Factors predicting the adhesion and prolonged lost days of work in patients with extensor tendon adhesion of the hand.

Objective: Extensor tendon adhesion receive less attention recently. This study aims to analyze influencing factors of adhesion and prolonged lost days of work in patients with extensor tendon adhesion of the hand. Method: We performed a retrospective study in patients with extensor tendon injuries who underwent primary surgical repair and early rehabilitation. We observed the differences between non-tendon adhesion and adhesion patients after surgical repair, and used the receiver operating characteristic curve to distinguish them. Then we explored the influencing factors of adhesion. In addition, we studied the lost days of work and the influencing factors. Results: A total of 305 patients were included. 24.6% patients appeared tendon adhesion and the mean lost days of work was 12 weeks. MHISS scores, VAS scores, occupation and blood triglyceride level were the influencing factors of adhesion. The adhesion patients have increased MHISS scores (p < 0.001), VAS scores (p < 0.001), blood triglyceride levels (p < 0.001) and lost days of work (p < 0.001) than non-tendon adhesion. The optimal cut-off value of blood triglyceride level to distinguish non-tendon adhesion from adhesion was 1.625 mml/L, and MHISS scores was 20.5. Smoking, MHISS scores, blood triglyceride levels were the influencing factors of lost days of work in adhesion patients. There was positive correlation between lost days of work and triglyceride level (r = 0.307, p = 0.007), and MHISS scores (r = 0.276, p = 0.016). Conclusion: To minimize the occurrence of adhesion, doctors should pay attention to patients with higher MHISS and VAS scores, blood triglyceride levels, especial for the blue-collar and unemployed one. High triglyceride level may be a new influencing factor.

Acetylation is required for full activation of the NLRP3 inflammasome.

Full activation of the NLRP3 inflammasome needs two sequential signals: a priming signal, followed by a second, assembly signal. Several studies have shown that the two signals trigger post-translational modification (PTM) of NLRP3, affecting activity of the inflammasome, however, the PTMs induced by the second signal are less well characterized. Here, we show that the assembly signal involves acetylation of NLRP3 at lysine 24, which is important for the oligomerization and the actual assembly of NLRP3 without affecting its recruitment to dispersed trans-Golgi network (dTGN). Accordingly, NLRP3 inflammasome activation is impaired in NLRP3-K24R knock-in mice. We identify KAT5 as an acetyltransferase able to acetylate NLRP3. KAT5 deficiency in myeloid cells and pharmacological inhibition of KAT5 enzymatic activity reduce activation of the NLRP3 inflammasome, both in vitro and in vivo. Thus, our study reveals a key mechanism for the oligomerization and full activation of NLRP3 and lays down the proof of principle for therapeutic targeting of the KAT5-NLRP3 axis.

Dapagliflozin prevents oxidative stress-induced endothelial dysfunction via sirtuin 1 activation.

Recent studies have demonstrated that dapagliflozin, a sodium-glucose cotransporter type 2 (SGLT2) inhibitor, prevents endothelial dysfunction; however, direct effects of dapagliflozin on the endothelium under oxidative stress and the underlying mechanism of action are not completely understood. This study aimed to define the role and related mechanisms of dapagliflozin in hydrogen peroxide (H2O2)-induced endothelial dysfunction. The endothelium-dependent vasorelaxation effect of dapagliflozin was assessed in an organ bath study. Endothelial dysfunction was assessed using protein expression level and phosphorylation of endothelial nitric oxide synthase (eNOS), nitric oxide (NO), reactive oxygen species (ROS), senescence-associated beta-galactosidase (SA-ß-gal) activity, and senescence marker proteins (p21, p53). Co-immunoprecipitation and protein acetylation were performed to detect protein interactions. Dapagliflozin exerted a direct vasorelaxant effect in the aortic rings of C57BL/6 J mice. Furthermore, there was a significant improvement in endothelium-dependent vasorelaxation in dapagliflozin-treated diabetic mice compared to vehicle controls. Moreover, intracellular ROS levels and ONOO- levels, increased by H2O2, were reduced by dapagliflozin. Importantly, dapagliflozin inhibited H2O2-induced senescence in the human umbilical vein endothelial cells (HUVECs), as indicated by reduced SA-ß-gal, p21, and p53. Mechanistically, dapagliflozin reversed the H2O2-mediated inhibition of eNOS serine phosphorylation and sirtuin 1 (SIRT1) expression in endothelial cells. In particular, SIRT1-mediated eNOS deacetylation is reportedly involved in dapagliflozin-enhanced eNOS activity. These findings indicate that dapagliflozin ameliorates endothelial dysfunction by restoring eNOS activity, restoring NO bioavailability, and reducing ROS generation via SIRT1 activation in oxidative stress-stimulated endothelial cells.

Identification of risk factors for infection after mitral valve surgery through machine learning approaches.

Background: Selecting features related to postoperative infection following cardiac surgery was highly valuable for effective intervention. We used machine learning methods to identify critical perioperative infection-related variables after mitral valve surgery and construct a prediction model. Methods: Participants comprised 1223 patients who underwent cardiac valvular surgery at eight large centers in China. The ninety-one demographic and perioperative parameters were collected. Random forest (RF) and least absolute shrinkage and selection operator (LASSO) techniques were used to identify postoperative infection-related variables; the Venn diagram determined overlapping variables. The following ML methods: random forest (RF), extreme gradient boosting (XGBoost), Support Vector Machine (SVM), Gradient Boosting Decision Tree (GBDT), AdaBoost, Naive Bayesian (NB), Logistic Regression (LogicR), Neural Networks (nnet) and artificial neural network (ANN) were developed to construct the models. We constructed receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC) was calculated to evaluate model performance. Results: We identified 47 and 35 variables with RF and LASSO, respectively. Twenty-one overlapping variables were finally selected for model construction: age, weight, hospital stay, total red blood cell (RBC) and total fresh frozen plasma (FFP) transfusions, New York Heart Association (NYHA) class, preoperative creatinine, left ventricular ejection fraction (LVEF), RBC count, platelet (PLT) count, prothrombin time, intraoperative autologous blood, total output, total input, aortic cross-clamp (ACC) time, postoperative white blood cell (WBC) count, aspartate aminotransferase (AST), alanine aminotransferase (ALT), PLT count, hemoglobin (Hb), and LVEF. The prediction models for infection after mitral valve surgery were established based on these variables, and they all showed excellent discrimination performance in the test set (AUC > 0.79). Conclusions: Key features selected by machine learning methods can accurately predict infection after mitral valve surgery, guiding physicians in taking appropriate preventive measures and diminishing the infection risk.

GSDMD-mediated pyroptosis restrains intracellular Chlamydia trachomatis growth in macrophages.

Pyroptosis, a type of programmed necrosis associated with inflammatory, is a host defense mechanism against microbial infections. Although Chlamydia has been shown to induce pyroptosis, whether pyroptosis directly impacts the growth of Chlamydia has not been demonstrated. In this study, we found that C. trachomatis L2 infection of the mouse macrophage RAW 264.7 cells induced pyroptosis by monitoring the ultrastructural changes under transmission electron microscopy and the release of LDH and IL-1ß. More importantly, this C. trachomatis-triggered pyroptosis with activation of caspase-1 and caspase-11 was also accompanied by gasdermin D (GSDMD) activation. Suppression of these two inflammatory caspases inhibited GSDMD activation. Interestingly, the C. trachomatis-triggered pyroptosis significantly inhibited the intracellular growth of C. trachomatis since inactivation of either GSDMD or caspase-1/11 significantly rescued infectious C. trachomatis yields, which suggests pyroptosis response can be utilized as an intrinsic mechanism to restrict C. trachomatis intracellular infection in addition to the well- documented extrinsic mechanisms by recruiting and enhancing inflammatory responses. This study may reveal novel targets for attenuating C. trachomatis infectivity and/or pathogenicity.

Enhancing Conformational Sampling for Intrinsically Disordered and Ordered Proteins by Variational Autoencoder.

Intrinsically disordered proteins (IDPs) account for more than 50% of the human proteome and are closely associated with tumors, cardiovascular diseases, and neurodegeneration, which have no fixed three-dimensional structure under physiological conditions. Due to the characteristic of conformational diversity, conventional experimental methods of structural biology, such as NMR, X-ray diffraction, and CryoEM, are unable to capture conformational ensembles. Molecular dynamics (MD) simulation can sample the dynamic conformations at the atomic level, which has become an effective method for studying the structure and function of IDPs. However, the high computational cost prevents MD simulations from being widely used for IDPs conformational sampling. In recent years, significant progress has been made in artificial intelligence, which makes it possible to solve the conformational reconstruction problem of IDP with fewer computational resources. Here, based on short MD simulations of different IDPs systems, we use variational autoencoders (VAEs) to achieve the generative reconstruction of IDPs structures and include a wider range of sampled conformations from longer simulations. Compared with the generative autoencoder (AEs), VAEs add an inference layer between the encoder and decoder in the latent space, which can cover the conformational landscape of IDPs more comprehensively and achieve the effect of enhanced sampling. Through experimental verification, the Cα RMSD between VAE-generated and MD simulation sampling conformations in the 5 IDPs test systems was significantly lower than that of AE. The Spearman correlation coefficient on the structure was higher than that of AE. VAE can also achieve excellent performance regarding structured proteins. In summary, VAEs can be used to effectively sample protein structures.

Leukadherin-1 inhibits NLRP3 inflammasome by blocking inflammasome assembly.

Aberrant activation of the NLRP3 inflammasome has been implicated in the occurrence and development of many inflammatory diseases, and thus potent inhibitors of the NLRP3 inflammasome should be explored. An antitumor agent, Leukadherin-1 (LA-1), tested in phase 1/2 clinical trials, has been reported to exert anti-inflammatory properties by blocking the NF-κB pathway. However, the effects of LA-1 on the NLRP3 inflammasome have not been conclusively determined. In this study, we found that at lower doses (below 1 µM) ex vivo, LA-1 blocked NLRP3 inflammasome activation without affecting NF-κB signaling. Accordingly, 1 mg/Kg LA-1 strongly inhibited the release of NLRP3-dependent cytokine, but only slightly inhibited NLRP3-independent-cytokines secretion in endotoxemia and alleviated NLRP3-dependent peritonitis in vivo. Mechanistically, LA-1 had no effects on ion flux or mitochondrial injury. Instead, it inhibited NLRP3 inflammasome assembly by suppressing ASC oligomerization, blocking NLRP3 self-assembly, and reducing interactions of NLRP3 with ASC and NEK7. Therefore, LA-1 inhibits NLRP3 inflammasome activation, implying that it is a potential treatment option for NLRP3-associated diseases.

ß-catenin promotes NLRP3 inflammasome activation via increasing the association between NLRP3 and ASC.

NLRP3 (NOD-, LRR- and pyrin domain- containing protein 3) inflammasome is involved in diverse inflammatory diseases, so the activation of NLRP3 inflammasome needs to be tightly regulated to prevent excessive inflammation. However, the endogenous regulatory mechanisms of NLRP3 inflammasome are still less defined. Here, we report that ß-catenin, which is the central mediator of the canonical Wnt/ß-catenin signaling, promotes NLRP3 inflammasome activation. When we suppressed the expression of ß-catenin by siRNA or pharmacological inhibitor, the NLRP3 inflammasome activation was impaired. Accordingly, ß-catenin inhibitor attenuated LPS-induced systemic inflammation in vivo. Mechanistically, we found ß-catenin interacted with NLRP3 and promoted the association between NLRP3 and ASC. Thus, our study revealed a novel role of ß-catenin in NLRP3 inflammasome activation and suggest an endogenous crosstalk between Wnt/ß-catenin signal and NLRP3 inflammasome.

Downregulated expression of miR-223 promotes Toll-like receptor-activated inflammatory responses in macrophages by targeting RhoB.

Toll-like receptors (TLRs) induced-inflammatory response must be tightly regulated to avoid impairment in host itself. Numerous factors have been identified in regulation of TLR-triggered inflammatory response. Among these, microRNAs (miRNAs) are small non-coding RNA molecules which have got much attention. MiR-223, which highly expresses in myeloid cells of the bone marrow, has reported to participate in kinds of inflammatory responses by targeting inflammasome sensor-NLRP3 to repress production of IL-6 and IL-1ß, and thus attenuate inflammatory response. However, the function of miR-223 in TLRs-activated inflammatory response of macrophages is not clear. Here we found miR-223 expression is dramatically reduced in macrophages by TLR ligand stimulation (e.g. LPS, CpG and poly (I:C)). The down-regulated miR-223 leads to the increase in the RhoB expression, which induce the activation of NF-κB and MAPK signaling, promoting TNF-α, IL-6 and IL-1ß production upon LPS stimulation. In addition, the histone deacetylase inhibitor trichostatin A increased miR-223 expression obviously in TLR-triggered macrophages, which in turn suppressed RhoB expression and downstream IL-6 production, suggesting that the inhibition of miR-223 by histone deacetylation may be involved in the regulation of TLR-activated inflammatory response. Herein, our findings suggest that miR-223-RhoB axis might be a novel target for the treatment of inflammatory diseases.