Hed on Th17 differentiation. Hed decreased nerve injury by modulating Th17 differentiation through the RORγt promoter. Hed regulates Th17 differentiation by reducing RORγt promoter activity, which reduces nerve injury and alleviates EAE.

Fitness cost of tet(A) type I variant-mediated tigecycline resistance in Klebsiella pneumoniae.

OBJECTIVE: The aim of the present study is to explore the impact of the tet(A) type I variant (tetA-v1) on its fitness effect in Klebsiella pneumoniae. METHODS: Clinical K. pneumoniae strains were utilized as parental strains to generate strains carrying only the plasmid vector (pBBR1MCS-5) or the tetA-v1 recombinant plasmid (ptetA-v1). Antimicrobial susceptibility testing was conducted to estimate the contribution of tetA-v1 to drug resistance. Plasmid stability was evaluated by serial passage over 10 consecutive days in the absence of tigecycline. Biological fitness was examined through growth curve analysis, in vitro competition assays and a neutropenic mouse thigh infection model. RESULTS: A 2-4-fold increase in tigecycline MIC was observed following the acquisition of tetA-v1. Without tigecycline treatment, the stability of ptetA-v1 plasmids has been decreasing since day 1. The ptetA-v1 plasmid in Kp89, Kp91, and Kp93 exhibited a decrease of about 20% compared to the pBBR1MCS-5 plasmid. The acquisition of the tetA-v1 gene could inhibit the growth ability of K. pneumoniae strains both in vitro and in vivo. tetA-v1 gene imposed a fitness cost in K. pneumoniae, particularly in the CRKP strain Kp51, with a W value of approximately 0.56. CONCLUSION: The presence of tetA-v1 is associated with a significant fitness cost in K. pneumoniae in the absence of tigecycline, both in vitro and in vivo.

Extracellular cold-inducible RNA-binding protein mediated neuroinflammation and neuronal apoptosis after traumatic brain injury.

Background: Extracellular cold-inducible RNA-binding protein (eCIRP) plays a vital role in the inflammatory response during cerebral ischaemia. However, the potential role and regulatory mechanism of eCIRP in traumatic brain injury (TBI) remain unclear. Here, we explored the effect of eCIRP on the development of TBI using a neural-specific CIRP knockout (KO) mouse model to determine the contribution of eCIRP to TBI-induced neuronal injury and to discover novel therapeutic targets for TBI. Methods: TBI animal models were generated in mice using the fluid percussion injury method. Microglia or neuron lines were subjected to different drug interventions. Histological and functional changes were observed by immunofluorescence and neurobehavioural testing. Apoptosis was examined by a TdT-mediated dUTP nick end labelling assay in vivo or by an annexin-V assay in vitro. Ultrastructural alterations in the cells were examined via electron microscopy. Tissue acetylation alterations were identified by non-labelled quantitative acetylation via proteomics. Protein or mRNA expression in cells and tissues was determined by western blot analysis or real-time quantitative polymerase chain reaction. The levels of inflammatory cytokines and mediators in the serum and supernatants were measured via enzyme-linked immunoassay. Results: There were closely positive correlations between eCIRP and inflammatory mediators, and between eCIRP and TBI markers in human and mouse serum. Neural-specific eCIRP KO decreased hemispheric volume loss and neuronal apoptosis and alleviated glial cell activation and neurological function damage after TBI. In contrast, eCIRP treatment resulted in endoplasmic reticulum disruption and ER stress (ERS)-related death of neurons and enhanced inflammatory mediators by glial cells. Mechanistically, we noted that eCIRP-induced neural apoptosis was associated with the activation of the protein kinase RNA-like ER kinase-activating transcription factor 4 (ATF4)-C/EBP homologous protein signalling pathway, and that eCIRP-induced microglial inflammation was associated with histone H3 acetylation and the α7 nicotinic acetylcholine receptor. Conclusions: These results suggest that TBI obviously enhances the secretion of eCIRP, thereby resulting in neural damage and inflammation in TBI. eCIRP may be a biomarker of TBI that can mediate the apoptosis of neuronal cells through the ERS apoptotic pathway and regulate the inflammatory response of microglia via histone modification.

Novel target and PCR assay for identification of hypervirulent ST1 (BI/NAP1/027) Clostridioides difficile and detection of toxigenic C. Difficile.

BACKGROUND AND AIMS: The incidence of Clostridioides difficile infection and the prevalence of hypervirulent ST1 (BI/NAP1/027)strain are increasing, especially in developing countries. We aimed to develop a new PCR assay for the identification of hypervirulent ST1 strains and toxigenic C. difficile in stool samples. MATERIALS AND METHODS: We established a quadruplex TaqMan real-time PCR (pilW_4-plex PCR) assay targeting the pilW, a ST1-specific type Ⅳ minor pilin gene, and three C. difficile genes including cdtB, tcdB, and hsp. The sensitivity and specificity of the assay was tested using 403C. difficile isolates and 180 unformed stool sample. The results were compared with anaerobic culture-based conventional PCR method and MLST. RESULTS: The pilW_4-plex PCR identified toxigenic C. difficile in 333 (82.6%, 333/403) isolates with 100% sensitivity and specificity, and in 78 (43.3%, 78/180) stool samples with the sensitivity and specificity of 94.7% and 93.3%, respectively. Hypervirulent ST1 were detected in 21 strains and nine stool samples by the pilW_4-plex PCR. The pilW_4-plex PCR assay has no cross-reaction with non-toxigenic C. difficile or other bacteria. CONCLUSION: The pilW_4-plex PCR assay is an accurate and rapid method with high sensitivity and specificity for identification of ST1 and detection of toxigenic C. difficile in stool.