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Abstract To promptly detect abnormal events in surveillance videos, this article designs a video anomaly detection method based on multiple instance learning. Generally, abnormal events occur less frequently compared to normal events. Traditional video surveillance relies on manual operation to monitor scenes and detect abnormal events by watching surveillance videos. However, watching surveillance footage is a labor‐intensive task, and prolonged observation can lead to visual fatigue and lack of concentration, which in turn results in missed detections and false positives [1]. Therefore, it is crucial to develop intelligent algorithms for video anomaly detection. The method can detect whether segments of a video contain abnormal events. First, the I3D network is used as a feature extractor to capture spatiotemporal features from the input video. Then, the spatiotemporal information is processed and input into a segment‐level anomaly detector based on multiple instance learning for detection. The authors treat abnormal videos as positive bags and normal videos as negative bags, and automatically learn a deep anomaly ranking model that can predict abnormal segments. Finally, the results of the training were tested and analyzed, demonstrating that the model is capable of detecting abnormal traffic segments.

Abstract Background Chronic obstructive pulmonary disease (COPD) is closely linked to cardiovascular diseases. We aimed to investigate the association between Life’s Essential 8 (LE8), the newly established measurement to assess cardiovascular health (CVH), and COPD among U.S. general adults. Methods This study extracted the National Health and Nutrition Examination Survey (2007–2018) data. Multivariate logistic regression models were used to examine the associations between LE8 and COPD. A restricted cubic spline regression model was used to explore the dose-response relationships between LE8 scores and COPD. In addition, subgroup and sensitivity analyses were performed to assess the robustness of our results. Results Our study included 19,774 participants representing 145.2 million non-institutionalized U.S. population aged ≥ 20 years. The overall age-adjusted prevalence of COPD was 4.5%. After adjusting for the potential covariates, LE8 was inversely associated with COPD [adjusted odds ratio (AOR) = 0.169, 95% CI: 0.115, 0.249], exhibiting a nonlinear dose-response relationship (P for nonlinearity

Abstract Pest rodents persistently undermine crop yields and food security. Fertility control could be a viable alternative for managing rodent populations. This study investigates the antifertility effects of various concentrations of clarithromycin combined with 1.0 mg/kg quinestrol on male rodents to determine an effective contraceptive dose that minimizes quinestrol usage, addressing key concerns such as potential environmental residue, which may impact ecological balance, and poor palatability, which could reduce ingestion and limit the sterilant’s effectiveness. Male mice were divided into five groups and administered different doses of clarithromycin or clarithromycin and quinestrol for three consecutive days, while the control group received sunflower seed oil only. After seven days, organ weights, reproductive organ weights, sperm density, serum hormone levels, and CYP3A4 content in small intestinal and liver tissues were measured to assess persistent effects. Compared with the control group, all treatment groups had significant reductions in epididymal weight, seminal vesicle weight, and serum T and LH levels. Higher concentrations of clarithromycin (2 mg/kg and 10 mg/kg) significantly impacted reproductive metrics, including sperm density, organ weights, and serum LH and testosterone levels, though complete sterilization was not achieved, with more than 60 million cauda epididymal spermatozoa remaining. However, the combination demonstrated potential as an effective strategy for male fertility control. The combination of 2.0 mg/kg clarithromycin and quinestrol can mitigate organ enlargement seen with quinestrol alone. This combination also decreased total enzyme content, thereby diminishing quinestrol’s induction of CYP3A4, which may increase the sterilization effectiveness of the treatment.

Abstract Background Inflammatory bowel disease (IBD) is a chronic, relapsing condition wherein biologics have improved disease prognosis but introduced elevated infection susceptibility. Vedolizumab (VDZ) demonstrates unique safety advantages; however, a comprehensive systematic comparison regarding the risk of Clostridioides difficile infection (CDI) between vedolizumab and alternative medications remains absent. Method Medline, Embase, Cochrane, and clinicaltrials.gov registry were comprehensively searched. Pooled estimates of CDI proportion, incidence, pooled risk ratio between ulcerative colitis (UC) and Crohn’s disease (CD), vedolizumab and other medications were calculated. Data synthesis was completed in R using the package “meta”. Results Of the 338 studies initially identified, 30 met the inclusion/exclusion criteria. For CDI risk, the pooled proportion was 0.013 (95% CI 0.010–0.017), as well as the pooled proportion of serious CDI was 0.004 (95% CI 0.002–0.008). The comparative pooled risk ratios revealed: UC versus CD at 2.25 (95% CI 1.73–2.92), vedolizumab versus anti-TNF agents at 0.15 (95% CI 0.04–0.63) for UC and 1.29 (95% CI 0.41–4.04) for CD. Conclusion The overall CDI risk in IBD patients exposed to vedolizumab was estimated to be 0.013. An increased risk of CDI was noted in UC patients receiving vedolizumab compared to those with CD. Vedolizumab potentially offers an advantage over anti-TNF agents for UC regarding CDI risk, but not for CD. Trial registration The study was registered on the PROSPERO registry (CRD42023465986).

Abstract Worldwide, governments imposed non-pharmaceutical interventions (NPIs) during the COVID-19 pandemic to contain the pandemic more effectively. We examined the effectiveness of individual NPIs in the United States during the first wave of the pandemic. Three types of analyses were performed. First, a prototypical Bayesian hierarchical model was employed to gauge the effectiveness of five NPIs and they are gathering restriction, restaurant capacity restriction, business closure, school closure, and stay-at-home order in the 42 states with over 100 deaths by the end of the wave. Second, we examined the effectiveness of the face mask mandate, the sixth and most controversial NPI by counterfactual modeling, which is a variant of the prototypical Bayesian hierarchical model allowing us to answer the question of what if the state had imposed the mandate or not. The third analysis used an advanced Bayesian hierarchical model to evaluate the effectiveness of all six NPIs in all 50 states and the District of Columbia, and thereby provide a full-scale estimation of the effectiveness of NPIs and the relative effectiveness of each NPI in the entire United States. Our results have enhanced the collective knowledge on the general effectiveness of NPIs in arresting the spread of COVID-19.

Traditional ventilation duct systems for embankments in cold regions are limited in their ability to regulate ventilation, which restricts their cooling effectiveness on the subgrade. This study introduces a design method for an Intelligent Adjustment Ventilation Embankment (IAVE) system that dynamically adjusts the ventilation status within the duct based on variations in ground and air temperatures. Numerical simulations were performed to compare the cooling performance and differential settlement control of the Normal Ventilation Embankment (NVE), Temperature-Controlled Ventilation Embankment (TCVE), and IAVE systems. The results demonstrated that, compared to NVE and TCVE, the IAVE system achieved more precise temperature regulation, optimized the use of environmental cooling energy, and exhibited superior long-term cooling and differential settlement control. Among the three main factors influencing IAVE performance—ventilation duct burial spacing, burial depth, and airflow velocity—the burial spacing has the most significant impact on the Artificial Permafrost Table (APT). It not only enhances cooling during cold seasons but also effectively mitigates the re-warming of the subgrade during warm seasons. This research offers an efficient, low-carbon energy utilization structure and provides calculation results to improve the thermal stability of engineering projects in cold regions.

Coronary artery fistulas (CAFs) are rare congenital heart defects that are typically managed through interventional closure, traditional surgery, or minimally invasive hybrid closure surgery. However, treating CAFs with complex anatomy, such as tortuous vessels, presents a significant challenge, particularly in young children. We report the case of a 3.8-year-old child (15 kg/100 cm) with a complex CAF, treated using a minimally invasive hybrid closure surgery approach with a 4 × 4 mm Amplatzer Duct Occluder II (ADO II) (Abbott, USA). Three-dimensional (3D) imaging was utilized to visualize the CAF's anatomy, guide the surgical planning, and accurately determine the puncture site on the right ventricular free wall, as well as the optimal sheath direction and insertion depth. The procedure was carried out efficiently and safely, guided by preoperative 3D imaging and intraoperative transesophageal echocardiography. Follow-up at one year demonstrated excellent outcomes with no complications.

Abstract Background Metabolic syndrome (MetS) presents a notable public health challenge on a global scale, exerting a considerable impact on individuals’ health and quality of life. There is mounting evidence indicating a robust association between MetS and levels of sex hormones. Therefore, the study aims to explore the relationship between sex hormone binding-globulin (SHBG) and MetS, and to provide evidence that could inform the development of effective prevention strategies for MetS. Methods Data for this cross-sectional investigation were collected during the 2013–2016 cycle of the National Health and Nutrition Examination Survey (NHANES), from which 5,499 adults were sampled. The criteria established by the Adult Treatment Program III of the National Cholesterol Education Program were utilized to define MetS. SHBG levels were measured using a standardized technique. Multivariate-adjusted logistic regression, multivariate restricted cubic spline, and threshold effect analyses were utilized to investigate the association between SHBG levels and MetS. Moreover, the stratified analyses and interaction tests of covariables were presented in a forest plot. Finally, sensitivity analysis was utilized to ensure the robustness of the results. Results Overall, 1822 participants had MetS. After adjusting for possible confounders, SHBG levels were associated with MetS (Odds ratio [OR], 0.984; 95% confidence interval [CI], 0.981–0.986; P

Abstract Heat delivered by the ocean circulation is melting the Antarctic ice sheet from below. This melt is largest where warm Circumpolar Deep Water accesses the continental shelf and reaches the ice shelf cavities. Future melt rate projections are based on ocean thermal forcing derived from climate models, which tend to be biased warm around Antarctica. The bias has been attributed to unresolved ocean processes that occur at scales poorly represented in models. Using a high-resolution model of the Denman Glacier region we show that seafloor roughness unresolved in climate models suppresses the impact of warm water on ice sheet melting. Seafloor roughness slows down the shelf circulation, reducing the presence of warm water over the shelf and the heat transport towards the ice cavities. As a result, the total meltwater discharge drops by 4 Gt year−1. Our results suggest a mechanism missing in global ocean and climate models that could reduce the spread in climate projections.

Abstract During the restoration of iron cultural relics, the removal of rust from these artifacts is necessary. However, this rust removal process may lead to inconsistent local color on the iron relics. To address this, mending materials are applied to treat the surface, ensuring consistent local color. In the surface treatment of iron cultural relics, a significant challenge lies in modulating the color of these mending materials. The corrosion products of Yuquan Iron Pagoda are mainly Fe3O4, γ-FeO(OH), α-FeO(OH) and α-Fe2O3, with contents of 13.1, 16.1, 40.2 and 30.6%, respectively. Due to their structural stability and suitable color characteristics, Fe3O4 and α-Fe2O3 are selected as the primary raw materials for the repair material. This study employs machine learning methods to predict the color of mending materials corresponding to varying contents of α-Fe2O3, Fe3O4, and epoxy resin. The Artificial Neural Network (ANN), eXtreme Gradient Boosting (XGBoost), and Light Gradient Boost Machine (LightGBM) algorithms are utilized to develop the model, and the predictive performance of these three algorithms is compared. XGBoost exhibits the best prediction performance, achieving a square correlation coefficient (R2) of 0.94238 and a mean absolute error (MAE) of 0.68485. Additionally, the SHapley Additive exPlanations (SHAP) method is employed to analyze the most crucial raw material affecting the color of mending materials, which is identified as Fe3O4. The study illustrates the specific process of employing this model by applying it to the surface treatment of the Yuquan Iron Pagoda, demonstrating the practicality of the model. This model can be applied to assist in the surface treatment of other iron cultural relics.

Highlights A series of layered oxide cathode materials were synthesized by high-temperature shock strategy for the first time. The approaching ultimate solid reaction rate of the layered nickel-rich layered oxide LiNixCoyMnzO2 was investigated for the first time. Ultrafast average reaction rate of phase transition from Ni0.6Co0.2Mn0.2(OH)2 to Li-containing oxides is 66.7 (% s-1), that is, taking only 1.5 s.

BackgroundMetabolic syndrome (MetS) has a close association with cardiovascular diseases. Few studies have investigated the association of Life’s Essential 8 (LE8), the updated measurement of cardiovascular health (CVH), with MetS.MethodsThe National Health and Nutrition Examination Survey (2005–2018) data was extracted. The LE8 comprised 4 health behaviors (diet, physical activity, nicotine exposure, and sleep health) and 4 health factors [body mass index (BMI), blood lipids, blood glucose, and blood pressure (BP)]. The total LE8 score is the average of 8 metric scores (0-100), categorized into low (0–49), moderate (50–79), and high CVH (80–100) levels. Multivariable logistic regression models, restricted cubic spline models and stratified analyses were performed to examine the relationship between LE8 and MetS.ResultsIn this study, a total of 21,543 participants represented 146.6 million non-institutionalized U.S. adults. Following adjustment for various potential covariates, participants who attained a moderate [adjusted odds ratio (AOR) = 0.234, 95% CI: 0.209, 0.262] or a high CVH level (AOR = 0.026, 95% CI: 0.021, 0.032) exhibited an inverse correlation with MetS risks when comparing those with a low CVH level. An inverse linear dose-response relationship between LE8 scores and MetS risks was also identified (P for nonlinearity > 0.05).ConclusionsLE8 was inversely associated with the risk of MetS. Adhering to LE8 guidelines to sustain a higher CVH level may be beneficial for preventing MetS.

Dimensional data directly reflects the growth rate of individual fish, an important economic trait of interest to fish researchers. Efficiently obtaining large-scale fish dimension data would be valuable for both selective breeding and production. To address this, our study proposes a custom dimension measurement method for fish using the YOLOv5-keypoint framework with multi-attention mechanisms. We optimized the YOLOv5 framework, incorporated the SimAM attention mechanism to achieve more accurate and faster fish detection, and added customizable landmarks to the network structure, enabling flexible configuration of the number and location of feature points in the training dataset. This method is applicable to various aquacultural species and other objects. We tested the effectiveness of the method using the economically important grass carp (Ctenopharyngodon idella). The proposed method outperforms pure YOLOv5, Faster R-CNN, and SSD in terms of precision and recall rates, achieving an impressive average precision of 0.9781. Notably, field trials confirmed the method's exceptional measurement accuracy, exceeding 97% compatibility with manual measurements, while demonstrating a real-time speed of 38 frames per second on the NVIDIA RTX A4000. This enables efficient and accurate large-scale surface dimension measurements of economic fish. To facilitate massive measurements in agricultural research, we have implemented this method as an online platform, called Mode-recognition Ruler (MrRuler, http://bioinfo.ihb.ac.cn/mrruler). The platform identifies objects in a single image at an average speed of 0.486 ​± ​0.005 ​s, based on a dataset of 10,000 images. MrRuler includes two preset carp models and allows users to upload training datasets for custom models of their targets of interest.

Disuse osteoporosis (OP) is a state of bone loss due to lack of mechanical stimuli, probably induced by prolonged bed rest, neurological diseases, as well as microgravity. Currently the precise treatment strategies of disuse OP remain largely unexplored. Piezo1, a mechanosensitive calcium (Ca2+) ion channel, is a key force sensor mediating mechanotransduction and it is demonstrated to regulate bone homeostasis and osteogenesis in response to mechanical forces. Using structure‐based drug design, a novel small‐molecule Piezo1 agonist, MCB‐22‐174, which can effectively activate Piezo1 and initiate Ca2+ influx, is developed and is more potent than the canonical Piezo1 agonist, Yoda1. Moreover, MCB‐22‐174 is found as a safe Piezo1 agonist without any signs of serious toxicity. Mechanistically, Piezo1 activation promotes the proliferation of bone marrow mesenchymal stem cells by activating the Ca2+‐related extracellular signal‐related kinases and calcium–calmodulin (CaM)‐dependent protein kinase II (CaMKII) pathway. Importantly, MCB‐22‐174 could effectively promote osteogenesis and attenuate disuse OP in vivo. Overall, the findings provide a promising therapeutic strategy for disuse OP by chemical activation of Piezo1.

This paper reports a strategy for more reliably obtaining sputtered thin yttrium–iron–garnet (YIG) films possessing both low magnetic damping (α) and a highly spin transparent surface, which represent two of the most important properties for YIG films applied in spintronic devices. The two key points of this strategy, concluded from our systematical studies, are as follows: oxygen reactive sputtering of a slight Y-rich YIG target to avoid the over-stoichiometry of the Fe component and at the same time minimize oxygen vacancy density; and employing phosphoric acid wet etching to remove the inevitable thin magnetic dead layer formed on the surface. The feasibility of this strategy was proved by the achievement of a high quality 30 nm-thick YIG film. It possesses a ferromagnetic resonance linewidth of only 3.4 Oe at 8 GHz, α of only 4.6 × 10−4, and a very spin-transparent surface, as proved by the measured extremely large spin pumping voltage of 650.1 µV after depositing a 3 nm Pt layer.

Abstract Halogenation of Y‐series small‐molecule acceptors (Y‐SMAs) is identified as an effective strategy to optimize photoelectric properties for achieving improved power‐conversion‐efficiencies (PCEs) in binary organic solar cells (OSCs). However, the effect of different halogenation in the 2D‐structured large π‐fused core of guest Y‐SMAs on ternary OSCs has not yet been systematically studied. Herein, four 2D‐conjugated Y‐SMAs (X‐QTP‐4F, including halogen‐free H‐QTP‐4F, chlorinated Cl‐QTP‐4F, brominated Br‐QTP‐4F, and iodinated I‐QTP‐4F) by attaching different halogens into 2D‐conjugation extended dibenzo[f,h]quinoxaline core are developed. Among these X‐QTP‐4F, Cl‐QTP‐4F has a higher absorption coefficient, optimized molecular crystallinity and packing, suitable cascade energy levels, and complementary absorption with PM6:L8‐BO host. Moreover, among ternary PM6:L8‐BO:X‐QTP‐4F blends, PM6:L8‐BO:Cl‐QTP‐4F obtains a more uniform and size‐suitable fibrillary network morphology, improved molecular crystallinity and packing, as well as optimized vertical phase distribution, thus boosting charge generation, transport, extraction, and suppressing energy loss of OSCs. Consequently, the PM6:L8‐BO:Cl‐QTP‐4F‐based OSCs achieve a 19.0% efficiency, which is among the state‐of‐the‐art OSCs based on 2D‐conjugated Y‐SMAs and superior to these devices based on PM6:L8‐BO host (17.70%) and with guests of H‐QTP‐4F (18.23%), Br‐QTP‐4F (18.39%), and I‐QTP‐4F (17.62%). The work indicates that halogenation in 2D‐structured dibenzo[f,h]quinoxaline core of Y‐SMAs guests is a promising strategy to gain efficient ternary OSCs.

This is an article in the field of ceramics and composites. Montmorillonite organic gel is a thixotropic gel, which is usually produced by wet process. It needs to be spray drying to obtain gel products. However, the drying cost accounts for the major part of the production cost due to the low efficiency and high energy consumption of spray drying. Therefore, it is of great importance to reduce the energy consumption in the process of dehydration. A new type of pre dehydration process with low energy consumption is proposed in this paper. A non-metallic mineral material with high specific surface area and good water absorption is filled into the dehydrated tank. The montmorillonite organic gel is injected into the dehydrated tank and stirred well to achieve the purpose of pre dehydration. The high-quality organic gel product is then obtained by spray drying. The special process for the pre-dewatering process is designed and the energy consumption of the pre-drying process and the spray drying process without pre dehydration are compared by thermal calculation. The results show that the pre dehydration process can save about 58% energy compared with the existing process.

Abstract Electrochemical carbon dioxide/carbon monoxide reduction reaction offers a promising route to synthesize fuels and value-added chemicals, unfortunately their activities and selectivities remain unsatisfactory. Here, we present a general surface molecular tuning strategy by modifying Cu2O with a molecular pyridine-derivative. The surface modified Cu2O nanocubes by 4-mercaptopyridine display a high Faradaic efficiency of greater than 60% in electrochemical carbon monoxide reduction reaction to acetate with a current density as large as 380 mA/cm2 in a liquid electrolyte flow cell. In-situ attenuated total reflectance surface-enhanced infrared absorption spectroscopy reveals stronger *CO signal with bridge configuration and stronger *OCCHO signal over modified Cu2O nanocubes by 4-mercaptopyridine than unmodified Cu2O nanocubes during electrochemical CO reduction. Density function theory calculations disclose that local molecular tuning can effectively regulate the electronic structure of copper catalyst, enhancing *CO and *CHO intermediates adsorption by the stabilization effect through hydrogen bonding, which can greatly promote asymmetric *CO-*CHO coupling in electrochemical carbon monoxide reduction reaction.

Objective: Systematically evaluate the efficacy of (1) isosorbide mononitrate sustained-release capsules combined with conventional therapy and (2) conventional therapy alone in the treatment of angina pectoris and analyze their economic value to provide evidence and a reference for clinical medication and decision-making. Methods: Randomized controlled trials on the efficacy of isosorbide mononitrate sustained-release capsules combined with conventional therapy and conventional therapy in the treatment of angina pectoris were searched and abstracted from major Chinese and English literature databases from August 26, 2003 to August 26, 2023, to calculate the rate of improvement in clinical symptoms using isosorbide mononitrate sustained-release capsules combined with conventional therapy (observation group) and using conventional therapy alone (control group). Review Manager 5.4 software was used for meta-analysis, and an economic evaluation was performed using cost-effectiveness analysis (CEA). Results: The effectiveness rates for clinical symptom improvement were 95% in the observation group and 78% in the control group. According to the meta-analysis results, the efficiency of clinical symptom improvement in the observation group, which received the combination therapy with isosorbide mononitrate sustained-release capsules, was significantly better than that of the control group (OR ​= ​3.38, 95% CI: 2.28 to 4.99, P ​

Introduction Smoking prevalence is high in China, and healthcare workers are important for tobacco control. This study aimed to determine the smoking status, cognition of tobacco hazards, and smoking cessation-related knowledge among respiratory healthcare workers, and to explore their ability to provide smoking cessation assistance. Methods A cross-sectional study was conducted in 2021 among 1028 respiratory healthcare workers from 89 hospitals in Fujian Province, China. A self-designed electronic questionnaire was used to collect data on smoking status, knowledge of smoking hazards, and smoking cessation knowledge. Descriptive statistics were calculated for all questions. Logistic regression analysis was used to explore the relationship between awareness of the tobacco control goals of Healthy China 2030 and demographic characteristics. Results Among the healthcare workers surveyed, 3.4% were smokers, all of whom were male. Most respondents (99.4%) were aware of smoking as a cause of lung cancer, but awareness of smoking as a cause of non-respiratory cancer was lower. The awareness rate of smoking cessation support was high (>90%), but only 40.0% of participants were aware of the Healthy China 2030 tobacco control targets. Male (HR=2.16; 95% CI: 1.69–2.80) and participation in the cessation clinic (HR=1.47; 95% CI: 1.10–1.96) were associated with higher awareness of the targets. Conclusions Respiratory healthcare workers in Fujian Province demonstrated a high level of awareness regarding behavioral and pharmacotherapy support for smoking cessation. In order to enable healthcare workers to play a more active role in tobacco control, there is a need to increase public awareness of smoking cessation services in Fujian Province.

Abstract Water splitting is a critical process for the production of green hydrogen, contributing to the advancement of a circular economy. However, the application of water splitting devices on a large scale is primarily impeded by the sluggish oxygen evolution reaction (OER) at the anode. Thus, developing and designing efficient OER catalysts is a significant target. NiFe‐based catalysts are extensively researched as excellent OER electrocatalysts due to their affordability, abundant reserves, and intrinsic activities. However, they still suffer from long‐term stability challenges. To date, few systematic strategies for improving OER durability have been reported. In this review, various advanced NiFe‐based catalysts are introduced. Moreover, the OER stability challenges of NiFe‐based electrocatalysts in alkaline media, including iron segregation, structural degradation, and peeling from the substrate are summarized. More importantly, strategies to enhance OER stability are highlighted and opportunities are discussed to facilitate future stability studies for alkaline water electrolysis. This review presents a design strategy for NiFe‐based electrocatalysts and anion exchange membrane (AEM) electrolyzers to overcome stability challenges in OER, which also emphasizes the importance of long‐term stability in alkaline media and its significance for achieving large‐scale commercialization.

Abstract Osteoarthritis (OA) is a common degenerative disease worldwide and new therapeutics that target inflammation and the crosstalk between immunocytes and chondrocytes are being developed to prevent and treat OA. These attempts involve repolarizing pro-inflammatory M1 macrophages into the anti-inflammatory M2 phenotype in synovium. In this study, we found that phosphoglycerate mutase 5 (PGAM5) significantly increased in macrophages in OA synovium compared to controls based on histology of human samples and single-cell RNA sequencing results of mice models. To address the role of PGAM5 in macrophages in OA, we found conditional knockout of PGAM5 in macrophages greatly alleviated OA symptoms and promoted anabolic metabolism of chondrocytes in vitro and in vivo. Mechanistically, we found that PGAM5 enhanced M1 polarization via AKT-mTOR/p38/ERK pathways, whereas inhibited M2 polarization via STAT6-PPARγ pathway in murine bone marrow-derived macrophages. Furthermore, we found that PGAM5 directly dephosphorylated Dishevelled Segment Polarity Protein 2 (DVL2) which resulted in the inhibition of β-catenin and repolarization of M2 macrophages into M1 macrophages. Conditional knockout of both PGAM5 and β-catenin in macrophages significantly exacerbated osteoarthritis compared to PGAM5-deficient mice. Motivated by these findings, we successfully designed mannose modified fluoropolymers combined with siPGAM5 to inhibit PGAM5 specifically in synovial macrophages via intra-articular injection, which possessed desired targeting abilities of synovial macrophages and greatly attenuated murine osteoarthritis. Collectively, these findings defined a key role for PGAM5 in orchestrating macrophage polarization and provides insights into novel macrophage-targeted strategy for treating OA.

Highlights A stable Zn anode was obtained by patterning Zn foil surfaces and endowing a zincphilic interface in microchannels. The accumulation of electrons in the microchannel and the zincphilic interface promoted preferential heteroepitaxial Zn deposition in the microchannel region and subsequent homoepitaxial Zn deposition on the array surface. The Zn symmetrical cells could undergo repeated plating/stripping for more than 25,000 cycles at the current densities of 10 and 20 mA cm−2.

Objective Rutin, also called vitamin P, is a flavonoids from plants. Previous studies have indicated that rutin can alleviate the injury of tissues and cells by inhibiting oxidative stress and ameliorating inflammation. There is no report on the protective effects of rutin on goat rumen epithelial cells (GRECs) at present. Hence, we investigated whether rutin can alleviate lipopolysaccharide (LPS)-induced damage in GRECs. Methods GRECs were cultured in basal medium or basal medium containing 1 μg/mL LPS, or 1 μg/mL LPS and 20 μg/mL rutin. Six replicates were performed for each group. After 3-h culture, the GRECs were harvested to detect the relevant parameters. Results Rutin significantly enhanced the cell activity (p

This study investigates whether ketoconazole, a CYP3A4 inhibitor, can enhance the suppressive effects of quinestrol on reproductive capacity, potentially allowing for a reduced quinestrol dosage while maintaining its efficacy. A total of 104 healthy adult male mice were divided into two groups, assessed at 10 and 30 days. Within each group, six treatment categories were tested: the control (CK), quinestrol alone (Q1, Q5), and quinestrol combined with varying doses of ketoconazole (Q1 + K0.4, Q1 + K2, Q5 + K0.4). The key parameters measured included internal and reproductive organ weights, sperm density, sperm motility, sperm abnormalities, and CYP3A4 enzyme content in intestinal and liver tissues. After 10 days, the combination of a low dose of quinestrol with ketoconazole (Q1 + K0.4) showed the most significant pronounced effects in reducing reproductive potential, with notable reductions in epididymal weight, sperm density, sperm abnormality rate and vitality, serum hormone levels, and CYP3A4 content in the small intestine and liver. Although some reproductive parameters returned to near-baseline levels after 30 days, the Q1 + K0.4 regimen continued to exhibit reduced seminal vesicle weight and testosterone levels. Importantly, the combination did not significantly increase CYP3A4 enzyme content, indicating effective metabolic inhibition. The combination of quinestrol and ketoconazole, especially the Q1 + K0.4 regimen, demonstrated the most noticeable impact on reducing reproductive capacity. This regimen significantly reduced key reproductive parameters and showed strong metabolic inhibition, suggesting that ketoconazole substantially enhances the efficacy of quinestrol in fertility control.

Land subsidence (LS) is a geological hazard driven by both natural conditions and human activities. Traditional LS time-series prediction models often struggle to accurately capture nonlinear data characteristics, leading to suboptimal predictions. To address this issue, this paper introduces a multi-component temporal convolutional gate recurrent unit (MC-TCGRU) model, which integrates a fully adaptive noise-ensemble empirical-mode decomposition algorithm with a deep neural network to account for the complexity of time-series data. The model was validated using typical InSAR subsidence data from Kunming, analyzing the impact of each component on the prediction performance. A comparative analysis with the TCGRU model and models based on seasonal-trend decomposition using LOESS (STL) and empirical-mode decomposition (EMD) revealed that the MC-TCGRU model significantly enhanced the prediction accuracy by reducing the complexity of the original data. The model achieved R² values of 0.90, 0.93, 0.51, 0.93, and 0.96 across five points, outperforming the compared models.

BackgroundAn accumulating body of research indicates that the pons is related to the occurrence of depression. Si-Ni-San (SNS) is a well-known Chinese herbal formula that is used to treat depression. Chinese herbal formulae have multiple therapeutic characteristics. Although it has been proven that SNS can exert antidepressant effects by improving changes in the limbic system, it is currently unclear whether SNS has therapeutic targets in the pons. This study aimed to explore the therapeutic targets of SNS in the pons for depression treatment.Materials and methodsTwo experiments were conducted. In Experiment 1, 32 rats were divided into four groups: (1) a Control (C) group that received distilled water as a vehicle; (2) a Model (M) group that received the chronic unpredictable mild stress (CUMS) procedure and was administered distilled water; (3) a Stress + SNS (MS) group that received the CUMS procedure and was administered SNS dissolved in distilled water; and (4) a Stress + Fluoxetine (MF) group that received the CUMS procedure and was administered fluoxetine dissolved in distilled water. The open field test (OFT), the sucrose preference test (SPT), and the novel object recognition test (NOR) were performed to test the antidepressant effects of SNS. High-throughput mRNA sequencing (RNA-seq) was used to explore possible gene targets of SNS in the pons, and quantitative real-time PCR was performed to verify the results. High-performance liquid chromatography was used to detect neurotransmitters. Finally, correlation analyses were conducted between behaviors, genes expression, and neurotransmitters. In Experiment 2, 18 rats were divided into the same three groups as in Experiment 1: (1) C, (2) M, and (3) MS. fMRI was used to confirm whether SNS altered the pons in a rat model of depression.ResultsSNS significantly improved sucrose preference in the SPT and TN-TO in the NOR compared to the M group (P < 0.05). RNA-seq filtered 49 differentially expressed genes(DEGs) that SNS could reverse in the pons of the CUMS depression model. Real-time PCR detected six genes, including Complexin2 (Cplx2), Serpinf1, Neuregulin1 (Nrg1), Annexin A1 (Anxa1), β-arrestin 1 (Arrb1) and presenilin 1 (Psen1). SNS significantly reversed changes in the expression of Anxa1, Nrg1, and Psen1 caused by CUMS (P < 0.05), which is consistent with the DEGs results. Additionally, SNS significantly reversed norepinephrine (NE) changes in the pons. There were 18 noteworthy correlations between behavior, genes, and neurotransmitters (P < 0.05). fMRI showed that SNS can decrease the amplitude of low-frequency fluctuations (ALFF) in the pons of living depressed rats.ConclusionThe pons is an important target brain region for SNS to exert its antidepressant effects. SNS may improve pontine NE levels by regulating the Anxa1, Nrg1, and Psen1 genes, thereby exerting antidepressant effects and improving cognitive function.

Abstract To investigate the clinical characteristics of febrile infection‐related epilepsy syndrome (FIRES). We used trajectory analysis and logistic regression analysis to investigate the clinical characteristics and prognostic risk factors respectively. Twenty‐seven patients (16 males) were included. The median age of onset was 7 (IQR: 4–9) years. Routine cerebrospinal fluid (CSF) examination was normal. Electroencephalogram (EEG) showed frequent microseizures and electroseizures in all patients. Eight patients had claustrum signs in the acute phase. Anesthetics and anti‐seizure medications (ASM) were used in all patients. All patients received immunotherapy, including plasma exchange (n = 4), immunoglobulin (n = 26), and corticosteroids (n = 19). Trajectory diagrams of seizure showed 6 patients had bimodal disease course. Besides, we found there may be a linear relationship between body temperature and convulsion frequency (R2 = 0.25). The median Glasgow outcome scale (GOS) was 3 (IQR: 1–4). Nine deaths occurred, including abandonment of treatment (n = 3), hemodynamic instability (n = 3), brain hernia (n = 2), and brain hernia with hemodynamic instability (n = 1). Seizure onset combined with fever (p = 0.003), periodic discharge (p = 0.002), and non‐ketogenic diet (non‐KD) (p = 0.005) were independent risk factors for death. The KD group (n = 10) had lower mortality (p = 0.009), lower convulsion frequency at latest follow‐up (p

Objective: The primary objective of this study was to investigate the immediate effects of two doses (Dose1 and Dose2,D1 and D2) of inertial Flywheel Eccentric Overload (FEOL), Eccentric Hook (EH), and High-intensity Half Squat (HHS) on muscle explosiveness in male sprinters. Methods: Twenty-one sub-elite male sprinters were randomly assigned to three groups: the FEOL group (n=7), the EH group (n=7), and the HSS group (n=7),Measurements of athletes' explosive jumps (CMJ, SJ, SLJ) heights, relative peak power indices, and 30-m sprint times were collected before and 6 min after the intervention. Results: At D1 loading dose, CMJ, SJ jump height, and relative peak power increased significantly (p 0.05). At D2 loading dose, CMJ, SJ jump height, and relative peak power increased significantly (p 0.05). CMJ vertical jump height and relative peak power were significantly higher after D2FEOL and D2EH interventions than after D1HHS (P

Methamphetamine is a potent and highly addictive neurotoxic psychostimulant that triggers a spectrum of adverse emotional responses during withdrawal. G-protein coupled receptor 55 (GPR55), a novel endocannabinoid receptor, is closely associated with mood regulation. Herein, we developed a murine model of methamphetamine-induced anxiety- and depressive-like behavior during abstinence which showed a decreased GPR55 expression in the hippocampus. Activation of GPR55 mitigated these behavioral symptoms, concomitantly ameliorating impairments in hippocampal neurogenesis and reducing neuroinflammation. These findings underscore the pivotal role of GPR55 in mediating the neuropsychological consequences of methamphetamine withdrawal, potentially via mechanisms involving the modulation of hippocampal neurogenesis and inflammation.

Objective: To report a patient of pseudoaneurysm of carotid artery caused by brucellosis infection and improve the recognition, diagnosis and treatment of this disease. Methods: The etiology, clinical data and treatment of false aneurysm were reviewed A 75-year-old man with a high probability of pseudoaneurysm of the left common carotid artery was found by enhanced CT. Open surgery was performed. Bacterial culture return was Brucella. After regular oral drug treatment, the patient recovered well. Results: The patient recovered well after surgery and took oral medication regularly for 3 months without recurrence. Conclusion: Pseudoaneurysms of the carotid artery caused by brucella infection are very rare, and correct diagnosis and open surgery combined with drug therapy are the best choices.

Large Language Models (LLMs) have demonstrated remarkable performance across various natural language tasks, marking significant strides towards general artificial intelligence. While general artificial intelligence is leveraged by developing increasingly large-scale models, there could be another branch to develop lightweight custom models that better serve certain domains, taking into account the high cost of training and deploying LLMs and the scarcity of resources. In this paper, we present MindLLM, a novel series of bilingual lightweight large language models, trained from scratch, alleviating such burdens by offering models with 1.3 billion and 3 billion parameters. A thorough account of experiences accrued during large model development is given, covering every step of the process, including data construction, model architecture, evaluation, and applications. Such insights are hopefully valuable for fellow academics and developers. MindLLM consistently matches or surpasses the performance of other open-source larger models on some public benchmarks. We also introduce an innovative instruction tuning framework tailored for smaller models to enhance their capabilities efficiently. Moreover, we explore the application of MindLLM in specific vertical domains such as law and finance, underscoring the agility and adaptability of our lightweight models.

Abstract Background Corybas taliensis is an endemic species of sky islands in China. Its habitat is fragile and unstable, and it is likely that the species is threatened. However, it is difficult to determine the conservation priority or unit without knowing the genetic background and the overall distribution of this species. In this study, we used double digest restriction-site associated DNA-sequencing (ddRAD-seq) to investigate the conservation genomics of C. taliensis. At the same time, we modeled the extent of suitable habitat for C. taliensis in present and future (2030 and 2090) habitat using the maximum-entropy (MaxEnt) model. Results The results suggested that the related C. fanjingshanensis belongs to C. taliensis and should not be considered a separate species. All the sampling locations were divided into three genetic groups: the Sichuan & Guizhou population (SG population), the Hengduan Mountains population (HD population) and Himalayan population (HM population), and we found that there was complex gene flow between the sampling locations of HD population. MT was distinct genetically from the other sampling locations due to the unique environment in Motuo. The genetic diversity (π, H e ) of C. taliensis was relatively high, but its contemporary effective population size (N e ) was small. C. taliensis might be currently affected by inbreeding depression, although its large population density may be able to reduce the effect of this. The predicted areas of suitable habitat currently found in higher mountains will not change significantly in the future, and these suitable habitats are predicted to spread to other higher mountains under future climate change. However, suitable habitat in relatively low altitude areas may disappear in the future. This suggests that C. taliensis will be caught in a ‘summit trap’ in low altitude areas, however, in contrast, the high altitude of the Himalaya and the Hengduan Mountains are predicted to act as ‘biological refuges’ for C. taliensis in the future. Conclusions These results not only provide a new understanding of the genetic background and potential resource distribution of C. taliensis, but also lay the foundation for its conservation and management.

Abstract Background Chlamydia pneumoniae (Cpn) IgG and IgA has been strongly linked to lung cancer, but its impact on patients' quality of life remains unclear. Our objective was to investigate the relationship between pre-treatment Cpn IgG and IgA and time to deterioration (TTD) of the HRQoL in patients with primary lung cancer. Methods A prospective hospital-based study was conducted from June 2017 to December 2018, enrolling 82 patients with primary lung cancer admitted to the First Affiliated Hospital of Fujian Medical University for questionnaire surveys. Cpn IgG and IgA was detected by microimmunofluorescence method. HRQoL was assessed at baseline and during follow-up using the EORTC Quality of Life Questionnaire version 3.0 (EORTC QLQ-C30) and EORTC Quality of Life Questionnaire-Lung Cancer (EORTC QLQ-LC13). HRQoL scores were calculated using the QoLR package, and TTD events were determined (minimum clinically significant difference = 5 points). Cox regression analysis was used to evaluate the effect of Cpn IgG and IgA on HRQoL. Results We investigated the relationship between Cpn IgG and IgA and quality of life in patients with primary lung cancer. The study was found that 75.61% of cases were Cpn IgG + and 45.12% were Cpn IgA + . Cpn IgA + IgG + was 41.46%. For EORTC QLQ-C30, Physical function (PF) and Pain (PA) TTD events on the functional scale and Symptom scale were the most common during follow-up. After adjusting for gender and smoking status, Pre-treatment Cpn IgA + was found to signifcantly delay TTD of Physical functioning(HR = 0.539, 95% CI: 0.291–0.996, P = 0.048). In addition, Cpn IgG + before treatment significantly delayed TTD in Emotional functioning (HR = 0.310, 95% CI: 0.115–0.836, P = 0.021). For EORTC QLQ-LC13, deterioration of dyspnea (LC-DY) was the most common event. However, Cpn IgG and IgA before treatment had no effect on the TTD of EORTC QLQ-LC13 items. Conclusions According to EORTC QLQ-C30 and EORTC QLQ-LC13, Cpn IgA delayed TTD in Physical functioning and Cpn IgG delayed TTD in Emotional functioning.

Fast charging technologies are now being developed, and the challenge of an efficient heat management solution for the charging module is aggravated. The transient thermal analysis model is firstly given to evaluate the novel thermal management system for the high power fast charging pile. Results show that adding the PCM into the thermal management system limits its thermal management performance in larger air convective coefficient and higher ambient temperature. However, applying the PCM exhibit a beneficial effect in the various liquid convective coefficients and heat generation powers. Increasing the liquid convective coefficient from 1098 W/(m2 K) to 2557 W/(m2 K), a highest temperature reduction of 27.01 °C is found. Adding the PCM to the thermal management system gives a maximum temperature reduction of 4.88 °C as the heat generation power increases from 60 W to 120 W, and the highest temperature of the charging module reduces from 100.05 °C to 94.29 °C with a decrease in maximum temperature of 5.76 °C as the shell emissivity increases from 0.1 to 0.9. A suitable PCM melting temperature is effective in controlling the temperature range of the charging module. These results will provide guidelines for the thermal management design of charging module, which is crucial for advancing the electric vehicles (EVs) adoption.

Diabetes mellitus is a chronic disease that affects over 500 million people worldwide, necessitating personalized health management programs for effective long-term control. Among the various biomarkers, glycated hemoglobin (HbA1c) is a crucial indicator for monitoring long-term blood glucose levels and assessing diabetes progression. This study introduces an innovative approach to diabetes management by integrating a mobile application and machine learning. We designed and implemented an intelligent application capable of collecting comprehensive data from diabetic patients, creating a novel diabetes dataset named DiabMini with 127 features of 88 instances, including medical information, personal information, and detailed nutrient intake and lifestyle. Leveraging the DiabMini, we focused the analysis on HbA1c dynamics due to their clinical significance in tracking diabetes progression. We developed a stacking model combining eXtreme Gradient Boosting (XGBoost), Support Vector Classifier (SVC), Extra Trees (ET), and K-Nearest Neighbors (KNN) to explore the impact of various influencing factors on HbA1c dynamics, which achieved a classification accuracy of 94.23%. Additionally, we applied SHapley Additive exPlanations (SHAP) to visualize the contributions of risk factors to HbA1c dynamics, thus clarifying the differential impacts of these factors on diabetes progression. In conclusion, this study demonstrates the potential of integrating mobile health applications with machine learning to enhance personalized diabetes management.

Mobile fans, as flexible and convenient new longitudinal ventilation and smoke extraction equipment for tunnels, demonstrate more significant effectiveness in an emergency response to tunnel fires compared to traditional smoke extraction methods. This study employs computational fluid dynamics simulation methods, selecting two fire scenarios to investigate the effects of fan inclined angles and fan airflow volumes on the longitudinal temperature distribution and smoke back-layering length in tunnels. The results indicate that when using mobile fans for longitudinal ventilation in tunnels, at a lower fan airflow volume, the temperature distribution along the longitudinal axis is nearly symmetrical. The fire source and the fan installed in the upstream are within a certain range, and it is more effective to use the horizontal angle for longitudinal ventilation. As the fan airflow volume increases, the back-layering length significantly decreases (210,000 m3/h < V < 270,000 m3/h). However, as the fan flow volume continues to increase (270,000 m3/h < V < 300,000 m3/h), the reduction in the back-layering length becomes less pronounced, the smoke spread distance of the latter is only 11% of that of the former. Therefore, selecting appropriate fan airflow volumes and fan inclined angles them can effectively enhance the performance of tunnel smoke extraction systems. Moreover, by comparing with traditional fans, we find that mobile fans provide an alternative effective strategy during firefighting by allowing adjustments in distance from the fire source and fan inclination angles, enhancing fire suppression effectiveness while reducing energy losses. The research findings can serve as a reference for tunnel fire prevention design.

This paper proposes a dual-parameter strain/displacement safety monitoring technology for railway tunnel lining structures. An integrated monitoring system with FBG (Fiber Bragg grating) and VDM (video displacement meter) components was used to monitor both the strain and deformation of the tunnel cross-section. Initially, a comprehensive experimental study was carried out using FBG strain sensors with temperature-compensated grating. The temperature-compensated grating was used to further improve the monitoring accuracy. The data show that the stability and accuracy were better than the traditional electronic strain sensor. Secondly, high-precision and multipoint monitoring of railway tunnel lining deformation was achieved by using VDM technology. Three months of case study results taken from the Gansu Railway Tunnel in China demonstrated a tunnel cross-section strain accuracy for microstrain and crown deformation at the submillimeter level, respectively. The technology provides a new high-precision way to monitor the condition of tunnel lining structures.

This study aimed to evaluate and compare the effects of inertial flywheel training and accentuated eccentric loading training on the neuromuscular performance of well-trained male college sprinters. Fourteen sprinters were recruited and randomly assigned to either the flywheel training (FWT, n = 7) group or the accentuated eccentric loading training (AELT, n = 7) group. The FWT group completed four sets of 2 + 7 repetitions of flywheel squats, whereas the AELT group performed four sets of seven repetitions of barbell squats (concentric/eccentric: 80%/120% 1RM). Both groups underwent an eight-week squat training program, with two sessions per week. A two-way repeated ANOVA analysis was used to find differences between the two groups and between the two testing times (pre-test vs. post-test). The results indicated significant improvements in all measured variables for the FWT group: 1RM (5.0%, ES = 1.28), CMJ (13.3%, ES = 5.42), SJ (6.0%, ES = 2.94), EUR (6.5%, ES = 4.42), SLJ (2.9%, ES = 1.77), and 30 m sprint (−3.4%, ES = −2.80); and for the AELT group: 1RM (6.3%, ES = 2.53), CMJ (7.4%, ES = 3.44), SJ (6.4%, ES = 2.21), SLJ (2.2%, ES = 1.20), and 30 m sprint (−3.0%, ES = −1.84), with the exception of EUR (0.9%, ES = 0.63, p = 0.134), showing no significant difference. In addition, no significant interaction effects between group and time were observed for 1RM back squat, SJ, SLJ, and 30 m sprint (p > 0.05). Conversely, a significant interaction effect between group and time was observed for both CMJ and EUR (p < 0.001); post hoc analysis revealed that the improvements in CMJ and EUR were significantly greater in the FWT group compared to the AELT group (p < 0.001). These findings indicate that both FWT and AELT are effective at enhancing lower-body strength, power, and speed in well-trained male college sprinters, with FWT being particularly more effective in promoting elastic energy storage and the full utilization of the stretch–shortening cycle.

The construction of a new generation of smart cities puts forward higher requirements for the digitization and intelligence of subway tunnel engineering. Digital twin technology has shown great potential in high-fidelity modeling, virtual–real mapping, and decision support based on data analysis, but its research is still in its infancy. To this end, this paper first discusses in depth the inherent complexity and safety risks of subway tunnel construction and emphasizes the significant advantages of digital twin technology compared with traditional technology. Then, by summarizing the existing concepts, this paper proposes a specific explanation of DT applicable to subway tunnel engineering. In order to deeply analyze the potential of digital twin technology in subway tunnel engineering, this paper first conducts a bibliometric analysis and organizes the relevant research directions in recent years based on a visual map. Then, the application of DT in the field of subway tunnel engineering is discussed, including the modeling method of the subway digital twin, intelligent management of the construction process, safety guarantee, operation and maintenance, and resource optimization of traffic facilities in subway stations. Finally, this paper discusses the prospects and gaps of digital twin technology in theoretical and practical applications, aiming to promote the practical application of this technology in subway tunnel engineering. Through the summary and prospect of the existing research, this paper provides a valuable reference for future research directions and practical applications.

Analysis of transport mode choice is crucial in transportation planning and optimization. Traditionally, the transport mode of individuals is detected by discrete choice models (DCMs), which rely on data regarding individual and household attributes. Using these attribute data raises privacy concerns and limits the applicability of the model. Meanwhile, the detection results of DCMs may be biased, despite providing insight into the impact of variables. The machine learning models are more effective for mode detection, but most models need more interpretability. In this study, an interpretable machine learning model is developed to detect the transport modes of individuals. The mobility features of individuals, which introduce the velocity and acceleration of the center of mass (COM) are innovatively considered in the detection model. These mobility features are combined with multi-source data, including land use mix, GDP, population and online map service data as detection features. Using the travel survey data from Nanjing, China in 2015, the effects of different machine learning models on fine-grained detection performance are investigated. The results indicate that the deep forest model presents the best detection performance and achieves an accuracy of 0.82 in the test dataset, demonstrating the effectiveness of the proposed detection model. Furthermore, t-distributed stochastic neighbor embedding (t-SNE) and ablation experiments are conducted to overcome the non-interpretability issue of the machine learning models. The results show that the mobility features of individuals are the most critical features for improving detection performance. This study is essential for improving the structure of transport modes and maintaining low-carbon and sustainable development in urban traffic systems.

Abstract In this work, via engineering the conformation of cobalt active center in cobalt phthalocyanine molecular catalyst, the catalytic efficiency of electrochemical carbon monoxide reduction to methanol can be dramatically tuned. Based on a collection of experimental investigations and density functional theory calculations, it reveals that the electron rearrangement of the Co 3d orbitals of cobalt phthalocyanine from the low-spin state (S = 1/2) to the high-spin state (S = 3/2), induced by molecular conformation change, is responsible for the greatly enhanced CO reduction reaction performance. Operando attenuated total reflectance surface-enhanced infrared absorption spectroscopy measurements disclose accelerated hydrogenation of CORR intermediates, and kinetic isotope effect validates expedited proton-feeding rate over cobalt phthalocyanine with high-spin state. Further natural population analysis and density functional theory calculations demonstrate that the high spin Co2+ can enhance the electron backdonation via the d xz /d yz −2π* bond and weaken the C-O bonding in *CO, promoting hydrogenation of CORR intermediates.

Abstract The global incidence of dengue fever has gradually increased in recent years, posing a serious threat to human health. In the absence of specific anti-dengue drugs, understanding the interaction of Dengue virus (DENV) with the host is essential for the development of effective therapeutic measures. Autophagy is often activated during DENV infection to promote viral replication, but the mechanism of how DENV's own proteins induce autophagy has not been clarified. In this study, we first preliminarily identified DENV-2 NS1 as the most likely viral protein for DENV-2-induced autophagy with the help of molecular docking techniques. Further experimental results confirmed that DENV-2 NS1 regulates DENV-2 infection of HUVEC-induced autophagy through the AMPK/ERK/mTOR signaling pathway. Mechanistically, DENV-2 NS1 mainly interacted with AMPK by means of its Wing structural domain, and NS1 bound to all three structural domains on the AMPKα subunit. Finally, the experimental results showed that DENV-2 NS1 promoted the interaction between LKB1 and AMPKα1 and thus activated AMPK by both increasing the expression of LKB1 and binding LKB1. In conclusion, the results of this study revealed that DENV-2 NS1 protein served as a platform for the interaction between AMPK and LKB1 after DENV-2 infection with HUVEC, and pulled AMPK and LKB1 together to form a complex. LKB1 to form a complex, promoting LKB1 action on the kinase structural domain of AMPKα1, which in turn promotes phosphorylation of the Thr172 site on the AMPK kinase structural domain and activates AMPK, thereby positively regulating the AMPK/ERK/mTOR signaling pathway and inducing autophagy. The present discovery improves our understanding of DENV-2-induced host autophagy and contributes to the development of anti-dengue drugs.

Abstract Background Chayote is an underutilized species of Cucurbitaceae. It is rich in nutrients such as protein, minerals, phenols and its extracts have anti-cardiovascular and anti-cancer effects, making it a versatile plant for both medicinal and culinary purposes. Although research on its root tuber is limited, they are rich in starch and have a structure similar to that of potatoes, cassava, and sweet potatoes. Therefore, they can serve as potential substitutes for potatoes and offer promising prospects as agricultural and industrial resources. However, the physiological and cellular mechanisms of chayote root tuber formation and development are still unclear. Results In this study, we observed the growth habit of ‘Tuershao’ (high yield of root tuber). The results revealed that the tuber enlargement period of ‘Tuershao’ lasts approximately 120 days, with the early enlargement phase occurring during 0–30 days, rapid enlargement phase during 30–90 days, and maturation phase during 90–120 days. Physiological indicators demonstrated a gradual increase in starch content as the tuber developed. The activities of sucrose synthase (SUS) and invertase (VIN) showed a consistent trend, reaching the highest level in the rapid expansion period, which was the key enzyme affecting tuber expansion. Moreover, the special petal like structure formed by the secondary phloem and secondary xylem of the tuber resulted in its enlargement, facilitating the accumulation of abundant starch within the thin-walled cells of this structure. Principal component analysis further confirmed that starch content, SUS and VIN activities, as well as the concentrations of calcium (Ca), iron (Fe), and selenium (Se), were the major factors influencing tuber development. Moreover, the low temperature environment not only promoted the growth of ‘Tuershao’ tubers but also enhanced the accumulation of nutritional substances. Conclusions These findings contribute to a deeper understanding of the formation and developmental mechanisms of ‘Tuershao’ tubers, providing valuable guidance for cultivation practices aimed at improving crop yield.

The prevailing customized electricity pricing methods in China primarily utilize a single power price, which is an extra service cost charged per kWh. This paper suggests a customed power pricing optimization method that takes into account not only electricity quantity (kWh), but also capacity (kVA), and considers the gaming ability of both users and the electricity retail company. Firstly, the method for determining level of the quality of power is introduced in this paper, which is based on various quality of power indices Next, an optimization model for the customized electricity pricing is suggested, which takes into account the gaming ability of both users and the new power sales company (NPSC). Lastly, this paper conducts a case study of four representative users situated in an industrial park in Chengdu, Sichuan province to demonstrate the practical application of the proposed approach. The findings indicate that the suggested approach can allocate customized electricity charges between capacity and electricity consumed by users in a rational manner, thus enhancing the efficiency of production equipment for users.

Abstract Background Cancer stem cells may be the source of cancer-causing mutant cells and are closely related to the prognosis of cancer. Our study aimed to investigate the potential association between single-nucleotide polymorphisms (SNPs) of cancer stem cell-related genes and the prognosis of lung cancer patients. Methods The SNP loci were genotyped by matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF–MS), and the overall survival of subjects was analyzed by log-rank test after stratifying and adjusting their demographic data, clinical data, and genotypes. The correlation between survival time and quality of life of lung cancer under codominant, dominant, recessive, and additive genetic models was analyzed by the Cox regression model. The association between SNP polymorphism and the prognosis of lung cancer was analyzed by Stata16.0 software, and their heterogeneity was tested. Interaction analysis was performed using R software (version 4.2.0). Results Stratified analysis unveiled that rs3740535 had recessive AA genotype and additive GG genotype; Rs3130932 dominant GT + GG genotype, additive TT genotype; Rs13409 additive TT genotype; Rs6815391 recessive CC genotype and additional TT genotype were associated with increased risk of lung cancer death. Rs3130932 recessive GG genotype was associated with a reduced risk of lung cancer death. Conclusion Rs3740535, rs3130932, rs13409, and rs6815391 are associated with the overall survival of lung cancer patients and may be valuable for the prognosis of lung cancer patients.

The application of edible coatings for preparing composite antibacterial spray coatings for fruit preservation by incorporating antibacterial nanoparticles has gained increasing attention. Chitosan (CS) is a natural polysaccharide used as an edible coating to preserve fruit; it has properties such as reducing water loss, enhancing appearance, and improving mechanical properties. By combining it with antibacterial material, it can reduce fruit microorganisms. Cerium (Ce) has excellent antibacterial activity combined with the advantages of safety and low cost. Therefore, this study proposes a biocatalytic spray coating for fruit preservation using a CS composite metal–organic framework (CS@Ce-MOF) with strawberry as a model fruit. CS@Ce-MOFs are superior to Ce-MOFs in the aqueous stability of their chemical structure, inoxidizability, antibacterial duration, and validity. The well-characterized CS@Ce-MOF was verified to simultaneously mimic good oxidase- and apyrase-like activities. CS@Ce-MOF biocatalytic spray coating demonstrated excellent antibacterial properties against two common foodborne pathogens: Escherichia coli and the Gram-positive bacterium Staphylococcus aureus, with high killing rates of up to 94.5%. This is due to the unique structure of the CS@Ce-MOF composite, which presents a large surface area for contact with pathogens and enhances the catalytic activity of the incorporated cerium oxide nanoparticles, leading to efficient sterilization. Furthermore, the scavenging rate of DPPH and ABTS free radicals is more than 80%, indicating that CS@Ce-MOF has excellent antioxidant properties. Moreover, CS@Ce-MOF minimized the weight loss and firmness of strawberries and bananas over 7 days of ambient storage. The use of such a biocatalytic spray coating has enormous potential for preserving the quality and safety of fresh produce, reducing food waste, and promoting sustainable agricultural practices.