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With the development of urbanization, there is an increasing demand for higher land utilization rates, leading to the emergence of high-rise residential and commercial complexes. Additionally, in coastal areas, the presence of soft soil and low bearing capacity of the foundation necessitate higher foundation bearing capacity. Large-diameter, super-long piles have been widely employed in engineering projects to address these challenges effectively. This study analyzes their vertical bearing characteristics through field load tests and determines vertical load distribution and transfer mechanisms by using Brillouin Optical Time Domain Reflectometry. A numerical computation and analysis method based on PLAXIS 3D was established, examining the effects of parameters such as pile diameter, length, and soil modulus on the vertical bearing characteristics. Results indicate that large-diameter, super-long piles mainly bear loads through side friction, with the tip bearing less load. As load levels increase, axial force increases linearly above 40 m depth and becomes nonlinear below. Frictional resistance is significant below 40 m at 3,700 kN load. Parameter analysis shows that increasing pile length and diameter enhances bearing capacity, suggesting this method to improve pile foundation capacity in engineering.

Abstract Background Amylose, a prebiotic found in yams is known to be beneficial for the gut microflora and is particularly advantageous for diabetic patients’ diet. However, the genetic machinery underlying amylose production remains elusive. A comprehensive characterization of the genetic basis of amylose content in yam tubers is a prerequisite for accelerating the genetic engineering of yams with respect to amylose content variation. Results To uncover the genetic variants underlying variation in amylose content, we evaluated amylose content in freshly harvested tubers from 150 accessions of Dioscorea zingibensis. With 30,000 high-quality single nucleotide polymorphisms (SNP), we performed a genome-wide association analysis (GWAS). The population structure analysis classified the D. zingiberensis accessions into three groups. A total of 115 significant loci were detected on four chromosomes. Of these, 112 significant SNPs (log10(p) = 5, q-value

Abstract In this study, we prepared a bionic nanosystem of trastuzumab-functionalized SK-BR-3 cell membrane hybrid liposome-coated pyrotinib (Ptb-M-Lip-Her) for the treatment of HER2-positive breast cancer. Transmission electron microscopy, dynamic light scattering, polyacrylamide gel electrophoresis (SDS-PAGE) and western blotting were used to verify the successful preparation of Ptb-M-Lip-Her. In vitro drug release experiments proved that Ptb-M-Lip-Her had a sustained release effect. Cell uptake experiments and in vivo imaging experiments proved that Ptb-M-Lip-Her had good targeting ability to homologous tumor cells (SK-BR-3). The results of cell experiments such as MTT, flow cytometry, immunofluorescence staining and in vivo antitumor experiments showed that Ptb-M-Lip-Her could significantly promote apoptosis and inhibit the proliferation of SK-BR-3 cells. These results clearly indicated that Ptb-M-Lip-Her may be a promising biomimetic nanosystem for targeted therapy of HER2-positive breast cancer.

Abstract Aim To explore the views and experiences of formal caregivers caring for older inpatients with physical disabilities. Methods It was a qualitative phenomenological study. Using purposive sampling, twelve formal caregivers were chosen in a tertiary comprehensive hospital in Hangzhou, China. Semi-structured, face-to-face interviews were conducted, guided by open-ended questions that focused on gaining rich insights into participants’ views and experiences. Coding reliability thematic analysis was used to guide data analysis and categorize, based on Lazarus and Folkman’s theory of transactional coping. Results Four themes emerged from the data analysis: (1) Caregiving Threats. (2) motivations. (3) Responsibility Management. (4) Fear. Conclusion Despite facing significant pressure at work, formal caregivers of elderly inpatients with physical disabilities possess the drive and various coping strategies to excel in their role. Identifying caregivers’ experiences of care can be helpful in improving resilience to stress and maintaining stability in formal caregivers.

Osteoarthritis (OA) progresses due to the excessive generation of reactive oxygen and nitrogen species (ROS/RNS) and abnormal ATP energy metabolism related to the oxidative phosphorylation pathway in the mitochondria. Highly active single-atom nanozymes (SAzymes) can help regulate the redox balance and have shown their potential in the treatment of inflammatory diseases. In this study, we innovatively utilised ligand-mediated strategies to chelate Pt4+ with modified g-C3N4 by π–π interaction to prepare g–C3N4–loaded Pt single-atom (Pt SA/C3N4) nanozymes that serve as superoxide dismutase (SOD)/catalase (CAT) mimics to scavenge ROS/RNS and regulate mitochondrial ATP production, ultimately delaying the progression of OA. Pt SA/C3N4 exhibited a high loading of Pt single atoms (2.45 wt%), with an excellent photothermal conversion efficiency (54.71%), resulting in tunable catalytic activities under near-infrared light (NIR) irradiation. Interestingly, the Pt–N6 active centres in Pt SA/C3N4 formed electron capture sites for electron holes, in which g-C3N4 regulated the d-band centre of Pt, and the N-rich sites transferred electrons to Pt, leading to the enhanced adsorption of free radicals and thus higher SOD- and CAT-like activities compared with pure g-C3N4 and g–C3N4–loaded Pt nanoparticles (Pt NPs/C3N4). Based on the use of H2O2-induced chondrocytes to simulate ROS-injured cartilage in vitro and an OA joint model in vivo, the results showed that Pt SA/C3N4 could reduce oxidative stress-induced damage, protect mitochondrial function, inhibit inflammation progression, and rebuild the OA microenvironment, thereby delaying the progression of OA. In particular, under NIR light irradiation, Pt SA/C3N4 could help reverse the oxidative stress-induced joint cartilage damage, bringing it closer to the state of the normal cartilage. Mechanistically, Pt SA/C3N4 regulated the expression of mitochondrial respiratory chain complexes, mainly NDUFV2 of complex 1 and MT-ATP6 of ATP synthase, to reduce ROS/RNS and promote ATP production. This study provides novel insights into the design of artificial nanozymes for treating oxidative stress-induced inflammatory diseases.

Abstract Chronic non-communicable diseases (CNCDs) pose a significant public health challenge. Addressing this issue, there has been a notable breakthrough in the prevention and mitigation of NCDs through the use of antioxidants and anti-inflammatory agents. In this study, we aim to explore the effectiveness of Eupatorium adenophora Spreng leaves (EASL) as an antioxidant and anti-inflammatory agent, and its potential applications. To construct a cellular model of oxidative damage and inflammation, Caco-2 cells were treated with tert-butyl hydroperoxide (t-BHP). The biocompatibility of EASL-AE with Caco-2 cells was assessed using the MTT assay, while compatibility was further verified by measuring LDH release and the protective effect against oxidative damage was also assessed using the MTT assay. Additionally, we measured intracellular oxidative stress indicators such as ROS and 8-OHdG, as well as inflammatory pathway signalling protein NFκB and inflammatory factors TNF-α and IL-1β using ELISA, to evaluate the antioxidant and anti-inflammatory capacity of EASL-AE. The scavenging capacity of EASL-AE against free radicals was determined through the DPPH Assay and ABTS Assay. Furthermore, we measured the total phenolic, total flavonoid, and total polysaccharide contents using common chemical methods. The chemical composition of EASL-AE was analyzed using the LC–MS/MS technique. Our findings demonstrate that EASL-AE is biocompatible with Caco-2 cells and non-toxic at experimental levels. Moreover, EASL-AE exhibits a significant protective effect on Caco-2 cells subjected to oxidative damage. The antioxidant effect of EASL-AE involves the scavenging of intracellular ROS, while its anti-inflammatory effect is achieved by down-regulation of the NFκB pathway. Which in turn reduces the release of inflammatory factors TNF-α and IL-1β. Through LC–MS/MS analysis, we identified 222 compounds in EASL-AE, among which gentianic acid, procaine and L-tyrosine were the compounds with high antioxidant capacity and may be the effective constituent for EASL-AE with antioxidant activity. These results suggest that EASL-AE is a natural and high-quality antioxidant and anti-inflammatory biomaterial that warrants further investigation. It holds great potential for applications in healthcare and other related fields.

Abstract Intra-articular drugs used to treat osteoarthritis (OA) often suffer from poor pharmacokinetics and stability. Nano-platforms as drug delivery systems for drug delivery are promising for OA therapy. In this study, we reported an M1 macrophage-targeted delivery system Bai@FA-UIO-66-NH2 based on folic acid (FA) -modified metal-organic framework (MOF) loaded with baicalin (Bai) as antioxidant agent for OA therapy. With outstanding biocompatibility and high drug loading efficiency, Bai@FA-UIO-66-NH2 could be specifically uptaken by LPS-induced macrophages to serve as a potent ROS scavenger, gradually releasing Bai at the subcellular level to reduce ROS production, modulate macrophage polarization to M2, leading to alleviation of synovial inflammation in OA joints. The synergistic effect of Bai@FA-UIO-66-NH2 on macrophage polarization and ROS scavenging significantly improved the therapeutic efficacy of OA, which may provide a new insight into the design of OA precision therapy.

Abstract Background Hospice care professionals often experience trauma patient deaths and multiple patient deaths in a short period of time (more so than other nurses). This repeated exposure to the death process and the death of patients leads to greater psychological pressure on hospice care professionals. But at present, people pay more attention to the feelings and care burden of the family members of dying patients but pay less attention to medical staff. Thus, this study aimed to develop a scale on the burden of care for hospice care providers and assess the coping capacity of hospice professionals. Raising awareness of the psychological burden of hospice professionals. Methods Through a literature review, research group discussion, Delphi method and a pre-survey of professional coping skills among nurses, 200 hospice professionals who had received training in hospice care from pilot institutions engaged in or providing hospice care were selected for investigation. Cronbach’s α coefficient and split-half reliability were used to test the internal consistency of the scale, and content validity and explore factor analysis (EFA) were used to test the construct validity of the scale. Results Two rounds of Delphi methods were carried out, and the effective recovery rate was 100%. The expert authority coefficients of the two rounds were 0.838 and 0.833, respectively. The Kendall’s W coefficient of experts in the first round was 0.121 ~ 0.200 (P 0.4, and the factor loading of each item was also > 0.4. Conclusion The scale is an open-access, short, easy-to-administer scale. And which for assessing hospice care burden among hospice professionals developed in this study demonstrated strong reliability and validity. This tool can serve as a dependable instrument for evaluating the burden of hospice care for terminally ill patients by professionals in the hospice setting.

The growth of marine economy urgently needs non-toxic coatings. This study provides a novel and green coating that obtains outstanding antifouling performance by combining the low surface energy effect and the fluorescent effect. The coating was synthesized by reacting tetraphenylethylene (TPE) as the fluorescent component with poly(ethylene-co-tetrafluoroethylene) resin. The introduction of TPE provided the resin coating with lower surface energy and fluorescent properties, leading to improve the antifouling performance. This study indicates fluorescent TPE polymers for marine antifouling and opens new horizons for the exploitation of fluorescent antifouling coatings.

Formaldehyde is one of the most common indoor air pollutants that seriously damage human health. It is of significant importance to effectively remove indoor formaldehyde. In this work, a novel cement-based composite with ZIF-8@TiO2-coated activated carbon fibers (TiO2-ACFs) was prepared and shown to remove the indoor formaldehyde effectively. TiO2 was coated on ACFs via atomic layer deposition, and then ZIF-8 was grown on the surface of TiO2-ACFs. The ZIF-8@TiO2-ACFs were then mixed with cement slurry and thus formed a cement-based composite, which exhibited excellent formaldehyde removal performance. In particular, if assisted with UV light, the removal efficiency for formaldehyde by the cement-based composite showed an obvious increase.

Abstract In view of the fact that mulberry branch has not been effectively utilized and polysaccharide is one of the main active components in mulberry branch, this study aims to reveal the structure and immunomodulatory activity of its polysaccharide. A type of neutral polysaccharides, named mulberry branch polysaccharide-2 (MBP-2), was separated from mulberry branch using DEAE-52 and Sephadex G-100. As analyzed, they were mainly composed of glucose with a molecular weight of approximately 21.7 kDa. Methylation analysis demonstrated that MBP-2 primary contained a → 4)-α-d-Glcp-(1 → , α-d-Glcp-(1 → and → 4, 6)-α-d-Glcp-(1 → structure, which was validated by nuclear magnetic resonance (NMR). In addition, cellular experiments indicated that MBP-2 significantly enhanced the production of NO, TNF-α and IL-6 in RAW264.7 cells, unraveling the potential immunoregulatory activity of MBP-2. Further analysis showed that MBP-2 exerted their immunoregulatory activity mainly via binding with TLR4 to activate the downstream TRIF-dependent signaling pathways. Graphical Abstract

Infection with Plasmodium falciparum is often deadly when it results in cerebral malaria, which is associated with neuropathology described as an overwhelming inflammatory response and mechanical obstruction of cerebral microvascular. PI3Kγ is a critical component of intracellular signal transduction and plays a central role in regulating cell chemotaxis, migration, and activation. The purpose of this study was to examine the relationship between inhibiting the PI3Kγ pathway and the outcome of experimental cerebral malaria (ECM) in C57BL/6J mice infected with the mouse malaria parasite, Plasmodium berghei ANKA. We observed that oral administration of the PI3Kγ inhibitor IPI549 after infection completely protected mice from ECM. IPI549 treatment significantly dampened the magnitude of inflammatory responses, with reduced production of pro-inflammatory factors, decreased T cell activation, and altered differentiation of antigen-presenting cells. IPI549 treatment protected the infected mice from neuropathology, as assessed by an observed reduction of pathogenic T cells in the brain. Treating the infected mice with IPI549 three days after parasite inoculation improved the murine blood brain barrier (BBB) integrity and helped the mice pass the onset of ECM. Together, these data indicate that oral administration of the PI3Kγ inhibitor IPI549 has a suppressive role in host inflammation and alleviates cerebral pathology, which supports IPI549 as a new malaria treatment option with potential therapeutic implications for cerebral malaria.

Abstract Objective TQB3602 is a novel orally bioavailable proteasome inhibitor. This study is the first‐in‐human phase I clinical trial to evaluate the safety, tolerability, pharmacokinetics, and preliminary efficacy of TQB3602 in relapsed/refractory multiple myeloma (RRMM). Methods This is a multicenter phase I clinical trial consisting of the 3+3 dose‐escalation phase and dose expansion phase. Patients with MM who have received ≥2 prior antimyeloma therapies were enrolled. TQB3602 is administered at a dose of 0.5~7mg on days 1, 8, 15 in 28‐day cycle. Results Twenty‐five RRMM patients who relapsed or failed ≥2 lines of therapies were enrolled in the dose escalation phase. Two patients in the 7.0 mg dose group developed dose‐limiting toxicity events (one with grade 2 peripheral neuropathy [PN] complicated by pain and one with diarrhea and abdominal pain), leading to a maximum tolerated dose of 6.0 mg. Any‐grade adverse events (AEs) occurred in 24 (96.0%) patients, while grade ≥3 AEs occurred in 13 (52.0%). The most common grade ≥3 AEs was anemia (6, 24.0%). The incidence rate of PN was 16% with no grade ≥3 PN occurred. TQB3602 was rapidly absorbed, resulting in a time‐to‐plasma peak concentration of 0.8–1.5 h. The mean half‐life was approximately 82 h. The AUClast and Cmax were approximately 1.9 times higher on day 15 than on day 1. Among 22 response‐evaluable patients, 63.7% achieved stable disease or better. Conclusions TQB3602 is well tolerated, with a favorable neurotoxicity profile, and has shown preliminary efficacy in patients with RRMM. The anticipated therapeutic dose was 6 mg and was adopted for an ongoing dose‐expansion phase.

Addressing the pressing need for optimized airport road maintenance, this study harnesses a machine-learning approach to predict road service life. This study introduces a novel EO-LightGBM model, refined through meticulous parameter optimization, feature selection, and model integration. The relationship between the characteristics of concrete structures and the service life of airport roads was deeply explored and revealed a significant correlation between concrete structural characteristics—compressive strength, flexural strength, density, moisture content, and temperature resistance—and road longevity. The established model not only accurately predicts the service life of airport roads, but also has good stability and adaptability. This study provides a new method for predicting and optimizing the service life of airport roads and provides effective support for the design, construction, and maintenance of airport roads.

Maillard reaction products (MRPs) derived from rice protein isolate hydrolysate and D-xylose, with or without L-cysteine, were developed as a potential meat flavoring. The combined impact of temperature (80–140 °C) and cysteine on fundamental physicochemical characteristics, antioxidant activity, and flavor of MRPs were investigated through assessments of pH, color, UV–visible spectra, fluorescence spectra, free amino acids, volatile compounds, E-nose, E-tongue, and sensory evaluation. Results suggested that increasing temperature would reduce pH, deepen color, promote volatile compounds formation, and reduce the overall umami and bitterness. Cysteine addition contributed to the color inhibition, enhancement of DPPH radical-scavenging activity and reducing power, improvement in mouthfulness and continuity, reduction of bitterness, and the formation of sulfur compounds responsible for meaty flavor. Overall, MRPs prepared at 120 °C with cysteine addition could be utilized as a potential meat flavoring with the highest antioxidant activity and relatively high mouthfulness, continuity, umami, meaty aroma, and relatively low bitterness.

Background: Head and neck cancer is the sixth most common malignancy worldwide, and oral squamous cell carcinoma (OSCC) is the most common head and neck cancer, being one of the leading causes of cancer morbidity and mortality worldwide. CC Chemokine receptor 7(CCR7) is a multifunctional G protein-coupled trans-membrane chemokine that affects immune cell chemotaxis, migration, and cancer progression through its interaction with its ligands C-C motif chemokine ligand 19(CCL19) and C-C motif chemokine ligand 21(CCL21). Numerous studies have demonstrated the involvement of CCR7 in the malignant progression of a variety of cancers, reflecting the pro-cancer properties of CCR7. The Cancer Genome Atlas data suggests CCR7 has elevated expression in oral cancer. Specifically, CCR7 expression in tumor microenvironment (TME) may regulate the ability of some immune cells to engage in anti-tumor immune responses. Since CD8+ T cells have become a key immunotherapeutic target, the role of CCR7 in antitumor immune response of naïve CD8+ T cells in TME has not been thoroughly investigated. Methods: A CCR7 knockout mouse model was constructed, and the mechanism of ccr7 on the regulation of tumor microenvironment by naïve CD8+ T cells was verified under the guidance of single-cell RNA sequencing combined with in vivo animal experiments and in vitro cell experiments. Results: CCR7 is knocked out with impaired tumor growth and altered CD8+ T cell profiles, revealing the importance of this protein in OSCC. Conclusions: Inhibition of CCR7 enhances CD8+ T cell activation, proliferation, and anti-tumor function, suggesting its potential as a therapeutic target.

Abstract Background Schizothorax o’connori is an endemic fish distributed in the upper and lower reaches of the Yarlung Zangbo River in China. It has experienced a fourth round of whole gene replication events and is a good model for exploring the genetic differentiation and environmental adaptability of fish in the Qinghai-Tibet Plateau. The uplift of the Qinghai-Tibet Plateau has led to changes in the river system, thereby affecting gene exchange and population differentiation between fish populations. With the release of fish whole genome data, whole genome resequencing has been widely used in genetic evolutionary analysis and screening of selected genes in fish, which can better elucidate the genetic basis and molecular environmental adaptation mechanisms of fish. Therefore, our purpose of this study was to understand the population structure and adaptive characteristics of S. o’connori using the whole-genome resequencing method. Results The results showed that 23,602,746 SNPs were identified from seven populations, mostly distributed on chromosomes 2 and 23. There was no significant genetic differentiation between the populations, and the genetic diversity was relatively low. However, the Zangga population could be separated from the Bomi, Linzhi, and Milin populations in the cluster analysis. Based on historical dynamics analysis of the population, the size of the ancestral population of S. o’connori was affected by the late accelerated uplift of the Qinghai Tibet Plateau and the Fourth Glacial Age. The selected sites were mostly enriched in pathways related to DNA repair and energy metabolism. Conclusion Overall, the whole-genome resequencing analysis provides valuable insights into the population structure and adaptive characteristics of S. o’connori. There was no obvious genetic differentiation at the genome level between the S. o’connori populations upstream and downstream of the Yarlung Zangbo River. The current distribution pattern and genetic diversity are influenced by the late accelerated uplift of the Qinghai Tibet Plateau and the Fourth Ice Age. The selected sites of S. o’connori are enriched in the energy metabolism and DNA repair pathways to adapt to the low temperature and strong ultraviolet radiation environment at high altitude.

Abstract Background The blood-based biomarkers are approaching the clinical practice of Alzheimer’s disease (AD). Chronic kidney disease (CKD) has a potential confounding effect on peripheral protein levels. It is essential to characterize the impact of renal function on AD markers. Methods Plasma phospho-tau181 (P-tau181), and neurofilament light (NfL) were assayed via the Simoa HD-X platform in 1189 dementia-free participants from the Shanghai Aging Study (SAS). The estimated glomerular filter rate (eGFR) was calculated. The association between renal function and blood NfL, P-tau181 was analyzed. An analysis of interactions between various demographic and comorbid factors and eGFR was conducted. Results The eGFR levels were negatively associated with plasma concentrations of NfL and P-tau181 (B = − 0.19, 95% CI − 0.224 to − 0.156, P

Abstract Lack of specific biomarkers and effective drug targets constrains therapeutic research in breast cancer (BC). In this regard, therapeutic modulation of damage-associated molecular patterns (DAMPs)-induced immunogenic cell death (ICD) may help improve the effect of immunotherapy in individuals with BC. The aim of this investigation was to develop biomarkers for ICD and to construct ICD-related risk estimation models to predict prognosis and immunotherapy outcomes of BC. RNA-seq transcriptome information and medical data from individuals with BC (n = 943) were obtained from TCGA. Expression data from a separate BC cohort (GEO: GSE20685) were used for validation. We identified subtypes of high and low ICD gene expression by consensus clustering and assessed the connection between ICD subtypes and tumor microenvironment (TME). In addition, different algorithms were used to construct ICD-based prognostic models of BC. BC samples were categorized into subtypes of high and low ICD expression depending on the expression of genes correlated with ICD. The subtype of ICD high-expression subtypes are correlated with poor prognosis in breast cancer, while ICD low-expression subtypes may predict better clinical outcomes. We also created and verified a predictive signature model depending on four ICD-related genes (ATG5, CD8A, CD8B, and HSP90AA1), which correlates with TME status and predicts clinical outcomes of BC patients. We highlight the connection of ICD subtypes with the dynamic evolution of TME in BC and present a novel ICD-based prognostic model of BC. In clinical practice, distinction of ICD subtype and assessment of ICD-related biomarkers should help guide treatment planning and improve the effectiveness of tumor immunotherapy.

Abstract Purpose Anxiety is a common emotion experienced by patients with prostate cancer (PCa), and can be exacerbated by testing the prostate-specific antigen (PSA) index. The Memorial Anxiety Scale for Prostate Cancer (MAX-PC) was developed to assess the cancer-specific anxiety of these patients, but lack of appropriate thresholds for this scale limits its use. This study aimed to utilize ROC curve analysis to identify the best cut-off values for the Chinese version of the MAX-PC scale. Methods A cross-sectional survey was conducted using the Chinese version of the MAX-PC scale and the Generalized Anxiety Disorder Scale (GAD). ROC curve analysis, Youden index, Kappa consistency test and McNemar test were used for the optimal cutoff points for screening mild, moderate, and severe cancer-specific anxiety levels in patients with PCa, on the Chinese version of the MAX-PC scale. Results Two hundred eighty-seven patients with PCa completed the survey. The appropriate cut-off values for the MAX-PC scale for screening patients with PCa for cancer-specific anxiety were 20, 28, and 38 for mild, moderate, and severe anxiety, respectively with the highest Youden indices. The Kappa and McNemar’s test showed the best level of consistency with values of 0.627, 0.580, and 0.606 for screening mild, moderate, and severe anxiety, respectively. Conclusions The scores 20, 28, and 38 are the best cut-off values for the Chinese version of the MAX-PC scale. This scale should be used for screening cancer-specific anxiety for patients with PCa to assess and evaluate their anxiety levels and provide targeted interventions.

Abstract The Beijing-Hangzhou Grand Canal carries unique social and cultural significance as a world cultural heritage, but with the acceleration of global urbanization, it has potentially severe environmental risks under continuous anthropogenic disturbances. Therefore, to protect the ecological and cultural values of the Grand Canal, it is necessary to assess the corresponding relationship of water quality to land use and the perception of ecosystem services that focus on cultural ecosystem services (CES). This study aims to analyze the water quality response to land use in the Beijing-Hangzhou Grand Canal, describe the land use types closely related to water quality, and propose corresponding management strategies for enhancing CES. This study investigated the impacts of land use structure and landscape pattern on water quality by calculating the correlation between land use structure and landscape pattern indices and water quality in buffer zones of different distances on both sides of the canal. The results show that green land dominates the land use structure and can effectively reduce water pollution in the canal. On the other hand, urban impervious surfaces showed a significant positive correlation with pollution contributing to low water quality. We accessed the impact of water quality on the perception of CES in the Beijing-Hangzhou Grand Canal and proposed optimization strategies for promoting CES. Both content analysis and thematic analysis were applied to analyze the impact of the water environment quality of the Beijing-Hangzhou Grand Canal on the perception of CES. We found that the perceptions of CES along the Beijing-Hangzhou Grand Canal are associated with the public’s opinions on its cultural heritage services and artistic inspiration services. The perceptions of CES are closely related to the quality of the water environment and riparian greenness, which affect the values of cultural heritage and conservation of the Beijing-Hangzhou Grand Canal.

ObjectiveOur aim was to develop a nomogram that integrates clinical and radiological data obtained from computed tomography (CT) scans, enabling the prediction of chronic hydrocephalus in patients with aneurysmal subarachnoid hemorrhage (aSAH).MethodA total of 318 patients diagnosed with subarachnoid hemorrhage (SAH) and admitted to the Department of Neurosurgery at the Affiliated People’s Hospital of Jiangsu University between January 2020 and December 2022 were enrolled in our study. We collected clinical characteristics from the hospital’s medical record system. To identify risk factors associated with chronic hydrocephalus, we conducted both univariate and LASSO regression models on these clinical characteristics and radiological features, accompanied with penalty parameter adjustments conducted through tenfold cross-validation. All features were then incorporated into multivariate logistic regression analyses. Based on these findings, we developed a clinical-radiological nomogram. To evaluate its discrimination performance, we conducted Receiver Operating Characteristic (ROC) curve analysis and calculated the Area Under the Curve (AUC). Additionally, we employed calibration curves, and utilized Brier scores as an indicator of concordance. Additionally, Decision Curve Analysis (DCA) was performed to determine the clinical utility of our models by estimating net benefits at various threshold probabilities for both training and testing groups.ResultsThe study included 181 patients, with a determined chronic hydrocephalus prevalence of 17.7%. Univariate logistic regression analysis identified 11 potential risk factors, while LASSO regression identified 7 significant risk factors associated with chronic hydrocephalus. Multivariate logistic regression analysis revealed three independent predictors for chronic hydrocephalus following aSAH: Periventricular white matter changes, External lumbar drainage, and Modified Fisher Grade. A nomogram incorporating these factors accurately predicted the risk of chronic hydrocephalus in both the training and testing cohorts. The AUC values were calculated as 0.810 and 0.811 for each cohort respectively, indicating good discriminative ability of the nomogram model. Calibration curves along with Hosmer-Lemeshow tests demonstrated excellent agreement between predicted probabilities and observed outcomes in both cohorts. Furthermore, Brier scores (0.127 for the training and 0.09 for testing groups) further validated the predictive performance of our nomogram model. The DCA confirmed that this nomogram provides superior net benefit across various risk thresholds when predicting chronic hydrocephalus. The decision curve demonstrated that when an individual’s threshold probability ranged from 5 to 62%, this model is more effective in predicting the occurrence of chronic hydrocephalus after aSAH.ConclusionA clinical-radiological nomogram was developed to combine clinical characteristics and radiological features from CT scans, aiming to enhance the accuracy of predicting chronic hydrocephalus in patients with aSAH. This innovative nomogram shows promising potential in assisting clinicians to create personalized and optimal treatment plans by providing precise predictions of chronic hydrocephalus among aSAH patients.

Bovine tuberculosis (bTB) is a chronic zoonotic disease caused by Mycobacterium bovis. A large number of cattle are infected with bTB every year, resulting in huge economic losses. How to control bTB is an important issue in the current global livestock economy. In this study, the original transcriptome sequences related to this study were obtained from the dataset GSE192537 by searching the Gene Expression Omnibus (GEO) database. Our differential gene analysis showed that there were obvious biological activities related to immune activation and immune regulation in the early stage of bTB. Immune-related biological processes were more active in the early stage of bTB than in the late. There were obvious immune activation and immune cell recruitment in the early stage of bTB. Regulations in immune receptors are associated with pathophysiological processes of the early stage of bTB. A gene module consisting of 236 genes significantly related to the early stage of bTB was obtained by weighted gene co-expression network analysis, and 18 hub genes were further identified as potential biomarkers or therapeutic targets. Finally, by random forest algorithm and logistic regression modeling, FCRL1 was identified as a representative mRNA marker in early bTB blood. FCRL1 has the potential to be a diagnostic biomarker in early bTB.

The risk prognosis model is a statistical model that uses a set of features to predict whether an individual will develop a specific disease or clinical outcome. It can be used in clinical practice to stratify disease severity and assess risk or prognosis. With the advancement of large-scale second-generation sequencing technology, along Prognosis models for osteosarcoma are increasingly being developed as large-scale second-generation sequencing technology advances and clinical and biological data becomes more abundant. This expansion greatly increases the number of prognostic models and candidate genes suitable for clinical use. This article will present the predictive effects and reliability of various prognosis models, serving as a reference for their evaluation and application.

Surface‐enhanced Raman scattering (SERS) is a versatile spectroscopic technique, which plays a crucial role in enhancing analytical sensitivity, investigating interfacial reaction mechanisms, enabling biosensing, and fostering efficient catalysis. Currently, the common SERS substrates are primarily metal nanostructures, which entail high manufacturing costs, complex processes, and the metal surface undergo change over time and with environmental conditions. These issues limit the development of SERS technology. In this work, a nitrogen‐doped graphene (N‐graphene) hydrangea was synthesized on a silicon (Si) substrate using plasma‐assisted chemical vapor deposition (PACVD), forming an N‐graphene hydrangea/Si hybrid structure as a SERS substrate. This substrate offers the advantages of high stability, ultra‐sensitivity, and reusability. The three‐dimensional nano‐cavity structure of graphene can increase the interaction between light and graphene, resulting in an increased localized electric field. Combining theoretical simulation analysis, the introduction of nitrogen (N) elements adjusts the Fermi level of graphene, promoting efficient charge transfer. In practical scenarios, Di(2‐ethylhexyl) phthalate (DEHP), a commonly used plasticizer, has raised concerns due to its potential as an endocrine disruptor and carcinogen. The as‐prepared SERS substrate achieves a remarkable detection limit of as low as 10−8 m for DEHP, providing significant support for environmental conservation and human health.

Abstract The two-spotted spider mite (TSSM, Tetranychus urticae Koch) is a significant agricultural pest, particularly in strawberries. Management of TSSM has traditionally relied on synthetic acaricides, but to mitigate dependency on these chemicals, the control of TSSM on strawberry is often combined with biological control measures and chemical control strategies. The predatory mite, Phytoseiulus persimilis, is a promising biological control agent, preying on all TSSM developmental stages. In this study, we examined the toxicity of six common acaricides on TSSM and P. persimilis, and cyetpyrafen was selected due to its highest relative toxicity value. Then, we examined the compatibility of cyetpyrafen with P. persimilis for TSSM management on strawberries. The results suggested that cyetpyrafen revealed no substantial differences in prey consumption or longevity when compared to the control, though minor effects on the development durations of protonymphs and deutonymphs were noted in the subsequent generation. Additionally, cyetpyrafen's toxicity on key pollinators, such as Apis mellifera and Bombus terrestris, was found to be low. Thus, an integrated strategy combining cyetpyrafen (0.83 mg/L) with P. persimilis (predator–prey ratio of 1:30) was examined under laboratory and field conditions. Laboratory trials demonstrated a reduction in mites per leaf from 32.72 to 14.50 within 3 days, correlating to a 70.23% control efficiency. This efficacy increased to 96.04% by day 9 and was sustained until the experiment concluded on day 27. Field trials similarly showed a reduction in TSSM from 53.93 to 9.63 mites/leaf by day 6, achieving an 83.64% control efficiency, and culminated in a 98.46% reduction by day 10. These findings suggested that an integrated approach utilizing cyetpyrafen in conjunction with P. persimilis can be an effective alternative for TSSM management on strawberry plants.

Abstract The rise of machine learning has fueled the discovery of new materials and, especially, metamaterials—truss lattices being their most prominent class. While their tailorable properties have been explored extensively, the design of truss-based metamaterials has remained highly limited and often heuristic, due to the vast, discrete design space and the lack of a comprehensive parameterization. We here present a graph-based deep learning generative framework, which combines a variational autoencoder and a property predictor, to construct a reduced, continuous latent representation covering an enormous range of trusses. This unified latent space allows for the fast generation of new designs through simple operations (e.g., traversing the latent space or interpolating between structures). We further demonstrate an optimization framework for the inverse design of trusses with customized mechanical properties in both the linear and nonlinear regimes, including designs exhibiting exceptionally stiff, auxetic, pentamode-like, and tailored nonlinear behaviors. This generative model can predict manufacturable (and counter-intuitive) designs with extreme target properties beyond the training domain.

Abstract Background Liver cancer stem cells (LCSCs) play an important role in hepatocellular carcinoma (HCC), but the mechanisms that link LCSCs to HCC metastasis remain largely unknown. This study aims to reveal the contributions of NRCAM to LCSC function and HCC metastasis, and further explore its mechanism in detail. Methods 117 HCC and 29 non-HCC patients with focal liver lesions were collected and analyzed to assess the association between NRCAM and HCC metastasis. Single-cell RNA sequencing (scRNA-seq) was used to explore the biological characteristics of cells with high NRCAM expression in metastatic HCC. The role and mechanism of NRCAM in LCSC dissemination and metastasis was explored in vitro and in vivo using MYC-driven LCSC organoids from murine liver cells. Results Serum NRCAM is associated with HCC metastasis and poor prognosis. A scRNA-seq analysis identified that NRCAM was highly expressed in LCSCs with MYC activation in metastatic HCC. Moreover, NRCAM facilitated LCSC migration and invasion, which was confirmed in MYC-driven LCSC organoids. The in vivo tumor allografts demonstrated that NRCAM mediated intra-hepatic/lung HCC metastasis by enhancing the ability of LCSCs to escape from tumors into the bloodstream. Nrcam expression inhibition in LCSCs blocked HCC metastasis. Mechanistically, NRCAM activated epithelial-mesenchymal transition (EMT) and metastasis-related matrix metalloproteinases (MMPs) through the MACF1 mediated β-catenin signaling pathway in LCSCs. Conclusions LCSCs typified by high NRCAM expression have a strong ability to invade and migrate, which is an important factor leading to HCC metastasis.

Abstract Background The widely reported associations between body mass index (BMI) and various chronic diseases, such as hypertension and asthma, have garnered significant attention. Nonetheless, there remains a dearth of research dedicated to understanding the health impacts of medical school on the students, who experience considerable academic pressure. In that context, this study was driven by the goal of investigating the intricate interplay between BMI, blood pressure (BP), and vital capacity among medical students. Methods This study included a cohort of 843 medical students enrolled at Southern Medical University who were selected through random cluster sampling. Within this cohort, measurements of height, weight, BP, and vital capacity were taken. Subsequently, both BMI and vital capacity index (VCI) were calculated for each participant. By categorizing the subjects into four groups according to BMI classifications, a comprehensive analysis that included correlation assessments and binomial logistic regression was conducted. Results Within the participant pool, 9.4% and 3.8% of participants were classified as overweight and obese, respectively. Additionally, the prevalence of prehypertension, hypertension, and poor VCI was 18.1%, 2.7%, and 13.5%, respectively. Notably, male students exhibited a higher prevalence of the aforementioned health issues than their female counterparts. Correlation analysis revealed that BMI displayed positive associations with systolic blood pressure (SBP), diastolic blood pressure (DBP), and vital capacity (r = 0.372, 0.257, 0.428; P

Abstract Fusarium oxysporum f. sp. cubense (Foc) causes Fusarium wilt of banana (Musa spp.), a notorious soil-borne vascular fungal disease threatening the global banana industry. Phytopathogens secrete effectors to suppress plant immunity. However, little is known about the effectors of Foc race 4 (Foc4). In this study, we built a streamlined screening system (candidate effector prediction, RNA-seq-based expression level analysis, and cell death manipulative activity assessment based on transient expression in Nicotiana benthamiana) to identify candidate virulence-related effectors. In total, 80 candidate effector genes (CEGs) differentially expressed during plant colonization were predicted; 12 out of 15 characterized CEGs, including FoSSP17, could suppress BAX-triggered programmed cell death (PCD) in N. benthamiana and were induced during the infection of plants. FoSSP17 encodes a novel protein conserved in the Fusarium genus. FoSSP17 gene deletion mutants were not affected in vegetative growth and conidiation but showed reduced virulence. Furthermore, the deletion mutants triggered higher expression levels of host defense-related genes including PR1, PR3, PR5, and PR10. Signal peptide activity assay and subcellular localization assay suggested that FoSSP17 is a conventional secretory protein that exerts cell-death-suppressive activity inside plant cells. In addition, FoSSP17 suppressed pattern-triggered immunity in plants by inhibiting reactive oxygen species (ROS) accumulation, reducing callose deposition, and suppressing the expression of NbLOX and NbERF1 genes related to jasmonic acid (JA)-pathway and ethylene (ET)-pathway, respectively. Overall, a systemic screening of Foc4 candidate effectors reveals that FoSSP17 contributes to the virulence of Foc4 and suppresses pattern-triggered immunity in plants.

Abstract Aim To develop a Chinese version of the return‐to‐work self‐efficacy (RTW‐SE‐11) and verify its reliability and validity. Design A validation study. Methods The RTW‐SE‐11 was translated into Chinese according to the Brislin's model, and then the semantic adjustment of questionnaire was carried out through multi‐field expert evaluation and preliminary investigation. Results All 11 items of the original questionnaire were retained. Content validity index (CVI) of the Chinese version of RTW‐SE‐11 indicated good validity, with Inter‐rater Agreement (IR) of 0.97, item CVI of 0.90–1.00 and questionnaire CVI of 0.91. Cronbach's α coefficient of RTW‐SE‐11 (Chinese version) was 0.923, suggesting high internal consistency, with test–retest reliability of 0.799 and half‐fold reliability of 0.926. Patient or public contribution: The Chinese version of the RTW‐SE‐11 questionnaire confirmed good reliability and validity for the assessment of return to work self‐efficacy in Chinese breast cancer patients.

Injectable hydrogels show great promise for bone tissue engineering applications due to their high biocompatibility and drug delivery capabilities. The bone defects in osteoporosis are usually characterized by an oxidative and inflammatory microenvironment that impairs the regeneration capability of bone tissues. To attenuate the reactive oxygen species (ROS) and promote bone regeneration, an anti-oxidative hydrogel with osteogenic capacity was developed in this study. The poorly water soluble, natural antioxidant, resveratrol, was encapsulated in thiolated Pluronic F-127 micelles with over 50-times-enhanced solubility. The injectable hydrogel was facilely formed because of the new thioester bond between the free thiol group in modified F-127 and the arylate group in hyaluronic acid (HA)–acrylate. The resveratrol-loaded hydrogel showed good viscoelastic properties and in vitro stability and was cyto-compatible with bone-marrow-derived mesenchymal stem cells (BMSCs). The hydrogel allowed for a sustained release of resveratrol for at least two weeks and effectively enhanced the osteogenic differentiation of BMSCs by the up-regulation of osteogenic markers, including ALP, OCN, RUNX-2, and COL1. Moreover, the hydrogel exhibited anti-oxidative and anti-inflammatory abilities through the scavenging of intracellular ROS in RAW264.7 cells and inhibiting the gene expression and secretion of pro-inflammatory cytokines TNF-α and IL-1β under LPS exposure. In summary, the results suggest that our multifunctional hydrogel loaded with resveratrol bearing osteogenic, anti-oxidative, and anti-inflammatory actions is easily prepared and represents a promising resveratrol delivery platform for the repair of osteoporotic bone defects.

The underwater curing agents have demonstrated promising potential in various applications, especially in underwater repair engineering, yet have proven considerable challenging. Here, we report a cardanol-based curing agent for epoxy resin that achieves robust adhesion to steel and concrete substrates both in air and underwater. Cardanol, paraformaldehyde, and m-phenyldimethylamine are selected as the polymeric monomers to synthesize curing agent by Mannich reaction in the absence of chemical cross-linker agents. The coating is completely cured within 46 ± 1 min in air and 54 ± 2 min under water with an adhesion of 0 or 1 and a hardness of 5H. The impact strength, shear strength, and tensile strength of coating on underwater concrete were 9.58 ± 0.41 kJ·m−2, 13.1 ± 0.3, and 10.5 ± 0.2 MPa, respectively, demonstrating exceptional flexibility and mechanical strength as well as favorable hydrophobicity. This work paves the way for the rehabilitation of underwater drainage network for urban infrastructure and water conservancy projects.

Industry 4.0 technologies have been gaining significant momentum in recent years. Despite widespread adoption, many companies struggle with the successful implementation of these technologies. This study aims to identify the critical success factors for implementing Industry 4.0 technologies and to examine the effects of various factor combinations. Using the technology–organization–environment framework and the practice-based view, this paper proposes a comprehensive research model. This study employs a hybrid approach combining structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to analyze survey data collected from 202 Chinese manufacturing firms. The SEM results indicate that top management support, technology competence, supplier support, and pilot projects are significantly associated with successful implementation. However, the fsQCA results reveal that individual factors alone are insufficient for success; rather, it is the combinations of these factors that drive successful implementation. Specifically, three key combinations lead to success: (1) top management support and technology competence; (2) top management support and supplier support; and (3) technology competence, supplier support, and pilot projects. By recognizing these combinations, manufacturing firms can develop more effective implementation strategies for Industry 4.0 technologies.

In the era of Industry 4.0, digital twin technology is revolutionizing traditional manufacturing paradigms. However, the adoption of this technology in modern manufacturing systems is fraught with challenges due to the scarcity of labeled data. Specifically, existing supervised machine learning algorithms, with their reliance on voluminous training data, find their applicability constrained in real-world production settings. This paper introduces an unsupervised 3D reconstruction approach tailored for industrial applications, aimed at bridging the data void in creating digital twin models. Our proposed model, by ingesting high-resolution 2D images, autonomously reconstructs precise 3D digital twin models without the need for manual annotations or prior knowledge. Through comparisons with multiple baseline models, we demonstrate the superiority of our method in terms of accuracy, speed, and generalization capabilities. This research not only offers an efficient approach to industrial 3D reconstruction but also paves the way for the widespread adoption of digital twin technology in manufacturing.

Meropenem is an ultrabroad-spectrum antimicrobial agent that is often recommended for the treatment of bacterial meningitis (BM) in children. However, a subtherapeutic phenomenon occurred in BM children complicated with augmented renal clearance (ARC) at the recommended dose of meropenem. To support its pharmacokinetics, a sensitive, fast and robust ultra-liquid chromatography–tandem mass spectrometry (UPLC–MS/MS) method was developed to measure meropenem concentrations in serum and cerebrospinal fluid (CSF). The method involved protein precipitation, and samples were diluted with a large proportion of water to eliminate solvent effects. The separation of samples was performed on a Waters Acquity™ BEH C18 column (2.1 × 50 mm i.d., 1.7 μm) with a gradient profile. The mobile phases were formic acid–water (1:1000, v/v) and acetonitrile. The linear range was good, with a concentration range of 0.100–100 μg/mL for serum and 0.0400–20.0 μg/mL for CSF. The intra-day and inter-day precisions were less than 8.0%, and the intra-day and inter-day accuracies varied −6.6% from 6.5% for the both serum and CSF. The selectivity, carry-over, dilution integrity, matrix effect, recovery and stability were validated according to international guidelines. The developed UPLC–MS/MS method successfully determined the meropenem concentrations in the serum and CSF of children with BM complicated with ARC. The results indicated that under the recommended dosing regimen (40 mg/kg every 8 h), the time to reach the effective treatment target of 50%T > MIC was only approximately 3 h and lower CSF concentrations of meropenem were observed in children with BM with ARC.

ObjectiveThe objective of this study was to investigate the effectiveness of a machine learning algorithm in diagnosing OSA in children based on clinical features that can be obtained in nonnocturnal and nonmedical environments.Patients and methodsThis study was conducted at Beijing Children's Hospital from April 2018 to October 2019. The participants in this study were 2464 children aged 3–18 suspected of having OSA who underwent clinical data collection and polysomnography(PSG). Participants’ data were randomly divided into a training set and a testing set at a ratio of 8:2. The elastic net algorithm was used for feature selection to simplify the model. Stratified 10-fold cross-validation was repeated five times to ensure the robustness of the results.ResultsFeature selection using Elastic Net resulted in 47 features for AHI ≥5 and 31 features for AHI ≥10 being retained. The machine learning model using these selected features achieved an average AUC of 0.73 for AHI ≥5 and 0.78 for AHI ≥10 when tested externally, outperforming models based on PSG questionnaire features. Linear Discriminant Analysis using the selected features identified OSA with a sensitivity of 44% and specificity of 90%, providing a feasible clinical alternative to PSG for stratifying OSA severity.ConclusionsThis study shows that a machine learning model based on children's clinical features effectively identifies OSA in children. Establishing a machine learning screening model based on the clinical features of the target population may be a feasible clinical alternative to nocturnal OSA sleep diagnosis.

Three reinforcement ratios (0, 50, and 100%) of carbon fiber reinforced plastics (CFRP) were selected to improve the mechanical properties of recycled brick concrete in this study. Utilizing axial compression test, X-ray diffractometer analysis, the evolution of parameters such as compressive strength, peak stress, and elastic modulus of reclaimed concrete were analyzed. The reclaimed brick concrete’ stress distribution and damage mechanism were revealed. The aggregate internal failure and CFRP reinforcement effect mechanism are discussed. The finite element model of red brick concrete reinforced by CFRP under uniaxial compression is established. The constitutive model for CFRP-reinforced recycled brick concrete is proposed.

Articular cartilage regeneration is still a difficult task due to the cartilage’s weak capacity for self-healing and the effectiveness of the available therapies. The engineering of cartilage tissue has seen widespread use of stem cell-based therapies. However, efficient orientation of line-specific bone marrow mesenchymal stem cells (BMSCs) to chondrogenesis and maintenance of chondrogenic differentiation challenged stem cell-based therapy. Herein, we developed a Fe-based metal-organic framework (MOF) loaded with hematoporphyrin monomethyl ether (HMME) and cartilage-targeting arginine-aspartate-glycine (RGD) peptide to form MOF-HMME-RGD sonosensitizer to regulate BMSCs chondrogenic differentiation for cartilage regeneration via the modulation of reactive oxygen species (ROS). By using sonodynamic therapy (SDT), the MOF-HMME-RGD demonstrated favorable biocompatibility, could generate a modest amount of ROS, and enhanced BMSCs chondrogenic differentiation through increased accumulation of glycosaminoglycan, an ECM component specific to cartilage, and upregulated expression of key chondrogenic genes (ACAN, SOX9, and Col2a1). Further, transplanted BMSCs loading MOF-HMME-RGD combined with SDT enhanced cartilage regeneration for cartilage defect repair after 8 weeks into treatment. This synergistic strategy based on MOF nanoparticles provides an instructive approach to developing alternative sonosensitizers for cartilage regeneration combined with SDT.

The explosive development of artificial intelligence technology greatly promotes the intelligent construction of museums and strengthens their cultural inheritance role. This paper takes artificial intelligence technology as its guide, analyzes the advantages of AI technology in the intelligent museum, and establishes the specific structure of an intelligent museum by combining VR technology. Wisdom Museum can realize the effective repair and presentation of cultural relics data. This paper uses three-dimensional laser scanning technology to obtain cultural relics point cloud data, repair the holes in the point cloud data through RBF, optimize the point cloud data by combining texture mapping, and input the optimized data into the GC-GAN model to realize the three-dimensional digital repair of cultural relics images. Moreover, the smart museum’s intelligent interaction system is built by combining virtual reality technology and related equipment. Taking Dunhuang mural point cloud data as an example, the number of point clouds of the RBF hole repair algorithm differs from the original data by only 5.86%, and the SSIM and PSNR values on the repaired portraits are 0.83 and 26.36 dB, respectively. The SUS total score for the user on the intelligent interactive system is 73.875, and the UEQ factor scores are averaged out at 1-3 points. The creation of a smart museum can be realized using AI technology, providing users with an immersive cultural relics viewing experience and activating the vitality of all kinds of cultural relics in the museum.

This study explores the peer and economic effects of corporate poverty alleviation behavior. Using the data of A-share non-financial listed corporates in Shanghai and Shenzhen of China from 2016 to 2020, the empirical analysis of this study finds that: corporate poverty alleviation behavior has significant peer effects; the guidance of local poverty alleviation policies weakens the peer effects of corporate poverty alleviation behavior; compared to private enterprises, the poverty alleviation behavior of the peer firms has a more significant impact on state-owned enterprises; and corporate poverty alleviation behavior can result in the backflow of economic benefits and achieve the organic unity of economic and social benefits. The purpose of this paper is to explore the peer effects of corporate poverty alleviation behaviors through empirical analysis using available public data. The results of the study not only increase the motivation of corporate to participate in poverty alleviation from a peer effects perspective, but also reveal key factors for sustaining corporate poverty alleviation behaviors.

Based on deep learning, this study explores a teaching model to promote college students’ English translation ability with the support of information technology. It mainly adopts the neural machine translation algorithm to make the training samples constitute data nodes with semantic feature-carrying properties through the profound training of semantic feature quantity. It then gets the best English translation utterance that recognizes the translated information. Using a combination of quantitative and qualitative methods, we explored the impact of deep learning strategies on English translation teaching in colleges and universities, as well as the evaluation of practical effects. The results of the study show that under the deep learning teaching mode, the English translation scores of college students are improved by 9.085 points, which is a significant difference (P=0.018) compared to the traditional teaching mode, indicating the excellent performance of the strategy in English translation teaching.

The emergence of the ChatGPT language model has sparked significant interest in educational circles, thanks to its capabilities in generating text, understanding context, and engaging in logical reasoning and conversation. This study explores the impact of ChatGPT on English writing, integrating statistical language models and TF-IDF word frequency analysis to develop a method for identifying and scoring deviations in English essays. Our findings demonstrate the model’s high accuracy in detecting digressions across three categories (88%, 73.33%, and 60%), and its scoring closely aligns with human assessments, with a mean error of just 5.17 and a Pearson correlation coefficient of 0.8024. This evidence supports the model’s reliability and significant potential for application in English writing evaluation.

The activation of pro-inflammatory M1-type macrophages by overexpression of reactive oxygen species (ROS) and reactive nitrogen species (RONS) in synovial membranes contributes to osteoarthritis (OA) progression and cartilage matrix degradation. Here, combing Pt and Se with potent catalytic activities, we developed a hybrid Pt–Se nanozymes as ROS and RONS scavengers to exert synergistic effects for OA therapy. As a result, Pt–Se nanozymes exhibited efficient scavenging effect on ROS and RONS levels, leading to repolarization of M1-type macrophages. Furthermore, the polarization of synovial macrophages to the M2 phenotype inhibited the expression of pro-inflammatory factors and salvaged mitochondrial function in arthritic chondrocytes. In vivo results also suggest that Pt–Se nanozymes effectively suppress the early progression of OA with an Osteoarthritis Research International Association score reduction of 68.21% and 82.66% for 4 and 8 weeks, respectively. In conclusion, this study provides a promising strategy to regulate inflammatory responses by macrophage repolarization processes for OA therapeutic.

As one of the concrete admixtures, water reducing admixtures and superplasticizers are usually used to reduce the mixing water volume and improve the performance of the harden concrete while maintaining better workability of the fresh concrete. However, the concrete strength and durability properties are affected differently by different types and dosages of the water reducing admixtures and superplasticizers. Based on the published literatures, this paper comprehensively reviews and analyzes this problem. Different types of the concretes, including ordinary Portland cement concrete, ordinary Portland cement concrete containing pozzolan, fly ash and ground granulated blast furnace slag, calcium sulfoaluminate cement concrete, ferrite aluminate cement concrete, recycled aggregates concrete, lightweight aggregate concrete, self-compacting concrete and ultra-high performance concrete, are considered to discuss the influence of types and dosages of the water reducing admixtures and superplasticizers on their strengths. Water absorption, frost resistance and permeability resistance of the concrete are mainly reviewed to discuss this influence on the durability properties of the concrete. Then, some suggestions on the application of the water reducing admixtures and superplasticizers in reinforced concrete structures and projects are proposed.

ObjectiveTo analyze the effects of different family environmental backgrounds and mental health problems on academic buoyancy and to explore the potential mechanisms of their effects, using a sample of 2085 medical students in Jiangsu province.MethodsUsing the multiple linear regression to analyze the impact of mental health problems on academic buoyancy in different family environment contexts.Results(1) Higher family income and parental literacy implied higher levels of academic buoyancy in children; (2) mental health problems and academic buoyancy were negatively related, and generalized anxiety and uncertainty stress negatively predicted academic buoyancy levels; (3) uncertainty stress may have an indirect effect on academic buoyancy levels through a partially mediating effect of generalized anxiety.

Ethnopharmacological relevance: Pearl oyster (Pinctada martensii) is used in Chinese traditional medicine use in photoprotective, anti-inflammatory, and wound treatment.Aim of the study: This study explored whether the mucus protein of Pearl oyster (protein of Pinctada martensii, PMP) affects human skin fibroblast (HSF) proliferation, migration, collagen-related gene expression related to collagen formation, and in vivo healing effects. Materials and methods: The PMP component was analyzed by LC-MS/MS. The cell viability was evaluated using a CCK-8 kit. The expression genes were measured by reverse transcription polymerase chain reaction. A full-thickness excisional wounding model in Sprague-Dawley (SD) rats was used to test the repairing effect of PMP in vivo, and Hematoxylin-Eosin (H&E) and Masson's Trichrome staining were applied to evaluate skin structure. Results: The components of PMP were identified using LC-MS/MS proteomics, and a total of 3023 proteins were detected. The results of PMP-treated HSF showed that PMP effectively promoted cell proliferation by 1.6-fold and cell migration by 1.5-fold at a concentration of 1 mg/mL. Additionally, PMP treatment up-regulated the expression levels of collagen-related genes COL1A1, COL3A1, and MMP-1 in fibroblasts. Furthermore, PMP was applied in the therapy of full-thickness excisional wounds in rats. The results demonstrated that PMP significantly accelerated wound healing time, resulted in the recovery of dermal and epithelial thickness, and stimulated collagen regeneration. The regenerated skin closely resembled the structure of normal skin. Conclusions: These findings provide solid evidence supporting the potential of PMP as a promising candidate for the treatment of skin wounds.

This study assessed the impact of milk on the bioactive compounds, physicochemical properties, antioxidant activity, ROS inhibition, and volatile flavor compounds of fermented black mulberry juice (FBMJ). Firstly, the results showed that 25% concentration of milk was the most suitable for preparing FBMJ-Milk. Compared to the control group, the addition of milk significantly increased the SOD activity and antioxidant capacity, as well as enhanced the total phenolic content (TPC) and SOD storage stability. Secondly, HS-SPME-GC–MS combined with OPLS-DA analysis identified 49 compounds in FBMJM, including 12 esters, 6 acids, 1 ketone, 2 aldehydes, 19 alcohols and 9 other compounds. During the storage, the levels of ethyl ester compounds decreased significantly, while the degradation of ester produced some acid and alcohol compounds. The findings revealed that the addition of milk was beneficial for maintaining the antioxidant stability of FBMJM during storage and enhancing the richness of product flavor.

Live-streaming e-commerce has become one of the mainstream marketing scenarios, attracting the attention of consumers and the academic community. In live-streaming e-commerce, retailers often use limited-time sales to induce a sense of urgency, prompting consumers to make impromptu purchase decisions. However, existing studies show contradictory results regarding the effectiveness and underlying mechanism of this marketing method. This study empirically investigates the relationship between time pressure and impulsive buying, including affective and cognitive aspects, using the Stimulus-Organism-Response (SOR) and Schachter-Singer (SST) theories. The results suggest that time pressure has a positive relationship with impulsive buying, with an affective rather than cognitive focus. Moreover, the relationship between time pressure and affective (vs. cognitive) impulsive buying is mediated by perceived value. Positive emotions positively moderate, while negative emotions negatively moderate, the relationship between time pressure and affective impulsive buying. This study enhances the understanding of how consumers make purchase decisions under time pressure in live e-commerce scenarios.