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Abstract Background Overall Survival (OS) and Progression-Free Interval (PFI) as survival times have been collected in The Cancer Genome Atlas (TCGA). It is of biomedical interest to consider their dependence in pathway detection and survival prediction. We intend to develop novel methods for integrating PFI as condition based on parametric survival models for identifying pathways associated with OS and predicting OS. Results Based on the framework of conditional probability, we developed a family of frailty-based parametric-models for this purpose, with exponential or Weibull distribution as baseline. We also considered two classes of existing methods with PFI as a covariate. We evaluated the performance of three approaches by analyzing RNA-seq expression data from TCGA for lung squamous cell carcinoma and lung adenocarcinoma (LUNG), brain lower grade glioma and glioblastoma multiforme (GBMLGG), as well as skin cutaneous melanoma (SKCM). Our focus was on fourteen general cancer-related pathways. The 10-fold cross-validation was employed for the evaluation of predictive accuracy. For LUNG, p53 signaling and cell cycle pathways were detected by all approaches. Furthermore, three approaches with the consideration of PFI demonstrated significantly better predictive performance compared to the approaches without the consideration of PFI. For GBMLGG, ten pathways (e.g., Wnt signaling, JAK-STAT signaling, ECM-receptor interaction, etc.) were detected by all approaches. Furthermore, three approaches with the consideration of PFI demonstrated better predictive performance compared to the approaches without the consideration of PFI. For SKCM, p53 signaling pathway was detected only by our Weibull-baseline-based model. And three approaches with the consideration of PFI demonstrated significantly better predictive performance compared to the approaches without the consideration of PFI. Conclusions Based on our study, it is necessary to incorporate PFI into the survival analysis of OS. Furthermore, PFI is a survival-type time, and improved results can be achieved by our conditional-probability-based approach.

Abstract Background Organophosphate flame retardants (OPFRs) are extensively distributed in our environment, prompting concerns about potential health hazards, including lung injuries resulting from OPFR exposure. Methods The present study recruited 125 lung cancer patients, assessing their exposure to 10 OPFR compounds through urine samples. The final analysis comprised 108 participants after excluding those lacking epidermal growth factor receptor (EGFR) status and those with chronic kidney disease. Demographic and clinical characteristics, as well as urinary OPFR concentrations, were compared based on OPFR detection. Spearman correlation was conducted to explore the relationship between OPFR compounds, while logistic regression was used to identify OPFR compounds associated with EGFR mutation. Results The study revealed widespread OPFR exposure among lung cancer patients, with an overall detection frequency of 99.07%. Tris(2‐butoxyethyl) phosphate (TBEP) exhibited a strong correlation to its metabolite bis(2‐butoxyethyl) phosphate (r = 0.88, p

Ultra-wideband through-wall radar, leveraging its ability to penetrate walls, can be used together with Multiple-Input Multiple-Output (MIMO) technology to image hidden targets behind walls. This approach provides rich information for detecting and locating people within buildings. This paper introduces a closed-loop interferometric calibration method based on a multitransmitter multireceiver ultrawideband wall-penetrating radar system in the Frequency Modulated Continuous Wave (FMCW) regime. This method aims to correct scattering issues caused by internal system errors. The presence of walls causes the target imaging position to deviate from the real position. To address this, this paper derives a three-Dimensional (3D) wall compensation algorithm jointing channels and pixel points. Then, a fast refocusing algorithm is proposed based on the geometric properties of the imaging area. The first step involves removing the influence of walls on delay time and determining the presence of the target. Subsequently, in view of the geometric properties of the region, a spherical coordinate grid division adapted to the region shape is selected. Localized refocusing is then performed in the subregion. This avoids the issue of electromagnetic wave attenuation, causing strong targets to mask weak ones in the imaging results. At the same time, the adoption of spherical coordinates for gridding and localized imaging greatly reduces the overall time consumption by the algorithm. Through simulation analysis and experimental verification, the proposed calibration method can effectively compensate for system errors. The fast refocusing algorithm can be used to realize multitarget 3D localization of the human body behind walls, with the localization accuracy of each dimension surpassing 10 cm and computational speeds improving by five times compared with those of existing algorithms. In terms of target detection probability, the proposed algorithm consistently identifies weak targets that other algorithms may overlook.

Abstract Neurotransmitters are key modulators in neuro-immune circuits and have been linked to tumor progression. Medullary thyroid cancer (MTC), an aggressive neuroendocrine tumor, expresses neurotransmitter calcitonin gene-related peptide (CGRP), is insensitive to chemo- and radiotherapies, and the effectiveness of immunotherapies remains unknown. Thus, a comprehensive analysis of the tumor microenvironment would facilitate effective therapies and provide evidence on CGRP’s function outside the nervous system. Here, we compare the single-cell landscape of MTC and papillary thyroid cancer (PTC) and find that expression of CGRP in MTC is associated with dendritic cell (DC) abnormal development characterized by activation of cAMP related pathways and high levels of Kruppel Like Factor 2 (KLF2), correlated with an impaired activity of tumor infiltrating T cells. A CGRP receptor antagonist could offset CGRP detrimental impact on DC development in vitro. Our study provides insights of the MTC immunosuppressive microenvironment, and proposes CGRP receptor as a potential therapeutic target.

The adaptability of conductive rubber in SO2/salt spray environment was studied by using graphene-filled conductive fluoroether rubber and alloy nickel powder-filled conductive silicone rubber in“SO2/salt spray” test. The macro morphology，Shore A hardness，tensile strength，elongation at break，tear strength and volume resistivity were tested to analyze the influence of the “SO2/salt spray” environment on the properties of conductive rubber. The results show before the test，the Shore A hardness of conductive fluoroether rubber and conductive silicone rubber are equivalent，the tensile strength of conductive fluoroether rubber is higher than that of conductive silicone rubber，and the volume resistivity is lower than that of conductive silicone rubber. After 8 cycles of “SO2/salt spray” test，the macro morphology of conductive fluoroether rubber does not change，Shore A hardness decreases by 3，tensile strength increases by 0.8 MPa（5%），elongation at break decreases by 18%， the volume resistivity increases by 2.1 Ω·cm（65.8%）and there is no change in tear strength；while the conductive silicone rubber has obvious corrosion，with green corrosion products appeared on the surface，Shore A hardness gradually decreases，and the tensile strength decreases by 1.2 MPa（16.4%），the elongation at break decreases by 2%，the volume resistivity decreases by 3.00 Ω·cm（52.4%）and there is no change in tear strength. The analysis of the comprehensive performances obtained by the study shows that the adaptability of conductive fluoroether rubber in “SO2/salt spray” environment is superior to that of conductive silicone rubber.

Introduction and Objectives: Prostate apoptosis response protein-4 (PAR-4) is considered a tumor suppressor. However, the role of PAR-4 in hepatocellular carcinoma (HCC) has rarely been reported. The study explores the role of PAR-4 in the malignant behaviors of HCC cells. Materials and Methods: TCGA database was applied to analyze the expression of PAR-4 in HCC. Evaluated PAR-4 relationship with clinical parameters and prognosis by tissue microarray; expression of STAT3, p-STAT3, Src and Ras was detected by Western blotting or laser confocal microscopy. Cell scratch and flow cytometry assays were used to observe IL-6 regulation of the malignant behaviors of HCC cells. The tumorigenic potential of HCC cells in vivo was evaluated in a nude mouse tumor model. Results: Analysis indicated that the expression of PAR-4 in HCC tissues was significantly higher than that in normal liver tissues; and PAR-4 interacted with STAT3. KEGG analysis showed that PAR-4 plays a role in the Janus kinase (JAK)/STAT signaling pathway. The positive expression rate of PAR-4 in HCC tissues was significantly higher than that in adjacent tissues. Positive correlation between IL-6 and PAR-4 expression in the HCC tissues. Exogenous IL-6 significantly promoted the proliferation and migration of HCC cells and up-regulated the expression of PAR-4 and p-STAT3 in HCC cells. Interference of the expression of PAR-4 could reduce the malignant behaviors of HCC cells and inhibit tumorigenesis in a nude mouse tumor model. Conclusions: PAR-4 expression is positively correlated with HCC; PAR-4 promotes malignant behavior of HCC cells mediated by the IL-6/STAT3 signaling pathway.

Background Determining the status of breast cancer susceptibility genes (BRCA) is crucial for guiding breast cancer treatment. Nevertheless, the need for BRCA genetic testing among breast cancer patients remains unmet due to high costs and limited resources. This study aimed to develop a Bi-directional Self-Attention Multiple Instance Learning (BiAMIL) algorithm to detect BRCA status from hematoxylin and eosin (H&E) pathological images. Methods A total of 319 histopathological slides from 254 breast cancer patients were included, comprising two dependent cohorts. Following image pre-processing, 633,484 tumor tiles from the training dataset were employed to train the self-developed deep-learning model. The performance of the network was evaluated in the internal and external test sets. Results BiAMIL achieved AUC values of 0.819 (95% CI [0.673–0.965]) in the internal test set, and 0.817 (95% CI [0.712–0.923]) in the external test set. To explore the relationship between BRCA status and interpretable morphological features in pathological images, we utilized Class Activation Mapping (CAM) technique and cluster analysis to investigate the connections between BRCA gene mutation status and tissue and cell features. Significantly, we observed that tumor-infiltrating lymphocytes and the morphological characteristics of tumor cells appeared to be potential features associated with BRCA status. Conclusions An interpretable deep neural network model based on the attention mechanism was developed to predict the BRCA status in breast cancer. Keywords: Breast cancer, BRCA, deep learning, self-attention, interpretability.

Purpose: Development and validation of a radiomics model for predicting occult locally advanced esophageal squamous cell carcinoma (LA-ESCC) on computed tomography (CT) radiomic features before implementation of treatment. Methods: The study retrospectively collected 574 patients with esophageal squamous cell carcinoma (ESCC) from two medical centers, which were divided into three cohorts for training, internal and external validation. After delineating volume of interest (VOI), radiomics features were extracted and subjected to feature selection using three robust methods. Subsequently, 10 machine learning models were constructed, among which the optimal model was utilized to establish a radiomics signature. Furthermore, a predictive nomogram incorporating both clinical and radiomics signatures was developed. The performance of these models was evaluated through receiver operating characteristic curves, calibration curves, decision curve analysis as well as measures including accuracy, sensitivity, and specificity. Results: A total of 19 radiomics features were selected. The multilayer perceptron (MLP), which was found to be optimal, achieved an AUC of 0.919, 0.864 and 0.882 in the training, internal and external validation cohorts, respectively. Similarly, MLP showed good accuracy in distinguish occult LA-ESCC in subgroup of cT1–2N0M0 diagnosed by clinicians with 0.803 and 0.789 in two validation cohorts respectively. By incorporating the radiomics signature with clinical signature, a predictive nomogram demonstrated superior prediction performance with an AUC of 0.877 and accuracy of 0.85 in external validation cohort. Conclusion: The radiomics and machine learning model can offers improved accuracy in prediction of occult LA-ESCC, providing valuable assistance to clinicians when choosing treatment plans.

Taking the filling mining in Yungang Coal Mine 8402 working face as the background, firstly, five gangue slurry with different proportions were prepared, and bleeding rate, setting time and uniaxial compressive strength tests were tested. Reasonable gangue slurry ratios were selected according to the requirements of use and cost, and the design of filling hydraulic support and filling mining technology was carried out. Considering the change of rock mass mechanical parameters with mining stress, based on Hoek-Brown model, FLAC3D software was used to study and analyze the spatial-temporal evolution law of deformation and failure of roof overburden in 8402 working face with or without filling. The results show that: when the dosage of cement and fly ash is 180 kg/m3 and 210 kg/m3 respectively, it can meet the requirements of filling mining and cost of 8402 working face in Yungang Coal Mine at the same time; under the condition of no filling, the 8402 working face has a periodical pressure step of 18-25 m, and the height of fracture zone is 108 m. While under the condition of 85% paste filling, the periodical pressure step of the working face is 36-40 m, and the height of fracture zone is 43 m; after the working face with 85% paste filling advances 120 m, the maximum subsidence and maximum tilt of the surface are basically kept unchanged at 165 mm and 2.62 mm/m, which are less than the requirements of the code and can ensure the safety of the ground building.

Abstract Alpha-fetoprotein (AFP), a serum glycoprotein, is expressed during embryonic development and the pathogenesis of liver cancer. It serves as a clinical tumor marker, function as a carcinogen, immune suppressor, and transport vehicle; but the detailed AFP structural information has not yet been reported. In this study, we used single-particle cryo-electron microscopy(cryo-EM) to analyze the structure of the recombinant AFP obtained a 3.31 Å cryo-EM structure and built an atomic model of AFP. We observed and identified certain structural features of AFP, including N-glycosylation at Asn251, four natural fatty acids bound to distinct domains, and the coordination of metal ions by residues His22, His264, His268, and Asp280. Furthermore, we compared the structural similarities and differences between AFP and human serum albumin. The elucidation of AFP’s structural characteristics not only contributes to a deeper understanding of its functional mechanisms, but also provides a structural basis for developing AFP-based drug vehicles.

AIM: To investigate the molecular diagnosis of a three-generation Chinese family affected with aniridia, and further to identify clinically a PAX6 missense mutation in members with atypical aniridia. METHODS: Eleven family members with and without atypical aniridia were recruited. All family members underwent comprehensive ophthalmic examinations. A combination of whole exome sequencing (WES) and direct Sanger sequencing were performed to uncover the causative mutation. RESULTS: Among the 11 family members, 8 were clinically diagnosed with congenital aniridia (atypical aniridia phenotype). A rare heterozygous mutation c.622C>T (p.Arg208Trp) in exon 8 of PAX6 was identified in all affected family members but not in the unaffected members or in healthy control subjects. CONCLUSION: A rare missense mutation in the PAX6 gene is found in members of a three-generation Chinese family with congenital atypical aniridia. This result contributes to an increase in the phenotypic spectrum caused by PAX6 missense heterozygous variants and provides useful information for the clinical diagnosis of atypical aniridia, which may also contribute to genetic counselling and family planning.

Purpose To develop and validate a web-based nomogram for predicting new incident chronic kidney disease (CKD) within 4 years in a cohort undergoing routine physical examination from two health examination centers.Methods One center was utilized for training and internal validation of a nomogram model involving 6515 patients, while a separate center was employed for external validation with 3152 patients. Sixteen candidate predictors, including patient demographics, medical histories, physical examination, and laboratory test data, were included in this study to ascertain factors linked to new incident CKD. A nomogram was created to predict CKD risks using a logistic model. The nomogram’s performance was assessed using the area under the receiver operating characteristic curve (AUC), calibration plot, and decision curve analysis.Results Out of the 9667 healthy individuals included in the study with mean age of 46 years, sex ratio (male/female) of 1.69 (6075/3592), 118 (2.59%), 51 (2.61%), and 60 (1.90%) individuals developed CKD in the training (n = 4563), internal validation (n = 1952), and external validation (n = 3152) datasets, respectively. Age, history of diabetes mellitus, systolic blood pressure, serum creatinine, albumin, and triglyceride levels were used to build the nomogram, which yielded excellent discrimination ability (training cohort, AUC = 0.8806, 95% confidence interval [CI] 0.8472–0.9141; internal validation cohort, AUC = 0.8506, 95% CI 0.7856–0.9156; external validation cohort, AUC = 0.9183, 95% CI 0.8698–0.9669). We further developed a web-based calculator for convenient application (https://luochuxuan.shinyapps.io/dynnomapp/).Conclusion Our web-based nomogram accurately predicted CKD risks in Chinese health individuals and can be easily used in clinical settings.

Background The status of BRCA1/2 genes plays a crucial role in the treatment decision-making process for multiple cancer types. However, due to high costs and limited resources, a demand for BRCA1/2 genetic testing among patients is currently unmet. Notably, not all patients with BRCA1/2 mutations achieve favorable outcomes with poly (ADP-ribose) polymerase inhibitors (PARPi), indicating the necessity for risk stratification. In this study, we aimed to develop and validate a multimodal model for predicting BRCA1/2 gene status and prognosis with PARPi treatment.Methods We included 1695 slides from 1417 patients with ovarian, breast, prostate, and pancreatic cancers across three independent cohorts. Using a self-attention mechanism, we constructed a multi-instance attention model (MIAM) to detect BRCA1/2 gene status from hematoxylin and eosin (H&E) pathological images. We further combined tissue features from the MIAM model, cell features, and clinical factors (the MIAM-C model) to predict BRCA1/2 mutations and progression-free survival (PFS) with PARPi therapy. Model performance was evaluated using area under the curve (AUC) and Kaplan-Meier analysis. Morphological features contributing to MIAM-C were analyzed for interpretability.Results Across the four cancer types, MIAM-C outperformed the deep learning-based MIAM in identifying the BRCA1/2 genotype. Interpretability analysis revealed that high-attention regions included high-grade tumors and lymphocytic infiltration, which correlated with BRCA1/2 mutations. Notably, high lymphocyte ratios appeared characteristic of BRCA1/2 mutations. Furthermore, MIAM-C predicted PARPi therapy response (log-rank p

Background The role of peripheral eosinophils in chronic kidney disease (CKD) requires further evaluation. We aimed to determine whether an eosinophil count increase is related to the occurrence of end-stage renal disease (ESRD).Methods This single-center, observational, retrospective cohort study was conducted between January 2016 and December 2018 in Hangzhou, China, and included 3163 patients, categorized into four groups according to peripheral eosinophil count (PEC) quartile values. The main outcome was ESRD development during follow-up. We evaluated the relationship between the serum eosinophil count, demographic and clinical information, and ESRD incidence. Cox proportional hazards models and Kaplan–Meier survival curves were used.Results A total of 3163 patients with CKD were included in this cohort, of whom 1254 (39.6%) were females. The median (interquartile range [IQR]) age was 75 [64, 85] years, and the median (IQR) estimated glomerular filtration rate was 55.16 [45.19, 61.19] mL/min/1.73 m2. The median PEC was 0.1224 × 109/L (IQR, 0.0625–0.212). Among the 3163 patients with CKD, 273 (8.6%) developed ESRD during a median follow-up time of 443.8 [238.8, 764.9] days. Individuals in the highest PEC quartile had a 66.2% higher ESRD risk than those in the lowest quartile (hazard ratio, 1.662; 95% confidence interval, 1.165–2.372). The results from the Kaplan–Meier survival curves confirmed the conclusion.Conclusions Alongside traditional risk factors, patients with CKD and an elevated PEC are more likely to develop ESRD. Therefore, more attention should be paid to those patients with CKD who have a high PEC.

AimComparing the safety, effectiveness, and mid-term survival rates of robot-assisted minimally invasive esophagectomy (RAMIE) and video-assisted minimally invasive esophagectomy (VAMIE).MethodsA total of 842 patients undergoing minimally invasive esophagectomy were analyzed, including 694 patients in VAMIE group and 148 in RAMIE group. PSM analysis was applied to generate matched pairs for further comparison. Operative outcomes, postoperative complications and Mid-term outcomes were compared between all patients in matched groups.ResultsAfter 1:4 PSM, 148 patients in the RAMIE and 592 patients in the VAMIE. Compared to VAMIE, RAMIE exhibited earlier removal of chest and neck drainage tubes, shorter postoperative hospital stays, and a higher number of lymph node dissections. However, the surgical duration of RAMIE was longer than that of VAMIE. Postoperative complications were no statistically significant between the RAMIE and VAMIE groups. There was no statistically significant difference in the 3-year OS and DFS between the two groups.ConclusionCompared to VAMIE, RAMIE emerges as a viable and safe surgical approach and suggests RAMIE as a potential alternative to minimally invasive esophagectomy.

Proliferative glomerulonephritis with monoclonal immunoglobulin deposits (PGNMID) is a rare disease without standardized treatment modalities. Daratumumab is a human IgG monoclonal anti-CD38 antibody that has been demonstrated to be highly effective and safe in the treatment of PGNMID. This article reports a 66-year-old female who suffered from edema in both lower limbs and face for 6 years with mild proteinuria and hypoproteinemia. Renal biopsy displayed eight glomeruli, among which two presented with glomerulosclerosis, and the remaining six exhibited moderate diffuse hyperplasia of glomerular mesangial cells and stroma with endothelial cell proliferation. Immunofluorescence microscopy revealed lumpy and diffuse deposits of C3, C1q, IgG, and κ light chain in the glomerular mesangium, with strongly positive staining for IgG3 and varying degrees of weak to negative staining for IgG1, IgG2, IgG4, and λ light chain. Additionally, ultrastructural analysis unveiled that the glomerular basement membrane was segmentally thickened, accompanied by diffuse pedicle fusion, segmental tethered insertion, subendothelial deposits, and electron-dense material in tethered areas. The patient received a total dose of 800 mg of daratumumab (400 mg daily for two consecutive days), as well as daily prednisone (25 mg) and valsartan (80 mg), for treatment and achieved complete remission after three-month follow-up. This case represents an early attempt to treat PGNMID with low-dose daratumumab but requires long-term follow-up.

Abstract The heterogeneity of macrophages influences the response to immune checkpoint inhibitor (ICI) therapy. However, few studies explore the impact of APOE+ macrophages on ICI therapy using single‐cell RNA sequencing (scRNA‐seq) and machine learning methods. The scRNA‐seq and bulk RNA‐seq data are Integrated to construct an M.Sig model for predicting ICI response based on the distinct molecular signatures of macrophage and machine learning algorithms. Comprehensive single‐cell analysis as well as in vivo and in vitro experiments are applied to explore the potential mechanisms of the APOE+ macrophage in affecting ICI response. The M.Sig model shows clear advantages in predicting the efficacy and prognosis of ICI therapy in pan‐cancer patients. The proportion of APOE+ macrophages is higher in ICI non‐responders of triple‐negative breast cancer compared with responders, and the interaction and longer distance between APOE+ macrophages and CD8+ exhausted T (Tex) cells affecting ICI response is confirmed by multiplex immunohistochemistry. In a 4T1 tumor‐bearing mice model, the APOE inhibitor combined with ICI treatment shows the best efficacy. The M.Sig model using real‐world immunotherapy data accurately predicts the ICI response of pan‐cancer, which may be associated with the interaction between APOE+ macrophages and CD8+ Tex cells.

Abstract Diabetic nephropathy is a critical complication of patients with type 1 diabetes, while epidemiological studies were scarce among Asian countries. We conducted a cross-sectional study to identify factors associated with diabetic nephropathy by questionnaires, using student’s t-test, chi-square test, and multivariable logistic regression. Among 898 participants, 16.7% had diabetic nephropathy. Compared with non-diabetic nephropathy patients, the patients with diabetic nephropathy had significantly higher percentage with onset age of type 1 diabetes between puberty and under 30 years old (female ≥ 12 or male ≥ 13 years old to 29 years old), longer diabetes duration, having family history of diabetes and diabetic nephropathy, accompanied with hypertension, hyperlipidemia, or coronary artery disease (CAD). Compared with patients with onset age before puberty, the odds of diabetic nephropathy occurrence increased to 1.61 times in patients with onset age between puberty and under 30 years old (p = 0.012) after adjusting diabetes duration. Age of diabetes onset between puberty and under 30 years old, diabetes duration, HbA1c, hospital admission within 3 years, diabetic retinopathy, hypertension, systolic blood pressure (SBP), triglyceride levels, and use of angiotensin converting enzyme inhibitor (ACEI) and/or angiotensin receptor blockers (ARB) were independent factors associated with diabetic nephropathy Screening for proteinuria is important in daily clinical practice and should be part of diabetes self-management education for patients with type 1 diabetes.

To accurately describe the dynamic inductance gradient during the operation process of the series enhanced four-rail electromagnetic rail launcher, an equivalent geometric model based on skin depth is constructed. The influence of armature motion on current diffusion in the rail is considered, and the velocity skin effect is derived. Combined with Biot-Savart Law, an analytical calculation method for dynamic inductance gradient is proposed, and an experimental platform for the series-enhanced four-rail electromagnetic launcher is built, Calculate the dynamic inductance gradient of the experimental device and compare it with the eddy current field simulation calculation, demonstrating the correctness of the proposed analytical method for calculating the dynamic inductance gradient. Analyze the influence of armature motion on the system inductance gradient, and obtain that the initial velocity of armature launching is small, and the distribution of rail current is affected by the current skin effect and related to the current frequency. As the armature velocity increases, the distribution of current in the middle section of armature launching is affected by the velocity skin effect, The skin depth decreases and the dynamic inductance gradient decreases. As the armature speed increases, the dynamic inductance gradient gradually decreases and tends to stabilize in the accelerated stage of armature launching.

Abstract Background For complete revascularization, patients with diffuse coronary artery disease should have a coronary endarterectomy and a coronary artery bypass graft (CE-CABG). Sadly, CE can lead to a lack of endothelium, which raises the risk of thrombotic events. Even though daily dual antiplatelet therapies (DAPT) have been shown to reduce thrombotic events, the risk of perioperative thrombotic events is high during the high-risk period after CE-CABG, and there is no consistent protocol to bridge DAPT. This trial aims to compare safety and efficacy between tirofiban and heparin as DAPT bridging strategies after CE-CABG. Methods In phase I, 266 patients undergoing CE-CABG will be randomly assigned to tirofiban and heparin treatment groups to compare the two treatments in terms of the primary safety endpoint, chest tube drainage in the first 24 h. If the phase I trial shows tirofiban non-inferiority, phase II will commence, in which an additional 464 patients will be randomly assigned. All 730 patients will be studied to compare major cardiovascular and cerebrovascular events (MACCEs) between the groups in the first 30 days after surgery. Discussion Given the possible benefits of tirofiban administration after CE-CABG, this trial has the potential to advance the field of adult coronary heart surgery. Trial registration chictr.org.cn, ChiCTR2200055697. Registered 6 January 2022. https://www.chictr.org.cn/com/25/showproj.aspx?proj=149451 . Current version: 20,220,620.

Abstract The 2023 update of the Chinese Society of Clinical Oncology (CSCO) Clinical Guidelines for Gastric Cancer focuses on standardizing cancer diagnosis and treatment in China, reflecting the latest advancements in evidence‐based medicine, healthcare resource availability, and precision medicine. These updates address the differences in epidemiological characteristics, clinicopathological features, tumor biology, treatment patterns, and drug selections between Eastern and Western gastric cancer patients. Key revisions include a structured template for imaging diagnosis reports, updated standards for molecular marker testing in pathological diagnosis, and an elevated recommendation for neoadjuvant chemotherapy in stage III gastric cancer. For advanced metastatic gastric cancer, the guidelines introduce new recommendations for immunotherapy, anti‐angiogenic therapy and targeted drugs, along with updated management strategies for human epidermal growth factor receptor 2 (HER2)‐positive and deficient DNA mismatch repair (dMMR)/microsatellite instability‐high (MSI‐H) patients. Additionally, the guidelines offer detailed screening recommendations for hereditary gastric cancer and an appendix listing drug treatment regimens for various stages of gastric cancer. The 2023 CSCO Clinical Guidelines for Gastric Cancer updates are based on both Chinese and international clinical research and expert consensus to enhance their applicability and relevance in clinical practice, particularly in the heterogeneous healthcare landscape of China, while maintaining a commitment to scientific rigor, impartiality, and timely revisions.

Abstract Background and objective Loneliness is detrimental to mental health, with university students at higher risk of feeling lonely than other population groups. The mental health of college students is a hot topic at present. Despite numerous studies exploring interventions for loneliness among university students. However, little research has explored early psychological manifestations of university students with different levels of loneliness. Despite numerous studies exploring interventions for loneliness among university students, little research has explored early psychological manifestations of university students with different levels of loneliness. Initial sandplay is a good tool to reveal psychological activity. Therefore, our study aims to explore the characteristics of initial sandplay application among university students with different levels of loneliness. Methods We recruited 60 volunteers from a university to perform a sandplay experiment from January to April 2021. The UCLA Loneliness Scale measured the levels of loneliness. These 60 participants were divided into the experimental group (n = 30) and control group (n = 30) according to their levels of loneliness. The experimental group included participants with a scale score of more than 44. Other participants with a scale score of less than 44 belong to the control group. We recorded their sandplay artwork and statistically analyzed it by the Sandplay Process Record Form. Group comparisons were performed using the t-test or Wilcoxon rank-sum test for continuous variables, and the chi-square test or Fisher’s exact test for categorical variables. The logistic regression analysis by forward stepwise method was conducted to analyze the sandplay theme features for loneliness. Results Regarding the sandplay tools, the experimental group used fewer transportation tools (t=-3.608, p

Abstract Background Patients with chronic kidney disease (CKD) are at high risk of drug-related problems (DRPs) because of extensive comorbidities and pharmacokinetic changes. This study aimed to identify DRPs and possible contributing factors in hospitalized patients with CKD, and evaluate the efficacy of the clinical pharmacist services in detection and intervention of DRPs in a large general hospital in Zhejiang Province, eastern China. Methods With the approval of the Ethics Committee, patients with CKD admitted to the nephrology ward from January to December 2020 were enrolled in this prospective study. The clinical pharmacist identified and intervened the DRPs during hospitalization. The DRPs were classified using the Pharmaceutical Care Network Europe (PCNE) DRP classification system, and all data were statistically analyzed using Statistical Package for Social Science (SPSS) version 26.0. Results A total of 914 patients with CKD were included, with 463 DRPs observed among 420 (45.95%) participants; the average DRP per patient was 0.51 (standard deviation [SD], 0.60) before pharmacist intervention. Treatment safety accounted for the highest proportion of problems (43.84%), followed by treatment efficacy, accounting for 43.20%. Drug selection was the most common cause of DRPs (60.26%), and antibiotics and cardiovascular agents were the most common drugs associated with DRPs (32.84% and 28.66%, respectively). A total of 85.53% of pharmaceutical intervention recommendations were followed, and 84.23% of DRPs were completely resolved after intervention by the clinical pharmacist. The proportion of patients who experienced DRPs decreased to 7.77%, with an average of 0.08 (SD 0.28) DRPs during hospitalization after pharmacist’s intervention. Significant contributing factors for DRPs were CKD stage 4, number of comorbid diseases, number of prescribed medications, and hospitalization days in both the univariate and multivariate logistic regression models. Conclusion DRPs are common among hospitalized patients with CKD in China. CKD stage 4, the number of comorbidities, use of multiple prescription drugs, and extended length of hospital stay are contributing factors for DRPs. Even only one clinical nephrology pharmacist in the nephrology ward, clinical pharmacist can play an important role in facilitating the identification of DRPs in patients with CKD and assisting physicians resolve DRPs in this single center study in China.

ABSTRACTTo provide scientific and technological support for the smooth development of flowers, regulation of florescence, and cultural management, among others, this study analyzes the corresponding relationship between bioclimatology and the characteristics of growth, development, and reproductive biology of A. sellowiana. Berg (Feijoa). Therefore, through optimized paraffin sections, this study examined the floral bud differentiation in five-year-old A. sellowiana trees and analyzed the dynamic changes in carbohydrate and nitrogenous compound metabolism during floral bud differentiation and flower development under natural growth conditions. The results showed that there were six stages in the differentiation process of A. sellowiana floral buds: the initiation of differentiation, inflorescence primordium differentiation, sepal primordium differentiation, petal primordium differentiation, stamen primordium differentiation and pistil primordium differentiation. Differentiation of floral buds began in late March in the Mianyang region, China, and lasted approximately 30 days. Following bud differentiation, the growth enters a period of bud development lasting approximately five months. Throughout the entire differentiation process, the flower buds contained significantly higher levels of total sugar, starch, soluble sugar, and nucleic acid than those in the leaves, and a peak of total nitrogen, nitrate nitrogen, and sucrose during the physiological transition period. Total nucleic acid and RNA content both increased, with RNA content increasing more significantly.

Smart agriculture has become an inevitable trend in the development of modern agriculture, especially promoted by the continuous progress of large language models like chat generative pre-trained transformer (ChatGPT) and general language model (ChatGLM). Although these large models perform well in general knowledge learning, they still have certain limitations and errors when facing agricultural professional knowledge about crop disease identification, growth stage judgment, and so on. Agricultural data involves images and texts and other modalities, which play an important role in agricultural production and management. In order to better learn the characteristics of different modal data in agriculture, realize cross-modal data fusion, and thus understand complex application scenarios, we propose a framework AgriVLM that uses a large amount of agricultural data to fine-tune the visual language model to analyze agricultural data. It can fuse multimodal data and provide more comprehensive agricultural decision support. Specifically, it utilizes Q-former as a bridge between an image encoder and a language model to achieve a cross-modal fusion of agricultural images and text data. Then, we apply a Low-Rank adaptive to fine-tune the language model to achieve an alignment between agricultural image features and a pre-trained language model. The experimental results prove that AgriVLM demonstrates great performance in crop disease recognition and growth stage recognition, with recognition accuracy exceeding 90%, demonstrating its capability to analyze different modalities of agricultural data.