A new paradigm for applying deep learning to protein-ligand interaction prediction.

Protein-ligand interaction prediction presents a significant challenge in drug design. Numerous machine learning and deep learning (DL) models have been developed to accurately identify docking poses of ligands and active compounds against specific targets. However, current models often suffer from inadequate accuracy or lack practical physical significance in their scoring systems. In this research paper, we introduce IGModel, a novel approach that utilizes the geometric information of protein-ligand complexes as input for predicting the root mean square deviation of docking poses and the binding strength (pKd, the negative value of the logarithm of binding affinity) within the same prediction framework. This ensures that the output scores carry intuitive meaning. We extensively evaluate the performance of IGModel on various docking power test sets, including the CASF-2016 benchmark, PDBbind-CrossDocked-Core and DISCO set, consistently achieving state-of-the-art accuracies. Furthermore, we assess IGModel's generalizability and robustness by evaluating it on unbiased test sets and sets containing target structures generated by AlphaFold2. The exceptional performance of IGModel on these sets demonstrates its efficacy. Additionally, we visualize the latent space of protein-ligand interactions encoded by IGModel and conduct interpretability analysis, providing valuable insights. This study presents a novel framework for DL-based prediction of protein-ligand interactions, contributing to the advancement of this field. The IGModel is available at GitHub repository https://github.com/zchwang/IGModel.

A fully differentiable ligand pose optimization framework guided by deep learning and a traditional scoring function.

The recently reported machine learning- or deep learning-based scoring functions (SFs) have shown exciting performance in predicting protein-ligand binding affinities with fruitful application prospects. However, the differentiation between highly similar ligand conformations, including the native binding pose (the global energy minimum state), remains challenging that could greatly enhance the docking. In this work, we propose a fully differentiable, end-to-end framework for ligand pose optimization based on a hybrid SF called DeepRMSD+Vina combined with a multi-layer perceptron (DeepRMSD) and the traditional AutoDock Vina SF. The DeepRMSD+Vina, which combines (1) the root mean square deviation (RMSD) of the docking pose with respect to the native pose and (2) the AutoDock Vina score, is fully differentiable; thus is capable of optimizing the ligand binding pose to the energy-lowest conformation. Evaluated by the CASF-2016 docking power dataset, the DeepRMSD+Vina reaches a success rate of 94.4%, which outperforms most reported SFs to date. We evaluated the ligand conformation optimization framework in practical molecular docking scenarios (redocking and cross-docking tasks), revealing the high potentialities of this framework in drug design and discovery. Structural analysis shows that this framework has the ability to identify key physical interactions in protein-ligand binding, such as hydrogen-bonding. Our work provides a paradigm for optimizing ligand conformations based on deep learning algorithms. The DeepRMSD+Vina model and the optimization framework are available at GitHub repository https://github.com/zchwang/DeepRMSD-Vina_Optimization.

Improving protein-ligand docking and screening accuracies by incorporating a scoring function correction term.

Scoring functions are important components in molecular docking for structure-based drug discovery. Traditional scoring functions, generally empirical- or force field-based, are robust and have proven to be useful for identifying hits and lead optimizations. Although multiple highly accurate deep learning- or machine learning-based scoring functions have been developed, their direct applications for docking and screening are limited. We describe a novel strategy to develop a reliable protein-ligand scoring function by augmenting the traditional scoring function Vina score using a correction term (OnionNet-SFCT). The correction term is developed based on an AdaBoost random forest model, utilizing multiple layers of contacts formed between protein residues and ligand atoms. In addition to the Vina score, the model considerably enhances the AutoDock Vina prediction abilities for docking and screening tasks based on different benchmarks (such as cross-docking dataset, CASF-2016, DUD-E and DUD-AD). Furthermore, our model could be combined with multiple docking applications to increase pose selection accuracies and screening abilities, indicating its wide usage for structure-based drug discoveries. Furthermore, in a reverse practice, the combined scoring strategy successfully identified multiple known receptors of a plant hormone. To summarize, the results show that the combination of data-driven model (OnionNet-SFCT) and empirical scoring function (Vina score) is a good scoring strategy that could be useful for structure-based drug discoveries and potentially target fishing in future.

Preparation and immunogenicity evaluation of C-HapS-P6 fusion protein vaccine against nontypeable Haemophilus influenzae in mice.

Nontypeable Haemophilus influenzae (NTHi) is the dominant pathogen in several infectious diseases. Currently the use of antibiotics is the main intervention to prevent NTHi infections, however with the emergence of drug resistant strains, it has compromised the treatment of respiratory infections with antibiotics. Therefore there is an urgent need to develop a safe and effective vaccine to prevent NTHi infections. We investigate the potential of C-HapS-P6 fusion protein as a vaccine for treating NTHi in murine models. PGEX-6P2/C-HapS-P6 fusion gene was constructed using overlap extension polymerase chain reaction. The recombined plasmid was transformed into Escherichia coli for protein expression. The mice were subjected to intraperitoneal immunization using purified antigens. Immunoglobulin (Ig) G in serum samples and IgA in nasal and lung lavage fluids were analyzed using enzyme-linked immunosorbent assay. Cytokine release and proliferation capacity of splenic lymphocytes in response to antigens were measured in vitro. The protective effect of the C-HapS-P6 protein against NTHi infection was evaluated by NTHi count and histological examination. The data showed that the C-HapS-P6 fusion protein increased significantly the levels of serum IgG and nasal and lung IgA, and promoted the release of interleukin (IL)-2, interferon-ϒ, IL-4, IL-5, and IL-17 and the proliferation of splenic lymphocytes compared with C-HapS or P6 protein treatment alone. Moreover, C-HapS-P6 effectively reduced the NTHi colonization in the nasopharynx and lungs of mice. In conclusion, our results demonstrated that the C-HapS-P6 fusion protein vaccine can significantly enhance humoral and cell immune responses and effectively prevent against NTHi infection in the respiratory tract in murine models.

Tectoridin alleviates caerulein-induced severe acute pancreatitis by targeting ERK2 to promote macrophage M2 polarization.

Severe acute pancreatitis (SAP) is an inflammatory disease of the pancreas with a high mortality rate. Macrophages play a crucial role in the pathogenesis of pancreatitis. Tectoridin (Tec) is a highly active isoflavone with anti-inflammatory pharmacological activity. However, the role of Tec in the SAP process is not known. The purpose of this study was to investigate the therapeutic effect and potential mechanism of Tec on SAP. To establish SAP mice by intraperitoneal injection of caerulein and Lipopolysaccharide (LPS), the role of Tec in the course of SAP was investigated based on histopathology, biochemical indicators of amylase and lipase and inflammatory factors. The relationship between Tec and macrophage polarization was verified by immunofluorescence, real-time quantitative PCR and Western blot analysis. We then further predicted the possible targets and signal pathways of action of Tec by network pharmacology and molecular docking, and validated them by in vivo and in vitro. In this study, we demonstrated that Tec significantly reduced pancreatic injury in SAP mice, and decreased serum levels of amylase and lipase. The immunofluorescence and Western blot analysis showed that Tec promoted macrophage M2 polarization. Network pharmacology and molecular docking predicted that Tec may target ERK2 for the treatment of SAP, and in vivo and in vitro experiments proved that Tec inhibited the ERK MAPK signal pathway. In summary, Tec can target ERK2, promote macrophage M2 polarization and attenuate pancreatic injury, Tec may be a potential drug for the treatment of SAP.

Downregulation of ALKBH5 rejuvenates aged human mesenchymal stem cells and enhances their therapeutic efficacy in myocardial infarction.

Despite promising results in myocardial infarction (MI), mesenchymal stem cell (MSC)-based therapy is limited by cell senescence. N6-methyladenosine (m6A) messenger RNA methylation has been reported to be closely associated with cell senescence. Nonetheless, its role in the regulation of MSC senescence remains unclear. We examined the role of ALKB homolog 5 (ALKBH5) in regulating MSC senescence and determined whether ALKBH5 downregulation could rejuvenate aged MSCs (AMSCs) to improve their therapeutic efficacy for MI. RNA methylation was determined by m6A dot blotting assay. MSC senescence was evaluated by senescence-associated ß-galactosidase (SA-ß-gal) staining. A mouse model of acute MI was established by ligation of the left anterior decedent coronary artery (LAD). Compared with young MSCs (YMSCs), m6A level was significantly reduced but ALKBH5 was greatly increased in AMSCs. Overexpression of ALKBH5 reduced m6A modification and accelerated YMSC senescence. Conversely, ALKBH5 knockdown increased m6A modifications and alleviated AMSC senescence. Mechanistically, ALKBH5 regulated the m6A modification and stability of CDKN1C mRNA, which further upregulated CDKN1C expression, leading to MSC senescence. CDKN1C overexpression ameliorated the inhibition of cellular senescence of ALKBH5 siRNA-treated AMSCs. More importantly, compared with AMSCs, shALKBH5-AMSCs transplantation provided a superior cardioprotective effect against MI in mice by improving MSC survival and angiogenesis. We determined that ALKBH5 accelerated MSC senescence through m6A modification-dependent stabilization of the CDKN1C transcript, providing a potential target for MSC rejuvenation. ALKBH5 knockdown rejuvenated AMSCs and enhanced cardiac function when transplanted into the mouse heart following infarction.

Current Advances of CO Sensing Based on Low Dimensional Materials.

Carbon monoxide (CO) is a harmful gas with significant impacts on human health and the environment. Its timely detection, especially in the event of thermal runaway in automotive lithium batteries, is crucial to prevent casualties. This paper reviews the progress in the development of efficient, sensitive, and reliable CO sensors, focusing on electrochemical, optical, and resistive sensing materials. Low-dimensional materials have a large specific surface area, providing an abundant number of active sites, which has drawn extensive attention from researchers. According to the different sensor signals, we categorized these sensors into electrical and optical signal sensors. We hope that by systematically introducing the sensing mechanism and sensing performance of these two kinds of sensors, appropriate CO sensors can be developed in different application scenarios so as to realize early warning and monitoring to the maximum extent, reduce industrial losses, and ensure the life and health of personnel.

Risk factors for pre-transplantation bacteremia in adults with end-stage liver disease: Effects on outcomes of liver transplantation.

BACKGROUND AND AIM: Limited data are available regarding pre-liver transplantation (LT) bacteremia in adults with end-stage liver disease. In this study, we investigated the risk factors independently associated with pre-LT bacteremia and their effects on clinical outcomes of LT. METHODS: This retrospective study performed between 2010 and 2021 included 1287 LT recipients. The study population was categorized into patients with pre-LT bacteremia and those without pre-LT infection. Pre-LT bacteremia was defined as bacteremia detected within 90 days before LT. RESULTS: Among 1287 LT recipients, 92 (7.1%) developed pre-LT bacteremia. The mean interval between bacteremia and LT was 28.3 ± 19.5 days. Of these 92 patients, seven (7.6%) patients died after LT. Of the 99 microorganisms isolated in this study, gram-negative bacteria were the most common microbes (72.7%). Bacteremia was mainly attributed to spontaneous bacterial peritonitis. The most common pathogen isolated was Escherichia coli (25.2%), followed by Klebsiella pneumoniae (18.2%), and Staphylococcus aureus (15.1%). Multivariate analysis showed that massive ascites (adjusted odds ratio [OR] 1.67, 95% confidence Interval [CI] 1.048-2.687) and a prolonged international normalized ratio for prothrombin time (adjusted OR 1.13, 95% CI 1.074-1.257) were independent risk factors for pre-LT bacteremia in patients with end-stage liver disease. Intensive care unit and in-hospital stay were significantly longer, and in-hospital mortality was significantly higher among LT recipients with pre-LT bacteremia than among those without pre-LT infection. CONCLUSIONS: This study highlights predictors of pre-LT bacteremia in patients with end-stage liver disease. Pre-LT bacteremia increases the post-transplantation mortality risk.

Fully Flexible Molecular Alignment Enables Accurate Ligand Structure Modeling.

Accurate protein-ligand binding poses are the prerequisites of structure-based binding affinity prediction and provide the structural basis for in-depth lead optimization in small molecule drug design. However, it is challenging to provide reasonable predictions of binding poses for different molecules due to the complexity and diversity of the chemical space of small molecules. Similarity-based molecular alignment techniques can effectively narrow the search range, as structurally similar molecules are likely to have similar binding modes, with higher similarity usually correlated to higher success rates. However, molecular similarity is not consistently high because molecules often require changes to achieve specific purposes, leading to reduced alignment precision. To address this issue, we propose a new alignment method─Z-align. This method uses topological structural information as a criterion for evaluating similarity, reducing the reliance on molecular fingerprint similarity. Our method has achieved success rates significantly higher than those of other methods at moderate levels of similarity. Additionally, our approach can comprehensively and flexibly optimize bond lengths and angles of molecules, maintaining a high accuracy even when dealing with larger molecules. Consequently, our proposed solution helps in achieving more accurate binding poses in protein-ligand docking problems, facilitating the development of small molecule drugs. Z-align is freely available as a web server at https://cloud.zelixir.com/zalign/home.

Britannin as a novel NLRP3 inhibitor, suppresses inflammasome activation in macrophages and alleviates NLRP3-related diseases in mice.

Overactivation of the NLRP3 inflammasomes induces production of pro-inflammatory cytokines and drives pathological processes. Pharmacological inhibition of NLRP3 is an explicit strategy for the treatment of inflammatory diseases. Thus far no drug specifically targeting NLRP3 has been approved by the FDA for clinical use. This study was aimed to discover novel NLRP3 inhibitors that could suppress NLRP3-mediated pyroptosis. We screened 95 natural products from our in-house library for their inhibitory activity on IL-1ß secretion in LPS + ATP-challenged BMDMs, found that Britannin exerted the most potent inhibitory effect with an IC50 value of 3.630 µM. We showed that Britannin (1, 5, 10 µM) dose-dependently inhibited secretion of the cleaved Caspase-1 (p20) and the mature IL-1ß, and suppressed NLRP3-mediated pyroptosis in both murine and human macrophages. We demonstrated that Britannin specifically inhibited the activation step of NLRP3 inflammasome in BMDMs via interrupting the assembly step, especially the interaction between NLRP3 and NEK7. We revealed that Britannin directly bound to NLRP3 NACHT domain at Arg335 and Gly271. Moreover, Britannin suppressed NLRP3 activation in an ATPase-independent way, suggesting it as a lead compound for design and development of novel NLRP3 inhibitors. In mouse models of MSU-induced gouty arthritis and LPS-induced acute lung injury (ALI), administration of Britannin (20 mg/kg, i.p.) significantly alleviated NLRP3-mediated inflammation; the therapeutic effects of Britannin were dismissed by NLRP3 knockout. In conclusion, Britannin is an effective natural NLRP3 inhibitor and a potential lead compound for the development of drugs targeting NLRP3.

Identifying symptom clusters and temporal interconnections in patients with lung tumors after CT-guided microwave ablation: A network analysis.

PURPOSE: To explore symptom clusters and interrelationships using a network analysis approach among symptoms in patients with lung tumors who underwent computed tomography (CT)-guided microwave ablation (MWA). METHODS: A longitudinal study was conducted, and 196 lung tumor patients undergoing MWA were recruited and were measured at 24 h, 48 h, and 72 h after MWA. The Chinese version of the MD Anderson Symptom Inventory and the Revised Lung Cancer Module were used to evaluate symptoms. Network analyses were performed to explore the symptom clusters and interrelationships among symptoms. RESULTS: Four stable symptom communities were identified within the networks. Distress, weight loss, and chest tightness were the central symptoms. Distress, and weight loss were also the most key bridge symptoms, followed by cough. Three symptom networks were temporally stable in terms of symptom centrality, global connectivity, and network structure. CONCLUSION: Our findings identified the central symptoms, bridge symptoms, and the stability of symptom networks of patients with lung tumors after MWA. These network results will have important implications for future targeted symptom management intervention development. Future research should focus on developing precise interventions for targeting central symptoms and bridge symptoms to promote patients' health.

The inhibitory impact of Schisandrin on inflammation and oxidative stress alleviates LPS-induced acute kidney injury.

Inflammation and oxidative stress (OS) are the major pathogenic characteristics of acute kidney injury (AKI). Studies have shown that Schisandrin (Sch) could regulate inflammatory disease. However, the function and mechanism of Sch in AKI progression are still unknown. Here, we investigated Sch's potential effects and mechanism on mice's renal damage and macrophages induced by lipopolysaccharide (LPS). Sch decreased LPS-induced inflammatory factor production while increasing the activity of related antioxidant enzymes in macrophages and mouse kidney tissues. Hematoxylin and eosin staining revealed that Sch may have the ability to profoundly inhibit inflammatory cell invasion and tissue damage caused by LPS in renal tissue. Furthermore, Western blot and immunohistochemical studies showed that Sch exerted its effects mainly through up-regulation of nuclear factor erythroid 2-related factor 2/heme oxygenase-1 and inhibition of Toll-like receptor 4‒mitogen-activated protein kinases/nuclear factor-kappa B pathways. Collectively, this study illustrates that Sch suppresses LPS-stimulated AKI by descending inflammation and OS, illuminating prospective AKI treatment options.

Breastfeeding and risk of food allergy and allergic rhinitis in offspring: a systematic review and meta-analysis of cohort studies.

The association between breastfeeding and the occurrence of allergic rhinitis (AR) and food allergy (FA) in offspring remains inconclusive. This review aims to comprehensively explore the potential relationships between various patterns and durations of breastfeeding and allergic diseases in offspring. We systematically searched PubMed, EMBASE, Cochrane, WOS databases, and Google Scholar for observational studies published up to March 30, 2023, that investigated the link between breastfeeding and allergies in offspring. The quality of the studies was assessed using the Newcastle-Ottawa Scale (NOS) and Joanna Briggs Institute (JBI). Pooled odds ratios (OR) and 95% confidence intervals (95% CI) were calculated employing an appropriate model based on the degree of heterogeneity. A total of 68 studies, encompassing 772,142 children, were ultimately included. The findings indicated that breastfeeding for more than 6 months was associated with a reduced risk of AR (OR = 0.88, 95% CI: 0.79 to 0.98) but posed a risk for FA (OR = 1.69, 95% CI: 1.27 to 2.25). Exclusive breastfeeding exhibited a protective effect against AR (OR = 0.94, 95% CI: 0.90 to 0.97), whereas non-breastfeeding was identified as a risk factor for AR (OR = 1.48; 95% CI: 1.03 to 2.12). No significant association was observed between breastfeeding patterns and FA. CONCLUSION: Breastfeeding for more than 6 months proves to be an effective preventive measure against AR. However, large prospective high-quality studies are needed to investigate the potential risk of FA in children with prolonged breastfeeding. WHAT IS KNOWN: • The impact of breastfeeding on allergic rhinitis and food allergy in offspring is controversial. • Previous meta-analyses fail to prove the effect of breastfeeding on food allergy in offspring of all ages. WHAT IS NEW: • Breastfeeding for more than 6 months proves to be an effective preventive measure against AR. However, it potentially elevates the risk of FA in children. Non-breastfeeding is linked to an increased risk of AR in children, but there is no evidence of an association between breastfeeding patterns and FA in children. • The impact of breastfeeding on allergic rhinitis and food allergy in offspring may vary with the time and pattern of breastfeeding.

Exosomal miR-9-5p derived from iPSC-MSCs ameliorates doxorubicin-induced cardiomyopathy by inhibiting cardiomyocyte senescence.

Doxorubicin (DOX) is a chemotherapeutic agent widely used for tumor treatment. Nonetheless its clinical application is heavily limited by its cardiotoxicity. There is accumulated evidence that transplantation of mesenchymal stem cell-derived exosomes (MSC-EXOs) can protect against Dox-induced cardiomyopathy (DIC). This study aimed to examine the cardioprotective effects of EXOs isolated from human induced pluripotent stem cell-derived MSCs (iPSC-MSCs) against DIC and explore the potential mechanisms. EXOs were isolated from the cultural supernatant of human BM-MSCs (BM-MSC-EXOs) and iPSC-MSCs (iPSC-MSC-EXOs) by ultracentrifugation. A mouse model of DIC was induced by intraperitoneal injection of Dox followed by tail vein injection of PBS, BM-MSC-EXOs, or iPSC-MSC-EXOs. Cardiac function, cardiomyocyte senescence and mitochondrial dynamics in each group were assessed. In vitro, neonatal mouse cardiomyocytes (NMCMs) were subjected to Dox and treated with BM-MSC-EXOs or iPSC-MSC-EXOs. The mitochondrial morphology and cellular senescence of NMCMs were examined by Mitotracker staining and senescence-associated-ß-galactosidase assay, respectively. Compared with BM-MSC-EXOs, mice treated with iPSC-MSC-EXOs displayed improved cardiac function and decreased cardiomyocyte mitochondrial fragmentation and senescence. In vitro, iPSC-MSC-EXOs were superior to BM-MSC-EXOs in attenuation of cardiomyocyte mitochondrial fragmentation and senescence caused by DOX. MicroRNA sequencing revealed a higher level of miR-9-5p in iPSC-MSC-EXOs than BM-MSC-EXOs. Mechanistically, iPSC-MSC-EXOs transported miR-9-5p into DOX-treated cardiomyocytes, thereby suppressing cardiomyocyte mitochondrial fragmentation and senescence via regulation of the VPO1/ERK signal pathway. These protective effects and cardioprotection against DIC were largely reversed by knockdown of miR-9-5p in iPSC-MSC-EXOs. Our results showed that miR-9-5p transferred by iPSC-MSC-EXOs protected against DIC by alleviating cardiomyocyte senescence via inhibition of the VPO1/ERK pathway. This study offers new insight into the application of iPSC-MSC-EXOs as a novel therapeutic strategy for DIC treatment.

A simple model to predict early recurrence of hepatocellular carcinoma after liver resection.

PURPOSE: Multiple studies have reported models for predicting early recurrence of hepatocellular carcinoma (HCC) after liver resection (LR). However, these models are too complex to use in daily practice. We aimed to develop a simple model. METHOD: We enrolled 1133 patients with newly diagnosed HCC undergoing LR. The Kaplan - Meier method and log-rank test were used for survival analysis and Cox proportional hazards analysis to identify prognostic factors associated with early recurrence (i.e., recurrence within two years after LR). RESULTS: Early recurrence was identified in 403 (35.1%) patients. In multivariate analysis, alpha-fetoprotein (AFP) 20-399 vs. < 20 ng/ml (HR = 1.282 [95% confidence interval = 1.002-1.639]; p = 0.048); AFP ≥ 400 vs. < 20 ng/ml (HR = 1.755 [1.382-2.229]; p < 0.001); 7th edition American Joint Committee on Cancer (AJCC) stage 2 vs. 1 (HR = 1.958 [1.505-2.547]; p < 0.001); AJCC stage 3 vs. 1 (HR = 4.099 [3.043-5.520]; p < 0.001); and pathology-defined cirrhosis (HR = 1.46 [1.200-1.775]; p < 0.001) were associated with early recurrence. We constructed a predictive model with these variables, which provided three risk strata for recurrence-free survival (RFS): low risk, intermediate risk, and high risk, with two-year RFS of 79%, 57%, and 35%, respectively (p < 0.001). CONCLUSION: We developed a simple model to predict early recurrence risk for patients undergoing LR for HCC.

Anti-inflammatory effect of proanthocyanidins from blueberry through NF-κß/NLRP3 signaling pathway in vivo and in vitro.

BACKGROUND: Systemic inflammatory response syndrome (SIRS) is an uncontrolled systemic inflammatory response. Proanthocyanidins (PC) is a general term of polyphenol compounds widely existed in blueberry fruits and can treat inflammation-related diseases. This study aimed to explore the regulatory effect of PC on lipopolysaccharide (LPS)-induced systemic inflammation and its potential mechanism, providing effective strategies for the further development of PC. METHODS: Here, RAW264.7 macrophages were stimulated with LPS to establish an inflammation model in vitro, while endotoxin shock mouse models were constructed by LPS in vivo. The function of PC was investigated by MTT, ELISA kits, H&E staining, immunohistochemistry, and Western blot analysis. RESULTS: Functionally, PC could demonstrate the potential to mitigate mortality in mice with endotoxin shock, as well as attenuated the levels of inflammatory cytokines (IL-6, TNF-α) and biochemical indicators (AST, ALT, CRE and BUN). Moreover, it had a significant protective effect on lung and kidney tissues damage. Mechanistically, PC exerted anti-inflammatory effects by inhibiting the activation of the NF-κB/NLRP3 signaling pathway. CONCLUSION: PC might have the potential ability of anti-inflammatory effects via modulation of the NF-κB/NLRP3 signaling pathway.

The impact of preoperative nutritional status on postoperative outcomes: an insight from Geriatric Nutritional Risk Index in elderly pancreaticoduodenectomy patients.

BACKGROUND: Malnutrition is not uncommon among the elderly undergoing pancreatoduodenectomy (PD) and is related to increased complications. Previous studies have shown that the Geriatric Nutritional Risk Index (GNRI) predicts outcomes in various populations. Nevertheless, the research exploring the correlation between GNRI and postoperative outcomes in PD is scarce. This study aimed to investigate the preoperative malnutrition, as measured by GNRI, on outcomes in elderly patients undergoing PD. MATERIALS AND METHODS: This retrospective analysis enrolled 144 elderly patients underwent PD for periampullary tumors from November 2016 to December 2021. Patients were stratified based on the GNRI value: high/moderate nutrition risk (GNRI ≤ 92, N = 54), low nutrition risk (92 < GNRI ≤ 98, N = 35), and no nutrition risk (GNRI > 98, N = 55). Perioperative outcomes and postoperative surgical complications were compared between these groups. Univariate and multivariate analyses were performed on major postoperative complications and prolonged postoperative length of stay (PLOS). RESULTS: Patients in the high/moderate risk group were significantly older, with lower BMI (P = 0.012), higher mortality rate (11.1%, P = 0.024), longer PLOS (P < 0.001), and higher incidence of over grade IIIB complications (37.0%, P = 0.001), Univariate and multivariate analyses showed the high/moderate risk GNRI group (OR 3.61, P = 0.032), increased age (OR 1.11, P = 0.014) and operative time over 8 h (OR 3.04, P = 0.027) were significantly associated with increased major postoperative complications. The high/moderate risk GNRI group was also a significant predictor for prolonged PLOS (OR 3.91, P = 0.002). CONCLUSIONS: Preoperative GNRI has the potential to be a predictive tool for identifying high-risk elderly patients and monitoring nutritional status preoperatively to improve postoperative surgical outcomes following PD.

Nomogram for predicting postoperative deep vein thrombosis in patients with spinal fractures caused by high-energy injuries.

OBJECTIVE: Deep venous thrombosis (DVT) is a common complication in patients with spinal fractures caused by high-energy injuries. Early identification of patients at high risk of postoperative DVT is essential for the prevention of thrombosis. This study aimed to develop and validate a prediction model based on a nomogram to predict DVT in patients with spinal fractures caused by high-energy injuries. METHODS: Clinical data were collected from 936 patients admitted to our hospital between January 2016 and December 2021 with spinal fractures caused by high-energy injuries. Multivariate logistic regression analysis was used to identify the risk factors for postoperative DVT and to develop a nomogram. The predictive performance of the nomogram was evaluated by the receiver operating characteristic (ROC) curve and calibration curve. RESULTS: The incidence of preoperative DVT was 15.38% (144/936). The postoperative incidence of DVT was 20.5% (192/936). The multivariate analysis revealed that age, operation time, blood transfusion, duration of bed rest, American Spinal Injury Association (ASIA) score and D-dimer were risk factors for postoperative DVT. The area under the ROC curve of the nomogram was 0.835 and the calibration curve showed good calibration. CONCLUSIONS: The nomogram showed a good ability to predict postoperative DVT in patients with spinal fractures caused by high-energy injuries, which may benefit pre- and postoperative DVT prophylaxis strategy development.

The outcomes and biliary complications of a staged biliary reconstruction in living donor liver transplantation: a propensity score matched analysis.

BACKGROUND: Uncontrolled massive bleeding and bowel edema are critical issues during liver transplantation. Temporal intra-abdominal packing with staged biliary reconstruction (SBR) yields acceptable outcomes in deceased donor liver transplantation; however, data on living donor liver transplantation (LDLT) are scarce. METHODS: A retrospective analysis of 1269 patients who underwent LDLT was performed. After one-to-two propensity score matching, patients who underwent LDLT with SBR were compared with those who underwent LDLT with one-stage biliary reconstruction (OSBR). The primary outcomes were graft survival (GS) and overall survival (OS), and the secondary outcomes were postoperative biliary complications. RESULTS: There were 55 and 110 patients in the SBR and OSBR groups, respectively. The median blood loss was 6500 mL in the SBR and 4875 mL in the OSBR group. Patients receiving SBR-LDLT had higher incidence of sepsis (69.0% vs. 43.6%; P < 0.01) and intra-abdominal infections (60.0% vs. 30.9%; P < 0.01). Biliary complication rates (14.5% vs. 19.1%; P = 0.47) and 1-and 5-year GS (87.27%, 74.60% vs. 83.64%, 72.71%; P = 0.98) and OS (89.09%, 78.44% vs. 84.55%, 73.70%; P = 0.752) rates were comparable between the two groups. CONCLUSIONS: SBR could serve as a life-saving procedure for patients undergoing complex critical LDLT, with GS, OS, and biliary outcomes comparable to those of OSBR.

zPoseScore model for accurate and robust protein-ligand docking pose scoring in CASP15.

We introduce a deep learning-based ligand pose scoring model called zPoseScore for predicting protein-ligand complexes in the 15th Critical Assessment of Protein Structure Prediction (CASP15). Our contributions are threefold: first, we generate six training and evaluation data sets by employing advanced data augmentation and sampling methods. Second, we redesign the "zFormer" module, inspired by AlphaFold2's Evoformer, to efficiently describe protein-ligand interactions. This module enables the extraction of protein-ligand paired features that lead to accurate predictions. Finally, we develop the zPoseScore framework with zFormer for scoring and ranking ligand poses, allowing for atomic-level protein-ligand feature encoding and fusion to output refined ligand poses and ligand per-atom deviations. Our results demonstrate excellent performance on various testing data sets, achieving Pearson's correlation R = 0.783 and 0.659 for ranking docking decoys generated based on experimental and predicted protein structures of CASF-2016 protein-ligand complexes. Additionally, we obtain an averaged local distance difference test (lDDT pli = 0.558) of AIchemy LIG2 in CASP15 for de novo protein-ligand complex structure predictions. Detailed analysis shows that accurate ligand binding site prediction and side-chain orientation are crucial for achieving better prediction performance. Our proposed model is one of the most accurate protein-ligand pose prediction models and could serve as a valuable tool in small molecule drug discovery.