Modulation of Host Death by Chlamydia trachomatis: the Role of the Chlamydia-specific Protease CPAF

Chlamydia is confirmed to modulate host cell death pathways to complete its own developmental cycle. In this study, the effect of Chlamydia trachomatis on activation of host cell death pathways was investigated. C. trachomatis infection induced caspase-3-independent cell death. After Chlamydia infection, nuclear protein PARP-1 was cleaved to necrotic-like multi-fragment. This cleavage was accompanied by a highly decreased enzymatic activity. PARP-1 silencing by siRNA in the host cells resulted in cell death similar to that induced by Chlamydia infection. Chlamydial but not host cell protease contributed to this PARP-1 cleavage. The purified proteolytic protein fraction exhibited a 29 kDa fragment, which corresponds to the NH2-terminal portion of chlamydial proteolytic activity factor (CPAF). The high mobility group box-1 (HMGB-1) protein, which is known to be released to the extracellular matrix to induce inflammation during necrotic cell death, was also degraded by CPAF in the late stage of the chlamydial infectious cycle. This gives the suggestion that Chlamydia may evade the host immune system by degrading this inflammatory factor. Under the stressful conditions like exposure to IFN-γ, C. trachomatis underwent a special form so called “persistence”, with minimal cultivability and low infectivity. During persistent chlamydial infection, the nuclear proteins PARP-1 and HMGB-1 were not degraded, suggesting the CPAF translocation to the host nucleus was inhibited during persistence. Our results gave the convincible evidence that the Chlamydia-secreted protease CPAF plays an important role in the regulation of host cell death pathways. During active infection, it could cleave nuclear proteins and induce the host cell instability and subsequent cell death. For the long-term persistence in host cells, the nuclear translocation of CPAF was inhibited. The nuclear proteins could keep intact to make sure the stability of the host cells

Therapy by physician–pharmacist combination and economic returns for cancer pain management in China: a cost-effectiveness analysis

Objective: To examine whether joint management of cancer pain by physicians and pharmacists in clinics provides economic advantages from the perspective of the Chinese healthcare system.Methods: From February 2018 to March 2020, 100 patients who visited the joint cancer pain clinic at the Xiangya Hospital of Central South University were included. These patients were randomly assigned to either the control or intervention groups. The control group received regular outpatient services from a physician, while the intervention group received regular outpatient services from a physician and medication education provided by a pharmacist. The study considered various direct costs, including drug expenses, physician-pharmacist outpatient services, adverse event management, consultations, examinations, and readmissions. The outcome indicators considered were the cancer pain control rate and the reduction in pain scores. Decision tree modeling, single-factor sensitivity analysis, and probabilistic sensitivity analysis were performed to evaluate the cost-effectiveness of joint physician-pharmacist outpatient services compared to physician-alone outpatient services.Results: The intervention group showed a significantly higher cancer pain control rate than the control group (0.69 vs. 0.39, p = 0.03). In the decision tree model, the intervention group had a significantly lower pain score than the control group (0.23 vs. 0.14). The cost per person in the intervention group was $165.39, while it was$191.1 per person in the control group. The univariate sensitivity analysis showed that the cost of self-management for patients in the control group was identified as the primary sensitivity factor. Probabilistic sensitivity analysis indicated that the joint clinic group had a favorable incremental cost-effectiveness compared to the physician clinic group. In addition, the probabilistic sensitivity analysis demonstrated an absolute advantage in the incremental cost-effectiveness of the joint clinic group over the outpatient physician group.Conclusion: The participation of pharmacists in joint cancer pain clinic services led to improved pain management for patients, demonstrating a clear advantage in terms of cost-effectiveness

Study on the Process and Mechanism of Slope Failure Induced by Mining under Open Pit Slope: A Case Study from Yanqianshan Iron Mine, China

Mining under an open pit slope results in the collapse and slide of the slope. In this paper, a combination of methods including Google Earth and field investigations is applied to investigate the process of eastern slope failure induced by underground mining in the Yanqianshan Iron Mine over five years. According to the observed ground deformation features, the geomorphic zone of the eastern slope can be divided into four regions (caved rock zone, cracking zone, toppling zone, and sliding zone). Break angles and fracture initiation angles at different times are counted separately. Based on the above work, the process of initiation and development of slope failure is studied. The analysis results show that the process of slope failure could be chronologically divided into three stages. First, a collapse pit, caused by the falling of the overlying strata above the goaf, appeared on the eastern slope. Then, the rock mass around the collapse pit slid into the pit to form a small landslide. Finally, because of mining disturbances and rock creep, a large landslide occurred on the northeastern phyllite slope. The control mechanisms of each failure stage are discussed separately. Finally, the RFPA3D code is employed to simulate the slope failure process under the influence of underground mining. The results are consistent with the field observations, which provided information on deformation failure and the mechanics of the slope that could not be directly observed in the field and deepened the mechanism analysis

The efficiency of Vpx-mediated SAMHD1 antagonism does not correlate with the potency of viral control in HIV-2-infected individuals

textabstractBackground: The presence of a vpx gene distinguishes HIV-2 from HIV-1, the main causative agent of AIDS. Vpx degrades the restriction factor SAMHD1 to boost HIV-2 infection of macrophages and dendritic cells and it has been suggested that the activation of antiviral innate immune responses after Vpx-dependent infection of myeloid cells may explain why most HIV-2-infected individuals efficiently control viral replication and become long-term survivors. However, the role of Vpx-mediated SAMHD1 antagonism in the virological and clinical outcome of HIV-2 infection remained to be investigated. Results: Here, we analyzed the anti-SAMHD1 activity of vpx alleles derived from seven viremic and four long-term aviremic HIV-2-infected individuals. We found that effective Vpx-mediated SAMHD1 degradation and enhancement of myeloid cell infection was preserved in most HIV-2-infected individuals including all seven that failed to control the virus and developed AIDS. The only exception were vpx alleles from an aviremic individual that predicted a M68K change in a highly conserved nuclear localization signal which disrupted the ability of Vpx to counteract SAMHD1. We also found that HIV-2 is less effective than HIV-1 in inducing innate immune activation in dendritic cells. Conclusions: Effective immune control of viral replication in HIV-2-infected individuals is not associated with increased Vpx-mediated degradation of SAMHD1

A Network Pharmacology-Based Approach to Investigating the Mechanisms of Fushen Granule Effects on Intestinal Barrier Injury in Chronic Renal Failure

Purpose. Fushen Granule (FSG) is a Chinese medicine prepared by doctors for treating patients with chronic renal failure, which is usually accompanied by gastrointestinal dysfunction. Here, we explore the protective effect of FSG on intestinal barrier injury in chronic renal failure through bioinformatic analysis and experimental verification. Methods. In this study, information on the components and targets of FSG related to CRF is collected to construct and visualize protein-protein interaction networks and drug-compound-target networks using network pharmacological methods. DAVID is used to conduct gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Then, it is validated by in vitro experiments. In this study, the human intestinal epithelial (T84) cells are used and divided into four groups: control group, model group, FSG low-dose group, and FSG high-dose group. After the experiment, the activity of T84 cells is detected by a MTT assay, and the expressions of tight junction protein ZO-1, claudin-1, nuclear factor erythroid 2-related factor (Nrf2), heme oxygenase-1 (HO-1), malondialdehyde (MDA), and cyclooxygenase-2 (COX-2) are examined by immunofluorescence and/or western blotting. Results. Eighty-six potential chronic renal failure-related targets are identified by FSG; among them, nine core genes are screened. Furthermore, GO enrichment analysis shows that the cancer-related signaling pathway, the PI3K-Akt signaling pathway, the HIF1 signaling pathway, and the TNF signaling pathway may play key roles in the treatment of CRF by FSG. The MTT method showed that FSG is not cytotoxic to uremic toxin-induced injured T84 cells. The results of immunofluorescence and WB indicate that compared with the control group, protein expressions level of ZO-1, claudin-1, and Nrf2 in T84 cells is decreased and protein expressions level of HO-1, MDA, and COX-2 is increased after urinary toxin treatment. Instead, compared with the model group, protein expressions level of ZO-1, claudin-1, and Nrf2 in T84 cells is increased and protein expressions level of HO-1, MDA, and COX-2 is decreased after FSG treatment. Conclusion. FSG had a protective effect on urinary toxin-induced intestinal epithelial barrier injury in chronic renal failure, and its mechanism may be related to the upregulation of Nrf2/HO-1 signal transduction and the inhibition of tissue oxidative stress and inflammatory responses. Screening CRF targets and identifying the corresponding FSG components by network pharmacological methods is a practical strategy to explain the mechanism of FSG in improving gastrointestinal dysfunction in CRF

Identification Method for Cone Yarn Based on the Improved Faster R-CNN Model

To solve the problems of high labor intensity, low efficiency, and frequent errors in the manual identification of cone yarn types, in this study five kinds of cone yarn were taken as the research objects, and an identification method for cone yarn based on the improved Faster R-CNN model was proposed. In total, 2750 images were collected of cone yarn samples in real of textile industry environments, then data enhancement was performed after marking the targets. The ResNet50 model with strong representation ability was used as the feature network to replace the VGG16 backbone network in the original Faster R-CNN model to extract the features of the cone yarn dataset. Training was performed with a stochastic gradient descent approach to obtain an optimally weighted file to predict the categories of cone yarn. Using the same training samples and environmental settings, we compared the method proposed in this paper with two mainstream target detection algorithms, YOLOv3 + DarkNet-53 and Faster R-CNN + VGG16. The results showed that the Faster R-CNN + ResNet50 algorithm had the highest mean average precision rate for the five types of cone yarn at 99.95%, as compared with the YOLOv3 + DarkNet-53 algorithm with a mean average precision rate that was 2.24% higher and the Faster R-CNN + VGG16 algorithm with a mean average precision that was 1.19% higher. Regarding cone yarn defects, shielding, and wear, the Faster R-CNN + ResNet50 algorithm can correctly identify these issues without misdetection occurring, with an average precision rate greater than 99.91%

Role of High-Mobility Group Box 1 Protein and Poly(ADP-Ribose) Polymerase 1 Degradation in Chlamydia trachomatis-Induced Cytopathicity▿

As intracellular bacteria, chlamydiae block the apoptotic pathways of their host cells. However, the infection of epithelial cells causes the loss of cell membrane integrity and can result in nonapoptotic death. Normally, cells undergoing necrosis release high-mobility group box 1 protein (HMGB1) that acts as an important proinflammatory mediator. Here, we show that in Chlamydia trachomatis-infected HeLa cells HMGB1 is not translocated from the nucleus to the cytosol and not released from injured cells in increased amounts. At 48 h after infection, degradation of HMGB1 was observed. In infected cells, poly(ADP-ribose) polymerase 1 (PARP-1), a DNA repair enzyme that also regulates HMGB1 translocation, was found to be cleaved into fragments that correspond to a necrosislike pattern of PARP-1 degradation. Cell-free cleavage assays and immunoprecipitation using purified proteolytic fractions from infected cells demonstrated that the chlamydial-protease-like activity factor (CPAF) is responsible for the cleavage of both HMGB1 and PARP-1. Proteolytic cleavage of PARP-1 was accompanied by a significant decrease in the enzymatic activity in a time-dependent manner. The loss of PARP-1 function obviously affects the viability of Chlamydia-infected cells because silencing of PARP-1 in uninfected HeLa cells with specific small interfering RNA results in increased cell membrane permeability. Our findings suggest that the Chlamydia-specific protease CPAF interferes with necrotic cell death pathways. By the degradation of HMGB1 and PARP-1, the pathogen may have evolved a strategy to reduce the inflammatory response to membrane-damaged cells in vivo

Table_1_Predicting diagnostic gene expression profiles associated with immune infiltration in patients with lupus nephritis.xlsx

ObjectiveTo identify potential diagnostic markers of lupus nephritis (LN) based on bioinformatics and machine learning and to explore the significance of immune cell infiltration in this pathology.MethodsSeven LN gene expression datasets were downloaded from the GEO database, and the larger sample size was used as the training group to obtain differential genes (DEGs) between LN and healthy controls, and to perform gene function, disease ontology (DO), and gene set enrichment analyses (GSEA). Two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE), were applied to identify candidate biomarkers. The diagnostic value of LN diagnostic gene biomarkers was further evaluated in the area under the ROC curve observed in the validation dataset. CIBERSORT was used to analyze 22 immune cell fractions from LN patients and to analyze their correlation with diagnostic markers.ResultsThirty and twenty-one DEGs were screened in kidney tissue and peripheral blood, respectively. Both of which covered macrophages and interferons. The disease enrichment analysis of DEGs in kidney tissues showed that they were mainly involved in immune and renal diseases, and in peripheral blood it was mainly enriched in cardiovascular system, bone marrow, and oral cavity. The machine learning algorithm combined with external dataset validation revealed that C1QA(AUC = 0.741), C1QB(AUC = 0.758), MX1(AUC = 0.865), RORC(AUC = 0.911), CD177(AUC = 0.855), DEFA4(AUC= 0.843)and HERC5(AUC = 0.880) had high diagnostic value and could be used as diagnostic biomarkers of LN. Compared to controls, pathways such as cell adhesion molecule cam, and systemic lupus erythematosus were activated in kidney tissues; cell cycle, cytoplasmic DNA sensing pathways, NOD-like receptor signaling pathways, proteasome, and RIG-1-like receptors were activated in peripheral blood. Immune cell infiltration analysis showed that diagnostic markers in kidney tissue were associated with T cells CD8 and Dendritic cells resting, and in blood were associated with T cells CD4 memory resting, suggesting that CD4 T cells, CD8 T cells and dendritic cells are closely related to the development and progression of LN.ConclusionC1QA, C1QB, MX1, RORC, CD177, DEFA4 and HERC5 could be used as new candidate molecular markers for LN. It may provide new insights into the diagnosis and molecular treatment of LN in the future.</p

Table_2_Predicting diagnostic gene expression profiles associated with immune infiltration in patients with lupus nephritis.xlsx

ObjectiveTo identify potential diagnostic markers of lupus nephritis (LN) based on bioinformatics and machine learning and to explore the significance of immune cell infiltration in this pathology.MethodsSeven LN gene expression datasets were downloaded from the GEO database, and the larger sample size was used as the training group to obtain differential genes (DEGs) between LN and healthy controls, and to perform gene function, disease ontology (DO), and gene set enrichment analyses (GSEA). Two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE), were applied to identify candidate biomarkers. The diagnostic value of LN diagnostic gene biomarkers was further evaluated in the area under the ROC curve observed in the validation dataset. CIBERSORT was used to analyze 22 immune cell fractions from LN patients and to analyze their correlation with diagnostic markers.ResultsThirty and twenty-one DEGs were screened in kidney tissue and peripheral blood, respectively. Both of which covered macrophages and interferons. The disease enrichment analysis of DEGs in kidney tissues showed that they were mainly involved in immune and renal diseases, and in peripheral blood it was mainly enriched in cardiovascular system, bone marrow, and oral cavity. The machine learning algorithm combined with external dataset validation revealed that C1QA(AUC = 0.741), C1QB(AUC = 0.758), MX1(AUC = 0.865), RORC(AUC = 0.911), CD177(AUC = 0.855), DEFA4(AUC= 0.843)and HERC5(AUC = 0.880) had high diagnostic value and could be used as diagnostic biomarkers of LN. Compared to controls, pathways such as cell adhesion molecule cam, and systemic lupus erythematosus were activated in kidney tissues; cell cycle, cytoplasmic DNA sensing pathways, NOD-like receptor signaling pathways, proteasome, and RIG-1-like receptors were activated in peripheral blood. Immune cell infiltration analysis showed that diagnostic markers in kidney tissue were associated with T cells CD8 and Dendritic cells resting, and in blood were associated with T cells CD4 memory resting, suggesting that CD4 T cells, CD8 T cells and dendritic cells are closely related to the development and progression of LN.ConclusionC1QA, C1QB, MX1, RORC, CD177, DEFA4 and HERC5 could be used as new candidate molecular markers for LN. It may provide new insights into the diagnosis and molecular treatment of LN in the future.</p

Link between Primate Lentiviral Coreceptor Usage and Nef Function

Simian immunodeficiency virus (SIVsmm) infection of sooty mangabeys (Cercocebus atys) is characterized by stable CD4+ T cell counts despite high plasma levels of CCR5-tropic viruses. However, in rare instances, SIVsmm acquires CXCR4 coreceptor tropism and causes severe CD4+ T cell depletion, albeit without clinical signs of immunodeficiency. Here, we show that CXCR4-tropic SIVsmm strains lost their ability to downmodulate TCR-CD3 by evolving unusual Nef mutations that initially reduced (I132V) and subsequently disrupted (I123L and L146F) interaction with the CD3 ζ chain. This coevolution of Env and Nef function suggests that CD3 downmodulation is advantageous for viral replication in activated CCR5+ memory T cells, but not in resting naive CXCR4+ T cells that have not yet undergone TCR-CD3-mediated stimulation. This may explain why HIV-1, which generally lacks the CD3 downmodulation function, commonly switches to CXCR4 usage, whereas this is extremely rare for SIV strains that have retained this Nef activity