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Abstract Enhancing farmers’ adoption of agricultural green production technology (AGPT) is crucial for the green transformation of the agricultural sector. Obtaining additional income is the primary motivation for farmers to adopt AGPTs. Therefore, clarifying the relationship between AGPTs’ adoption degree and income will facilitate the possibility of farmers’ adoption of AGPTs. Based on research data obtained from 805 citrus farmers in Sichuan Province, this study examines the impact of the degree of AGPT adoption on farmers’ income and its mechanisms using the inverse probability weighted regression adjustment (IPWRA) model. These findings indicate: (1) The greater the degree of adoption of AGPTs by farmers, the more pronounced the impact on income increase. Using 1, 2, and 3 AGTs can increase farmers’ income from citrus sales by 7.1, 10.5, and 19.8 percentage points, respectively. (2) The adoption of AGPTs leads to increased income through higher yields and sales prices, which offset the incurred costs. (3) Market channels and farmers’ operating scales can affect the revenue effect of AGPT adoption. (4) Factors (i.e., education level, physical health status, and cultivation area) can affect farmers’ adoption of AGPTs. This study presents policy recommendations based on the above conclusions, aiming to guide the government in promoting AGPTs and advancing agricultural green transformation.

Abstract We aimed to assess long-term disease progression in patients with severe keratoconus (KC). Clinical records of 125 patients (201 eyes) with severe KC followed-up for > 12 months were retrospectively analyzed. From these, 28 patients (31 eyes) were included. Corneal topography parameters evaluated included thinnest corneal thickness (TCT), maximum keratometry (Kmax), anterior and posterior mean corneal radii of 3 mm (aKM, pKM), steep keratometry, and KC screening indices. All patients wore rigid gas permeable contact lenses (RGPCLs) for an extended period. The median patient age and follow-up period were 20 (interquartile range [IQR] 17–22) years and 25 (15–38) months, respectively. Compared to baseline, the aKM, Kmax, and KC screening indices on the anterior corneal surface were reduced at the final follow-up (P

Abstract Untargeted metabolomic analysis using mass spectrometry provides comprehensive metabolic profiling, but its medical application faces challenges of complex data processing, high inter-batch variability, and unidentified metabolites. Here, we present DeepMSProfiler, an explainable deep-learning-based method, enabling end-to-end analysis on raw metabolic signals with output of high accuracy and reliability. Using cross-hospital 859 human serum samples from lung adenocarcinoma, benign lung nodules, and healthy individuals, DeepMSProfiler successfully differentiates the metabolomic profiles of different groups (AUC 0.99) and detects early-stage lung adenocarcinoma (accuracy 0.961). Model flow and ablation experiments demonstrate that DeepMSProfiler overcomes inter-hospital variability and effects of unknown metabolites signals. Our ensemble strategy removes background-category phenomena in multi-classification deep-learning models, and the novel interpretability enables direct access to disease-related metabolite-protein networks. Further applying to lipid metabolomic data unveils correlations of important metabolites and proteins. Overall, DeepMSProfiler offers a straightforward and reliable method for disease diagnosis and mechanism discovery, enhancing its broad applicability.

Abstract Background Gastric cancer (GC) is a prevalent malignant tumor, and the RNA-binding protein polypyrimidine tract-binding protein 1 (PTBP1) has been identified as a crucial factor in various tumor types. Moreover, abnormal autophagy levels have been shown to significantly impact tumorigenesis and progression. Despite this, the precise regulatory mechanism of PTBP1 in autophagy regulation in GC remains poorly understood. Methods To assess the expression of PTBP1 in GC, we employed a comprehensive approach utilizing western blot, real-time quantitative polymerase chain reaction (RT–qPCR), and bioinformatics analysis. To further identify the downstream target genes that bind to PTBP1 in GC cells, we utilized RNA immunoprecipitation coupled with sequencing (si-PTBP1 RNA-seq). To evaluate the impact of PTBP1 on gastric carcinogenesis, we conducted CCK-8 assays, colony formation assays, and GC xenograft mouse model assays. Additionally, we utilized a transmission electron microscope, immunofluorescence, flow cytometry, western blot, RT–qPCR, and GC xenograft mouse model experiments to elucidate the specific mechanism underlying PTBP1’s regulation of autophagy in GC. Results Our findings indicated that PTBP1 was significantly overexpressed in GC tissues compared with adjacent normal tissues. Silencing PTBP1 resulted in abnormal accumulation of autophagosomes, thereby inhibiting GC cell viability both in vitro and in vivo. Mechanistically, interference with PTBP1 promoted the stability of thioredoxin-interacting protein (TXNIP) mRNA, leading to increased TXNIP-mediated oxidative stress. Consequently, this impaired lysosomal function, ultimately resulting in blockage of autophagic flux. Furthermore, our results suggested that interference with PTBP1 enhanced the antitumor effects of chloroquine, both in vitro and in vivo. Conclusion PTBP1 knockdown impairs GC progression by directly binding to TXNIP mRNA and promoting its expression. Based on these results, PTBP1 emerges as a promising therapeutic target for GC. Graphical Abstract

Abstract Introduction To evaluate the intraocular differences in optical coherence tomography (OCT)-based macular curvature index (MCI) among children with anisomyopia and to investigate the relationship between MCI and the macular microvasculature. Methods Fifty-two schoolchildren with anisometropia > 2.00 D were enrolled and underwent comprehensive examinations including cycloplegic refraction, axial length (AL), and swept source OCT/OCT angiography. OCT-based MCIs were determined from horizontal and vertical B-scans by a customized curve fitting model in MATLAB R2022 at 1-mm-, 3-mm-, and 6-mm-diameter circles at fovea. Characteristics and topographic variation of MCI was analyzed, and the relationships with microvascularity and its associated factors were investigated. Results MCI achieved high reliability and repeatability. There were overall larger MCIs in the more myopic eyes than the less myopic eyes in 1-mm-, 3-mm-, and 6-mm-diameter circles at fovea (all p

Abstract The oxidation chemistry of two‐dimensional transition metal carbide MXenes has brought new research significance to their protection and application. However, the oxidation behavior and degradation mechanism of MXenes, in particular with time under oxygen conditions at room temperature, remain largely unexplored. Here, several experimental and theoretical techniques are used to determine a very early stage of the oxidation mechanism of HF‐etched Ti3C2Tx (a major member of MXenes and Tx = surface functional groups) in an oxygen environment at room temperature. Aberration‐corrected environmental transmission electron microscopy coupled with reactive molecular dynamics simulations show that the crystal plane‐dependent oxidation rate of Ti3C2Tx and oxide expansion are attributed to differences in the coordination and charge of superficial Ti atoms, and the existence of the channels between neighboring MXene layers on the different crystal planes. The complementary x‐ray photoelectron spectroscopy and Raman spectroscopy analyses indicate that the anatase and a tiny fraction of brookite TiO2 successively precipitate from the amorphous region of oxidized Ti3C2Tx, grow irregularly and transform to rutile TiO2. Our study reveals the early‐stage structural evolution of MXenes in the presence of oxygen and facilitates further tailoring of the MXene performance employing oxidation strategy.

Abstract Background Clear cell renal cell carcinoma (ccRCC) is the most prevalent kidney cancer with high aggressive phenotype and poor prognosis. Accumulating evidence suggests that circRNAs have been identified as pivotal mediators in cancers. However, the role of circRNAs in ccRCC progression remains elusive. Methods The differentially expressed circRNAs in 4 paired human ccRCC and adjacent noncancerous tissues ccRCC were screened using circRNA microarrays and the candidate target was selected based on circRNA expression level using weighted gene correlation network analysis (WGCNA) and the gene expression omnibus (GEO) database. CircPDHK1 expression in ccRCC and adjacent noncancerous tissues (n = 148) were evaluated along with clinically relevant information. RT-qPCR, RNase R digestion, and actinomycin D (ActD) stability test were conducted to identify the characteristics of circPDHK1. The subcellular distribution of circPDHK1 was analyzed by subcellular fractionation assay and fluorescence in situ hybridization (FISH). Immunoprecipitation-mass spectrometry (IP-MS) and immunofluorescence (IF) were employed to evaluate the protein-coding ability of circPDHK1. ccRCC cells were transfected with siRNAs, plasmids or lentivirus approach, and cell proliferation, migration and invasion, as well as tumorigenesis and metastasis in nude mice were assessed to clarify the functional roles of circPDHK1 and its encoded peptide PDHK1-241aa. RNA-sequencing, western blot analysis, immunoprecipitation (IP) and chromatin immunoprecipitation (ChIP) assays were further employed to identify the underlying mechanisms regulated by PDHK1-241aa. Results CircPDHK1 was upregulated in ccRCC tissues and closely related to WHO/ISUP stage, T stage, distant metastasis, VHL mutation and Ki-67 levels. CircPDHK1 had a functional internal ribosome entry site (IRES) and encoded a novel peptide PDHK1-241aa. Functionally, we confirmed that PDHK1-241aa and not the circPDHK1 promoted the proliferation, migration and invasion of ccRCC. Mechanistically, circPDHK1 was activated by HIF-2A at the transcriptional level. PDHK1-241aa was upregulated and interacted with PPP1CA, causing the relocation of PPP1CA to the nucleus. This thereby inhibited AKT dephosphorylation and activated the AKT-mTOR signaling pathway. Conclusions Our data indicated that circPDHK1-encoded PDHK1-241aa promotes ccRCC progression by interacting with PPP1CA to inhibit AKT dephosphorylation. This study provides novel insights into the multiplicity of circRNAs and highlights the potential use of circPDHK1 or PDHK1-241aa as a therapeutic target for ccRCC.

Abstract Indoleamine 2,3‐dioxygenase 1 (IDO1), the key enzyme in the catabolism of the essential amino acid tryptophan (Trp) through kynurenine pathway, induces immune tolerance and is considered as a critical immune checkpoint, but its impacts as a metabolism enzyme on glucose and lipid metabolism are overlooked. We aim to clarify the potential role of IDO1 in aerobic glycolysis in pancreatic cancer (PC). Analysis of database revealed the positive correlation in PC between the expressions of IDO1 and genes encoding important glycolytic enzyme hexokinase 2 (HK2), pyruvate kinase (PK), lactate dehydrogenase A (LDHA) and glucose transporter 1 (GLUT1). It was found that IDO1 could modulate glycolysis and glucose uptake in PC cells, Trp deficiency caused by IDO1 overexpression enhanced glucose uptake by stimulating GLUT1 translocation to the plasma membrane of PC cells. Besides, Trp deficiency caused by IDO1 overexpression suppressed the apoptosis of PC cells via promoting glycolysis, which reveals the presence of IDO1–glycolysis–apoptosis axis in PC. IDO1 inhibitors could inhibit glycolysis, promote apoptosis, and exhibit robust therapeutic efficacy when combined with GLUT1 inhibitor in PC mice. Our study reveals the function of IDO1 in the glucose metabolism of PC and provides new insights into the therapeutic strategy for PC.

Clear cell renal cell carcinoma (ccRCC) is the most prevalent kidney cancer, with a highly aggressive phenotype and poor prognosis. RNA binding proteins (RBPs) play crucial roles in post-transcriptional gene regulation and have been implicated in tumorigenesis. RBPs have the potential to become a new therapeutic target for ccRCC. In this study, we screened and validated that insulin-like growth factor 2 mRNA binding protein 2 (IGF2BP2) as an RBP, was down-regulated in ccRCC tissues and cell lines. Functionally, we verified that IGF2BP2 significantly suppressed the migration and invasion ability of ccRCC in vitro and in vivo. Mechanistically, RIP-seq and actinomycin D experiments results showed that IGF2BP2 enhanced the expression of Creatine Kinase B (CKB) by binding to CKB mRNA and enhancing its mRNA stability. Thus, IGF2BP2 inhibited ccRCC metastasis through enhancing the expression of CKB. Taken together, these finding suggests that IGF2BP2 is a novel metastasis suppressor of ccRCC and may serve as a potential therapeutic target.

AbstractHuman papillomavirus (HPV) is the infectious etiological agent for diseases such as cervical cancer. Developing HPV vaccines is of great significance for cancer prevention. During the development of polyvalent HPV vaccines, such as 9-valent and 15-valent HPV vaccines, specifical identification of different HPV antigen is very important. The homemade HPV31 L1 VLPs was used as an immunogen to generate HPV 31 monoclonal antibodies (mAbs) through hybridoma cell culture. We generated several mAbs through hybridoma cell culture and selected two specific neutralizing antibodies, 19B2 and 19C4, which were further analyzed and characterized for binding activity, neutralizing activity, and specificity by enzyme-linked immunosorbent assays (ELISA). It is shown that both 19B2 and 19C4 could specifically recognize HPV31 L1 virus-like particles (VLPs). These two specific mAbs were further used to assemble a HPV31 antigen ELISA test kit. The assembled kit with high detection performance could be widely applied for the quantitative detection of HPV31 antigen during vaccine production as well as in the preliminary analysis of HPV31 infection.

Abstract N4-acetylcytidine (ac4C) is a post-transcriptional RNA modification that regulates in various important biological processes. However, its role in human cancer, especially lymph node metastasis, remains largely unknown. Here, we demonstrated N-Acetyltransferase 10 (NAT10), as the only known “writer” of ac4C mRNA modification, was highly expressed in head and neck squamous cell carcinoma (HNSCC) patients with lymph node metastasis. High NAT10 levels in the lymph nodes of patients with HNSCC patients are a predictor of poor overall survival. Moreover, we found that high expression of NAT10 was positively upregulated by Nuclear Respiratory Factor 1 (NRF1) transcription factor. Gain- and loss-of-function experiments displayed that NAT10 promoted cell metastasis in mice. Mechanistically, NAT10 induced ac4C modification of Glycosylated Lysosomal Membrane Protein (GLMP) and stabilized its mRNA, which triggered the activation of the MAPK/ERK signaling pathway. Finally, the NAT10-specific inhibitor, remodelin, could inhibit HNSCC tumorigenesis in a 4-Nitroquinoline 1-oxide (4NQO)-induced murine tumor model and remodel the tumor microenvironment, including angiogenesis, CD8+ T cells and Treg recruitment. These results demonstrate that NAT10 promotes lymph node metastasis in HNSCC via ac4C-dependent stabilization of the GLMP transcript, providing a potential epitranscriptomic-targeted therapeutic strategy for HNSCC.

As a standard clean production technology, the wide use of green control techniques (GCT) helps improve the quality of agricultural products and protect the environment. However, the level of application of GCT by Chinese farmers is not high. The market, as the ultimate place to realize the value of grain and the returns of grain farmers, plays an essential part in promoting GCT. Based on survey data from grain farmers in Sichuan Province, China, this study used a conditional mixed process (CMP) model to examine the effect of farmers’ market participation on their GCT adoption behavior and a mediated effects model to test the impact mechanism. The study further explored the effect of farmers’ market participation capability on their GCT adoption behavior. The results showed that (1) farmers’ market participation could significantly increase the likelihood of adopting GCT. (2) Market participation could influence farmers’ adoption behavior through agricultural income, market information, and green cognition. (3) Further research found that farmers were more likely to adopt GCT if their market participation capability was strong. These findings highlight the fact that developing countries have increased their efforts to encourage farmers to participate in markets and to enhance their market participation capability, thereby facilitating the adoption of GCT by farmers.

The convergence of software-defined networking (SDN) and the Internet of Things (IoT) provides a scalable method for handling the considerable volumes of data produced by IoT devices. However, the lack of appropriate security measures can lead to unauthorized access to sensitive data, potential breaches, and privacy violations, as well as time-consuming and inefficient data retrieval methods in SDN-IoT systems that require decrypting the entire dataset. To address these challenges, this article proposes the time-attribute-based access control scheme in SDN-IoT (TAAC). The TAAC scheme combines ciphertext-policy attribute-based encryption with a novel time-attribute-based access tree to ensure fine-grained access control on time and attributes, enabling secure ciphertext interaction and information sharing across domains. Furthermore, the TAAC scheme also incorporates searchable encryption, which enhances the efficiency of data retrieval. By implementing searchable encryption techniques, the data receiver can generate trapdoors to search and retrieve specific encrypted data without the need to decrypt the entire dataset. In summary, the TAAC scheme improves storage efficiency and computation, enhances scalability, and provides robust security, offering an efficient and secure solution for ciphertext sharing in SDN-IoT environments. Experimental results have demonstrated that the TAAC scheme shows excellent performance and outperforms other attribute-based searchable encryption algorithms.

With the rapid increase of the number of agricultural cooperatives in China, the problem of fake cooperatives has become more and more serious. The core problem is that some members do not use cooperative services, and elite capture phenomenon appears in the organization. Since services are one of the most important public goods attributes of cooperatives, it is important to ensure that more members use them. What are the factors that affect members' utilization level of cooperative services? Existing research does not provide a comprehensive answer. Based on the micro-survey data of 74 citrus cooperatives and 524 citrus members in China, the article found out that 50.9% of the members did not use any services provided by cooperatives, and only 20.04% of the members used cooperatives' sales services. So, this study empirically analyzes the factors that influence the use of cooperatives' services by puns model. The results show that quality of service, service convenience and mountain terrain promote the use of cooperative sales services for members. In addition, cooperative knowledge, planting area, surplus distribution, quality of service, and service convenience significantly increased the utilization leve of cooperative sales services by members. Finally, the study puts forward some suggestions, such as propagating cooperative sales service, improving the quality of cooperative sales service, perfecting cooperative distribution system.

Abstract Building reduced-order models (ROMs) is essential for efficient forecasting and control of complex dynamical systems. Recently, autoencoder-based methods for building such models have gained significant traction, but their demand for data limits their use when the data is scarce and expensive. We propose aiding a model’s training with the knowledge of physics using a collocation-based physics-informed loss term. Our innovation builds on ideas from classical collocation methods of numerical analysis to embed knowledge from a known equation into the latent-space dynamics of a ROM. We show that the addition of our physics-informed loss allows for exceptional data supply strategies that improves the performance of ROMs in data-scarce settings, where training high-quality data-driven models is impossible. Namely, for a problem of modeling a high-dimensional nonlinear PDE, our experiments show $$\times$$ × 5 performance gains, measured by prediction error, in a low-data regime, $$\times$$ × 10 performance gains in tasks of high-noise learning, $$\times$$ × 100 gains in the efficiency of utilizing the latent-space dimension, and $$\times$$ × 200 gains in tasks of far-out out-of-distribution forecasting relative to purely data-driven models. These improvements pave the way for broader adoption of network-based physics-informed ROMs in compressive sensing and control applications.

Abstract Background Insulin like growth factor II mRNA binding protein 3 (IGF2BP3) is an RNA binding protein with multiple roles in regulation of gene expression at the post-transcriptional level and is implicated in tumorigenesis and progression of numerous cancers including gastric cancer (GC). Circular RNAs (circRNAs) are a diverse endogenous noncoding RNA population that have important regulatory roles in cancer. However, circRNAs that regulate the expression of IGF2BP3 in GC is largely unknown. Methods CircRNAs that bound to IGF2BP3 were screened in GC cells using RNA immunoprecipitation and sequencing (RIP-seq). The identification and localization of circular nuclear factor of activated T cells 3 (circNFATC3) were identified using Sanger sequencing, RNase R assays, qRT-PCR, nuclear-cytoplasmic fractionation and RNA-FISH assays. CircNFATC3 expression in human GC tissues and adjacent normal tissues were measured by qRT-PCR and ISH. The biological role of circNFATC3 in GC was confirmed by in vivo and in vitro experiments. Furthermore, RIP, RNA-FISH/IF, IP and rescue experiments were performed to uncover interactions between circNFATC3, IGF2BP3 and cyclin D1 (CCND1). Results We identified a GC-associated circRNA, circNFATC3, that interacted with IGF2BP3. CircNFATC3 was significantly overexpressed in GC tissues and was positively associated with tumor volume. Functionally, the proliferation of GC cells decreased significantly after circNFATC3 knockdown in vivo and in vitro. Mechanistically, circNFATC3 bound to IGF2BP3 in the cytoplasm, which enhanced the stability of IGF2BP3 by preventing ubiquitin E3 ligase TRIM25-mediated ubiquitination, thereby enhancing the regulatory axis of IGF2BP3-CCND1 and promoting CCND1 mRNA stability. Conclusions Our findings demonstrate that circNFATC3 promotes GC proliferation by stabilizing IGF2BP3 protein to enhance CCND1 mRNA stability. Therefore, circNFATC3 is a potential novel target for the treatment of GC.

Abstract Differential diagnosis of pulmonary nodules detected by computed tomography (CT) remains a challenge in clinical practice. Here, we characterize the global metabolomes of 480 serum samples including healthy controls, benign pulmonary nodules, and stage I lung adenocarcinoma. The adenocarcinoma demonstrates a distinct metabolomic signature, whereas benign nodules and healthy controls share major similarities in metabolomic profiles. A panel of 27 metabolites is identified in the discovery cohort (n = 306) to distinguish between benign and malignant nodules. The discriminant model achieves an AUC of 0.915 and 0.945 in the internal validation (n = 104) and external validation cohort (n = 111), respectively. Pathway analysis reveals elevation in glycolytic metabolites associated with decreased tryptophan in serum of lung adenocarcinoma vs benign nodules and healthy controls, and demonstrates that uptake of tryptophan promotes glycolysis in lung cancer cells. Our study highlights the value of the serum metabolite biomarkers in risk assessment of pulmonary nodules detected by CT screening.

IntroductionFrequent resignation of young workers brings huge costs to the organizational management of enterprises. The frequent turnover behavior is a sign of low career identity, and exploring the paths that influence career identity behaviors is necessary. Previous studies have found that internship satisfaction and the psychological contract can influence career identity behavior. However, the dimensions of the psychological contract are unclear, and it is uncertain whether internship satisfaction can influence career identity behavior through the different dimensions of the psychological contract. This study attempts to expand the concept of psychological contract and construct a multiple mediation model. It aims to analyze the mediating role of different dimensions of the psychological contract between internship satisfaction and career identity behavior.MethodsA sample survey was conducted on Chinese fresh graduates by way of the questionnaire survey, and a total of 576 valid questionnaires were collected. Amos 26.0 was used to analyze the data and verify the multiple mediation model.ResultsThe results showed that psychological contract can be divided into three dimensions: transactional contract, relational contract, and developmental contract. Internship satisfaction can positively influence career identity behavior via the three dimensions of psychological contract, and there are differences in mediating effects among the dimensions. The mediating effect of developmental contract is the highest, relational contract is the second, and transactional contract is the lowest.DiscussionThis article expands the dimensions of psychological contract, emphasizes the importance of developmental contract, contributes to the literature on organizational psychology, and provides scales and empirical evidence for future research. The analysis points out that fresh graduates with long-term development opportunities often show higher career identity behavior. This provides valuable insights for enhancing career identity behavior, improving career sustainability, and assisting organizations in managing human resource mobility.

ABSTRACTExtraintestinal pathogenic Escherichia coli (ExPEC) is an important zoonotic pathogen. Recently, ExPEC has been reported to be an emerging problem in pig farming. However, the mechanism of pathogenicity of porcine ExPEC remains to be revealed. In this study, we constructed a transposon (Tn) mutagenesis library covering Tn insertion in over 72% of the chromosome-encoded genes of a virulent and multi-drug resistant porcine ExPEC strain PCN033. By using a mouse infection model, a transposon-directed insertion site sequencing (TraDIS) assay was performed to identify in vivo fitness factors. By comparing the Tn insertion frequencies between the input Tn library and the recovered library from different organs, 64 genes were identified to be involved in fitness during systemic infection. 15 genes were selected and individual gene deletion mutants were constructed. The in vivo fitness was evaluated by using a competitive infection assay. Among them, ΔfimG was significantly outcompeted by the WT strain in vivo and showed defective adhesion to host cells. rfa which was involved in lipopolysaccharide biosynthesis was shown to be critical for in vivo fitness which may have resulted from its role in the resistance to serum killing. In addition, several metabolic genes including fepB, sdhC, fepG, gltS, dcuA, ccmH, ddpD, narU, glpD, malM, and yabL and two regulatory genes metJ and baeS were shown as important determinants of in vivo fitness of porcine ExPEC. Collectively, this study performed a genome-wide screening for in vivo fitness factors which will be important for understanding the pathogenicity of porcine ExPEC.

BackgroundPoorly differentiated non-small cell lung cancer (NSCLC) is characteristic of high rate of distant metastasis and late stages at diagnosis. Small intestine metastasis is a rare but severe complication of lung cancer with a high rate of mortality. However, there is currently a lack of genetic profile studies on the small intestine metastasis of lung cancer.Case presentationsWe present 2 cases of male patients in their 60s with primary NSCLC of low differentiation, initially with no distant metastasis detected. Biopsy samples were obtained from the primary pulmonary lesions, and both patients received systematic radiotherapy (RT) and chemotherapy. However, both cases presented with abdominal pain and distension, and immunohistochemistry of small intestine biopsy samples obtained by endoscopy confirmed lung cancer metastasis. Next generation sequencing was used to explore the genetic profiles from the biopsy samples of both the primary pulmonary lesions and small intestine metastases. The correlated genes responsible for the small intestine metastasis from poorly differentiated NSCLC in these 2 patients included TP53, LRP1B, and FGFR2. The reports of small intestine metastasis from poorly differentiated NSCLC with the past 5 years were systematically reviewed and summarized subsequently.ConclusionsPoorly differentiated NSCLC with small intestine metastases, while rare, substantially impacts the prognosis and poses major challenges for diagnosis and treatment. Through comparisons of genetic profiles between patients and in the same patient before and after metastasis, we identified the mutations in genes such as TP53, LRP1B, and FGFR2, which were correlated with the occurrence and progression of poorly differentiated NSCLC, as well as its small intestinal metastasis. This discovery has the potential to guide clinicians in developing personalized treatment plans through the manipulation of targeted and radiation therapies.

Introduction Lung nodules are one of the most prevalent diseases. Medical imaging methods have a high false positive rate for distinguishing malignant nodules from benign nodules. Therefore, developing new technologies with high accuracy for screening malignant nodules is of great importance for lung nodule surveillance. Use of flow cytometry to detect biomarkers in blood macrophages (epitop detect in macrophages/macrophages) has opened a new era for early and noninvasive diagnosis of cancer. This planned study aims to examine whether the peripheral blood macrophage factors Apo10 and TKTL1 accurately distinguish malignant nodules from benign nodules.Methods and analyses We plan to enrol in this study 3825 participants with lung nodules who will attend their annual physical examination at Sun Yat-sen University Cancer Center. Apo10 and TKTL1 levels in all patients will be tested at 60 min after their last meal every 6 months during their 3-year follow-up. Biopsy or surgical pathology results will be collected as the gold standard to assess the accuracy of Apo10 and TKTL1 in distinguishing malignant nodules from benign nodules. The sensitivity, specificity, positive predictive value, negative predictive value and area under the receiving operating characteristic curve will also be evaluated.Ethics and dissemination The study is approved by the medical ethics committee of Sun Yat-sen University (SL-G2022-005-02). The results of this study will be disseminated in peer-reviewed publications and presentations at international scientific meetings and will also be disseminated to the participants.Trial registration number ChiCTR2300073823; Pre-results.

Abstract Background Surgeon and anesthetist share the airway in a simpler way in the resection and reconstruction phase of tracheal surgery in tubeless spontaneous-ventilation video-assisted thoracoscopic surgery (SV-VATS). Tubeless SV-VATS means stable spontaneous ventilation in the resection and reconstruction phase to anesthesiologist, and unobstructed surgical field to surgeon. What’s the ideal airway management strategy during “Visual Field tubeless” SV-VATS for tracheal surgery is still an open question in the field. Methods We retrospectively reviewed 33 patients without sleeve and carina resections during the study period (2018–2020) in our hospital. The initial management strategy for these patients was spontaneous ventilation for intrathoracic tracheal resection and reconstruction. We obtained and reviewed medical records from our institution’s clinical medical records system to evaluate the airway management strategy and device failure rate for tracheal resection in Tubeless SV-VATS. Results Between 2018 and 2020, SV-VATS was first attempted in the 33 patients who had intrathoracic tracheal surgery but without sleeve and carina resections. All patients underwent bronchoscopy (33/33) and 8 patients (8/33) received partial resection before surgery. During the surgery, the airway device comprised either a ProSeal laryngeal mask airway (ProSeal LMA) (n = 27) or single lumen endotracheal tube (n = 6). During the resection and reconstruction phase, Visual Field tubeless SV-VATS failed in 9 patients, and breathing support switched to plan B which is traditional ventilation of a single lumen endotracheal tube for cross field intubation (n = 4) and ProSeal LMA alongside a high-frequency catheter (high-frequency jet ventilation, HFJV) (n = 5) into the distal trachea ventilation. Preoperative respiratory failure or other ventilation-related complications were not observed in this cohort. Conclusion Base on current analysis either ProSeal LMA or endotracheal tube is an effective airway management strategy for tubeless SV-VATS with appropriate patient selection. It also provides breathing support conversion option when there’s inadequate ventilation.

Reasonable matching of capacity resources and transported cargoes is the key to realizing intelligent scheduling of less-than-truck-load (LTL) logistics. In practice, there are many types and numbers of participating objects involved in LTL logistics, such as customers, orders, trucks, unitized implements, etc. This results in a complex and large number of matching schemes where truck assignments interact with customer order service sequencing. For the truck–cargo online matching problem under real-time demand, it is necessary to comprehensively consider the online matching process of multi-node orders and the scheduling of multi-types of trucks. Combined with the actual operation scenario, a mixed-integer nonlinear programming model is introduced, and an online matching algorithm with a double-layer nested time window is designed to solve it. By solving the model in a small numerical case using Gurobi and the online matching algorithm, the validity of the model and the effectiveness of the algorithm are verified. The results indicate that the online matching algorithm can obtain optimization results with a lower gap while outperforming in terms of computation time. Relying on the realistic large-scale case for empirical analysis, the optimization results in a significant reduction in the number of trips for smaller types of trucks, and the average truck loading efficiency has reached close to 95%. The experimental results demonstrate the general applicability and effectiveness of the algorithm. Thus, it helps to realize the on-demand allocation of capacity resources and the timely response of transportation scheduling of LTL logistics hubs.

The probiotic Limosilactobacillus reuteri DSM 17938 produces anti-inflammatory effects in scurfy (SF) mice, a model characterized by immune dysregulation, polyendocrinopathy, enteropathy, and X-linked inheritance (called IPEX syndrome in humans), caused by regulatory T cell (Treg) deficiency and is due to a Foxp3 gene mutation. Considering the pivotal role of lipids in autoimmune inflammatory processes, we investigated alterations in the relative abundance of lipid profiles in SF mice (± treatment with DSM 17938) compared to normal WT mice. We also examined the correlation between plasma lipids and gut microbiota and circulating inflammatory markers. We noted a significant upregulation of plasma lipids associated with autoimmune disease in SF mice, many of which were downregulated by DSM 17938. The upregulated lipids in SF mice demonstrated a significant correlation with gut bacteria known to be implicated in the pathogenesis of various autoimmune diseases. Chronic hepatitis in SF livers responded to DSM 17938 treatment with a reduction in hepatic inflammation. Altered gene expression associated with lipid metabolism and the positive correlation between lipids and inflammatory cytokines together suggest that autoimmunity leads to dyslipidemia with impaired fatty acid oxidation in SF mice. Probiotics are presumed to contribute to the reduction of lipids by reducing inflammatory pathways.

The combined application of manure and chemical fertilizers has been recognized as a critical factor driving significant changes in crop yield and nutrient use efficiency, holding the potential to optimize agricultural management to achieve high yields. In this 40-year study, we investigated the effect of manure amendment on soybean and maize yields, water and nitrogen use efficiencies (WUE and NUE), and water and mineral N storage at 0–100 cm soil depths from 2017 to 2018 to explore the optimization of fertilization management strategies for soybean and maize production in Northeast China. To elucidate the impact of chemical fertilizers and manure, twelve treatments—control (CK); single N fertilizer at a low rate (N1) and that at a high rate (N2); N1, phosphorus (P), and potassium (K) fertilizer (N1PK); manure alone at 13.5 and 27 t ha−1 (M1 and M2); and those combined with N, P, or K fertilizer (M1N1, M1N2, and M1N1PK and M2N1, M2N2, and M2N1PK)—were selected and studied. The results showed that long-term amendment with manure significantly increased crop biomass and yield in the soybean–maize–maize rotation system. Combining with manure increased the WUE, the partial factor productivity of N fertilizer (PFPN), and N physiological efficiency (PEN) in both the soybean and maize seasons; conserved soil water (mainly at 40–60 cm); and increased soil N retention (in the upper 60 cm layer), which reduced the risk of N leaching, with a better effect being observed after the application of 13.5 t ha−1 manure. These results provide insight into the potential of using fertilization management strategies that include amendment with 13.5 t ha−1 manure in combination with N, P, and K fertilizer in the maize season and only chemical fertilizer in the soybean season, as these results indicate that such strategies can achieve high yields and be used to implement agricultural sustainable development in brown soil regions in Northeast China.

Gastric cancer (GC) is the most common type of malignant tumor within the gastrointestinal tract, and GC metastasis is associated with poor prognosis. Polypyrimidine tract binding protein 1 (PTBP1) is an RNA-binding protein implicated in various types of tumor development and metastasis. However, the role of PTBP1 in GC metastasis remains elusive. In this study, we verified that PTBP1 was upregulated in GC tissues and cell lines, and higher PTBP1 level was associated with poorer prognosis. It was shown that PTBP1 knockdown in vitro inhibited GC cell migration, whereas PTBP1 overexpression promoted the migration of GC cells. In vivo, the knockdown of PTBP1 notably reduced both the size and occurrence of metastatic nodules in a nude mice liver metastasis model. We identified phosphoglycerate kinase 1 (PGK1) as a downstream target of PTBP1 and found that PTBP1 increased the stability of PGK1 by directly binding to its mRNA. Furthermore, the PGK1/SNAIL axis could be required for PTBP1’s function in the promotion of GC cell migration. These discoveries suggest that PTBP1 could be a promising therapeutic target for GC.

BackgroundLung cancer is the most common cause of cancer-related mortality in the world. Unfortunately, more than 50% of patients have already metastasized at the time of diagnosis, contributing to morbidity and mortality. Common sites of metastasis are adrenal glands, liver, bone, and brain. Bladder metastasis is rare and should prompt a careful differential consideration of primary bladder cancer.Case descriptionHere, we report a 72-year-old female who went to the hospital for “gross hematuria for one day”. Cystoscopy showed space-occupying lesions in the bladder. During the general CT examination, space-occupying lesions in the lower lobe of the lung were found. Peripheral lung cancer with multiple lymph node metastases, pulmonary metastasis, and left pleural effusion were considered. Transurethral cystoscopic resection of the bladder tumor and pleural effusion cell block examination were performed to clarify the diagnosis. Combined with morphological and immunohistochemical results, both pathological results supported a diagnosis of lung adenocarcinoma metastasis, and gene detection was carried out. EGFR, ALK, and ROS-1 were negative. According to the genetic testing results, there was no corresponding targeted drug, so we administered chemotherapy, and one-year survival was achieved, which was better than expected based on other studies.ConclusionThis paper describes a case of lung adenocarcinoma metastatic to the bladder and includes a review of the literature to provide clinicians with diagnostic and treatment experience and help avoid misdiagnosis and mistreatment.

Abstract Background Radiotherapy has been widely used to treat various cancers, but its efficacy depends on the individual involved. Traditional gene-based machine-learning models have been widely used to predict radiosensitivity. However, there is still a lack of emerging powerful models, artificial neural networks (ANN), in the practice of gene-based radiosensitivity prediction. In addition, ANN may overfit and learn biologically irrelevant features. Methods We developed a novel ANN with Selective Connection based on Gene Patterns (namely ANN-SCGP) to predict radiosensitivity and radiocurability. We creatively used gene patterns (gene similarity or gene interaction information) to control the "on–off" of the first layer of weights, enabling the low-dimensional features to learn the gene pattern information. ANN-SCGP was trained and tested in 82 cell lines and 1,101 patients from the 11 pan-cancer cohorts. Results For survival fraction at 2 Gy, the root mean squared errors (RMSE) of prediction in ANN-SCGP was the smallest among all algorithms (mean RMSE: 0.1587–0.1654). For radiocurability, ANN-SCGP achieved the first and second largest C-index in the 12/20 and 4/20 tests, respectively. The low dimensional output of ANN-SCGP reproduced the patterns of gene similarity. Moreover, the pan-cancer analysis indicated that immune signals and DNA damage responses were associated with radiocurability. Conclusions As a model including gene pattern information, ANN-SCGP had superior prediction abilities than traditional models. Our work provided novel insights into radiosensitivity and radiocurability.

Abstract Background Gastric cancer (GC) is one of the most common malignant tumors in China. Circular RNAs (circRNAs) are novel non-coding RNAs with important regulatory roles in cancer progression. IGF2BP3 has been found to play oncogenic roles in various cancers including GC, while the exact mechanism of IGF2BP3 is largely unknown. Methods The expression of IGF2BP3 in GC was evaluated by Western Blot and bioinformatics analysis. CircRNA expression profiles were screened via IGF2BP3 RIP-seq in GC. Sanger sequencing, RNase R digestion, nucleo-plasmic separation and RNA-FISH assays were used to detect the existence and expression of circARID1A. RNA ISH assay was employed to test the expression of circARID1A in paraffin-embedded GC tissues. Moreover, the function of circARID1A on cellular proliferation was assessed by CCK-8, plate colony formation, EdU assays and GC xenograft mouse model in vivo. Furthermore, the location or binding of circARID1A, IGF2BP3 protein and SLC7A5 in GC was evaluated by RNA-FISH/IF or RNA pull-down assays. Results We identified a novel circRNA, circARID1A, that can bind to IGF2BP3 protein. CircARID1A was significantly upregulated in GC tissues compared with noncancerous tissues and positively correlated with tumor length, tumor volume, and TNM stage. CircARID1A knockdown inhibited the proliferation of GC cells in vitro and in vivo and circARID1A played an important role in the oncogenic function of IGF2BP3. Mechanistically, circARID1A served as a scaffold to facilitate the interaction between IGF2BP3 and SLC7A5 mRNA, finally increasing SLC7A5 mRNA stability. Additionally, circARID1A was able to directly bind SLC7A5 mRNA through complementary base-pairing and then formed the circARID1A-IGF2BP3-SLC7A5 RNA–protein ternary complex and promoted the proliferation of GC via regulating AKT/mTOR pathway. Conclusions Altogether, our data suggest that circARID1A is involved in the function of IGF2BP3 and GC proliferation, and the circARID1A-IGF2BP3-SLC7A5 axis has the potential to serve as a novel therapeutic target for GC.

Nanoplastics (NPs) are a matter of widespread concern, as they are easily absorbed by a wide variety of organisms and accumulate in biological tissues. While there is evidence that nanoplastics are toxic to various organisms, few studies have investigated the mechanisms underlying the toxicities of NPs with different surface functionalizations to macrophage cells. In this study, mouse mononuclear macrophage (RAW264.7) cells were exposed to polystyrene nanoplastics (PS-NPs) with three different surface functionalizations, namely pristine polystyrene (PS), carboxyl-functionalized polystyrene (PS-COOH), and amino-functionalized polystyrene (PS-NH2), to evaluate the cellular endocytosis, lactate dehydrogenase (LDH) release, cell viability, reactive oxygen species (ROS), mitochondrial membrane potential, apoptosis, and related gene expression. Results showed that all three PS-NPs were endocytosed into cells. However, in the concentration range of 0–100 μg/mL, PS had no effect on cell viability or apoptosis, but it slightly increased cellular ROS and decreased mitochondrial membrane potential. PS-NH2 exhibited the highest cytotoxicity. PS-COOH and PS-NH2 induced ROS production, altered the mitochondrial membrane potential, and caused cell apoptosis regulated by the mitochondrial apoptosis pathway. Results also showed that cell membrane damage induced by PS-NH2 is one of the primary mechanisms of its cytotoxicity to RAW264.7 cells. The results of this study clarify the toxicities of PS-NPs with different surface functionalizations to macrophages, thereby improving the identification of immune system risks related to nanoplastics.

Global awareness of the need to enhance crop production and reduce environmental issues associated with nitrogen (N) fertilizer has increased. However, studies on how the N fate changed with manure addition are still limited. To explore efficient fertilization management for an improved grain yield, N recovery efficiency, and reduced N residual in the soil or that unaccounted for, a field 15N micro-plot trial in a soybean–maize–maize rotation was conducted to evaluate the effect of fertilization regimes on soybean and maize yields and the fertilizer N fate in the plant–soil system during 2017–2019 within a 41-year experiment in Northeast China. Treatments included chemical N alone (N), N and phosphorus (NP), N, P, and potassium (NPK), and those combined with manure (MN, MNP, and MNPK). Application of manure increased grain yield, on average, by 153% for soybean (2017) and 105% and 222% for maize (2018 and 2019) compared to no manure, with the highest at MNPK. Crop N uptake and that from labeled 15N-urea also benefited from manure addition, mainly partitioned to grain, and the average 15N-urea recovery was 28.8% in the soybean season with a reduction in the subsequent maize seasons (12.6%, and 4.1%). Across the three years, the fertilizer 15N recovery ranged from 31.2–63.1% (crop) and 21.9–40.5% (0–40 cm soil), with 14.6–29.9% unaccounted for, including N losses. In the two maize seasons, manure addition significantly increased the residual 15N recovery in crop attributed to the enhancing 15N remineralization, and reduced that in soil and unaccounted for compared to single chemical fertilizer, with MNPK performing the best. Therefore, applying N, P, and K fertilizers in the soybean season and NPK combined with manure (13.5 t ha–1) in the maize seasons is a promising fertilization management strategy in Northeast China and similar regions.

Effective biosecurity measures are crucial in controlling and preventing major pig diseases, ultimately ensuring farm income and social stability. This study extracted data from 205 farmer surveys in Sichuan Province, China, to construct a biosecurity index system for pig farms. The biosecurity levels of pig farms were evaluated using a projection pursuit method to identify weak areas. The Tobit model was then utilized to determine the factors that influenced the biosecurity levels. The results indicated that the overall biosecurity levels of the pig farms were low. The study found that the average biosecurity score among farms was 0.61, with a minimum score of 0.37 and a maximum score of 0.89 (on a scale of 0 to 1). These results suggest that there are significant differences in biosecurity levels among the farms. The study also found that the scores for first-level indicators related to breeding environment management, as well as second-level indicators related to personnel management and awareness of African swine fever prevention and control, were significantly lower than scores for other indicators in the farmers’ biosecurity systems. This study investigated the factors influencing biosecurity on farms and found that technical training, farm size, income share, production organization, and government inspections had a significant impact on the level of biosecurity implemented. This study emphasizes the significance of biosecurity in enhancing pig farm biosecurity and its role in improving farm resilience to major animal diseases like African swine fever. It also provides valuable insights for policymakers to make informed decisions regarding related policies.

African Swine Fever (ASF) is a highly infectious disease, severely affecting domestic pigs and wild boar. It has significantly contributed to economic losses within the pig farming industry. As a critical component of biosecurity measures, the selection of cleaning and disinfection (C&D) procedures is a dynamic and long-term decision that demands a deeper knowledge base among pig farmers. This study uses a binary logit model to explore the effect of epidemic prevention training on the adoption of C&D procedures among pig farmers with irregular and regular C&D procedures based on micro-survey data obtained from 333 pig farmers from Sichuan. The endogeneity issue was handled using propensity score matching, resulting in solid conclusions. In addition, the critical mediating impact of biosecurity cognition was investigated using a bootstrap analysis. The empirical study demonstrated that epidemic prevention training encourages pig farmers to adopt C&D procedures, with biosecurity cognition significantly mediating. Furthermore, epidemic prevention training was more likely to promote the adoption of C&D procedures among pig farmers with shorter breeding experiences and those having breeding insurance. Our study emphasized the importance of implementing epidemic prevention training to improving pig farmers’ biosecurity cognition and promoting the adoption of C&D procedures. The results included suggested references for preventing ASF and the next epidemic of animal diseases.

There have been outbreaks of SARS-CoV-2 around the world for over three years, and its variants continue to evolve. This has become a major global health threat. The main protease (Mpro, also called 3CLpro) plays a key role in viral replication and proliferation, making it an attractive drug target. Here, we have identified a novel potential inhibitor of Mpro, by applying the virtual screening of hundreds of nilotinib-structure-like compounds that we designed and synthesized. The screened compounds were assessed using SP docking, XP docking, MM-GBSA analysis, IFD docking, MD simulation, ADME/T prediction, and then an enzymatic assay in vitro. We finally identified the compound V291 as a potential SARS-CoV-2 Mpro inhibitor, with a high docking affinity and enzyme inhibitory activity. Moreover, the docking results indicate that His41 is a favorable amino acid for pi-pi interactions, while Glu166 can participate in salt-bridge formation with the protonated primary or secondary amines in the screened molecules. Thus, the compounds reported here are capable of engaging the key amino acids His41 and Glu166 in ligand-receptor interactions. A pharmacophore analysis further validates this assertion.

Large-scale crop mapping is of fundamental importance to tackle food security problems. SAR remote sensing has lately received great attention for crop type mapping due to its stability in the revisit cycle and is not hindered by cloud cover. However, most SAR image-classification studies focused on the application of backscattering characteristics with machine learning models, while few investigated the potential of the polarization decomposition and deep-learning models. This study investigated whether the radar polarization information mined by polarization decomposition, the patch strategy and the approaches for combining recurrent and convolutional neural networks (Conv2d + LSTM and ConvLSTM2d) could effectively improve the accuracy of crop type mapping. Sentinel-1 SLC and GRD products in 2020 were collected as data sources to extract VH, VV, VH/VV, VV + VH, Entropy, Anisotropy, and Alpha 7-dimensional features for classification. The results showed that the three-dimensional Convolutional Neural Network (Conv3d) was the best classifier with an accuracy and kappa up to 88.9% and 0.875, respectively, and the ConvLSTM2d and Conv2d + LSTM achieved the second and third position. Compared to backscatter coefficients, the polarization decomposition features could provide additional phase information for classification in the time dimension. The optimal patch size was 17, and the patch-based Conv3d outperformed the pixel-based Conv1d by 11.3% in accuracy and 0.128 in kappa. This study demonstrated the value of applying polarization decomposition features to deep-learning models and provided a strong technical support to efficient large-scale crop mapping.

Abstract Insect olfaction system plays a key role in the foraging food, pollination, mating, oviposition, reproduction and other insect physiological behavior. Odorant binding protein are widely found in the various olfactory sensilla of different insect antennae and involved in chemical signals discrimination from natural environment. In this study, a novel OBP gene, MvitOBP3 is identified from the legume pod borer, Maruca vitrata, which it mainly harms important legume vegetables including cowpea, soybean and lablab bean. Real-time PCR results demonstrated that MvitOBP3 gene was abundantly expressed in the antennal tissue of M. vitrata, while low levels were distributed in the head, thorax, abdomen, leg and wing of adult moths. The recombinant OBP3 protein was purified using the prokaryotic expression and affinity chromatography system. Fluorescence competitive binding experiments indicated that that MvitOBP3 protein exhibited greater binding affinities with host-plant flower volatiles including Butanoic acid butyl ester, Limonene, 1H-indol-4-ol and 2-methyl-3-phenylpropanal, highlighting they may have attractant activities for the oviposition of female moths on the legume vegetables. Moreover, protein homology modeling and molecular docking analysis revealed that there are six amino acid sites of MvitOBP3 involved in the binding of the host-plant volatiles. These findings will further promote to understand the key role of odorant binding protein during host perception and oviposition of M. vitrata moths, which improve the efficiency of semiochemical-based prevention and monitoring for this pest in the legume vegetables field.

Abstract Background Clear cell renal cell carcinoma (ccRCC) is a common malignant tumour of the urinary tract. The major causes of poor prognosis are the lack of early diagnosis and metastasis. Accumulating research reveals that circular RNAs (circRNAs) can play key roles in the development and the progression of cancer. However, the role of circRNAs in ccRCC is still uncertain. Methods The circRNAs microarray (n = 4) was performed to investigate the circRNAs with differential expression in ccRCC tissues. The candidate circRNA was selected based on the cut‐off criteria, such as circRNA expression abundance, circRNA size and the design of divergent primers. The circ‐transportin‐3 (TNPO3) levels in ccRCC tissues were tested by quantitative real‐time (qRT)‐PCR (n = 110). The characteristics and subcellular localization of circ‐TNPO3 were identified via RNase R assay, qRT‐PCR and fluorescence in situ hybridization (FISH). Then, we explored the biological roles of circ‐TNPO3 in ccRCC via the function experiments in vitro and in vivo. RNA pull‐down, RNA immunoprecipitation, bioinformatic analysis, RNA‐FISH assays and rescue assays were applied to validate the interactions between circ‐TNPO3, insulin‐like growth factor 2 mRNA‐binding protein 2 (IGF2BP2) and serpin family H member 1 (SERPINH1) to uncover the underlying molecular mechanisms of circ‐TNPO3. Results We detected the obvious downregulation of circ‐TNPO3 in ccRCC compared to matched adjacent normal tissues (n = 110). The lower circ‐TNPO3 expression was found in ccRCC patients with distant metastasis, higher World Health Organization/International Society of Urologic Pathologists (WHO/ISUP) grade and more advanced tumour T stage. In vitro and in vivo, circ‐TNPO3 significantly suppressed the proliferation and migration of ccRCC cells. Mechanistically, we elucidated that circ‐TNPO3 directly bound to IGF2BP2 protein and then destabilized SERPINH1 mRNA. Moreover, IGF2BP2/SERPINH1 axis was responsible for circ‐TNPO3's function of inhibiting ccRCC metastasis. Epithelial splicing regulatory protein 1 (ESRP1) was probably involved in the biogenesis of circ‐TNPO3. Conclusions Circ‐TNPO3 can suppress ccRCC progression and metastasis via directly binding to IGF2BP2 protein and destabilizing SERPINH1 mRNA. Circ‐TNPO3 may act as a potential target for ccRCC treatment.

Abstract Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) invades the alveoli, where abundant alveolar macrophages (AMs) reside. How AMs respond to SARS-CoV-2 invasion remains elusive. Here, we show that classically activated M1 AMs facilitate viral spread; however, alternatively activated M2 AMs limit the spread. M1 AMs utilize cellular softness to efficiently take up SARS-CoV-2. Subsequently, the invaded viruses take over the endo-lysosomal system to escape. M1 AMs have a lower endosomal pH, favoring membrane fusion and allowing the entry of viral RNA from the endosomes into the cytoplasm, where the virus achieves replication and is packaged to be released. In contrast, M2 AMs have a higher endosomal pH but a lower lysosomal pH, thus delivering the virus to lysosomes for degradation. In hACE2 transgenic mouse model, M1 AMs are found to facilitate SARS-CoV-2 infection of the lungs. These findings provide insights into the complex roles of AMs during SARS-CoV-2 infection, along with potential therapeutic targets.

During orchid seed culture, seeds germinate as protocorms, and protocorms normally develop into plant with leaves and roots. Orchids require many years of vegetative development for flowering. However, under a certain combination of growth cultures, we observed that protocorms can directly flower without leaves and roots. Therefore, we performed comparative transcriptome analysis to identify the different transcriptional regulators of two types of protocorms of Cymbidium ensifolium, Cymbidium sinense, and Cymbidium goeringii. Zinc finger, MYB, AP2, and bHLH were the most abundant transcription factor (TF) families in the transcriptome. Weighted gene coexpression network analysis (WGCNA) was performed to identify hub genes related to leaf and flower development. The key hubs included SPL6, SVP, SEP2, KNOX1, AP2, OFP1, COL12, MYB13, MYB36, MYB59, bHLH086, and ARF7. The hub genes were further validated through statistical tools to propose the roles of key TFs. Therefore, this study initiates to answer that why there is no leaf initiation and root development and how can protocorm bypass the vegetative phase to flower? The outcomes can direct future research on short-span flowering in orchids through protocorms.

BackgroundEchinococcosis is a severe zoonotic disease that imposes a substantial burden on human life. This meta-analysis aimed to summarize available data on the prevalence of human echinococcosis and identify the key risk factors for echinococcosis in the Chinese general population.MethodsRelevant studies were comprehensively searched in the PubMed, EMBASE, Web of Science, Cochrane, Chinese National Knowledge Infrastructure (CNKI), Chongqing VIP Information (VIP), Wanfang and SinoMed databases until August 22, 2020. A random-effects model was used to estimate the pooled odds ratio (OR) and 95% confidence interval (95% CI). The I2 and Q statistics were calculated to evaluate the heterogeneity, and potential sources of heterogeneity were identified using sensitivity analysis and subgroup analysis. Publication bias was estimated by funnel plots and Egger's test.ResultsA total of 1026 studies were identified through the database search, of which 26 were eligible for this meta-analysis. The pooled prevalence of AE and CE were 2.88% and 5.66%, respectively. Ethnicity (OR = 2.93, 95% CI: 1.81–4.75; I2 = 0), herdsman occupation (OR = 2.66, 95% CI: 2.25–3.14; I2 = 8.0%), not washing hands before meals (OR = 2.40, 95% CI: 1.34–4.28; I2 = 82.8%) and being female (OR = 1.45, 95% CI: 1.26–1.66; I2 = 33.9%) were risk factors for AE. The top five risk factors for CE were ethnicity (OR = 3.18, 95% CI: 1.55–6.52; I2 = 79.2%), nomadism (OR = 2.71, 95% CI: 1.65–4.47; I2 = 55.8%), drinking nonboiled water (OR = 2.47, 95% CI: 1.36–4.47; I2 = 85.7), feeding viscera to dogs (OR = 2.35, 95% CI: 1.89–2.91; I2 = 21.5%), and herdsman occupation (OR = 2.19, 95% CI: 1.67–2.86; I2 = 85.1%).ConclusionsThis study generalized articles that have contributed to our current understanding of the epidemic of human echinococcosis (AE and CE) in China over the years. The results support that the ethnicity and dog-related factors are major risk factors for both CE and AE. The identification of echinococcosis risk factors may aid researchers and policymakers in improving surveillance and preventive measures aimed at reducing Echinococcus granulosus and Echinococcus multilocularis infection in humans.

BackgroundThis study aimed to explore the value of combining the modified geriatric nutrition risk index (mGNRI) and handgrip strength (HGS) in the prognosis assessment of cancer.MethodsThis multicenter, prospective cohort study, enrolled 5,607 cancer patients from 27 medical centers across 17 provinces in China between June 2012 and December 2019. The primary outcome was overall survival. Secondary outcomes included the Karnofsky Performance Scale (KPS) score, Patient-Generated Subjective Global Assessment (PG-SGA) score, cachexia, and admission 90-day outcome. A composite prognostic score (mGNRI-HGS score) was developed based on the mGNRI and HGS. The Kaplan–Meier method was used to draw the survival curve, and log-rank analysis was used to estimate the survival rate. The Cox proportional hazards model was used to investigate the associations of the mGNRI, HGS or mGNRI-HGS score with risk of mortality among the cancer patients, adjusted for potential confounders.ResultsA low mGNRI (HR = 0.99, 95%CI = 0.98–0.99, p < 0.001) and low HGS (HR = 0.99, 95%CI = 0.98–0.99, p = 0.001) were associated with an increased risk of mortality. A severe mGNRI-HGS score was independently associated with reduced survival. Compared with patients with normal scores, the risk of mortality among the patients with moderate and severe mGNRI-HGS scores was 28.8 and 13.3% higher, respectively. Even within the same pathological stage, it presented significant gradient prognostic stratification. Additionally, a low mGNRI-HGS score was also independently associated with a higher risk of low KPS (p < 0.001), high PGSGA (p < 0.001), cachexia (p < 0.001), and adverse admission 90-day outcome (p < 0.001).ConclusionsThe mGNRI and HGS may be useful predictors of long-term prognosis in cancer patients. The combination of the two methods provides effective prognostic stratification for cancer patients and could predict physical frailty, malnutrition, and cachexia.

Abstract Background Hereditary retinopathy is a significant cause of blindness worldwide. Despite the discovery of many mutations in various retinopathies, a large number of patients remain genetically undiagnosed. Targeted next-generation sequencing of the human genome is a suitable approach for the molecular diagnosis of retinopathy. Methods We describe a cohort of 211 families from central China with various forms of retinopathy; 95 patients were investigated using multigene panel sequencing, and the other 116 with suspected Leber hereditary optic neuropathy (LHON) were tested by Sanger sequencing. The detected variation of targeted sequencing was verified by PCR-based Sanger sequencing. We performed a comprehensive analysis of the cases using sequencing data and ophthalmologic examination information. Results Potential causal mutations were identified in the majority of families with retinopathy (57.9% of 95 families) and suspected LHON (21.6% of 116 families). There were 68 variants of a certain significance distributed in 31 known disease-causing genes in the 95 families; 37 of the variants are novel and have not been reported to be related to hereditary retinopathy. The NGS panel solution provided a 45.3% potential diagnostic rate for retinopathy families, with candidate gene mutations of undefined pathogenicity revealed in another 12.6%of the families. Conclusion Our study uncovered novel mutations and phenotypic aspects of retinopathy and demonstrated the genetic and clinical heterogeneity of related conditions. The findings show the detection rate of pathogenic variants in patients with hereditary retinopathy in central China as well as the diversity and gene distribution of these variants. The significance of molecular genetic testing for patients with hereditary retinopathy is also highlighted.

An adversarial reinforced report-generation framework for chest x-ray images is proposed. Previous medical-report-generation models are mostly trained by minimizing the cross-entropy loss or further optimizing the common image-captioning metrics, such as CIDEr, ignoring diagnostic accuracy, which should be the first consideration in this area. Inspired by the generative adversarial network, an adversarial reinforcement learning approach is proposed for report generation of chest x-ray images considering both diagnostic accuracy and language fluency. Specifically, an accuracy discriminator (AD) and fluency discriminator (FD) are built that serve as the evaluators by which a report based on these two aspects is scored. The FD checks how likely a report originates from a human expert, while the AD determines how much a report covers the key chest observations. The weighted score is viewed as a “reward” used for training the report generator via reinforcement learning, which solves the problem that the gradient cannot be passed back to the generative model when the output is discrete. Simultaneously, these two discriminators are optimized by maximum-likelihood estimation for better assessment ability. Additionally, a multi-type medical concept fused encoder followed by a hierarchical decoder is adopted as the report generator. Experiments on two large radiograph datasets demonstrate that the proposed model outperforms all methods to which it is compared.

Abstract Levels of intestinal toll-like receptor 4 (TLR4) impact inflammation in the neonatal gastrointestinal tract. While surfactant protein A (SP-A) is known to regulate TLR4 in the lung, it also reduces intestinal damage, TLR4 and inflammation in an experimental model of necrotizing enterocolitis (NEC) in neonatal rats. We hypothesized that SP-A-deficient (SP-A−/−) mice have increased ileal TLR4 and inflammatory cytokine levels compared to wild type mice, impacting intestinal physiology. We found that ileal TLR4 and proinflammatory cytokine levels were significantly higher in infant SP-A−/− mice compared to wild type mice. Gavage of neonatal SP-A−/− mice with purified SP-A reduced ileal TLR4 protein levels. SP-A reduced expression of TLR4 and proinflammatory cytokines in normal human intestinal epithelial cells (FHs74int), suggesting a direct effect. However, incubation of gastrointestinal cell lines with proteasome inhibitors did not abrogate the effect of SP-A on TLR4 protein levels, suggesting that proteasomal degradation is not involved. In a mouse model of experimental NEC, SP-A−/− mice were more susceptible to intestinal stress resembling NEC, while gavage with SP-A significantly decreased ileal damage, TLR4 and proinflammatory cytokine mRNA levels. Our data suggests that SP-A has an extrapulmonary role in the intestinal health of neonatal mice by modulating TLR4 and proinflammatory cytokines mRNA expression in intestinal epithelium.

Electrocardiogram (ECG) signals are among the significant physiological signals that indicate the essential properties of the human body. In recent years, the measurement of ECG signals has become more portable thanks to the increasing usage of wearable health testing technology. However, the enormous amount of signal data gathered over a long period of time does impose a heavy load on medical professionals. In addition, false alarms might occur due to the potential for the detected signal to become jumbled with noise and motion perturbations. Therefore, analyzing the quality of the measured raw ECG signal automatically is a valuable task. In this paper, we propose a new single-channel ECG signal quality assessment method that combines the Resnet network structure and the principle of self-attention to extract ECG signal features using the principle of similarity between individual QRS heartbeats within a time slice of ten seconds. In addition, an improved self-attention module is introduced into the deep neural network to learn the similarity between features. Finally, the network distinguishes between acceptable and unacceptable ECG segments. The model test results indicate that the F1-score can approach 0.954, which leads to a more accurate assessment of the ECG signal quality.

Nonalcoholic fatty liver disease (NAFLD) is one of the common metabolic diseases characterized by hepatic lipid accumulation. Insulin resistance and microcirculation dysfunction are strongly associated with NAFLD. CX08005, an inhibitor of PTP1B with the IC50 of 0.75 ± 0.07 μM, has been proven to directly enhance insulin sensitivity. The present study aimed to investigate the effects of CX08005 on hepatic lipid accumulation and microcirculation dysfunction in both KKAy mice and diet-induced obesity (DIO) mice. Hepatic lipid accumulation was evaluated by hepatic triglyceride determination and B-ultrasound analysis in KKAy mice. Insulin sensitivity and blood lipids were assessed by insulin tolerance test (ITT) and triglyceride (TG)/total cholesterol (TC) contents, respectively. In addition, the hepatic microcirculation was examined in DIO mice by in vivo microscopy. The results showed that CX08005 intervention significantly reduced the TG and echo-intensity attenuation coefficient in the livers of KKAy mice. Furthermore, we found that CX08005 treatment significantly enhanced insulin sensitivity, and decreased plasma TG and/or TC contents in KKAy and DIO mice, respectively. In addition, CX08005 treatment ameliorated hepatic microcirculation dysfunction in DIO mice, as evidenced by increased RBCs velocity and shear rate of the blood flow in central veins and in the interlobular veins, as well as enhanced rate of perfused hepatic sinusoids in central vein area. Additionally, CX08005 administration decreased the adhered leukocytes both in the center veins and in the hepatic sinusoids area. Taken together, CX08005 exhibited beneficial effects on hepatic lipid accumulation and microcirculation dysfunction associated with NAFLD, which was involved with modulating insulin sensitivity and leukocyte recruitment, as well as restoration of normal microcirculatory blood flow.

With the continuous development of deep learning, more and more domains use deep learning technique to solve key problems. The security issues of deep learning models have also received more and more attention. Nowadays, malware has become a huge security threat in cyberspace. Traditional signature-based malware detection methods are not adaptable to the current large-scale malware detection. Thus many deep learning-based malware detection models are widely used in real malware detection scenarios. Therefore, we need to secure the deep learning-based malware detection models. However, model testing currently focuses on image and natural language processing models. There is no related work to test deep learning-based malware detection models specifically. Therefore, to fill this gap, we propose MalFuzz. MalFuzz uses the idea of coverage-guided fuzzing to test deep learning-based malware detection models. To solve the model state representation problem, MalFuzz uses the first and last layer neuron values to approximately represent the model state. To solve the new coverage calculation problem, MalFuzz uses the fast approximate nearest neighbor algorithm to compute the new coverage. The mutation strategy and seed selection strategy in image model or natural language processing model testing is not appropriate in deep learning-based malware detection model testing. Hence MalFuzz designs the seed selection strategy and seed mutation strategy for malware detection model testing. We performed extensive experiments to demonstrate the effectiveness of MalFuzz. Based on MalConv, Convnet, and CNN 2-d, we compared the modified TensorFuzz and MAB-malware with MalFuzz. Experiment results show that MalFuzz can detect more model classification errors. Likewise, the mutation operation of MalFuzz can retain the original functionality of malware with high probability. Moreover, the seed selection strategy of MalFuzz can help us explore the model state space quickly.

A diffusive epidemic model with two delays subjecting to Neumann boundary conditions is considered. First we obtain the existence and the stability of the positive constant steady state. Then we investigate the existence of Hopf bifurcations by analyzing the distribution of the eigenvalues. Furthermore, we derive the normal form on the center manifold near the Hopf bifurcation singularity. Finally, some numerical simulations are carried out to illustrate the theoretical results.

Glycogen can be metabolized via glycogenolysis and the pentose phosphate pathway as well as into the production of UDP glucose, which when secreted can bind the P2Y14 receptor. Here the authors show how these glycogen metabolism pathways contribute to proinflammatory macrophage activation and susceptibility to sepsis.