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Mental rotation has emerged as an important predictor for success in science, technology, engineering, and math fields. Previous studies have shown that males and females perform mental rotation tasks differently. However, how the brain functions to support this difference remains poorly understood. Recent advancements in neuroimaging techniques have enabled the identification of sex differences in large-scale brain network connectivity. Using a classic mental rotation task with functional magnetic resonance imaging, the present study investigated whether there are any sex differences in large-scale brain network connectivity for mental rotation performance. Our results revealed that, relative to females, males exhibited less cross-network interaction (i.e. lower inter-network connectivity and participation coefficient) of the visual network but more intra-network integration (i.e. higher intra-network connectivity and local efficiency) and cross-network interaction (i.e. higher inter-network connectivity and participation coefficient) of the salience network. Across all participants, mental rotation performance was negatively correlated with cross-network interaction (i.e. participation coefficient) of the visual network, was positively correlated with cross-network interaction (i.e. inter-network connectivity) of the salience network, and was positively correlated with intra-network integration (i.e. local efficiency) of the somato-motor network. Interestingly, the cross-network integration indexes of both the visual and salience networks significantly mediated sex difference in mental rotation performance. The present findings suggest that large-scale brain network connectivity may constitute an essential neural basis for sex difference in mental rotation, and highlight the importance of considering sex as a research variable in investigating the complex network underpinnings of spatial cognition.

BackgroundThis systematic review and meta-analysis aimed to explore the effects of different sodium–glucose cotransporter-2 inhibitors (SGLT2i) on prognosis and cardiac structural remodeling in patients with heart failure (HF).MethodsRelevant studies published up to 20 March 2024 were retrieved from PubMed, EMBASE, Web of Science, and Cochrane Library CNKI, China Biomedical Literature Service, VIP, and WanFang databases. We included randomized controlled trials of different SGLT2i and pooled the prognosis data of patients with HF. We compared the efficacy of different SGLT2i in patients with HF and conducted a sub-analysis based on left ventricular ejection fraction (LVEF).ResultsWe identified 77 randomized controlled trials involving 43,561 patients. The results showed that SGLT2i significantly enhanced outcomes in HF, including a composite of hospitalizations for HF and cardiovascular death, individual hospitalizations for HF, Kansas City Cardiomyopathy Questionnaire (KCCQ) scores, left atrial volume index (LAVi), and LVEF among all HF patients (P

Abstract To promote the widespread use of mobile robots in diverse fields, the performance of trajectory tracking must be ensured. To address the constraints and nonlinear features associated with mobile robot systems, nonlinear model predictive control (MPC) is applied to realize trajectory tracking of mobile robots. Specifically, to alleviate the online computational complexity of nonlinear MPC, this paper devises a lattice piecewise affine (PWA) approximation method that can approximate both the nonlinear system and control law of explicit nonlinear MPC. The kinematic model of the mobile robot is successively linearized along the trajectory to obtain a linear time‐varying description of the system, which is then expressed using a lattice PWA model. Subsequently, the nonlinear MPC problem can be transformed into a series of linear MPC problems. Furthermore, to reduce the complexity of online calculation of multiple linear MPC problems, the optimal solution of the linear MPCs is approximated by using the lattice PWA models. That is, for different sampling states, the optimal control inputs are obtained offline, and lattice PWA approximations are constructed for the state control pairs. Simulations are performed to evaluate the performance of the method in comparison with the state‐of‐the‐art methods, and the results show that the method has a higher online computing speed and can decrease the offline computing time without significantly increasing the tracking error.

B7 homolog 3 (B7-H3) has attracted much attention in glioblastoma (GBM) radioimmunotherapy (RIT) due to its abnormally high expression on tumor cells. In this study, we report that two specific humanized anti-human B7-H3 antibodies (hu4G4 and hu4H12) derived from mouse anti-human B7-H3 antibodies that were generated by computer-aided design and exclusively recognize membrane expression of B7-H3 by human glioma cells. Hu4G4 and hu4H12 were radiolabeled with 89Zr for RIT antibody screening. Micro-positron emission tomography (PET) imaging, biodistribution and pharmacokinetic (PK) analyses of 89Zr-labeled antibodies were performed in U87-xenografted models. 125I labelling of the antibodies for single-photon emission computed tomography (SPECT) imaging was also used to investigate the biological behavior of the antibodies in vivo. Furthermore, the pharmacodynamic (PD) of the 131I-labeled antibodies were evaluated in U87-xenografted mice and GL261 Red-FLuc-B7-H3 in situ glioma tumor models. Micro-PET imaging and biodistribution analysis with a gamma counter showed that 89Zr-deferoxamine (DFO)-hu4G4 had higher tumor targeting performance with lower liver uptake than 89Zr-DFO-(hu4H12, immunoglobulin G (IgG)). The biodistribution results of 125I-SPECT imaging were similar to those of 89Zr-PET imaging, though the biodistribution in long bone joints and the thyroid varied. The PD analysis results indicated that 131I-hu4G4 had an excellent therapeutic effect and high safety with no apparent toxicity. Interestingly, 131I-hu4G4 improved the tumor vasculature in tissues with higher expression of collagen type IV and platelet-derived growth factor receptor β (PDGFR-β) compared with control treatment, as determined by immunofluorescence (IF), which contributed to inhibiting tumor growth. Taken together, our data indicate that hu4G4 exhibits good tumor targeting and specificity, achieves low nonspecific concentrations in normal tissues, and has acceptable PK characteristics. 131I-hu4G4 also exerts effective antitumor effects with an ideal safety profile. Therefore, we expect hu4G4 to be an excellent antibody for the development of GBM RIT.

Background: The long-term prognosis of heart failure with preserved ejection fraction (HFpEF) is influenced by malnutrition. Currently, there’s a deficit in objective and comprehensive nutritional assessment methods to evaluate the nutritional status and predicting the long-term outcomes of HFpEF patients. Methods: Our retrospective study included two hundred and eighteen elderly HFpEF patients admitted to the cardiovascular ward at the Air Force Medical Centre from January 2016 to December 2021. Based on follow-up outcomes, patients were categorized into all-cause death (99 cases) and Survival (119 cases) groups. We compared general data, laboratory results, and nutritional indexes between groups. Differences in subgroups based on Triglyceride-Total Cholesterol-Body Weight Index (TCBI), Geriatric Nutritional Risk Index (GNRI), Prognostic Nutritional Index (PNI), and Controlled Nutrition Score (CONUT) were analyzed using Kaplan-Meier survival curves and log-rank test. COX regression was used to identify all-cause mortality risk factors, and the predictive accuracy of the four nutritional indices was assessed using receiver operating characteristic (ROC) curves and Delong test analysis. Results: A total of 101 (45.41%) HFpEF patients experienced all-cause mortality during 59.02 ± 1.79 months of follow-up. The all-cause mortality group exhibited lower GNRI and PNI levels, and higher CONUT levels than the Survival group (p < 0.05). Kaplan-Meier analysis revealed lower cumulative survival in the low GNRI (≤96.50) and low PNI (≤43.75) groups, but higher in the low CONUT (≤2) group, compared to their respective medium and high-value groups. Multifactorial COX regression identified low PNI (≤43.75) as an independent all-cause mortality risk factor in elderly HFpEF patients. ROC and Delong’s test indicated PNI (area under the curve [AUC] = 0.698, 95% confidence interval [CI] 0.629–0.768) as a more effective predictor of all-cause mortality than TCBI (AUC = 0.533, 95% CI 0.456–0.610) and CONUT (AUC = 0.621, 95% CI 0.547–0.695; p < 0.05). However, there was no significant difference compared to GNRI (AUC = 0.663, 95% CI 0.590–0.735; p > 0.05). Conclusions: In elderly HFpEF patients a PNI ≤43.75 was identified as an independent risk factor for all-cause mortality. Moreover, PNI demonstrates superior prognostic performance in predicting all-cause mortality in elderly patients with HFpEF when compared to TCBI, GNRI, and COUNT.

Background: Restenosis poses a significant challenge for individuals afflicted with peripheral artery diseases, often leading to considerable morbidity and necessitating repeated interventions. The primary culprit behind the pathogenesis of restenosis is intimal hyperplasia (IH), in which the hyperproliferative and migratory vascular smooth muscle cell (VSMC) accumulate excessively in the tunica intima. 6-Phosphogluconate dehydrogenase (6PGD), sometimes referred to as PGD, is one of the critical enzymes in pentose phosphate pathway (PPP). In this study, we sought to probe whether 6PGD is aberrantly regulated in IH and contributes to VSMC phenotypic switching. Methods: We used clinical specimens of diseased human coronary arteries with IH lesions and observed robust upregulation of 6PGD at protein level in both the medial and intimal layers in comparison with healthy arterial segments. Results: 6PGD activity and protein expression were profoundly stimulated upon platelet-derived growth factor-induced VSMC phenotypic switching. Using gain-of-function (dCas9-mediated transcriptional activation) and loss-of-function (small interfering RNA-mediated) silencing, we were able to demonstrate the pathogenic role of 6PGD in driving VSMC hyperproliferation, migration, dedifferentiation, and inflammation. Finally, we conducted a rat model of balloon angioplasty in the common carotid artery, with Pluronic hydrogel-assisted perivascular delivery of Physcion, a selective 6PGD inhibitor with poor systemic bioavailability, and observed effective mitigation of IH. Conclusions: We contend that aberrant 6PGD expression and activity—indicative of a metabolic shift toward pentose phosphate pathway—could serve as a new disease-driving mechanism and, hence, an actionable target for the development of effective new therapies for IH and restenosis after endovascular interventions.

Abdominal aortic aneurysm (AAA) is a permanent, asymptomatic segmental dilatation of the abdominal aorta, with a high mortality risk upon rupture. Identification of potential key genes and pathways may help to develop curative drugs for AAA. We conducted RNA-seq on abdominal aortic tissues from both AAA patients and normal individuals as a control group. Integrated bioinformatic analysis was subsequently performed to comprehensively reveal potential key genes and pathways. A total of 1148 differential expressed genes (DEGs) (631 up-regulated and 517 down-regulated) were identified in our study. Gene Ontology (GO) analysis revealed enrichment in terms related to extracellular matrix organization, while KEGG analysis indicated enrichment in hematopoietic cell lineage and ECM-receptor interaction. Protein-protein interaction (PPI) network analysis revealed several candidate key genes, and differential expression of 6 key genes (CXCL8, CCL2, PTGS2, SELL, CCR7, and CXCL1) was validated by Gene Expression Omnibus (GEO) datasets. Receiver operating characteristic curve (ROC) analysis demonstrated these genes’ high discriminatory ability between AAA and normal tissues. Immunohistochemistry indicated that several key genes were highly expressed in AAA tissues. Single-cell RNA sequencing revealed differential distribution patterns of these identified key genes among various cell types. 26 potential drugs linked to our key genes were found through DGIdb. Overall, our study provides a comprehensive evaluation of potential key genes and pathways in AAA, which could pave the way for the development of curative pharmacological therapies.

Vehicle tracking detection, recognition and counting is an important part of vehicle analysis. Designing such a model with excellent performance is difficult. The traditional target detection algorithm based on artificial features has poor generalization ability and robustness. In order to take use the deep learning method for vehicle tracking detection, recognition and counting, this paper proposes a vehicle detection method based on yolov5. This method uses the deep learning technology, takes the running vehicles video as the research object, analysis the target detection algorithm, proposes a vehicle detection framework and platform. The relevant detection algorithm of the platform designed in this paper has great adaptability, when displayed under various conditions, such as heavy traffic, night environment, multiple vehicles overlap with each other, partial loss of vehicles, etc. it has good performance. The experimental results show that the algorithm can accurately segment and identify vehicles according to the edge contour of vehicles. It can take use the materials includes pictures, videos, and real-time monitoring, and has a high recognition rate in real-time performance.

Deep vein thrombosis (DVT) is a life-threatening condition that can lead to its sequelae pulmonary embolism (PE) or post-thrombotic syndrome (PTS). Murine models of DVT are frequently used in early-stage disease research and to assess potential therapies. This creates the need for the reliable and easy quantification of blood clots. In this paper, we present a novel high-frequency 3D ultrasound approach for the quantitative evaluation of the volume of DVT in an in vitro model and an in vivo murine model. The proposed method involves the use of a high-resolution ultrasound acquisition system and semiautomatic segmentation of the clot. The measured 3D volume of blood clots was validated to be correlated with in vitro blood clot weights with an R2 of 0.89. Additionally, the method was confirmed with an R2 of 0.91 in the in vivo mouse model with a cylindrical volume from macroscopic measurement. We anticipate that the proposed method will be useful in pharmacological or therapeutic studies in murine models of DVT.

Background: Accurate detection of atrial fibrillation (AF) recurrence after catheter ablation is crucial. In this study, we aimed to conduct a systematic review of machine-learning-based recurrence detection in the relevant literature. Methods: We conducted a comprehensive search of PubMed, Embase, Cochrane, and Web of Science databases from 1980 to December 31, 2022 to identify studies on prediction models for AF recurrence risk after catheter ablation. We used the prediction model risk of bias assessment tool (PROBAST) to assess the risk of bias, and R4.2.0 for meta-analysis, with subgroup analysis based on model type. Results: After screening, 40 papers were eligible for synthesis. The pooled concordance index (C-index) in the training set was 0.760 (95% confidence interval [CI] 0.739 to 0.781), the sensitivity was 0.74 (95% CI 0.69 to 0.77), and the specificity was 0.76 (95% CI 0.72 to 0.80). The combined C-index in the validation set was 0.787 (95% CI 0.752 to 0.821), the sensitivity was 0.78 (95% CI 0.73 to 0.83), and the specificity was 0.75 (95% CI 0.65 to 0.82). The subgroup analysis revealed no significant difference in the pooled C-index between models constructed based on radiomics features and those based on clinical characteristics. However, radiomics based showed a slightly higher sensitivity (training set: 0.82 vs. 0.71, validation set: 0.83 vs. 0.73). Logistic regression, one of the most common machine learning (ML) methods, exhibited an overall pooled C-index of 0.785 and 0.804 in the training and validation sets, respectively. The Convolutional Neural Networks (CNN) models outperformed these results with an overall pooled C-index of 0.862 and 0.861. Age, radiomics features, left atrial diameter, AF type, and AF duration were identified as the key modeling variables. Conclusions: ML has demonstrated excellent performance in predicting AF recurrence after catheter ablation. Logistic regression (LR) being the most widely used ML algorithm for predicting AF recurrence, also showed high accuracy. The development of risk prediction nomograms for wide application is warranted.

BackgroundRecently, identifying the psychological mechanism of college students’ loneliness has attracted wide attention because the maladjustment caused by college students’ loneliness is increasingly common. This study explored the relationship and potential mechanism between college students’ neuroticism and loneliness in a large sample.MethodsA total of 4,600 college students completed the Big Five Personality Scale, Loneliness Scale, Self-efficacy Scale and Social Avoidance and Distress Scale.ResultsBy examining the chain mediating roles of self-efficacy, social avoidance and distress (SAD) in the relation between neuroticism and loneliness, the present study found that college students’ neuroticism was positively associated with loneliness via self-efficacy and SAD, respectively, and sequentially.ConclusionsThe results suggest a significant positive association between neuroticism and loneliness, which is influenced by the mediating effects of both self-efficacy and social avoidance and distress (SAD), as well as the chained mediating effects of self-efficacy and SAD.

BackgroundPrevious observational studies have shown an association between smoking and coronary artery disease (CAD) in patients with diabetes. Whether this association reflects causality remains unestablished. This study aimed to explore the causal effect of smoking on CAD in patients with diabetes.MethodsGenetic signatures for smoking were extracted from a large genome-wide association study (GWAS), consisted of up to 1.2 million participants. Four smoking phenotypes were included: smoking initiation, cigarettes per day, age at initiation of regular smoking, and smoking cessation. Genetic associations with CAD in patients with diabetes were extracted from another GWAS, which included 15,666 participants (3,968 CAD cases and 11,696 controls). The analyses were performed using the univariable and multivariable Mendelian randomization (MR) method.ResultsMR analysis revealed that smoking initiation was positively related to CAD risk in patients with diabetes (OR = 1.322, 95% CI = 1.114 – 1.568, P = 0.001), but this association was attenuated when adjusted for cardiovascular risk factors (OR = 1.212, 95% CI = 1.008 – 1.457, P = 0.041). Age at initiation of regular smoking was negatively related to CAD in patients with diabetes (OR = 0.214, 95% CI = 0.070 – 0.656, P = 0.007), but this association became insignificant when adjusted for cardiovascular risk factors.ConclusionsThis study supported the effect of smoking initiation on the risk of CAD in patients with diabetes.

Biofilms enable bacterial cells to adhere and thrive on surfaces, with associated changes in growth and gene expression aiding their survival in challenging environments. While previous research has explored E. coli biofilm formation, there has been limited exploration of its application in industrial production. Prior studies have shown that immobilized fermentation can enhance L-threonine production. This study aims to augment biofilm formation and subsequently increase L-threonine production in E. coli by regulating the quorum sensing system, focusing on key AI-2-related genes, including luxS, lsrB, lsrK, and lsrR. In +pluxS and +plsrB strains, AI-2 levels were significantly altered, resulting in enhanced biofilm formation, increased curli expression, shorter free-cell fermentation periods, and improved production efficiency through immobilized continuous fermentation. In a single batch of free-cell fermentation with E. coli W1688, L-threonine production was 10.16 g/L. However, +pluxS and +plsrB strains achieved L-threonine yields of 15.27 g/L and 13.38 g/L, respectively, after seven fermentation batches. Additionally, the fermentation period was reduced from 36 h to 28 h and 30 h, respectively.

Abstract Background To investigate the causal association between serum 25-hydroxyvitamin D (25OHD), calcium (Ca), and parathyroid hormone (PTH) levels and the risk of coronary artery disease (CAD) in patients with diabetes using a Mendelian randomization approach. Methods Genetic signatures associated with serum 25OHD, Ca, and PTH levels were extracted from recently published genome-wide association study (GWAS), including 79,366, 39,400, 29,155 individuals, respectively. Genetic association estimates for CAD in patients with diabetes were obtained from a GWAS of 15,666 individuals with diabetes (3,968 CAD cases, 11,696 controls). The inverse-variance-weighted method was employed for the primary analysis, and other robust methods were applied for sensitivity analyses. Results Six, seven and five single nucleotide polymorphisms were identified as instrumental variables for serum 25OHD, Ca and PTH levels, respectively. There was no significant association between genetically predicted serum 25OHD levels and the risk of CAD in patients with diabetes (odds ratio (OR) = 1.04, 95% confidence interval (CI): 0.58 - 1.87, P = 0.888). Similarly, genetically predicted serum Ca (OR = 1.83, 95% CI: 0.62 – 5.35, P = 0.273) and PTH levels (OR = 1.27, 95% CI: 0.67 – 2.44, P = 0.464) were not significantly associated with the risk of CAD in patients with diabetes. These findings were robust in sensitivity analyses. Conclusions/interpretation Serum 25OHD, Ca and PTH levels may not be causally associated with the risk of CAD in patients with diabetes.

ABSTRACT Escherichia coli biofilm may form naturally on biotic and abiotic surfaces; this represents a promising approach for efficient biochemical production in industrial fermentation. Recently, industrial exploitation of the advantages of optogenetics, such as simple operation, high spatiotemporal control, and programmability, for regulation of biofilm formation has garnered considerable attention. In this study, we used the blue light signaling-induced optogenetic system Magnet in an E. coli biofilm-based immobilized fermentation system to produce l-threonine in sufficient quantity. Blue light signaling significantly affected the phenotype of E. coli W1688. A series of biofilm-related experiments confirmed the inhibitory effect of blue light signaling on E. coli W1688 biofilm. Subsequently, a strain lacking a blue light-sensing protein (YcgF) was constructed via genetic engineering, which substantially reduced the inhibitory effect of blue light signaling on biofilm. A high-efficiency biofilm-forming system, Magnet, was constructed, which enhanced bacterial aggregation and biofilm formation. Furthermore, l-threonine production was increased from 10.12 to 16.57 g/L during immobilized fermentation, and the fermentation period was shortened by 6 h. IMPORTANCE We confirmed the mechanism underlying the inhibitory effects of blue light signaling on E. coli biofilm formation and constructed a strain lacking a blue light-sensing protein; this mitigated the aforementioned effects of blue light signaling and ensured normal fermentation performance. Furthermore, this study elucidated that the blue light signaling-induced optogenetic system Magnet effectively regulates E. coli biofilm formation and contributes to l-threonine production. This study not only enriches the mechanism of blue light signaling to regulate E. coli biofilm formation but also provides a theoretical basis and feasibility reference for the application of optogenetics technology in biofilm-based immobilized fermentation systems.

Abstract Background Balloon dilatation with stent implantation has been proved to be an effective option for left iliac vein compression syndrome (LIVCS), but thrombosis may still occur after the operation. Currently, warfarin is used for anticoagulant therapy, but long-term monitoring is required, while rivaroxaban does not need laboratory monitoring, which can simplify treatment. Therefore, this study aimed to compare the efficacy and safety of rivaroxaban and warfarin in anticoagulation. Methods This study is a multicenter, randomized controlled trial. We will recruit 224 patients with thrombotic LIVCS from 9 hospitals. Moreover, these patients will be randomized to either the experimental group (rivaroxaban) or the control group (warfarin plus nadroparin). The primary outcome is stent occlusion rate. Secondary outcomes are quality of life scale survey results, all-cause mortality, anticoagulation-related mortality, and the proportion of participants with stent displacement/fracture, thrombosis, hemorrhage, and other vascular events. Discussion This study will provide reliable, evidence-based clinical evidence for the efficacy and safety of rivaroxaban antithrombotic therapy after stent implantation. Trial registration ClinicalTrials.gov NCT04067505 . Registered on August 26, 2019.

Background: Although several observational studies have shown an association between birth weight (BW) and atrial fibrillation (AF), controversy remains. In this study, we aimed to explore the role of elevated BW on the etiology of AF.Methods: A two-sample Mendelian randomization (MR) study was designed to infer the causality. The genetic data on the associations of single-nucleotide polymorphisms (SNPs) with BW and AF were separately obtained from two large-scale genome-wide association studies with up to 321,223 and 1,030,836 individuals, respectively. SNPs were identified at a genome-wide significant level (p

An abdominal aortic aneurysm (AAA) is a localized dilatation of the aorta related to the regional weakening of the wall structure, resulting in substantial morbidity and mortality with the aortic ruptures as complications. Ruptured AAA is a dramatic catastrophe, and aortic emergencies constitute one of the leading causes of acute death in older adults. AAA management has been centered on surgical repair of larger aneurysms to mitigate the risks of rupture, and curative early diagnosis and effective pharmacological treatments for this condition are still lacking. Nanoscience provided a possibility of more targeted imaging and drug delivery system. Multifunctional nanoparticles (NPs) may be modified with ligands or biomembranes to target agents' delivery to the lesion site, thus reducing systemic toxicity. Furthermore, NPs can improve drug solubility, circulation time, bioavailability, and efficacy after systemic administration. The varied judiciously engineered nano-biomaterials can exist stably in the blood vessels for a long time without being taken up by cells. Here, in this review, we focused on the NP application in the imaging and treatment of AAA. We hope to make an overview of NP-assisted diagnoses and therapy in AAA and discussed the potential of NP-assisted treatment.

BackgroundAlthough several observational studies have suggested an association of elevated plasma homocysteine (Hcy) levels with increased risk of atrial fibrillation (AF), it remains unclear whether this association reflects causality. In this study, we aimed to investigate the causal association of plasma Hcy levels with AF risk.MethodsA two-sample Mendelian randomization (MR) study was designed to investigate the causal association of Hcy with AF. Summary data on association of single nucleotide polymorphisms (SNPs) with Hcy were extracted from the hitherto largest genome-wide association study (GWAS) with up to 44,147 individuals, and statistics data on association of SNPs with AF were obtained from another recently published GWAS with up to 1,030,836 individuals. SNPs were selected at a genome-wide significance threshold (p < 5 × 10–8). Fixed-effect inverse variance weighting (IVW) method was used to calculate the causal estimate. Other statistical methods and leave-one-out analysis were applied in the follow-up sensitivity analyses. MR-Egger intercept test was conducted to detect the potential directional pleiotropy.ResultsIn total, nine SNPs were identified as valid instrumental variables in our two-sample MR analysis. Fixed-effect IVW analysis indicated no evidence of causal association of genetically predicted Hcy with AF. The odds ratio (OR) and 95% confidence interval (CI) of AF per standard deviation (SD) increase in Hcy were 1.077 (0.993, 1.168), p = 0.075. Similar results were observed in the sensitivity analyses. MR-Egger intercept test suggested no evidence of potential horizonal pleiotropy.ConclusionsThis two-sample MR analysis found no evidence to support causal association of Hcy with AF.