Cannabis use and acute postoperative pain outcomes in older adults: a propensity matched retrospective cohort study.

INTRODUCTION: Cannabis use is increasing among older adults, but its impact on postoperative pain outcomes remains unclear in this population. We examined the association between cannabis use and postoperative pain levels and opioid doses within 24 hours of surgery. METHODS: We conducted a propensity score-matched retrospective cohort study using electronic health records data of 22 476 older surgical patients with at least 24-hour hospital stays at University of Florida Health between 2018 and 2020. Of the original cohort, 2577 patients were eligible for propensity-score matching (1:3 cannabis user: non-user). Cannabis use status was determined via natural language processing of clinical notes within 60 days of surgery and structured data. The primary outcomes were average Defense and Veterans Pain Rating Scale (DVPRS) score and total oral morphine equivalents (OME) within 24 hours of surgery. RESULTS: 504 patients were included (126 cannabis users and 378 non-users). The median (IQR) age was 69 (65-72) years; 295 (58.53%) were male, and 442 (87.70%) were non-Hispanic white. Baseline characteristics were well balanced. Cannabis users had significantly higher average DVPRS scores (median (IQR): 4.68 (2.71-5.96) vs 3.88 (2.33, 5.17); difference=0.80; 95% confidence limit (CL), 0.19 to 1.36; p=0.01) and total OME (median (IQR): 42.50 (15.00-60.00) mg vs 30.00 (7.50-60.00) mg; difference=12.5 mg; 95% CL, 3.80 mg to 21.20 mg; p=0.02) than non-users within 24 hours of surgery. DISCUSSION: This study showed that cannabis use in older adults was associated with increased postoperative pain levels and opioid doses.

Cannabis Use and Inhalational Anesthesia Administration in Older Adults: A Propensity Matched Retrospective Cohort Study.

BACKGROUND: Cannabis use is associated with higher intravenous anesthetic administration. Similar data regarding inhalational anesthetics are limited. With rising cannabis use prevalence, understanding any potential relationship with inhalational anesthetic dosing is crucial. We compared average intraoperative isoflurane/sevoflurane minimum alveolar concentration equivalents between older adults with and without cannabis use. METHODS: The electronic health records of 22,476 surgical patients ≥65 years old at the University of Florida Health System between 2018-2020 were reviewed. The primary exposure was cannabis use within 60 days of surgery, determined via i) a previously published natural language processing algorithm applied to unstructured notes and ii) structured data, including International Classification of Disease codes for cannabis use disorders and poisoning by cannabis, laboratory cannabinoids screening results, and RxNorm codes. The primary outcome was the intraoperative time-weighted average of isoflurane/sevoflurane minimum alveolar concentration equivalents at one-minute resolution. No a priori minimally clinically important difference was established. Patients demonstrating cannabis use were matched 4:1 to non-cannabis use controls using a propensity score. RESULTS: Among 5,118 meeting inclusion criteria, 1,340 patients (268 cannabis users and 1,072 nonusers) remained after propensity score matching. The median and interquartile range (IQR) age was 69 (67, 73) years; 872 (65.0%) were male, and 1,143 (85.3%) were non-Hispanic White. The median (IQR) anesthesia duration was 175 (118, 268) minutes. After matching, all baseline characteristics were well-balanced by exposure. Cannabis users had statistically significantly higher average minimum alveolar concentrations than nonusers [mean±SD: 0.58±0.23 versus 0.54±0.22, respectively; mean difference=0.04; 95% confidence limits, 0.01 to 0.06; p=0.020]. CONCLUSION: Cannabis use was associated with administering statistically significantly higher inhalational anesthetic minimum alveolar concentration equivalents in older adults, but the clinical significance of this difference is unclear. These data do not support the hypothesis that cannabis users require clinically meaningfully higher inhalational anesthetics doses.

Predictors of left atrial appendage thrombus in atrial fibrillation patients undergoing cardioversion.

BACKGROUND: Atrial fibrillation and atrial flutter represent the most prevalent clinically significant cardiac arrhythmias. While the CHA2DS2-VASc score is commonly used to inform anticoagulation therapy decisions for patients with these conditions, its predictive power is limited. Therefore, we sought to improve risk prediction for left atrial appendage thrombus (LAAT), a known risk factor for stroke in these patients. METHODS: We developed and validated an explainable machine learning model using the eXtreme Gradient Boosting algorithm with 5 × 5 nested cross-validation. The primary outcome was to predict the probability of LAAT in patients with atrial fibrillation and atrial flutter who underwent transesophageal echocardiogram prior to cardioversion. Our algorithm used 37 demographic, comorbid, and transthoracic echocardiographic variables. RESULTS: A total of 795 patients were included in our analysis. LAAT was present in 11.3% of the patients. The average age of patients was 63.3 years and 34.7% were women. Patients with LAAT had significantly lower left ventricular ejection fraction (29.9% vs 43.5%; p < 0.001), lower E' lateral velocity (5.7 cm vs. 7.9 cm; p < 0.001) and higher E/A ratio (2.6 vs 1.8; p = 0.002). Our machine learning model achieved a high AUC of 0.79, with a high specificity of 0.82, and modest sensitivity of 0.57. Left ventricular ejection fraction was the most important variable in predicting LAAT. Patients were split into 10 buckets based on the percentile of their predicted probability of having thrombus. The lower the percentile (e.g., 10%), the lower the probability of having thrombus. Using a cutoff point of 0.16 which includes 10.0% of the patients, we can rule out thrombus with 100% confidence. CONCLUSION: Using machine learning, we refined the predictive power of predicting LAAT and explained the model. These results show promise in providing better guidance for anticoagulation therapy and cardioversion in AF and AFL patients.

Exploring the Activation Mechanism of the GPR183 Receptor.

The G protein-coupled receptors (GPCRs) play a pivotal role in numerous biological processes as crucial cell membrane receptors. However, the dynamic mechanisms underlying the activation of GPR183, a specific GPCR, remain largely elusive. To address this, we employed computational simulation techniques to elucidate the activation process and key events associated with GPR183, including conformational changes from inactive to active state, binding interactions with the Gi protein complex, and GDP release. Our findings demonstrate that the association between GPR183 and the Gi protein involves the formation of receptor-specific conformations, the gradual proximity of the Gi protein to the binding pocket, and fine adjustments of the protein conformation, ultimately leading to a stable GPR183-Gi complex characterized by a high energy barrier. The presence of Gi protein partially promotes GPR183 activation, which is consistent with the observation of GPCR constitutive activity test experiments, thus illustrating the reliability of our calculations. Moreover, our study suggests the existence of a stable partially activated state preceding complete activation, providing novel avenues for future investigations. In addition, the relevance of GPR183 for various diseases, such as colitis, the response of eosinophils to Mycobacterium tuberculosis infection, antiviral properties, and pulmonary inflammation, has been emphasized, underscoring its therapeutic potential. Consequently, understanding the activation process of GPR183 through molecular dynamic simulations offers valuable kinetic insights that can aid in the development of targeted therapies.

An explainable machine learning approach using contemporary UNOS data to identify patients who fail to bridge to heart transplantation.

Background: The use of Intra-aortic Balloon Pump (IABP) and Impella devices as a bridge to heart transplantation (HTx) has increased significantly in recent times. This study aimed to create and validate an explainable machine learning (ML) model that can predict the failure of status two listings and identify the clinical features that significantly impact this outcome. Methods: We used the UNOS registry database to identify HTx candidates listed as UNOS Status 2 between 2018 and 2022 and supported with either Impella (5.0 or 5.5) or IABP. We used the eXtreme Gradient Boosting (XGBoost) algorithm to build and validate ML models. We developed two models: (1) a comprehensive model that included all patients in our cohort and (2) separate models designed for each of the 11 UNOS regions. Results: We analyzed data from 4,178 patients listed as Status 2. Out of them, 12% had primary outcomes indicating Status 2 failure. Our ML models were based on 19 variables from the UNOS data. The comprehensive model had an area under the curve (AUC) of 0.71 (±0.03), with a range between 0.44 (±0.08) and 0.74 (±0.01) across different regions. The models' specificity ranged from 0.75 to 0.96. The top five most important predictors were the number of inotropes, creatinine, sodium, BMI, and blood group. Conclusion: Using ML is clinically valuable for highlighting patients at risk, enabling healthcare providers to offer intensified monitoring, optimization, and care escalation selectively.

Exploration of the mechanism of Traditional Chinese Medicine for anxiety and depression in patients with diarrheal irritable bowel syndrome based on network pharmacology and meta-analysis.

Background: The efficacy of Chinese herbal medicine (CHM) in managing irritable bowel syndrome with diarrhea (IBS-D) accompanied by anxiety and depression remains uncertain. Thus, a systematic review was carried out employing meta-analysis and network pharmacology to ascertain the efficacy and underlying mechanisms of CHM therapy. Methods: By conducting a systematic review, including literature search, screening, and data extraction, we identified 25 randomized controlled trials to assess CHM's effectiveness in treating irritable bowel syndrome alongside anxiety and depression. Network pharmacology was utilized to scrutinize the metabolite utility of CHM in addressing this condition. Potential primary mechanisms were synthesized using information sourced from the PubMed database. Results: Twenty-five studies, including 2055 patients, were analyzed, revealing significant treatment efficacy for IBS-D in the trial group compared to controls [OR = 4.01, 95% CI (2.99, 5.36), I2 = 0%] Additionally, treatment for depression [SMD = -1.08, 95% CI (-1.30, -0.86), p < 0.00001, I2 = 68%; SDS: SMD = -1.69, 95% CI (-2.48, -0.90), p < 0.0001, I2 = 96%] and anxiety [HAMA: SMD = -1.29, 95% CI (-1.68, -0.91), p < 0.00001, I2 = 89%; SAS: SMD = -1.75, 95% CI (-2.55, -0.95), p < 0.00001, I2 = 96%] significantly improved in the trial group. Furthermore, the trial group exhibited a significantly lower disease relapse rate [OR = 0.30, 95% CI (0.20, 0.44), p < 0.00001, I2 = 0%]. CHM treatment consistently improved IBS severity (IBS-SSS) and symptom scores. Network pharmacology analysis identified key chemical metabolites in traditional Chinese medicine formulations, including Beta-sitosterol, Stigmasterol, Quercetin, Naringenin, Luteolin, Kaempferol, Nobiletin, Wogonin, Formononetin, and Isorhamnetin. Utilizing the STRING database and Cytoscape v3.9.0 software, a protein-protein interaction (PPI) network revealed the top eight key targets: IL-6, TNF, PPARG, PTGS2, ESR1, NOS3, MAPK8, and AKT1, implicated in anti-inflammatory responses, antioxidant stress modulation, and neurotransmitter homeostasis maintenance. Conclusion: Chinese Herbal Medicine (CHM) offers a promising and safe treatment approach for patients dealing with Diarrheal Irritable Bowel Syndrome (IBS-D) accompanied by anxiety and depression; thus, indicating its potential for practical implementation. The most active metabolites of CHM could simultaneously act on the pathological targets of IBS-D, anxiety, and depression.The diverse scope of CHM's therapeutic role includes various aspects and objectives, underscoring its potential for broad utilization.

Regulation of gut microbiota and serum neurotransmitters in mice by Streptococcus thermophilus GA8- and Lacticaseibacillus rhamnosus HAO9-fermented milk containing high levels of gamma-aminobutyric acid.

BACKGROUND: Gamma-aminobutyric acid (GABA) is an important neurotransmitter in the human body, with several negative emotions reported as being associated with GABA dysregulation. This study investigates the safety and modulatory effects of GABA-enriched milk, fermented by Streptococcus thermophilus GA8 and Lacticasebacillus rhamnosus HAO9, on the gut microbiota and neurotransmitter profiles in mice. RESULTS: Through rigorous culturing and fermentation processes, we achieved consistent GABA production in milk, with concentrations reaching 4.6 and 8.5 g L-1 for GA8-fermented and co-fermented milk, respectively, after 48 h. Using SPF male C57BL/6J mice, we administered either mono-culture or combined-culture milk treatments and monitored physiological impacts. The treatments did not affect mouse body weight but induced significant changes in gut microbiota composition. Beta diversity analysis revealed distinct microbial profiles between treatment groups, highlighting fermentation-specific microbial shifts, such as an increase in Verrucomicrobia for the GA8 group and a modulation in Saccharibacteria_genera_incertae_sedis for the GA8 + HAO9 group. Serum neurotransmitter levels were elevated in both treatment groups, with significant increases in l-glutamine, l-tryptophan and, notably, serotonin hydrochloride in the GA8 + HAO9 group. Correlation analysis identified a positive association between specific bacterial genera and neurotransmitter levels, suggesting a probiotic effect on neuroactive substances. CONCLUSION: These findings suggest that fermented milk has potential as a probiotic supplement for mood improvement and stress relief, highlighting its role in modulating the gut-brain axis. © 2024 Society of Chemical Industry.

Multi-Responsive Peptide-Based Ultrathin Nanosheets Prepared by a Horizontal Monolayer Assembly.

In this study, peptide-based self-assembled nanosheets with a thickness of approximately 1 nm were prepared using a hierarchical covalent physical fabrication strategy. The covalent alternating polymerization of helical peptide E3 with an azobenzene (AZO) structure yielded copolymers CoP(E3-AZO), which physically self-assembled into ultrathin nanosheets in an unanticipated two-dimensional horizontal monolayer arrangement. This special monolayer arrangement enabled the thickness of the nanosheets to be equal to the cross-sectional diameter of a single linear copolymer, which is a rare phenomenon. Molecular dynamics simulations suggested that the synergistic effect of multiple molecular interactions drives the self-assembly of CoP(E3-AZO) into nanosheets and that various methods, including phototreatment, pH adjustment, the addition of additives, and introduction of cosolvents, can alter the molecular interactions and modulate the self-assembly of CoP(E3-AZO), yielding diverse nanostructures. Remarkably, the ultrathin nanosheets selectively inhibited cancer cells at certain concentrations.

Exploring the activation mechanism of metabotropic glutamate receptor 2.

Homomeric dimerization of metabotropic glutamate receptors (mGlus) is essential for the modulation of their functions and represents a promising avenue for the development of novel therapeutic approaches to address central nervous system diseases. Yet, the scarcity of detailed molecular and energetic data on mGlu2 impedes our in-depth comprehension of their activation process. Here, we employ computational simulation methods to elucidate the activation process and key events associated with the mGlu2, including a detailed analysis of its conformational transitions, the binding of agonists, Gi protein coupling, and the guanosine diphosphate (GDP) release. Our results demonstrate that the activation of mGlu2 is a stepwise process and several energy barriers need to be overcome. Moreover, we also identify the rate-determining step of the mGlu2's transition from the agonist-bound state to its active state. From the perspective of free-energy analysis, we find that the conformational dynamics of mGlu2's subunit follow coupled rather than discrete, independent actions. Asymmetric dimerization is critical for receptor activation. Our calculation results are consistent with the observation of cross-linking and fluorescent-labeled blot experiments, thus illustrating the reliability of our calculations. Besides, we also identify potential key residues in the Gi protein binding position on mGlu2, mGlu2 dimer's TM6-TM6 interface, and Gi α5 helix by the change of energy barriers after mutation. The implications of our findings could lead to a more comprehensive grasp of class C G protein-coupled receptor activation.

Exploring the Molecular Mechanisms of Huaier on Modulating Metabolic Reprogramming of Hepatocellular Carcinoma: A Study based on Network Pharmacology, Molecular Docking and Bioinformatics.

BACKGROUND: Huaier (Trametes robiniophila Murr), a traditional Chinese medicine, is widely used in China as a complementary and alternative therapy to treat hepatocellular carcinoma (HCC). Past studies have shown that Huaier can arrest the cell cycle, promote apoptosis and inhibit the proliferation of cancer cells. However, how it regulates the metabolism of HCC is still unclear. OBJECTIVE: This study explores the metabolic-related function of Huaier in treating HCC with an in-silico approach. METHODS: A network pharmacology and bioinformatics-based approach was employed to investigate the molecular pathogenesis of metabolic reprogramming in HCC with Huaier. The compounds of Huaier were obtained from public databases. Oral bioavailability and drug likeness were screened using the TCMSP platform. The differential gene expressions between HCC and non-tumor tissue were calculated and used to find the overlap from the targets of Huaier. The enrichment analysis of the overlapped targets by Metascape helped filter out the metabolism-related targets of Huaier in treating HCC. Protein-protein interaction (PPI) network construction and topological screening revealed the hub nodes. The prognosis and clinical correlation of these targets were validated from the cancer genome atlas (TCGA) database, and the interactions between the hub nodes and active ingredients were validated by molecular docking. RESULTS: The results showed that Peroxyergosterol, Daucosterol, and Kaempferol were the primary active compounds of Huaier involved in the metabolic reprogramming of HCC. The top 6 metabolic targets included AKR1C3, CYP1A1, CYP3A4, CYP1A2, CYP17A1, and HSD11B1. The decreased expression of CYP3A4 and increased expression of AKR1C3 were related to the poor overall survival of HCC patients. The molecular docking validated that Peroxyergosterol and Kaempferol exhibited the potential to modulate CYP3A4 and AKR1C3 from a computational perspective. CONCLUSION: This study provided a workflow for understanding the mechanism of Huaier in regulating the metabolic reprogramming of HCC.

OsMAPK6 phosphorylation and CLG1 ubiquitylation of GW6a non-additively enhance rice grain size through stabilization of the substrate.

The chromatin modifier GRAIN WEIGHT 6a (GW6a) enhances rice grain size and yield. However, little is known about its gene network determining grain size. Here, we report that MITOGEN-ACTIVED PROTEIN KINASE 6 (OsMAPK6) and E3 ligase CHANG LI GENG 1 (CLG1) interact with and target GW6a for phosphorylation and ubiquitylation, respectively. Unexpectedly, however, in vitro and in vivo assays reveal that both of the two post-translational modifications stabilize GW6a. Furthermore, we uncover two major GW6a phosphorylation sites (serine142 and threonine186) targeted by OsMAPK6 serving an important role in modulating grain size. In addition, our genetic and molecular results suggest that the OsMAPK6-GW6a and CLG1-GW6a axes are crucial and operate in a non-additive manner to control grain size. Overall, our findings identify a previously unknown mechanism by which phosphorylation and ubiquitylation non-additively stabilize GW6a to enhance grain size, and reveal correlations and interactions of these posttranslational modifications during rice grain development.

Guided diffusion for molecular generation with interaction prompt.

Molecular generative models have exhibited promising capabilities in designing molecules from scratch with high binding affinities in a predetermined protein pocket, offering potential synergies with traditional structural-based drug design strategy. However, the generative processes of such models are random and the atomic interaction information between ligand and protein are ignored. On the other hand, the ligand has high propensity to bind with residues called hotspots. Hotspot residues contribute to the majority of the binding free energies and have been recognized as appealing targets for designed molecules. In this work, we develop an interaction prompt guided diffusion model, InterDiff to deal with the challenges. Four kinds of atomic interactions are involved in our model and represented as learnable vector embeddings. These embeddings serve as conditions for individual residue to guide the molecular generative process. Comprehensive in silico experiments evince that our model could generate molecules with desired ligand-protein interactions in a guidable way. Furthermore, we validate InterDiff on two realistic protein-based therapeutic agents. Results show that InterDiff could generate molecules with better or similar binding mode compared to known targeted drugs.

Clinical Application and Research Progress of Remimazolam for Pediatric Patients.

Remimazolam is a novel ultrashort-acting benzodiazepine that allosterically modulates γ-aminobutyric acid type A (GABAA) receptors to exert sedative effects. Remimazolam has the properties of controllable sedation, rapid onset, and a short duration of action, along with minor depression of circulation and respiration. Remimazolam has been approved for clinical use since 2020 in Japan, and it has been applied for procedural sedation, general anesthesia induction and maintenance, and sedation in ICU patients, and has been proven to be safe and effective. Currently, no consensus has been reached on the clinical application of remimazolam in pediatric patients. This review introduces the clinical research progress and limitations of remimazolam in recent years, aiming to supply scientific guidance and a theoretical reference for the application of remimazolam in pediatric anaesthesia.

Exploring the Structural Plasticity Mechanism of Corticospinal Tract during Stroke Rehabilitation Based Automated Fiber Quantification Tractography.

BACKGROUND: Corticospinal tract (CST) is the principal motor pathway; we aim to explore the structural plasticity mechanism in CST during stroke rehabilitation. METHODS: A total of 25 patients underwent diffusion tensor imaging before rehabilitation (T1), 1-month post-rehabilitation (T2), 2 months post-rehabilitation (T3), and 1-year post-discharge (T4). The CST was segmented, and fractional anisotropy (FA), axial diffusion (AD), mean diffusivity (MD), and radial diffusivity (RD) were determined using automated fiber quantification tractography. Baseline level of laterality index (LI) and motor function for correlation analysis. RESULTS: The FA values of all segments in the ipsilesional CST (IL-CST) were lower compared with normal CST. Repeated measures analysis of variance showed time-related effects on FA, AD, and MD of the IL-CST, and there were similar dynamic trends in these 3 parameters. At T1, FA, AD, and MD values of the mid-upper segments of IL-CST (around the core lesions) were the lowest; at T2 and T3, values for the mid-lower segments were lower than those at T1, while the values for the mid-upper segments gradually increased; at T4, the values for almost entire IL-CST were higher than before. The highest LI was observed at T2, with a predominance in contralesional CST. The LIs for the FA and AD at T1 were positively correlated with the change rate of motor function. CONCLUSIONS: IL-CST showed aggravation followed by improvement from around the lesion to the distal end. Balance of interhemispheric CST may be closely related to motor function, and LIs for FA and AD may have predictive value for mild-to-moderate stroke rehabilitation. Clinical Trial Registration. URL: http://www.chictr.org.cn; Unique Identifier: ChiCTR1800019474.

What is China's efficient power generation portfolio under carbon neutrality target? An empirical analysis considering flexibility and system cost.

Variable renewable energy (VRE) is the most promising form of primary generation under a carbon neutrality target due to its environmental benefits, incentive policy, and technological progress. However, the increasing proportion of VRE generation, such as solar and wind power, has sharply increased integration cost and reduced power grid stability. This study uses portfolio theory to investigate China's optimal power generation portfolio by 2050 considering flexibility constraint and system cost, including technical and integration costs. The results demonstrate that non-fossil-fuel power generation technologies have cost and emission reduction advantages over fossil-fuel-based technologies. VRE generation technologies must be developed in synergy with other forms of power generation when considering flexibility requirement and integration cost. A complete phase-out of fossil-fuel power generation technologies in China appears unlikely in the study period. Gas-fired and coal-fired power generation are the pillar forms of power generation to meet future flexibility needs.

Predicting Mutational Effects on Ca2+-Activated Chloride Conduction of TMEM16A Based on a Simulation Study.

The dysfunction and defects of ion channels are associated with many human diseases, especially for loss-of-function mutations in ion channels such as cystic fibrosis transmembrane conductance regulator mutations in cystic fibrosis. Understanding ion channels is of great current importance for both medical and fundamental purposes. Such an understanding should include the ability to predict mutational effects and describe functional and mechanistic effects. In this work, we introduce an approach to predict mutational effects based on kinetic information (including reaction barriers and transition state locations) obtained by studying the working mechanism of target proteins. Specifically, we take the Ca2+-activated chloride channel TMEM16A as an example and utilize the computational biology model to predict the mutational effects of key residues. Encouragingly, we verified our predictions through electrophysiological experiments, demonstrating a 94% prediction accuracy regarding mutational directions. The mutational strength assessed by Pearson's correlation coefficient is -0.80 between our calculations and the experimental results. These findings suggest that the proposed methodology is reliable and can provide valuable guidance for revealing functional mechanisms and identifying key residues of the TMEM16A channel. The proposed approach can be extended to a broad scope of biophysical systems.

Optimizing rice grain size by attenuating phosphorylation-triggered functional impairment of a chromatin modifier ternary complex.

Histone acetylation affects numerous cellular processes, such as gene transcription, in both plants and animals. However, the posttranslational modification-participated regulatory networks for crop-yield-related traits are largely unexplored. Here, we characterize a regulatory axis for controlling rice grain size and yield, centered on a potent histone acetyltransferase (chromatin modifier) known as HHC4. HHC4 interacts with and forms a ternary complex with adaptor protein ADA2 and transcription factor bZIP23, wherein bZIP23 recruits HHC4 to specific promoters, and ADA2 and HHC4 additively enhance bZIP23 transactivation on target genes. Meanwhile, HHC4 interacts with and is phosphorylated by GSK3-like kinase TGW3. The resultant phosphorylation triggers several functional impairments of the HHC4 ternary complex. In addition, we identify two major phosphorylation sites of HHC4 by TGW3-sites which play an important role in controlling rice grain size. Overall, our findings thus have critical implications for understanding epigenetic basis of grain size control and manipulating the knowledge for higher crop productivity.

Genetic associations with longevity are on average stronger in females than in males.

It is long observed that females tend to live longer than males in nearly every country. However, the underlying mechanism remains elusive. In this study, we discovered that genetic associations with longevity are on average stronger in females than in males through bio-demographic analyses of genome-wide association studies (GWAS) dataset of 2178 centenarians and 2299 middle-age controls of Chinese Longitudinal Healthy Longevity Study (CLHLS). This discovery is replicated across North and South regions of China, and is further confirmed by North-South discovery/replication analyses of different and independent datasets of Chinese healthy aging candidate genes with CLHLS participants who are not in CLHLS GWAS, including 2972 centenarians and 1992 middle-age controls. Our polygenic risk score analyses of eight exclusive groups of sex-specific genes, analyses of sex-specific and not-sex-specific individual genes, and Genome-wide Complex Trait Analysis using all SNPs all reconfirm that genetic associations with longevity are on average stronger in females than in males. Our discovery/replication analyses are based on genetic datasets of in total 5150 centenarians and compatible middle-age controls, which comprises the worldwide largest sample of centenarians. The present study's findings may partially explain the well-known male-female health-survival paradox and suggest that genetic variants may be associated with different reactions between males and females to the same vaccine, drug treatment and/or nutritional intervention. Thus, our findings provide evidence to steer away from traditional view that "one-size-fits-all" for clinical interventions, and to consider sex differences for improving healthcare efficiency. We suggest future investigations focusing on effects of interactions between sex-specific genetic variants and environment on longevity as well as biological function.

Mechanistic study of the transmission pattern of the SARS-CoV-2 omicron variant.

The omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) characterized by 30 mutations in its spike protein, has rapidly spread worldwide since November 2021, significantly exacerbating the ongoing COVID-19 pandemic. In order to investigate the relationship between these mutations and the variant's high transmissibility, we conducted a systematic analysis of the mutational effect on spike-angiotensin-converting enzyme-2 (ACE2) interactions and explored the structural/energy correlation of key mutations, utilizing a reliable coarse-grained model. Our study extended beyond the receptor-binding domain (RBD) of spike trimer through comprehensive modeling of the full-length spike trimer rather than just the RBD. Our free-energy calculation revealed that the enhanced binding affinity between the spike protein and the ACE2 receptor is correlated with the increased structural stability of the isolated spike protein, thus explaining the omicron variant's heightened transmissibility. The conclusion was supported by our experimental analyses involving the expression and purification of the full-length spike trimer. Furthermore, the energy decomposition analysis established those electrostatic interactions make major contributions to this effect. We categorized the mutations into four groups and established an analytical framework that can be employed in studying future mutations. Additionally, our calculations rationalized the reduced affinity of the omicron variant towards most available therapeutic neutralizing antibodies, when compared with the wild type. By providing concrete experimental data and offering a solid explanation, this study contributes to a better understanding of the relationship between theories and observations and lays the foundation for future investigations.

IL-22 relieves hepatic ischemia-reperfusion injury by inhibiting mitochondrial apoptosis based on the activation of STAT3.

INTRODUCTION: Interleukin-22 (IL-22) has been proven to exhibit a protective role in hepatic ischemia-reperfusion injury (HIRI). This study aimed to explore the change of IL-22 and IL-22 receptor 1 (IL-22R1) axis in HIRI and its role in mitochondrial apoptosis associated with STAT3 activation. MATERIALS AND METHODS: I/R mice were examined for the expression of IL-22, IL-22R1 and IL-22BP. The roles of IL-22 in hepatic histopathology and oxidative stress injuries (ALT, MDA and SOD) were determined. Oxidative stress damages of AML-12 cells were induced by H2O2, and were indicated by apoptosis, Ca2+ concentration, and mitochondrial function. The effects of IL-22 on p-STAT3Try705 were analyzed. RESULTS: We found that the expression of IL-22, IL-22R1, and IL-22BP was elevated 24 h after I/R induction, while decreased 48 h after I/R induction. Furthermore, we also discovered that IL-22 rescued the morphological damages and dysfunction of hepatocytes induced by H2O2, which were antagonized by IL-22BP, an endogenous antagonist of IL-22. Additionally, increased levels of Ca2+ concentration, MDA, ROS, apoptosis and mitochondrial dysfunction were noticed in H2O2-treated hepatocytes. However, IL-22 ameliorated the effects of I/R or H2O2. The protective effects of IL-22 were reversed by AG490, a specific antagonist of STAT3. CONCLUSIONS: In conclusion, our results indicated that IL-22 inhibited I/R-induced oxidative stress injury, Ca2+ overload, and mitochondrial apoptosis via STAT3 activation.