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Abstract Purpose To explore the potential of crystalline lens decentration and tilt as indicators for screening cataract patients for presbyopia-correcting intraocular lens (IOL) implantation. Methods Prospective observational study. Patients undergoing phacoemulsification with bifocal (Tecnis ZMB00) or extended depth-of-focus (EDOF) (Tecnis ZXR00) IOL implantation were consecutively enrolled. The decentration and tilt of the crystalline lens and the IOL were quantified through the utilization of swept-source optical coherence tomography (SS-OCT, Casia2). Postoperative visual acuity (VA), contrast sensitivity (CS), objective optical quality, and patient-reported outcomes were assessed at a 3-month follow-up. A LOWESS (LOcally WEighted Scatterplot Smoothing) curve was employed to analyze the changes in VA, CS, and objective optical quality relative to the decentration or tilt of crystalline lenses. A further comparison of visual outcomes was conducted based on the inflection points suggested by the curves. Results Eighty‑seven patients with ZMB00 IOL and 76 patients with ZXR00 IOL were included. Multiple 6-mm internal aberrations showed a nonlinear increase with greater crystalline lens decentration. The inflection points for the steep increase were observed to be 0.28 mm for the bifocal group and 0.35 mm for the EDOF group. Beyond these points, internal aberrations such as coma increased significantly (all P

Abstract Objectives Postoperative nausea and vomiting (PONV) is common after video-assisted thoracic surgery, which may be associated with the use of intraoperative opioids. We tested the hypothesis that balanced opioid-free anesthesia (OFA) might reduce the incidence of PONV after video-assisted thoracic surgery. Methods One hundred and sixty-eight adults undergoing video-assisted thoracic assisted surgery were randomly assigned to receive balanced opioid-free anesthesia or balanced opioid-based anesthesia (OBA). The primary outcome was the incidence of PONV, which was assessed with the Myles’s simplified PONV impact scale during the initial 24 h after surgery. Results Compared with OBA group, the overall incidence of PONV in OFA group was significant reduced (14.6% vs. 30.1%, P = 0.017), and OFA reduced the risk of PONV events within 24 h of surgery (HR, 0.44; 95%CI: 0.22–0.87, P = 0.018). The incidence of other postoperative complications in OFA group was lower than that in OBA group (19.5% vs. 33.7%, P = 0.039). The quality of recovery, distance of 6-minute walk test, pain scores, and 36-item short form survey were comparable at each time points. Conclusion In patients undergoing video-assisted thoracic surgery, the use of balanced OFA anesthesia can help reduce the incidence of PONV events. This anesthetic regimen has shown good feasibility without significantly increasing the patient’s pain score and complications. Clinical trial registration number Clinicaltrials.gov, Identifier: NCT05411159. First posted date: 9 Jun, 2022.

ABSTRACT: The objective of this study was to reveal the synergistic antibacterial activity and mechanism of Echinacea purpurea (L.) Moench crude extract (EE) and citric acid (CA) against Cronobacter sakazakii isolated from powdered infant formula (PIF). The minimum inhibitory concentration (MIC) of EE against C. sakazakii was determined, and then growth curve and time-kill analysis were used to screen the optimal antibacterial combination of 1 MIC of EE and CA. Changes in cell membrane potential, cell integrity, cell permeability, bacterial protein, DNA, and intracellular reactive oxygen species (ROS) levels, and cell morphology of C. sakazakii were used to reveal the synergistic inhibitory mechanism of EE and CA. The inactivation effect of EE in combination with CA against C. sakazakii on common contact surfaces was used to evaluate its efficacy as a natural disinfectant. The results showed that the MIC value of EE against C. sakazakii was 60 mg/mL, and the growth curve of C. sakazakii treated by 1 MIC of EE combined with CA (pH 3.0) was significantly inhibited compared with the control groups. The results of time-kill analysis showed that after combined treatment with 1 MIC of EE and CA (pH 3.0) for 30 min, approximately 8 log cfu/mL of C. sakazakii were inactivated. Cell membrane hyperpolarization, damaged cell membrane integrity, improved cell membrane permeability, decreased bacterial protein and DNA levels, increased and then decreased intracellular ROS contents, and deformed and ruptured cell morphology were found in C. sakazakii treated by EE combined with CA, and these phenomena were more pronounced than in C. sakazakii treated by EE or CA alone. When inoculated stainless steel, glass, ceramic, polystyrene, bamboo, and wood were sprayed with 1 MIC of EE combined with CA (pH 3.0) and after 15 min of treatment, approximately 5 log cfu/mL of C. sakazakii were inactivated. These findings suggest that EE combined with CA can effectively inactivate C. sakazakii isolated from PIF and can be used as a natural disinfectant to reduce the contamination of C. sakazakii in PIF production environments or households.

Due to the complexity of electricity pricing policies, multiple implementation steps, and difficulty in regulation, errors in electricity pricing implementation occur from time to time. This not only damages the fairness and efficiency of the electricity market but also affects the economic benefits of power enterprises and the electricity costs of users. A method was proposed for detecting electricity price anomalies at charging stations based on secondary clustering. Firstly, the electricity price anomalies were classified and the electricity consumption characteristics were analyzed. Secondly,the K-means clustering algorithm was used to extract electric vehicle users. Then, in the second clustering, the density-based spatial clustering of applications with noise (DBSCAN) algorithm was used to accurately identify more complex default situations,such as high price and low connection. The proposed method improves the accuracy and efficiency of electricity price implementation through two rounds of cluster analysis, and has certain theoretical significance and application value.

Abstract Background Abdominal fluid collection (AFC) is one of the most common complications after pancreatic surgery, yet there are few recommendations on how to manage it. Most cases of AFC only require observation, while others may require more invasive techniques. Unfortunately, there are no drugs that effectively promote the absorption of AFCs. The aim of this study was to evaluate the potential efficacy of Glauber’s salt solution for promoting the absorption of AFCs after pancreatectomy. Methods This study included 196 patients who underwent pancreatomy and had AFCs on at least 2 cross-sectional follow-up CT images between 2020 and 2022. AFCs were defined as effusion with a diameter ≥ 3 cm and located around the pancreatic resection margin. We retrospectively investigated the relationship between Glauber’s salt concentration and clinical variables. Results The rate of clinically significant pancreatic fistula (grades B + C) was significantly higher in the control group (62.8% vs. 40.7%, P = 0.014). The median maximum diameter of the AFC was smaller, and the median time for the AFC to decrease to 30 mm in diameter was shorter in the Glauber’s salt group than in the control group (41.9 mm vs. 53.5 mm, P = 0.008; 35.5 d vs. 100 d, P

Abstract Background The adverse effects of environmental toxic metal exposure on human health are well-documented. However, the specific influence of heavy metal exposure on stroke prevalence remains underexplored. Methods This study utilized data from the National Health and Nutrition Examination Survey (NHANES) spanning from 2011 to 2018 to investigate the association between blood metal concentrations and the incidence of stroke. Four analytical approaches—logistic regression, Restricted Cubic Splines (RCS), Weighted Quantile Sum regression (WQS), and Bayesian Kernel Machine Regression (BKMR)—were employed to assess the relationship, with a mediation analysis conducted to explore the role of inflammatory markers in Pb exposure-induced stroke. Results Among the 9,399 participants in this project, 421 (4.4%) were diagnosed with stroke. After adjusting for covariates, a multivariable logistic regression model identified a positive association between the logarithmic concentration of Pb and the incidence of stroke. Besides, the analysis conducted using both WQS and BKMR methodologies found a consistent positive association between the composite exposure to heavy metals and the frequency of stroke cases, with Pb emerging as the predominant factor in this relationship. An evident saturation phenomenon was noted in the correlation between lead exposure and the risk of stroke. Additionally, the interplay between Pb exposure and stroke manifestation was found to be partially mediated by inflammatory markers, which were responsible for 6.9% of the observed effect (95%CI:0.01, 0.24, P = 0.03). Conclusion These findings indicate a notable contribution of Pb exposure to stroke risk, highlighting inflammation as a significant intermediary mechanism in the Pb exposure-stroke association.

Abstract Background To evaluate the prognostic values of GNRI for major postoperative complications in emergency femoral hernia patients. Methods In this cross-sectional study, we enrolled 105 emergency femoral hernia patients. GNRI was calculated using preoperative body weight, height, and serum albumin. The primary outcome was a composite of major postoperative complications. Univariable and multivariable logistic regression analyses were used to examine the association between GNRI and major complications. The ability of GNRI in detecting major complications was assessed by area under the curve (AUC). Results The prevalence of low, moderate, and severe nutritional risk was 18.1%, 25.7%, and 10.5%. Five patients (4.8%) had major postoperative complications. Higher GNRI was associated with lower risk of major complications after adjusting for age and sex (aOR = 0.90, 95% CI: 0.81-1.00, P = 0.044). The AUC for GNRI identifying major complications was 0.812 (95% CI: 0.640–0.984, P = 0.019), and the optimal cut-point value was 90.96 (sensitivity: 80.0%; specificity: 72.0%). Conclusions GNRI is significantly associated with major postoperative complications. It is a simple and useful prognostic tool for femoral hernia patients in emergency settings.

This study addressed the issue of unstable fluoride levels in the effluent caused by the susceptibility of the wastewater to biochemical oxidation in the sewage treatment plant of an organic fluorine chemical park. In order to enhance the stability of the effluent and to reduce the concentration of organic fluorine compounds in the wastewater. Fenton oxidation/efficient precipitation method was chosen to upgrade the sewage treatment plant. Preliminary trials indicated that the organic fluorine compounds in the influent of the sewage treatment plant could be oxidized by both Fenton oxidation and ozone oxidation methods, resulting in an average fluoride increase rates of 35.48% and 46.79%, respectively. Engineering practices demonstrated that wastewater containing organic fluorine compounds could be treated by the combination of Fenton oxidation/efficient precipitation method. After Fenton oxidation, the average increase rate of fluorides was 29.40%, and the two-stage efficient precipitation achieved fluoride removal rates of 29.98% and 17.97%, respectively. The concentration of fluoride in the treated effluent was less than 4.5 mg/L, to meet the requirements of the discharge standard. The operating cost of the sewage treatment increased by 1.95 yuan per ton of water.

Dual-fuel engines, which are powered by natural gas while using a small amount of diesel for ignition, have become an attractive option in the marine sector due to their fuel flexibility and relatively good emission characteristics. Altering the fuel injection timing can change the combustion state of natural gas in the cylinder, which in turn affects engine stability and leads to engine knocking.

［Objective］To enable proactive adjustment of the cooling capacity for metro train AC (air-conditioning) system based on ambient temperature, it is essential to study the prediction of return air temperature in metro train AC systems. ［Method］A time series forecasting method is employed to predict the variation trend in return air temperature of metro train AC systems. Real-time operational data from the air-conditioning system of a Guangzhou Metro train are collected through AC sensors. Outliers are removed using a boxplot, and a sliding window approach is applied to handle the time span of input and output data. An LSTM (long short-term memory) neural network model is then constructed to predict the return air temperature of the AC units, and the impact of different sample sizes on the model prediction accuracy is comparatively analyzed. ［Result & Conclusion］The LSTM neural network model can learn the temperature control logic of metro train AC system, with the predicted temperature curve closely matching the actual temperature curve, therefore is suitable for predicting the return air temperature of metro AC units. Through parameter optimization, the model accuracy is improved to 0.84, enabling precise prediction of unit return air temperature. Increasing the sample size for a single training session can shorten model training time but may reduce the model final prediction accuracy to some extent correspondently.

Background: Mounting evidence underscores the importance of cell communication within the tumor microenvironment, which is pivotal in tumor proliferation, invasion, and metastasis. Exosomes play a crucial role in cell-to-cell communication. Although single-cell RNA sequencing (scRNA-seq) provides insights into individual cell transcriptional characteristics, it falls short of comprehensively capturing exosome-mediated intercellular communication. Method: We analyzed Pancreatic Ductal Adenocarcinoma (PDAC) tissues, separating supernatant and precipitate for exosome purification and single-cell nucleus suspension. We then constructed Single-nucleus RNA sequencing (snRNA-seq) and small RNA-seq libraries from these components. Our bioinformatic analysis integrated these sequences with ligand-receptor analysis and public miRNA data to map the cell communication network. Results: We established intercellular communication networks using bioinformatic analysis to track exosome miRNA effects and ligand-receptor pairs. Significantly, hsa-miR-1293 emerged as a prognostic biomarker for pancreatic cancer, linked to immune evasion, increased myeloid-derived suppressor cells, and poorer prognosis. Targeting this miRNA may enhance anti-tumor immunity and improve outcomes. Conclusion: Our study offers a novel approach to constructing intercellular communication networks using snRNA-seq and exosome-small RNA sequencing. By integrating miRNA tracing with ligand-receptor analysis, we illuminate the complex interactions in the pancreatic cancer microenvironment, highlighting the pivotal role of miRNAs and identifying potential biomarkers and therapeutic targets.

Abstract Background The objective of this study was to analyze the impact of diabetes mellitus (DM) on short and long term outcomes following radical gastrectomy using propensity score matching (PSM) method, as well as to further investigate the factors influencing patient survival post-radical gastrectomy. Methods The patients who underwent radical gastrectomy for gastric cancer (GC) between January 2011 and December 2015 were selected as study population, and PSM procedure was conducted with a matching ratio of 1:3 between the DM and non-DM groups. The short-term recovery and long-term survival outcomes were compared between the DM and non-DM group. Subsequently, univariate and multivariate COX regression analyses were conducted to further explore the factors that influence survival outcomes. Results Among the cohort of 2508 GC patients who underwent radical surgery prior to PSM, a total of 295 (11.8%) individuals were diagnosed with DM. After conducting 1:3 PSM, 293 DM patients and 821 control patients were enrolled. The results of comparative analysis revealed that the DM group exhibited a significantly higher rate of overall complications (P 65years (P 5 cm (P

Abstract Purpose To investigate the potential relationship between subretinal microglia and transplanted donor photoreceptors. Methods Photoreceptor precursors were transplanted into wild-type mice and rd1 mice by trans-scleral injection. Immunohistochemistry was employed to detect microglia and macrophages. PlX5622 feed was used to achieve microglia depletion and microglia repopulation. RNA-seq and qPCR were utilized to evaluate gene expression. Confocal microscopy was used to observe the interaction between microglia and donor photoreceptors. Results Donor photoreceptors survived in rd1 mice but not in wild-type mice after trans-scleral injection. The microglial cells closely interacted with donor cells. While donor cells failed to survive in rd1 mice after microglia depletion, they could survive following microglia repopulation. The RNA-seq analysis showed a pro-neurodevelopmental effect of sub-retinal microglia/RPE tissue in rd1 mice. Conclusions Subretinal microglia supported donor photoreceptor survival in rd1 mice.

Abstract Objective To retrospectively evaluate thoracic duct (TD) congestion in hepatic lymphorrhea (HL) and propose treatment suggestions. Methods Retrospectively analyze cases of postoperative HL admitted from August 2007 to November 2023. Twenty cases were enrolled and followed up. The medical history, ascites characteristics, lymphoscintigraphy, direct lymphangiography, and other clinical data were reviewed. Results Twenty patients with ascites after cholecystectomy or radical gastrectomy were included. There were 15 patients with cirrhosis and 5 patients with hepatitis. Ascites were light yellow even if the patients had a non-low-fat diet. Triglyceride level mean of ascites was 0.61 ± 0.20 mmol/L. There were 94.1% (16/17) of patients whose ascitic cholesterol ≥ 45 mg/dL or SAAG

Abstract Single-cell technology depicts integrated tumor profiles including both tumor cells and tumor microenvironments, which theoretically enables more robust diagnosis than traditional diagnostic standards based on only pathology. However, the inherent challenges of single-cell RNA sequencing (scRNA-seq) data, such as high dimensionality, low signal-to-noise ratio (SNR), sparse and non-Euclidean nature, pose significant obstacles for traditional diagnostic approaches. The diagnostic value of single-cell technology has been largely unexplored despite the potential advantages. Here, we present a graph neural network-based framework tailored for molecular diagnosis of primary liver tumors using scRNA-seq data. Our approach capitalizes on the biological plausibility inherent in the intercellular communication networks within tumor samples. By integrating pathway activation features within cell clusters and modeling unidirectional inter-cellular communication, we achieve robust discrimination between malignant tumors (including hepatocellular carcinoma, HCC, and intrahepatic cholangiocarcinoma, iCCA) and benign tumors (focal nodular hyperplasia, FNH) by scRNA data of all tissue cells and immunocytes only. The efficacy to distinguish iCCA from HCC was further validated on public datasets. Through extending the application of high-throughput scRNA-seq data into diagnosis approaches focusing on integrated tumor microenvironment profiles rather than a few tumor markers, this framework also sheds light on minimal-invasive diagnostic methods based on migrating/circulating immunocytes.

Abstract This study aimed to analyze the complications and long-term survival outcomes in patients who underwent radical gastrectomy for gastric cancer, as well as to identify the risk factors associated with postoperative complications. After conducting a comprehensive search within the medical records system, a total of 2508 patients who underwent radical gastrectomy and met the inclusion criteria were enrolled. Of the 2508 patients, 301 were diagnosed with postoperative complications. The pathological data, postoperative recovery, and survival outcome were compared between complication and control group. Subsequently, univariate and multivariate logistic regression analyses were conducted to identified the risk factors. According to the Clavien-Dindo grading criteria for postoperative complications, the proportions of grade I, II, III, IV, and V complications following radical gastrectomy were observed to be 28.2%, 42.9%, 19.6%, 8.0%, and 1.3%, respectively. The presence of postoperative complications significantly prolonged the duration of gastrointestinal decompression (P 65years [odds ratio (OR) = 1.378, P = 0.020], presence of diabetes (OR = 2.042, P 215 min (OR = 1.450, P = 0.006), intraoperative blood loss > 275 ml (OR = 1.474, P = 0.004), and Roux-en-Y anastomosis for both whole stomach (OR = 1.567, P = 0.021) and distal gastric cancer (OR = 2.083, P = 0.003) were identified as independent risk factors for postoperative complications. This study analyzed the complications and survival outcomes following radical gastrectomy, and investigated the predictors for postoperative complications, thereby providing valuable guidance on the prevention and management of surgical complications in gastric cancer.

In order to study the influence of diaphragm thickness on the torque transmission and misalignment compensation performance of wind turbine couplings, the overall finite element model of the coupling was established, the stress nephogram under the combined action of torque, axial displacement and angular displacement load was obtained, and the feasibility of the finite element simulation analysis was verified by combining with the actual broken position of the diaphragm. The stress response of each diaphragm thickness under different loads was given, the influence of different loads on the stress of each diaphragm thickness was analyzed, and the influence of preload force and contact friction coefficient on the performance of the coupling was discussed. The results show that the increase of diaphragm thickness can improve the torque transmission capacity of the coupling, but will weaken its misalignment compensation capacity. The influence of different loads on the stresses of different diaphragm thicknesses is different, and the comprehensive performance of the coupling is the strongest when the diaphragm thickness is 3 mm. The influence of bolt preload on the performance of the coupling is great, while the influence of contact friction coefficient between diaphragms on the performance of the coupling is smaller.

In order to explore the effectiveness of the laboratory’s self-developed equipment - horizontal box cage stacked peanut pods room temperature ventilation drying equipment, this study used this equipment to conduct drying experiments on newly harvested peanut pods. The research focused on analyzing the drying rate of peanuts, changes in temperature and humidity within the pile, and energy consumption, and the results were then compared with natural sun drying and similar drying equipment. The research has found that under the same weather conditions (mainly cloudy and rainy weather), the moisture content of peanuts reduced from an initial 43.77% to below 10% within 9 days with a horizontal box cage stacked peanut pods room temperature ventilation drying equipment. The drying rate was 43% higher than that of natural drying. The drying energy efficiency of peanut pods was 2.64×106 J/kg, and the moisture content of the inner and outer layers of the stacked peanut pods decreased uniformly. This study has demonstrated that the horizontal box cage stacked peanut pods drying equipment can be used for the emergency drying of newly harvested peanut pods.

Abstract Infection after anterior cruciate ligament reconstruction (ACLR) is a rare and catastrophic postoperative complication. The aims of this study were to investigate the diagnostic, treatment and rehabilitation measures for postoperative infection following after ACLR. A retrospective study was conducted on 1500 patients who underwent ACLR between January 2011 and January 2022. Twenty patients who met the criteria for summarizing the incidence patterns and treatment experiences were selected for a complete investigation of their diagnostic, therapeutic, and rehabilitation processes, as well as outpatient follow-up results. Among the 20 patients who developed postoperative infections, Staphylococcus aureus was the main pathogen (80%). The clinical manifestations mainly included fever (80%) and knee joint pain (100%). Laboratory tests demonstrated that C-reactive protein (CRP) levels were greater than 50 mmol/L in fifteen patients (75%). All of the patients received intravenous antibiotic therapy. Five patients (25%) of tendon socket infection were treated with continuous negative pressure suction irrigation, whereas the other fifteen patients with intra-articular infection were treated with arthroscopic debridement and continuous flushing. The Lysholm score of the affected knee was compared before treatment and 6 months after treatment, and the difference was statistically significant (t = 20.78, P

Sintering temperature is the key factor affecting the structure and performance of tungsten carbide (WC) ceramics. Thus, the effect of sintering temperature on the microstructure and mechanical properties of WC-Ni-Co coarse grain ceramics, obtained from the mixture containing: 60wt.% of ultra-coarse WC, 30 wt.% of fine WC, 7 wt.% of Co and 3wt.% of Ni powders, was analysed. The mechanical properties of WC ceramics did not change much when the sintering temperature was varied between 1410 and 1430 °C and the comprehensive performances of the ceramics were the best in this temperature range. In order to confirm that the coarse grain WC-Ni-Co ceramics can be applicable for harsh environments, it was compared with the standard WC-Co ceramics of the same grain size, and the reasons and mechanisms for the differences in microstructure and properties between the two ceramics were tested and analysed. The study shows that the average grain size of two ceramics does not differ much, and there are no decarburisation, graphite-phase and other impurity phases inside the ceramics. In addition, the difference in the mechanical properties is also small. However, the addition of Ni effectively improves the corrosion resistance of the WC-Co ceramics. Therefore, WC-Ni-Co can replace WC-Co ceramics as shield cutting tool material with the same grain size.

Abstract With the development of the digital economy, the power demand for data centers (DCs) is rising rapidly, which presents a challenge to the economic and low‐carbon operation of the future distribution system. To this end, this paper fully considers the multiple flexibility of DC and its impact on the active distribution network, and establishes a collaborative planning model of DC and active distribution network. Differing from most existing studies that apply robust optimization or stochastic optimization for uncertainty characterization, this study employs a novel interval optimization approach to capture the inherent uncertainties within the system (including the renewable energy source (RES) generation, electricity price, electrical loads, emissions factor and workloads). Subsequently, the planning model is reformulated as the interval multi‐objective optimization problem (IMOP) to minimize economic cost and carbon emission. On this basis, instead of using a conventional deterministic‐conversion approach, an interval multi‐objective optimization evolutionary algorithm based on decomposition (IMOEA/D) is proposed to solve the proposed IMOP, which is able to fully preserve the uncertainty inherent in interval‐typed information and allow to obtain an interval‐formed Pareto front for risk‐averse decision‐making. Finally, an IEEE 33‐node active distribution network is utilized for simulation and analysis to confirm the efficacy of the proposed approach.

Against the backdrop of growing attention being paid to both ecological compensation and the digital economy, this paper explores the impact of digital financial inclusion on green economic growth in counties within China’s National Key Ecological Functional Zones (NKEFZs) from 2014 to 2022, using panel data from 393 counties. Employing a two-way fixed-effects model, the study finds that digital financial inclusion promotes both traditional and green economic growth. The study results are robust, even after a series of robustness tests. The mechanisms identified include agricultural technology progress, industrial structure upgrading, and enterprise innovation and entrepreneurship. However, the effect is less significant in western and northeastern regions, as well as in windbreak and sand-fixing zones. The study highlights the potential of digital finance to help resource-rich, underdeveloped regions overcome the “resource curse” and foster sustainable economic growth.

This study explores the often-overlooked influence of artificial intelligence (AI) on wealth distribution. Using a continuous-time heterogeneous agent dynamic general equilibrium model, we investigate AI's impact on production technology as a form of biased technological progress. Our findings highlight a temporal dichotomy in AI's effects on wealth inequality: in the short term, AI exacerbates disparities in wealth distribution, while the long-term outcomes depend on the extent of AI's influence across different technological domains. The nuanced nature of AI-driven technological progress leads to distinct consequences for the rate of return on capital—showing short-term increases across all forms of technological progress, but with varying long-term effects. Based on these results, we propose policy recommendations for China to leverage AI for economic growth while mitigating inequality. This research provides a comprehensive analysis of AI's role in wealth distribution, offering valuable insights for both academic inquiry and policy formulation.

Background The thyroid gland is an important endocrine gland in animals that secretes thyroid hormones and acts on various organs throughout the body. lncRNAs are long non-coding RNAs that play an important role in animal reproduction; however, there is a lack of understanding of their expression patterns and potential roles in the thyroid gland of the Small Tail Han (STH) sheep. In this study, we used RNA-Seq technology to examine the transcriptome expression pattern of the thyroid from the luteal phase (LP) and follicular phase (FP) of FecB BB (MM) STH sheep.Results We identified a total of 122 and 1287 differential expression lncRNAs (DELs) and differential expression mRNAs (DEGs), respectively, which were significantly differentially expressed. These DELs target genes and DEGs can be enriched in several signalling pathways related to the animal reproduction process.Conclusions The expression profiles of DELs and DEGs in thyroid glands provide a more comprehensive resource for elucidating the reproductive regulatory mechanisms of STH sheep.

The thyroid gland is an important endocrine gland in animals, which mainly secretes thyroid hormones and acts on various organs of the body. Long-chain non-coding RNA (lncRNA) plays an important role in animal reproduction. However, there is still a lack of understanding of their expression patterns and potential roles in the thyroid of Small Tail Han (STH) sheep. In this study, RNA-seq was used to examine the transcriptome expression patterns of lncRNAs and mRNAs in the follicular phase (ww_FT) and luteal phase (ww_LT) in FecB++ genotype STH Sheep. A total of 17,217 lncRNAs and 39,112 mRNAs were identified including 96 differentially expressed lncRNAs (DELs) and 1054 differentially expressed mRNAs (DEGs). Functional analysis of genes with significant differences in expression level showed that these genes could be enriched in Ras signalling pathway, hedgehog (HH) signalling pathway, ATP-binding cassette (ABC) transporters and other signalling pathways related to animal reproduction. In addition, through correlation analysis for lncRNA–mRNA co-expression and network construction, we found that LNC_009115 and LNC_005796 trans target NIK-related kinase (NRK) and poly(A)-specific ribonuclease (PARN). LNC_007189 and LNC_002045 trans target progesterone-induced blocking factor 1 (PIBF1), LNC_009013 trans targets small mothers against decapentaplegic (SMAD1) are related to animal reproduction. These genes add new resources for elucidating the regulatory mechanisms of reproduction in sheep with different reproductive cycles of the FecB++ genotype STH sheep.

A Kovar alloy composite wire inlaid with copper core was developed through hot isostatic pressing sintering and subsequent multi-pass drawing. The interface between the Kovar alloy and copper was revealed, and the physical properties of the composite wire were investigated. The results show that the Kovar alloy and copper diffuse mutually during the forming process, producing a stable metallurgical bond. When the diameter of the wire is 2.8 mm, a diffusion layer of about 16.5 μm was found at the interface. The concentration of the diffused element had a gradient distribution from the interface to both sides. Combining the excellent properties of Kovar alloy and copper, the composite wire has comprehensive physical properties. The electrical and thermal conductivities are 9.38 × 106 S·m−1 and 72.2 W·m−1·K−1, respectively. The composite wire has a low coefficient of thermal expansion, and the average coefficient of thermal expansion is lower than 6.36 × 10−6 ℃−1 in the temperature range of 25–450°C.

When a large number of distributed photovoltaic (PV) systems are integrated into the distribution network, power flow becomes bidirectionally fluctuating, resulting in variable line losses. In the scenario of reverse flow, the increase in line loss is particularly significant. The bidirectional reactive power regulation of photovoltaic inverters is an effective approach to reduce losses in the distribution network. However, despite the benefits of reducing losses, reactive power regulation by photovoltaic inverters also incurs additional costs. Therefore, there is a need for research into a comprehensive benefit optimization method for inverters participation in reducing reactive power losses in distribution networks. Firstly, the cost quantification models for the investment, transformation, operation, and lifespan loss of the photovoltaic inverters involved in reactive power loss reduction are established. Secondly, the benefit quantification models for loss reduction and power factor improvement are developed. Thirdly, considering various operational scenarios of both photovoltaic systems and loads, a comprehensive benefit optimization method for photovoltaic inverters participating in reactive power loss reduction in distribution networks is proposed. Finally, through example analysis, the cost and benefit are calculated and fitted in different scenarios, and the optimization calculation is carried out. Compared to the scenario where the photovoltaic inverter operates at the maximum reactive power regulation capacity, the optimized comprehensive benefit is increased by 21.20%. The proposed method is validated to effectively enhance the comprehensive benefits of inverters participation in reactive power loss reduction.

Background: To investigate the visual acuity outcome and choroid thickness (CT) change after intravitreal ranibizumab in highly myopic eyes with or without dome-shaped macula (DSM) in Chinese patients. Methods: This retrospective, observative study included 80 treatment-naive eyes (80 patients), which received ranibizumab according to the 1+PRN protocol. The best corrective visual acuity (BCVA) and CT change were compared between eyes with or without DSM. Results: There was no significant difference between eyes with or without DSM in BCVA and central macular thickness (CMT). The recurrent rate was not different between the two groups during the first year of treatment. The CT was significantly thinner in eyes with DSM than in eyes without DSM before treatment (median 40.00um versus 71.00um), at 1 month after treatment (median 31.00um versus 65.50um), and in the last follow up (median, 32.00um versus 65.00um) (p = 0.0101). Axial length (AL) was longer in eyes with DSM than those without DSM (median, 29.17 mm versus 28.10 mm) before treatment, and in the last follow up (median, 29.44 mm versus 28.20 mm) (p = 0.0055). The CT was significantly correlated with AL (p < 0.0001). Conclusions: No difference was found in visual outcome between eyes with or without DSM. The visual acuity significantly improved at 1 month after ranibizumab injection and it was recovery sooner in extrafoveal choroidal neovascularization (CNV) group than in subfoveal CNV group. The CT was thinner in eyes with DSM, which was significantly correlated with AL.

Abstract Anaplastic thyroid carcinoma (ATC) is a highly aggressive human malignancy without effective treatment. Yes-associated protein (YAP) is a critical effector of the Hippo pathway, which is essential in thyroid carcinogenesis. However, the underlying mechanisms of aberrant YAP expression in ATC are not completely understood. Ubiquitylation-related enzyme siRNA screening identified the ubiquitin protein ligase E3 component n-recognin 1 (UBR1) as a stabilizer of YAP in ATC cells. UBR1 deficiency reduced YAP protein levels and its target gene expression. UBR1 directly interacted with YAP and promoted its monoubiquitylation, competitively suppressing its polyubiquitylation and resulting in extended protein half-life. UBR1 depletion reduced ATC cell proliferation and migration in vitro. Xenograft tumor studies also suggested that UBR1 knockdown suppressed ATC cell growth in vivo. Furthermore, exogenous YAP expression partially reversed the inhibitive effects of UBR1 depletion on ATC cell proliferation and migration. Our studies demonstrated that UBR1 directly interacts with YAP and stabilized it in a monoubiquitylation-dependent manner, consequently promoting ATC tumorigenesis, suggesting that UBR1 might be a potentially therapeutic target for ATC treatment.

Colletotrichum species can function as plant pathogens, saprobes or endophytes on a wide variety of plant hosts and are considered amongst the ten most significant genera of plant pathogens globally. China contributes almost half the walnut production in the world. However, Colletotrichum species occurring on walnut remain largely unresolved in China. To explore the Colletotrichum species found on walnut in China, 470 walnut fruit or leaf samples with anthracnose were collected from 14 main walnut-producing regions across seven provinces. A total of 165 Colletotrichum strains were isolated from these samples. The Colletotrichum isolates were identified, based on morphological characteristics and sequence analyses of ACT, CHS-1, GAPDH, ITS and TUB2. Twelve species, including 11 known Colletotrichum species (C. boninense, C. citrulli, C. fioriniae, C. fructicola, C. godetiae, C. juglandicola, C. karsti, C. mengyinense, C. pandanicola, C. peakense and C. siamense) and a novel species (C. chinensis sp. nov.) were identified. The species distribution revealed regional prevalence as follows: C. mengyinense was the most dominant species in Gansu, C. mengyinense and C. siamense in Shandong, C. chinensis in Beijing, C. pandanicola in Shaanxi and C. godetiae in Yunnan. Colletotrichum siamense was the sole species isolated in Sichuan and Xinjiang Provinces. Koch’s postulates were fulfilled, demonstrating that all 12 species cause anthracnose on walnut. This is the first report of C. boninense, C. citrulli and C. karsti as pathogens of walnut anthracnose worldwide.

[Objective] Collaborative governance is increasingly important in coping with complex grassland resource and environmental problems under dynamic changes, but the effectiveness of governance also depends partly on the fit between the governing and governed systems, thus there is a need to embed a fit perspective for advancing the scientific understanding of the formation mechanism of collaborative governance network. [Methods] Based on the first-hand data from surveys conducted in 2020 and 2022 at Yangrang Village, Gonghe County, Qinghai Province, we constructed the social-ecological network of herders and rangeland using multilevel network and minimum building block methods, and further empirically examined the role of structural, actor attribute, covariate, and fit effects in the formation of collaborative governance network among herders using the multilevel exponential random graph model based on the description of the basic characteristics of the network. [Results] (1) The collaborative network is characterized by low density and high centralization, and each herder has two collaborative ties on average. (2) Among the structural effects, only ties closure promotes the formation of collaborative network, i.e., collaborative ties are more likely to be established between herders who share a common collaborative partner. (3) In the actor attribute effects, the activity effect is stronger than the homophily effect. For the former, social status, years of education and managed pastureland area all have a positive effect on the formation of collaborative ties; for the latter, collaborative ties are more likely to be established between herders with similar numbers of livestock. (4) Affective network has an entraining effect on the establishment of collaborative network, suggesting that collaborative ties are more likely to be established between herders with kinship or close blood ties. (5) Among the ecological fit effects, only sharing fit has a significant effect on the formation of collaborative network. [Conclusion] There is still much room for improvement in the collaborative governance of rangeland resources for herders. It is desirable to promote the establishment of collaboration among herders with similar capabilities and resources while letting self-organization and affective dependence play a role, and to make full use of the path of resource sharing to cultivate and develop collaborative governance. In addition, awareness and understanding of the ecological changes in grasslands and ecological linkages of pastures should be strengthened, and herders should be guided and encouraged to collaborate in solving the problem related to scale fit, in order to help herders break through path dependence and enhance the pathways and effectiveness of collaborative governance.

Objective: This study aimed to establish a hollow fiber ligand fishing method for screening γ- Aminobutyrate transaminase (GABA-T) inhibitory component from the volatile oil of Acorus tatarinowii. Methods: Based on optimizing the enzyme assisted extraction process of volatile oil from A. tatarinowii using response surface methodology, GABA-T solution was injected into the hollow fiber lumen and used as a "bait" to fish out the potential active components in A. tatarinowii volatile oil, and its GABA-T inhibitory activity was verified. Results: The results showed that the optimum extraction conditions of volatile oil from A. tatarinowii were as follows: cellulase content 3 165 U/g, enzymolysis time 1.8 h, enzymolysis temperature 45 ℃, and the yield of volatile oil from A. tatarinowii was 2.56%. Finally, 51 compounds were identified, mainly including olefins, alcohols, ethers, ketones, phenols, acids, and other compounds. 3 mg/mL of GABA-T solution was injected into the cavity of the U-shaped hollow fiber tube, incubated for 160 min, sealed, and placed in the volatile oil of A. tatarinowii for ultrasonic (60 kHz) fishing for 20 min, and then analyzed with LCMS-IT-TOF system. Successfully filtered out α-Asarone has a concentration-dependent inhibitory effect on GABA-T activity, with an IC50 of 57.9 μg/mL. Conclusion: The established hollow fiber ligand fishing method is stable, feasible, and easy to operate.

Abstract Our research endeavors are directed towards unraveling the stem cell characteristics of lower-grade glioma patients, with the ultimate goal of formulating personalized treatment strategies. We computed enrichment stemness scores and performed consensus clustering to categorize phenotypes. Subsequently, we constructed a prognostic risk model using weighted gene correlation network analysis (WGCNA), random survival forest regression analysis as well as full subset regression analysis. To validate the expression differences of key genes, we employed experimental methods such as quantitative Polymerase Chain Reaction (qPCR) and assessed cell line proliferation, migration, and invasion. Three subtypes were assigned to patients diagnosed with LGG. Notably, Cluster 2 (C2), exhibiting the poorest survival outcomes, manifested characteristics indicative of the subtype characterized by immunosuppression. This was marked by elevated levels of M1 macrophages, activated mast cells, along with higher immune and stromal scores. Four hub genes—CDCA8, ORC1, DLGAP5, and SMC4—were identified and validated through cell experiments and qPCR. Subsequently, these validated genes were utilized to construct a stemness risk signature. Which revealed that Lower-Grade Glioma (LGG) patients with lower scores were more inclined to demonstrate favorable responses to immune therapy. Our study illuminates the stemness characteristics of gliomas, which lays the foundation for developing therapeutic approaches targeting CSCs and enhancing the efficacy of current immunotherapies. By identifying the stemness subtype and its correlation with prognosis and TME patterns in glioma patients, we aim to advance the development of personalized treatments, enhancing the ability to predict and improve overall patient prognosis.

This study selects provincial panel data from 2008 to 2019 and constructs a panel vector autoregressive (PVAR) model to explore the bidirectional interactive relationship between digital economy, consumption upgrading and domestic demand level through the Granger causality test, the analysis of impulse response function and variance decomposition. Firstly, the GMM estimation results show that there is a significant bidirectional interactive effect between digital economy and domestic demand level, and a significant bidirectional interactive effect between digital economy and consumption upgrading, while the interactive effect between consumption upgrading and domestic demand level is weak. Secondly, the analysis of impulse response function shows that domestic demand level can sustainably promote the development of digital economy, and the promotion effect of digital economy on domestic demand level is immediate. However, in the long run, digital economy has a gradually weakening hindering effect on domestic demand level. Digital economy and consumption upgrading show a “V-shaped” relationship. The shackles of mutual promotion between consumption structure and scale still exist. Thirdly, the analysis of variance decomposition shows that the mutual contribution rate of digital economy and domestic demand level is low, the mutual contribution rate of digital economy and consumption upgrading is high, and the mutual contribution rate of consumption upgrading and domestic demand level is low. The implications in this study can help drive digital economy development, promote consumption upgrading and raise domestic demand level.

The prevalent itching condition associated with aging, historically referred to as senile pruritus, diminishes quality of life. Despite its impact, effective treatments remain elusive, largely due to an incomplete understanding of its pathological cause. In this study, we reveal a subset of dorsal root ganglion neurons enriched with Zn2+ that express the vesicular Zn2+ transporter TMEM163. These neurons form direct synapses with and modulate the activity of spinal NPY+ inhibitory interneurons. In aged mice, both the expression of TMEM163 and the concentration of vesicular Zn2+ within the central terminals of TMEM163+ primary afferents show marked elevation. Importantly, the excessive release of vesicular Zn2+ significantly dampens the activity of NPY+ neurons, triggering the disinhibition of itch-transmitting neural circuits and resulting in chronic itch. Intriguingly, chelating Zn2+ within the spinal dorsal horn effectively relieves itch in aged mice. Our study thus unveils a novel molecular mechanism underlying senile pruritus.

The increasing environmental presence of nanoplastics (NPs) has raised concerns about their potential impact on biological systems. We investigated the repercussions of polymethyl methacrylate (PMMA) NPs exposure on normal gastric epithelial cells and revealed a pronounced increase in senescence-associated β-galactosidase activity and G1 phase cell cycle arrest. Our study demonstrated a dose-dependent increase in reactive oxygen species (ROS) and DNA damage, underscoring the pivotal role of ROS in PMMA NPs-mediated effects, a novel contribution to the existing body of knowledge dominated by polystyrene particles. Furthermore, we explored the influence of PMMA NPs on DNA damage response mechanisms, highlighting the significant inhibition of nonhomologous end-joining (NHEJ). Our findings help to elucidate the consequent genomic instability, as evidenced by increased chromosomal aberrations and micronuclei formation. By connecting these cellular manifestations to organism-level effects, we hypothesize that PMMA NPs play a critical role in aging processes. Our work revealed an activated cGAS-STING signaling pathway after PMMA NPs exposure, which correlated with aging-related inflammation and behavioral changes in mice. Importantly, our study provides comprehensive evidence of PMMA NPs-induced premature aging in gastric epithelial cells, shedding light on the molecular intricacies underlying DNA damage, repair impairment, and inflammation. Our research prompts heightened caution regarding the risks of NPs exposure and calls for further investigation into the broader implications of these environmental pollutants on aging processes in higher organisms.

Factor XI deficiency is a rare inherited coagulation disorder with an estimated prevalence of affecting 1 in 1 million. It is characterized by mild and variable bleeding phenotypes, including bruises, nosebleeds, hematuria, and postpartum hemorrhage. It can be caused by either allelic or biallelic variants in coagulation factor XI (F11). Coagulation factor XI is a glycoprotein that circulates in plasma as a non-covalent complex with high-molecular-weight kininogen. It is converted to an active protease, coagulation factor XIa, which participates in blood coagulation as a catalyst. In this study, we recruited a family with Factor XI deficiency and identified two F11 variants using whole-exome sequencing. One (NM_000128.4: c.841C>T, p.Q281X) was a known variant, and the other (NM_000128.4: c.1832T>G, p.V611G) had not been reported. In addition, we compiled the characteristics of known missense variants in coagulation factor XI. Our findings enriched the variant spectrum of Factor XI deficiency and contributed to the genetic counseling and molecular diagnostics of Factor XI deficiency.

This study examines the link between genuine earnings management and management's integrity commitment using data from A-share listed firms on the Shanghai and Shenzhen stock exchanges (2007–2021). Findings indicate that following genuine earnings management, management tends to emphasize integrity in the MD&A section of annual reports, suggesting moral camouflage in response to negative moral emotions. This behavior is more pronounced with higher information asymmetry between management and investors, amplifying the tendency towards moral camouflage. Further analysis shows that post-earnings management, there is no significant increase in charitable contributions or CSR performance, and agency costs remain high, underscoring a preference for moral camouflage over moral purity. Additionally, management's integrity commitment does not affect analysts' future market valuations or reduce the likelihood of regulatory inquiries. The study also finds that the relationship between earnings management and integrity commitment strengthens under increased moral pressure. This research provides theoretical insights into executive behavior driven by negative moral emotions and offers practical implications for investors, auditors, and regulators.

Background: The purpose of this study was to investigate the vessel density (VD) of the macular superficial capillary plexus (SCP) and its associated factors in healthy subjects. Methods: This prospective, cross-sectional study enrolled healthy Chinese volunteers. The optical coherence tomography angiography (OCTA) was used to measure the superficial VD in macula. A generalized estimation equation (GEE) model was used to analyze the ocular and systemic associated factors. Results: A total of 516 eyes of 262 healthy subjects were included (mean age 38.59 ± 21.03 years). The total VD of macular SCP was 16.85 ± 2.28 mm−1. The VD in the inner ring and outer ring were significantly higher than that in the central ring, with the density being highest in nasal quadrant and lowest in the superior quadrant. After adjusting the ocular and systemic factors, age (β=-0.0085, P = 0.0122) and SSI (β=1.3261, P < 0.001) were significantly associated with total VD of the macular SCP. Conclusions: Among the healthy Chinese subjects included in the study, the mean total VD of macular SCP was 16.85 ± 2.28mm-1. The macular superficial capillary density was positively associated with age and SSI. Further studies are still required to better understand the change of macular VD in aging and other pathological conditions.

BackgroundThere is still a lack of clinically validated biomarkers to screen lung cancer patients suitable for programmed dead cell-1 (PD-1)/programmed dead cell receptor-1 (PD-L1) immunotherapy. Detection of PD-L1 expression is invasively operated, and some PD-L1-negative patients can also benefit from immunotherapy; thus, the joint modeling of both deep learning images and clinical features was used to improve the prediction performance of PD-L1 expression in non-small cell lung cancer (NSCLC).MethodsRetrospective collection of 101 patients diagnosed with pathology in our hospital who underwent 18F FDG PET/CT scans, with lung cancer tissue Tumor Propulsion Score (TPS) ≥1% as a positive expression. Lesions were extracted after preprocessing PET/CT images, and using deep learning 3D DenseNet121 to learn lesions in PET, CT, and PET/CT images, 1,024 fully connected features were extracted; clinical features (age, gender, smoking/no smoking history, lesion diameter, lesion volume, maximum standard uptake value of lesions [SUVmax], mean standard uptake value of lesions [SUVmean], total lesion glycolysis [TLG]) were combined for joint modeling based on the structured data Category Embedding Model.ResultsArea under a receiver operating characteristic (ROC) curve (AUC) and accuracy of predicting PD-L1 positive for PET, CT, and PET/CT test groups were 0.814 ± 0.0152, 0.7212 ± 0.0861, and 0.90 ± 0.0605, 0.806 ± 0.023, 0.70 ± 0.074, and 0.950 ± 0.0250, respectively. After joint clinical feature modeling, the AUC and accuracy of predicting PD-L1 positive for PET/CT were 0.96 ± 0.00905 and 0.950 ± 0.0250, respectively.ConclusionThis study combines the features of 18F-FDG PET/CT images with clinical features using deep learning to predict the expression of PD-L1 in NSCLC, suggesting that 18F-FDG PET/CT images can be conducted as biomarkers for PD-L1 expression.

BackgroundDespite the emerging application of clinical decision support systems (CDSS) in pregnancy care and the proliferation of artificial intelligence (AI) over the last decade, it remains understudied regarding the role of AI in CDSS specialized for pregnancy care. ObjectiveTo identify and synthesize AI-augmented CDSS in pregnancy care, CDSS functionality, AI methodologies, and clinical implementation, we reported a systematic review based on empirical studies that examined AI-augmented CDSS in pregnancy care. MethodsWe retrieved studies that examined AI-augmented CDSS in pregnancy care using database queries involved with titles, abstracts, keywords, and MeSH (Medical Subject Headings) terms. Bibliographic records from their inception to 2022 were retrieved from PubMed/MEDLINE (n=206), Embase (n=101), and ACM Digital Library (n=377), followed by eligibility screening and literature review. The eligibility criteria include empirical studies that (1) developed or tested AI methods, (2) developed or tested CDSS or CDSS components, and (3) focused on pregnancy care. Data of studies used for review and appraisal include title, abstract, keywords, MeSH terms, full text, and supplements. Publications with ancillary information or overlapping outcomes were synthesized as one single study. Reviewers independently reviewed and assessed the quality of selected studies. ResultsWe identified 30 distinct studies of 684 studies from their inception to 2022. Topics of clinical applications covered AI-augmented CDSS from prenatal, early pregnancy, obstetric care, and postpartum care. Topics of CDSS functions include diagnostic support, clinical prediction, therapeutics recommendation, and knowledge base. ConclusionsOur review acknowledged recent advances in CDSS studies including early diagnosis of prenatal abnormalities, cost-effective surveillance, prenatal ultrasound support, and ontology development. To recommend future directions, we also noted key gaps from existing studies, including (1) decision support in current childbirth deliveries without using observational data from consequential fetal or maternal outcomes in future pregnancies; (2) scarcity of studies in identifying several high-profile biases from CDSS, including social determinants of health highlighted by the American College of Obstetricians and Gynecologists; and (3) chasm between internally validated CDSS models, external validity, and clinical implementation.

Objective: Though an increased risk of atherosclerosis is associated with anti-CTLA-4 antibody therapy, the underlying mechanisms remain unclear. Methods: C57BL/6 mice were treated with anti-cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) antibody twice a week for 4 weeks, after being injected with AAV8-PCSK9 and fed a Paigen diet (PD). The proportion of aortic plaque and lipid accumulation were assessed using Oil Red O staining, while the morphology of atherosclerotic lesions was analyzed with hematoxylin and eosin staining. Collagen content was evaluated through Picrosirius Red (PSR) staining, while inflammatory cell infiltration was examined with immunofluorescence staining. CD4+ T cells secreting IFN-γ and IL-4, which represent Th1 and Th2 cells respectively, were detected by flow cytometry and real-time PCR. Protein levels of p-IκBα, IκBα, p-p65, and p65 were determined by Western blot. Results: Inhibiting CTLA-4 exacerbated PD-induced plaque progression and promoted CD4+ T cell infiltration in the aortic root. The anti-CTLA-4 antibody promoted CD4+ T cell differentiation toward the Th1 type, as indicated by an increase in the Th1/Th2 ratio. Compared to the anti-IgG group, treatment with anti-CTLA-4 antibody significantly elevated the protein levels of p-IκBα and p-p65, as well as the mRNA levels of TNF-α, IL-6, ICAM-1, and VCAM-1. Inhibiting the NF-κB signaling pathway attenuated the overall pathological phenotype induced by the anti-CTLA-4 antibody treatment. Conclusion: Anti-CTLA-4 treatment promotes the progression of atherosclerosis by activating NF-κB signaling and modulating the Th1/Th2 balance. Our results provide a rationale for preventing and/or treating atherosclerosis accelerated by anti-CTLA-4 antibody therapy in cancer patients.

Abstract The risk for suffering immune checkpoint inhibitors (ICIs)‐associated myocarditis increases in patients with pre‐existing conditions and the mechanisms remain to be clarified. Spatial transcriptomics, single‐cell RNA sequencing, and flow cytometry are used to decipher how anti‐cytotoxic T lymphocyte antigen‐4 m2a antibody (anti‐CTLA‐4 m2a antibody) aggravated cardiac injury in experimental autoimmune myocarditis (EAM) mice. It is found that anti‐CTLA‐4 m2a antibody increases cardiac fibroblast‐derived C‐X‐C motif chemokine ligand 1 (Cxcl1), which promots neutrophil infiltration to the myocarditic zones (MZs) of EAM mice via enhanced Cxcl1‐Cxcr2 chemotaxis. It is identified that the C–C motif chemokine ligand 5 (Ccl5)‐neutrophil subpopulation is responsible for high activity of cytokine production, adaptive immune response, NF‐κB signaling, and cellular response to interferon‐gamma and that the Ccl5‐neutrophil subpopulation and its‐associated proinflammatory cytokines/chemokines promoted macrophage (Mφ) polarization to M1 Mφ. These altered infiltrating landscape and phenotypic switch of immune cells, and proinflammatory factors synergistically aggravated anti‐CTLA‐4 m2a antibody‐induced cardiac injury in EAM mice. Neutralizing neutrophils, Cxcl1, and applying Cxcr2 antagonist dramatically alleviates anti‐CTLA‐4 m2a antibody‐induced leukocyte infiltration, cardiac fibrosis, and dysfunction. It is suggested that Ccl5‐neutrophil subpopulation plays a critical role in aggravating anti‐CTLA‐4 m2a antibody‐induced cardiac injury in EAM mice. This data may provide a strategic rational for preventing/curing ICIs‐associated myocarditis.

Abstract Aqueous zinc‐ion batteries have been regarded as the most potential candidate to substitute lithium‐ion batteries. However, many serious challenges such as suppressing zinc dendrite growth and undesirable reactions, and achieving fully accepted mechanism also have not been solved. Herein, the commensal composite microspheres with α‐MnO2 nano‐wires and carbon nanotubes were achieved and could effectively suppress ZnSO4·3Zn(OH)2·nH2O rampant crystallization. The electrode assembled with the microspheres delivered a high initial capacity at a current density of 0.05 A g−1 and maintained a significantly prominent capacity retention of 88% over 2500 cycles. Furthermore, a novel energy‐storage mechanism, in which multivalent manganese oxides play a synergistic effect, was comprehensively investigated by the quantitative and qualitative analysis for ZnSO4·3Zn(OH)2·nH2O. The capacity contribution of multivalent manganese oxides and the crystal structure dissection in the transformed processes were completely identified. Therefore, our research could provide a novel strategy for designing improved electrode structure and a comprehensive understanding of the energy storage mechanism of α‐MnO2 cathodes.

Abstract Aspirin is widely used for both primary and secondary prevention of panvascular diseases, such as stroke and coronary heart disease (CHD). The optimal balance between reducing panvascular disease events and the potential increase in bleeding risk remains unclear. This study aimed to develop a predictive model specifically designed to assess bleeding risk in individuals using aspirin. A total of 58,415 individuals treated with aspirin were included in this study. Detailed data regarding patient demographics, clinical characteristics, comorbidities, medical history, and laboratory test results were collected from the Affiliated Dongyang Hospital of Wenzhou Medical University. The patients were randomly divided into two groups at a ratio of 7:3. The larger group was used for model development, while the smaller group was used for internal validation. To develop the prediction model, we employed least absolute shrinkage and selection operator (LASSO) regression followed by multivariate logistic regression. The performance of the model was assessed through metrics such as the area under the receiver operating characteristic (ROC) curve (AUC), calibration curves, and decision curve analysis (DCA). The LASSO-derived model employed in this study incorporated six variables, namely, sex, operation, previous bleeding, hemoglobin, platelet count, and cerebral infarction. It demonstrated excellent performance at predicting bleeding risk among aspirin users, with a high AUC of 0.866 (95% CI 0.857–0.874) in the training dataset and 0.861 (95% CI 0.848–0.875) in the test dataset. At a cutoff value of 0.047, the model achieved moderate sensitivity (83.0%) and specificity (73.9%). The calibration curve analysis revealed that the nomogram closely approximated the ideal curve, indicating good calibration. The DCA curve demonstrated a favorable clinical net benefit associated with the nomogram model. Our developed LASSO-derived predictive model has potential as an alternative tool for predicting bleeding in clinical settings.

With the continuous improvement of living standards, people are concerned about not only whether foods are tasty or not, but also the combination of health elements and good flavor. Food flavor components are not only important factors in sensory quality, but also key indicators of the nutritional level of foods. At present, the traditional methods to evaluate and predict food flavor components are time-consuming and labor-intensive, and unable to handle large amounts of data. In contrast, machine learning (ML), the core of artificial intelligence, has incomparable advantages over traditional analytical techniques in distinguishing differences and finding commonalities, and has found good application in the field of food flavor analysis. In this context, this paper focuses on the current research status of ML in the field of food flavor, and introduces the principles and advantages of commonly used ML methods, as well as their latest applications and prospects in food flavor prediction and regulation. It also focuses on the advantages and future trends of modern intelligent sensory evaluation techniques combined with ML in the field of food flavor analysis, with a view to providing new ideas and theoretical foundations for food flavor analysis and prediction.

To compare the volatile flavor characteristics of red jujube from different origins, volatile aroma components of jujube fruit from five origins (Xinzheng, Lingbao, Yulin, Hotan and Dezhou) were analyzed by headspace solid-phase microextraction combined with gas chromatography mass spectrometry. The results showed that a total of 51 compounds were identified, among which the most volatile compounds were contained in Xinjiang Hotan jujube. Combined with multivariate statistical analysis, the differences in the overall volatile flavor substances of red jujube from different origins could be well distinguished. Under the conditions of satisfying the variable importance in projection>1 and P

Abstract Background Type 2 diabetes mellitus (T2DM) causes severe bone loss after tooth extraction as a hyperglycemic environment causes aberrant bone homeostasis. Artesunate (ART) is known to possess anti-inflammation and osteogenic properties. However, its osteogenesis property in alveolar bone remains unclear. This study aimed to explore the osteogenic and immunoregulatory effects of artesunate-loaded thermosensitive chitosan hydrogel (ART-loaded TCH) on maxilla tooth extraction in T2DM rats. Methods T2DM rats were induced by a high-fat diet and streptozotocin. Different concentrations of ART-loaded TCH were applied in tooth extraction sockets. Bone loss and the expression of osteogenic regulatory factors (OPG, ALP, RANK) were evaluated. The immunoregulatory effects of ART-loaded TCH were observed through detecting the infiltration of T lymphocytes and their cytokines. The underlying mechanisms were explored. Results Results showed that the 150 mg/ml ART-loaded TCH group significantly ameliorated maxilla bone height and bone mineral density when compared with the T2DM group (p

The longitudinal dispersion of the projectile in shooting tests of two-dimensional trajectory corrections fused with fixed canards is extremely large that it sometimes exceeds the correction ability of the correction fuse actuator. The impact point easily deviates from the target, and thus the correction result cannot be readily evaluated. However, the cost of shooting tests is considerably high to conduct many tests for data collection. To address this issue, this study proposes an aiming method for shooting tests based on small sample size. The proposed method uses the Bootstrap method to expand the test data; repeatedly iterates and corrects the position of the simulated theoretical impact points through an improved compatibility test method; and dynamically adjusts the weight of the prior distribution of simulation results based on Kullback–Leibler divergence, which to some extent avoids the real data being ''submerged'' by the simulation data and achieves the fusion Bayesian estimation of the dispersion center. The experimental results show that when the simulation accuracy is sufficiently high, the proposed method yields a smaller mean-square deviation in estimating the dispersion center and higher shooting accuracy than those of the three comparison methods, which is more conducive to reflecting the effect of the control algorithm and facilitating test personnel to iterate their proposed structures and algorithms.; in addition, this study provides a knowledge base for further comprehensive studies in the future.