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This study investigates the long-term service effects on Chinese fir (Cunninghamia lanceolata) components from ancient timber buildings in southern China. Anisotropic mechanical tests were performed to examine the evolution of mechanical properties from the perspectives of moisture absorption behavior, chemical composition, and microstructural characteristics. The results show that, after approximately 217 ± 12 years (Lvb specimens) and 481 ± 23 years (Xuc specimens) of service, the longitudinal compressive strength and corresponding elastic modulus of Chinese fir increased by about 11% and 15% and 33% and 71%, respectively, compared with fresh timber. The bending strength of the Lvb sample exhibited a slight reduction (approximately 6%), whereas the Xuc specimens showed the highest increase (33%). This difference is mainly attributed to long-term bending loads that caused structural damage in the Lvb beam specimens. In contrast, changes in lateral mechanical properties were negligible. Chemical composition analysis revealed an increase in extractive content and a reduction in cellulose and hemicellulose, leading to a notable rise in crystallinity. Scanning electron microscopy (SEM) observations further showed interlayer separation, wrinkling, and local collapse of the cell walls, suggesting significant cell wall densification. Overall, the evolution of mechanical properties is governed by the combined effects of increased crystallinity and microstructural densification, which together enhance the longitudinal and bending performance of aged timber with increasing service time. The findings provide a scientific basis for evaluating the performance and structural safety of aged timber components in the conservation of ancient timber buildings.

Purpose68 Ga-PSMA PET/CT has high specificity and sensitivity for the detection of both intraprostatic tumor focal lesions and metastasis. However, approximately 10% of primary prostate cancer are invisible on PSMA-PET (exhibit no or minimal uptake). In this work, we investigated whether machine learning-based radiomics models derived from PSMA-PET images could predict invisible intraprostatic lesions on 68 Ga-PSMA-11 PET in patients with primary prostate cancer.MethodsIn this retrospective study, patients with or without prostate cancer who underwent 68 Ga-PSMA PET/CT and presented negative on PSMA-PET image at either of two different institutions were included: institution 1 (between 2017 and 2020) for the training set and institution 2 (between 2019 and 2020) for the external test set. Three random forest (RF) models were built using selected features extracted from standard PET images, delayed PET images, and both standard and delayed PET images. Then, subsequent tenfold cross-validation was performed. In the test phase, the three RF models and PSA density (PSAD, cut-off value: 0.15 ng/ml/ml) were tested with the external test set. The area under the receiver operating characteristic curve (AUC) was calculated for the models and PSAD. The AUCs of the radiomics model and PSAD were compared.ResultsA total of 64 patients (39 with prostate cancer and 25 with benign prostate disease) were in the training set, and 36 (21 with prostate cancer and 15 with benign prostate disease) were in the test set. The average AUCs of the three RF models from tenfold cross-validation were 0.87 (95% CI: 0.72, 1.00), 0.86 (95% CI: 0.63, 1.00), and 0.91 (95% CI: 0.69, 1.00), respectively. In the test set, the AUCs of the three trained RF models and PSAD were 0.903 (95% CI: 0.830, 0.975), 0.856 (95% CI: 0.748, 0.964), 0.925 (95% CI:0.838, 1.00), and 0.662 (95% CI: 0.510, 0.813). The AUCs of the three radiomics models were higher than that of PSAD (0.903, 0.856, and 0.925 vs. 0.662, respectively; P = .007, P = .045, and P = .005, respectively).ConclusionRandom forest models developed by 68 Ga-PSMA-11 PET-based radiomics features were proven useful for accurate prediction of invisible intraprostatic lesion on 68 Ga-PSMA-11 PET in patients with primary prostate cancer and showed better diagnostic performance compared with PSAD.

Background Chemotherapy side effects can easily contribute to malnutrition and disrupt the normal diet of breast cancer patients. Offering early multidisciplinary team interventions during chemotherapy can establish a solid groundwork for dietary management and enhance the quality of life throughout the survival period. This study aims to assess the impact of early multidisciplinary team interventions on dietary management behavior, self-care self-efficacy, quality of life, and body mass index in breast cancer patients undergoing chemotherapy. Methods A prospective, two-arm, single-blind, single-center randomized controlled trial was conducted between November 2023 and July 2024 from a tertiary-level general hospital in Shaanxi, China. A total of 88 participants who were either preparing for or undergoing early or middle stage chemotherapy were enrolled for this intervention. The intervention group received diet-related early multidisciplinary team interventions, in addition to the usual dietary education. The control group only received the usual dietary education. The intervention program included 8 themes, which were covered each week. The data on dietary management behavior, self-care self-efficacy, quality of life, and body mass index were measured at baseline (T0), immediately after the intervention (T1), 1 month after (T2), and 3 months after (T3) the intervention. Results Seventy-nine participants, divided into an intervention group of 40 and a control group of 39, completed all the measures. There were statistically significant intergroup effects between the two groups and time effects on dietary management behavior, self-care self-efficacy, and quality of life. Additionally, there was an interaction effect ( P  < 0.05). However, there was no statistically significant intergroup effect on body mass index before and after the intervention ( P  > 0.05). Conclusion The early multidisciplinary team interventions are an effective method for improving dietary management behavior and confidence among breast cancer patients undergoing chemotherapy. Nurses should be attentive to the dietary issues faced by female patients during chemotherapy and should work to train and organize a multidisciplinary team to provide this intervention. This may lay a theoretical and capable foundation for managing a healthy lifestyle for future survival period. Trial registration This intervention was registered with the Chinese Clinical Trials Registry (ChiCTR2300076503, October 10, 2023).

Background The immune system plays a vital role in the pathophysiology of acute myocardial infarction (AMI). However, the exact immune related mechanism is still unclear. This research study aimed to identify key immune-related genes involved in AMI. Methods CIBERSORT, a deconvolution algorithm, was used to determine the proportions of 22 subsets of immune cells in blood samples. The weighted gene co-expression network analysis (WGCNA) was used to identify key modules that are significantly associated with AMI. Then, CIBERSORT combined with WGCNA were used to identify key immune-modules. The protein–protein interaction (PPI) network was constructed and Molecular Complex Detection (MCODE) combined with cytoHubba plugins were used to identify key immune-related genes that may play an important role in the occurrence and progression of AMI. Results The CIBERSORT results suggested that there was a decrease in the infiltration of CD8 + T cells, gamma delta (γδ) T cells, and resting mast cells, along with an increase in the infiltration of neutrophils and M0 macrophages in AMI patients. Then, two modules (midnightblue and lightyellow) that were significantly correlated with AMI were identified, and the salmon module was found to be significantly associated with memory B cells. Gene enrichment analysis indicated that the 1,171 genes included in the salmon module are mainly involved in immune-related biological processes. MCODE analysis was used to identify four different MCODE complexes in the salmon module, while four hub genes ( EEF1B2 , RAC2 , SPI1 , and ITGAM ) were found to be significantly correlated with AMI. The correlation analysis between the key genes and infiltrating immune cells showed that SPI1 and ITGAM were positively associated with neutrophils and M0 macrophages, while they were negatively associated with CD8 + T cells, γδ T cells, regulatory T cells (Tregs), and resting mast cells. The RT-qPCR validation results found that the expression of the ITGAM and SPI1 genes were significantly elevated in the AMI samples compared with the samples from healthy individuals, and the ROC curve analysis showed that ITGAM and SPI1 had a high diagnostic efficiency for the recognition of AMI. Conclusions Immune cell infiltration plays a crucial role in the occurrence and development of AMI. ITGAM and SPI1 are key immune-related genes that are potential novel targets for the prevention and treatment of AMI.

Background Accurate fasting plasma glucose (FPG) trend prediction is important for management and treatment of patients with type 2 diabetes mellitus (T2DM), a globally prevalent chronic disease. (Generalised) linear mixed-effects (LME) models and machine learning (ML) are commonly used to analyse longitudinal data; however, the former is insufficient for dealing with complex, nonlinear data, whereas with the latter, random effects are ignored. The aim of this study was to develop LME, back propagation neural network (BPNN), and mixed-effects NN models that combine the 2 to predict FPG levels. Methods Monitoring data from 779 patients with T2DM from a multicentre, prospective study from the shared platform Figshare repository were divided 80/20 into training/test sets. The first 10 important features were modelled via random forest (RF) screening. First, an LME model was built to model interindividual differences, analyse the factors affecting FPG levels, compare the AIC and BIC values to screen the optimal model, and predict FPG levels. Second, multiple BPNN models were constructed via different variable sets to screen the optimal BPNN. Finally, an LME/BPNN combined model, named LMENN, was constructed via stacking integration. A 10-fold cross-validation cycle was performed using the training set to build the model and evaluate its performance, and then the final model was evaluated on the test set. Results The top 10 variables screened by RF were HOMA-β, HbA1c, HOMA–IR, urinary sugar, insulin, BMI, waist circumference, weight, age, and group. The best-fitting random-intercept mixed-effects (lm22) model showed that each patient’s baseline glucose levels influenced subsequent glucose measurements, but the trend over time was consistent. The LMENN model combines the strengths of LME and BPNN and accounts for random effects. The RMSE of the LMENN model ranges were 0.447–0.471 (training set), 0.525–0.552 (validation set), and 0.511–0.565 (test set). It improves the prediction performance of the single LME and BPNN models and shows some advantages in predicting FPG levels. Conclusions The LMENN model built by integrating LME and BPNN has several potential applications in analysing longitudinal FPG monitoring data. This study provides new ideas and methods for further research in the field of blood glucose prediction.

Background Controversy exists around the locoregional management of the primary tumor for breast cancer associated with synchronous ipsilateral supraclavicular lymph node metastasis (sISLM) due to the rarity of the disease and limited available data. This study aimed to compare outcomes of patients in the Surveillance, Epidemiology, and End Results (SEER) database with sISLM who underwent surgical resection and radiation of the primary tumor with those who did not. Methods This population-based retrospective study included breast cancer patients with sISLM without distant metastases from 2004 to 2016 in the SEER database. In this study, patients had been stratified by operative management, and propensity score matching (PSM) had been successfully applied. Results A total of 1172 breast cancer patients with sISLM were included in the study: 863 (73.6%) of patients underwent the primary tumor resection, and 309 (26.4%) patients did not undergo surgery. The median survival time in the surgery group was longer compared to the nonsurgery group in the overall cohort and the PSM cohort. We concluded that the primary tumor resection was associated with improved survival. Subgroup analysis further demonstrated that local surgery was not inferior to radical surgery. Conclusion For selected breast cancer patients with sISLM, surgery is a promising local intervention which may improve the survival.

Background Abnormal expression of six-transmembrane epithelial antigen of prostate 4 ( STEAP4 ) has been implicated in the carcinogenesis of hepatocellular carcinoma (HCC). However, the biological role and regulatory mechanisms of STEAP4 in HCC remain unclear. Methods and Results Here, we analyzed STEAP4 expression levels and differentially expressed genes (DEGs) between STEAP4 high- and low-expression groups using multiple databases. Proliferation assays, 5-ethynyl-2’-deoxyuridine (EdU) assays, propidium iodide (PI) flow cytometry, and colony formation assays were conducted to assess the effects of STEAP4 on HCC cell proliferation, cell cycle progression, and clonogenic capacity. STEAP4 was downregulated in HCC tumor tissues, with lower expression associated with poorer overall survival (OS) and disease-free survival (DFS) in patients. Functional network analysis suggested that STEAP4 regulates cell cycle signaling, with tumor sections showing a negative correlation between STEAP4 and cell cycle proteins. Overexpression of STEAP4, combined with non-cytotoxic copper exposure in the HepG2 cell line, reduced proliferation and clonogenicity, induced cell cycle arrest, and downregulated the mRNA and protein levels of cell cycle-regulating genes. A predictive model based on STEAP4 and cell cycle gene demonstrated prognostic value in HCC patients. Conclusions Our results lay a foundation for further study of the cell cycle regulatory role of STEAP4 with Cu 2+ reductase activity in HCC, indicating that STEAP4 may be a promising therapeutic target for HCC.

Background Spontaneous abortion, affecting over 20% of pregnancies, presents significant physical and psychological burdens. While chromosomal aneuploidy and environmental factors contribute to its etiology, the role of maternal genetic and psychiatric factors remains underexplored. Emerging evidence links psychiatric disorders, particularly bipolar disorder, to increased spontaneous abortion risk, potentially via immune or neuroendocrine dysregulation. This research examines the causal link between bipolar disorder and spontaneous abortion using mendelian randomization (MR) and delves into molecular mechanisms via bioinformatics analysis. Results Initial MR analysis revealed no direct causal association between bipolar disorder and spontaneous abortion ( odds ratio (OR)  =  1.05, 95% Confidence Interval (CI): 0.99–1.12 ). However, single-nucleotide-polymorphism-level analysis identified rs1054442 as a potential mediator, linked to reduced expression of DDN , a gene implicated in neurodevelopment and immune modulation. Microarray data demonstrated significant downregulation of DDN in endometrial tissue from spontaneous abortion patients ( logFold Change ( logFC)  = − 1.21 , p  =  0.004 ). Concurrently, immune checkpoint genes— CTLA4 , IGSF8 , ITPRIPL1 , and TIGIT —exhibited altered expression patterns, suggesting disrupted immune tolerance at the maternal–fetal interface. Conclusions Although bipolar disorder does not directly elevate spontaneous abortion risk, genetic variants associated with the disorder may contribute to immune dysfunction via DDN dysregulation, indirectly predisposing to spontaneous abortion. These discoveries point to the potential influence of maternal immune modulation in the origins of spontaneous abortion and indicate therapeutic targets for those at risk. Further studies are needed to validate these mechanisms and explore clinical interventions targeting immune checkpoint pathways.

Background Chemotherapy is the primary established systemic treatment for patients with breast cancer, especially those with the triple-negative subtype. Simultaneously, the resistance of triple-negative breast cancer (TNBC) to chemotherapy remains a major clinical problem. Our previous study demonstrated that the expression levels of PTN and its receptor PTPRZ1 were upregulated in recurrent TNBC tissue after chemotherapy, and this increase was closely related to poor prognosis in those patients. However, the mechanism and function of chemotherapy-driven increases in PTN/PTPRZ1 expression are still unclear. Methods We compared the expression of PTN and PTPRZ1 between normal breast and cancer tissues as well as before and after chemotherapy in cancer tissue using the microarray analysis data from the GEPIA database and GEO database. The role of chemotherapy-driven increases in PTN/PTPRZ1 expression was examined with a CCK-8 assay, colony formation efficiency assay and apoptosis analysis with TNBC cells. The potential upstream pathways involved in the chemotherapy-driven increases in PTN/PTPRZ1 expression in TNBC cells were explored using microarray analysis, and the downstream mechanism was dissected with siRNA. Results We demonstrated that the expression of PTN and PTPRZ1 was upregulated by chemotherapy, and this change in expression decreased chemosensitivity by promoting tumour proliferation and inhibiting apoptosis. CDKN1A was the critical switch that regulated the expression of PTN/PTPRZ1 in TNBC cells receiving chemotherapy. We further demonstrated that the mechanism of chemoresistance by chemotherapy-driven increases in the CDKN1A/PTN/PTPRZ1 axis depended on the NF-κB pathway. Conclusions Our studies indicated that chemotherapy-driven increases in the CDKN1A/PTN/PTPRZ1 axis play a critical role in chemoresistance, which suggests a novel strategy to enhance chemosensitivity in breast cancer cells, especially in those of the triple-negative subtype.

BackgroundSquamous cell/adenosquamous carcinoma (SC/ASC) is a rarely identified form of gallbladder cancer with poorly understood clinical features. As such, there is an urgent need to identify novel prognostic biomarkers for such gallbladder SC/ASC cases, and for gallbladder adenocarcinomas (ACs).MethodsThe levels of ACO2 and ANPEP proteins were assessed via an EnVision-based immunohistochemical approach using 46 SC/ASC and 80 AC patient samples.ResultsThere was a marked reduction in levels of ACO2 and ANPEP in gallbladder AC relative to normal adjacent tissue or benign gallbladder lesions. The was a significant correlation between lack of ACO2 and ANPEP and larger tumors, higher tumor-node-metastasis (TNM) staging, invasion, metastasis to regional lymph nodes, and ineligibility for surgical resection in both SC/ASC and AC tumor samples. Kaplan–Meier survival analyses further confirmed a relationship between ACO2 and ANPEP negativity and decreased overall survival in patients with these diseases (p < 0.05 or p < 0.01), and a multivariate regression analysis further established that ACO2 negativity and ANPEP negativity were independently predictive of poor SC/ASC and AC patient outcomes.ConclusionsACO2 and ANPEP may have key physiological relevance in cancers of the gallbladder and thus warrant investigation as prognostic biomarkers.