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Background: Preadolescents, who are in a transitional phase of development, may experience higher exposure to heterosexual interactions while facing higher risks regarding misinformation in sexual knowledge and unsafe engagement in sexual activities. There is a deficiency in the availability of qualified educators and age-appropriate teaching materials for sexuality education in China. Methods: We implemented an animation-based comprehensive sexuality education package among preadolescents aged 9 to 12 years from eight schools in Anhui, China. The first round of intervention included 1,835 participants, lasting 2 months from September to November 2020. A total of 374 participants, accounting for 52% of the intervention group, received a second round of intervention in September 2021. Participants completed immediate follow-up assessment and 1-year follow-up assessment to assess changes in their sexual knowledge, attitudes, and other outcomes. Propensity score matching and difference-in-difference analysis were performed to determine the short- and long-term impacts. Results: Significant improvements were observed for both sexual knowledge and sexual attitudes in the immediate follow-up. There was no significant effect on pornography-seeking behavior or awareness of experiencing sexual abuse. After 1 year, the effect was sustained for sexual knowledge, but slightly declined for sexual attitudes. The second intervention significantly improved sexual knowledge; however, no significant change in sexual attitudes, pornography-seeking behavior, or awareness of experiencing sexual abuse was observed. Conclusions: Our comprehensive sexuality education package was effective in improving sexual knowledge both immediately and 1 year after the intervention. Repeated intervention can be an effective strategy for promoting preadolescent health development regarding comprehensive sexuality education.

Abstract NOTCH1 signaling, a vital regulator of cell proliferation and differentiation, is widely involved in the occurrence and development of malignant tumors. Pharmacological regulation of NOTCH1 is promising in tumor immunotherapy, whereas the effective rate of existing therapies remains low. NOTCH1 functions, as a cancer suppressor or a cancer promoter in different cancers, is engaged in the crosstalk between the immune microenvironment and cancer cells, posing a major challenge to immunotherapy. Therefore, a comprehensive view of the overall situation of NOTCH1-associated immune infiltration in pan-cancer should be built. The relation between NOTCH1 and immune infiltration was initially investigated in this paper. In this study, the data originated from the Genotype-Tissue Expression (GTEx) and the Cancer Genome Atlas (TCGA) databases were input into multiple online bioinformatic tools to study the characteristics of NOTCH1 in pan-cancer. We found that there was obvious heterogeneity in the NOTCH1-associated tumor immune infiltration in pan-cancer. In accordance with the heterogeneity, pan-cancer mainly fell into two categories, i.e., cancers that NOTCH1 promoted immune infiltration (termed hot tumors) and NOTCH1 inhibited immune infiltration (termed cold tumors). We further analyzed the changes of immune infiltration in pan-carcinoma species from the perspectives of NOTCH1 expression, mutation, gene function, tumor metastasis and drugs. NOTCH1 expression was significantly up-regulated in cold tumors but down-regulated in hot tumors. The Gene ontology (GO) enrichment analysis of NOTCH1 with the two categories placed stress on angiogenesis and protein dealkylation, respectively. Further, the gene sets of angiogenesis facilitated immune infiltration, whereas the gene sets of protein dealkylation hindered immune infiltration. The tsRNA associated with NOTCH1 is a type of angiogenin that potentially exerts a significant influence on angiogenesis. We have conducted a meticulous analysis of the function of this tsRNA. NOTCH1 was conducive to cancer-associated fibroblasts (CAFs) immune infiltration, while the metastatic process was more dependent on the differentiation and angiogenesis function of NOTCH1. Accordingly, the heterogeneity of NOTCH1 in immune infiltration was extensively analyzed in this study based on the pan-cancer study, which can contribute to the formulation of specific immunotherapy strategies.

Background Hepatocellular carcinoma (HCC) is the third leading cause of common cancer-related mortality globally, accounting for approximately 90% of all primary liver cancer cases. Its recurrence and mortality rates are high, with the underlying molecular mechanisms remaining unclear. Objective To explore potential molecular mechanisms of HCC and explore novel biomarkers. Methods RNA-seq expression data and clinical information were retrieved from TCGA database, differential gene expression analysis was conducted between normal liver tissue and HCC tissue. Enrichment analysis on the differentially expressed genes was performed. Based on the gene expression data profiles of HCC in TCGA, a co-expression network was established using the WGCNA R package, and weighted gene co-expression network analysis (WGCNA) was performed to select clinically significant modules and screen candidate Hub genes; the candidate Hub genes were further analyzed for significant differential expression in HCC tissues and normal liver tissues, and whether they were significantly correlated with the overall survival and disease-free survival of HCC patients. The Hub genes were conclusively identified, and their protein expression was validated through the Human Protein Atlas database. Results The genetic expression data in this study were obtained from 50 normal liver tissue samples and 373 HCC tissue samples. Through differential gene expression analysis, a total of 7 230 genes differential expression between HCC and normal hepatic tissue, comprising 3 691 up-regulated genes and 3 539 down-regulated genes in HCC were identified. Enrichment analysis showed that the up-regulated differentially expressed genes were mainly involved in cell cycle regulation and mitotic processes; the down-regulated differentially expressed genes were mainly involved in processes such as small molecule metabolism and organic acid metabolism. WGCNA identified 19 gene modules related to the clinical features of HCC patients, the cyan and purple modules were screened by analyzing the relationship between the modules and the clinical features. The first two genes in the cyan module genes that were strongly associated with both overall survival and disease-free survival of patients were VPS45 and FAM189B. In the purple module genes, first two genes that were strongly associated with both overall survival and disease-free survival of patients were CLEC1B and FCN3, respectively; therefore, VPS45, FAM189B, CLEC1B and FCN3 were identified as the final Hub genes. Immunohistochemical staining in the Human Protein Atlas database showed that VPS45 and FAM189B were expressed higher in HCC tissues than in normal liver tissues. FCN3 was expressed in HCC tissues lower than in normal liver tissues, the difference in the expression of CLEC1B between HCC tissues and normal liver tissues was not obvious. Conclusion VPS45, FAM189B, CLEC1B and FCN3 have been preliminary identified as possible novel potential biomarkers for HCC, which may provide a theoretical basis for targeted therapy of HCC.

In this paper, we utilise blockchain technology (BT) and circular q-rung orthopair fuzzy sets (Cq-ROFS) to address practical issues related to urban transportation and supply chain management (SCM). Recognising the weaknesses of earlier approaches such as circular intuitionistic fuzzy sets (C-IFS), we work Cq-ROFS to better accommodate imprecise input. Novel approaches that use into metaverse settings are being investigated as a means of addressing the complex problems associated with urban mobility. This study use the SWARA-AROMAN approach to evaluate potential blockchain integration possibilities for metaverse urban mobility. Sensitivity analysis and comprehensive evaluation yield powerful insights into the robustness and adaptability of solutions. With these findings at their disposal, policymakers will be more equipped to take on unpredictability and take advantage of opportunities for sustainable urban mobility. To enhance urban transportation solutions in the dynamic metaverse, future strategies should concentrate on improving processes and exploring novel technology. Ultimately, this research emphasises how critical it is to foster interdisciplinary collaboration and ongoing innovation if we hope to influence the patterns of urban mobility in the metaverse.

Abstract Background To explore the utility of 5.0T ultra‐high field magnetic resonance (MR) for the assessment of the superior cerebellar artery (SCA). Methods Imaging data from 55 patients (19 men and 36 women) who underwent three‐dimensional time of flight MR angiography (3D‐TOF‐MRA) with 5.0T MRI in the Shandong University Affiliated Shandong Provincial Third Hospital from May 22, 2023 to June 16, 2023 were retrospectively analyzed. The origin, caliber, and course of the SCA were recorded. An independent sample t‐test was used to compare the differences in quantitative indexes between the two groups. Results A total of 123 superior cerebellar arteries were detected in 55 patients. We found that 86.99% of superior cerebellar arteries were longer than the P3 segment of the posterior cerebral artery. The superior cerebellar arteries were divided into nine types according to the origin of the SCA, with Type A accounting for the highest proportion (approximately 49.09%). The mean diameter of the SCA was 1.11 ± 0.22 mm, while the mean diameters of the right and left sides were 1.13 ± 0.24 mm and 1.07 ± 0.27 mm, respectively. There were no differences in SCA diameters between the two sides (p > 0.05). Conclusions 3D‐TOF‐MRA with ultra‐high field 5.0T MR can effectively evaluate the SCA, and provides a new effective imaging evaluation method for clinical practice.

Antibodies targeting non-structural protein 1 (NS1) confer protection against Zika virus (ZIKV). Although monoclonal antibodies (MAbs) 3G2 and 4B8 are more potent than MAb 4F10 in suppressing ZIKV infection in neonatal mice models, the epitopes are unclear. Herein, we determined the Cryo-electron microscopy (Cryo-EM) structures of ZIKV NS1 in complex with five human antibodies at 2.6–2.9 Å resolution. Group I antibodies (3G2 and 4B8) recognize the previously unreported epitopes on the outer surface of the NS1 dimer. The unique binding mode of Group I antibodies led to a stronger recognition of the cell surface form of NS1 and completely inhibited secreted form non-structural protein 1 (sNS1)-induced endothelial permeability via their immunoglobulin G (IgG) and Fab. Group II antibodies (4F10, 2E11, and 14G5) recognize common epitopes in the distal end of the β-ladder domain, with a blockade efficiency that may be related to their affinity for the sNS1 protein and the presence of full-length IgG. These findings elucidate the correlation between epitope recognition and protective efficacy of anti-NS1 antibodies and highlight the diagnostic and therapeutic potential of 3G2 and 4B8.

Abstract Antibody-dependent enhancement (ADE) is a potential concern for the development of Zika virus (ZIKV) vaccines. Cross-reactive but poorly neutralizing antibodies, usually targeting viral pre-membrane or envelope (E) proteins, can potentially enhance dengue virus (DENV) infection. Although E domain III (EDIII) contains ZIKV-specific epitopes, its immunogenicity is poor. Here, we show that dimeric EDIII, fused to human IgG1 Fc fragment (EDIII-Fc) and encoded by circular RNA (circRNA), induces better germinal center reactions and higher neutralizing antibodies compared to circRNAs encoding monomeric or trimeric EDIII. Two doses of circRNAs encoding EDIII-Fc and ZIKV nonstructural protein NS1, another protective antigen, prevent lethal ZIKV infection in neonates born to immunized C57BL/6 mice and in interferon-α/β receptor knockout adult C57BL/6 mice. Importantly, a single-dose optimized circRNA vaccine with improved antigen expression confers potent and durable protection without inducing obvious DENV ADE in mice, laying the groundwork for developing flavivirus vaccines based on circRNAs encoding EDIII-Fc and NS1.

Abstract Agricultural practices affect soil microbes which are critical to soil health and sustainable agriculture. To understand prokaryotic and fungal assembly under agricultural practices, we use machine learning-based methods. We show that fertility source is the most pronounced factor for microbial assembly especially for fungi, and its effect decreases with soil depths. Fertility source also shapes microbial co-occurrence patterns revealed by machine learning, leading to fungi-dominated modules sensitive to fertility down to 30 cm depth. Tillage affects soil microbiomes at 0-20 cm depth, enhancing dispersal and stochastic processes but potentially jeopardizing microbial interactions. Cover crop effects are less pronounced and lack depth-dependent patterns. Machine learning reveals that the impact of agricultural practices on microbial communities is multifaceted and highlights the role of fertility source over the soil depth. Machine learning overcomes the linear limitations of traditional methods and offers enhanced insights into the mechanisms underlying microbial assembly and distributions in agriculture soils.

Abstract Background Konjac corms are known for their alkaloid content, which possesses pharmacological properties. In the primary cultivation areas of konjac, nitrogen deficiency is a common problem that significantly influences alkaloid synthesis. The impact of nitrogen deficiency on the alkaloids in konjac corms remains unclear, further complicated by the transition from mother to daughter corms during their growth cycle. Results This study examined 21 alkaloids, including eight indole alkaloids, five isoquinoline alkaloids, and eight other types of alkaloids, along with the associated gene expressions throughout the development of Amorphophallus muelleri Blume under varying nitrogen levels. Nitrogen deficiency significantly reduced corm diameter and fresh weight and delayed the transformation process. Under low nitrogen conditions, the content of indole alkaloids and the expression of genes involved in their biosynthesis, such as tryptophan synthase (TRP) and tryptophan decarboxylase (TDC), exhibited a substantial increase in daughter corms, with fold changes of 61.99 and 19.31, respectively. Conversely, in the mother corm, TDC expression was markedly reduced, showing only 0.04 times the expression level observed under 10 N treatment. The patterns of isoquinoline alkaloid accumulation in corms subjected to nitrogen deficiency were notably distinct from those observed for indole alkaloids. The accumulation of isoquinoline alkaloids was significantly higher in mother corms, with expression levels of aspartate aminotransferase (GOT), chorismate mutase (CM), tyrosine aminotransferase (TAT), and pyruvate decarboxylase (PD) being 4.30, 2.89, 921.18, and 191.40 times greater, respectively. Conversely, in daughter corms, the expression levels of GOT and CM in the 0 N treatment were markedly lower (0.01 and 0.83, respectively) compared to the 10 N treatment. Conclusions The study suggests that under nitrogen deficiency, daughter corms preferentially convert chorismate into tryptophan to synthesize indole alkaloids, while mother corms convert it into tyrosine, boosting the production of isoquinoline alkaloids. This research provides valuable insights into the mechanisms of alkaloid biosynthesis in A. muelleri and can aid in developing nitrogen fertilization strategies and in the extraction and utilization of alkaloids.

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

Electrocardiography (ECG) signals are often referred to as the language of the heart and have been widely utilized for diagnosing various heart ailments, particularly arrhythmias. Consequently, numerous machine learning models have been employed to automatically detect heart disorders using ECG signals. In this research, the primary objective is to detect arrhythmias using a center-symmetric self-organized textual pattern. A novel feature engineering model has been introduced, which includes the following components: (i) multilevel feature extraction using the proposed center-symmetric self-organized textual pattern (CSSOTP), (ii) iterative neighborhood component analysis (INCA), and (iii) classification using k-nearest neighbors (kNN) with 10-fold cross-validation. During the feature extraction phase, a multilevel feature extraction model incorporating maximum absolute pooling (MAP) and the proposed CSSOTP was applied. The CSSOTP was designed to select the most appropriate pattern for the given data block. A large language model (LLM) was leveraged to generate text for creating patterns, and ChatGPT was used to assist in text generation. To identify the most informative features, the INCA feature selector was employed, and the selected features were subsequently classified using the kNN classifier. An impressive 96.20 % classification accuracy was achieved by the CSSOTP-based feature engineering model when tested on an ECG dataset containing 17 classes. Furthermore, comparisons with state-of-the-art feature engineering models were conducted, demonstrating that the proposed model has superior classification capabilities.

Background With the changing disease spectrum of the population and the advancement of the national tiered diagnosis and treatment system, general practitioners play a vital role in disease diagnosis and treatment. At the same time, the continuous updating of medical knowledge and the ongoing changes in the health service demands of the residents necessitate the ongoing participation of general practitioners in continuing education and training. This ensures they can make the best diagnostic and treatment decisions and manage diseases effectively for their patients. Objective To analyze the current developments, training quality and research quality of continuing education research of general practice in China in the past ten years (2013-2022) . Methods In January 2023, eight Chinese and English databases including PubMed, Cochrane Library, Embase, CINAHL, ERIC, China National Knowledge Infrastructure (CNKI), Wanfang Data Knowledge Service Platform, and China Biology Medicine Literature Service System were used as data sources to obtain research on the training of continuing education for general practitioners in China. The literature was read, analyzed, organized, and summarized, with the search period ranging from January 2013 to December 2022. The Medical Education Research Study Quality Instrument (MERSQI) was utilized to comprehensively evaluate the quality of the literature. Results This review included a total of 49 articles, of which 11 were in English and 38 in Chinese. The themes of continuing education training focused on cardiovascular and cerebrovascular diseases (22.4%), emergency-related content (6.1%), and mental health (6.1%). The training formats were relatively singular, mainly based on traditional expert lectures (69.3%), with only 6.1% adopting the form of skill training, and 4.0% of the studies using problem-based learning (PBL) or team-based learning (TBL) training formats. There was usually a lack of rigorous evaluation: 31 studies (63.2%) used questionnaires to assess the effectiveness of the training, of which 19 had not undergone validity and reliability testing. In the study design, the largest proportion was single-group pre-post comparison (53.1%), followed by randomized controlled trials with pre-post measurements (26.5%), and the smallest proportion was controlled pre-post comparison (4.1%). Only 9 studies (18.3%) explicitly mentioned ethical approval, while the majority of studies (81.7%) did not undergo ethical review. The evaluations focused on the enhancement of knowledge and skills of general practitioners before and after trainin (85.7%), with less coverage of actual behavioral changes (14.2%) and benefits to patients and healthcare facilities (22.4%) . Conclusion In the past decade, the attention to general practice continuing education research has been insufficient, but there is significant room for development. In the future, it is necessary to expand training themes and adopt diverse training methods based on actual needs. Utilizing assessment tools with good validity and reliability, and focusing on the actual behavioral changes brought about by training, will benefit patients and enhance the quality of continuing education for general practitioners in multiple dimensions.

A preliminary study was conducted on the inactivation effects and mechanisms of spore inactivation of Aspergillus flavus and Aspergillus chevalieri spores, as well as the degradation of aflatoxins (AFs) and deoxynivalenol (DON) by ultraviolet combined with cold plasma. The results showed that ultraviolet combined with cold plasma could completely inactivate the two kinds of fungal spores and cause damage to cell membrane and nucleus when treated for 80 s. More than 70% of the two fungi carried by maize kernels were inactivated at 600 s. In terms of degradation of mycotoxins, the degradation rate of standard DON and aflatoxin B group exceeded 60% and 50% respectively at 600 s, and aflatoxin G group was less than 50%. However, toxins carried by maize kernels took longer time to degrade. The degradation rate of DON after 20 minutes of treatment was 36.41%, but the degradation rate of AFS did not exceed 30%. The use of ultraviolet combined with cold plasma treatment shows potential for the inactivation of fungal spores and the degradation of fungal toxins.

Jupiter is one of the top priorities for deep space exploration in China and other countries. The structure of Jupiter’s interior, in particular, is a crucial but still unclear scientific topic. This paper discusses current scientific understanding of Jupiter’s interior by summarizing the history of past and current exploration and data analysis. We review recent space-based and ground-based observation methods and analyze their feasibility. To gain new insight into the internal structure of Jupiter, we propose to study Jupiter’s innards by planetary seismology. Ground-based observation, namely the Jupiter Seismologic Interferometer Polarization Imager (SIPI) in Lenghu, will be developed to obtain the Doppler velocity distribution on the surface of Jupiter and identify oscillation signals. Lenghu has observation conditions that are not only exceptional in China but even in the world, capable of providing novel insight into the interior of Jupiter. This will also be the first study in China of the interior of Jupiter using asteroseismology, which has significant implications for China’s plans to explore Jupiter via spacecraft-mounted instruments.

Considerable research has been conducted into the efficacy of individual probiotics in broiler production, however information on the most effective combinations of synergistic Bacillus probiotic is lacking. This study investigated the impact of different Bacillus strain combinations in broiler chickens, as well as in vitro enzyme production. In experiment one, a total of 576 Ross 308 broilers at 1 d old were grown for 21 d across 6 treatments of maize-soybean diets (n = 12 pens per treatment) to compare three different strain combinations (formulation 1 [F1]: 3 strains Bacillus amyloliquefaciens; F2: Bacillus coagulans and 2 strains B. amyloliquefaciens; F3: B. coagulans, Bacillus licheniformis and 2 strains B. amyloliquefaciens; F5: Bacillus subtilis, B. licheniformis and 2 strains B. amyloliquefaciens), positive control (PC), and a negative control antibiotic treatment group (NC). In Exp. 2, a total of 360 one-day-old ROSS308 broilers were used to test five treatments (n = 9) including PC, NC, F1 and F5 (selected from Exp. 1), and F4 (Bacillus pumilis and 2 strains B. amyloliquefaciens) in a maize-soybean diet. B. amyloliquefaciens F1 demonstrated a significant improvement in feed conversion ratio (FCR) compared to F2 at d 14 (1.49 vs 2.10; P = 0.038) and the body weight (BW) at d 21 (847.0 g vs 787.4 g) compared to other combinations (P = 0.027). The FCR at d 21 tended to be lower in birds fed F1 (1.46 vs 1.66) compared to the control (P = 0.068). Probiotic treatments had significantly improved nutrient digestibility compared to the PC and NC. Also, probiotic treatments supported the growth of Streptococcus, a common commensal genus and reduced the abundance of genera that correlated with low weight gain such as Akkermansia. Experiment two revealed that F4 improved FCR (P

Rare actinomycete genera are highly recognized as a promising source of structurally diverse and bioactive natural products. Among these genera, Allokutzneria and Kibdelosporangium are two phylogenetically closely related and have been reported to encode some valuable biosynthetic enzymes and secondary metabolites. However, there is currently no relevant systematic research available to outline the linkage of genomic and metabolomics for specific secondary metabolites in these two promising genera. In this study, we first investigated the genus-specific secondary metabolic potential in Allokutzneria and Kibdelosporangium by comparing the diversity and novelty of their secondary metabolite biosynthetic gene clusters (BGCs). The specific secondary metabolites produced by two representative strains of these genera were comprehensively investigated using untargeted metabolomics techniques. The findings unveiled that the majority (95.4%) of the gene cluster families (GCFs) encoded by Allokutzneria and Kibdelosporangium were genus-specific, including NRPS GCFs encoding siderophores. The untargeted metabolomics analysis revealed that the metabolic profiles of two representative strains exhibit extensive specificity, with the culture medium having a big impact on the metabolic profiles. Besides, an MS-cluster featuring a series of hydroxamate-type siderophores was identified from Allokutzneria albata JCM 9917, with two of them, including a novel one (N-deoxy arthrobactin A), being experimentally validated. The present study offers valuable insights for the targeted discovery of genus-specific natural products from microorganisms.

Abstract Reporting the results of quality indicators can narrow the gap in the quality of care between hospitals. While most studies rely on outcome indicators, they may not accurately measure the quality of care. Process indicators are not only strongly associated with treatment outcomes, but are also more sensitive to whether patients are treated accurately, enabling timely intervention. Our study aims to investigate whether process indicators provide a more reasonable assessment of hospital quality of care compared to outcome indicators. Data were sourced from the Specific Disease Medical Service Quality Management and Control System in China. A total of 113,942 patients with breast cancer treated in 298 hospitals between January 2019 and April 2023 were included in this retrospective study. The rankability of 11 process indicators was calculated and used as a weight to create a new composite indicator. The composite indicators and outcome measures were compared using the O/E ratio categories. Finally, in order to determine the impact of different years on the results, a sensitivity analysis was conducted using bootstrap sampling. The rankability ( $$\rho$$ ρ ) values of the eleven process indicators showed significant differences, with the highest $$\rho$$ ρ value for preoperative cytological or histological examination before surgery (0.919). The $$\rho$$ ρ value for the outcome indicator was 0.011. The rankability-weighting method yielded a comprehensive score ( $$\rho$$ ρ = 0.883). The comparison with categorical results of the outcome indicator has different performance classifications for 113 hospitals (37.92%) for composite scores and 140 (46.98%) for preoperative cytological or histological examinationbefore surgery. Process indicators are more suitable than outcome indicators for assessing the quality of breast cancer care in hospitals. Healthcare providers can use process indicators to identify specific areas for improvement, thereby driving continuous quality improvement efforts.

Abstract Interrupted sampling repeater jamming (ISRJ) with flexible modulation parameters and coherent processing gain seriously threatens the radar detection system. The jamming suppression and target detection performance of existing anti‐jamming methods are limited by strong noise and jamming signals. An ISRJ suppression method combining multiple extended complex‐valued convolutional auto‐encoders (CVCAEs) and compressed sensing (CS) reconstruction is proposed. For the different tasks of parameter estimation and signal denoising, the extended CVCAEs including a complex‐valued convolutional shrinkage network (CVCSNet) and a complex‐valued UNet (CVUNet) are developed. Based on the time‐domain discontinuity of ISRJ signals, the CVCSNet is first used to directly estimate the parameters representing signal components and extract jamming‐free signals from received signals. Then, the extracted signals are denoised using the CVUNet. After that, relying on the denoised signals and the frequency sparsity of de‐chirped target signals, a CS model is established and solved to recover complete target signals for jamming suppression. Utilising the advantages of deep neural networks in weak feature extraction and signal representation, the CVCSNet and CVUNet can effectively improve the signal extraction accuracy and alleviate the limitation of noise on target signal reconstruction. Experimental results verify that the proposed method has superior ISRJ suppression performance and is robust to varying signal‐to‐noise ratios, jamming‐to‐signal ratios and jamming parameters.

Abstract This study aimed to identify factors associated with optimal weight loss response by analyzing pre-weight loss data from a cohort of 2577 patients with obesity who visited weight management clinics between 2013 and 2022. Out of these, 1276 patients had follow-up data available. Following dietary and exercise interventions, 580 participants achieved optimal weight loss outcomes. Participants were subsequently divided into two groups based on their weight loss outcomes: those who achieved optimal weight loss response and those who did not. Statistical analysis, conducted using RStudio, identified thirteen predictor variables through LASSO and logistic regression, with age emerging as the most influential predictor. A nomogram was developed to predict optimal weight loss response, showing good predictive performance (AUC = 0.807) and clinical applicability, validated by internal validation methods. Decision curve analysis (DCA) further illustrated the nomogram's clinical utility. The developed nomogram prediction model for optimal weight loss response is user-friendly, highly accurate, and demonstrates excellent discriminative and calibration capabilities.