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BackgroundChidamide is subtype-selective histone deacetylase (HDAC) inhibitor that showed promising result in clinical trials to improve prognosis of angioimmunoblastic T-cell lymphoma (AITL) patients. However, in real world settings, contradictory reports existed as to whether chidamide improve overall survival (OS). Therefore, we aimed to develop an interpretable machine learning (Machine learning)–based model to predict the 2-year overall survival of AITL patients based on chidamide usage and baseline features.MethodsA total of 183 patients with AITL were randomly divided into training set and testing set. We used 5 ML algorithms to build predictive models. Recursive feature elimination (RFE) method was used to filter for the most important features. The ML models were interpreted and the relevance of the selected features was determined using the Shapley additive explanations (SHAP) method and the local interpretable model–agnostic explanationalgorithm.ResultsA total of 183 patients with newly diagnosed AITL from 2012 to 2022 from 3 centers in China were enrolled in our study. Seventy-one patients were dead within 2 years after diagnosis. Five ML algorithms were built based on chidamide usage and 16 baseline features to predict 2-year OS. Catboost model presented to be the best predictive model. After RFE screening, 12 variables demonstrated the best performance (AUC = 0.8651). Using chidamide ranked third among all the variables that correlated with 2-year OS.ConclusionThis study demonstrated that the Catboost model with 12 variables could effectively predict the 2-year OS of AITL patients. Combining chidamide in the treatment therapy was positively correlated with longer OS of AITL patients.

Introduction This study investigated the relationship between environment support, social support and smoking cessation, to provide suggestions for the construction of environment and social support for tobacco control. Methods This was a secondary analysis based on two cross-sectional surveys of adult smokers who participated in the six-month community smoking cessation intervention projects in Beijing. The study subjects were divided into a successful group (n=159) and an unsuccessful group (n=253). The status of the environment support, community tobacco exposure, and social support were compared between groups. A structural equation model (SEM) was established for Confirmatory Factor Analysis. Results The univariate analysis showed that there were differences in smoking cessation outcomes among smokers with different home tobacco regulations, workplace tobacco regulations and number of smokers in the family. Differences in 6-month smoking reduction were also found with different promotion levels of anti-tobacco messaging and the frequency of smoking events at home. The logistic regression analysis indicated that home tobacco regulations (OR=1.30; 95% CI: 1.00–1.69), workplace tobacco regulations (OR=1.27; 95% CI: 1.05– 1.54), and frequency of smoking events at home (OR=1.15; 95% CI: 1.02–1.29), were associated with smoking cessation. The results of the SEM showed that environment support (β=0.39; 95% CI: 0.05–0.73, p=0.026) and social support (β=0.37; 95% CI: 0.05–0.68, p=0.022) had influence on smoking cessation. Conclusions Environment support and social support are related to smoking cessation. Attention should be paid to the smoking regulations at home and workplace, anti-tobacco messaging, and social support by the family. TRIAL REGISTRATION The study was registered on the official website of the China Clinical Trial Registration Center. Identifier: ChiCTR1900024991

BackgroundEducation, intelligence and cognition affect occupational performance and socioeconomic status and may influence virous diseases development. However, the impact of these factors on gastrointestinal diseases and their mediating risk factors remains unclear.MethodsWe utilized genome-wide association studies from European ancestry populations to perform two-sample Mendelian randomization analyses, aiming to estimate genetic instruments associated with education, intelligence, or cognition in relation to 24 gastrointestinal diseases Subsequently, we evaluated 14 potential mediators of this association and calculated the corresponding mediated proportions through two-step Mendelian randomization analyses.ResultAs the dominant factor in gastrointestinal diseases, education had a statistically significant association with 2 gastrointestinal diseases (acute pancreatitis, gastroesophageal reflux) and a suggestive association with 6 diseases (cirrhosis, alcoholic liver disease, cholecystitis, cholelithiasis, chronic gastritis and gastric ulcer). Of the 14 mediators, smoking and adiposity traits played a major role in mediating the effects.ConclusionThe study demonstrated the causal, independent impact of education on specific gastrointestinal diseases. Smoking and adiposity traits emerged as primary mediators, illuminating potential avenues for targeted interventions for prevention of them.

Abstract Background Following external situation reports, individuals perceive risks, experience different emotional reactions, and further change their behaviors. Therefor people’s psychology will also be affected by adjustment of COVID-19 epidemic prevention and control policy, but it remains unknown what kind of coping behaviors will be produced due to psychology. This study defines coping behavior as “medical behavior and irrational consumption behavior after the adjustment of COVID-19 epidemic prevention and control policy in China”, assesses the prevalence of negative emotions in the Chinese population after policy adjustments, and explores how negative emotions affect people’s coping behaviors, conducts baseline research, provides references and suggestions for policy formulation. Methods A cross-sectional online survey was conducted during 21–28 December 2022, included sociodemographic characteristics, COVID-19 infection and irrational purchase behavior, psychological assessment, and opinion polling. Depression and anxiety status are assessed by PHQ-9 and GAD-7. The relationship between anxiety, depression and coping behavior was analyzed by Pearson χ2 test, Fisher’s exact test and logistic regression. Results A total of 3995 infected participants were included in this study, of which 2363(59.1%) and 1194(29.9%) had depression and anxiety. There was a significant difference in clinical treatment and irrational purchase behavior between different level of depression and anxiety. Depression was a risk factor for self- medication (OR = 1.254), seeking professional treatment (OR = 1.215), using online services of medical institutions (OR = 1.320), large-scale purchases of medicines (OR = 1.154) and masks (OR = 1.096). Anxiety was a risk factor for seeking professional treatment (OR = 1.285) and large-scale purchases of masks (OR = 1.168). Conclusion After the adjustment of COVID-19 epidemic prevention and control policy, patient risk perception can increase depression and anxiety. We found that associated with depression, COVID-19 patients are more likely to have medical behaviors such as self- medication, seeking professional treatment, using online services of medical institutions, and storage behaviors of medicines and masks; and anxiety associated with the coping behavior of patients to seek professional treatment and store masks in large quantities. We should improve people’s mental health, and on the other hand, we should give people effective psychological education during the epidemic. Therefore, we should set up psychological outpatient clinics in community health institutions, expanding mental health screening and guidance; relying on the psychological outpatient clinic, establish groups of people with depression or anxiety to carry out COVID-19 health education and peer education, to reduce adverse drug reactions, avoid panic seeking professional treatment and irrational purchase behavior, and protect public mental health. Trial registration This study has been approved by the Medical Ethics Committee of Capital Medical University (2023SY086), and informed consent was obtained from the study subjects before the investigation.

Introduction We study the relationship between psychological traits of smokers and their smoking cessation effects, and provide more scientific evidence for smoking cessation intervention. Methods The study was conducted as a nested case-control study. Smokers who participated in the community smoking cessation intervention projects in Beijing in 2018–2020, were selected as the research participants and divided into two groups: a successful smoking cessation and unsuccessful smoking cessation group, according to their smoking cessation effects at 6 months. Psychological traits of quitters including smoking abstinence self-efficacy, willingness to quit smoking, and trait coping style, were compared between the two groups, and a structural equation model was established for confirmatory factor analysis to analyze their mechanisms. Results There were differences in smoking cessation results between the successful smoking cessation group and the unsuccessful smoking cessation group in terms of smoking abstinence self-efficacy and willingness to quit smoking. Willingness to quit smoking (OR=1.06; 95% CI: 1.008–1.118) is a risk factor, while smoking abstinence self-efficacy in habit/addiction situations (OR=0.77; 95% CI: 0.657– 0.912) is a protective factor. The results of the structural equation model showed that smoking abstinence self-efficacy (β=0.199, p=0.002) and trait coping style (β= -0.166, p=0.042) could influence smoking cessation effects. The structural equation model was well fitted, which showed that smoking abstinence selfefficacy (β=0.199, p=0.002) and trait coping style (β= -0.166, p=0.042) might have influenced the effect of smoking cessation among smokers. Conclusions Willingness to quit smoking has a positive impact on the smoking cessation effect, while smoking abstinence self-efficacy in habit/addiction situations and negative trait coping style have a negative impact. Smoking abstinence self-efficacy and trait coping styles can significantly affect smoking cessation outcomes. CLINICAL TRIAL REGISTRATION The study has been registered on the official website of the China Clinical Trials Registry. Its registration name is Search for Optimization of Tobacco Dependence Management Model Based on Hospital and Community, and registration number is ChiCTR1900024991.

In the field of deep-sea positioning, this paper aims to enhance accuracy and computational efficiency in positioning calculations. We propose an improved method based on layered clustering of sound velocity profiles, where the profiles are stratified according to maximum distance and maximum density. Subsequently, a secondary curve fitting is applied to the stratified data. Ultimately, the underwater positioning is conducted using the sound velocity profiles’ post-layered fitting. We compare our approach with traditional methods such as k-means clustering, layered clustering, and gradient-based stratification. Experimental results demonstrate that, in the application scenario of a USBL system with a transducer tilted at 30°, and under the premise of autonomously controlling the number of layers, our method significantly improves positioning accuracy.

ObjectiveTo assess the effect of the hospital-community integrated management model of tobacco dependence on smoking cessation among community residents compared with a brief smoking cessation intervention.MethodsOur study recruited 651 smokers who were willing to quit in 19 communities in Beijing and conducted a 6-month smoking cessation intervention. The control group receiving a brief smoking cessation intervention and the pilot group receiving an integrated smoking cessation intervention. Intention-to-treat analysis (ITT) and generalized estimating equations were used to assess the effects of the integrated intervention and smoking cessation medication on average number of cigarettes smoked per day (ACSD) and smoking cessation rate.ResultsSimple effects analysis showed that smokers taking medication had significantly lower ACSD than those not taking medication at follow-up, the control group reduced smoking by 3.270, 4.830, and 4.760 cigarettes in the first, third and sixth months, respectively, while the pilot group reduced by 6.230, 5.820, and 4.100 cigarettes. The integrated intervention significantly reduced ACSD among medication-taking smokers at 1st month (reduced by 3.420, P < 0.05) and 3rd month (reduced by 2.050, P < 0.05), but had no significant effect among non-medication taking smokers. The 3rd month smoking cessation rate among medication-taking smokers was 27.0%, which was significantly higher than the smokers with brief smoking cessation intervention.ConclusionThe integrated hospital-community intervention can significantly promote smoking cessation among smokers taking medication, but the issue of payment for medication and additional labor compensation for medical staff should be addressed before its popularization.

The research on how to reduce energy consumption and improve the efficiency of amorphous motors has extensive coverage. This study systematically investigates the influence of internal stress induced by impregnation curing and interference fit on the soft magnetic properties and loss characteristics of Fe80Co3Si3B10P1C3 (CAF4) amorphous alloy iron cores. The amorphous iron core samples undergo analysis through differential scanning calorimetry (DSC), transmission electron microscopy (TEM), X-ray diffraction (XRD), magnetic performance testing equipment, flexible pressure sensors, and magnetostriction testers. The CAF4 amorphous iron core after impregnation curing (AIC) exhibits the lowest loss of P1.2T,1.5 kHz = 22.8 W/kg when annealed at 260 °C, representing a 21% increase compared to the pre-impregnation curing (BIC) state. Within the commonly utilized interference fit range, the loss growth rate of CAF4 amorphous iron cores is lower than that of Fe80Si9B11 (1K101). Likewise, at a frequency of 50 Hz and an excitation of 1000 A/m, the magnetostriction coefficient of CAF4 is smaller than that of 1K101. Within the typical interference fit range, the magnetization performance of CAF4 amorphous iron cores surpasses that of 1K101, favoring lightweight and compact motor designs and reducing copper losses. Consequently, CAF4 amorphous iron cores exhibit significant advantages when employed in motors.

In order to effectively estimate the depth of the source in the acoustic pressure field, this study investigated the relationship between the distribution of acoustic pressure fields in different adjacent mode groups and the depth of the source in shallow waveguides and proposed a method to estimate the depth of the source on the basis of the adjacent mode group acoustic pressure field. We first derived and calculated the adjacent mode group acoustic pressure field of a typical shallow waveguide, then verified the accuracy of this derivation process through simulations. In addition, combined with singular value decomposition mode extraction, the adjacent mode group acoustic pressure field of the SACLANT experimental data was obtained and used as a comparative parameter for the method presented in this paper. By using the depth of the source as the estimation variable, a simulated annealing algorithm and related parameters were designed, and the feasibility of this method was verified through simulation and experiments. The proposed method achieved a higher localization accuracy without the need for accurate modeling of underwater acoustic channels. Under the conditions of the simulation environment, the average estimation error rate of the method was 0.24%, and with increases in the temperature coefficient and Markov chain length, the average estimation error rate of the method decreased. In the experimental environment, the average estimation error rate of the method was 0.45%. This study provides a method to obtain the depth of source in a shallow waveguide via the adjacent mode group acoustic pressure field.

This research paper investigated the impact of normal annealing (NA) and magnetic field annealing (FA) on the soft magnetic properties and microstructure of Fe82Si2B13P1C3 amorphous alloy iron cores. The annealing process involved various methods of magnetic field application: transverse magnetic field annealing (TFA), longitudinal magnetic field annealing (LFA), transverse magnetic field annealing followed by longitudinal magnetic field annealing (TLFA) and longitudinal magnetic field annealing followed by transverse magnetic field annealing (LTFA). The annealed samples were subjected to testing and analysis using techniques such as differential scanning calorimetry (DSC), transmission electron microscopy (TEM), X-ray diffraction (XRD), magnetic performance testing equipment and magneto-optical Kerr microscopy. The obtained results were then compared with those of commercially produced Fe80Si9B11. Fe82Si2B13P1C3 demonstrated the lowest loss of P1.4T,2kHz = 8.1 W/kg when annealed in a transverse magnetic field at 370 °C, which was 17% lower than that of Fe80Si9B11. When influenced by the longitudinal magnetic field, the magnetization curve tended to become more rectangular, and the coercivity (B3500A/m) of Fe82Si2B13P1C3 reached 1.6 T, which was 0.05 T higher than that of Fe80Si9B11. During the 370 °C annealing process of the Fe82Si2B13P1C3 amorphous iron core, the internal stress in the strip gradually dissipated, and impurity domains such as fingerprint domains disappeared and aligned with the length direction of the strip. Consequently, wide strip domains with low resistance and easy magnetization were formed, thereby reducing the overall loss of the amorphous iron core.

Feature loss in IoT scenarios is a common problem. This situation poses a greater challenge in terms of real-time and accuracy for the security of intelligent edge computing systems, which also includes network security intrusion detection systems (NIDS). Losing some packet information can easily confuse NIDS and cause an oversight of security systems. We propose a novel network intrusion detection framework based on an improved neural network. The new framework uses 23 subframes and a mixer for multi-classification work, which improves the parallelism of NIDS and is more adaptable to edge networks. We also incorporate the K-Nearest Neighbors (KNN) algorithm and Genetic Algorithm (GA) for feature selection, reducing parameters, communication, and memory overhead. We named the above system as Combinatorial Multi-Classification-NIDS (CM-NIDS). Experiments demonstrate that our framework can be more flexible in terms of the parameters of binary classification, has a fairly high accuracy in multi-classification, and is less affected by feature loss.

Underwater vehicles are key carriers for underwater inspection and operation tasks, and the successful implementation of these tasks depends on the positioning and navigation equipment with corresponding accuracy. In practice, multiple positioning and navigation devices are often combined to integrate the advantages of each equipment. Currently, the most common method for integrated navigation is combination of the Strapdown Inertial Navigation System (SINS) and Doppler Velocity Log (DVL). Various errors will occur when SINS and DVL are combined together, such as installation declination. In addition, DVL itself also has errors in the measurement of speed. These errors will affect the final accuracy of the combined positioning and navigation system. Therefore, error correction technology has great significance for underwater inspection and operation tasks. This paper takes the SINS/DVL integrated positioning and navigation system as the research object and deeply studies the DVL error correction technology in the integrated system.

BackgroundThe prevalence of cigarette smoking in China is high and the utilization of smoking cessation clinics is very low. Multicomponent smoking cessation interventions involving community and hospital collaboration have the potential to increase the smoking cessation rate. However, the cost-effectiveness of this intervention model is unknown.MethodsWe conducted a smoking cessation intervention trial in 19 community health service centers in Beijing, China. A cost-effectiveness analysis was performed from a societal perspective to compare three strategies of smoking cessation: no intervention (NI), pharmacological intervention (PI), and comprehensive intervention (CI) (PI plus online health promotion). A Markov model, with a time horizon of 20 years, was used to simulate the natural progression of estimated 10,000 male smokers. A cross-sectional survey was conducted to obtain data on costs and quality-adjusted life years (QALYs) by using the five-level EuroQol-5-dimension (EQ-5D-5L) questionnaire. Probabilistic sensitivity analysis was performed to explore parameters of uncertainty in the model.ResultsA total of 680 participants were included in this study, including 283 in the PI group and 397 in the CI group. After 6 months of follow-up, the smoking cessation rate reached 30.0% in the CI group and 21.2% in the PI group. Using the Markov model, compared with the NI group, the intervention strategies of the PI group and the CI group were found to be cost-effective, with an incremental cost-effectiveness ratio (ICER) of $535.62/QALY and $366.19/QALY, respectively. The probabilistic sensitivity analysis indicated that the CI strategy was always the most cost-effective intervention.ConclusionCI for smoking cessation, based in hospital and community in China, is more cost-effective than PI alone. Therefore, this smoking cessation model should be considered to be implemented in healthcare settings.

Alternative end joining (A-EJ) catalyzes substantial level of antibody class switch recombination (CSR) in B cells deficient for classical non-homologous end joining, featuring increased switch (S) region DSB resection and junctional microhomology (MH). While resection has been suggested to initiate A-EJ in model DSB repair systems using engineered endonucleases, the contribution of resection factors to A-EJ-mediated CSR remains unclear. In this study, we systematically dissected the requirement for individual DSB resection factors in A-EJ-mediated class switching with a cell-based assay system and high-throughput sequencing. We show that while CtIP and Mre11 both are mildly required for CSR in WT cells, they play more critical roles in mediating A-EJ CSR, which depend on the exonuclease activity of Mre11. While DNA2 and the helicase/HRDC domain of BLM are required for A-EJ by mediating long S region DSB resection, in contrast, Exo1’s resection-related function does not play any obvious roles for class switching in either c-NHEJ or A-EJ cells, or mediated in an AID-independent manner by joining of Cas9 breaks. Furthermore, ATM and its kinase activity functions at least in part independent of CtIP/Mre11 to mediate A-EJ switching in Lig4-deficient cells. In stark contrast to Lig4 deficiency, 53BP1-deficient cells do not depend on ATM/Mre11/CtIP for residual joining. We discuss the roles for each resection factor in A-EJ-mediated CSR and suggest that the extent of requirements for resection is context dependent.

In this paper, we estimated the temperature-dependent critical inclusion size for microcracking under residual stress and applied stress for particulate-reinforced ultra-high-temperature ceramic matrix composites. The critical flaw size and applied stress for the stable growth of radial cracks under different temperatures were also estimated. It was found that under a lower applied stress, the critical inclusion size was sensitive to the temperature. Under higher applied stresses, the sensitivity became smaller. For ceramic materials with pre-existing microcracks, the crack resistance could be improved by increasing the service stress when the service stress was low. As the temperature increased, the critical flaw size of the materials decreased; the applied stress first increased and then decreased. Finally, a temperature-dependent fracture strength model of composites with a pre-existing critical flaw was proposed. A good agreement was obtained between the model prediction and the experimental data. In this work, we show a method for the characterization of the effects of temperature on the fracture behavior of ceramic-based composites.

The objectives of the study were to investigate serum ANGPTL8 concentrations in different glucose metabolic statuses and to explore the correlations between serum ANGPTL8 levels and various metabolic parameters. Serum ANGPTL8 levels were determined using ELISA in 22 subjects with NGT (normal glucose tolerance), 74 subjects with IGR (impaired glucose regulation), and 33 subjects with T2DM (type 2 diabetes mellitus). Subjects with IFG, IGT, CGI, and T2DM had higher levels of serum ANGPTL8 than subjects with NGT. Serum ANGPTL8 was positively correlated with FPG, fasting C-peptide, and postprandial C-peptide and negatively correlated with BETA/IR when adjusted for age and BMI. Multivariate analysis suggested FPG and fasting C-peptide as independent factors associated with serum ANGPTL8 levels. Serum ANGPTL8 concentrations were significantly increased in IGR and T2DM. Serum ANGPTL8 might play a role in the pathological mechanism of glucose intolerance.

The study is aimed to investigate the pathogenesis underlying the increased prevalence of thyroid nodule (TN) in different levels of metabolic syndrome (MetS) components and analyze the relationships between TN and MetS components. A total of 6,798 subjects, including 2201 patients with TN, were enrolled in this study. Anthropometric, biochemical, thyroid ultrasonographic, and other metabolic parameters were all measured. There was obviously sexual difference in the prevalence of TN (males 26.0%, females 38.5%, resp.). The prevalence of TN in hyperuricemia (45.7% versus 37.4%, P = 0.001), NAFLD (41.2% versus 36.4%, P < 0.05), and MetS (41.4% versus 35.4%, P < 0.001) groups was significantly increased only in females. Insulin resistance [OR = 1.31 (1.15, 1.49)], MetS [OR = 1.18 (1.03, 1.35)], and diabetes [OR = 1.25 (1.06, 1.48)] were all independent risk factors for TN in total subjects, whereas, after stratified analysis of gender, MetS [OR = 1.29, (1.09, 1.53)] and diabetes [OR = 1.47, (1.17, 1.84)] are still strongly and independently associated with the higher risks of TN in female subjects, but not in males. Our results suggest that the components of MetS might associate with the higher risks of TN in women than in men, but further cohort study of this gender disparity in the association between TN and MetS is required.

The mechanisms facilitating hypertension in diabetes still remain to be elucidated. Nonalcoholic fatty liver disease (NAFLD), which is a higher risk factor for insulin resistance, shares many predisposing factors with diabetes. However, little work has been performed on the pathogenesis of hypertension in type 2 diabetes (T2DM) with NAFLD. The aim of this study is to investigate the prevalence of hypertension in different glycemic statuses and to analyze relationships between NAFLD, metabolic risks, and hypertension within a large community-based population after informed written consent. A total of 9473 subjects aged over 45 years, including 1648 patients with T2DM, were enrolled in this cross-sectional study. Clinical and biochemical parameters of all participants were determined. The results suggested that the patients with prediabetes or T2DM were with higher risks to have hypertension. T2DM with NAFLD had significantly higher levels of blood pressure, triglyceride, uric acid, and HOMA-IR than those without NAFLD. Data analyses suggested that hypertriglyceridemia [OR = 1.773 (1.396, 2.251)], NAFLD [OR = 2.344 (1.736, 3.165)], hyperuricemia [OR = 1.474 (1.079, 2.012)], and insulin resistance [OR = 1.948 (1.540, 2.465)] were associated with the higher prevalence of hypertension independent of other metabolic risk factors in type 2 diabetes. Further studies are needed to focus on these associations.

The AP2 clathrin adaptor complex links protein cargo to the endocytic machinery but it is unclear how AP2 is activated on the plasma membrane. Here we demonstrate that the membrane-associated proteins FCHo and SGIP1 convert AP2 into an open, active conformation. We screened for Caenorhabditis elegans mutants that phenocopy the loss of AP2 subunits and found that AP2 remains inactive in fcho-1 mutants. A subsequent screen for bypass suppressors of fcho-1 nulls identified 71 compensatory mutations in all four AP2 subunits. Using a protease-sensitivity assay we show that these mutations restore the open conformation in vivo. The domain of FCHo that induces this rearrangement is not the F-BAR domain or the µ-homology domain, but rather is an uncharacterized 90 amino acid motif, found in both FCHo and SGIP proteins, that directly binds AP2. Thus, these proteins stabilize nascent endocytic pits by exposing membrane and cargo binding sites on AP2.

The clathrin adaptor complex AP2 is thought to be an obligate heterotetramer. We identify null mutations in the α subunit of AP2 in the nematode Caenorhabditis elegans. α-adaptin mutants are viable and the remaining μ2/β hemicomplex retains some function. Conversely, in μ2 mutants, the alpha/sigma2 hemicomplex is localized and is partially functional. α-μ2 double mutants disrupt both halves of the complex and are lethal. The lethality can be rescued by expression of AP2 components in the skin, which allowed us to evaluate the requirement for AP2 subunits at synapses. Mutations in either α or μ2 subunits alone reduce the number of synaptic vesicles by about 30%; however, simultaneous loss of both α and μ2 subunits leads to a 70% reduction in synaptic vesicles and the presence of large vacuoles. These data suggest that AP2 may function as two partially independent hemicomplexes.

The recycling of synaptic vesicles requires the recovery of vesicle proteins and membrane. Members of the stonin protein family (Drosophila Stoned B, mammalian stonin 2) have been shown to link the synaptic vesicle protein synaptotagmin to the endocytic machinery. Here we characterize the unc-41 gene, which encodes the stonin ortholog in the nematode Caenorhabditis elegans. Transgenic expression of Drosophila stonedB rescues unc-41 mutant phenotypes, demonstrating that UNC-41 is a bona fide member of the stonin family. In unc-41 mutants, synaptotagmin is present in axons, but is mislocalized and diffuse. In contrast, UNC-41 is localized normally in synaptotagmin mutants, demonstrating a unidirectional relationship for localization. The phenotype of snt-1 unc-41 double mutants is stronger than snt-1 mutants, suggesting that UNC-41 may have additional, synaptotagmin-independent functions. We also show that unc-41 mutants have defects in synaptic vesicle membrane endocytosis, including a ∼50% reduction of vesicles in both acetylcholine and GABA motor neurons. These endocytic defects are similar to those observed in apm-2 mutants, which lack the µ2 subunit of the AP2 adaptor complex. However, no further reduction in synaptic vesicles was observed in unc-41 apm-2 double mutants, suggesting that UNC-41 acts in the same endocytic pathway as µ2 adaptin.

In oil and gas exploration, elucidating the complex interdependencies among geological variables is paramount. Our study introduces the application of sophisticated regression analysis method at the forefront, aiming not just at predicting geophysical logging curve values but also innovatively mitigate hydrocarbon depletion observed in geochemical logging. Through a rigorous assessment, we explore the efficacy of eight regression models, bifurcated into linear and nonlinear groups, to accommodate the multifaceted nature of geological datasets. Our linear model suite encompasses the Standard Equation, Ridge Regression, Least Absolute Shrinkage and Selection Operator, and Elastic Net, each presenting distinct advantages. The Standard Equation serves as a foundational benchmark, whereas Ridge Regression implements penalty terms to counteract overfitting, thus bolstering model robustness in the presence of multicollinearity. The Least Absolute Shrinkage and Selection Operator for variable selection functions to streamline models, enhancing their interpretability, while Elastic Net amalgamates the merits of Ridge Regression and Least Absolute Shrinkage and Selection Operator, offering a harmonized solution to model complexity and comprehensibility. On the nonlinear front, Gradient Descent, Kernel Ridge Regression, Support Vector Regression, and Piecewise Function-Fitting methods introduce innovative approaches. Gradient Descent assures computational efficiency in optimizing solutions, Kernel Ridge Regression leverages the kernel trick to navigate nonlinear patterns, and Support Vector Regression is proficient in forecasting extremities, pivotal for exploration risk assessment. The Piecewise Function-Fitting approach, tailored for geological data, facilitates adaptable modeling of variable interrelations, accommodating abrupt data trend shifts. Our analysis identifies Ridge Regression, particularly when augmented by Piecewise Function-Fitting, as superior in recouping hydrocarbon losses, and underscoring its utility in resource quantification refinement. Meanwhile, Kernel Ridge Regression emerges as a noteworthy strategy in ameliorating porosity-logging curve prediction for well A, evidencing its aptness for intricate geological structures. This research attests to the scientific ascendancy and broad-spectrum relevance of these regression techniques over conventional methods while heralding new horizons for their deployment in the oil and gas sector. The insights garnered from these advanced modeling strategies are set to transform geological and engineering practices in hydrocarbon prediction, evaluation, and recovery.

Stimulator of interferon genes (STING) has recently been found to play a crucial role in cardiac sterile inflammation and dysfunction. The role of stimulator of interferon genes (STING) in cardiac sterile inflammation and dysfunction has been recently discovered. This study aims to examine the involvement of STING in pathological cardiac remodeling and the mechanisms that govern the activation of the STING pathway. To investigate this, transverse aortic constriction (TAC) was performed on STING knockout mice to induce pressure overload-induced cardiac remodeling. Subsequently, cardiac function, remodeling, and inflammation levels were evaluated. The STING pathway was found to be activated in the pressure overload-stressed heart and angiotensin II (Ang II)-stimulated cardiac fibroblasts. Loss of STING expression led to a significant reduction in inflammatory responses, mitochondrial fragmentation, and oxidative stress in the heart, resulting in attenuated cardiac remodeling and dysfunction. Furthermore, the exacerbation of pressure overload-induced STING-mediated inflammation and pathological cardiac remodeling was observed when mitophagy was suppressed through the silencing of Parkin, an E3 ubiquitin ligase. Taken together, these findings indicate that STING represents a newly identified and significant molecule implicated in the process of pathological cardiac remodeling and that mitophagy is an upstream mechanism that regulates STING activation. Targeting STING may therefore provide a novel therapeutic strategy for pathological cardiac remodeling and heart failure.

Dapagliflozin (DAPA) has been demonstrated to reduce cardiovascular mortality and heart failure hospitalization rates in diabetic patients. However, the mechanism underlying its cardio-protective effect in non-diabetic patients remains unclear. Our study aimed to explore the cardio-protective impact of DAPA on myocardial infarction in non-diabetic mice. We induced myocardial infarction in C57BL/6 mice by ligating the descending branch of the left coronary artery. After surgery, the animals were randomly treated with either saline or DAPA. We employed echocardiography, Western blot analysis, and tissue staining to assess post-infarction myocardial injury. Additionally, we investigated the mechanism of action through cell experiments. Compared to the myocardial infarction group, DAPA treatment significantly attenuated ventricular remodeling and improved cardiac function. By mitigating myocardial oxidative stress and apoptosis, DAPA may activate the AMPKα signaling pathway, thereby exerting a protective effect. These findings suggest that DAPA could serve as a novel therapeutic approach for patients with cardiac infarction.