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Abstract Advances in atomic physics have led to the possibility of a coherent transformation between ultracold atoms and molecules including between completely bosonic condensates. Such transformations are enabled by the magneto-association of atoms at a Feshbach resonance which results in a passage through a quantum critical point. In this study, we show that the presence of generic interaction between the constituent atoms and molecules can fundamentally alter the nature of the critical point, change the yield of the reaction and the order of the consequent phase transition. We find that the correlations introduced by this interaction induce nontrivial many-body physics such as coherent oscillations between atoms and molecules, and a selective formation of squeezed molecular quantum states and quantum cat states. We provide analytical and numerical descriptions of these effects, along with scaling laws for the reaction yield in non-adiabatic regimes.

Abstract Facial expression is among the most natural methods for human beings to convey their emotional information in daily life. Although the neural mechanisms of facial expression have been extensively studied employing lab-controlled images and a small number of lab-controlled video stimuli, how the human brain processes natural dynamic facial expression videos still needs to be investigated. To our knowledge, this type of data specifically on large-scale natural facial expression videos is currently missing. We describe here the natural Facial Expressions Dataset (NFED), an fMRI dataset including responses to 1,320 short (3-second) natural facial expression video clips. These video clips are annotated with three types of labels: emotion, gender, and ethnicity, along with accompanying metadata. We validate that the dataset has good quality within and across participants and, notably, can capture temporal and spatial stimuli features. NFED provides researchers with fMRI data for understanding of the visual processing of large number of natural facial expression videos.

Abstract Background The 24-hour movement guidelines (24-HMG) include screen time (ST), sleep duration, and physical activity. Previous studies have explored the associations of adherence to the 24-HMG with depression and anxiety symptoms among adolescents, ignoring changes in behaviors. This study aimed to examine whether changes in adherence to the 24-HMG were associated with depression and anxiety symptoms among adolescents. Methods We recruited adolescents from Shenzhen, China in 2021 and followed them up 1 year later. Changes in adherence to the individual 24-HMG were categorized into four groups: persistent non-adherence, adherence to non-adherence, non-adherence to adherence, and persistent adherence. Changes in the numbers of adherence to the overall 24-HMG were obtained by subtracting the number of guidelines adhered to in wave 2 from that in wave 1. Results We included 12,570 participants aged 9–18 years with 52.2% boys. Compared with persistent non-adherence for the ST/sleep duration guideline, non-adherence to adherence and persistent adherence were associated with lower depression and anxiety symptoms, but adherence to non-adherence was not. Changes in adherence to the physical activity guideline were not related to outcomes. The β coefficients (95% CIs) for each point increase in changes in the numbers of adherence to guidelines were − 0.58 (− 0.69, − 0.47) and − 0.43 (− 0.53, − 0.33) for depression and anxiety symptoms, respectively. The association of persistently adhering to sleep guideline with anxiety symptoms and the associations of changes in the numbers of adherence to the 24-HMG had sex differences. Conclusions Maintaining and strengthening healthy movement behaviors to meet more guidelines of the 24-HMG, especially sleep and ST, may be beneficial for preventing depression and anxiety symptoms in adolescents.

Polymer flooding is an effective method widely applied for enhancing oil recovery (EOR) by reducing the mobility ratio between the injected water and crude oil. However, traditional polymers encounter challenges in high salinity reservoirs due to their salt sensitivity. To overcome this challenge, we synthesized a zwitterion polymer (PAMNS) with salt-induced tackifying property through copolymerization of acrylamide and a zwitterion monomer, methylacrylamide propyl-N, N-dimethylbutylsulfonate (NS). NS monomer is obtained from the reaction between 1,4-butanesultone and dimethylamino propyl methylacrylamide. In this study, the rheological properties, salt responsiveness, and EOR efficiency of PAMNS were evaluated. Results demonstrate that PAMNS exhibits desirable salt-induced tackifying characteristics, with viscosity increasing up to 2.4 times as the NaCl concentration reaches a salinity of 30 × 104 mg L−1. Furthermore, high valence ions possess a much stronger effect on enhancing viscosity, manifested as Mg2+ > Ca2+ > Na+. Molecular dynamics simulations (MD) and fluid dynamics experiment results demonstrate that PAMNS molecules exhibit a more stretched state and enhanced intermolecular associations in high-salinity environments. It is because of the salt-induced tackifying, PAMNS demonstrates superior performance in polymer flooding experiments under salinity ranges from 5 × 104 mg L−1 to 20 × 104 mg L−1, leading to 10.38–19.83% higher EOR than traditional polymers.

Abstract Objectives Sleep characteristics such as duration, continuity, and irregularity are associated with the risk of hypertension. This study aimed to investigate the association between sleep timing (including bedtime, wake-up time, and sleep midpoint) and the prevalence of hypertension. Methods Participants were selected from the Sleep Heart Health Study (n = 5504). Bedtime and wake-up times were assessed using sleep habit questionnaires. The sleep midpoint was calculated as the halfway point between the bedtime and wake-up time. Restricted cubic splines and logistic regression analyses were performed to explore the association between sleep timing and hypertension. Results A significant nonlinear association was observed between bedtime (Poverall 12:00AM and 23:01PM to 12:00AM) and early (≤ 22:00PM) bedtimes were associated with an increased risk of hypertension compared to bedtimes between 22:01PM and 23:00PM. In addition, individuals with late (> 7:00AM) and early (≤ 5:00AM) wake-up times had a higher prevalence of hypertension than those with wake-up times ranging between 5:01AM and 6:00AM. Delaying the sleep midpoint (> 3:00AM) was also associated with an increased risk of hypertension. Furthermore, no significant interaction effect was found in the subgroup analyses stratified by age, sex, or apnea-hypopnea index. Conclusions Our findings identified a nonlinear association between sleep timing and hypertension. Individuals with both early and late sleep timing had a high prevalence of hypertension.

Abstract Indoor photovoltaics (IPVs) have attracted increasing attention for sustainably powering Internet of Things (IoT) electronics. Sb2S3 is a promising IPV candidate material with a bandgap of ~1.75 eV, which is near the optimal value for indoor energy harvesting. However, the performance of Sb2S3 solar cells is limited by nonradiative recombination, which is dependent on the quality of the absorber films. Additive engineering is an effective strategy to fine tune the properties of solution-processed films. This work shows that the addition of monoethanolamine (MEA) into the precursor solution allows the nucleation and growth of Sb2S3 films to be controlled, enabling the deposition of high-quality Sb2S3 absorbers with reduced grain boundary density, optimized band positions, and increased carrier concentration. Complemented with computations, it is revealed that the incorporation of MEA leads to a more efficient and energetically favorable deposition for enhanced heterogeneous nucleation on the substrate, which increases the grain size and accelerates the deposition rate of Sb2S3 films. Due to suppressed carrier recombination and improved charge-carrier transport in Sb2S3 absorber films, the MEA-modulated Sb2S3 solar cell yields a power conversion efficiency (PCE) of 7.22% under AM1.5 G illumination, and an IPV PCE of 17.55% under 1000 lux white light emitting diode (WLED) illumination, which is the highest yet reported for Sb2S3 IPVs. Furthermore, we construct high performance large-area Sb2S3 IPV minimodules to power IoT wireless sensors, and realize the long-term continuous recording of environmental parameters under WLED illumination in an office. This work highlights the great prospect of Sb2S3 photovoltaics for indoor energy harvesting.

Male infertility is a global issue caused by poor sperm quality, particularly motility. Enhancement of the sperm quality may improve the fertilization rate in assisted reproductive technology (ART) treatment. Scriptaid, with a novel human sperm motility-stimulating activity, has been investigated as a prospective agent for improving sperm quality and fertilization rate in ART. We evaluated the effects of Scriptaid on asthenozoospermic (AZS) semen, including its impact on motility stimulation and protective effects on cryopreservation and duration of motility, by computer-aided sperm analysis (CASA). Sperm quality improvement by Scriptaid was characterized by increased hyaluronan-binding activity, tyrosine phosphorylation, adenosine triphosphate (ATP) concentration, mitochondrial membrane potential, and an ameliorated AZS fertilization rate in clinical intracytoplasmic sperm injection (ICSI) experiments. Furthermore, our identification of active Scriptaid analogs and different metabolites induced by Scriptaid in spermatozoa lays a solid foundation for the future biomechanical exploration of sperm function. In summary, Scriptaid is a potential candidate for the treatment of male infertility in vitro as it improves sperm quality, prolongs sperm viability, and increases the fertilization rate.

Abstract Background Meeting the 24-hour movement behavior (24-HMB) guideline helps enhance quality of life (QOL) of adolescents. This study aimed to assess the associations between the 24-HMB (physical activity, screen time, sleep) and QOL among adolescents with idiopathic scoliosis. Methods A cross-sectional study was conducted between September 2021 and September 2023. 24-HMB, QOL and demographic variables were collected through a self-reported questionnaire. Linear regression models and stratified analyses were used to explore statistical associations between the 24-HMB and QOL. Results A total of 1073 participants aged 10–18 years with a spinal Cobb angle between 10° and 40° were included. Overall, 20 participants (1.9%) met all three behavioral guidelines, and 272 participants (25.3%) met none. Compared to those who did not meet any of the guidelines, adolescents meeting both screen time and sleep duration (β = 4.10, 95% CI: 2.02–6.18, P

Current analysis of fragile bronzes mainly relies on the research of two-dimensional aspects such as sample cross-sections and surfaces while typically utilizing optical and electronic microscopy, Raman spectroscopy, and X-ray fluorescence spectroscopy (XRF). As a fast and nondestructive testing method, computer tomography (CT) can be used to characterize and detect the internal structures, corrosion conditions, and corrosion distribution of bronzes. This study used the CT imaging results of fragile bronzes to analyze, locate, and measure corrosion in fragile bronzes quickly and accurately, thus providing strong support for corrosion evaluation and protection research of fragile bronzes. The results verified the value and application prospects of CT technology in the protection of cultural relics.

Abstract Background The incongruity between the regional supply and demand of healthcare services is a persistent challenge both globally and in China. Patient mobility plays a pivotal role in addressing this issue. This study aims to delineate the cross-provincial inpatient mobility network (CIMN) in China and identify the underlying factors influencing this CIMN. Methods We established China’s CIMN by applying a spatial transfer matrix, utilizing the flow information from 5,994,624 cross-provincial inpatients in 2019, and identified the primary demand and supply provinces for healthcare services. Subsequently, we employed GeoDetector to analyze the impact of 10 influencing factors—including medical resources, medical quality, and medical expenses—on the spatial patterns of CIMN. Findings Beijing, Shanghai, Zhejiang, and Jiangsu provinces are the preferred medical destinations for cross-provincial inpatients, while Anhui, Henan, Hebei, and Jiangsu provinces are the main sources for cross-provincial inpatients. Patient flow between provinces decreases with distance. The spatial distribution of medical resources, medical quality, and medical expenses account for 87%, 73%, and 56% of the formation of CIMN, respectively. Additionally, interactions between these factors enhance explanatory power, suggesting that considering their interactions can more effectively optimize medical resources and services. Conclusions The analysis of CIMN reveals the supply and demand patterns of healthcare services, providing insights into the inequality characteristics of healthcare access. Furthermore, understanding the driving factors and their interactions offers essential evidence for optimizing healthcare services.

Abstract Background COVID-19 can cause cardiac complications and the latter are associated with poor prognosis and increased mortality. SARS-CoV-2 variants differ in their infectivity and pathogenicity, but how they affect cardiomyocytes (CMs) is unclear. Methods The effects of SARS-CoV-2 variants were investigated using human induced pluripotent stem cell-derived (hiPSC-) CMs in vitro and Golden Syrian hamsters in vivo. Results Different variants exhibited distinct tropism, mechanism of viral entry and pathology in the heart. Omicron BA.2 most efficiently infected and injured CMs in vitro and in vivo, and induced expression changes consistent with increased cardiac dysfunction, compared to other variants tested. Bioinformatics and upstream regulator analyses identified transcription factors and network predicted to control the unique transcriptome of Omicron BA.2 infected CMs. Increased infectivity of Omicron BA.2 is attributed to its ability to infect via endocytosis, independently of TMPRSS2, which is absent in CMs. Conclusions In this study, we reveal previously unknown differences in how different SARS-CoV-2 variants affect CMs. Omicron BA.2, which is generally thought to cause mild disease, can damage CMs in vitro and in vivo. Our study highlights the need for further investigations to define the pathogenesis of cardiac complications arising from different SARS-CoV-2 variants.

Abstract Aphidoletes aphidimyza is widely recognized as an effective predator of aphids in agricultural systems. However, there is limited understanding of its predation mechanisms. In this study, we generated a high-quality chromosome level of the A. aphidimyza genome by combining PacBio, Illumina, and Hi-C data. The genome has a size of 192.08 Mb, with a scaffold N50 size of 46.85 Mb, and 99.08% (190.35 Mb) of the assembly is located on four chromosomes. The BUSCO analysis of our assembly indicates a completeness of 97.8% (n = 1,367), including 1,307 (95.6%) single-copy BUSCOs and 30 (2.2%) duplicated BUSCOs. Additionally, we annotated a total of 13,073 protein-coding genes, 18.43% (35.40 Mb) repetitive elements, and 376 non-coding RNAs. Our study is the first time to report the chromosome-scale genome for the species of A. aphidimyza. It provides a valuable genomic resource for the molecular study of A. aphidimyza.

Abstract Single image super‐resolution (SISR) is a promising research direction in computer vision and image processing for improving the visual perception of low‐quality images. In recent years, deep learning algorithms have driven tremendous development in SR, and SR methods based on various network architectures have significantly improved the quality of reconstructed images. Although there has been a large amount of reviews focusing on SISR, few studies have focused specifically on network architectures for SISR. This paper aims to provide a systematic overview of the design ideas of SISR using multiple architectures, including Convolutional Neural Networks (CNN), Generative Adversarial Networks (GAN), Transformer, and Diffusion model. In addition, an experimental analysis and comparison of state‐of‐the‐art SR algorithms have been performed on publicly available quantitative and qualitative datasets. Finally, some future directions are discussed that may help other community researchers.

Targeting the issues of seed leakage and cutting segment adhesion due to poor seed feeding and cutting in real-time seed-cutting cassava planters, this study developed a seeding quality monitoring system. Based on the structure and working principle of the seed cutting and discharging device, the installation methods of the matrix fiber optic sensor and rotary encoder were determined. By combining the operational characteristics of the planter’s ground wheel drive with seed cutting and seed dropping, a monitoring model correlating the sowing parameters with seed dropping time was established; a monitoring window was created by extracting and processing the rotary encoder pulse signal, and the number of seeds sown after each opposing cutter’s operation was calculated based on the pulse width information within the monitoring window. The monitoring system’s statistics were compared and analyzed with the manual statistics, and the bench test showed that the monitoring system designed in this study offers high accuracy. When the simulated rotational speed of the opposing cutter ranges from 10 to 30 rpm, the average monitoring error between the monitored and actual seeding quantities for the left and right rows is less than 1.4%. The monitoring system can promptly and accurately activate sound and light alarms for faults, achieving a 100% success rate in alarms and an average fault response time of less than 0.4 seconds. Field tests demonstrate that the average error in seeding volume is 0.91%, and the monitoring system can timely alert to faults occurring in the planter. The system fulfills the requirements for real-time monitoring of cassava seeding volume at various operating speeds in field conditions, and can serve as a reference for monitoring operational parameters in subsequent cassava combine harvesters.

To tackle the challenge of a one-size-fits-all and inconsistent approach to evaluating school development across districts, we have zeroed in on five key urban districts in Changsha City. Fourteen secondary indicators, spanning four critical categories — campus environment, teaching facilities, financial investment, and teacher resources — were selected to comprehensively assess the development of elementary schools in 2021. This assessment was conducted using the Advanced Interpretive Structural Model (AISM). Drawing on the principles of partial order set theory, AISM delves into the partial relationships among these indicators, considering the raw data matrix, optimistic positive and negative distances, and program fit degree. Subsequently, Haas map technology is employed to graphically represent the partial order relationship of elementary school development in each region, providing a clear picture of the hierarchical structure and merit ranking of the evaluation objects. The evaluation results reveal stark differences in the development of elementary schools in Changsha's districts, primary schools in Furong and Kaifu districts stand out for their superior development quality, while Yuhua and Yuelu districts lag behind in terms of elementary school development. Based on these findings, we propose policy recommendations aimed at achieving balanced primary education across districts and ensuring the adequacy of teacher resources.

Abstract Background A higher Life's Essential 8 (LE8)-based cardiovascular health (CVH) has been reported to be associated with a lower risk of both all-cause mortality and cardio-cerebrovascular diseases (CCVDs) related mortality in adults in the United States. At the same time, multiple studies have shown a significant negative association of CVH with the risk of stroke and CCVDs. Since no research has investigated the applicability of the LE8 in stroke patients, this study aimed to explore the association of LE8 with all-cause mortality and cardio-cerebrovascular mortality in stroke patients. Methods Data of patients were extracted from the National Health and Nutrition Examination Surveys (NHANES) database in 2007–2018 in this retrospective cohort study. Weighted univariate and multivariate COX regression analyses were utilized to investigate the associations of LE8 with all-cause mortality and cardio-cerebrovascular mortality. We further explored these relationships in subgroups of age, gender, body mass index (BMI), cancer, congestive heart failure (CHF), and coronary heart disease (CHD). The evaluation indexes were hazard ratios (HRs) and 95% confidence intervals (CIs). Results Among the eligible patients, 278 died from all-cause and 89 (8.38%) of them died due to CCVDs. After adjusting for covariates, patients with LE8 score ≥ 58.75 seemed to have both lower risk of all-cause mortality (HR = 0.46, 95%CI: 0.31–0.69) and cardio-cerebrovascular mortality (HR = 0.51, 95%CI: 0.26–0.98), comparing to those with LE8 score

Abstract Background Patients with cleft lip and palate (CLP) have an oronasal communication differed from the closed state in healthy individuals, leading to a unique oral microbiome. This study aimed to determine if variances in the oral microbiota persist among CLP patients who have received treatments for the closure of these fistulas compared to the microbiota of healthy individuals. Methods Saliva samples were collected from a cohort comprising 28 CLP patients (CLP group) and 30 healthy controls (HC group). Utilizing 16S rRNA sequencing on the Illumina NovaSeq platform, we conducted a comprehensive analysis of the diversity and composition of the oral microbiota. Results The analysis of the microbiota in the saliva samples revealed a total of 23 microbial phyla, 38 classes, 111 orders, 184 families, 327 genera and 612 species. The alpha diversity with microbial abundance and evenness indicated the significant difference between the CLP and HC groups. Principal coordinate analysis (PCoA) and the ADONIS test further supported the presence of distinct microorganisms between the two groups. The CLP group displayed elevated abundances of Neisseria, Haemophilus, Porphyromonas, and Granulicatella, as indicated by LefSe analysis. Conversely, Rothia, Veillonella, and Pauljensenia exhibited significant reductions in abundance in the CLP group. The results of the PICRUSt analysis indicated significant differences in the relative abundance of 25 KEGG pathways within the CLP group. Through Spearman correlation analysis, strong associations between Rothia, Veillonella, and Pauljensenia and 25 functional pathways linked to CLP were identified. Conclusion Findings of this study offer a thorough comprehension of the microbiome profiles of CLP patients after the restoration of oronasal structure and are anticipated to present innovative concepts for the treatment of CLP.

Abstract Background Despite advancements in school scoliosis screening (SSS), there are still no effective indicators to estimate the severity of spinal curvature. We aim to investigate the association between incorrect postures and curve magnitude of adolescent idiopathic scoliosis (AIS) among Chinese adolescents. Methods In this SSS program, we examined the incorrect posture, Adam’s forward bending test (FBT) results, and angle of trunk rotation (ATR) in adolescents. Those with suspected scoliosis were referred for a standing anteroposterior whole-spine radiography as outpatients. The radiographic data of 426 students with lateral Cobb angles were collected from 2016 to 2022 and the associations were studied using logistic regression (LR) models and receiver operating characteristic (ROC) curves. Results Univariate LR revealed that female gender [odds ratio (OR) = 2.92, 95% confidence interval (CI) 1.67–5.09, P

Abstract Ensemble learning has the potential to enhance the efficacy of feeble classifiers significantly and is increasingly being utilized in Twitter bot detection. Previous methods have utilized stacking techniques to train the primary classifiers, implementing cross-validation to mitigate overfitting and enhance predictive accuracy. However, cross-validation substantially amplifies the computation time associated with stacking. To overcome this challenge, this paper presents a novel approach, the Simplified Stacking Graph Neural Network (SStackGNN), specifically designed for the detection of social bots. Our methodology leverages the power of Graph Neural Networks (GNNs) as base classifiers, enabling effective capturing of inter-account interactions. In addition, a Multilayer Perceptron (MLP) serves as a secondary classifier, amalgamating the outcomes of the foundational classifiers to generate final predictions, thereby enhancing the predictive performance of the GNNs. Instead of relying on cross-validation and distinct base classifier structures, we employ node-level, edge-level, and feature-level graph data augmentation techniques to acquire diverse foundational classifiers. This approach significantly alleviates the computational complexity while achieving superior performance. Experimental results demonstrate that our proposed SStackGNN outperforms other approaches.

Abstract Background Diabetic macular edema (DME) is a leading cause of vision loss in patients with diabetes. This study aimed to develop and evaluate an OCT-omics prediction model for assessing anti-vascular endothelial growth factor (VEGF) treatment response in patients with DME. Methods A retrospective analysis of 113 eyes from 82 patients with DME was conducted. Comprehensive feature engineering was applied to clinical and optical coherence tomography (OCT) data. Logistic regression, support vector machine (SVM), and backpropagation neural network (BPNN) classifiers were trained using a training set of 79 eyes, and evaluated on a test set of 34 eyes. Clinical implications of the OCT-omics prediction model were assessed by decision curve analysis. Performance metrics (sensitivity, specificity, F1 score, and AUC) were calculated. Results The logistic, SVM, and BPNN classifiers demonstrated robust discriminative abilities in both the training and test sets. In the training set, the logistic classifier achieved a sensitivity of 0.904, specificity of 0.741, F1 score of 0.887, and AUC of 0.910. The SVM classifier showed a sensitivity of 0.923, specificity of 0.667, F1 score of 0.881, and AUC of 0.897. The BPNN classifier exhibited a sensitivity of 0.962, specificity of 0.926, F1 score of 0.962, and AUC of 0.982. Similar discriminative capabilities were maintained in the test set. The OCT-omics scores were significantly higher in the non-persistent DME group than in the persistent DME group (p

ObjectiveThis study analyzed the prevalence, epidemiological characteristics and risk factors of birth defects among livebirths in central China, aiming to provide evidences for the prevention of birth defects and government Decision-makings.MethodsBirth data from China’s Hubei Province between 2015 and 2022 were collected, including basic information of the livebirths, the mothers and the fathers, as well as information about delivery and each prenatal examination. The livebirths prevalence of birth defects was calculated and the trends were mapped. The basic characteristics of birth defects were evaluated by the difference analysis between case and health groups. Univariate and multivariate Poisson regression was performed to examine the independent risk factors for birth defects.ResultsAmong 43,568 livebirths, 166 livebirths were born with birth defects, resulted in a total prevalence rate of 3.81 per 1,000 livebirths, showing a remarkable uptrend from 0.41per 1,000 livebirths in 2015 to 9.23 per 1,000 livebirths in 2022. The peak of the prevalence was in January and February. Congenital malformation of the musculoskeletal system was the main type of birth defect in central China livebirths, followed by cleft lip and cleft palate. Overall, newborns with birth defect had significantly earlier delivery gestational age, poorer health and higher proportion of infants with low birth weight than healthy births. The gender of livebirths, excess weight at delivery (≥80 kg) of mothers, more than 2 times of gravidity or parity of mothers, and advanced paternal age (≥40 years) were independent risk factors for birth defects (or specific birth defects).ConclusionThe livebirths prevalence of birth defects shows increasing trend in central China, which deserves the attention of the government and would-be parents. Elevated paternal age, excess maternal weight, gravidity and parity should be considered when planning their families.

IntroductionWhile lymph node metastasis (LNM) plays a critical role in determining treatment options for endometrial cancer (EC) patients, the existing preoperative methods for evaluating the lymph node state are not always satisfactory. This study aimed to develop and validate a nomogram based on intra- and peritumoral radiomics features and multiparameter magnetic resonance imaging (MRI) features to preoperatively predict LNM in EC patients.MethodsThree hundred and seventy-four women with histologically confirmed EC were divided into training (n = 220), test (n = 94), and independent validation (n = 60) cohorts. Radiomic features were extracted from intra- and peritumoral regions via axial T2-weighted imaging (T2WI) and apparent diffusion coefficient (ADC) mapping. A radiomics model (annotated as the Radscore) was established using the selected features from different regions. The clinical parameters were statistically analyzed. A nomogram was developed by combining the Radscore and the most predictive clinical parameters. Decision curve analysis (DCA) and the net reclassification index (NRI) were used to assess the clinical benefit of using the nomogram.ResultsNine radiomics features were ultimately selected from the intra- and peritumoral regions via ADC mapping and T2WI. The nomogram combining the Radscore, serum CA125 level, and tumor area ratio achieved the highest AUCs in the training, test and independent validation sets (nomogram vs. Radscore vs. clinical model: 0.878 vs. 0.850 vs. 0.674 (training), 0.877 vs. 0.838 vs. 0.668 (test), and 0.864 vs. 0.836 vs. 0.618 (independent validation)). The DCA and NRI results revealed the nomogram had greater diagnostic performance and net clinical benefits than the Radscore alone.ConclusionThe combined intra- and peritumoral region multiparameter MRI radiomics nomogram showed good diagnostic performance and could be used to preoperatively predict LNM in patients with EC.

IntroductionPhosphorus nutrition and hormone concentration both affect crop yield formation. Ascertaining the interaction of phosphorus and GA3 has a synergistic effect on the grain yield and phosphorus utilization efficiency of oilseed flax in dryland. It is extremely important for improving grain yield and phosphorus utilization efficiency.MethodsA field experiment was conducted in 2019 and 2020 at the Dingxi Oil Crops Test Station to investigated the effects of phosphorus, gibberellin (GA3), and their interaction on the grain yield and phosphorus-utilization efficiency of oilseed flax plants. Phosphorus fertilizer was applied at three levels (0, 67.5, 135 kg P2O5·ha-1) and GA3 was also sprayed at three concentrations (0, 15, and 30 mg·L-1).ResultsThe results showed that application of 67.5 kg P2O5·ha-1 reduced leaves acid phosphatase (ACPase) activity, but increased phosphorus accumulation throughout the growth period, the 1000-kernel weight (TKW), and the number of grains per capsule. Spraying GA3 significantly increased the leaves ACPase activity, phosphorus accumulation after anthesis and its contribution to grain, phosphorus-utilization efficiency, the number of capsules per plant, and TKW. The phosphorus accumulation at the anthesis, kernel, and maturity stages under the treatment of fertilizing 67.5 kg P2O5·ha-1 and spraying 30 mg·L-1 GA3 were increased by 56.06%, 73.51%, and 62.17%, respectively, compared with the control (no phosphorus, no GA3). And the phosphorus accumulation after anthesis and its contribution to grain also increased. 67.5 kg P2O5·ha-1 combined with 30 mg·L-1 GA3 and 135 kg P2O5·ha-1 combined with 15 mg·L-1 GA3 both significantly increased grain yield of oilseed flax, reaching 1696 kg·ha-1 and 1716 kg·ha-1 across two years, respectively. And there was no significant difference between them. However, the former treatment significant increased the apparent utilization rate, agronomic utilization rate, and partial productivity of phosphorus. The interaction between phosphorus and GA3 was significant for grain yield.ConclusionTherefore, the application of 67.5 kg P2O5·ha-1 in combination with 30 mg·L-1 GA3 is an effective fertilization approach for enhancing oilseed flax growth and grain yield in the experiment region and other similar areas.

Designing photocatalysts with p-n heterojunction structures is an effective way to boost the separation of photogenerated carriers and stimulate the photocatalytic degradation activity. Herein, an efficient visible-light responsive AgI/BiSI p-n heterojunction photocatalyst was successfully constructed. X-ray photoelectron spectroscopy (XPS), photoluminescence (PL) spectroscopy, and electrochemical measurements confirmed that the AgI/BiSI p-n heterojunction structure was beneficial to the separation and transfer of photogenerated carriers, promoting the generation of main active species (•O2− and h+). Furthermore, the photocatalytic degradation rate constants of Acid Red 1 (0.4699 min−1) and metronidazole (0.0730 min−1) over the optimal AgI/BiSI were about 8.4 and 3.0 times higher than those over pure AgI, respectively. This work provides a heterojunction engineering strategy to design high-efficient photocatalysts for the degradation of refractory organic pollutants.

Three new species of the leafhopper genus Arboridia Zachvatkin 1946, Arboridia (Arboridia) furcata Han, sp. nov., Arboridia (Arboridia) rubrovittata Han, sp. nov., and Arboridia (Arboridia) robustipenis Han, sp. nov., are described and illustrated from fruit trees in Southwest China. A key and checklist to known species from China are provided.

Abstract In recent years, the rapid advancement of digital technology has supported the growth of the digital economy. The transformation towards digitization in the public health sector serves as a key indicator of this economic shift. Understanding how the digital economy continuously improves the efficiency of public health services and its various pathways of influence has become increasingly important. It is essential to clarify the impact mechanism of the digital economy on public health services to optimize health expenditures and advance digital economic construction. This study investigates the impact of digital economic development on the efficiency of public health services from a novel perspective, considering social media usage and urban–rural healthcare disparities while constructing a comprehensive index of digital economic development. The findings indicate that the digital economy reduces the efficiency of public health services primarily through two transmission mechanisms: the promotion of social media usage and the widening urban–rural healthcare gap. Moreover, these impacts and transmission pathways exhibit spatial heterogeneity. This study unveils the intrinsic connection and mechanisms of interaction between digital economic development and the efficiency of public health services, providing a theoretical basis and reference for government policy formulation. However, it also prompts further considerations on achieving synergy and interaction between the digital economy and public health services.

Abstract We propose to utilize angularity distributions in Higgs boson decay to probe light quark Yukawa couplings at e + e − colliders. Angularities τ a are a class of 2-jet event shapes with variable and tunable sensitivity to the distribution of radiation in hadronic jets in the final state. Using soft-collinear effective theory (SCET), we present a prediction of angularity distributions from Higgs decaying to quark and gluon states at e + e − colliders to NNLL + 𝒪(α s ) accuracy. Due to the different color structures in quark and gluon jets, the angularity distributions from H → $$q\overline{q }$$ and H → gg show different behaviors and can be used to constrain the light quark Yukawa couplings. We show that the upper limit of light quark Yukawa couplings could be probed to the level of ~ 15% of the bottom quark Yukawa coupling in the Standard Model in a conservative analysis window far away from nonperturbative effects and other uncertainties; the limit can be pushed to ≲ 7 – 9% with better control of the nonperturbative effects especially on gluon angularity distributions and/or with multiple angularities.

Abstract Background Adolescent idiopathic scoliosis (AIS), three-dimensional spine deformation, affects body motion. Previous research had indicated pathological gait patterns of AIS. However, the impact of the curve number on the walking mechanism has not been established. Therefore, this study aimed to compare the gait symmetry and kinematics in AIS patients with different curve numbers to healthy control. Results In the spinal region, double curves AIS patients demonstrated a smaller sagittal symmetry angle (SA) and larger sagittal convex ROM of the trunk and lower spine than the control group. In the lower extremities, the single curve patients showed a significantly reduced SA of the knee joint in the frontal plane, while the double curves patients showed a significantly reduced SA of the hip in the transverse plane. Conclusion The curve number indeed affects gait symmetry and kinematics in AIS patients. The double curves patients seemed to adopt a more "careful walking" strategy to compensate for the effect of spinal deformation on sensory integration deficits. This compensation mainly occurred in the sagittal plane. Compared to double curves patients, single curve patients unitized a similar walking strategy with healthy subjects.

The dikraneurine leafhopper genus Anaka is reviewed based on a comparative morphological study. Five new species, Anaka auricula sp. nov., Anaka cruciata sp. nov., Anaka curvata sp. nov., Anaka rosacea sp. nov., and Anaka spiralis sp. nov. from China are described and illustrated in detail. Additionally, a key to known Anaka species is provided along with a checklist of all species and their distributions.

Shield tunnel backfill grouting is vital to stabilize tunnel settlement at a later stage; however, most shield tunnel backfill grouting designs lack a complete theoretical reference, and numerical simulations of the grouting process are rarely conducted. This study presents the fundamental theories of grout diffusion and pressure variation for backfill grouting during shield construction. Moreover, the numerical simulation methods coupled with discrete element methods (DEM) and finite difference methods (FDM) are achieved to simulate the process of grout injection from the grouting hole into the shield tail gap and generate grout pressure on the surrounding rock. The diffusion state of the grout in the shield tail gap and the squeezing effect on the surrounding rock under two shield tail disengagement modes are analyzed, as well as the impact of various grouting pressure on the surface settlement. The results indicated that the grout diffusion in the shield tail gap can be divided into three stages: the stage of diffusion with each grouting hole as the starting point, the stage of interconnection and contact of the grout injected in each grouting hole, and the final gap filling stage. Each of the three stages can be described using the proposed equation. During the grouting process, the grout is injected into the shield tail gap at a certain pressure, but the grout diffuses slowly to both sides and upwards, which causes a rapid rise of the principal stresses in the soil around the tunnel. After grouting is complete, the grout pressure gradually dissipates and stabilizes, and the principal stress decreases. In addition, backfill grouting can reduce surface settlement, but it does not affect its distribution width.

Spectral computed tomography (spectral CT) is a promising medical imaging technology because of its ability to provide information on material characterization and quantification. However, the difficulty of decomposition increases due to the nonlinearity of the measurements and the text ill-condition of the problem, especially in the case of geometric inconsistency, which typically leads to low image qualities. Therefore, it is a crucial issue for inconsistent spectral CT imaging to improve the accuracy of material decomposition while suppressing noise. This paper proposes one-step multi-material algorithms based on a statistical reconstruction model with different priors. In these approaches, the gradient sparsity based and convolutional neural network based methods are designed for the case of the consistent numbers of material and energies. Furthermore, volume conservation constraint is developed while the two numbers are not equal. An efficient Newton descent method is adopted based on a simple surrogate function. For simulation experiments with different noise levels, the largest peak signal-to-noise ratio (PSNR) obtained by the proposed method approximately increases by 20.924 dB and 18.283 dB compared with those of other algorithms. Magnified areas of real data also demonstrated that the proposed methods have a better ability to suppress noise. Numerical experiments verify that the proposed methods efficiently reconstruct the material maps and reduced noise compared with the state-of-the-art methods.

Spectral computed tomography (CT) has a wide range of applications in material discrimination, clinical diagnosis and tissue representation. However, the photon counting detector measurements are subject to serious quantum noise caused by photon starvation, photon accumulation, charge sharing, and other factors, which will lead to a decrease in the quality of the reconstructed image and make clinical diagnosis more difficult. To tackle with this problem, this paper proposes a spectral CT reconstruction technique that exploits the spatial sparsity of inter-channel images and the high correlation of images between different energy channels. Specifically, similar patches from spatial and spectral domains are extracted to form the low-rank tensors. Then the tensor-train rank, which is derived from a well-balanced matricization technique, is adopted to depict the high correlation among different energy channels. To capture the self-similarity of the low-rank tensors, the L0-norm of the image gradient is employed for image smoothing. An efficient algorithm is devised to solve the reconstruction model utilizing the Alternating Direction Method of Multipliers. For the sake of testing and verifying the effectiveness of the proposed algorithm, numerical simulations and real data experiments are conducted. Qualitatively, the designed method demonstrates a clear advantage in image quality over the existing state-of-the-art algorithms. For instance, when taking the full energy bin image as an example, the proposed method reduces the Root Mean Square Error (RMSE) by 52.07%, 38.69%, 35.13%, 12.67%, respectively, compared to the competing methods. Quantitative and qualitative assessment indices have revealed that the suggested method has excellent noise suppression, artifact elimination, and image detail preservation properties.

The Earth's induced magnetic field is a result of the electrical current that is generated by the space current system within the Earth's interior. By observing Earth's induced magnetic field, we can acquire information on the space current system and the electrical structure of the Earth's interior, which is an important physical parameter to study the mechanism of space weather events and seismic sphere coupling. The Meridian Project has set up several induction magnetometers in the shape of a "#" along the longitudes of 120° E and 100° E and latitudes of 30° N and 40° N in China's mainland and Antarctic regions, to carry out fixed, long-term, and continuous measurements of the Earth's induced magnetic field. The first phase of the Meridian Project is equipped with 14 LEMI-30 induction magnetometers produced by Ukraine, which have been in routine operation since 2009 and will be integrated with the grid of the second phase of the Meridian Project. Thirteen induction magnetometers will be installed in the second phase of the Meridian Project, which is scheduled to commence operation in 2023. Together with the equipment already installed in the first phase of the Meridian Project, a network of 27 induction magnetometers will be established. China is independently developing the induction magnetometer of the second phase of the Meridian Project. The magnetic core incorporates a new alloy material with high permeability. The multi-piece superposition technology was adopted to effectively gather the magnetic field, enhance the induction output signal, and improve the sensor's ability to pick up weak signals. The test results show that the frequency range of the induction magnetometer used in the second phase of the Meridian Project is wider, up to 0.001–30 Hz; its sensitivity is high, with a resolution of 10 pT; and its long-term operation is very stable.

Realizing the integration of intelligent fruit picking and grading for apple harvesting robots is an inevitable requirement for the future development of smart agriculture and precision agriculture. Therefore, an apple maximum diameter estimation model based on RGB-D camera fusion depth information was proposed in the study. Firstly, the maximum diameter parameters of Red Fuji apples were collected, and the results were statistically analyzed. Then, based on the Intel RealSense D435 RGB-D depth camera and LabelImg software, the depth information of apples and the two-dimensional size information of fruit images were obtained. Furthermore, the relationship between fruit depth information, two-dimensional size information of fruit images, and the maximum diameter of apples was explored. Based on Origin software, multiple regression analysis and nonlinear surface fitting were used to analyze the correlation between fruit depth, diagonal length of fruit bounding rectangle, and maximum diameter. A model for estimating the maximum diameter of apples was constructed. Finally, the constructed maximum diameter estimation model was experimentally validated and evaluated for imitation apples in the laboratory and fruits on the Red Fuji fruit trees in modern apple orchards. The experimental results showed that the average maximum relative error of the constructed model in the laboratory imitation apple validation set was ±4.1%, the correlation coefficient (R2) of the estimated model was 0.98613, and the root mean square error (RMSE) was 3.21 mm. The average maximum diameter estimation relative error on the modern orchard Red Fuji apple validation set was ±3.77%, the correlation coefficient (R2) of the estimation model was 0.84, and the root mean square error (RMSE) was 3.95 mm. The proposed model can provide theoretical basis and technical support for the selective apple-picking operation of intelligent robots based on apple size grading.

Cassava is one of the world’s staple crops and an important economic and food crop for one billion people. It holds significant value in food, feed, and industrial raw materials. However, cassava production is faced with the following problems: agricultural machinery and agronomy are not integrated, work efficiency is not high, it is not suitable for large-scale planting plots, and there is a lack of large-scale equipment, automation, and intelligent cassava production equipment. This study reviews research on cassava planting agronomy and mechanized production technologies and equipment, including planting, stem–tuber separation, and harvesting, both globally and in China. The shortcomings are analyzed, and recommendations are provided for current mechanized cassava production to accelerate the development of intelligent equipment and strengthen the shortcomings. Meanwhile, we used typical and extensive Chinese planting and harvesting machines as case studies. The future trends in cassava production are forecasted, underscoring the importance of advancing global mechanized technology and equipment for cassava production to enhance its efficiency, competitiveness, and modernization.

The study introduces an innovative three-stage nested power generation system that enables the cascading utilization of LNG cold energy. It makes the most of wasted energy by using ship jacket cooling water (JCW) and exhaust gas (EG) as heat sources, a trans-critical carbon dioxide cycle as internal circulation, and utilizing the pressure exergy of LNG. We choose two azeotrope mixing fluids that match the requirements and create four cases for the outer and middle cycle working fluids in the three-stage nested system. To discover the ideal system performance from the perspectives of exergy (E), economy (E), and environment (E), four cases were subjected to multi-objective optimization using the multi-objective particle swarm optimization technique (MOPSO). Finally, the optimal solution was found by applying the TOPSIS decision-making method. Through comparative analysis, the optimal system is selected among the four optimization results. R170 (22.66%) and R1150 (77.34%) are used as the outer circulating working medium, while R170 (90.86%) and R1270 (9.14%) are utilized as the inter-cycle working fluid. The net output work is 575.75 kW, the optimal exergy efficiency is 46.09%, the optimal electricity production cost is $0.04009 per kWh, the carbon dioxide emissions can be reduced by 36,910 tons, and the payback period is 2.548 years. After optimization, a more energy-efficient and environmentally friendly power generation system is obtained.

Data augmentation is an important task of using existing data to expand data sets. Using generative countermeasure network technology to realize data augmentation has the advantages of high-quality generated samples, simple training, and fewer restrictions on the number of generated samples. However, in the field of transmission line insulator images, the freely synthesized samples are prone to produce fuzzy backgrounds and disordered samples of the main insulator features. To solve the above problems, this paper uses cycle generative adversarial network (Cycle-GAN) used for domain conversion in the generation countermeasure network as the initial framework and uses the self-attention mechanism and the channel attention mechanism to assist the conversion to realize the mutual conversion of different insulator samples. The attention module with prior knowledge is used to build the generation countermeasure network, and the GAN model with local controllable generation is built to realize the directional generation of insulator belt defect samples. The experimental results show that the samples obtained by this method are improved in a number of quality indicators, and the quality effect of the samples obtained is excellent, which has a reference value for the data expansion of insulator images.

IntroductionThe rapid spread of plasmid-mediated tet(X4) conferring high tigecycline resistance poses a significant threat to public health. Escherichia coli as the most common pathogen which carries tet(X4) has been widely disseminated in China. Thus, comprehensive investigations are required to understand the mechanism of transmission of tet(X4)-positive E. coli.MethodsIn this study, a total of 775 nonduplicate samples were collected in Guangdong, China from 2019 to 2020. We screened for tet(X4)-positive E. coli by PCR amplification and species identification. Furthermore, we analyzed the phylogenetics and genetic context of tet(X4)-positive E. coli through whole-genome sequencing and long-reads sequencing.ResultsOverall, 146 (18.84%) tet(X4)-positive E. coli were isolated, comprising 2 isolates from humans and 144 isolates from pigs. The majority of tet(X4)-positive E. coli exhibited resistance to multiple antibiotics but all of them were susceptible to amikacin and colistin. Phylogenetic analysis showed that ST877, ST871, and ST195 emerged as the predominant sequence types in tet(X4)-positive E. coli. Further analysis revealed various genetic environments associated with the horizontal transfer of tet(X4). Notably, a 100-kbp large fragment insertion was discovered downstream of tet(X4), containing a replicon and a 40-kbp gene cluster for the bacterial type IV secretion system.DiscussionThe high colonization rate of tet(X4)-positive E. coli in animals suggests that colonization as a key factor in its dissemination to humans. Diverse genetic context may contribute to the transfer of tet(X4). Our findings underline the urgent need for controlling the spread of plasmid-mediated tigecycline resistance.

Summary: Sorafenib, a first-line drug for advanced hepatocellular carcinoma (HCC), unfortunately encounters resistance in most patients, leading to disease progression. Traditional approaches to counteract this resistance, particularly those targeting the RAF-MEK-ERK pathway, often face clinical feasibility limitations. Magnetic hyperthermia (MH), unlike conventional thermal therapies, emerges as a promising alternative. It uniquely combines magnetothermal effects with an increase in reactive oxygen species (ROS). This study found the potential of intracellular MH enhanced the efficacy of sorafenib, increased cellular sensitivity to sorafenib, and reversed sorafenib resistance by inhibiting the RAF-MEK-ERK pathway in an ROS-dependent manner in a sorafenib-resistant HCC cell. Further, in a sorafenib-resistant HCC mouse model, MH significantly sensitized tumors to sorafenib therapy, resulting in inhibited tumor growth and improved survival rates. This presents a promising strategy to overcome sorafenib resistance in HCC, potentially enhancing therapeutic outcomes for patients with this challenging condition.

IntroductionMagnetic resonance imaging (MRI)-guided wire localization can be applied to assist to remove suspected breast lesions accurately. This study aimed to evaluate the clinical application value of this technique in Chinese women.MethodsA total of 126 patients (131 lesions) who had underwent such technique in our hospital from April 2017 to June 2023 were enrolled. 1.5T MRI system and a wire localization device were used. Image characteristics, clinical features and postoperative pathology were collected and analyzed.ResultsAll of 126 patients (131 lesions) were successfully localized by MRI and excised for biopsy. There were 39 malignant lesions (29.77%) and 92 benign lesions (70.23%). There was no significant correlation between the morphology of DCE-MRI and the ratio of malignant lesions (P=0.763), while there was a statistical correlation between the BPE, TIC curve and the malignancy rate (P

BackgroundType 2 diabetes mellitus (T2DM) and hearing loss (HL) constitute significant public health challenges worldwide. Recently, the association between T2DM and HL has aroused attention. However, possible residual confounding factors and other biases inherent to observational study designs make this association undetermined. In this study, we performed univariate and multivariable Mendelian Randomization (MR) analysis to elucidate the causal association between T2DM and common hearing disorders that lead to HL.MethodsOur study employed univariate and multivariable MR analyses, with the Inverse Variance Weighted method as the primary approach to assessing the potential causal association between T2DM and hearing disorders. We selected 164 and 9 genetic variants representing T2DM from the NHGRI-EBI and DIAGRAM consortium, respectively. Summary-level data for 10 hearing disorders were obtained from over 500,000 participants in the FinnGen consortium and MRC-IEU. Sensitivity analysis revealed no significant heterogeneity of instrumental variables or pleiotropy was detected.ResultsIn univariate MR analysis, genetically predicted T2DM from both sources was associated with an increased risk of acute suppurative otitis media (ASOM) (In NHGRI-EBI: OR = 1.07, 95% CI: 1.02-1.13, P = 0.012; In DIAGRAM: OR = 1.14, 95% CI: 1.02-1.26, P = 0.016). Multivariable MR analysis, adjusting for genetically predicted sleep duration, alcohol consumption, body mass index, and smoking, either individually or collectively, maintained these associations. Sensitivity analyses confirmed the robustness of the results.ConclusionT2DM was associated with an increased risk of ASOM. Strict glycemic control is essential for the minimization of the effects of T2DM on ASOM.

More attention has been paid to environmental regulation of greenhouse gas emissions in the energy industry under the transformation of industrial structure. This paper takes microdata of Chinese energy enterprises from 1998 to 2012 as a sample to build a duty-sharing model, analyzes the effect of environmental regulations on the industrial chain, and explains the “double growth” phenomenon that occurred in China, which is nothing short of miraculous in terms of the environment and economy. In the industrial chain, the environmental obligations and responsibilities will be shared between upstream and downstream enterprises due to trade linkages. This paper finds that environmental responsibilities will move forward through the industrial chain when environmental regulations are strengthened. Downstream companies will loosen “relative” control constraints, thereby expanding output but increasing demand for upstream products. Different from the existing research, we claim that, since environmental regulation has a differential effect on the industrial chain, it will promote the growth of output in the entire chain, in contrast to the theory of “cost compliance”, which claims that environmental regulation will inevitably lead to the output. Based on this research, this paper puts forward some suggestions and insights on how the government implements environmental regulations.

Abstract Background Gait model consists of a marker set and a segment pose estimation algorithm. Plugin marker set and inverse kinematic algorithm (IK.) are prevalent in gait analysis, especially musculoskeletal motion analysis. Adding extra markers for the plugin marker set could increase the robustness to marker misplacement, motion artifacts, and even markers occlusion. However, how the different marker sets affect the gait analysis's kinematic output is unclear. Therefore, this study aims to investigate the effect of marker sets on the kinematic output during level walking in different populations. Results In all three planes, there are significant differences (P

Abstract Element detection is a key step in non‐destructive testing of printed circuit board (PCB) based on computed tomography (CT). In recent years, some image segmentation methods based on deep learning have shown great potential in the element segmentation task of PCB CT images, and greatly improved the efficiency and accuracy. However, since image segmentation is based on pixel‐level classification, the annotation of training data is difficult and costly. Aiming at this problem, the authors proposed a new active learning method based on the integration of relevant information about segmentation tasks and data variance. In this method, the Result Quality Evaluation Module (RQEM) proposed by us is used to generate task‐related information, and an adversarial network is used to generate the difference information between samples and the initial labelled data. Finally, the two parts of information are fused and used as the standard of data selecting. In the PCB CT image element segmentation task, the authors only need to select 12.7% of the whole training set with their proposed method to make Mean Intersection Over Union (MIOU) reach 79.7, which has reached 95% of the optimal performance of 83.7. The in‐depth analysis also verifies the effectiveness and stability of the authors’ method.

Male infertility affects millions of men worldwide and is increasing in prevalence, with asthenozoospermia (AS) and oligoasthenozoospermia (OA) being the most frequent causes, and current treatments are limited. A previous research reported that Linggui Yangyuan paste (LGYY) enhanced sperm viability and motility, but there is a lack of multicenter, rigorous, randomized and controlled studies on its efficacy. Wuzi Yanzong oral solution (WZYZ), a traditional Chinese herbal formula, is one of the most important and first-line drugs for AS and OA in China. We designed a direct comparison of LGYY’s effectiveness and safety against WZYZ in treating male infertility, specifically AS and OA. We propose a multicenter, double-blind, double-dummy, randomized controlled trial, which is planned to recruit 162 participants with AS or OA from five centers and will randomize them into two groups, whereby the treatment group will receive intervention with LGYY and WZYZ mimetics, while the control group will receive intervention with WZYZ and LGYY mimetics. The medications will be administered twice daily for 12 weeks, followed by a 12-week follow-up. The primary outcome will be total progressive motile sperm count (TPMSC), and the secondary outcomes will be semen parameters, including semen volume, sperm concentration, total sperm count, progressive motility (PR), PR + nonprogressive motility (NP), Chinese Medicine Symptoms Score (CMSS), spouse pregnancy rate and time to pregnancy. The safety outcomes will be based on the results of routine blood and urine tests, liver and kidney function tests and electrocardiography. Overall, this study aims to provide valuable insights into the potential efficacy and safety of LGYY compared to WZYZ for male infertility (AS or OA), which could guide clinicians to an alternative drug approach to treat patients with AS or OA. This clinical trial is registered at ClinicalTrials.org under the identifier NCT05792813.

Abstract Background Red ginseng (RG) is a traditional herb commonly used in China, Korea, and other East Asian countries. Recently, it has demonstrated a better clinical value in men’s reproductive health (MRH). The present review aimed to examine the effects of RG treatment on MRH. Results Overall, 42 articles related to RG application in MRH were reviewed, of which 31 were animal experiments and 11 were clinical studies. Furthermore, this review analyzed the use of RG in some male reproductive diseases in clinical trials and determined the associated mechanisms of action. The mechanism of action of RG in MRH may be related to oxidative stress, regulation of sex hormones and spermatogenesis-related proteins, and anti-inflammation. Conclusions The application of RG for the treatment of male infertility, erectile dysfunction, and prostate diseases has the potential to contribute to MRH.

Background: C1q/tumor necrosis factor-related protein-9 (CTRP9) is critically involved in the pathophysiology of metabolic and cardiovascular disorders. This investigation aimed to clarify the mechanism underlying the role of CTRP9 in atherosclerosis in apolipoprotein E (ApoE) knockout (KO) mice. Methods: ApoE KO mice were fed a Western diet and injected with a virus which resulted in CTRP9 overexpression or knockdown for 12 weeks. The plasma lipid levels and atherosclerotic plaque areas were measured after the mice were euthanized. Aortas were isolated, and RNA sequencing was performed to identify the differentially expressed genes and related signaling pathways. Finally, plasma oxidative stress factors were measured to demonstrate the reliability of the RNA sequencing results. Results: The plasma lipid levels in the CTRP9 overexpression group did not significantly differ from those in the green fluorescence protein (GFP) group. Markablely, CTRP9 overexpression inhibited atherosclerotic plaque formation in ApoE KO mice, whereas CTRP9 knockdown promoted plaque formation. RNA sequencing analysis identified 3485 differentially expressed genes that were prominently enriched across 55 signaling pathways. Additionally, plasma oxidative stress factors were significantly reduced after CTRP9 overexpression, whereas these factors were increased after CTRP9 knockdown, which was consistent with the results of the RNA sequencing analysis. Conclusions: These findings demonstrated that CTRP9 alleviated inflammation and cholesterol metabolism, which reduced oxidative stress in an atherosclerotic animal model. These beneficial effects may mediate the suppression of lesion development in the aorta.

The injudicious use of water and fertilizer to maximize crop yield not only leads to environmental pollution, but also causes enormous economic losses. For this reason, we investigated the effect of nitrogen (N) (N0 (0), N60 (60 kg ha−1), and N120 (120 kg ha−1)) at different irrigation levels (I0 (0), I1200 (budding 600 m3 ha−1 + kernel 600 m3 ha−1), and I1800 (budding 900 m3 ha−1 + kernel 900 m3 ha−1)) on oilseed flax in the Loess Plateau of China in 2019 and 2020. The objective was to establish appropriate irrigation and fertilizer management strategies that enhance the grain yield (GY) of oilseed flax and maximize water and N productivity. The results demonstrated that irrigation and N application and their coupling effects promoted dry matter accumulation (DMA) and non-structural carbohydrate (NSC) synthesis, and increased the GY of oilseed flax. The contents of NSC in various organs of flax were closely related to grain yield and yield components. Higher NSC in stems was conducive to increased sink capacity (effective capsule number per plant (EC) and thousand kernel weight (TKW)), and the coupling of irrigation and N affected GY by promoting NSC synthesis. Higher GY was obtained by the interaction of irrigation and N fertilizer, with the increase rate ranging from 15.84% to 35.40%. Additionally, in the increased yield of oilseed flax, 39.70–78.06%, 14.49–54.11%, and −10.6–24.93% were contributed by the application of irrigation and nitrogen and the interaction of irrigation and nitrogen (I × N), respectively. Irrigation was the main factor for increasing the GY of oilseed flax. In addition, different climatic conditions changed the contribution of irrigation and N and their interaction to yield increase in oilseed flax. Drought and low temperature induced soluble sugar (SS) and starch (ST) synthesis to resist an unfavorable environment, respectively. The structural equation model showed that the key factors to increasing the GY of oilseed flax by irrigation and nitrogen fertilization were the differential increases in DMA, EC, and TKW. The increases in EC and TKW were attributed to the promotion of DMA and NSC synthesis in oilseed flax organs by irrigation, nitrogen fertilization, and their coupling effects. The I1200N60 treatment obtained higher water use efficiency (WUE) and N partial factor productivity (NPFP) due to lower actual evapotranspiration (ETa) and lower N application rate. Therefore, the strategy of 1200 m3 ha−1 irrigation and 60 kg ha−1 N application is recommended for oilseed flax in semi-arid and similar areas to achieve high grain yield and efficient use of resources.

Deep learning technology can automatically learn features from large amounts of data, with powerful feature extraction and pattern recognition capabilities, thereby improving the accuracy and efficiency of object detection. [The objective of this study]: In order to improve the accuracy and speed of mask wearing deep learning detection models in the post pandemic era, the [Problem this study aimed to resolve] was based on the fact that no research work has been reported on standardized detection models for mask wearing with detecting nose targets specially. [The topic and method of this study]: A mask wearing normalization detection model (towards the wearing style exposing the nose to outside, which is the most obvious characteristic of non-normalized style) based on improved YOLOv5s (You Only Look Once v5s is an object detection network model) was proposed. [The improved method of the proposed model]: The improvement design work of the detection model mainly includes (1) the BottleneckCSP (abbreviation of Bottleneck Cross Stage Partial) module was improved to a BottleneckCSP-MASK (abbreviation of Bottleneck Cross Stage Partial-MASK) module, which was utilized to replace the BottleneckCSP module in the backbone architecture of the original YOLOv5s model, which reduced the weight parameters’ number of the YOLOv5s model while ensuring the feature extraction effect of the bonding fusion module. (2) An SE module was inserted into the proposed improved model, and the bonding fusion layer in the original YOLOv5s model was improved for better extraction of the features of mask and nose targets. [Results and validation]: The experimental results indicated that, towards different people and complex backgrounds, the proposed mask wearing normalization detection model can effectively detect whether people are wearing masks and whether they are wearing masks in a normalized manner. The overall detection accuracy was 99.3% and the average detection speed was 0.014 s/pic. Contrasted with original YOLOv5s, v5m, and v5l models, the detection results for two types of target objects on the test set indicated that the mAP of the improved model increased by 0.5%, 0.49%, and 0.52%, respectively, and the size of the proposed model compressed by 10% compared to original v5s model. The designed model can achieve precise identification for mask wearing behaviors of people, including not wearing a mask, normalized wearing, and wearing a mask non-normalized.