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Abstract Objective To retrospectively evaluate thoracic duct (TD) congestion in hepatic lymphorrhea (HL) and propose treatment suggestions. Methods Retrospectively analyze cases of postoperative HL admitted from August 2007 to November 2023. Twenty cases were enrolled and followed up. The medical history, ascites characteristics, lymphoscintigraphy, direct lymphangiography, and other clinical data were reviewed. Results Twenty patients with ascites after cholecystectomy or radical gastrectomy were included. There were 15 patients with cirrhosis and 5 patients with hepatitis. Ascites were light yellow even if the patients had a non-low-fat diet. Triglyceride level mean of ascites was 0.61 ± 0.20 mmol/L. There were 94.1% (16/17) of patients whose ascitic cholesterol ≥ 45 mg/dL or SAAG

Abstract This study aimed to analyze the complications and long-term survival outcomes in patients who underwent radical gastrectomy for gastric cancer, as well as to identify the risk factors associated with postoperative complications. After conducting a comprehensive search within the medical records system, a total of 2508 patients who underwent radical gastrectomy and met the inclusion criteria were enrolled. Of the 2508 patients, 301 were diagnosed with postoperative complications. The pathological data, postoperative recovery, and survival outcome were compared between complication and control group. Subsequently, univariate and multivariate logistic regression analyses were conducted to identified the risk factors. According to the Clavien-Dindo grading criteria for postoperative complications, the proportions of grade I, II, III, IV, and V complications following radical gastrectomy were observed to be 28.2%, 42.9%, 19.6%, 8.0%, and 1.3%, respectively. The presence of postoperative complications significantly prolonged the duration of gastrointestinal decompression (P 65years [odds ratio (OR) = 1.378, P = 0.020], presence of diabetes (OR = 2.042, P 215 min (OR = 1.450, P = 0.006), intraoperative blood loss > 275 ml (OR = 1.474, P = 0.004), and Roux-en-Y anastomosis for both whole stomach (OR = 1.567, P = 0.021) and distal gastric cancer (OR = 2.083, P = 0.003) were identified as independent risk factors for postoperative complications. This study analyzed the complications and survival outcomes following radical gastrectomy, and investigated the predictors for postoperative complications, thereby providing valuable guidance on the prevention and management of surgical complications in gastric cancer.

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.

Abstract With the development of the digital economy, the power demand for data centers (DCs) is rising rapidly, which presents a challenge to the economic and low‐carbon operation of the future distribution system. To this end, this paper fully considers the multiple flexibility of DC and its impact on the active distribution network, and establishes a collaborative planning model of DC and active distribution network. Differing from most existing studies that apply robust optimization or stochastic optimization for uncertainty characterization, this study employs a novel interval optimization approach to capture the inherent uncertainties within the system (including the renewable energy source (RES) generation, electricity price, electrical loads, emissions factor and workloads). Subsequently, the planning model is reformulated as the interval multi‐objective optimization problem (IMOP) to minimize economic cost and carbon emission. On this basis, instead of using a conventional deterministic‐conversion approach, an interval multi‐objective optimization evolutionary algorithm based on decomposition (IMOEA/D) is proposed to solve the proposed IMOP, which is able to fully preserve the uncertainty inherent in interval‐typed information and allow to obtain an interval‐formed Pareto front for risk‐averse decision‐making. Finally, an IEEE 33‐node active distribution network is utilized for simulation and analysis to confirm the efficacy of the proposed approach.

Sintering temperature is the key factor affecting the structure and performance of tungsten carbide (WC) ceramics. Thus, the effect of sintering temperature on the microstructure and mechanical properties of WC-Ni-Co coarse grain ceramics, obtained from the mixture containing: 60wt.% of ultra-coarse WC, 30 wt.% of fine WC, 7 wt.% of Co and 3wt.% of Ni powders, was analysed. The mechanical properties of WC ceramics did not change much when the sintering temperature was varied between 1410 and 1430 °C and the comprehensive performances of the ceramics were the best in this temperature range. In order to confirm that the coarse grain WC-Ni-Co ceramics can be applicable for harsh environments, it was compared with the standard WC-Co ceramics of the same grain size, and the reasons and mechanisms for the differences in microstructure and properties between the two ceramics were tested and analysed. The study shows that the average grain size of two ceramics does not differ much, and there are no decarburisation, graphite-phase and other impurity phases inside the ceramics. In addition, the difference in the mechanical properties is also small. However, the addition of Ni effectively improves the corrosion resistance of the WC-Co ceramics. Therefore, WC-Ni-Co can replace WC-Co ceramics as shield cutting tool material with the same grain size.

Abstract Infection after anterior cruciate ligament reconstruction (ACLR) is a rare and catastrophic postoperative complication. The aims of this study were to investigate the diagnostic, treatment and rehabilitation measures for postoperative infection following after ACLR. A retrospective study was conducted on 1500 patients who underwent ACLR between January 2011 and January 2022. Twenty patients who met the criteria for summarizing the incidence patterns and treatment experiences were selected for a complete investigation of their diagnostic, therapeutic, and rehabilitation processes, as well as outpatient follow-up results. Among the 20 patients who developed postoperative infections, Staphylococcus aureus was the main pathogen (80%). The clinical manifestations mainly included fever (80%) and knee joint pain (100%). Laboratory tests demonstrated that C-reactive protein (CRP) levels were greater than 50 mmol/L in fifteen patients (75%). All of the patients received intravenous antibiotic therapy. Five patients (25%) of tendon socket infection were treated with continuous negative pressure suction irrigation, whereas the other fifteen patients with intra-articular infection were treated with arthroscopic debridement and continuous flushing. The Lysholm score of the affected knee was compared before treatment and 6 months after treatment, and the difference was statistically significant (t = 20.78, P

In order to explore the effectiveness of the laboratory’s self-developed equipment - horizontal box cage stacked peanut pods room temperature ventilation drying equipment, this study used this equipment to conduct drying experiments on newly harvested peanut pods. The research focused on analyzing the drying rate of peanuts, changes in temperature and humidity within the pile, and energy consumption, and the results were then compared with natural sun drying and similar drying equipment. The research has found that under the same weather conditions (mainly cloudy and rainy weather), the moisture content of peanuts reduced from an initial 43.77% to below 10% within 9 days with a horizontal box cage stacked peanut pods room temperature ventilation drying equipment. The drying rate was 43% higher than that of natural drying. The drying energy efficiency of peanut pods was 2.64×106 J/kg, and the moisture content of the inner and outer layers of the stacked peanut pods decreased uniformly. This study has demonstrated that the horizontal box cage stacked peanut pods drying equipment can be used for the emergency drying of newly harvested peanut pods.

Background: Mounting evidence underscores the importance of cell communication within the tumor microenvironment, which is pivotal in tumor proliferation, invasion, and metastasis. Exosomes play a crucial role in cell-to-cell communication. Although single-cell RNA sequencing (scRNA-seq) provides insights into individual cell transcriptional characteristics, it falls short of comprehensively capturing exosome-mediated intercellular communication. Method: We analyzed Pancreatic Ductal Adenocarcinoma (PDAC) tissues, separating supernatant and precipitate for exosome purification and single-cell nucleus suspension. We then constructed Single-nucleus RNA sequencing (snRNA-seq) and small RNA-seq libraries from these components. Our bioinformatic analysis integrated these sequences with ligand-receptor analysis and public miRNA data to map the cell communication network. Results: We established intercellular communication networks using bioinformatic analysis to track exosome miRNA effects and ligand-receptor pairs. Significantly, hsa-miR-1293 emerged as a prognostic biomarker for pancreatic cancer, linked to immune evasion, increased myeloid-derived suppressor cells, and poorer prognosis. Targeting this miRNA may enhance anti-tumor immunity and improve outcomes. Conclusion: Our study offers a novel approach to constructing intercellular communication networks using snRNA-seq and exosome-small RNA sequencing. By integrating miRNA tracing with ligand-receptor analysis, we illuminate the complex interactions in the pancreatic cancer microenvironment, highlighting the pivotal role of miRNAs and identifying potential biomarkers and therapeutic targets.

[Objective] Collaborative governance is increasingly important in coping with complex grassland resource and environmental problems under dynamic changes, but the effectiveness of governance also depends partly on the fit between the governing and governed systems, thus there is a need to embed a fit perspective for advancing the scientific understanding of the formation mechanism of collaborative governance network. [Methods] Based on the first-hand data from surveys conducted in 2020 and 2022 at Yangrang Village, Gonghe County, Qinghai Province, we constructed the social-ecological network of herders and rangeland using multilevel network and minimum building block methods, and further empirically examined the role of structural, actor attribute, covariate, and fit effects in the formation of collaborative governance network among herders using the multilevel exponential random graph model based on the description of the basic characteristics of the network. [Results] (1) The collaborative network is characterized by low density and high centralization, and each herder has two collaborative ties on average. (2) Among the structural effects, only ties closure promotes the formation of collaborative network, i.e., collaborative ties are more likely to be established between herders who share a common collaborative partner. (3) In the actor attribute effects, the activity effect is stronger than the homophily effect. For the former, social status, years of education and managed pastureland area all have a positive effect on the formation of collaborative ties; for the latter, collaborative ties are more likely to be established between herders with similar numbers of livestock. (4) Affective network has an entraining effect on the establishment of collaborative network, suggesting that collaborative ties are more likely to be established between herders with kinship or close blood ties. (5) Among the ecological fit effects, only sharing fit has a significant effect on the formation of collaborative network. [Conclusion] There is still much room for improvement in the collaborative governance of rangeland resources for herders. It is desirable to promote the establishment of collaboration among herders with similar capabilities and resources while letting self-organization and affective dependence play a role, and to make full use of the path of resource sharing to cultivate and develop collaborative governance. In addition, awareness and understanding of the ecological changes in grasslands and ecological linkages of pastures should be strengthened, and herders should be guided and encouraged to collaborate in solving the problem related to scale fit, in order to help herders break through path dependence and enhance the pathways and effectiveness of collaborative governance.

Colletotrichum species can function as plant pathogens, saprobes or endophytes on a wide variety of plant hosts and are considered amongst the ten most significant genera of plant pathogens globally. China contributes almost half the walnut production in the world. However, Colletotrichum species occurring on walnut remain largely unresolved in China. To explore the Colletotrichum species found on walnut in China, 470 walnut fruit or leaf samples with anthracnose were collected from 14 main walnut-producing regions across seven provinces. A total of 165 Colletotrichum strains were isolated from these samples. The Colletotrichum isolates were identified, based on morphological characteristics and sequence analyses of ACT, CHS-1, GAPDH, ITS and TUB2. Twelve species, including 11 known Colletotrichum species (C. boninense, C. citrulli, C. fioriniae, C. fructicola, C. godetiae, C. juglandicola, C. karsti, C. mengyinense, C. pandanicola, C. peakense and C. siamense) and a novel species (C. chinensis sp. nov.) were identified. The species distribution revealed regional prevalence as follows: C. mengyinense was the most dominant species in Gansu, C. mengyinense and C. siamense in Shandong, C. chinensis in Beijing, C. pandanicola in Shaanxi and C. godetiae in Yunnan. Colletotrichum siamense was the sole species isolated in Sichuan and Xinjiang Provinces. Koch’s postulates were fulfilled, demonstrating that all 12 species cause anthracnose on walnut. This is the first report of C. boninense, C. citrulli and C. karsti as pathogens of walnut anthracnose worldwide.

Abstract Anaplastic thyroid carcinoma (ATC) is a highly aggressive human malignancy without effective treatment. Yes-associated protein (YAP) is a critical effector of the Hippo pathway, which is essential in thyroid carcinogenesis. However, the underlying mechanisms of aberrant YAP expression in ATC are not completely understood. Ubiquitylation-related enzyme siRNA screening identified the ubiquitin protein ligase E3 component n-recognin 1 (UBR1) as a stabilizer of YAP in ATC cells. UBR1 deficiency reduced YAP protein levels and its target gene expression. UBR1 directly interacted with YAP and promoted its monoubiquitylation, competitively suppressing its polyubiquitylation and resulting in extended protein half-life. UBR1 depletion reduced ATC cell proliferation and migration in vitro. Xenograft tumor studies also suggested that UBR1 knockdown suppressed ATC cell growth in vivo. Furthermore, exogenous YAP expression partially reversed the inhibitive effects of UBR1 depletion on ATC cell proliferation and migration. Our studies demonstrated that UBR1 directly interacts with YAP and stabilized it in a monoubiquitylation-dependent manner, consequently promoting ATC tumorigenesis, suggesting that UBR1 might be a potentially therapeutic target for ATC treatment.

Objective: This study aimed to establish a hollow fiber ligand fishing method for screening γ- Aminobutyrate transaminase (GABA-T) inhibitory component from the volatile oil of Acorus tatarinowii. Methods: Based on optimizing the enzyme assisted extraction process of volatile oil from A. tatarinowii using response surface methodology, GABA-T solution was injected into the hollow fiber lumen and used as a "bait" to fish out the potential active components in A. tatarinowii volatile oil, and its GABA-T inhibitory activity was verified. Results: The results showed that the optimum extraction conditions of volatile oil from A. tatarinowii were as follows: cellulase content 3 165 U/g, enzymolysis time 1.8 h, enzymolysis temperature 45 ℃, and the yield of volatile oil from A. tatarinowii was 2.56%. Finally, 51 compounds were identified, mainly including olefins, alcohols, ethers, ketones, phenols, acids, and other compounds. 3 mg/mL of GABA-T solution was injected into the cavity of the U-shaped hollow fiber tube, incubated for 160 min, sealed, and placed in the volatile oil of A. tatarinowii for ultrasonic (60 kHz) fishing for 20 min, and then analyzed with LCMS-IT-TOF system. Successfully filtered out α-Asarone has a concentration-dependent inhibitory effect on GABA-T activity, with an IC50 of 57.9 μg/mL. Conclusion: The established hollow fiber ligand fishing method is stable, feasible, and easy to operate.

Abstract Our research endeavors are directed towards unraveling the stem cell characteristics of lower-grade glioma patients, with the ultimate goal of formulating personalized treatment strategies. We computed enrichment stemness scores and performed consensus clustering to categorize phenotypes. Subsequently, we constructed a prognostic risk model using weighted gene correlation network analysis (WGCNA), random survival forest regression analysis as well as full subset regression analysis. To validate the expression differences of key genes, we employed experimental methods such as quantitative Polymerase Chain Reaction (qPCR) and assessed cell line proliferation, migration, and invasion. Three subtypes were assigned to patients diagnosed with LGG. Notably, Cluster 2 (C2), exhibiting the poorest survival outcomes, manifested characteristics indicative of the subtype characterized by immunosuppression. This was marked by elevated levels of M1 macrophages, activated mast cells, along with higher immune and stromal scores. Four hub genes—CDCA8, ORC1, DLGAP5, and SMC4—were identified and validated through cell experiments and qPCR. Subsequently, these validated genes were utilized to construct a stemness risk signature. Which revealed that Lower-Grade Glioma (LGG) patients with lower scores were more inclined to demonstrate favorable responses to immune therapy. Our study illuminates the stemness characteristics of gliomas, which lays the foundation for developing therapeutic approaches targeting CSCs and enhancing the efficacy of current immunotherapies. By identifying the stemness subtype and its correlation with prognosis and TME patterns in glioma patients, we aim to advance the development of personalized treatments, enhancing the ability to predict and improve overall patient prognosis.

Factor XI deficiency is a rare inherited coagulation disorder with an estimated prevalence of affecting 1 in 1 million. It is characterized by mild and variable bleeding phenotypes, including bruises, nosebleeds, hematuria, and postpartum hemorrhage. It can be caused by either allelic or biallelic variants in coagulation factor XI (F11). Coagulation factor XI is a glycoprotein that circulates in plasma as a non-covalent complex with high-molecular-weight kininogen. It is converted to an active protease, coagulation factor XIa, which participates in blood coagulation as a catalyst. In this study, we recruited a family with Factor XI deficiency and identified two F11 variants using whole-exome sequencing. One (NM_000128.4: c.841C>T, p.Q281X) was a known variant, and the other (NM_000128.4: c.1832T>G, p.V611G) had not been reported. In addition, we compiled the characteristics of known missense variants in coagulation factor XI. Our findings enriched the variant spectrum of Factor XI deficiency and contributed to the genetic counseling and molecular diagnostics of Factor XI deficiency.

Background: The purpose of this study was to investigate the vessel density (VD) of the macular superficial capillary plexus (SCP) and its associated factors in healthy subjects. Methods: This prospective, cross-sectional study enrolled healthy Chinese volunteers. The optical coherence tomography angiography (OCTA) was used to measure the superficial VD in macula. A generalized estimation equation (GEE) model was used to analyze the ocular and systemic associated factors. Results: A total of 516 eyes of 262 healthy subjects were included (mean age 38.59 ± 21.03 years). The total VD of macular SCP was 16.85 ± 2.28 mm−1. The VD in the inner ring and outer ring were significantly higher than that in the central ring, with the density being highest in nasal quadrant and lowest in the superior quadrant. After adjusting the ocular and systemic factors, age (β=-0.0085, P = 0.0122) and SSI (β=1.3261, P < 0.001) were significantly associated with total VD of the macular SCP. Conclusions: Among the healthy Chinese subjects included in the study, the mean total VD of macular SCP was 16.85 ± 2.28mm-1. The macular superficial capillary density was positively associated with age and SSI. Further studies are still required to better understand the change of macular VD in aging and other pathological conditions.

This study examines the link between genuine earnings management and management's integrity commitment using data from A-share listed firms on the Shanghai and Shenzhen stock exchanges (2007–2021). Findings indicate that following genuine earnings management, management tends to emphasize integrity in the MD&A section of annual reports, suggesting moral camouflage in response to negative moral emotions. This behavior is more pronounced with higher information asymmetry between management and investors, amplifying the tendency towards moral camouflage. Further analysis shows that post-earnings management, there is no significant increase in charitable contributions or CSR performance, and agency costs remain high, underscoring a preference for moral camouflage over moral purity. Additionally, management's integrity commitment does not affect analysts' future market valuations or reduce the likelihood of regulatory inquiries. The study also finds that the relationship between earnings management and integrity commitment strengthens under increased moral pressure. This research provides theoretical insights into executive behavior driven by negative moral emotions and offers practical implications for investors, auditors, and regulators.

Abstract Aqueous zinc‐ion batteries have been regarded as the most potential candidate to substitute lithium‐ion batteries. However, many serious challenges such as suppressing zinc dendrite growth and undesirable reactions, and achieving fully accepted mechanism also have not been solved. Herein, the commensal composite microspheres with α‐MnO2 nano‐wires and carbon nanotubes were achieved and could effectively suppress ZnSO4·3Zn(OH)2·nH2O rampant crystallization. The electrode assembled with the microspheres delivered a high initial capacity at a current density of 0.05 A g−1 and maintained a significantly prominent capacity retention of 88% over 2500 cycles. Furthermore, a novel energy‐storage mechanism, in which multivalent manganese oxides play a synergistic effect, was comprehensively investigated by the quantitative and qualitative analysis for ZnSO4·3Zn(OH)2·nH2O. The capacity contribution of multivalent manganese oxides and the crystal structure dissection in the transformed processes were completely identified. Therefore, our research could provide a novel strategy for designing improved electrode structure and a comprehensive understanding of the energy storage mechanism of α‐MnO2 cathodes.

Abstract The risk for suffering immune checkpoint inhibitors (ICIs)‐associated myocarditis increases in patients with pre‐existing conditions and the mechanisms remain to be clarified. Spatial transcriptomics, single‐cell RNA sequencing, and flow cytometry are used to decipher how anti‐cytotoxic T lymphocyte antigen‐4 m2a antibody (anti‐CTLA‐4 m2a antibody) aggravated cardiac injury in experimental autoimmune myocarditis (EAM) mice. It is found that anti‐CTLA‐4 m2a antibody increases cardiac fibroblast‐derived C‐X‐C motif chemokine ligand 1 (Cxcl1), which promots neutrophil infiltration to the myocarditic zones (MZs) of EAM mice via enhanced Cxcl1‐Cxcr2 chemotaxis. It is identified that the C–C motif chemokine ligand 5 (Ccl5)‐neutrophil subpopulation is responsible for high activity of cytokine production, adaptive immune response, NF‐κB signaling, and cellular response to interferon‐gamma and that the Ccl5‐neutrophil subpopulation and its‐associated proinflammatory cytokines/chemokines promoted macrophage (Mφ) polarization to M1 Mφ. These altered infiltrating landscape and phenotypic switch of immune cells, and proinflammatory factors synergistically aggravated anti‐CTLA‐4 m2a antibody‐induced cardiac injury in EAM mice. Neutralizing neutrophils, Cxcl1, and applying Cxcr2 antagonist dramatically alleviates anti‐CTLA‐4 m2a antibody‐induced leukocyte infiltration, cardiac fibrosis, and dysfunction. It is suggested that Ccl5‐neutrophil subpopulation plays a critical role in aggravating anti‐CTLA‐4 m2a antibody‐induced cardiac injury in EAM mice. This data may provide a strategic rational for preventing/curing ICIs‐associated myocarditis.

BackgroundDespite the emerging application of clinical decision support systems (CDSS) in pregnancy care and the proliferation of artificial intelligence (AI) over the last decade, it remains understudied regarding the role of AI in CDSS specialized for pregnancy care. ObjectiveTo identify and synthesize AI-augmented CDSS in pregnancy care, CDSS functionality, AI methodologies, and clinical implementation, we reported a systematic review based on empirical studies that examined AI-augmented CDSS in pregnancy care. MethodsWe retrieved studies that examined AI-augmented CDSS in pregnancy care using database queries involved with titles, abstracts, keywords, and MeSH (Medical Subject Headings) terms. Bibliographic records from their inception to 2022 were retrieved from PubMed/MEDLINE (n=206), Embase (n=101), and ACM Digital Library (n=377), followed by eligibility screening and literature review. The eligibility criteria include empirical studies that (1) developed or tested AI methods, (2) developed or tested CDSS or CDSS components, and (3) focused on pregnancy care. Data of studies used for review and appraisal include title, abstract, keywords, MeSH terms, full text, and supplements. Publications with ancillary information or overlapping outcomes were synthesized as one single study. Reviewers independently reviewed and assessed the quality of selected studies. ResultsWe identified 30 distinct studies of 684 studies from their inception to 2022. Topics of clinical applications covered AI-augmented CDSS from prenatal, early pregnancy, obstetric care, and postpartum care. Topics of CDSS functions include diagnostic support, clinical prediction, therapeutics recommendation, and knowledge base. ConclusionsOur review acknowledged recent advances in CDSS studies including early diagnosis of prenatal abnormalities, cost-effective surveillance, prenatal ultrasound support, and ontology development. To recommend future directions, we also noted key gaps from existing studies, including (1) decision support in current childbirth deliveries without using observational data from consequential fetal or maternal outcomes in future pregnancies; (2) scarcity of studies in identifying several high-profile biases from CDSS, including social determinants of health highlighted by the American College of Obstetricians and Gynecologists; and (3) chasm between internally validated CDSS models, external validity, and clinical implementation.

BackgroundThere is still a lack of clinically validated biomarkers to screen lung cancer patients suitable for programmed dead cell-1 (PD-1)/programmed dead cell receptor-1 (PD-L1) immunotherapy. Detection of PD-L1 expression is invasively operated, and some PD-L1-negative patients can also benefit from immunotherapy; thus, the joint modeling of both deep learning images and clinical features was used to improve the prediction performance of PD-L1 expression in non-small cell lung cancer (NSCLC).MethodsRetrospective collection of 101 patients diagnosed with pathology in our hospital who underwent 18F FDG PET/CT scans, with lung cancer tissue Tumor Propulsion Score (TPS) ≥1% as a positive expression. Lesions were extracted after preprocessing PET/CT images, and using deep learning 3D DenseNet121 to learn lesions in PET, CT, and PET/CT images, 1,024 fully connected features were extracted; clinical features (age, gender, smoking/no smoking history, lesion diameter, lesion volume, maximum standard uptake value of lesions [SUVmax], mean standard uptake value of lesions [SUVmean], total lesion glycolysis [TLG]) were combined for joint modeling based on the structured data Category Embedding Model.ResultsArea under a receiver operating characteristic (ROC) curve (AUC) and accuracy of predicting PD-L1 positive for PET, CT, and PET/CT test groups were 0.814 ± 0.0152, 0.7212 ± 0.0861, and 0.90 ± 0.0605, 0.806 ± 0.023, 0.70 ± 0.074, and 0.950 ± 0.0250, respectively. After joint clinical feature modeling, the AUC and accuracy of predicting PD-L1 positive for PET/CT were 0.96 ± 0.00905 and 0.950 ± 0.0250, respectively.ConclusionThis study combines the features of 18F-FDG PET/CT images with clinical features using deep learning to predict the expression of PD-L1 in NSCLC, suggesting that 18F-FDG PET/CT images can be conducted as biomarkers for PD-L1 expression.

Objective: Though an increased risk of atherosclerosis is associated with anti-CTLA-4 antibody therapy, the underlying mechanisms remain unclear. Methods: C57BL/6 mice were treated with anti-cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) antibody twice a week for 4 weeks, after being injected with AAV8-PCSK9 and fed a Paigen diet (PD). The proportion of aortic plaque and lipid accumulation were assessed using Oil Red O staining, while the morphology of atherosclerotic lesions was analyzed with hematoxylin and eosin staining. Collagen content was evaluated through Picrosirius Red (PSR) staining, while inflammatory cell infiltration was examined with immunofluorescence staining. CD4+ T cells secreting IFN-γ and IL-4, which represent Th1 and Th2 cells respectively, were detected by flow cytometry and real-time PCR. Protein levels of p-IκBα, IκBα, p-p65, and p65 were determined by Western blot. Results: Inhibiting CTLA-4 exacerbated PD-induced plaque progression and promoted CD4+ T cell infiltration in the aortic root. The anti-CTLA-4 antibody promoted CD4+ T cell differentiation toward the Th1 type, as indicated by an increase in the Th1/Th2 ratio. Compared to the anti-IgG group, treatment with anti-CTLA-4 antibody significantly elevated the protein levels of p-IκBα and p-p65, as well as the mRNA levels of TNF-α, IL-6, ICAM-1, and VCAM-1. Inhibiting the NF-κB signaling pathway attenuated the overall pathological phenotype induced by the anti-CTLA-4 antibody treatment. Conclusion: Anti-CTLA-4 treatment promotes the progression of atherosclerosis by activating NF-κB signaling and modulating the Th1/Th2 balance. Our results provide a rationale for preventing and/or treating atherosclerosis accelerated by anti-CTLA-4 antibody therapy in cancer patients.

With the continuous improvement of living standards, people are concerned about not only whether foods are tasty or not, but also the combination of health elements and good flavor. Food flavor components are not only important factors in sensory quality, but also key indicators of the nutritional level of foods. At present, the traditional methods to evaluate and predict food flavor components are time-consuming and labor-intensive, and unable to handle large amounts of data. In contrast, machine learning (ML), the core of artificial intelligence, has incomparable advantages over traditional analytical techniques in distinguishing differences and finding commonalities, and has found good application in the field of food flavor analysis. In this context, this paper focuses on the current research status of ML in the field of food flavor, and introduces the principles and advantages of commonly used ML methods, as well as their latest applications and prospects in food flavor prediction and regulation. It also focuses on the advantages and future trends of modern intelligent sensory evaluation techniques combined with ML in the field of food flavor analysis, with a view to providing new ideas and theoretical foundations for food flavor analysis and prediction.

Abstract Aspirin is widely used for both primary and secondary prevention of panvascular diseases, such as stroke and coronary heart disease (CHD). The optimal balance between reducing panvascular disease events and the potential increase in bleeding risk remains unclear. This study aimed to develop a predictive model specifically designed to assess bleeding risk in individuals using aspirin. A total of 58,415 individuals treated with aspirin were included in this study. Detailed data regarding patient demographics, clinical characteristics, comorbidities, medical history, and laboratory test results were collected from the Affiliated Dongyang Hospital of Wenzhou Medical University. The patients were randomly divided into two groups at a ratio of 7:3. The larger group was used for model development, while the smaller group was used for internal validation. To develop the prediction model, we employed least absolute shrinkage and selection operator (LASSO) regression followed by multivariate logistic regression. The performance of the model was assessed through metrics such as the area under the receiver operating characteristic (ROC) curve (AUC), calibration curves, and decision curve analysis (DCA). The LASSO-derived model employed in this study incorporated six variables, namely, sex, operation, previous bleeding, hemoglobin, platelet count, and cerebral infarction. It demonstrated excellent performance at predicting bleeding risk among aspirin users, with a high AUC of 0.866 (95% CI 0.857–0.874) in the training dataset and 0.861 (95% CI 0.848–0.875) in the test dataset. At a cutoff value of 0.047, the model achieved moderate sensitivity (83.0%) and specificity (73.9%). The calibration curve analysis revealed that the nomogram closely approximated the ideal curve, indicating good calibration. The DCA curve demonstrated a favorable clinical net benefit associated with the nomogram model. Our developed LASSO-derived predictive model has potential as an alternative tool for predicting bleeding in clinical settings.

Moral education is an important channel to shape national identity, that is, the identity, commonality and "sense of us" of citizens, and school moral education has always been an important theme of the Party and national education. Since the new era, the integration of moral education has become higher, wider and deeper. In terms of height, the integration of moral education in the new era is proposed by the Party and the country to cultivate a new generation for the great rejuvenation of the Chinese nation. In terms of breadth, it is designed from the perspective of the whole society, all the people, the entire process and all-round participation. In terms of depth, it is an in-depth exploration of moral education on the basis of new education and teaching research results and the achievements of socialism with Chinese characteristics, to greatly promote and deepen the understanding of the laws of moral education. In the future, the integration of moral education should, on the basis of existing achievements, adhere to the system concept, face problems directly, abide by integrity and innovation, and further work hard on management mechanism, textbook construction and teacher teaching.

Developing lithium-ion batteries (LIBs) with higher energy densities has been necessary in recent years to satisfy the increasing requirements of the energy storage and conversion fields. The limited performance of LIBs stems from their low available capacities and cycling stability. As one of the most important components of LIBs, the cathode material plays an essential role in determining the energy density and cycling stability of LIBs. Among the cathode materials, lithium-rich manganese-based materials are considered to be promising cathode materials for the next generation. This is due to their high specific capacity (theoretical capacity > 250 mA·h·g−1 for 1 Li+ extraction and approximately 378 mA·h·g−1 for 1.2 Li+ extractions), high energy density (approximately 900 W·h·kg−1 vs Li metal), and low cost. Despite these advantages, one major weakness of xLi2MnO3·(1–x) LiMO2 is its intrinsically poor rate capability. This has been recently verified to be associated with the retardation of mass transport of the rearranged surface after activating Li2MnO3 at >4.5 V charge. This rearrangement causes a large capacity loss. In addition, these materials exhibit fragile surface properties at high potentials, erosion from the electrolytes, and dissolution of transition metal ions. In addition, the high working voltage not only ensures high energy density but also triggers a side reaction between the electrode material and the electrolyte. This leads to problems such as transition metal dissolution, surface cracks, and laminated structure collapse during the cycling process, limiting the material’s commercial application. Surface coating can effectively alleviate the side reactions between the electrode and electrolyte, suppress the dissolution of transition metals, and thus improve the material’s coulombic efficiency and cycling stability during cycling. Until now, there have been many reports on the surface coating modification of Li-rich manganese-based materials; however, there are few review reports in this field. This paper summarizes the structure and characteristics of Li-rich manganese-based materials and their problems during the cycle process. Furthermore, it introduces the latest progress in the coating modification of Li-rich manganese-based cathode materials and systematically describes the application of different coating materials, such as electrochemically active materials, non-electrochemically active materials, and conductive polymers. Moreover, this study addresses the coating methods of single-layer coating, double-layer composite coating, and in situ coating and further analyzes the failure and enhancement mechanisms of cycling stability of the modification methods and coatings. Finally, a future development direction for Li1.2Mn0.54Ni0.13Co0.13O2 (LMNC) materials and modification methods is envisioned. This result provides a reference for the practical application of Li-rich cathode materials.

Mosquito-borne diseases are threatening half of the world's population. To prevent the spread of malaria, dengue fever, or other mosquito-borne diseases, a new disease control strategy is to reduce or eradicate the wild mosquito population by releasing sterile mosquitoes. To study the effects of sterile insect technique on mosquito populations, we developed a mathematical model of constant release of sterile Aedes aegypti mosquitoes with strong and weak Allee effect and considered interspecific competition with Anopheles mosquitoes. We calculated multiple release thresholds and investigated the dynamical behavior of this model. In order to get closer to reality, an impulsive differential equation model was also introduced to study mosquito suppression dynamics under the strategy of releasing $ c $ sterile male mosquitoes at each interval time $ T $. Finally, the relationship between the releasing amount or the waiting period and the number of days required to suppress mosquitoes was illustrated by numerical simulations.

The longitudinal dispersion of the projectile in shooting tests of two-dimensional trajectory corrections fused with fixed canards is extremely large that it sometimes exceeds the correction ability of the correction fuse actuator. The impact point easily deviates from the target, and thus the correction result cannot be readily evaluated. However, the cost of shooting tests is considerably high to conduct many tests for data collection. To address this issue, this study proposes an aiming method for shooting tests based on small sample size. The proposed method uses the Bootstrap method to expand the test data; repeatedly iterates and corrects the position of the simulated theoretical impact points through an improved compatibility test method; and dynamically adjusts the weight of the prior distribution of simulation results based on Kullback–Leibler divergence, which to some extent avoids the real data being ''submerged'' by the simulation data and achieves the fusion Bayesian estimation of the dispersion center. The experimental results show that when the simulation accuracy is sufficiently high, the proposed method yields a smaller mean-square deviation in estimating the dispersion center and higher shooting accuracy than those of the three comparison methods, which is more conducive to reflecting the effect of the control algorithm and facilitating test personnel to iterate their proposed structures and algorithms.; in addition, this study provides a knowledge base for further comprehensive studies in the future.

Abstract Background Type 2 diabetes mellitus (T2DM) causes severe bone loss after tooth extraction as a hyperglycemic environment causes aberrant bone homeostasis. Artesunate (ART) is known to possess anti-inflammation and osteogenic properties. However, its osteogenesis property in alveolar bone remains unclear. This study aimed to explore the osteogenic and immunoregulatory effects of artesunate-loaded thermosensitive chitosan hydrogel (ART-loaded TCH) on maxilla tooth extraction in T2DM rats. Methods T2DM rats were induced by a high-fat diet and streptozotocin. Different concentrations of ART-loaded TCH were applied in tooth extraction sockets. Bone loss and the expression of osteogenic regulatory factors (OPG, ALP, RANK) were evaluated. The immunoregulatory effects of ART-loaded TCH were observed through detecting the infiltration of T lymphocytes and their cytokines. The underlying mechanisms were explored. Results Results showed that the 150 mg/ml ART-loaded TCH group significantly ameliorated maxilla bone height and bone mineral density when compared with the T2DM group (p

To compare the volatile flavor characteristics of red jujube from different origins, volatile aroma components of jujube fruit from five origins (Xinzheng, Lingbao, Yulin, Hotan and Dezhou) were analyzed by headspace solid-phase microextraction combined with gas chromatography mass spectrometry. The results showed that a total of 51 compounds were identified, among which the most volatile compounds were contained in Xinjiang Hotan jujube. Combined with multivariate statistical analysis, the differences in the overall volatile flavor substances of red jujube from different origins could be well distinguished. Under the conditions of satisfying the variable importance in projection>1 and P

Background: To investigate the visual acuity outcome and choroid thickness (CT) change after intravitreal ranibizumab in highly myopic eyes with or without dome-shaped macula (DSM) in Chinese patients. Methods: This retrospective, observative study included 80 treatment-naive eyes (80 patients), which received ranibizumab according to the 1+PRN protocol. The best corrective visual acuity (BCVA) and CT change were compared between eyes with or without DSM. Results: There was no significant difference between eyes with or without DSM in BCVA and central macular thickness (CMT). The recurrent rate was not different between the two groups during the first year of treatment. The CT was significantly thinner in eyes with DSM than in eyes without DSM before treatment (median 40.00um versus 71.00um), at 1 month after treatment (median 31.00um versus 65.50um), and in the last follow up (median, 32.00um versus 65.00um) (p = 0.0101). Axial length (AL) was longer in eyes with DSM than those without DSM (median, 29.17 mm versus 28.10 mm) before treatment, and in the last follow up (median, 29.44 mm versus 28.20 mm) (p = 0.0055). The CT was significantly correlated with AL (p < 0.0001). Conclusions: No difference was found in visual outcome between eyes with or without DSM. The visual acuity significantly improved at 1 month after ranibizumab injection and it was recovery sooner in extrafoveal choroidal neovascularization (CNV) group than in subfoveal CNV group. The CT was thinner in eyes with DSM, which was significantly correlated with AL.

PurposeThe learning subjective well-being of high school students has significant value for their academic achievement and future life development. A growth mindset is one of the key factors affecting the learning subjective well-being of high school students. However, research on the mechanism by which a growth mindset affects learning subjective well-being is still relatively limited. Therefore, the study aims to investigate the impact of a growth mindset on the learning subjective well-being of high school students, as well as the role that achievement motivation and grit play as serial mediators in this relationship.MethodsThis study employed a convenience sampling method to select 708 high school students from Chinese public high schools as participants. The research utilized the Growth Mindset Scale, Achievement Motivation Scale, Grit Scale, and the Learning Subjective Well-being Questionnaire for High School Students to collect data. All data were analyzed using SPSS 26.0, employing Model 6 from Hayes’ SPSS PROCESS macro to test the serial mediation model.ResultsOur results found that (1) high school students’ growth mindset positively predicted their learning subjective well-being. (2) Achievement motivation played a mediating role between a growth mindset and learning subjective well-being among high school students. (3) Grit acted as a mediator between learning subjective well-being and growth mindset among high school students. (4) Achievement motivation and grit served as serial mediators between a growth mindset and learning subjective well-being among high school students.ConclusionA growth mindset can influence the learning subjective well-being of high school students through achievement motivation and grit. Educators can enhance the learning subjective well-being of high school students by implementing intervention strategies that foster a growth mindset, achievement motivation, and grit.

Currently, chemotherapy remains occupying a pivotal place in the treatment of pancreatic ductal adenocarcinoma (PDAC). Nonetheless, the emergence of drug resistance in recent years has limited the clinical efficacy of chemotherapeutic agents, especially gemcitabine (GEM). Through bioinformatics analysis, AT-rich Interactive Domain-containing Protein 3A (ARID3A), one of transcription factors, is discovered to possibly participate in this progress. This study thoroughly investigates the potential role of ARID3A in the malignant progression and GEM chemoresistance of PDAC and explores the underlying mechanisms. The results indicate that ARID3A knockdown suppresses tumor development and enhances the sensitivity of PDAC cells to GEM in vitro and vivo. Mechanically, CUT&Tag profiling sequencing, RNA‐sequencing and functional studies demonstrates that decreased ARID3A expression alleviates the transcriptional inhibition of phosphatase and tensin homolog (PTEN), consequently leading to glutathione peroxidase 4 (GPX4) depletion and increased lipid peroxidation levels. Activated ferroptosis induced by the inhibition of GPX4 subsequently restricts tumor progression and reduces GEM resistance in PDAC. This research identifies the ferroptosis regulatory pathway of ARID3A-PTEN-GPX4 axis and reveals its critical role in driving the progression and chemoresistance of pancreatic cancer. Notably, both inhibition of ARID3A and enhancement of ferroptosis can increase chemosensitivity to GEM, which offers a promising opportunity for developing therapeutic strategies to combat acquired chemotherapy resistance in pancreatic cancer.

Summary: HIV-1 hijacks host proteins involved in membrane trafficking, endocytosis, and autophagy that are critical for virus replication. Molecular details are lacking but are essential to inform on the development of alternative antiviral strategies. Despite their potential as clinical targets, only a few membrane trafficking proteins have been functionally characterized in HIV-1 replication. To further elucidate roles in HIV-1 replication, we performed a CRISPR-Cas9 screen on 140 membrane trafficking proteins. We identified phosphatidylinositol-binding clathrin assembly protein (PICALM) that influences not only infection dynamics but also CD4+ SupT1 biology. The knockout (KO) of PICALM inhibited viral entry. In CD4+ SupT1 T cells, KO cells exhibited defects in intracellular trafficking and increased abundance of intracellular Gag and significant alterations in autophagy, immune checkpoint PD-1 levels, and differentiation markers. Thus, PICALM modulates a variety of pathways that ultimately affect HIV-1 replication, underscoring the potential of PICALM as a future target to control HIV-1.

Summary: Non-apoptotic regulated cell death (RCD) of tumor cells profoundly affects tumor progression and plays critical roles in determining response to immune checkpoint inhibitors (ICIs). Prognosis-distinctive HCC subtypes were identified by consensus cluster analysis based on the expressions of 507 non-apoptotic RCD genes obtained from databases and literature. Meanwhile, a set of bioinformatic tools was integrated to analyze the differences of the tumor immune microenvironment infiltration, genetic mutation, copy number variation, and epigenetics alternations within two subtypes. Finally, a non-apoptotic RCDRS signature was constructed and its reliability was evaluated in HCC patients’ tissues. The high-RCDRS HCC subgroup showed a significantly lower overall survival and less sensitivity to ICIs compared to low-RCDRS subgroup, but higher sensitivity to cisplatin, paclitaxel, and sorafenib. Overall, we established an RCDRS panel consisting of four non-apoptotic RCD genes, which might be a promising predictor for evaluating HCC prognosis, guiding therapeutic decision-making, and ultimately improving patient outcomes.

Visual Dialog is a multi-modal task involving both computer vision and dialog systems. The goal is to answer multiple questions in conversation style, given an image as the context. Neural networks with attention modules are widely used for this task, because of their effectiveness in reasoning the relevance between the texts and images. In this work, we study how to further improve the quality of such reasoning, which is an open challenge. Our baseline is the Recursive Visual Attention (RVA) model, which refines the vision-text attention by iteratively visiting the dialog history. Building on top of that, we propose to improve the attention mechanism with contrastive learning. We train a Matching-Aware Attention Kernel (MAAK) by aligning the deep feature embeddings of an image and its caption, to provide better attention scores. Experiments show consistent improvements from MAAK. In addition, we study the effect of using Multimodal Compact Bilinear (MCB) pooling as a three-way feature fusion for the visual, textual and dialog history embeddings. We analyze the performance of both methods in the discussion section, and propose further ideas to resolve current limitations.

In the context of large-scale grid connection of new energy, short-term load forecasting is a vital and challenging task for power system to balance supply and demand. To effectively improve the forecasting accuracy, a new load forecasting method is proposed aiming to mine the characteristics of load data and study the application of artificial intelligence algorithms. In this paper, the seasonal and trend decomposition using loess (STL) method is firstly applied to decompose the load data into the trend, seasonal and residual components and the residual component with the highest complexity is further decomposed by the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) approach. Secondly, in order to reduce the number of components, the improved hierarchical clustering technique is proposed to cluster all intrinsic mode functions (IMFs) obtained by CEEMDAN into high-frequency and low-frequency components. Then, different network models are trained to get the prediction results for different components, and the total load prediction value is achieved by stacking all of them. Finally, the national demand dataset of Great Britain in 2021–2022 is used to conduct the ablation and comparative experiments. The mean absolute percentage error (MAPE) and the root mean square error (RMSE) of the proposed method are 2.064% and 724.01 MW, respectively, which verified the effectiveness and advancement of the proposed method.

In order to reveal the stress distribution law of a bottom of the ultra-short flexspline under load, a theoretical calculation method of the load equivalent stress of the bottom of the flexspline is proposed. The flexural and symmetrical deformation model of flexural cylinder under the action of wave generator is established, and the flexural normal stress and shear stress caused by assembly deformation and shear stress under the load torque are solved. Based on the Mises yield criterion, the theoretical expression of the load equivalent stress at the bottom of the flexspline is obtained. The finite element model is established and the theoretical solutions of the assembly and load stress at the bottom of the flexspline are verified numerically. The results show that the bending radial normal stress is the main stress of the assembly stress at the bottom of the flexspline cylinder; the maximum shear stress at the bottom of the flexspline under the rated torque is at 45°; with the increase of the load torque, the maximum shear stress gradually passes to the fixed end, and the equivalent stress is evenly distributed at the fixed end. The shear stress at the maximum instantaneous allowable torque is the principal stress of the equivalent stress at the bottom of the flexspline, which provides guidance for the strength design of the bottom of the flexspline.

Abstract Background Brucellosis, developing complications including arthritis, spondylitis, sacroiliitis, and osteomyelitis, is one of the most common zoonotic diseases in the current world which causes economic losses to the livestock industry and is a great public health concern. Brucella melitensis are the main pathogen of brucellosis epidemics in China, most of which are located in northern China. However, there is limited knowledge about the epidemiology of osteoarthritis-associated brucellosis. This study was aimed to reveal the prevalence of osteoarthritis-associated brucellosis in Inner Mongolia and also to investigate the molecular characteristics of B. melitensis isolates. Methods and results In 2018, the osteoarthritis symptoms of brucellosis in the Brucellosis department of a hospital in Inner Mongolia were investigated. Twenty osteoarthritis-associated B. melitensis strains, isolated from the inpatients in Inner Mongolia during 2013–2017, were subjected to whole genome sequencing. The multilocus sequence type (MLST) and core genome SNP (cgSNP) analysis were conducted to detect molecular epidemiological characteristics. The incidence of brucellosis osteoarthritis symptoms in males (85/120, 70.8%) was significantly higher than that in females (35/120, 29.2%), and the age of patients was concentrated between 41 and 60 years old. In silico analyses indicated ST8 was the prevalent sequence type and the transmission of osteoarthritis-associated B. melitensis among different geographical areas. All strains carry virulence genes, including cgs, lpsA, manCoAg, pgm, pmm, virB4, wbdA and wboA. Conclusion Our study showed the close epidemiologically connection of osteoarthritis-associated B. melitensis strains in northern China. And ST8 was the prevalent sequence type which need our attention.

Abstract Background Metastasis is the leading cause of death among prostate cancer (PCa) patients. Obesity is associated with both PCa-specific and all-cause mortality. High-fat diet (HFD) is a risk factor contributing to obesity. However, the association of HFD with PCa metastasis and its underlying mechanisms are unclear. Methods Tumor xenografts were conducted by intrasplenic injections. The ability of migration or invasion was detected by transwell assay. The expression levels of RPS27 were detected by QRT-PCR and western blot. Results The present study verified the increase in PCa metastasis caused by HFD in mice. Bioinformatics analysis demonstrated increased RPS27 in the experimentally induced PCa in HFD mice, indicating that it is an unfavorable prognostic factor. Intrasplenic injections were used to demonstrate that RPS27 overexpression promotes, while RPS27 knockdown significantly reduces, PCa liver metastasis. Moreover, RPS27 inhibition suppresses the effects of HFD on PCa metastasis. Further mRNA sequencing analysis revealed that RPS27 promotes PCa metastasis by selectively enhancing the expression of various genes. Conclusion Our findings indicate that HFD increases the risk of PCa metastasis by elevating RPS27 expression and, subsequently, the expression of genes involved in PRAD progression. Therefore, RPS27 may serve as a novel target for the diagnosis and treatment of metastatic PCa.

Within the realm of public health, the end-to-end traceability and monitoring of vaccines play an indispensable role in ascertaining the safety and efficacy of vaccines, especially the precise localization of vaccines in the vaccine cold storage. However, challenges such as limited space, dense stacking of boxes, and frequent obstructions in the vaccine cold storage, particularly in Small to Medium Cold Storage (SMCS), pose significant obstacles to effective localizing. Existing vaccine box localizing methods in cold storage, like manual localizing, Radio Frequency Identification (RFID) technology, and traditional visual localizing, struggle with obstructions and inefficiencies, leading to limited accuracy and real-time update capabilities. This paper introduces an innovative solution for vaccine box localization in obstructed environment within SMCS, leveraging computer vision technology. Specifically, to address the challenge of accurately locating vaccine boxes in densely stacked and heavily obstructed SMCS, this paper exploits the strong correlation between the vaccine boxes and workers during the storage process. The vaccine box is indirectly located by focusing on the less numerous and less obstructed cold storage workers. Furthermore, to enhance the tracking accuracy of the workers, the YOLOv5 model was modified, resulting in the development of the Vaccine Cold Storages YOLOV5 (VCS-YOLOv5) model tailored for obstructed environment in SMCS. Additionally, the final location of the vaccine box is determined by a behavior recognition model, identifying instances where the workers’ hands are not in contact with the vaccine box. Extensive experiments confirm that VCS-YOLOv5 sets a new benchmark in vaccine box localization and worker tracking, significantly surpassing the performance of standard models in accuracy and real-time effectiveness.

Stability analysis of underground constructions requires a model study of rock masses’ long-term performance. Creep tests under different stress conditions was conducted on intact granite and granite samples fractured at 30° and 45° angles. The experimental results indicate that the steady creep strain rates of intact and fractured rock present an exponential increase trend with the increase of stress level. A nonlinear creep model is developed based on the experimental results, in which the initial damage caused by fracture together with the damage caused by constant load have been taken into consideration. The fitting analysis results indicated that the model proposed is more accurate at identifying the full creep regions in fractured granite, especially the accelerated stage of creep deformation. The least-square fit error of the proposed creep model is significantly lower than that of Nishihara model by almost an order of magnitude. An analysis of the effects of elastic modulus, viscosity coefficient, and damage factors on fractured rock strain rate and creep strain is conducted. If no consideration is given to the effects of the damage, the proposed nonlinear creep model can degenerate into to the classical Nishihara model.

Long text matching is widely used in various sub-tasks of natural language processing. However, conducting research in this field can be challenging due to excessive redundant and distracting information, the complex semantic context, and the limited availability of high quality public datasets. Existing long text matching methods generally do not fully use the rich local features embedded in text information, and focus more on encoding long text as fixed length vectors to calculate the semantic distance, disregarding the importance of feature interaction in the text matching process. Therefore, the performance of the relevant models needs to be improved. To address these problems, a hierarchical and multiple-perspective interaction network (HMIN) is proposed in this paper. First, the long text is encoded at the word and sentence levels to extract global features, while one-dimensional convolutional neural networks and attention mechanisms are used to focus on important local features in long texts. Second, the different types of features are compared separately using the comparison function, and then, the comparison results are aggregated. Finally, whether long texts are matched is determined in the prediction layer. We have conducted comparative experiments on two datasets, the results show that HMIN has an improvement in accuracy and F1 values compared with the same type of existing algorithms, and the related experimental analysis demonstrates the effectiveness of the proposed method.

Abstract Background Immunotherapy targeting PD-1/PD-L1 has revolutionized the treatment of extensive-stage small cell lung cancer (ES-SCLC). However, clinical trials suggest differential efficacy of anti-PD-1 agents and anti-PD-L1 agents in first-line treatment of ES-SCLC. This retrospective multicenter study aimed to compare the efficacy and safety of anti-PD-1 agents versus anti-PD-L1 agents in first-line treatment of ES-SCLC in real-world practice. Methods Patients with pathologically or cytologically confirmed ES-SCLC treated with platinum plus etoposide combined with anti-PD-1 or PD-L1 agents as first-line treatment in different centers of PLA General Hospital between January 2017 and October 2021 were included for this study. Survival outcomes and safety were compared between patients receiving anti-PD-1 and PD-L1 agents. Results Of the total 154 included patients, 68 received anti-PD-1 agents plus chemotherapy (PD-1 group), and 86 received anti-PD-L1 agents plus chemotherapy (PD-L1 group). Progression-free survival (PFS) and overall survival (OS) in the entire cohort were 7.6 months (95% confidence interval [CI]: 6.5–8.2 months) and 17.4 months (95% CI: 15.3–19.3 months), respectively. Median PFS and OS were comparable between the PD-1 group and PD-L1 group (PFS: 7.6 months vs. 8.3 months, HR = 1.13, 95% CI: 0.79–1.62, p = 0.415; OS: 26.9 months vs. 25.6 months, HR = 0.96, 95% CI: 0.63–1.47, p = 0.859. The objective response rate and disease control rate were comparable between the two groups: 79.4% vs. 79.1% and 92.6% vs. 94.2%, respectively. The 6-month, 12-month, and 18-month PFS and OS rates were slightly higher in the PD-L1 group than in the PD-1 group, while the 24-month PFS rate was slightly higher in the PD-1 group than in the PD-L1 group. Stratified analysis showed that locoregional thoracic radiotherapy and normal lactate dehydrogenase level were independent predictors of better OS in ES-SCLC patients treated with first-line chemotherapy plus ICI. Adverse events were not significantly different between the two groups. Conclusions Anti-PD-1 agents and anti-PD-L1 agents combined with chemotherapy as first-line treatment for ES-SCLC are comparably effective and well tolerated.

Abstract Intratumoral immune status influences tumor therapeutic response, but it remains largely unclear how the status determines therapies for patients with intrahepatic cholangiocarcinoma. Here, we examine the single-cell transcriptional and TCR profiles of 18 tumor tissues pre- and post- therapy of gemcitabine plus oxaliplatin, in combination with lenvatinib and anti-PD1 antibody for intrahepatic cholangiocarcinoma. We find that high CD8 GZMB+ and CD8 proliferating proportions and a low Macro CD5L+ proportion predict good response to the therapy. In patients with a poor response, the CD8 GZMB+ and CD8 proliferating proportions are increased, but the CD8 GZMK+ proportion is decreased after the therapy. Transition of CD8 proliferating and CD8 GZMB+ to CD8 GZMK+ facilitates good response to the therapy, while Macro CD5L+–CD8 GZMB+ crosstalk impairs the response by increasing CTLA4 in CD8 GZMB+. Anti-CTLA4 antibody reverses resistance of the therapy in intrahepatic cholangiocarcinoma. Our data provide a resource for predicting response of the combination therapy and highlight the importance of CD8+T-cell status conversion and exhaustion induced by Macro CD5L+ in influencing the response, suggesting future avenues for cancer treatment optimization.

Abstract In this paper, we construct the multi-state Dirac stars (MSDSs) consisting of two pairs of Dirac fields. The two pairs of Dirac fields are in the ground state and the first excited state, respectively, with opposite spins to ensure that the system possesses spherical symmetry. We discuss the solutions of the MSDSs under synchronized and nonsynchronized frequencies. By varying the ratio of masses between the two sets of Dirac fields, different branches of solutions can be obtained. Furthermore, we analyze the characteristics of the various MSDSs solutions and analyze the relationship between the ADM mass M of the MSDSs and the synchronized and nonsynchronized frequencies. Subsequently, we calculate the binding energy $$E_B$$ E B of the MSDSs and discuss the stability of the solutions. Then, we investigated the solutions of the MSDSs under the single particle condition. Finally, we discuss the feasibility of simulating the dark matter halos using MSDSs.

In recent years, the Internet of Things (IoT) has experienced extensive adoption in industrial environments, healthcare, smart cities, and more, playing a vital role in these domains. Within IoT-based systems, wireless sensor networks (WSNs) have emerged as a crucial method for collecting peripheral environmental data within industries, owing to their self-organizational attributes. Nevertheless, the enormous volume of heterogeneous data from various sensing devices presents many challenges for IoT-enabled WSNs, encompassing high transmission delay times (TD) and excessive battery energy consumption (EC). To address these challenges, it is imperative to prioritize efficiency and optimize energy utilization. Moreover, enhancing energy efficiency within the Industrial Internet of Things (IIoT) realm hinges significantly on factors such as data transmission modes and the allocation of cluster head nodes. Numerous researchers have proposed algorithms to minimize transmission time and energy consumption, specifically focusing on industrial environments. This paper introduces an inventive clustering-based data transmission algorithm for IIoT, LEACH-D, to enhance efficiency. The LEACH-D algorithm improves the transmission task duration while maintaining consistent battery energy consumption. It also seeks to elevate performance in metrics such as average transmission time during the first node death (FND). Numerous experimental results provide strong evidence that the algorithm introduced in this paper has effectively reduced the average transmission time by remarkable percentages: 51.32%, 12.12%, 12.96%, and 5.42%, while simultaneously increasing the number of FND rounds by significant margins: 222.43%, 36.63%, 33.72%, and 7.81%, respectively. These improvements stand in stark contrast to the performance of existing algorithms, including FREE_MODE, LEACH, EE-LEACH, and ETH-LEACH.

Abstract The reniform nematode, Rotylenchulus reniformis, is a sedentary root parasite that poses a significant threat to agricultural production in tropical and subtropical regions worldwide. In 2021–2022, a population of R. reniformis was identified in a melon greenhouse in Jimo District, Qingdao, China. To characterize this population, we employed morphological, morphometric, and molecular methods, which confirmed the identity of the nematodes as R. reniformis. Our investigation revealed that R. reniformis successfully infected the roots of melon plants and laid eggs, which could have led to significant crop damage. This report represents the first documented example of R. reniformis infecting melon plants in China. We evaluated several control strategies to combat this nematode, and our results indicated that soil solarization and the use of fosthiazate or chitooligosaccharide copper in combination with soil solarization were effective measures for managing R. reniformis in a greenhouse setting. In addition, combining soil solarization with chitooligosaccharide copper promoted melon plant growth and increased the relative abundance of microorganisms with biocontrol potential.