Disruption of TIGAR-TAK1 alleviates immunopathology in a murine model of sepsis.

Macrophage-orchestrated inflammation contributes to multiple diseases including sepsis. However, the underlying mechanisms remain to be defined clearly. Here, we show that macrophage TP53-induced glycolysis and apoptosis regulator (TIGAR) is up-regulated in murine sepsis models. When myeloid Tigar is ablated, sepsis induced by either lipopolysaccharide treatment or cecal ligation puncture in male mice is attenuated via inflammation inhibition. Mechanistic characterizations indicate that TIGAR directly binds to transforming growth factor ß-activated kinase (TAK1) and promotes tumor necrosis factor receptor-associated factor 6-mediated ubiquitination and auto-phosphorylation of TAK1, in which residues 152-161 of TIGAR constitute crucial motif independent of its phosphatase activity. Interference with the binding of TIGAR to TAK1 by 5Z-7-oxozeaenol exhibits therapeutic effects in male murine model of sepsis. These findings demonstrate a non-canonical function of macrophage TIGAR in promoting inflammation, and confer a potential therapeutic target for sepsis by disruption of TIGAR-TAK1 interaction.

Accurate Characterization of Binding Kinetics and Allosteric Mechanisms for the HSP90 Chaperone Inhibitors Using AI-Augmented Integrative Biophysical Studies.

The binding kinetics of drugs to their targets are gradually being recognized as a crucial indicator of the efficacy of drugs in vivo, leading to the development of various computational methods for predicting the binding kinetics in recent years. However, compared with the prediction of binding affinity, the underlying structure and dynamic determinants of binding kinetics are more complicated. Efficient and accurate methods for predicting binding kinetics are still lacking. In this study, quantitative structure-kinetics relationship (QSKR) models were developed using 132 inhibitors targeting the ATP binding domain of heat shock protein 90α (HSP90α) to predict the dissociation rate constant (koff), enabling a direct assessment of the drug-target residence time. These models demonstrated good predictive performance, where hydrophobic and hydrogen bond interactions significantly influence the koff prediction. In subsequent applications, our models were used to assist in the discovery of new inhibitors for the N-terminal domain of HSP90α (N-HSP90α), demonstrating predictive capabilities on an experimental validation set with a new scaffold. In X-ray crystallography experiments, the loop-middle conformation of apo N-HSP90α was observed for the first time (previously, the loop-middle conformation had only been observed in holo-N-HSP90α structures). Interestingly, we observed different conformations of apo N-HSP90α simultaneously in an asymmetric unit, which was also observed in a holo-N-HSP90α structure, suggesting an equilibrium of conformations between different states in solution, which could be one of the determinants affecting the binding kinetics of the ligand. Different ligands can undergo conformational selection or alter the equilibrium of conformations, inducing conformational rearrangements and resulting in different effects on binding kinetics. We then used molecular dynamics simulations to describe conformational changes of apo N-HSP90α in different conformational states. In summary, the study of the binding kinetics and molecular mechanisms of N-HSP90α provides valuable information for the development of more targeted therapeutic approaches.

Construction of Risk Prediction Model of Type 2 Diabetic Kidney Disease Based on Deep Learning.

Background: This study aimed to develop a diabetic kidney disease (DKD) prediction model using long short term memory (LSTM) neural network and evaluate its performance using accuracy, precision, recall, and area under the curve (AUC) of the receiver operating characteristic (ROC) curve. Methods: The study identified DKD risk factors through literature review and physician focus group, and collected 7 years of data from 6,040 type 2 diabetes mellitus patients based on the risk factors. Pytorch was used to build the LSTM neural network, with 70% of the data used for training and the other 30% for testing. Three models were established to examine the impact of glycosylated hemoglobin (HbA1c), systolic blood pressure (SBP), and pulse pressure (PP) variabilities on the model's performance. Results: The developed model achieved an accuracy of 83% and an AUC of 0.83. When the risk factor of HbA1c variability, SBP variability, or PP variability was removed one by one, the accuracy of each model was significantly lower than that of the optimal model, with an accuracy of 78% (P<0.001), 79% (P<0.001), and 81% (P<0.001), respectively. The AUC of ROC was also significantly lower for each model, with values of 0.72 (P<0.001), 0.75 (P<0.001), and 0.77 (P<0.05). Conclusion: The developed DKD risk predictive model using LSTM neural networks demonstrated high accuracy and AUC value. When HbA1c, SBP, and PP variabilities were added to the model as featured characteristics, the model's performance was greatly improved.

Blockade of aryl hydrocarbon receptor restricts omeprazole-induced chronic kidney disease.

Chronic kidney disease (CKD) is the 16th leading cause of mortality worldwide. Clinical studies have raised that long-term use of omeprazole (OME) is associated with the morbidity of CKD. OME is commonly used in clinical practice to treat peptic ulcers and gastroesophageal reflux disease. However, the mechanism underlying renal failure following OME treatment remains mostly unknown and the rodent model of OME-induced CKD is yet to be established. We described the process of renal injury after exposure to OME in mice; the early renal injury markers were increased in renal tubular epithelial cells (RTECs). And after long-term OME treatment, the OME-induced CKD mice model was established. Herein, aryl hydrocarbon receptor (AHR) translocation appeared after exposure to OME in HK-2 cells. Then for both in vivo and in vitro, we found that Ahr-knockout (KO) and AHR small interfering RNA (siRNA) substantially alleviated the OME-induced renal function impairment and tubular cell damage. Furthermore, our data demonstrate that antagonists of AHR and CYP1A1 could attenuate OME-induced tubular cell impairment in HK-2 cells. Taken together, these data indicate that OME induces CKD through the activation of the AHR-CYP axis in RTECs. Our findings suggest that blocking the AHR-CYP1A1 pathway acts as a potential strategy for the treatment of CKD caused by OME. KEY MESSAGES: We provide an omeprazole-induced chronic kidney disease (CKD) mice model. AHR activation and translocation process was involved in renal tubular damage and promoted the occurrence of CKD. The process of omeprazole nephrotoxicity can be ameliorated by blockade of the AHR-CYP1A1 axis.

Application of targeted liposomes-based salvianolic acid A for the treatment of ischemic stroke.

Novel therapeutics for the treatment of ischemic stroke remains to be the unmet clinical needs. Previous studies have indicated that salvianolic acid A (SAA) is a promising candidate for the treatment of the brain diseases. However, SAA has poor absolute bioavailability and does not efficiently cross the intact blood-brain barrier (BBB), which limit its efficacy. To this end we developed a brain-targeted liposomes for transporting SAA via the BBB by incorporating the liposomes to a transport receptor, insulin-like growth factor-1 receptor (IGF1R). The liposomes were prepared by ammonium sulfate gradients loading method. The prepared SAA-loaded liposomes (Lipo/SAA) were modified with IGF1R monoclonal antibody to generate IGF1R antibody-conjugated Lipo/SAA (IGF1R-targeted Lipo/SAA). The penetration of IGF1R-targeted Lipo/SAA into the brain was confirmed by labeling with Texas Red, and their efficacy were evaluate using middle cerebral artery occlusion (MCAO) model. The results showed that IGF1R-targeted Lipo/SAA are capable of transporting SAA across the BBB into the brain, accumulation in brain tissue, and sustained releasing SAA for several hours. Administration o IGF1R-targeted Lipo/SAA notably reduced infarct size and neuronal damage, improved neurological function and inhibited cerebral inflammation, which had much higher efficiency than no-targeted SAA.

Structure-based design of pan-coronavirus inhibitors targeting host cathepsin L and calpain-1.

Respiratory disease caused by coronavirus infection remains a global health crisis. Although several SARS-CoV-2-specific vaccines and direct-acting antivirals are available, their efficacy on emerging coronaviruses in the future, including SARS-CoV-2 variants, might be compromised. Host-targeting antivirals provide preventive and therapeutic strategies to overcome resistance and manage future outbreak of emerging coronaviruses. Cathepsin L (CTSL) and calpain-1 (CAPN1) are host cysteine proteases which play crucial roles in coronaviral entrance into cells and infection-related immune response. Here, two peptidomimetic α-ketoamide compounds, 14a and 14b, were identified as potent dual target inhibitors against CTSL and CAPN1. The X-ray crystal structures of human CTSL and CAPN1 in complex with 14a and 14b revealed the covalent binding of α-ketoamide groups of 14a and 14b to C25 of CTSL and C115 of CAPN1. Both showed potent and broad-spectrum anticoronaviral activities in vitro, and it is worth noting that they exhibited low nanomolar potency against SARS-CoV-2 and its variants of concern (VOCs) with EC50 values ranging from 0.80 to 161.7 nM in various cells. Preliminary mechanistic exploration indicated that they exhibited anticoronaviral activity through blocking viral entrance. Moreover, 14a and 14b exhibited good oral pharmacokinetic properties in mice, rats and dogs, and favorable safety in mice. In addition, both 14a and 14b treatments demonstrated potent antiviral potency against SARS-CoV-2 XBB 1.16 variant infection in a K18-hACE2 transgenic mouse model. And 14b also showed effective antiviral activity against HCoV-OC43 infection in a mouse model with a final survival rate of 60%. Further evaluation showed that 14a and 14b exhibited excellent anti-inflammatory effects in Raw 264.7 mouse macrophages and in mice with acute pneumonia. Taken together, these results suggested that 14a and 14b are promising drug candidates, providing novel insight into developing pan-coronavirus inhibitors with antiviral and anti-inflammatory properties.

Novel biomarkers related to oxidative stress and immunity in chronic kidney disease.

Introduction: The incidence of chronic kidney disease (CKD) has been increasing in recent years, gradually becoming a global health crisis. Due to limited treatment options, novel molecular pathways are urgently required to advance the treatment and diagnosis of CKD. Materials and methods: The characteristics of differentially expressed genes (DEGs) in CKD patients were analyzed using Gene Expression Omnibus (GEO) database, and genes related to oxidative stress were retrieved from the Genecard database. Subsequently, a comprehensive approach was applied, including immune infiltration analysis, weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network analysis, to identify hub genes among differentially expressed immune-related oxidative stress genes (DEIOSGs). Validation of hub genes was performed using an external data set, and diagnostic potential capability was evaluated through receiver operating curve (ROC) analysis. In animal experiments, the expression of hub genes in CKD was confirmed by inducing a CKD model through a 5/6 nephrectomy procedure. Finally, the relationship between these hub genes and clinical characteristics were assessed using the Nephroseq v5 database. Results: 29 DEIOSGs were identified by comprehensive bioinformatics analysis. PPI analysis screened the hub genes NCF2, S100A9, and SELL. ROC analysis demonstrated excellent diagnostic efficacy. Further validation from other databases and animal experiments confirmed a substantial upregulation in the expression of hub genes in CKD. Additionally, clinical correlation analysis established a clear link between hub gene expression and renal function deterioration. Conclusions: Our study confirms NCF2, S100A9, and SELL as diagnostic biomarkers associated with immune response and oxidative stress in CKD, suggesting their potential as novel targets for CKD diagnosis and treatment.

Perioperative Insulin Pump Therapy Decreases Readmission Risk and Improves Outcomes in Patients with Diabetes.

OBJECTIVE: To evaluate the impact of temporary insulin pump use during hospitalization on glycemia, postoperative complications, and cost/utilization in perioperative patients with diabetes. METHODS: Patients (n=159) with type 2 diabetes and hospitalized for elective surgery were recruited from three hospitals. Subjects were categorized into the insulin pump group and the multiple daily subcutaneous insulin injection group according to their treatment therapy. Data were collected at admission, discharge, and 3 months post-discharge. RESULTS: Subjects in the CSII group who were still on insulin therapy transitioned from CSII to MDII; however, their daily insulin dosages were lower than those in the MDII group (15.31±10.98 U/d vs. 23.48±17.02 U/d, P=0.015) after discharge. In terms of medical costs, the CSII group had significantly higher hospitalization costs than the MDII group (112.36±103.43 thousand RMB vs. 82.65±77.98 thousand RMB, P=0.043). After 3 months, the CSII group had significantly lower outpatient costs than the MDII group (3.17±0.94 thousand RMB vs. 3.98±1.76 thousand RMB, P ˂ 0.001). In the MDII group, 10 patients reported severe postoperative complications requiring re-hospitalization; there were no similar reports in the CSII group. CONCLUSION: Temporary use of insulin pump therapy for perioperative patients with diabetes results in a reduction in blood glucose and blood glucose fluctuation during hospitalization, HbA1c, and the risk of postoperative complication and readmission, thus significantly decreasing costs in this complex patient cohort. Further work is needed to better understand indications for utilizing pump therapy based on diabetes phenotype and the complexity of planned surgical intervention.

Salvianolic acid B attenuates liver fibrosis by targeting Ecm1 and inhibiting hepatocyte ferroptosis.

Hepatocyte ferroptosis promotes the pathogenesis and progression of liver fibrosis. Salvianolic acid B (Sal B) exerts antifibrotic effects. However, the pharmacological mechanism and target has not yet been fully elucidated. In this study, liver fibrosis was induced by CCl4 in wild-type mice and hepatocyte-specific extracellular matrix protein 1 (Ecm1)-deficient mice, which were separately treated with Sal B, ferrostatin-1, sorafenib or cilengitide. Erastin- or CCl4-induced hepatocyte ferroptosis models with or without Ecm1 gene knockdown were evaluated in vitro. Subsequently, the interaction between Ecm1 and xCT and the binding kinetics of Sal B and Ecm1 were determined. We found that Sal B significantly attenuated liver fibrosis in CCl4-induced mice. Ecm1 deletion in hepatocytes abolished the antifibrotic effect of Sal B. Mechanistically, Sal B protected against hepatocyte ferroptosis by upregulating Ecm1. Further research revealed that Ecm1 as a direct target for treating liver fibrosis with Sal B. Interestingly, Ecm1 interacted with xCT to regulate hepatocyte ferroptosis. Hepatocyte ferroptosis in vitro was significantly attenuated by Sal B treatment, which was abrogated after knockdown of Ecm1 in LO2 cells. Therefore, Sal B alleviates liver fibrosis in mice by targeting up-regulation of Ecm1 and inhibiting hepatocyte ferroptosis. The interaction between Ecm1 and xCT regulates hepatocyte ferroptosis.

THEMIS is a substrate and allosteric activator of SHP1, playing dual roles during T cell development.

THEMIS plays an indispensable role in T cells, but its mechanism of action has remained highly controversial. Using the systematic proximity labeling methodology PEPSI, we identify THEMIS as an uncharacterized substrate for the phosphatase SHP1. Saturated mutagenesis assays and mass spectrometry analysis reveal that phosphorylation of THEMIS at the evolutionally conserved Tyr34 residue is oppositely regulated by SHP1 and the kinase LCK. Similar to THEMIS-/- mice, THEMISY34F/Y34F knock-in mice show a significant decrease in CD4 thymocytes and mature CD4 T cells, but display normal thymic development and peripheral homeostasis of CD8 T cells. Mechanistically, the Tyr34 motif in THEMIS, when phosphorylated upon T cell antigen receptor activation, appears to act as an allosteric regulator, binding and stabilizing SHP1 in its active conformation, thus ensuring appropriate negative regulation of T cell antigen receptor signaling. However, cytokine signaling in CD8 T cells fails to elicit THEMIS Tyr34 phosphorylation, indicating both Tyr34 phosphorylation-dependent and phosphorylation-independent roles of THEMIS in controlling T cell maturation and expansion.

Scavenger Receptor Class B Type I Deficiency Induces Iron Overload and Ferroptosis in Renal Tubular Epithelial Cells via Hypoxia-Inducible Factor-1α/Transferrin Receptor 1 Signaling Pathway.

Aims: Scavenger receptor class B type I (SRBI) promotes cell cholesterol efflux and the clearance of plasma cholesterol. Thus, SRBI deficiency causes abnormal cholesterol metabolism and hyperlipidemia. Studies have suggested that ferroptosis is involved in lipotoxicity; however, whether SRBI deficiency could induce ferroptosis remains to be investigated. Results: We knocked down or knocked out SRBI in renal HK-2 cells and C57BL/6 mice to determine the expression levels of ferroptosis-related regulators. Our results demonstrated that SRBI deficiency upregulates transferrin receptor 1 (TFR1) expression and downregulates ferroportin expression, which induces iron overload and subsequent ferroptosis in renal tubular epithelial cells. TFR1 is known to be regulated by hypoxia-inducible factor-1α (HIF-1α). Next, we investigated whether SRBI deletion affected HIF-1α. SRBI deletion upregulated the mRNA and protein expression of HIF-1α, and promoted its translocation to the nucleus. To determine whether HIF-1α plays a key role in SRBI-deficiency-induced ferroptosis, we used HIF-1α inhibitor and siHIF-1α in HK-2 cells, and found that downregulation of HIF-1α prevented SRBI-silencing-induced TFR1 upregulation and iron overload, and eventually reduced ferroptosis. The underlying mechanism of HIF-1α activation was explored next, and the results showed that SRBI knockout or knockdown may upregulate the expression of HIF-1α, and promote HIF-1α translocation from the cytoplasm into the nucleus via the PKC-ß/NF-κB signaling pathway. Innovation and Conclusion: Our study showed, for the first time, that SRBI deficiency induces iron overload and subsequent ferroptosis via the HIF-1α/TFR1 pathway.

The association of normal-range serum phosphorus with immunoglobulin A nephropathy progression: a retrospective cohort study.

PURPOSE: The relationship between serum phosphorus and immunoglobulin A (IgA) nephropathy progression remains uncertain, especially normal-range serum phosphorus. Therefore, we herein examined the relationship between the normal-range serum phosphorus and the progression of IgA nephropathy. METHODS: One hundred sixty-two patients with primary IgA nephropathy were divided into three groups according to tertiles of baseline serum phosphorus (first tertile: 0.73-1.04 mmol/L; second tertile: 1.04-1.21 mmol/L; third tertile: 1.21-1.60 mmol/L). Estimated glomerular filtration rate (eGFR) was calculated using the chronic kidney disease epidemiology collaboration. The composite outcome was defined as a decrease of at least 50% in eGFR from baseline or end-stage kidney disease (ESKD). The association of serum phosphorus with IgA nephropathy progression was estimated using Cox proportional hazards models, adjusting for potential confounders. RESULTS: During a median 16 month follow-up period, 15 patients reached a composite outcome. In the crude Cox proportional hazard model, baseline serum phosphorus as a continuous variable was associated with increased risk for adverse renal outcomes [hazard ratio (HR) = 63.510, 95% confidence interval (CI) = 3.953-1020.284, P = 0.003], and the high tertile of serum phosphorus group had an increased risk of the composite outcome by using the low tertile group as the reference (HR = 11.895, 95% CI = 1.522-92.993, P = 0.018). After adjustment for traditional risk factors, the high tertile of serum phosphorus group was significantly related to IgA nephropathy progression compared with the low tertile group (HR = 9.424, 95% CI = 1.019-87.165, P = 0.048). CONCLUSIONS: Relatively higher serum phosphorus levels within the normal range were significantly associated with the progression of IgA nephropathy.

TEFDTA: a transformer encoder and fingerprint representation combined prediction method for bonded and non-bonded drug-target affinities.

MOTIVATION: The prediction of binding affinity between drug and target is crucial in drug discovery. However, the accuracy of current methods still needs to be improved. On the other hand, most deep learning methods focus only on the prediction of non-covalent (non-bonded) binding molecular systems, but neglect the cases of covalent binding, which has gained increasing attention in the field of drug development. RESULTS: In this work, a new attention-based model, A Transformer Encoder and Fingerprint combined Prediction method for Drug-Target Affinity (TEFDTA) is proposed to predict the binding affinity for bonded and non-bonded drug-target interactions. To deal with such complicated problems, we used different representations for protein and drug molecules, respectively. In detail, an initial framework was built by training our model using the datasets of non-bonded protein-ligand interactions. For the widely used dataset Davis, an additional contribution of this study is that we provide a manually corrected Davis database. The model was subsequently fine-tuned on a smaller dataset of covalent interactions from the CovalentInDB database to optimize performance. The results demonstrate a significant improvement over existing approaches, with an average improvement of 7.6% in predicting non-covalent binding affinity and a remarkable average improvement of 62.9% in predicting covalent binding affinity compared to using BindingDB data alone. At the end, the potential ability of our model to identify activity cliffs was investigated through a case study. The prediction results indicate that our model is sensitive to discriminate the difference of binding affinities arising from small variances in the structures of compounds. AVAILABILITY AND IMPLEMENTATION: The codes and datasets of TEFDTA are available at https://github.com/lizongquan01/TEFDTA.

A new variant of the colistin resistance gene MCR-1 with co-resistance to ß-lactam antibiotics reveals a potential novel antimicrobial peptide.

The emerging and global spread of a novel plasmid-mediated colistin resistance gene, mcr-1, threatens human health. Expression of the MCR-1 protein affects bacterial fitness and this cost correlates with lipid A perturbation. However, the exact molecular mechanism remains unclear. Here, we identified the MCR-1 M6 variant carrying two-point mutations that conferred co-resistance to ß-lactam antibiotics. Compared to wild-type (WT) MCR-1, this variant caused severe disturbance in lipid A, resulting in up-regulation of L, D-transpeptidases (LDTs) pathway, which explains co-resistance to ß-lactams. Moreover, we show that a lipid A loading pocket is localized at the linker domain of MCR-1 where these 2 mutations are located. This pocket governs colistin resistance and bacterial membrane permeability, and the mutated pocket in M6 enhances the binding affinity towards lipid A. Based on this new information, we also designed synthetic peptides derived from M6 that exhibit broad-spectrum antimicrobial activity, exposing a potential vulnerability that could be exploited for future antimicrobial drug design.

MvaT binds to the PexsC promoter to repress the type III secretion system in Pseudomonas aeruginosa.

Pseudomonas aeruginosa is an opportunistic human pathogen capable of causing a variety of acute and chronic infections. Its type III secretion system (T3SS) plays a critical role in pathogenesis during acute infection. ExsA is a master regulator that activates the expression of all T3SS genes. Transcription of exsA is driven by two distinct promoters, its own promoter PexsA and its operon promoter PexsC. Here, in combination with a DNA pull-down assay and mass spectrometric analysis, we found that a histone-like nucleoid-structuring (H-NS) family protein MvaT can bind to the PexsC promoter. Using EMSA and reporter assays, we further found that MvaT directly binds to the PexsC promoter to repress the expression of T3SS genes. The repression of MvaT on PexsC is independent of ExsA, with MvaT binding to the -429 to -380 bp region relative to the transcription start site of the exsC gene. The presented work further reveals the complex regulatory network of the T3SS in P. aeruginosa.

DeepSA: a deep-learning driven predictor of compound synthesis accessibility.

With the continuous development of artificial intelligence technology, more and more computational models for generating new molecules are being developed. However, we are often confronted with the question of whether these compounds are easy or difficult to synthesize, which refers to synthetic accessibility of compounds. In this study, a deep learning based computational model called DeepSA, was proposed to predict the synthesis accessibility of compounds, which provides a useful tool to choose molecules. DeepSA is a chemical language model that was developed by training on a dataset of 3,593,053 molecules using various natural language processing (NLP) algorithms, offering advantages over state-of-the-art methods and having a much higher area under the receiver operating characteristic curve (AUROC), i.e., 89.6%, in discriminating those molecules that are difficult to synthesize. This helps users select less expensive molecules for synthesis, reducing the time and cost required for drug discovery and development. Interestingly, a comparison of DeepSA with a Graph Attention-based method shows that using SMILES alone can also efficiently visualize and extract compound's informative features. DeepSA is available online on the below web server ( https://bailab.siais.shanghaitech.edu.cn/services/deepsa/ ) of our group, and the code is available at https://github.com/Shihang-Wang-58/DeepSA .

Correlation Between the Variability of Different Obesity Indices and Diabetic Kidney Disease: A Retrospective Cohort Study Based on Populations in Taiwan.

Purpose: To investigate the association of five obesity indices and the variability of these indices with diabetic kidney disease (DKD) in patients with type 2 diabetes and compare the predictive validity of these markers for the risk of DKD in this large longitudinal cohort study. Patients and Methods: A total of 2659 patients with type 2 diabetes who did not have DKD were enrolled between 2006 and 2019 at Lee's United Clinic in Taiwan. Data were collected for each subject, including demographic data, personal medical history, clinical parameters and calculated Body mass index (BMI), visceral adiposity index (VAI), lipid accumulation product (LAP), body roundness index (BRI) and variability of five obesity indices. Cox regression analysis was performed to determine the relationship between different obesity indicators and DKD risk. Cox's proportional hazards model was evaluated the predictive effect of obesity indices on DKD. Results: The risk of developing DKD increased with an increase in the BRI, LAP, VAI, WC and BMI (all P trend<0.05), and the variability of VAI was significantly associated with DKD [HR=1.132, 95% CI (1.001, 1.281)] after adjusting for corresponding variables. BRI had the strongest predictive effect on DKD. BRI had the best predictive performance, with AUC of 0.807, 0.663 and 0.673 at 1, 3 and 5 years, respectively. Cox regression analysis of risk factors for DKD in patients stratified by BRI quartiles showed that patients in the Q4 group had the highest risk of developing DKD [HR=1.356, 95% CI (1.131, 1.626)]. Conclusion: BMI, WC, VAI, LAP, BRI and VAI variability were associated with a significant increase in the risk of DKD events, and BRI was superior and alternative obesity index for predicting DKD.

Murepavadin induces envelope stress response and enhances the killing efficacies of ß-lactam antibiotics by impairing the outer membrane integrity of Pseudomonas aeruginosa.

Pseudomonas aeruginosa is a ubiquitous opportunistic pathogen that can cause a variety of acute and chronic infections. The bacterium is highly resistant to numerous antibiotics. Murepavadin is a peptidomimetic antibiotic that blocks the function of P. aeruginosa lipopolysaccharide (LPS) transport protein D (LptD), thus inhibiting the insertion of LPS into the outer membrane. In this study, we demonstrated that sublethal concentrations of murepavadin enhance the bacterial outer membrane permeability. Proteomic analyses revealed the alteration of protein composition in bacterial inner and outer membranes following murepavadin treatment. The antisigma factor MucA was upregulated by murepavadin. In addition, the expression of the sigma E factor gene algU and the alginate synthesis gene algD was induced by murepavadin. Deletion of the algU gene reduces bacterial survival following murepavadin treatment, indicating a role of the envelope stress response in bacterial tolerance. We further demonstrated that murepavadin enhances the bactericidal activities of ß-lactam antibiotics by promoting drug influx across the outer membrane. In a mouse model of acute pneumonia, the murepavadin-ceftazidime/avibactam combination showed synergistic therapeutic effect against P. aeruginosa infection. In addition, the combination of murepavadin with ceftazidime/avibactam slowed down the resistance development. In conclusion, our results reveal the response mechanism of P. aeruginosa to murepavadin and provide a promising antibiotic combination for the treatment of P. aeruginosa infections.IMPORTANCEThe ever increasing resistance of bacteria to antibiotics poses a serious threat to global public health. Novel antibiotics and treatment strategies are urgently needed. Murepavadin is a novel antibiotic that blocks the assembly of lipopolysaccharide (LPS) into the Pseudomonas aeruginosa outer membrane by inhibiting LPS transport protein D (LptD). Here, we demonstrated that murepavadin impairs bacterial outer membrane integrity, which induces the envelope stress response. We further found that the impaired outer membrane integrity increases the influx of ß-lactam antibiotics, resulting in enhanced bactericidal effects. In addition, the combination of murepavadin and a ß-lactam/ß-lactamase inhibitor mixture (ceftazidime/avibactam) slowed down the resistance development of P. aeruginosa. Overall, this study demonstrates the bacterial response to murepavadin and provides a new combination strategy for effective treatment.

DnaJ-induced miRNA-146a negatively regulates the expression of IL-8 in macrophages.

As a member of the damage-associated molecular patterns, heat shock proteins (HSPs) are widely recognized for their role in initiating innate immune responses. These highly conserved proteins are expressed ubiquitously in both prokaryotes and eukaryotes. In this study, our aim was to investigate how DnaJ, a HSP40 homolog derived from Pseudomonas aeruginosa (P. aeruginosa), influences the regulation of IL-8 expression in macrophages. Treatment with DnaJ served as a stimulus, inducing a more robust expression of IL-8 compared to other HSP homologs, including DnaK, GroEL, and HtpG. This effect was achieved through the activation of the NF-κB signaling pathway. Interestingly, DnaJ treatment also significantly increased the expression of microRNA-146a (miR-146a), which appears to play a role in modulating the expression of innate defense genes. As a consequence, pre-treatment with DnaJ led to a reduction in the extent of IL-8 induction in response to P. aeruginosa treatment. Notably, this reduction was counteracted by transfection of a miR-146a inhibitor, highlighting the involvement of miR-146a in P. aeruginosa-mediated induction of IL-8 expression. Therefore, this study uncovers the role of DnaJ in triggering the expression of miR-146a, which, in turn, modulates the excessive expression of IL-8 induced by P. aeruginosa infection.