Comprehensive analysis of risk factors for flap necrosis in free flap reconstruction of postoperative tissue defects in oral and maxillofacial tumors.

Free flap reconstruction for postoperative tissue defects in oral and maxillofacial tumors is a critical component of reconstructive surgery. Identifying risk factors for flap necrosis is essential for improving surgical outcomes and patient quality of life. A retrospective study was conducted on patients who underwent free flap reconstruction between January 2020 and December 2023. Patients were included if they had comprehensive medical records and at least a six-month follow-up. We excluded those with a history of flap necrosis, uncontrolled systemic diseases, non-adherence to postoperative care, or concurrent malignancy treatments. Data on demographics, comorbidities, flap characteristics, and operative details were collected and analyzed using univariate analysis and logistic regression tests. Univariate analysis did not find a significant correlation between flap necrosis and factors such as hyperlipidemia, lymph node metastasis, or flap type. However, diabetes mellitus, oral infections, and albumin levels below 35 g/L were significantly associated with flap necrosis. Multivariate logistic regression showed diabetes mellitus increased the odds of flap necrosis by approximately ninefold, and oral infection increased it by over tenfold. Diabetes mellitus, oral infection, and low albumin levels are significant risk factors for flap necrosis in free flap reconstruction after oral and maxillofacial surgery. Prompt identification and management of these factors are crucial to mitigate the risk of flap necrosis.

Janus sponge/electrospun fibre composite combined with EGF/bFGF/CHX promotes reconstruction in oral tissue regeneration.

Guided bone regeneration (GBR) is currently the most widely used bone augmentation technique in oral clinics. However, infection and soft tissue management remain the greatest challenge. In this study, a Janus sponge/electrospun fibre membrane containing epidermal growth factor (EGF), basic fibroblast growth factor (bFGF) and chlorhexidine (CHX) were prepared to optimize its application as a barrier membrane for GBR. The loose sponge part was covalently bonded with the fiber part which has a dense structure. The composed scaffold exhibited superior biocompatibility and antibacterial activity verified by in vitro test. A rat model of unilateral skull bone injury was used to confirm the effectiveness on both hard and soft tissue regeneration. The chitosan sponge on the soft tissue side containing EGF, bFGF and CHX had a loose structure, promoting collagen and cell regeneration and exerting an antibacterial effect. Meanwhile, the dense PLGA/PCL layer on the hard tissue side prevented fibroblast entry into the bone defect, thereby facilitating bone regeneration. The Janus composite scaffold provides a promising strategy for oral tissue restoration.

Clinical outcomes of multidrug-resistant tracheobronchial tuberculosis receiving anti-tuberculosis regimens containing bedaquiline or delamanid.

The treatment of multidrug-resistant tracheobronchial tuberculosis poses challenges, and research investigating the efficacy of bedaquiline or delamanid as treatment for this condition is limited. This retrospective cohort study was conducted from 2017 to 2021. The study extracted data of patients with multidrug-resistant tracheobronchial tuberculosis from medical records and followed up on prognoses. Participants were divided into three groups: the bedaquiline, delamanid, and control group. Clinical outcomes and the risk factors associated with early culture conversion were analyzed. This study included 101 patients, with 32, 25, and 44 patients in the bedaquiline, delamanid, and control groups respectively. The differences in the treatment success rates among the three groups did not show statistical significance. Both the bedaquiline and delamanid groups had significantly higher culture conversion rates compared to the control after 2 or 6 months of treatment, with significantly shorter median times to culture conversion (bedaquiline group: 2 weeks, delamanid group: 2 weeks, control group: 12 weeks, P < 0.001). Treatment with bedaquiline or delamanid were identified as independent predictors of culture conversion at 2 months (bedaquiline group: aOR = 13.417, 95% CI 4.067-44.260, delamanid group: aOR = 9.333, 95% CI 2.498-34.878) or 6 months (bedaquiline group: aOR = 13.333, 95% CI 3.379-52.610, delamanid group: aOR = 5.000, 95% CI 1.357-18.426) of treatment through multivariable logistic regression analyses. The delamanid group showed better improvement in lumen stenosis compared to bedaquiline. Regimens containing bedaquiline or delamanid may accelerate the culture conversion during the early treatment phase in multidrug-resistant tracheobronchial tuberculosis, and delamanid appears to have the potential to effectively improve airway stenosis.

Firefly toxin lucibufagins evolved after the origin of bioluminescence.

Fireflies were believed to originally evolve their novel bioluminescence as warning signals to advertise their toxicity to predators, which was later adopted in adult mating. Although the evolution of bioluminescence has been investigated extensively, the warning signal hypothesis of its origin has not been tested. In this study, we test this hypothesis by systematically determining the presence or absence of firefly toxin lucibufagins (LBGs) across firefly species and inferring the time of origin of LBGs. We confirm the presence of LBGs in the subfamily Lampyrinae, but more importantly, we reveal the absence of LBGs in other lineages, including the subfamilies of Luciolinae, Ototretinae, and Psilocladinae, two incertae sedis lineages, and the Rhagophthalmidae family. Ancestral state reconstructions for LBGs based on firefly phylogeny constructed using genomic data suggest that the presence of LBGs in the common ancestor of the Lampyrinae subfamily is highly supported but unsupported in more ancient nodes, including firefly common ancestors. Our results suggest that firefly LBGs probably evolved much later than the evolution of bioluminescence. We thus conclude that firefly bioluminescence did not originally evolve as direct warning signals for toxic LBGs and advise that future studies should focus on other hypotheses. Moreover, LBG toxins are known to directly target and inhibit the α subunit of Na+, K+-ATPase (ATPα). We further examine the effects of amino acid substitutions in firefly ATPα on its interactions with LBGs. We find that ATPα in LBG-containing fireflies is relatively insensitive to LBGs, which suggests that target-site insensitivity contributes to LBG-containing fireflies' ability to deal with their own toxins.

SurfPro-NN: A 3D point cloud neural network for the scoring of protein-protein docking models based on surfaces features and protein language models.

Protein-protein interactions (PPI) play a crucial role in numerous key biological processes, and the structure of protein complexes provides valuable clues for in-depth exploration of molecular-level biological processes. Protein-protein docking technology is widely used to simulate the spatial structure of proteins. However, there are still challenges in selecting candidate decoys that closely resemble the native structure from protein-protein docking simulations. In this study, we introduce a docking evaluation method based on three-dimensional point cloud neural networks named SurfPro-NN, which represents protein structures as point clouds and learns interaction information from protein interfaces by applying a point cloud neural network. With the continuous advancement of deep learning in the field of biology, a series of knowledge-rich pre-trained models have emerged. We incorporate protein surface representation models and language models into our approach, greatly enhancing feature representation capabilities and achieving superior performance in protein docking model scoring tasks. Through comprehensive testing on public datasets, we find that our method outperforms state-of-the-art deep learning approaches in protein-protein docking model scoring. Not only does it significantly improve performance, but it also greatly accelerates training speed. This study demonstrates the potential of our approach in addressing protein interaction assessment problems, providing strong support for future research and applications in the field of biology.

Association between plasma metal exposure and health span in very elderly adults: a prospective cohort study with mixture statistical approach.

BACKGROUND: Metals have been linked to a diverse spectrum of age-related diseases; however, the effects of metal exposure on health span remains largely unknown. This cohort study aims to determine the association between plasma metal and health span in elder adults aged ≥ 90 years. METHODS: The plasma concentrations of seven metals were measured at baseline in 300 elder adults. The end of the health span (EHS) was identified as the occurrence of one of eight major morbidities or mortality events. We used Cox regression to assess hazard ratios (HR). The combined effects of multiple metal mixtures were estimated using grouped-weighted quantile sum (GWQS), quantile g-computation (Q-gcomp), and Bayesian kernel machine regression (BKMR) methods. RESULTS: The estimated HR for EHS with an inter-quartile range (IQR) increment for selenium (Se) was 0.826 (95% confidence interval [CI]: 0.737-0.926); magnesium (Mg), 0.806 (95% CI: 0.691-0.941); iron (Fe), 0.756 (95% CI: 0.623-0.917), and copper (Cu), 0.856 (95% CI: 0.750-0.976). The P for trend of Se, Mg, and Fe were all < 0.05. In the mixture analyses, Q-gcomp showed a negative correlation with EHS (P = 0.904), with the sum of the negative coefficients being -0.211. CONCLUSION: Higher plasma Se, Mg, and Fe reduced the risk of premature end of health span, suggesting that essential metal elements played a role in health maintenance in elder adults.

Multiconfigurational actinide nitrides assisted by double Möbius aromaticity.

Understanding the bonding nature between actinides and main-group elements remains a key challenge in actinide chemistry due to the involvement of f orbitals. Herein, we propose a unique "aromaticity-assisted multiconfiguration" (AAM) model to elucidate the bonding nature in actinide nitrides (An2N2, An = Ac, Th, Pa, U). Each planar four-membered An2N2 with equivalent An-N bonds possesses four delocalized π electrons and four delocalized σ electrons, forming a new family of double Möbius aromaticity that contributes to the molecular stability. The unprecedented aromaticity further supports actinide nitrides to exhibit multiconfigurational characters, where the unpaired electrons (2, 4 or 6 in naked Th2N2, Pa2N2 or U2N2, respectively) either are spin-free and localized on metal centres or form metal-ligand bonds. High-level multiconfigurational computations confirm an open-shell singlet ground state for actinide nitrides, with small energy gaps to high spin states. This is consistent with the antiferromagnetic nature observed experimentally in uranium nitrides. The novel AAM bonding model can be authenticated in both experimentally identified compounds containing a U2N2 motif and other theoretically modelled An2N2 clusters and is thus expected to be a general chemical bonding pattern between actinides and main-group elements.

Association and mediation between educational attainment and respiratory diseases: a Mendelian randomization study.

BACKGROUND: Respiratory diseases are a major health burden, and educational inequalities may influence disease prevalence. We aim to evaluate the causal link between educational attainment and respiratory disease, and to determine the mediating influence of several known modifiable risk factors. METHODS: We conducted a two-step, two-sample Mendelian randomization (MR) analysis using summary statistics from genome-wide association studies (GWAS) and single nucleotide polymorphisms (SNPs) as instrumental variables for educational attainment and respiratory diseases. Additionally, we performed a multivariable MR analysis to estimate the direct causal effect of each exposure variable included in the analysis on the outcome, conditional on the other exposure variables included in the model. The mediating roles of body mass index (BMI), physical activity, and smoking were also assessed. FINDINGS: MR analyses provide evidence of genetically predicted educational attainment on the risk of FEV1 (ß = 0.10, 95% CI 0.06, 0.14), FVC (ß = 0.12, 95% CI 0.07, 0.16), FEV1/FVC (ß = - 0.005, 95% CI - 0.05, 0.04), lung cancer (OR = 0.54, 95% CI 0.45, 0.65) and asthma (OR = 0.86, 95% CI 0.78, 0.94). Multivariable MR dicated the effect of educational attainment on FEV1 (ß = 0.10, 95% CI 0.04, 0.16), FVC (ß = 0.07, 95% CI 0.01, 0.12), FEV1/FVC (ß = 0.07, 95% CI 0.01, 0.01), lung cancer (OR = 0.55, 95% CI 0.42, 0.71) and asthma (OR = 0.88, 95% CI 0.78, 0.99) persisted after adjusting BMI and cigarettes per day. Of the 23 potential risk factors, BMI, smoking may partially mediate the relationship between education and lung disease. CONCLUSION: High levels of educational attainment have a potential causal protective effect on respiratory diseases. Reducing smoking and adiposity may be a target for the prevention of respiratory diseases attributable to low educational attainment.

Molecular mechanisms of Na+-driven bile acid transport in human NTCP.

Human Na+ taurocholate co-transporting protein (hNTCP) is a key bile salt transporter to maintain enterohepatic circulation and is responsible for the recognition of hepatitis B and D viruses. Despite landmark cryoelectron microscopy studies revealing open-pore and inward-facing states of hNTCP stabilized by antibodies, the transport mechanism remains largely unknown. To address this knowledge gap, we used molecular dynamics and enhanced sampling metadynamics simulations to elucidate the intrinsic mechanism of hNTCP-mediated taurocholate acid (TCA) transport driven by Na+ binding. We uncovered three TCA-binding modes, including one that closely matched the limited cryoelectron microscopy density observed in the open-pore hNTCP. We also captured several key hNTCP conformations in the substrate transport cycle, particularly including an outward-facing, substrate-bound state. Furthermore, we provided thermodynamic evidence supporting that changes in the Na+-binding state drive the TCA transport by exploiting the amphiphilic nature of the substrate and modulating the protein environment, thereby enabling the TCA molecule to flip through. Understanding these mechanistic details of Na+-driven bile acid transport may aid in the development of hNTCP-targeted therapies for liver diseases.

Self-Enhancement of Perfluorinated Sulfonic Acid Proton Exchange Membrane with Its Own Nanofibers.

High-performance proton exchange membrane (PEM) is crucial for the proton exchange membrane fuel cell (PEMFC). Herein, a novel "self-enhanced" PEM is fabricated for the first time, which is composed of perfluorinated sulfonic acid (PFSA) resin and its own nanofibers as reinforcement. With this strategy, the interfacial compatibility issue of conventional fiber-reinforced membranes is fully addressed and up to 80 wt% loading of PFSA nanofibers can be incorporated. Furthermore, on account of chain orientation within the PFSA nanofiber, single fiber exhibits super-high conductivity of 1.45 S cm-1, leading to state-of-the-art proton conductivity (1.1 S cm-1) of the as-prepared "self-enhanced" PEM so far, which is an order of magnitude increase compared with the bulk PFSA membrane (0.29 S cm-1). It surpasses any commercial PEM including the popular GORE-SELECT and Nafion HP membranes and is the only PEM with conductivity at 100 S cm-1 level. In addition, the mechanical strength and swelling ratio of membranes are both substantially improved simultaneously. Based on the high-performance "self-enhanced" PEM, high peak power densities of up to 3.6 W cm-2 and 1.7 W cm-2 are achieved in H2-O2 and H2-Air fuel cells, respectively. This strategy can be applied in any polymeric electrolyte membrane.

Tpgen: a language model for stable protein design with a specific topology structure.

BACKGROUND: Natural proteins occupy a small portion of the protein sequence space, whereas artificial proteins can explore a wider range of possibilities within the sequence space. However, specific requirements may not be met when generating sequences blindly. Research indicates that small proteins have notable advantages, including high stability, accurate resolution prediction, and facile specificity modification. RESULTS: This study involves the construction of a neural network model named TopoProGenerator(TPGen) using a transformer decoder. The model is trained with sequences consisting of a maximum of 65 amino acids. The training process of TopoProGenerator incorporates reinforcement learning and adversarial learning, for fine-tuning. Additionally, it encompasses a stability predictive model trained with a dataset comprising over 200,000 sequences. The results demonstrate that TopoProGenerator is capable of designing stable small protein sequences with specified topology structures. CONCLUSION: TPGen has the ability to generate protein sequences that fold into the specified topology, and the pretraining and fine-tuning methods proposed in this study can serve as a framework for designing various types of proteins.

Mechanical Metamaterials for Handwritten Digits Recognition.

The increasing needs for new types of computing lie in the requirements in harsh environments. In this study, the successful development of a non-electrical neural network is presented that functions based on mechanical computing. By overcoming the challenges of low mechanical signal transmission efficiency and intricate layout design methodologies, a mechanical neural network based on bistable kirigami-based mechanical metamaterials have designed. In preliminary tests, the system exhibits high reliability in recognizing handwritten digits and proves operable in low-temperature environments. This work paves the way for a new, alternative computing system with broad applications in areas where electricity is not accessible. By integrating with the traditional electronic computers, the present system lays the foundation for a more diversified form of computing.

Epidemiological characteristics of HIV transmission in southeastern China from 2015 to 2020 based on HIV molecular network.

Objective: HIV/AIDS remains a global public health problem, and understanding the structure of social networks of people living with HIV/AIDS is of great importance to unravel HIV transmission, propose precision control and reduce new infections. This study aimed to investigate the epidemiological characteristics of HIV transmission in Fujian province, southeastern China from 2015 to 2020 based on HIV molecular network. Methods: Newly diagnosed, treatment-naive HIV/AIDS patients were randomly sampled from Fujian province in 2015 and 2020. Plasma was sampled for in-house genotyping resistance test, and HIV molecular network was created using the HIV-TRACE tool. Factors affecting the inclusion of variables in the HIV molecular network were identified using univariate and multivariate logistic regression analyses. Results: A total of 1,714 eligible cases were finally recruited, including 806 cases in 2015 and 908 cases in 2020. The dominant HIV subtypes were CRF01_AE (41.7%) and CRF07_BC (38.3%) in 2015 and CRF07_BC (53. 3%) and CRF01_AE (29.1%) in 2020, and the prevalence of HIV drug resistance was 4.2% in 2015 and 5.3% in 2020. Sequences of CRF07_BC formed the largest HIV-1 transmission cluster at a genetic distance threshold of both 1.5 and 0.5%. Univariate and multivariate logistic regression analyses showed that ages of under 20 years and over 60 years, CRF07_BC subtype, Han ethnicity, sampling in 2015, absence of HIV drug resistance, married with spouse, sampling from three cities of Jinjiang, Nanping and Quanzhou resulted in higher proportions of sequences included in the HIV transmission molecular network at a genetic distance threshold of 1.5% (p < 0.05). Conclusion: Our findings unravel the HIV molecular transmission network of newly diagnosed HIV/AIDS patients in Fujian province, southeastern China, which facilitates the understanding of HIV transmission patterns in the province.

A 2-step prediction model for diagnosis of germinomas in the pineal region.

Background: Germinomas are sensitive to radiation and chemotherapy, and their management distinctly differs from other kinds of pineal region tumors. The aim of this study was to construct a prediction model based on clinical features and preoperative magnetic resonance (MR) manifestations to achieve noninvasive diagnosis of germinomas in pineal region. Methods: A total of 126 patients with pineal region tumors were enrolled, including 36 germinomas, 53 nongerminomatous germ cell tumors (NGGCTs), and 37 pineal parenchymal tumors (PPTs). They were divided into a training cohort (n = 90) and a validation cohort (n = 36). Features were extracted from clinical records and conventional MR images. Multivariate analysis was performed to screen for independent predictors to differentiate germ cell tumors (GCTs) and PPTs, germinomas, and NGGCTs, respectively. From this, a 2-step nomogram model was established, with model 1 for discriminating GCTs from PPTs and model 2 for identifying germinomas in GCTs. The model was tested in a validation cohort. Results: Both model 1 and model 2 yielded good predictive efficacy, with c-indexes of 0.967 and 0.896 for the diagnosis of GCT and germinoma, respectively. Calibration curve, decision curve, and clinical impact curve analysis further confirmed their predictive accuracy and clinical usefulness. The validation cohort achieved areas under the receiver operating curves of 0.885 and 0.926, respectively. Conclusions: The 2-step model in this study can noninvasively differentiate GCTs from PPTs and further identify germinomas, thus holding potential to facilitate treatment decision-making for pineal region tumors.

Physics-supervised deep learning-based optimization (PSDLO) with accuracy and efficiency.

Identifying efficient and accurate optimization algorithms is a long-desired goal for the scientific community. At present, a combination of evolutionary and deep-learning methods is widely used for optimization. In this paper, we demonstrate three cases involving different physics and conclude that no matter how accurate a deep-learning model is for a single, specific problem, a simple combination of evolutionary and deep-learning methods cannot achieve the desired optimization because of the intrinsic nature of the evolutionary method. We begin by using a physics-supervised deep-learning optimization algorithm (PSDLO) to supervise the results from the deep-learning model. We then intervene in the evolutionary process to eventually achieve simultaneous accuracy and efficiency. PSDLO is successfully demonstrated using both sufficient and insufficient datasets. PSDLO offers a perspective for solving optimization problems and can tackle complex science and engineering problems having many features. This approach to optimization algorithms holds tremendous potential for application in real-world engineering domains.

Association of ambient PM10 and PM2.5 with coronary stenosis measured using selective coronary angiography.

BACKGROUND: Long-term ambient particulate matter (PM) exposure exerts detrimental effects on cardiovascular health. Evidence on the relation of chronically exposed ambient PM10 and PM2.5 with coronary stenosis remains lacking. Our aim was to investigate the association of PM10 and PM2.5 with coronary stenosis in patients undergoing coronary angiography. METHODS: We performed a retrospective cohort study consisting of 7513 individuals who underwent coronary angiography in Fujian Province, China, from January 2019 to December 2021. We calculated a modified Gensini score (GS) to represent the degree of stenosis in coronary arteries by selective coronary angiography. We fitted linear regressions and logistic models to assess the association of PM10 and PM2.5 with coronary stenosis. We employed restricted cubic splines to describe the exposure-response curves. We performed mediation analyses to assess the potential mediators. RESULTS: Long-term ambient PM10 and PM2.5 (prior three years average) exposure was significantly associated with the GS, with a breakpoint concentration of 47.5 µg/m3 and 25.8 µg/m3 for PM10 and PM2.5, respectively, above which we found a linear positive exposure-response relationship of ambient PM with GS. Each 10 µg /m3 increase in PM10 exposure (ß: 4.81, 95 % CI: 0.44-9.19) and PM2.5 exposure [ß: 10.50, 95 % CI: 3.14-17.86] were positively related to the GS. The adjusted odds ratio (OR) for each 10 µg/m3 increment in PM10 exposure on severe coronary stenosis was 1.33 (95 % CI: 1.04-1.76). Correspondingly, the adjusted OR for PM2.5 was 1.87 (95 % CI: 1.24-2.99). The mediation analysis indicated that the effect of PM10 on coronary stenosis may be partially mediated through total cholesterol, low-density lipoprotein cholesterol, apolipoprotein B, serum creatinine and blood urea nitrogen, and the effect of PM2.5 may be mediated in part by hemoglobin A1c. CONCLUSION: Our study provides the first evidence that chronic ambient PM10 and PM2.5 exposure was associated with coronary stenosis assessed by GS in patients with suspected coronary artery disease and reveals its potential mediators.

Differences in epidemiological and clinical features between adult and pediatric tracheobronchial tuberculosis patients in Southwest China.

Background: Tracheobronchial tuberculosis (TBTB) is a common form of extrapulmonary tuberculosis that affects the tracheobronchial tree. However, the mechanism has not been fully elucidated. Comparisons of clinical characteristics in various age groups can aid in the understanding of TBTB. Methods: This retrospective study was conducted at the Public Health Clinical Center of Chengdu between July 2017 and December 2021, including adults and children with TBTB. Clinical data were extracted from medical records. T/T' test, Mann-Whitney U test, Chi-square test, or Fisher's exact test were used in this study. Results: This study enrolled 347 patients with TBTB (175 adults and 172 children). Adult females were more susceptible to TBTB, whereas gender-based differences were not observed in children. Children had a higher occurrence of irritant dry cough and fever, and acute hematogenous disseminated PTB, and specific types of EPTB, but a shorter interval before diagnosis, and lower diagnostic yields compared to adults (P < 0.05). Adults presented more extensive lung lesions and cavitations as compared to children. Granulation hyperplasia and lymph fistula were more frequently observed in children, as well as airway stenosis, but less severe. Conclusions: The study revealed important variations exist in multiple respects between adults and children with TBTB.

Xuebijing injection protects sepsis induced myocardial injury by mediating TLR4/NF-κB/IKKα and JAK2/STAT3 signaling pathways.

OBJECTIVE: Compelling evidence has demonstrated that Xuebijing (XBJ) exerted protective effects against SIMI. The aims of this study were to investigate whether TLR4/IKKα-mediated NF-κB and JAK2/STAT3 pathways were involved in XBJ's cardio-protection during sepsis and the mechanisms. METHODS: In this study, rats were randomly assigned to three groups: Sham group; CLP group; XBJ group. Rats were treated with XBJ or sanitary saline after CLP. Echocardiography, myocardial enzymes and HE were used to detect cardiac function. IL-1ß, IL-6 and TNF-α in serum were measured using ELISA kits. Cardiomyocyte apoptosis were tested by TUNEL staining. The protein levels of Bax, Bcl-2, Bcl-xl, Cleaved-Caspase 3, Cleaved-Caspase 9, Cleaved-PARP, TLR4, p-NF-κB, p-IKKα, p-JAK2 and p-STAT3 in the myocardium were assayed by western blotting. And finally, immunofluorescence was used to assess the level of p-JAK2 and p-STAT3 in heart tissue. RESULTS: The results of echocardiography, myocardial enzyme and HE test showed that XBJ could significantly improve SIMI. The IL-1ß, IL-6 and TNF-α levels in the serum were markedly lower in the XBJ group than in the CLP group (p<0.05). TUNEL staining's results showed that XBJ ameliorated CLP-induced cardiomyocyte apoptosis. Meanwhile, XBJ downregulated the protein levels of Bax, Cleaved-Caspase 3, Cleaved-Caspase 9, Cleaved-PARP, TLR4, p-NF-κB, p-IKKα, p-JAK2 and p-STAT3, as well as upregulated the protein levels of Bcl-2, Bcl-xl (p <0.05). CONCLUSIONS: In here, we observed that XBJ's cardioprotective advantages may be attributable to its ability to suppress inflammation and apoptosis via inhibiting the TLR4/ IKKα-mediated NF-κB and JAK2/STAT3 pathways during sepsis.