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Abstract Underwater target detection technology is very important for Marine resources detection and underwater environment perception. The problems of low-quality underwater images, a large amount of calculation, and low accuracy of target detection models still need to be solved. Firstly, a new underwater image enhancement algorithm based on multi-scale fusion is proposed. The algorithm combines the improved white balance algorithm and the improved CLAHE (Contrast Limited Adaptive Histogram Equalization) and realizes the multi-scale fusion strategy by introducing different weight maps, aiming to improve the visual effect and quality of underwater images. Secondly, to further improve the accuracy and efficiency of underwater target detection, an improved YOLOv5s lightweight underwater target detection algorithm is proposed. The algorithm combines the Ghost convolution module, EMA(Efficient Multi-Scale Attention) mechanism, and CARAFE (Content-Aware ReAssembly of FEatures) up-sampling mode. The comparison on the URPC(Underwater Robot Perception Challenge) public dataset shows that the proposed algorithm has achieved significant improvement in terms of model size, parameter amount, calculation amount, and mAP@0.5. Thirdly, to verify the effectiveness of the image enhancement algorithm and underwater target detection algorithm proposed in this paper, the ROV(Remote Operated Vehicle) is used to conduct experiments in the experimental pool. By designing underwater target detection experiments before and after image enhancement, the results show that the enhanced image significantly improves the detection ability of underwater targets. Finally, underwater target detection software is developed to provide strong support for the application of underwater-related fields.

Abstract This randomized, prospective, multicenter (12 centers in China) phase III trial (Chinese Clinical Trial Registry #ChiCTR2000041170) compared drug-eluting bead transarterial chemoembolization (DEB-TACE) combined with apatinib and DEB-TACE monotherapy for patients with unresectable hepatocellular carcinoma (uHCC). Progression-free survival (PFS) was the primary endpoint. Overall survival (OS), mRECIST-based objective response rates (ORR) and disease control rates (DCR), and treatment-related adverse events (TRAEs) were secondary endpoints. Totally 243 cases were randomized, with 122 and 121 in the DEB-TACE + apatinib and DEB-TACE groups, respectively. Cases administered DEB-TACE + apatinib displayed markedly improved median PFS (7.1 months [95%CI 6.6–8.3] vs. 5.2 months [95%CI 5.0–5.9]) and OS (23.3 months [95%CI 20.7–29.6] vs. 18.9 months [95%CI 17.9–20.1] compared with those treated with DEB-TACE (both p

Based on the thermo-fluid-solid coupling law of coal and gas outburst in deep mining, a numerical model of coal and gas outburst is established, and the response of multi-physical parameters in the whole process of coal and gas outburst under high stress condition is analyzed. The results show that the response rule of the stress field around the outburst hole is initial vibration-sudden attenuation-late stability. The decreasing rate of gas pressure is negatively correlated with the length of the outburst hole. In the outburst process, the adsorbed gas contained in the crushed coal quickly desorbed and expanded to do work, resulting in a decrease in temperature; the areas with significant changes in permeability after outburst can be divided into sudden increase area, medium increase area and increase area. With the increase of stress, the proportion of elastic potential in total coal and gas outburst energy increases, and the proportion of elastic potential is positively correlated with stress.

Coal and gas outburst is one of the most serious kinetic disasters in coal mines, and the use of gas hydrate curing technology to reduce the gas pressure and its gradient in the coal body can reduce the probability of coal and gas outburst accidents. In order to investigate the influence of driving force on the growth kinetics of CH4 hydrate in coal medium, the experimental study on the growth kinetics of gas hydrate in coal medium under three driving force conditions was carried out by using the experimental system of gas hydrate growth kinetics, and the influence of the driving force on the parameters such as gas consumption and growth rate during the synthesis process of gas hydrate in coal medium was discussed. The results show that: within the same particle size range, the nucleation time of hydrate in each particle size range does not completely follow the law of subsequent shortening when the driving force is increased, and the nucleation of CH4 hydrate in coal medium has a certain degree of randomness; the phenomenon of multiple nucleation occurs in the synthesis process; the gas consumption of CH4 hydrate in the coal medium increases with the increase of the driving force; the growth rate of gas hydrate in coal medium is increased with the increase of the driving force, and the growth rate of gas hydrate in coal medium is improved with the increase of driving force under the condition of unchanged temperature and particle size. The effect of driving force on the average growth rate at the early stage of synthesis is more significant.

Early cancer diagnosis from bisulfite‐treated cell‐free DNA (cfDNA) fragments requires tedious data analytical procedures. Here, we present a deep‐learning‐based approach for early cancer interception and diagnosis (DECIDIA) that can achieve accurate cancer diagnosis exclusively from bisulfite‐treated cfDNA sequencing fragments. DECIDIA relies on transformer‐based representation learning of DNA fragments and weakly supervised multiple‐instance learning for classification. We systematically evaluate the performance of DECIDIA for cancer diagnosis and cancer type prediction on a curated dataset of 5389 samples that consist of colorectal cancer (CRC; n = 1574), hepatocellular cell carcinoma (HCC; n = 1181), lung cancer (n = 654), and non‐cancer control (n = 1980). DECIDIA achieved an area under the receiver operating curve (AUROC) of 0.980 (95% CI, 0.976–0.984) in 10‐fold cross‐validation settings on the CRC dataset by differentiating cancer patients from cancer‐free controls, outperforming benchmarked methods that are based on methylation intensities. Noticeably, DECIDIA achieved an AUROC of 0.910 (95% CI, 0.896–0.924) on the externally independent HCC testing set in distinguishing HCC patients from cancer‐free controls, although there was no HCC data used in model development. In the settings of cancer‐type classification, we observed that DECIDIA achieved a micro‐average AUROC of 0.963 (95% CI, 0.960–0.966) and an overall accuracy of 82.8% (95% CI, 81.8–83.9). In addition, we distilled four sequence signatures from the raw sequencing reads that exhibited differential patterns in cancer versus control and among different cancer types. Our approach represents a new paradigm towards eliminating the tedious data analytical procedures for liquid biopsy that uses bisulfite‐treated cfDNA methylome.

Abstract Background The biological significance of cancer-associated fibroblasts (CAFs) in bladder urothelial carcinoma (BUC) warrants further investigation. There is an urgent need to explore the predictive utility of CAF-related genes for prognosis in BUC. Methods The transcriptome and clinical data of 407 BUC patients in The Cancer Genome Atlas (TCGA) database were analyzed and a prognostic model was established. A total of 476 BUC cases from the E-MTAB-4321 database were used for validation. A risk model was constructed utilizing CAF-related genes through LASSO Cox regression, investigating its association with prognosis, gene mutations, immune cell infiltration, and drug sensitivity in BUC. Results We identified five CAF-related genes (EGFL6, NRSN2, SEMA3D, TM4SF1 and TPST1) in both the TCGA and E-MTAB-4321 datasets, and established a prognostic model using LASSO Cox regression. The high-risk group showed a significant correlation with poor survival. Furthermore, the low-risk group exhibited higher tumor mutational burden and lower levels of immune cell infiltration, and this model holds promise for guiding drug selection in BUC patients. Conclusions These findings underscore the pivotal role of CAF-related genes in prognostic prediction for BUC patients. Clinical decision-making and tailored therapeutics stand to benefit from these results, providing a valuable reference for future research endeavors.

Abstract Background During the COVID-19 pandemic, non-therapeutic interventions (NPIs), such as traffic restrictions, work stoppages, and school suspensions, have led to a sharp decline in the concentration of air pollutants in the epidemic sites. However, few studies focused on the impact of air pollutant changes on the risk of nonaccidental death. Method We selected Yancheng City, China, as the study site and applied a Generalized Additive Model (GAM) based on the quasi-Poisson distribution to evaluate the impact of atmospheric pollutants exposure on the nonaccidental death of local residents. The time span of this study was set from January 1, 2013, to December 21, 2022, that is, before and after the outbreak of COVID-19. Results The concentration of some air pollutants has greatly varied after the outbreak of COVID-19, with a significant decline for PM2.5 (− 43.4%), PM10 (− 38.5%), SO2 (− 62.9%), and NO2 (− 22.6%), but an increase for O3 (+ 4.3%). Comparative analysis showed that PM2.5 contributed to an increased risk of nonaccidental death after the outbreak of COVID-19. With an increase in PM2.5 by 10 µg/m³, the excess relative risks (ER) of nonaccidental death of residents increased by 1.01% (95%CI: 0.19%,1.84%). The stratified analysis revealed that air pollutants impacted nonaccidental deaths in both men and women before the outbreak of COVID-19. After the outbreak of COVID-19, PM10 had a significant effect on male nonaccidental deaths. The concentrations of PM2.5, PM10, and SO2 increased by 10 µg/m³, the ER of PM2.5, PM10, and SO2 on female nonaccidental death increased by 1.52% (0.38%,2.67%), 0.58% (0.02%,1.13%), and 15.09% (5.73%,25.28%), respectively. Before the outbreak of COVID-19, five air pollutants had an impact on the death of residents from cardiovascular disease (CVD). After the outbreak of COVID-19, only PM10 significantly affected the death risk of CVD. In addition, we discovered that PM2.5, PM10, and SO2 significantly impacted the risk of death due to respiratory diseases before and after the outbreak of COVID-19. Conclusions Air pollutants have different effects on nonaccidental deaths before and after the COVID-19 outbreak. A decrease in air pollutant concentration due to the NPIs for COVID-19 had a significant effect on the reduction of the risk of nonaccidental death.

Abstract. Background:. Thyroid cancer (TC) is the most common malignancy of the endocrine system. This study aimed to assess the global distribution of TC incidence and mortality in 2022, as well as to predict the burden for the year 2050. Methods:. Data from the GLOBOCAN 2022 database were used to analyze the age-standardized incidence and mortality rates of TC by sex, age group (

Abstract This work investigates the impact of different ultrasonic treatment durations on the synthesis and electrochemical performance of NiZnCo2O4 (NZC) supercapacitor electrodes. Optimizing treatment to 20 min resulted in a uniform, compact NiZnCo2O4 layer with improved nanostructures, which increased the surface area and active sites for electrochemical reactions. X-ray diffraction (XRD) confirmed successful NiZnCo2O4 synthesis, revealing distinct crystalline phases of NiO, ZnCo2O4, and Co3O4, with improved crystallinity. Electrochemical tests, conducted using a 1.0 M KOH electrolyte, demonstrated that the NZC-2 electrode treated for 20 min achieved the highest 5.678 F/cm3 volumetric capacitance at 0.5 mA/cm2 current density along with 70.5 Wh/kg an energy density at 260 W/kg power density. The galvanostatic charge-discharge and cyclic voltammetry tests revealed that NZC-2 maintained superior charge-discharge efficiency, showing the longest discharge time at 1 mA/cm². Electrochemical impedance spectroscopy (EIS) measurements demonstrated that NZC-2 exhibited the lowest total impedance, thereby enhancing ion transport efficiency. The NZC-2/AC asymmetric supercapacitor showed excellent long-term stability, retaining 64.2% of its capacity after 20,000 charge-discharge cycles. It successfully powered a 1.2 V small fan, demonstrating its practical applicability. The results highlight the crucial importance of ultrasonic treatment in greatly improving the structural and electrochemical characteristics of NiZnCo2O4 electrodes, which opens up possibilities for the advancement of high-performance supercapacitors.

ObjectiveThis paper seeks to solve the problem of the partial failure of the actuator of an underwater salvage robot caused by a decrease in the shipborne power supply voltage or corrosion of the control system circuit. Methods Considering the influence of complex ocean conditions on deep-sea torpedoes, cargo shipwrecks, and other engineering salvage operations, the terminal sliding mode observer is used to observe the uncertain disturbance of the system, while the fault-tolerant control method and finite-time control method are used to estimate the fault coefficient of the actuator on-line, and a finite-time trajectory tracking fault-tolerant control scheme with a terminal sliding mode observer is designed. ResultThe system output of this scheme is smooth, stable, and can reach the desired trajectory quickly. At the same time, compared with the traditional fault-tolerant control scheme, the steady-state time of the underwater salvage robot's control system is reduced (the lateral displacement is reduced by 10 s and the longitudinal displacement by 15 s).ConclusionThis study has practical engineering significance and can provide theoretical references for the trajectory tracking of underwater construction machinery.

Bromate–thiourea coordinated leaching of gold sulfide ore for gold sulfide ore as leaching object. The effects of leaching reagent, stirring speed, and leaching time on gold leaching were investigated in this article. The results showed that the optimum leaching conditions were potassium bromate 0.1 M, thiourea 0.6 g·L−1, hydrochloric acid 0.2 M, agitation speed 250 rpm, ratio of liquid to solid 4, and leaching time 10 min. Under these conditions, high efficiency and rapid leaching of gold can be achieved, and reagent consumption is reduced. The research results have theoretical and practical significance for expanding new green gold extraction technology.

Abstract This study evaluated the reliability and validity of the Chinese version of the “Motivational Climate in Physical Education Scale” (MCPES) among middle school students. Data were collected from 1,008 students, with 473 completing the MCPES, the Physical Needs Support in Physical Education Scale (PNS-PE), and the Youth Sports Friendship Quality Scale (YSFQS). Additionally, 437 students completed only the MCPES, and 200 valid retest questionnaires were gathered three weeks later. Exploratory factor analysis identified four factors: perceived mastery climate, perceived performance climate, perceived autonomy support, and perceived relatedness support with a total of 16 items. Confirmatory factor analysis supported the four-factor structure (χ2/df = 3.38, GFI = 0.92, NFI = 0.90, RMSEA = 0.07, CFI = 0.93, IFI = 0.93, SRMR = 0.05). The scale exhibited strict measurement invariance across genders and strong invariance across grade levels. It was positively correlated with teacher autonomy support (r = 0.34–0.53) and with each dimension and total score of sports friendship (r = 0.21–0.61). Cronbach’s α coefficients for the MCPES and its dimensions were 0.75, 0.82, 0.79, 0.80, and 0.88, respectively. Intraclass correlation coefficients (ICCs) for the three-week retest were 0.64, 0.63, 0.72, and 0.76. In conclusion, the Chinese version of the MCPES demonstrates robust reliability and validity for use with middle school students.

Abstract There is a significant interrelationship between cardiovascular disease and obstructive sleep apnea (OSA), as they share common risk factors and comorbidities. This study aimed to investigate the knowledge, attitude, and practice (KAP) of inpatients with cardiovascular disease towards OSA. This cross-sectional study was conducted between January, 2022 and January, 2023 at Zhongda Hospital Affiliated to Southeast University among inpatients with cardiovascular disease using a self-administered questionnaire. A self-designed questionnaire was used to assess KAP, and the STOP-Bang questionnaire was applied to evaluate participants’ OSA risk. Spearman correlation and path analyses were conducted to explore relationships among KAP scores and high OSA risk. Subgroup analyses were conducted within the high-risk population identified by the STOP-Bang questionnaire. In a study analyzing 591 questionnaires, 66.33% were males. Mean scores were 6.81 ± 4.903 for knowledge, 26.84 ± 4.273 for attitude, and 14.46 ± 2.445 for practice. Path analysis revealed high risk of OSA positively impacting knowledge (β = 2.351, P

Abstract In multi-criteria decision-making and model evaluation, determining the weight of criteria is crucial. With the rapid development of information technology and the advent of the big data era, the need for complex problem analysis and decision-making has intensified. Traditional CRiteria Importance Through Intercriteria Correlation (CRITIC) methods rely on Pearson correlation, which may not adequately address nonlinearity in some scenarios. This study aims to refine the CRITIC method to better accommodate nonlinear relationships and enhance its robustness. We have developed a novel method named CRiteria Importance Through Intercriteria Dependence (CRITID), which leverages cutting-edge independence testing methods such as distance correlation among others. This approach enhances the assessment of intercriteria relationships. Upon application across diverse data distributions, the CRITID method has demonstrated enhanced rationality and robustness relative to the traditional CRITIC method. These improvements significantly benefit multi-criteria decision-making and model evaluation, providing a more accurate and dependable framework for analyzing complex datasets.

Abstract Impact ionization effect has been demonstrated in transistors to enable sub-60 mV dec−1 subthreshold swing. However, traditionally, impact ionization in silicon devices requires a high operation voltage due to limited electrical field near the device drain, contradicting the low energy operation purpose. Here, we report a vertical subthreshold swing device composed of a graphene/silicon heterojunction drain and a silicon channel. This structure creates a low voltage avalanche impact ionization phenomenon and leads to steep switching of the silicon-based device. Experimental measurements reveal a small average subthreshold swing of 16 µV dec−1 over 6 decades of drain current and nearly hysteresis-free, and the operating voltage at which a vertical subthreshold swing occurs can be as low as 0.4 V at room temperature. Furthermore, a complementary silicon-based logic inverter is experimentally demonstrated to reach a voltage gain of 311 at a supply voltage of 2 V.

Abstract Aim To explore the topological organization alterations of functional connectomes in type 2 diabetes (T2DM) patients with and without mild cognitive impairment (MCI), and compare these with structural connectomes changes. Methods Twenty-six T2DM patients with MCI (DM-MCI), 26 without cognitive impairment (DM-NC), and 28 healthy controls were included. Diffusion tensor imaging (DTI) and resting-state functional MRI images were acquired. Networks were constructed and graph-theory based network measurements were calculated. The global network parameters and nodal efficiencies were compared across the three groups using one-way ANOVA and a false-discovery rate correction was applied for multiple comparisons. Partial correlation analyses were performed to investigate relationships between network parameters, cognitive performance and clinical variables. Results In the structural connectome, the DM-MCI group exhibited significantly decreased global efficiency (Eglob) and local efficiency (Eloc) compared to the DM-NC and control groups. In the functional connectome, the DM-MCI group exhibited increased Eloc and clustering coefficient (Cp) compared to the controls. No significant differences were found in Eglob, Eloc, or Cp between the DM-NC and the control group, both in structural and functional connectomes. Nodal efficiencies decreased in some brain regions of structural and functional networks in the DM-MCI and DM-NC groups, but increased in five regions in functional network, some of which were involved in the default-mode network. Conclusion Unlike the consistently decreased global properties and nodal efficiencies in the structural connectome of T2DM patients, increases in Eloc, Cp, and nodal efficiencies in the functional connectome may be viewed as a compensatory mechanism due to functional plasticity and reorganization. Altered nodal efficiency can hint at cognitive decrements at an early stage in T2DM patients.

Abstract PROteolysis TArgeting Chimeras (PROTACs) have been considered the next blockbuster therapies. However, due to their inherent limitations, the efficacy of PROTACs is frequently impaired by limited tissue penetration and particularly insufficient cellular internalization into their action sites. Herein, based on the ultra-pH-sensitive and enzyme-sensitive nanotechnology, a type of polymer PROTAC conjugated and pH/cathepsin B sequential responsive nanoparticles (PSRNs) are deliberately designed, following the construction of the PROTAC for Cyclin-dependent kinase 4 and 6 (CDK4/6). Colorectal cancer (CRC) which hardly responds to many treatments even immune checkpoint blockades was selected as the tumor model in this study. As a result, PSRNs were found to maintain nanostructure (40 nm) in circulation and efficiently accumulated in tumors via enhanced permeation and retention effect. Then, they were dissociated into unimers (

In articular cartilage, zone-specific cellular morphology is a typical characteristic of cartilage tissue, which is related with chondrocyte function, inflammation and osteoarthritis (OA). Chondrocyte hypertrophic phenotype is a criticle physiological process which indicates a hallmark of chondrocyte terminal differentiation and bone formation. Thus, developing a in vitro cell culture system for dynamic regulation of single chondrocyte volume at a three-dimensional (3D) level is particularly necessary for understanding how physical cues of matrix microenvironment regulate chondrocyte fate and the degeneration of articular cartilage. Here, based on the soft lithography techniques, we have constructed well-defined single-cell 3D dynamic volume control system to recapitulate the physiological matrix microenvironment of single chondrocyte niche. The results of finite element analysis indicated that the stress and strain distribution in the cell culture region is homogeneous during the stretching process. Additionally, 3D dynamic volume expansion and compression of single cells in physiological or hyperphysiological can be realized in this cell culture system. Our device for single-cell 3D dynamic culture provides a microphysiological culture system for chondrocytes to explore the mechanisms of cartilage hypertrophy, as well as develops a new paradigm for functional cartilage tissue engineering and regenerative medicine.

Abstract Background Innovative attempt to explore the feasibility and accuracy of using indocyanine green fluorescence (ICGF) to identify the intersegmental plane by the target segmental veins preferential ligation during thoracoscopic segmentectomy. Methods A retrospective analysis was conducted on clinical data of 32 consecutive patients who underwent thoracoscopic segmentectomy with intersegmental plane identification using both ICGF and inflation-deflation method after target segmental veins prioritized blocking at Nanjing Chest Hospital from December 2022 to June 2023. Preoperative three-dimensional reconstruction was used to identify the target segment and the anatomical structure of the arteries, veins, and bronchi. After ligating the target segmental veins during surgery, the first intersegmental plane was immediately identified and marked with an electrocoagulation device using an inflation-deflation method. Subsequently, the second intersegmental plane was determined using the ICGF method. Finally, the consistency of the two intersegmental planes was evaluated. Results All the 32 patients successfully completed thoracoscopic segmentectomy without ICG-related complications and perioperative death. The average operation time was (98.59 ± 20.72) min, the average intraoperative blood loss was (45.31 ± 35.65) ml, and the average postoperative chest tube removal time was (3.5 ± 1.16) days. The average postoperative hospital stay was (4.66 ± 1.29) days, and the average tumor margin width was (26.96 ± 5.86) mm. The intersegmental plane determined by ICGF method was basically consistent with inflation-deflation method in all patients. Conclusion The ICGF can safely and accurately identify the intersegmental plane by target segmental veins preferential ligation during thoracoscopic segmentectomy, which is a beneficial exploration and important supplement to the simplified thoracoscopic anatomical segmentectomy.

Abstract Neuroinflammation is an emerging clinical feature in spinal muscular atrophy (SMA). Characterizing neuroinflammatory cytokines in cerebrospinal fluid (CSF) in SMA and their response to nusinersen is important for identifying new biomarkers and understanding the pathophysiology of SMA. We measured twenty-seven neuroinflammatory markers in CSF from twenty SMA children at different time points, and correlated the findings with motor function improvement. At baseline, MCP-1, IL-7 and IL-8 were significantly increased in SMA1 patients compared to SMA2, and were significantly correlated with disease severity. After six months of nusinersen treatment, CSF levels of eotaxin and MIP-1β were markedly reduced, while IL-2, IL-4 and VEGF-A were increased. The decreases in eotaxin and MIP-1β were associated with changes in motor scores in SMA1. We also detected a transient increase in MCP-1, MDC, MIP-1α, IL-12/IL-23p40 and IL-8 after the first or second injection of nusinersen, followed by a steady return to baseline levels within six months. Our study provides a detailed profile of neuroinflammatory markers in SMA CSF. Our data confirms the potential of MCP-1, eotaxin and MIP-1β as new neuroinflammatory biomarkers in SMA1 and indicates the presence of a subtle inflammatory response to nusinersen during the early phase of treatment.

Abstract Promoters play a crucial role in regulating gene transcription. However, our understanding of how genetic variants influence alternative promoter selection is still incomplete. In this study, we implement a framework to identify genetic variants that affect the relative usage of alternative promoters, known as promoter usage quantitative trait loci (puQTLs). By constructing an atlas of human puQTLs across 49 different tissues from 838 individuals, we have identified approximately 76,856 independent loci associated with promoter usage, encompassing 602,009 genetic variants. Our study demonstrates that puQTLs represent a distinct type of molecular quantitative trait loci, effectively uncovering regulatory targets and patterns. Furthermore, puQTLs are regulating in a tissue-specific manner and are enriched with binding sites of epigenetic marks and transcription factors, especially those involved in chromatin architecture formation. Notably, we have also found that puQTLs colocalize with complex traits or diseases and contribute to their heritability. Collectively, our findings underscore the significant role of puQTLs in elucidating the molecular mechanisms underlying tissue development and complex diseases.

Abstract Objective With the progress of economic globalization and food diversification, foodborne parasitic diseases pose a significant public health challenge in China. This study aimed to explore the knowledge, attitudes, and practices regarding foodborne parasitic diseases among the Chinese population via WeChat, which is a promising tool for disease surveillance and health education. Methods Using a questionnaire, this cross-sectional study was conducted on September 25, 2023. Participants completed a structured questionnaire by scanning a QR code provided in a tweet from the WeChat official account of the Jiangsu Institute of Parasite Disease. Multivariable logistic regression analysis was employed to explore potential independent determinants of adequate knowledge of foodborne parasitic diseases, and the positive attitude and good practice rates of the participants were calculated. Results In total, 5,675 valid questionnaires were collected via the WeChat official account. Most participants (79.91%) fell within the age range of 20–40 years, with a higher representation of males (53.18%), and 89.80% were of Han Chinese ethnicity. It was found that 76.65% of the participants had adequate level of knowledge. Multivariable logistic regression analysis revealed that individuals of Hui nationality (OR = 0.57, 95% CI: 0.40–0.81, p = 0.002), clinicians (OR = 0.13, 95% CI: 0.09–0.19, p

Abstract Introduction HIV is widely prevalent in all regions of the world. The use of antiretroviral drugs has dramatically reduced the mortality rate of HIV-related diseases, but correspondingly increased the incidence of chronic complications in HIV-positive people. Related studies have found that the incidence of osteonecrosis of the femoral head is higher in HIV-positive people, but the co-occurrence of femoral head necrosis, acetabular necrosis and hip joint dislocation in HIV-positive patients is rare. Methods We report a 50-year-old man with a 15-month history of progressively worsening right hip pain with movement restriction. According to the CT findings of the other hospital, the patient was admitted to the hospital with femoral head necrosis. After the admission, the relevant X-ray, CT and MRI examinations showed that the right femoral head collapsed and deformed, with the surrounding bone sclerosis, bone fragments, loose body of the joint, right hip subluxation, acetabular marginal osteogeny, and local microcystic degeneration. The left femoral head was in good shape, and cystic degeneration can be seen under the articular surface. The patient was finally diagnosed with femoral head necrosis and acetabular necrosis combined with hip subluxation. Results The pain of the patient was significantly relieved after the operation, and the patient was discharged from the hospital one week after the start of treatment to continue rehabilitation training. During the follow-up one month after the operation, the self-reported pain disappeared completely, and the limitation of activity was significantly improved.

Achieving robust joint utilization of multidomain characteristics and deep-network features while maintaining a high jamming-recognition accuracy with limited samples is challenging. To address this issue, this paper proposes a multidomain characteristic-guided multimodal contrastive recognition method for active radar jamming. This method involves first thoroughly extracting the multidomain characteristics of active jamming and then designing an optimization unit to automatically select effective characteristics and generate a text modality imbued with implicit expert knowledge. The text modality and involved time-frequency transformation image are separately fed into text and image encoders to construct multimodal-feature pairs and map them to a high-dimensional space for modal alignment. The text features are used as anchors and a guide to time-frequency image features for aggregation around the anchors through contrastive learning, optimizing the image encoder’s representation capability, achieving tight intraclass and separated interclass distributions of active jamming. Experiments show that compared to existing methods, which involve directly combining multidomain characteristics and deep-network features, the proposed guided-joint method can achieve differential feature processing, thereby enhancing the discriminative and generalization capabilities of recognition features. Moreover, under extremely small-sample conditions (2～3 training samples for each type of jamming), the accuracy of our method is 9.84% higher than those of comparative methods, proving the effectiveness and robustness of the proposed method.

Abstract This study aims to objectively assess the effect of three surgical approaches for posterior uterine fibroid resection: transumbilical laparoendoscopic single-site surgery (LESS), vaginal natural orifice transluminal endoscopic surgery (vNOTES) in prone position (vNOTES-P), and vNOTES in the lithotomy position (vNOTES-L). A retrospective analysis was conducted on data pertaining to all patients who underwent vNOTES and LESS for single posterior fibroids at our institution from January 2023 to July 2023. Patients were categorized into three groups based on the surgical approach: vNOTES-P group (n = 30), vNOTES-L group (n = 17), and LESS group (n = 32). Comparative analysis was performed on the demographic characteristics and perioperative outcomes among the three groups of patients. All 79 patients underwent surgery without the need for conversion to laparotomy. There were no statistically significant differences among the LESS group, vNOTES-P group, and vNOTES-L group in terms of operative time, intraoperative blood loss, and perioperative complication rates. In the vNOTES-L group, two patients required conversion to LESS during surgery. Patients had faster return of bowel function (less time to flatus) in the vNOTES group compared to the LESS group (P

Abstract Background Low back pain has become a globally challenging health problem, and about 90% of cases are nonspecific. Due to the risks associated with opioid use and the limited effectiveness of drug treatment, acupuncture and other non-drug methods have become the first-line treatment for this disease. However, the best acupuncture method has not yet been determined. In this study, the effects of different acupuncture methods on chronic nonspecific low back pain (CNLBP) were compared by network meta-analysis, aiming at identifying the best option and providing a basis for precise treatment of CNLBP. Methods Clinical randomized controlled trials (RCTs) on acupuncture in the treatment of NSLBP were searched in eight databases including PubMed, Embase, Cochrane Library, Web of Science, Sinomed, CNKI, Wanfang Data and VIP from the inception of databases to January 21, 2024. The Cochrane risk-of-bias tool 2.0 (RoB 2.0) and Stata 15.0 (Stata Corp, College Station, Texas, USA) were used to evaluate the literature quality and meta-analysis, and the evidence quality was assessed based on GRADE guidelines. This systematic review was registered at the International Prospective Register of Systematic Reviews. Results A total of 27 articles were included, involving 2579 patients. The results of the network meta-analysis showed that the top three treatment schemes were warm needle acupuncture, intensive silver needle therapy and meridian-sinew theory-based treatment. In terms of relieving pain, the top three treatments were electrical warm needling, intensive silver needle therapy and warm needle acupuncture. In improving mobility, the top three were meridian-sinew theory-based treatment, routine acupuncture and electroacupuncture. Conclusion For CNLBP patients, warm needle acupuncture, electrical warm needling and meridian-sinew theory-based treatment are mainly recommended. If patients have significant pain, electroacupuncture is strongly suggested. On the contrary, for patients with decreased joint mobility, meridian-sinew theory-based treatment is advocated.

Abstract Background An adaptive design allows modifying the design based on accumulated data while maintaining trial validity and integrity. The final sample size may be unknown when designing an adaptive trial. It is therefore important to consider what sample size is used in the planning of the study and how that is communicated to add transparency to the understanding of the trial design and facilitate robust planning. In this paper, we reviewed trial protocols and grant applications on the sample size reporting for randomised adaptive trials. Method We searched protocols of randomised trials with comparative objectives on ClinicalTrials.gov (01/01/2010 to 31/12/2022). Contemporary eligible grant applications accessed from UK publicly funded researchers were also included. Suitable records of adaptive designs were reviewed, and key information was extracted and descriptively analysed. Results We identified 439 records, and 265 trials were eligible. Of these, 164 (61.9%) and 101 (38.1%) were sponsored by industry and public sectors, respectively, with 169 (63.8%) of all trials using a group sequential design although trial adaptations used were diverse. The maximum and minimum sample sizes were the most reported or directly inferred (n = 199, 75.1%). The sample size assuming no adaptation would be triggered was usually set as the estimated target sample size in the protocol. However, of the 152 completed trials, 15 (9.9%) and 33 (21.7%) had their sample size increased or reduced triggered by trial adaptations, respectively. The sample size calculation process was generally well reported in most cases (n = 216, 81.5%); however, the justification for the sample size calculation parameters was missing in 116 (43.8%) trials. Less than half gave sufficient information on the study design operating characteristics (n = 119, 44.9%). Conclusion Although the reporting of sample sizes varied, the maximum and minimum sample sizes were usually reported. Most of the trials were planned for estimated enrolment assuming no adaptation would be triggered. This is despite the fact a third of reported trials changed their sample size. The sample size calculation was generally well reported, but the justification of sample size calculation parameters and the reporting of the statistical behaviour of the adaptive design could still be improved.

Abstract Background Ovarian granulosa cells (GCs) play crucial roles in follicular growth and development. Their normal function is influenced by various factors, including oxidative stress, which is a significant factor. Afamin protein is a vitamin E-specific binding protein that acts as a vitamin E carrier in follicular fluid. Although the mechanism of the protective effect of afamin on human ovarian GCs is still unclear, there is evidence it has an antioxidant effect in neuronal cells. Methods In this study, we investigated the protective effects of afamin proteins on testosterone propionate (TP)-induced ovarian GCs using a human ovarian tumor granulosa cell line (KGN). Results The results showed that afamin reduced TP-induced oxidative stress in KGN cells by decreasing the levels of oxidative damage markers, enhancing the activity of antioxidant enzymes, and exerting a protective effect on GCs. Supplementation with afamin repaired mitochondrial dysfunction by improving mitochondrial membrane potential damage and ATP levels. It counteracted TP-induced apoptosis by decreasing the activity of Caspase-3 and upregulating the expression of the anti-apoptotic gene (BCL-2) while downregulating the expression of the pro-apoptotic gene BCL-2-associated X protein (BAX). In addition, afamin regulated the expression of genes related to ovarian steroid hormone synthesis, ameliorating the endocrine dysfunction observed in TP-induced KGN cells. Conclusion Therefore, Afamin proteins may serve as important complementary factors that protect GCs from other types of damage, such as oxidative stress, and may help improve ovarian follicle quality and female reproductive function.

Abstract Dental implant restoration shows an effective method for the rehabilitation of missing teeth. The failure rate of periodontal implants in patients with chronic periodontitis is associated with periodontal flora, inflammation, and long-term periodontal bone resorption caused by chronic periodontitis. However, the therapeutic effects of dental implant restoration on inflammation in patients with chronic periodontitis have not addressed. The purpose of this study is to evaluate the risk indicators for inflammation, bone loss and implant failure in patients with chronic periodontitis. A total of 284 patients with dental implant restoration were recruited and divided into periodontally healthy patients (n = 128) and chronic periodontitis patients (n = 156). Periodontal indices including probing depth (PD), sulcus bleeding index (SBI), plaque index (PLI), gingival bleeding (GIL) and bleeding on probing (BOP) were compared in two groups. Inflammatory cytokines including tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), interleukin-1 (IL-1), matrix metalloproteinase-2 (MMP-2) and matrix metalloproteinase-9 (MMP-9) levels at baseline, 6 and 12 months after surgery, and the implant survival rate at 12 months after surgery, as well as the risk factors associated with failure of dental implant were also assessed. Outcomes demonstrated that patients in the chronic periodontitis group had higher values of periodontal indices than those in the periodontally healthy group. All inflammatory parameters in the chronic periodontitis group were higher than those in the periodontally healthy group and negatively associated with the chronic periodontal index (CPI) in chronic periodontitis patients. Chronic periodontitis patients had higher the prevalence of mucositis and peri-implantitis than patients with healthy periodontium. Implant diameter, length and design was associated with the risk of implant failure for chronic periodontitis patients receiving dental implant. The cumulative implant failure rate and incidence of implant fractures for chronic periodontitis patients at 12 months after surgery were 12.10% and 7.23% (p

Abstract Objective This paper investigates the relationships between physical activity (PA), school bullying, emotion regulation self-efficacy (ERS), and interpersonal relationship distress (IRD) among junior high school students. It also examines the underlying mechanisms of school bullying to provide insights into reducing adolescent bullying and to lay the groundwork for preventing and controlling aggressive behaviors. Methods A survey was conducted on 484 students (240 males, 12.18 ± 0.8 years) from 4 secondary schools using the Physical Activity Rating Scale (PARS), Emotional Management Self-Efficacy Scale (EMSS), Interpersonal Relationship Distress Scale (IRDS), and Campus Bullying Scale (CBS) to examine the effects among the variables. A stratified random sampling method was used to select the sample, and data were collected with a structured questionnaire. The data were analyzed using SPSS 24.0 and AMOS 24.0 statistical software. The analysis included Pearson correlation analysis, structural equation modeling, and bias-corrected percentile Bootstrap methods. Results (1) PA negatively predicts IRD, which in turn has an indirect effect on bullying (PA → IRD → Bullying), ES = -0.063. Additionally, EM and IRD act as mediators between PA and school bullying (PA → EM → IRD → Bullying), ES = 0.025. (2) PA negatively predicts IRD, which has an indirect effect on being bullied (PA → IRD → Being bullied), ES = -0.044. EM and IRD serve as chain mediators between PA and being bullied (PA → EM → IRD → Being bullied), ES = -0.071. Conclusion PA can positively predict bullying, but it can be mitigated through EM to reduce IRD, thereby decreasing the occurrence of campus bullying and being bullied.

Abstract Dynamic tracking of spinal instrumentation could facilitate real-time evaluation of hardware integrity and in so doing alert patients/clinicians of potential failure(s). Critically, no method yet exists to continually monitor the integrity of spinal hardware and by proxy the process of spinal arthrodesis; as such hardware failures are often not appreciated until clinical symptoms manifest. Accordingly, herein, we report on the development and engineering of a bio-adhesive metal detector array (BioMDA), a potential wearable solution for real-time, non-invasive positional analyses of osseous implants within the spine. The electromagnetic coupling mechanism and intimate interfacial adhesion enable the precise sensing of the metallic implants position without the use of radiation. The customized decoupling models developed facilitate the precise determination of the horizontal and vertical positions of the implants with incredible levels of accuracy (e.g.,

Abstract China faces challenges in reaching its carbon neutrality goal by the year 2060 to meet the Paris Agreement and improving air quality simultaneously. Dramatic nitrogen emission reductions will be brought by this ambitious target, yet their impact on the natural ecosystem is not clear. Here, by combining two atmospheric chemistry models and two process-based terrestrial ecosystem models constrained using nationwide measurements, we show that atmospheric nitrogen deposition in China’s terrestrial land will decrease by 44–57% following two emission control scenarios including one aiming at carbon neutrality. They consequently result in a pronounced shrinkage in terrestrial net ecosystem production, by 11–20% depending on models and emission scenarios. Our results indicate that the nitrogen emission reductions accompanying decarbonization would undermine natural carbon sinks and in turn set back progress toward carbon neutrality. This unintended impact calls for great concern about the trade-offs between nitrogen management and carbon neutrality.

Abstract Tumour detection with high selectivity and sensitivity is crucial for delineating tumour margins and identifying metastatic foci during image-guided surgery. Optical nanoprobes with preferential tumour accumulation is often limited by inefficient amplification of biological signals. Here, we report the design of a library of hydrophobic core-tunable ultra-pH-sensitive nanoprobes (HUNPs) for orthogonally amplifying tumour microenvironmental signals on multiple tumour models. We find that tuning the hydrophobicity of nanoparticle core composition with non-ionizable monomers can enhance cellular association of HUNPs by more than ten-fold, resulting in a high cellular internalization efficiency of HUNPs with up to 50% in tumours. Combining high tumour accumulation and high cell internalization efficiency, HUNPs show orthogonally amplified fluorescence signals, permitting the precise locating and delineating margins between malignant lesions and normal tissues with high contrast-to-noise ratio and resolution. Our study provides key strategies to design nanomedicines with high intracellular bioavailability for cancer detection, drug/gene delivery, and therapy.

Rainfall is a common trigger for landslide reactivation, as it raises groundwater levels and reduces bedrock or soil shear resistance. This study focuses on the Kualiangzi landslide in the southern region of Sichuan Province, China. Real-time monitoring of groundwater levels and rainfall from July 2013 to September 2016 is analyzed. Groundwater table increments, considering groundwater drainage rate, were calculated using the water-table fluctuation and master recession curve method and the response time of the groundwater table to rainfall events was estimated using the cross-correlation function. Results reveal that groundwater level declines from tension troughs to landslide fronts in the rainy season, with a significant positive correlation between the groundwater level in the tension trough and landslide surface displacement. Evaluated spring elevations for groundwater discharge range from 410 m to 440 m, which is in agreement with the actual spring elevations (390–423 m). Lag times of groundwater response to rainfall decreases with cumulative rainfall of the rainy periods. In the middle part of the landslide, two responses between rainfall and groundwater levels indicate two water movement pathways: Vertical cracks or fractures resulting from the slow landslide movement, and matrix pore space in unconsolidated sediment. Variations in peak values of the cross-correlation function suggest early dominance of the uniform matrix flow and later dominance of preferential flow during the rainy period.

In order to improve the stability and stealth of vector propulsion motors in deep-sea exploration, a control method of deep-sea vector propulsion motors based on the position-sensorless and variable carrier frequency was derived from surface-mounted permanent magnet synchronous motors by using periodic spread spectrum modulation technology and position-sensorless control technology of improved sliding mode observer. Through simulations of motors’ variable carrier frequency, motor start-up speed variation, and sudden load change, the control effects of the proposed method were analyzed. The simulation results show that the rotation speed estimation of the studied control method is accurate, and the method has good dynamic tracking performance for rotation speed. The estimation error rate at the rated rotation speed is only 0.32%, and the estimation error rate at 0.5 times the rated rotation speed is only 0.09%. In addition, the proposed control method has an obvious high frequency harmonic spread spectrum suppression effect and good dynamic anti-interference performance. Combined with the simplification effect of reducing the motor structure brought by the position sensor, the control method proposed in this paper can effectively lower the failure rate of the deep-sea vector propulsion motor during operation, reduce the high-order fixed frequency harmonics that are easy to be detected, improve the reliability and stealth of the deep-sea vector propulsion motor, and provide efficient and reliable power guarantee for deep-sea unmanned undersea vehicles.

To address the challenges of fracture recognition in the CT scanning images of coal or rock, particularly the interference of gangue and the recognition of fractures at different scales, proposed and implemented a network model for coal-rock fracture extraction based on deep learning (MCSN). According to the U-Net architecture, the model utilized its encoder-decoder structure and skip connections to segment the fracture structure images from complex coal-rock body images. Firstly, the fracture structures in the CT scanning images were annotated manually using the internal scan images captured by a coal industrial CT scanning system. And the annotated original data was augmented to create a coal-rock CT fracture dataset. Subsequently, to make the extraction network of main features have a stronger extraction capability of fracture structure features, the weights of a pre-trained VGG16 model were transferred to the U-Net encoder through a transfer learning technique. Simultaneously, the decoder part of the U-Net model was improved using the deep separable dilated convolutional modules (DCAC) and residual modules to effectively boost the recognition capability of fracture structures in the CT images, demonstrating a superior segmentation accuracy and robustness. To validate the effectiveness of the coal-rock fracture extraction network model proposed, the results obtained by the MCSN were compared with those of classical convolutional neural networks and threshold segmentation methods. Experimental comparisons revealed a significant advantage of the model proposed in both qualitative and quantitative analyses. The proposed model, employing a multi-scale fusion strategy, demonstrated the capability to effectively extract fractures in complex coal-rock images, thereby enhancing the efficiency and accuracy of fracture identification. The model was applied to the identification of fractures in roadway surrounding rock based on borehole imaging. Fracture extraction was performed through the analysis of borehole videos and planar unfolded images collected by a borehole imaging instrument. The results from both sources were cross-validated to obtain an accurate distribution of fractures in roadway surrounding rock. Furthermore, the model provides guidelines for the injection and sealing of boreholes, increasing volume fraction of coal seam gas extraction.

Abstract Purpose Bone and joint tuberculosis (BJTB) is a distinct variant of tuberculosis in which clinical diagnosis often leads to relative misdiagnosis and missed diagnoses. This study aimed to evaluate the diagnostic accuracy of the targeted nanopore sequencing (TNPseq) assay for BJTB patients in China. Method The study enrolled a cohort of 163 patients with suspected BJTB. Diagnostic testing was performed using the TNPseq assay on samples including punctured tissue, pus, and blood. The diagnostic accuracy of the TNPseq assay was then compared with that of the T-SPOT and Xpert MTB/RIF assays. Result TNPseq exhibited superior performance in terms of accuracy, demonstrating a sensitivity of 76.3% (95% CI: 71.0-81.6%) and a specificity of 98.8% (95% CI: 93.5–100%) in clinical diagnosis. When evaluated against a composite reference standard, TNPseq demonstrated a sensitivity of 74.4% (95% CI: 69.3–79.5%) and a specificity of 98.8% (95% CI: 93.7–100%). These results exceed the performance of both the T-SPOT and Xpert MTB/RIF tests. Notably, TNPseq demonstrated high specificity and accuracy in puncture specimens, with a sensitivity of 75.0% (95% CI: 70.2–79.8%) and a specificity of 98.3% (95% CI: 92.7–100%), as well as in pus samples, with a sensitivity of 83.3% (95% CI: 78.6–88.1%) and a specificity of 100% (95% CI: 100–100%). Additionally, TNPseq facilitated the detection of mixed infection scenarios, identifying 20 cases of bacterial-fungal co-infection, 17 cases of bacterial-viral co-infection, and two cases of simultaneous bacterial-fungal-viral co-infection. Conclusion TNPseq demonstrated great potential in the diagnosis of BJTB due to its high sensitivity and specificity. The ability of TNPseq to diagnose pathogens and detect drug resistance genes can also guide subsequent treatment. Expanding the application scenarios and scope of TNPseq will enable it to benefit more clinical treatments.

Abstract The lockbolt structure is essential in railway wagons, and a scientific lockbolt layout can ensure uniform load distribution, thereby preventing failure. However, current engineering lacks layout optimization methods that address multidimensional failure modes. This paper presents a new lockbolt structure layout optimization method based on submodel, parametric models, and a multi-strategy integrated NSGA-III (MSNSGA-III), adhering to the DVS EFB 3435-2 standard. This method simultaneously optimizes the number and spacing of lockbolts to prevent tensile, bearing, shear, and other static failure modes under specified load conditions. The proposed method was applied during the design phase of a container flatcar. Optimization results indicate that, compared to NSGA-III, this method achieves the best IGD and HV values across multiple complex test functions, demonstrating superior performance in solving complex Pareto front optimization problems. Additionally, the optimized lockbolt structure's safety margins increased by a maximum of 59.81%, passing the full vehicle strength test and significantly enhancing resistance to multidimensional failure modes. These results highlight the method's significant practical application value in addressing the optimization of railway wagon lockbolt structures under complex multidimensional failure modes.

Abstract Background: The rise of network pharmacology has led to the widespread use of network-based computational methods in predicting drug target interaction (DTI). However, existing DTI prediction models typically rely on a limited amount of data to extract drug and target features, potentially affecting the comprehensiveness and robustness of features. In addition, although multiple networks are used for DTI prediction, the integration of heterogeneous information often involves simplistic aggregation and attention mechanisms, which may impose certain limitations. Results: MSH-DTI, a deep learning model for predicting drug-target interactions, is proposed in this paper. The model uses self-supervised learning methods to obtain drug and target structure features. A Heterogeneous Interaction-enhanced Feature Fusion Module is designed for multi-graph construction, and the graph convolutional networks are used to extract node features. With the help of an attention mechanism, the model focuses on the important parts of different features for prediction. Experimental results show that the AUROC and AUPR of MSH-DTI are 0.9620 and 0.9605 respectively, outperforming other models on the DTINet dataset. Conclusion: The proposed MSH-DTI is a helpful tool to discover drug-target interactions, which is also validated through case studies in predicting new DTIs.

Abstract Forest soils store substantial amounts of carbon in various soil organic matter (SOM) components due to high plant litter inputs and active microbial turnover. However, the variations in plant- and microbial-derived SOM components in surface and subsurface forest soils across a wide geographic scale remain poorly understood. This study investigated the SOM components from aboveground and belowground plant inputs and fungal and bacterial necromass in surface (soil0–5 cm) and subsurface (soil5–10 cm) soils across 32 forest sites in China and analyzed their relationships with climate and edaphic factors. Compared to soil0–5 cm, soil5–10 cm exhibited lower soil organic carbon content and cutin biomarker concentration but higher concentrations of fungal necromass carbon and lignin phenols. Higher mean annual precipitation led to higher concentrations of cutin and suberin biomarkers in soil0–5 cm and soil5–10 cm, respectively. Higher soil organic carbon content was associated with lower plant-derived lignin biomarkers, higher lignin oxidation degrees, and increased microbial necromass-derived amino sugars across sites, highlighting the pivotal role of microbial necromass in SOM stabilization. Additionally, both fungal and bacterial necromass decreased with increasing mineral weathering across sites. These insights improve the understanding of environmental drivers of source-specific carbon storage in forest soils. Graphical Abstract

Abstract Plastic pollution is an emerging environmental issue, with microplastics and nanoplastics raising health concerns due to bioaccumulation. This work explored the impact of polystyrene nanoparticle (PS-NPs) exposure during prepuberty on male reproductive function post maturation in rats. Rats were gavaged with PS-NPs (80 nm) at 0, 3, 6, 12 mg/kg/day from postnatal day 21 to 95. PS-NPs accumulated in the testes and reduced sperm quality, serum reproductive hormones, and testicular coefficients. HE staining showed impaired spermatogenesis. PS-NPs disrupted the blood-testis barrier (BTB) by decreasing junction proteins, inducing inflammation and apoptosis. Transcriptomics identified differentially expressed genes related to metabolism, lysosome, apoptosis, and TLR4 signaling. Molecular docking revealed Cordycepin could compete with polystyrene for binding to TLR4. Cordycepin alleviated oxidative stress and improved barrier function in PS-NPs treated Sertoli cells. In conclusion, prepubertal PS-NPs exposure induces long-term reproductive toxicity in male rats, likely by disrupting spermatogenesis through oxidative stress and BTB damage. Cordycepin could potentially antagonize this effect by targeting TLR4 and warrants further study as a protective agent. This study elucidates the mechanisms underlying reproductive toxicity of PS-NPs and explores therapeutic strategies.

In the title molecule, C11H11BrO3, the dihydroindene moiety is essentially planar but with a slight twist in the saturated portion of the five-membered ring. The methoxy groups lie close to the above plane. In the crystal, π-stacking interactions between six-membered rings form stacks of molecules extending along the a-axis direction, which are linked by weak C—H...O and C—H...Br hydrogen bonds. A Hirshfeld surface analysis was performed showing H...H, O...H/H...O and Br...H/H...Br contacts make the largest contributions to intermolecular interactions in the crystal.

In ship detection through remote sensing images, optical images often provide rich details and texture information; however, the quality of such optical images can be affected by cloud and fog interferences. In contrast, Synthetic Aperture Radar (SAR) provides all-weather and all-day imaging capabilities; however, SAR images are susceptible to interference from complex sea clutter. Cooperative ship detection combining the advantages of optical and SAR images can enhance the detection performance of ships. In this paper, by focusing on the slight shift of ships in a small neighborhood range in the prior and later temporal images, we propose a method for cooperative ship detection based on neighborhood saliency in multisource heterogeneous remote sensing images, including optical and SAR data. Initially, a sea-land segmentation algorithm of optical and SAR images is applied to reduce interference from land regions. Next, single-source ship detection from optical and SAR images is performed using the RetinaNet and YOLOv5s models, respectively. Then, we introduce a multisource cooperative ship target detection strategy based on the neighborhood window opening of single-source detection results in remote sensing images and secondary detection of neighborhood salient ships. This strategy further leverages the complementary advantages of both optical and SAR heterogeneous images, reducing the possibility of missing ship and false alarms to improve overall detection performance. The performance of the proposed method has been validated using optical and SAR remote sensing data measured from Yantai, China, in 2022. Compared with existing ship detection methods, our method improves detection accuracy AP50 by ≥1.9%, demonstrating its effectiveness and superiority.

Abstract Retrosynthesis is a crucial task in drug discovery and organic synthesis, where artificial intelligence (AI) is increasingly employed to expedite the process. However, existing approaches employ token-by-token decoding methods to translate target molecule strings into corresponding precursors, exhibiting unsatisfactory performance and limited diversity. As chemical reactions typically induce local molecular changes, reactants and products often overlap significantly. Inspired by this fact, we propose reframing single-step retrosynthesis prediction as a molecular string editing task, iteratively refining target molecule strings to generate precursor compounds. Our proposed approach involves a fragment-based generative editing model that uses explicit sequence editing operations. Additionally, we design an inference module with reposition sampling and sequence augmentation to enhance both prediction accuracy and diversity. Extensive experiments demonstrate that our model generates high-quality and diverse results, achieving superior performance with a promising top-1 accuracy of 60.8% on the standard benchmark dataset USPTO-50 K.

Abstract Multiferroic Ba2CuGe2O7 was anticipated as a potential member of the exciting group of materials hosting a skyrmion or vortex lattice because of its profound Dzyaloshinskii–Moriya interaction (DMI) and the absence of single ion anisotropy (SIA). This phase, however, could not be evidenced and instead, it exhibits a complex incommensurate antiferromagnetic (AFM) cycloidal structure. Its sister compound Ba2MnGe2O7, in contrast, is characterized by a relatively strong in-plane exchange interaction that competes with a non-vanishing SIA and the weak DMI, resulting in a quasi-two-dimensional commensurate AFM structure. Considering this versatility in the magnetic interactions, a mixed solid solution of Cu and Mn in Ba2Cu1−x Mn x Ge2O7 can hold an interesting playground for its interactive DMI and SIA depending on the mixed spin states of the transition metal ions towards the skyrmion physics. Here, we present a detailed study of the micro- and macroscopic spin structure of the Ba2Cu1 − x Mn x Ge2O7 solid solution series using high-resolution neutron powder diffraction techniques. We have developed a remarkably rich magnetic phase diagram as a function of the applied magnetic field and x, which consists of two end-line phases separated by a potentially quantum-critical phase at x = 0.57. An AFM conical structure at zero magnetic field is demonstrated to persist up to x = 0.50. Our results provide crucial information on the spin structure and magnetic properties, which are necessary for the general understanding and theoretical developments on multiferroicity in the frame of skyrmion type or frustrated AFM lattice where DMI and SIA play an important role.

Abstract In this study, we investigated the status and influencing factors of coronavirus disease 2019 (COVID-19) vaccination in patients with chronic obstructive pulmonary disease (COPD). A questionnaire on COVID-19 vaccination in patients with COPD was developed. The clinical characteristics, COVID-19 vaccination status, other relevant vaccinations, and vaccination status of the patients with COPD were collected anonymously. Logistic regression analysis was used to analyze the factors influencing COVID-19 vaccination in patients with COPD. There were 1898 returned questionnaires, of which 1874 were valid. The proportion of patients who completed the COVID-19 vaccination program was 78.60%. Factors influencing the COVID-19 vaccination rate were: the age of individuals who were 75–85 years old and > 85 years old, acute exacerbation 3–4 times in the previous year, comorbid cardiovascular and endocrine system diseases, failure to take regular medication for COPD, application of non-invasive ventilation machines, believing that their current health condition has deteriorated, believing that the current COVID-19 vaccine is not safe, medical staff not specifying whether they would recommend vaccination against COVID-19, medical staff not recommending the COVID-19 vaccine, and fear of adverse reactions and aggravation of COPD. Patients with COPD had a high COVID-19 vaccination rate in China, whereas patients with pneumonia, influenza, and herpes zoster had a low vaccination rate. Improving the patients’ understanding of the safety and effectiveness of the vaccine and promoting effective communication between medical staff and patients would help increase the vaccination rate of patients with COPD.

Abstract Accurate and reliable prediction of porosity forms the foundational basis for evaluating reservoir quality, which is essential for the systematic deployment of oil and gas exploration and development plans. When data quality of samples is low, and critical model parameters are typically determined through subjective experience, resulting in diminished accuracy and reliability of porosity prediction methods utilizing gated recurrent units (GRU), a committee-voting ensemble learning (EL) method, and an enhanced particle swarm optimization (PSO) algorithm are proposed to optimize the GRU-based porosity prediction model. Initially, outliers are eliminated through box plots and the min–max normalization is applied to enhance data quality. To address issues related to model accuracy and high training costs arising from dimensional complexity, substantial noise, and redundant information in logging data, a committee-voting EL strategy based on four feature selection algorithms is introduced. Following data preprocessing, this approach is employed to identify logging parameters highly correlated with porosity, thereby furnishing the most pertinent data samples for the GRU model, mitigating constraints imposed by single-feature selection methods. Second, an improved PSO algorithm is suggested to tackle challenges associated with low convergence accuracy stemming from random population initialization, alongside the absence of global optimal solutions due to overly rapid particle movement during iteration. This algorithm uses a good-point set for population initialization and incorporates a compression factor to devise an adaptive velocity updating strategy, thereby enhancing search efficacy. The enhanced PSO algorithm’s superiority is substantiated through comparison with four alternative swarm intelligent algorithms across 10 benchmark test functions. Ultimately, optimal hyper-parameters for the GRU model are determined using the improved PSO algorithm, thereby minimizing the influence of human factors. Experimental findings based on approximately 15,000 logging data points from well A01 in an operational field validate that, relative to three other deep learning methodologies, the proposed model proficiently extracts spatiotemporal features from logging data, yielding enhanced accuracy in porosity prediction. The mean squared error on the test set was 7.19 × 10–6, the mean absolute error stood at 0.0082, and coefficient of determination reached 0.99, offering novel insights for predicting reservoir porosity.

Abstract Objective it was to explore the influence of the postoperative pain management mode on the psychological state, quality of life (QOL), and nursing satisfaction of late patients in the intensive care unit (ICU) and improve the nursing effect of late patients in the ICU. Methods seventy patients who were admitted to the postoperative ICU for gastric cancer and received treatment in our hospital from March 2021 to May 2022 were selected. The patients were assigned into a research group and a control (Ctrl) group according to a random number table, with 70 cases in each group. The Ctrl group received routine nursing intervention, while research group received nursing intervention based on routine nursing intervention with postoperative pain management mode and received psychological care. Good communication was established with the patients, and the postoperative pain assessment was well conducted. The general information, state-trait anxiety (STAI) score, World Health Organization’s Quality of Life Instrument (WHO QOL-BREF) score, and care satisfaction were compared. Results the general information differed slightly, such as sex, age, and ward type, between groups, with comparability (P > 0.05). S-AI scores (13.15 ± 1.53 vs. 16.23 ± 1.24) and T-AI scores (14.73 ± 3.12 vs. 18.73 ± 3.16) in research group were inferior to those in Ctrl group (P

Abstract Background This study aims to analyze the pathogenic gene in a Chinese family with non-syndromic hearing loss and identify a novel mutation site in the TNC gene. Methods A five-generation Chinese family from Anhui Province, presenting with autosomal dominant non-syndromic hearing loss, was recruited for this study. By analyzing the family history, conducting clinical examinations, and performing genetic analysis, we have thoroughly investigated potential pathogenic factors in this family. The peripheral blood samples were obtained from 20 family members, and the pathogenic genes were identified through whole exome sequencing. Subsequently, the mutation of gene locus was confirmed using Sanger sequencing. The conservation of TNC mutation sites was assessed using Clustal Omega software. We utilized functional prediction software including dbscSNV_AdaBoost, dbscSNV_RandomForest, NNSplice, NetGene2, and Mutation Taster to accurately predict the pathogenicity of these mutations. Furthermore, exon deletions were validated through RT-PCR analysis. Results The family exhibited autosomal dominant, progressive, post-lingual, non-syndromic hearing loss. A novel synonymous variant (c.5247A > T, p.Gly1749Gly) in TNC was identified in affected members. This variant is situated at the exon–intron junction boundary towards the end of exon 18. Notably, glycine residue at position 1749 is highly conserved across various species. Bioinformatics analysis indicates that this synonymous mutation leads to the disruption of the 5' end donor splicing site in the 18th intron of the TNC gene. Meanwhile, verification experiments have demonstrated that this synonymous mutation disrupts the splicing process of exon 18, leading to complete exon 18 skipping and direct splicing between exons 17 and 19. Conclusion This novel splice-altering variant (c.5247A > T, p.Gly1749Gly) in exon 18 of the TNC gene disrupts normal gene splicing and causes hearing loss among HBD families.

Abstract Noise impairs the performance of inverse synthetic aperture radar (ISAR) motion compensation, which induces severe defocusing under low signal‐to‐noise ratio environments. To overcome this issue, a novel similarity‐oriented (SO) method with a two‐domain denoising strategy is proposed. A PIxEl similarity‐oriented (PIE‐SO) denoising method designed for range‐Doppler (RD) domain and a modified RAnge Profile Similarity‐Oriented (RAP‐SO) denoising method designed for high‐resolution range profile (HRRP) matrix are included in the presented framework. Firstly, the PIE‐SO method directly performs a two‐dimensional fast Fourier transform on dechirp processed echo data to form a coarsely focusing ISAR image in the RD domain. Then the focusing image is separated from the noise background by virtue of pixel similarity, after which the noise is preliminarily removed. Subsequently, the coarsely denoised image is transformed into the HRRP matrix. Considering the range profile similarity impaired by noise is restored by the PIE‐SO denoising, a Laplacian regularised‐weighted nuclear norm proximal (LR‐WNNP) operator is proposed. The proposed modified RAP‐SO method, that is, the LR‐WNNP operator, exploits the low‐rank property of the HRRP matrix and the local similarity of adjacent HRRPs to reduce the residual noise. As a result, ISAR imaging quality is significantly improved. Comprehensive experiments illustrate the effectiveness and superiority of the presented method.