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Abstract To investigate the location of white matter lesions (WMLs) in migraineurs with right‒to‒left shunts (RLS); the relationships among the severity of WMLs, changes in brain structural volume and RLS shunts; and the relationships among the severity of WMLs, changes in brain structural volume and degree of headache in RLS migraine patients. A total of 102 migraineurs with RLS admitted to the affiliated Central Hospital of Dalian University of Technology from December 2018 to December 2022 were enrolled in this study. RLS flow and the 6-item Headache Impact Test (HIT-6) scores were recorded to reflect the degree of headache. The brain structural volumes of 102 migraineurs with RLS were calculated from T1-weighted images via artificial intelligence, and the brain structural volumes of healthy controls matched according to age and sex were also calculated. The correlations among WML location, RLS, headache degree, WML severity and brain structural volume changes in migraineurs were analyzed. (1) The WMLs of migraineurs with RLS were concentrated mainly in the white matter of the lateral ventricular margin and deep white matter. Subcortical WMLs were concentrated mainly in the parietal lobe, occipital lobe and frontal lobe. (2) There were no significant differences in the WML variables of cerebral white matter high signal volume, ratio of high-signal white matter volume to whole-brain white matter volume (%) or Fazekas score among migraineurs with different RLS flows, but there were significant differences in WML variables among migraineurs with RLS with different HIT-6 grades and MIDAS grades. RLS flow, HIT-6 score and MIDAS grade were not correlated with the WML variables measured in this study. (3) There was a significant difference in the volume of the precentral gyrus between migraineurs with RLS and normal controls (P

Fused silica is widely used in high-power laser systems, astronomy and military fields due to its excellent optical and physical properties. However, Subsurface defects(SSDs), such as microcracks, scratches, plastic deformation, and pits are often formed during mechanical processing, which can seriously reduce the optical performance and durability of fused silica. This paper first discusses the formation mechanism of SSDs in fused silica due to mechanical stress, thermal effects, etc. during mechanical processing such as cutting, grinding, and polishing. Then, the commonly used destructive and non-destructive detection methods are reviewed, and the principles and latest progress of each technique are discussed. The potential of deep learning algorithms for SSD detection is also examined. Finally, future directions for research and development are proposed to provide a valuable reference for researchers in the field.

The presented work concerns with some novel solutions of the (2+1)-dimensional Boussinesq equation (BE), which acts as an important model for shallow water wave. Some resonant soliton solutions such as the X-shape soliton (XSS) and Y-shape soliton (YSS) solutions are developed via imposing the resonant conditions on the N-soliton solutions (N-SSs) that developed by the Hirota bilinear approach(HBA). Based on the XSS and YSS solutions, the novel hybrid interactions including the interaction between the 1-soliton and the YSS, the interaction between two YSS solutions are extracted. In addition, the complex N-SSs are also explored and discussed. Finally, the travelling wave solutions including the bright solitary and kinky solitary wave solutions are studied by employing the Bernoulli sub-equation function method (BSEFM). The graphs of the attained solutions are drawn to show the physical properties. The findings of this study are expected to help us apprehend the dynamics of the (2+1)-dimensional BE better.

Abstract Background The global rise in developmental delays underscores the critical need for a thorough understanding and timely interventions during early childhood. Addressing this issue, the Chinese Baby Connectome Project (CBCP)’s behavior branch is dedicated to examining language acquisition, social-emotional development, and environmental factors affecting Chinese children. The research framework is built around three primary objectives: developing a 0–6 Child Development Assessment Toolkit, implementing an Intelligent Coding System, and investigating environmental influence. Methods Utilizing an accelerated longitudinal design, the CBCP aims to enlist a minimum of 1000 typically developing Chinese children aged 0–6. The data collected in this branch constitutes parental questionnaires, behavioral assessments, and observational experiments to capture their developmental milestones and environmental influences holistically. The parental questionnaires will gauge children’s developmental levels in language and social-emotional domains, alongside parental mental well-being, life events, parenting stress, parenting styles, and family relationships. Behavioral assessments will involve neurofunctional developmental evaluations using tools such as the Griffiths Development Scales and Wechsler Preschool and Primary Scale of Intelligence. Additionally, the assessments will encompass measuring children’s executive functions (e.g., Head-Toe-Knee-Shoulder), social cognitive abilities (e.g., theory of mind), and language development (e.g., Early Chinese Vocabulary Test). A series of behavior observation. experiments will be conducted targeting children of different age groups, focusing primarily on aspects such as behavioral inhibition, compliance, self-control, and social-emotional regulation. To achieve the objectives, established international questionnaires will be adapted to suit local contexts and devise customized metrics for evaluating children’s language and social-emotional development; deep learning algorithms will be developed in the observational experiments to enable automated behavioral analysis; and statistical models will be built to factor in various environmental variables to comprehensively outline developmental trajectories and relationships. Discussion This study’s integration of diverse assessments and AI technology will offer a detailed analysis of early childhood development in China, particularly in the realms of language acquisition and social-emotional skills. The development of a comprehensive assessment toolkit and coding system will enhance our ability to understand and support the development of Chinese children, contributing significantly to the field of early childhood development research. Trial registration This study was registered with clinicaltrials.gov NCT05040542 on September 10, 2021.

Abstract Numerous deep-learning models have been developed using task-specific data, but they ignore the inherent connections among different tasks. By jointly learning a wide range of segmentation tasks, we prove that a general medical image segmentation model can improve segmentation performance for computerized tomography (CT) volumes. The proposed general CT image segmentation (gCIS) model utilizes a common transformer-based encoder for all tasks and incorporates automatic pathway modules for task prompt-based decoding. It is trained on one of the largest datasets, comprising 36,419 CT scans and 83 tasks. gCIS can automatically perform various segmentation tasks using automatic pathway modules of decoding networks through text prompt inputs, achieving an average Dice coefficient of 82.84%. Furthermore, the proposed automatic pathway routing mechanism allows for parameter pruning of the network during deployment, and gCIS can also be quickly adapted to unseen tasks with minimal training samples while maintaining great performance.

Abstract Background To construct and compare merged models integrating clinical factors, MRI-based radiomics features and deep learning (DL) models for predicting pathological complete response (pCR) to neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC). Methods Totally 197 patients with LARC administered surgical resection after nCRT were assigned to cohort 1 (training and test sets); meanwhile, 52 cases were assigned to cohort 2 as a validation set. Radscore and DL models were established for predicting pCR applying pre- and post-nCRT MRI data, respectively. Different merged models integrating clinical factors, Radscore and DL model were constituted. Their predictive performances were validated and compared by receiver operating characteristic (ROC) and decision curve analyses (DCA). Results Merged models were established integrating selected clinical factors, Radscore and DL model for pCR prediction. The areas under the ROC curves (AUCs) of the pre-nCRT merged model were 0.834 (95% CI: 0.737–0.931) and 0.742 (95% CI: 0.650–0.834) in test and validation sets, respectively. The AUCs of the post-nCRT merged model were 0.746 (95% CI: 0.636–0.856) and 0.737 (95% CI: 0.646–0.828) in test and validation sets, respectively. DCA showed that the pretreatment algorithm could yield enhanced clinically benefit than the post-nCRT approach. Conclusions The pre-nCRT merged model including clinical factors, Radscore and DL model constitutes an effective non-invasive tool for pCR prediction in LARC.

Abstract Approximately 15% of patients with colorectal cancer (CRC) exhibit a distinct molecular phenotype known as microsatellite instability (MSI). Accurate and non-invasive prediction of MSI status is crucial for cost savings and guiding clinical treatment strategies. The retrospective study enrolled 307 CRC patients between January 2020 and October 2022. Preoperative images of computed tomography and postoperative status of MSI information were available for analysis. The stratified fivefold cross-validation was used to avoid sample bias in grouping. Feature extraction and model construction were performed as follows: first, inter-/intra-correlation coefficients and the least absolute shrinkage and selection operator algorithm were used to identify the most predictive feature subset. Subsequently, multiple discriminant models were constructed to explore and optimize the combination of six feature preprocessors (Box-Cox, Yeo-Johnson, Max-Abs, Min–Max, Z-score, and Quantile) and three classifiers (logistic regression, support vector machine, and random forest). Selecting the one with the highest average value of the area under the curve (AUC) in the test set as the radiomics model, and the clinical screening model and combined model were also established using the same processing steps as the radiomics model. Finally, the performances of the three models were evaluated and analyzed using decision and correction curves.We observed that the logistic regression model based on the quantile preprocessor had the highest average AUC value in the discriminant models. Additionally, tumor location, the clinical of N stage, and hypertension were identified as independent clinical predictors of MSI status. In the test set, the clinical screening model demonstrated good predictive performance, with the average AUC of 0.762 (95% confidence interval, 0.635–0.890). Furthermore, the combined model showed excellent predictive performance (AUC, 0.958; accuracy, 0.899; sensitivity, 0.929) and favorable clinical applicability and correction effects. The logistic regression model based on the quantile preprocessor exhibited excellent performance and repeatability, which may further reduce the variability of input data and improve the model performance for predicting MSI status in CRC.

Abstract Background It is uncertain whether the weekend warrior pattern is associated with all-cause mortality among adults living with type 2 diabetes. This study explored how the ‘weekend warrior’ physical activity (PA) pattern was associated with all-cause mortality among adults living with type 2 diabetes. Methods This prospective cohort study investigated US adults living with type 2 diabetes in the National Health and Nutrition Examination Survey (NHANES). Mortality data was linked to the National Death Index. Based on self-reported leisure-time and occupational moderate-to-vigorous PA (MVPA), participants were categorized into 3 groups: physically inactive (

Abstract Background This study aims to utilize the deep learning method of VB-Net to locate and segment the trigeminal nerve, and employ radiomics methods to distinguish between CTN patients and healthy individuals. Methods A total of 165 CTN patients and 175 healthy controls, matched for gender and age, were recruited. All subjects underwent magnetic resonance scans. VB-Net was used to locate and segment the bilateral trigeminal nerve of all subjects, followed by the application of radiomics methods for feature extraction, dimensionality reduction, feature selection, model construction, and model evaluation. Results On the test set for trigeminal nerve segmentation, our segmentation parameters are as follows: the mean Dice Similarity Coefficient (mDCS) is 0.74, the Average Symmetric Surface Distance (ASSD) is 0.64 mm, and the Hausdorff Distance (HD) is 3.34 mm, which are within the acceptable range. Analysis of CTN patients and healthy controls identified 12 features with larger weights, and there was a statistically significant difference in Rad_score between the two groups (p

In the process of grain storage, the use of low-temperature grain storage technology can effectively reduce grain losses during storage and ensure grain quality, which is of great significance for maintaining a stable grain supply. Radiative cooling materials, as a new energy-free cooling technology, achieve cooling by radiating heat in the form of electromagnetic waves into outer space. This approach can address issues associated with traditional cooling methods, such as high energy consumption and high chemical oxygen demand (COD) emissions, offering a green and environmentally friendly new approach to low-temperature grain storage. This paper explained the working principle of polymer-based radiative cooling materials and systematically introduced the composition and selection criteria of polymer-based radiative cooling systems. It also categorized and summarized polymer-based radiative cooling materials according to their structural characteristics. The existing problems with different structured radiative cooling materials, as well as future research directions, were also analyzed. This provides a certain research framework for applying radiative cooling materials to grain storage facilities to achieve low-temperature grain storage.

IntroductionResidual film pollution has become a key factor that affects the sustainable development of cotton, and intercropping may be an economical and environmentally friendly method to reduce the negative effects of nonmulched conditions on cotton growth. We hypothesized that optimizing the cotton/cumin intercropping density would improve the soil environment and increase crop productivity and resource utilization.MethodsTherefore, in this study, singlecropping cotton (CK) was used as the control, and three intercropping cumin seeding densities were used (plants ha-1: 5×105, ID1; 8×105, ID2; and 11×105, ID3). Through a two-year field experiment, the effects of cotton-cumin intercropping on the soil moisture, temperature, salt, respiration rate, weed density, cotton yield formation and intercropping advantages were studied.Results and discussionCompared with the CK treatment, the ID2 treatment decreased the water content in the 0–30 cm soil layer by 8.3%, increased the water consumption by 9.1%, increased the soil temperature by 0.5°C, and decreased the electrical conductivity of the 0–15 cm soil layer by 17.7%. Compared with the CK treatment, the ID1 treatment significantly decreased the soil respiration rate by 33.6%, and the weed density decreased in the following order: CK>ID1>ID2>ID3. During the nonsymbiotic period, compared with CK, ID2 increased the soil water content by 5.7%, increased the soil respiration rate by 17.7%, and decreased the electrical conductivity by 15.6%. Compared with those for CK and ID3, the seed yield for ID2 increased by 2.0% and 5.8%, respectively, and that for ID1 decreased by 1.6%. However, the land equivalent of the ID2 treatment was 4.3% greater than that for the ID1 treatment. Therefore, intercropping cumin at a density of 8×105 plants ha-1 is beneficial for increasing surface coverage, significantly increasing crop water consumption, increasing surface temperature, reducing soil electrical conductivity and carbon emissions, and improving the crop yield and economic benefits. This model can be used as an agroecologically friendly and sustainable planting model.

Background & Aims: Tumor-infiltrating lymphocytes (TILs), particularly CD8+ TILs, are key prognostic markers in many cancers. However, their prognostic value in hepatocellular carcinoma (HCC) remains controversial, with different evidence. Given the heterogeneous outcomes in patients with HCC undergoing liver resection, this study aims to develop an AI-based system to quantify CD8+ TILs and assess their prognostic value for patients with HCC. Methods: We conducted a retrospective multicenter study on patients undergoing liver resection across three cohorts (N = 514). We trained a deep neural network and a random forest model to segment tumor regions and locate CD8+ TILs in H&E and CD8-stained whole-slide images. We quantified CD8+ TIL density and established an Automated CD8+ Tumor-infiltrating Lymphocyte Scoring (ATLS-8) system to assess its prognostic value. Results: In the discovery cohort, the 5-year overall survival (OS) rates were 34.05% for ATLS-8 low-score and 65.03% for ATLS-8 high-score groups (hazard ratio [HR] 2.40; 95% CI, 1.37–4.19; p = 0.015). These findings were confirmed in validation cohort 1, which had 5-year OS rates of 28.57% and 68.73% (HR 3.38; 95% CI, 1.27–9.02; p = 0.0098), and validation cohort 2, which had 59.26% and 81.48% (HR 2.74; 95% CI, 1.05–7.15; p = 0.031). ATLS-8 improved the prognostic model based on clinical variables (C-index 0.770 vs. 0.757; 0.769 vs. 0.727; 0.712 vs. 0.642 in three cohorts). Conclusions: We developed an automated system using CD8-stained whole-slide images to assess immune infiltration (ATLS-8). In patients with HCC undergoing resection, higher CD8+ TIL density correlates with better OS, as per ATLS-8 assessment. This system is a promising tool for advancing clinical immune microenvironment assessment and outcome prediction. Impact and implications:: CD8+ tumor-infiltrating lymphocytes (TILs) have been identified as a prognostic factor associated with many cancers. In this study, CD8+ TILs were identified as an independent prognostic factor for overall survival in patients with hepatocellular carcinoma who undergoing liver resection. Therefore, ATLS-8, a novel digital biomarker based on whole-slide image-level CD8+ TILs, could play an important role in the prognostic assessment of patients with HCC and could be integrated into clinicopathological models to participate in the decision-making and prognostic assessment of patients. The scoring system combined with artificial intelligence is essential for automated, quantitative, whole-slide image-level assessment of TILs, which can be widely applied to quantify the immune profile of multi-cancer disease types with the discussion of subsequent immunotherapy.

ObjectiveTo establish a combined radiomics-clinical model for the early prediction of a prostate-specific antigen(PSA) response in patients with metastatic castration-resistant prostate cancer(mCRPC) after treatment with abiraterone acetate(AA).MethodsThe data of a total of 60 mCRPC patients from two hospitals were retrospectively analyzed and randomized into a training group(n=48) or a validation group(n=12). By extracting features from biparametric MRI, including T2-weighted imaging(T2WI), diffusion-weighted imaging(DWI), and apparent diffusion coefficient(ADC) maps, radiomics features from the training dataset were selected using least absolute shrinkage and selection operator(LASSO) regression. Four predictive models were developed to assess the efficacy of abiraterone in treating patients with mCRPC. The primary outcome variable was the PSA response following AA treatment. The performance of each model was evaluated using the area under the receiver operating characteristic curve(AUC). Univariate and multivariate analyses were performed using Cox regression to identify significant predictors of the efficacy of abiraterone treatment in patients with mCRPC.ResultsThe integrated model was constructed from seven radiomics features extracted from the T2WI, DWI, and ADC sequence images of the training data. This model demonstrated the highest AUC in both the training and validation cohorts, with values of 0.889 (95% CI, 0.764-0.961) and 0.875 (95% CI, 0.564-0.991). The Rad-score served as an independent predictor of the response to abiraterone treatment in patients with mCRPC (HR: 2.21, 95% CI: 1.01-4.44).ConclusionThe biparametric MRI-based radiomics model has the potential to predict the PSA response in patients with mCRPC following abiraterone treatment.Clinical relevance statementThe MRI-based radiomics model could be used to noninvasively identify the AA response in mCRPC patients, which is helpful for early clinical decision-making.

Abstract Two‐dimensional porous carbon nanosheets (PCNSs) are considered promising anodes for lithium‐ion batteries due to their synergetic features arising from both graphene and porous structures. Herein, using naturally abundant and biocompatible sodium humate (SH) as the precursor, PCNSs are prepared from the laboratory scale up to the kilogram scale by a method of a facile ice‐templating‐induced puzzle coupled with a carbonization strategy. Such obtained SH‐derived PCNSs (SH‐PCNSs) possess a hierarchical porous structure dominated by mesopores having a specific surface area (~127.19 2 g−1), pore volume (~0.134 cm3 g−1), sheet‐like morphology (~2.18 nm in thickness), and nitrogen/oxygen‐containing functional groups. Owing to these merits, the SH‐PCNSs present impressive Li‐ion storage characteristics, including high reversible capacity (1011 mAh g−1 at 0.1 A g−1), excellent rate capability (465 mAh g−1 at 5 A g−1), and superior cycle stability (76.8% capacitance retention after 1000 cycles at 5 A g−1). It is noted that the SH‐PCNSs prepared from the kilogram‐scale production procedure possess comparable electrochemical properties. Furthermore, coupling with a LiNi1/3Co1/3Mn1/3O2 cathode, the full cells deliver a high capacity of 167 mAh g−1 at 0.2 A g−1 and exhibit an outstanding energy density of 128.8 Wh kg−1, highlighting the practicability of this porous carbon nanosheets and the potential commercial opportunity of the scalable processing approach.

As the global population continues to grow, so does the demand for food. However, cold stress due to global climate change greatly threatens the safe production of rice. Piriformospora indica plays a pivotal role as a functional microbiota in improving cold tolerance in rice. However, the addition of P. indica alone has a limited effect. In this study, an attempt was made to select plant growth-promoting bacteria (Agrobacterium rhizogenes and Bacillus subtilis) as helper bacteria to help P. indica function better and further enhance rice cold tolerance. Under cold stress, the co-addition of the three beneficial microorganisms significantly increased the biomass, photosynthetic performance indicators, osmoregulatory substance contents, and antioxidant enzyme activities of rice. P. indica and helper bacteria significantly reduced the cold stress-induced increases in malondialdehyde content and electrolyte leakage rate in rice leaves and triggered a substantial upregulation of cold-tolerant genes in rice. This suggests that P. indica and helper bacteria can synergistically improve the cold resistance of rice. The findings of the research offer a conceptual foundation and practical assistance for enhancing rice's resilience to cold temperatures.

ObjectivesTo investigate the function of the glymphatic system (GS) and its association with neuropsychological tests in spontaneous intracerebral hemorrhage (sICH) by diffusion tensor imaging analysis along the perivascular space (DTI-ALPS).MethodsThis retrospective study included 58 patients with sICH and 63 age- and sex-matched healthy controls (HCs). Partial correlation analyses were performed to examine the relationships between the DTI-ALPS index and radiological as well as clinical data. Mediation analyses were performed to explore the mediating role of the grey matter proportion (GM%) in the relationship between DTI-ALPS index and Montreal Cognitive Assessment (MoCA) score.ResultsSignificantly lower DTI-ALPS index values were observed in sICH compared with HCs (FDR-p

Accurately identifying life-threatening prostate cancer (PCa) at time of diagnosis remains an unsolved problem. We evaluated whether DNA methylation status of selected candidate genes can predict the risk of metastasis beyond clinical risk factors in men with untreated PCa. A nested case-control study was conducted among men diagnosed with localized PCa at Kaiser Permanente California between 01/01/1997–12/31/2006 who did not receive curative treatments. Cases were those who developed metastasis within 10 years from diagnosis. Controls were selected using density sampling. Ninety-eight candidate genes were selected from functional categories of cell cycle control, metastasis/tumour suppressors, cell signalling, cell adhesion/motility/invasion, angiogenesis, and immune function, and 41 from pluripotency genes. Cancer DNA from diagnostic biopsy blocks were extracted and analysed. Associations of methylation status were assessed using CpG site level and principal components-based analysis in conditional logistic regressions. In 215 cases and 404 controls, 27 candidate genes were found to be statistically significant in at least one of the two analytical approaches. The agreement between the methods was 25.9% (7 candidate genes, including 2 pluripotency markers). The DNA methylation status of several candidate genes was significantly associated with risk of metastasis in untreated localized PCa patients. These findings may inform future risk prediction models for PCa metastasis beyond clinical characteristics.

Objective To investigate the association between atherogenic index of plasma (AIP) and kidney stones (KS) occurrence and recurrence.Methods Data were obtained from the National Health and Nutrition Examination Survey (NHANES) 2007–2014. Non-pregnant adults who provided complete information on AIP and KS were included in the analyses. AIP was calculated as log (triglyceride/high-density lipoprotein cholesterol). KS was ascertained with questionnaires. Weighted multivariable logistic regression model and restricted cubic spline (RCS) were applied to examine the associations between AIP and KS occurrence and recurrence.Results A total of 6488 subjects (weighted mean age 43.19 years and 49.26% male) with a weighted mean AIP of 0.66 were included in this study. The multivariable-adjusted OR for nephrolithiasis occurrence across consecutive tertiles was 1.00 (reference), 1.21 (95% CI: 0.90–1.62), and 1.85 (95% CI: 1.39–2.48), respectively. Moreover, each SD increment of AIP was associated with a 50% (OR:1.50, 95% CI: 1.25–1.81) higher risk of nephrolithiasis recurrence. RCSs showed significant and linear dose-response relationships between AIP and nephrolithiasis occurrence (p-overall = 0.006, p-nonlinear = 0.689) and recurrence (p-overall = 0.001, p-nonlinear = 0.848). The positive associations between AIP and nephrolithiasis occurrence and recurrence persisted in sensitivity analyses, suggesting the robustness of the results.Conclusion In the current US nationally representative cross-sectional study, AIP was positively associated with KS occurrence and recurrence.

Subsurface drip irrigation in arid areas has the potential to replace traditional mulched drip irrigation to achieve green and sustainable cotton production. However, the suitable irrigation amount and frequency are still unclear, which seriously limits the ability of this model to improve water productivity and water-saving potential. Therefore, a field experiment was carried out from 2021 to 2023; a split plot experimental design was adopted with two irrigation amounts (W1, 3177 m3 ha−1; W2, 3840 m3 ha−1) and three irrigation frequencies (F1, 9; F2, 8; F3, 7). The effects of different irrigation strategies on the soil microenvironment, moisture content, biomass, and water use efficiency (WUE) of cotton organs were evaluated. The W2 treatment improved the soil moisture content, increased the soil temperature gradient, and reduced the soil conductivity, thereby increasing the moisture content and biomass of various organs. Moreover, compared with the F1 treatment, the F2 and F3 treatments were more likely to increase the soil moisture content, soil temperature gradient, WUEStem, WUELeaf and WUEBoll. In addition, the water consumption of the F2 and F3 treatments decreased by 3.9 % and 0.9 %, respectively, compared with that of the F1 treatment. These findings indicate that W2F2 can reduce water consumption while increasing boll biomass and WUEBoll. Further analysis revealed that under W2F2, WUEBoll was positively correlated with soil temperature gradient and soil conductivity and negatively correlated with leaf moisture content (LMC) and water consumption. In summary, with an irrigation amount of 3840 m3 ha−1, delaying the initial irrigation event and increasing the irrigation quota (8 irrigation events) improve the water environment in cotton fields, reducing soil temperature fluctuations and surface salt accumulation and synergistically increasing the boll biomass of cotton organs and WUEBoll. This irrigation strategy represents an effective cotton cultivation method to maximize cotton yield and improve resource utilization efficiency.

Abstract Background Whether endobiliary radiofrequency ablation (EB-RFA) changes the standard role of stent placement in treating unresectable malignant biliary obstruction (MBO) remains unclear. The aim of this study is to compare percutaneous EB-RFA and metal stent placement (RFA-Stent) with metal stent placement alone (Stent) in treating unresectable MBO using a propensity score matching (PSM) analysis. Methods From June 2013 to June 2018, clinical data from 163 patients with malignant biliary obstruction who underwent percutaneous RFA-Stent or stenting alone were retrospectively analyzed using a nearest-neighbor algorithm to one-to-one PSM analysis to compare primary and secondary stent patency (PSP, SSP), overall survival (OS) and complications between the two groups. Results Before matching, for whole patients, RFA-Stent resulted in longer median PSP (8.0 vs. 5.1 months, P = 0.003), SSP (9.8 vs. 5.1 months, P

Abstract Mycoplasma bovis (M. bovis) is capable of causing a range of diseases in cattle, encompassing calf pneumonia, arthritis, conjunctivitis, meningitis, and mastitis. It is widely recognized as one of the predominant pathogens posing a significant threat to the global cattle industry. Therefore, accurate and sensitive methods are urgently needed to detect M. bovis. This study aims to detect M. bovis by combining colloidal gold with biotin-labeled oligonucleotides to improve detection sensitivity and form a chromogenic detection probe based on signal amplification technology. Here, we developed a sensitive and specific polymerase chain reaction-lateral flow dipstick assay (PCR-LFD) strip for efficient nucleic acid detection of M. bovis. A pair of specific primers with 5’ ends labeled with biotin and digoxigenin probes was designed for PCR experiments. Colloidal gold particles-labeled anti-digoxigenin IgG coated gold-labeled test strip was prepared, streptavidin was used as the detection probe, and nitrocellulose membrane coated goat anti-mouse IgG was used as the control line. Our results showed that the detection limit of the PCR-LFD was 89 fg/µL for the M. bovis DNA. The results from the test strip were highly consistent with those from real-time qPCR. This assay were highly specific for M. bovis, as there were no cross-reactions with other microorganisms tested and the detection sensitivity of the test was also relatively high (97.67%). The novel strips present a promising tool for the cost-effective and sensitive diagnosis of M. bovis.

Abstract Objective Mitosis karyorrhexis index (MKI) can reflect the proliferation status of neuroblastoma cells. This study aimed to investigate the contrast-enhanced computed tomography (CECT) radiomics features associated with the MKI status in neuroblastoma. Materials and methods 246 neuroblastoma patients were retrospectively included and divided into three groups: low-MKI, intermediate-MKI, and high-MKI. They were randomly stratified into a training set and a testing set at a ratio of 8:2. Tumor regions of interest were delineated on arterial-phase CECT images, and radiomics features were extracted. After reducing the dimensionality of the radiomics features, a random forest algorithm was employed to establish a three-class classification model to predict MKI status. Results The classification model consisted of 5 radiomics features. The mean area under the curve (AUC) of the classification model was 0.916 (95% confidence interval (CI) 0.913–0.921) in the training set and 0.858 (95% CI 0.841–0.864) in the testing set. Specifically, the classification model achieved AUCs of 0.928 (95% CI 0.927–0.934), 0.915 (95% CI 0.912–0.919), and 0.901 (95% CI 0.900–0.909) for predicting low-MKI, intermediate-MKI, and high-MKI, respectively, in the training set. In the testing set, the classification model achieved AUCs of 0.873 (95% CI 0.859–0.882), 0.860 (95% CI 0.852–0.872), and 0.820 (95% CI 0.813–0.839) for predicting low-MKI, intermediate-MKI, and high-MKI, respectively. Conclusions CECT radiomics features were found to be correlated with MKI status and are helpful for reflecting the proliferation status of neuroblastoma cells.

Introduction: Although programmed death ligand 1 (PD-L1) inhibitor plus chemotherapy regimen is a promising strategy for malignant tumors, it can induce significant immune-related adverse events, such as immune-related pneumonitis. Here, we report the first case of lethal immune-related pneumonitis in an Asian patient receiving anti-PD-L1 treatment. Case Presentation: A 68-year-old man was diagnosed with small cell lung cancer and interstitial pneumonia. After his pulmonary infection was relieved by comprehensive treatment, the patient received first-line treatment with durvalumab plus etoposide and carboplatin. Two weeks after starting durvalumab treatment, the patient had chest pain and shortness of breath. He was diagnosed with immune-induced pneumonia and treated with methylprednisolone, cefoperazone, and sulbactam, followed by oxygen and pirfenidone. Oxygen partial pressure decreased to 58 mm Hg within next the 4 days and laboratory assessment suggested cytokine storm. The patient underwent 2 plasma exchanges, one double filtration plasmapheresis and oxygen saturation decreased continuously. The patient died 1 month after durvalumab treatment. Conclusion: Immune-related pneumonitis induced by PD-L1 inhibitors is rare but life-threatening. Infection should be ruled out before starting immunotherapy.

Phosphorus (P) fertilizer is a significant cost in crop production. Understanding the mechanisms behind P fertilizer–soil–crop interactions can enhance phosphorus use efficiency (PUE) and increasing yield. We conducted a rice cultivation bucket experiment in red soil (pH = 5.9) and lime concretion black soil (pH = 7.8) and applied single superphosphate (SSP), calcium magnesium phosphate (CMP), diammonium phosphate (DAP), triple superphosphate (TSP), ammonium polyphosphate (APP), and a control group (CK, no P fertilizer). We analyzed rice P uptake and utilization patterns, evaluated the impact of varying P fertilizer formulations on rice root morphology, yield, and PUE, and investigated changes in soil P pools. In red soil, the APP treatment produced the greatest total root length, rice yield, PUE and increased soil Olsen-P, NaHCO3-Pi at anthesis. In lime concretion black soil, the TSP and APP treatments had the highest rice yields and increased Olsen-P, H2O-P, NaHCO3-Pi at anthesis. Moreover, the TSP treatment had the greatest total root length and root surface area at anthesis and the APP treatment had the largest PUE. Random forest regression analysis revealed that residual-P and Olsen-P significantly impacted rice yield in red soil and lime concretion black soil, respectively. We recommend using APP in red soil and TSP and APP in lime concretion black soil for rice cultivation to optimize soil P pool characteristics and root morphology for nutrient uptake, ultimately leading to the highest yields and PUE.

Objective To investigate the association between the triglyceride-glucose (TyG) index, a surrogate marker of insulin resistance and the risk of kidney stones (KSs) in a Chinese population.Design Case–control study.Setting Three Physical Examination Centers in Shanghai, China, between January 2020 and December 2022.Participants A total of 117 757 Chinese adults underwent health check-ups during the study period.Primary and secondary outcome measures The association between the TyG index and the risk of KS was assessed using multivariable logistic regression analysis. The dose–response relationship between the TyG index and KS risk was evaluated with a restricted cubic spline (RCS) analysis. Stratified analyses were conducted to explore whether factors such as age, sex, obesity, hypertension and diabetes modify the association between the TyG index and KS risk.Results Out Of the 117 757 participants, 11 645 (9.9%) were diagnosed with KS using ultrasound. Individuals with KS had significantly higher TyG values than controls (p

ObjectivesTo explore the relationship between glymphatic dysfunction and cognitive impairment in unilateral temporal lobe epilepsy (TLE).MethodsThis study retrospectively included 38 patients with unilateral TLE and 26 age- and gender-matched healthy controls (HCs). The diffusion tensor image analysis along the perivascular space (DTI-ALPS) index, choroid plexus volume (CPV), and cognitive assessment were obtained for each participant. Neuropsychological test batteries included Montreal Cognitive Assessment (MoCA), Minimum Mental State Examination, Arithmetic Test (AT), Digit Symbol Substitution Test (DSST), Digit Span Test (DST), Boston Naming Test, Block design, Phonological Fluency Test (PFT), and Semantic Verbal Fluency (SVF).ResultsCompared to HCs, TLE patients had lower scores of MoCA, AT, DSST, DST, Block design, PFT and SVF (all p

The coexistence of microorganisms in complex soil environments greatly affects the environmental behavior and ecological effects of microplastics (MPs). However, relevant studies are sparse, and internal mechanisms remain unclear. Herein, arbuscular mycorrhizal fungi (AMF), a common symbiotic microorganism in the soil–plant system, was proved to significantly affect MPs absorption and migration with a “size effect”. Specifically, the existence of AMF accelerated small-sized MPs (0.5 μm) uptake but slowed large-sized MPs (2 μm) uptake in lettuce. The content of 0.5 μm MPs absorbed by plants with AMF was 1.26 times that of the non-AMF group, while the content of 2 μm MPs was only 77.62 % that of non-AMF group. Additionally, the different effects of microorganisms on the intake content of MPs with different particle sizes in plants also led to different toxic effects of MPs on lettuce, that is, AMF exacerbated small-size MPs toxicity in lettuce (e.g., reduced plant biomass, photosynthesis, etc), and it weakened large-sized MPs toxicity (e.g., increased plant height, antioxidant enzyme activity, etc). The above phenomenon mainly because of the change in AMF on the plant root structure, which can be visually observed through the intraradical and extraradical hyphae. The symbiotic structure (hyphae) formed by AMF and host plants root could enhance the absorption pathway for small-sized MPs in lettuce, although not for large-sized MPs. Additionally, the effects of AMF varied with the soil environment of differently sized MPs, which promoted the migration of small-particle MPs to plants but aggravated large-particle MPs fixation at the soil interface. These findings could deepen the understanding of MPs pollution in terrestrial systems and provide theoretical basis and technical support to accurately assess soil MPs pollution.

Soybean soluble dietary fiber (SSDF) was extracted from soy sauce residue and soybean meal. The influence of SSDF on the physicochemical stability and digestive characteristics of soybean oil body (SOB) lotion was investigated by taking the absolute value of Zeta potential, average particle size, peroxide value (POV value), thiobarbituric acid value (TBARS value) and fatty acid release rate (FFA) as characteristic parameters. The results showed that certain concentration of SSDF could effectively reduce the Zeta potential, average particle size, POV value, TBARS value of SOB lotion system, and significantly improve the physical and chemical stability of SOB lotion. In addition, in vitro simulated digestion experiments further showed that the introduction of SSDF can significantly reduce the FFA release rate of SOB emulsion, which effectively delayed the digestion process of lipids in the gastrointestinal tract. This study can provide theoretical basis and reference for the high-value utilization of soybean processing by- products such as soy sauce oil residue and soybean meal, which could improve the processing applicability of SOB, and develop new low-fat health foods containing SOB and SSDF.

This study aimed to investigate the effect of oxidation temperature on the physical properties of β-Ga2O3 grown by thermal oxidation of GaN in the O2 ambient at high oxidation temperatures from 900 to 1400 °C. Notably, the analysis of the oxidation temperatures ranging from 1100 to 1400 °C remains unexplored in the other studies. The effects of the oxidation temperature on the physical properties were investigated via X-ray diffraction, X-ray photoelectron spectroscopy, and field-emission scanning electron microscopy (FESEM). At all oxidation temperatures, XPS results revealed oxygen deficiency. The top FESEM images indicated disordered nanocolumn structures on the surface of the oxide layer, which increased in abundance with oxidation temperatures exceeding 1100 °C. Energy-filtered high-resolution transmission electron microscopy images and the selected area electron diffraction patterns revealed that the top nanocolumns and the oxidized layer comprised polycrystalline β-Ga2O3. Additionally, the cross-sectional lamellae prepared through focused ion beam milling revealed an increase in the thickness of the β-Ga2O3 layer with oxidation temperature. To account for the variations in the oxide layer thickness, the oxidation temperatures were classified into two ranges of 900–1100 °C and 1100–1400 °C for calculating the activation energy. Moreover, this study assumed that the activation energy required for the oxidation process remained constant within each temperature interval. According to Arrhenius's model, the activation energy from 900 to 1100 °C was calculated to be 286.15 kJ/mol (2.97 eV). Furthermore, the activation energy from 1100 to 1400 °C was determined to be 111.33 kJ/mol (1.15 eV).

Abstract Despite the abundance of genotype-phenotype association studies, the resulting association outcomes often lack robustness and interpretations. To address these challenges, we introduce PheSeq, a Bayesian deep learning model that enhances and interprets association studies through the integration and perception of phenotype descriptions. By implementing the PheSeq model in three case studies on Alzheimer’s disease, breast cancer, and lung cancer, we identify 1024 priority genes for Alzheimer’s disease and 818 and 566 genes for breast cancer and lung cancer, respectively. Benefiting from data fusion, these findings represent moderate positive rates, high recall rates, and interpretation in gene-disease association studies.

In order to further clarify the growth-promoting effect of the non-core Metarhizium sp. Marquandomyces marquandii on plants, M. marquandii SGSF043, which was obtained via pre-screening in the laboratory, was selected as a test strain and the seed soaking method was adopted. The effects of a fermentation broth obtained from this strain on the seed germination, seedling growth, and rhizosphere soil enzyme activity of maize were studied. The results were as follows: In seed germination tests, M. marquandii SGSF043 fermentation liquid had a certain inhibitory effect on corn seed germination, and the germination rate was only 15%. When the fermentation solution was diluted 10 times, the germination rate reached 97%. After the germination test, the growth of maize plumules was promoted in the groups treated with 10-times and 1000-times dilutions. In the field community experiment, based on the comprehensive evaluation of seedling biomass indicators, the solution diluted 100 times had the best growth-promoting effect. The aboveground fresh weight was increased by 127.13% compared with the control group. The results show that M. marquandii SGSF043 has the potential to promote the growth of maize and improve the soil environment, which provides a theoretical basis for the research on and the application of M. marquandii in farmland.

Abstract The development of stable and efficient ligands is of vital significance to enhance the catalytic performance of carbonylation reactions of alkenes. Herein, an aryldiphosphine ligand (L11) bearing the [Ph2P(ortho-C6H4)]2CH2 skeleton is reported for palladium-catalyzed regioselective carbonylation of alkenes. Compared with the industrially successful Pd/1,2-bis(di-tert-butylphosphinomethyl)benzene catalyst, catalytic efficiency catalyzed by Pd/L11 on methoxycarbonylation of ethylene is obtained, exhibiting better catalytic performance (TON: >2,390,000; TOF: 100,000 h−1; selectivity: >99%) and stronger oxygen-resistance stability. Moreover, a substrate compatibility (122 examples) including chiral and bioactive alkenes or alcohols is achieved with up to 99% yield and 99% regioselectivity. Experimental and computational investigations show that the appropriate bite angle of aryldiphosphine ligand and the favorable interaction of 1,4-dioxane with Pd/L11 synergistically contribute to high activity and selectivity while the electron deficient phosphines originated from electron delocalization endow L11 with excellent oxygen-resistance stability.

Cooperation is a fundamental aspect of social and biological systems, yet achieving and maintaining high levels of cooperation remains a significant challenge. This study investigates the dynamics of cooperation among players engaged in repeated two-player Prisoner’s Dilemma games, utilizing a novel integration of the Bush–Mosteller reinforcement learning model with adaptive network rewiring mechanisms. Each player updates its probability of cooperation and rewires its connections based on the payoffs received from neighbors. Our results demonstrate that incorporating network rewiring guided by reinforcement learning significantly enhances both the level of cooperation and the average payoff across the population. Players that prioritize rewiring over strategy updates are found to form more stable cooperative structures, while those with heightened sensitivity to payoffs and optimal aspiration levels achieve greater cooperation. By identifying and analyzing key parameters that influence cooperative dynamics, our findings provide deep insights into the mechanisms that drive cooperative behavior. This research not only highlights the transformative potential of adaptive network rewiring in promoting cooperation within complex adaptive systems but also offers a framework for designing resilient cooperative networks across diverse domains.

With the sudden advancement of glucose biosensors for monitoring blood glucose levels for the prevention and diagnosis of diabetes, non-enzymatic glucose sensors have aroused great interest owing to their sensitivity, stability, and economy. Recently, researchers have dedicated themselves to developing non-enzymatic electrochemical glucose sensors for the rapid, convenient, and sensitive determination of glucose. However, it is desirable to explore economic and effective nanomaterials with a high non-enzymatic catalysis performance toward glucose to modify electrodes. Metal oxides (MOs) and metal sulfides (MSs) have attracted extensive interest among scholars owing to their excellent catalytic activity, good biocompatibility, low cost, simple synthesis process, and controllable morphology and structure. Nonetheless, the exploitation of MOs and MSs in non-enzymatic electrochemical glucose sensors still suffers from relatively low conductivity and biocompatibility. Therefore, it is of significance to integrate MOs and MSs with metal/carbon/conducive polymers to modify electrodes for compensating the aforementioned deficiency. This review introduces the recent developments in non-enzymatic electrochemical glucose sensors based on MOs and MSs, focusing on their preparation methods and how their structural composition influences sensing performance. Finally, this review discusses the prospects and challenges of non-enzymatic electrochemical glucose sensors.

Dynamic facades allow for effective climate adaptability, representing a new trend in future building envelope design. Present research on dynamic facades often focuses solely on certain aspects of the built environment or relies entirely on simulation outcomes. Meanwhile, the real-time changing nature of dynamic facades poses challenges in accurately simulating these schemes. Therefore, it remains essential to quantify the energy consumption performances of different types of dynamic facades and their influence on the indoor environment comfort in response to ventilation, light, and thermal environment to improve energy savings. This study uses an energy management system to simulate the ability of five dynamic facades—an intelligent ventilated facade, a dynamic exterior shading, a dynamic interior shading, a buffer layer, and phase-change material (PCM) facades—to provide adequate comfort and reduce energy consumption in four climate zones in China. The simulation model of a nearly net-zero energy Solar Decathlon house “Nature Between” was validated with experimental data. Among the five dynamic facades, the energy-saving efficiency of intelligent ventilation was highest, followed by exterior shading. Compared with houses without dynamic facades, the use of the dynamic facades reduced energy consumption (and annual glare time) by 19.87% (90.65%), 22.37% (74.84%), 15.19% (72.09%), and 9.23% (75.53%) in Xiamen, Shanghai, Beijing, and Harbin, respectively. Findings regarding the dynamic facade-driven energy savings and favorable indoor environment comfort provide new and actionable insights into the design and application of dynamic facades in four climate regions in China.

Background: Psoriasis is a chronic and incurable skin inflammation driven by an abnormal immune response. Our study aims to investigate the potential of interferon-γ (IFN-γ) primed mesenchymal stem cells (IMSCs) in targeting T cells to attenuate psoriasis-like inflammation, and to elucidate the underlying molecular mechanism involved. Methods: Mesenchymal stem cells (MSCs) were isolated from the umbilical cord and identified based on their surface markers. Psoriasis models were established and then treated with IMSCs. Flow cytometry analysis was used to examine cell surface markers and T cell percentages. Indoleamine-2,3-dioxygenase (IDO) was knocked down by small interfering RNA (siRNA) and examined with western blot assay. The proliferative capacity of T cells was assessed using water-soluble tetrazolium salt-1(WST-1). Additionally, an immunohistochemical assay was used to determine epidermal thickness. The psoriasis area and severity index (PASI) scores were also assessed. Results: We observed significant therapeutic efficacy of IMSCs against psoriasis-like inflammation in mice. Treatment with IMSCs resulted in a notable reduction in T cell infiltration within psoriatic lesions. Furthermore, we demonstrated that the therapeutic efficacy was mediated by the upregulation of IDO through IFN-γ stimulation. In vitro, IDO inhibited T cell proliferation, and in vivo, the therapeutic efficacy was eliminated when MSCs were transfected with IDO siRNA. Conclusion: IMSCs can treat psoriasis by suppressing T cell infiltration and the suppression is mediated by IDO.

X-linked severe combined immunodeficiency (X-SCID), caused by mutations in the gamma-chain gene of the interleukin-2 receptor (IL2RG), is a prevalent form of SCID characterized by recurrent and fatal opportunistic infections that occur early in life. The incidence of disseminated bacillus Calmette-Guérin (BCG) disease among children with SCID is much higher than in the general population. Here, we report the case of a 4-month-old male infant who presented with subcutaneous induration, fever, an unhealed BCG vaccination site, and hepatosplenomegaly. Metagenomic next-generation sequencing in blood, and the detection of gastric juice and skin nodule pus all confirmed the infection of Mycobacterium tuberculosis. Lymphocyte subset analysis confirmed the presence of T-B+NK immunodeficiency. Whole-exome and Sanger sequencing revealed a novel microdeletion insertion mutation (c.316_318delinsGTGAT p.Leu106ValfsTer42) in the IL2RG gene, resulting in a rare shift in the amino acid sequence of the coding protein. Consequently, the child was diagnosed with X-SCID caused by a novel mutation in IL2RG, complicated by systemic disseminated BCG disease. Despite receiving systemic anti-infection treatment and four days of hospitalization, the patient died three days after discharge. To the best of our knowledge, this specific IL2RG mutation has not been previously reported. In our systemic review, we outline the efficacy of systemic anti-tuberculosis therapy, hematopoietic stem cell transplantation, and gene therapy in children with SCID and BCG diseases caused by IL2RG gene mutation.

Soil salinization is one of the major factors limiting agricultural production. Utilizing beneficial microorganisms like Piriformospora indica (P. indica) to enhance plant tolerance to abiotic stresses is a highly effective method, but the influence of P. indica on the growth of soybean in natural saline-alkaline soil remains unclear. Therefore, we investigated the effects of non-inoculation, P. indica inoculation, and fertilization on the growth, antioxidant defense, osmotic adjustment, and photosynthetic gas exchange parameters of soybean under two different levels of saline-alkaline stress in non-sterilized natural saline-alkaline soil. The study found that: 1) P. indica inoculation significantly promoted soybean growth, increasing plant height, root length, and biomass. Under mildly saline-alkaline stress, the increases were 11.5%, 16.0%, and 14.8%, respectively, compared to non-inoculated treatment. Under higher stress, P. indica inoculation achieved the same level of biomass increase as fertilization, while fertilization only significantly improved stem diameter. 2) Under saline-alkaline stress, P. indica inoculation significantly increased antioxidant enzyme activities and reduced malondialdehyde (MDA) content. Under mildly stress, MDA content was reduced by 47.1% and 43.3% compared to non-inoculated and fertilized treatments, respectively. Under moderate stress, the MDA content in the inoculated group was reduced by 29.9% and 36.6% compared to non-inoculated and fertilized treatments, respectively. Fertilization only had a positive effect on peroxidase (POD) activity. 3) P. indica inoculation induced plants to produce more osmotic adjustment substances. Under mildly stress, proline, soluble sugars, and soluble proteins were increased by 345.7%, 104.4%, and 6.9%, respectively, compared to non-inoculated treatment. Under higher stress, the increases were 75.4%, 179.7%, and 12.6%, respectively. Fertilization had no significant positive effect on proline content. 4) With increasing stress, soybean photosynthetic capacity in the P. indica-inoculated treatment was significantly higher than in the non-inoculated treatment, with net photosynthetic rate increased by 14.8% and 37.0% under different stress levels. These results indicate that P. indica can enhance soybean’s adaptive ability to saline-alkaline stress by regulating ROS scavenging capacity, osmotic adjustment substance content, and photosynthetic capacity, thereby promoting plant growth. This suggests that P. indica has great potential in improving soybean productivity in natural saline-alkaline soils.

BackgroundDietary behaviors significantly influence health outcomes across populations. Unhealthy diets are linked to serious diseases and substantial economic burdens, contributing to approximately 11 million deaths and significant disability-adjusted life years annually. Digital dietary interventions offer accessible solutions to improve dietary behaviors. However, attrition, defined as participant dropout before intervention completion, is a major challenge, with rates as high as 75%-99%. High attrition compromises intervention validity and reliability and exacerbates health disparities, highlighting the need to understand and address its causes. ObjectiveThis study systematically reviews the literature on attrition in digital dietary interventions to identify the underlying causes, propose potential solutions, and integrate these findings with behavior theory concepts to develop a comprehensive theoretical framework. This framework aims to elucidate the behavioral mechanisms behind attrition and guide the design and implementation of more effective digital dietary interventions, ultimately reducing attrition rates and mitigating health inequalities. MethodsWe conducted a systematic review, meta-analysis, and thematic synthesis. A comprehensive search across 7 electronic databases (PubMed, MEDLINE, Embase, CENTRAL, Web of Science, CINAHL Plus, and Academic Search Complete) was performed for studies published between 2013 and 2023. Eligibility criteria included original research exploring attrition in digital dietary interventions. Data extraction focused on study characteristics, sample demographics, attrition rates, reasons for attrition, and potential solutions. We followed ENTREQ (Enhancing the Transparency in Reporting the Synthesis of Qualitative Research) and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and used RStudio (Posit) for meta-analysis and NVivo for thematic synthesis. ResultsOut of the 442 identified studies, 21 met the inclusion criteria. The meta-analysis showed mean attrition rates of 35% for control groups, 38% for intervention groups, and 40% for observational studies, with high heterogeneity (I²=94%-99%) indicating diverse influencing factors. Thematic synthesis identified 15 interconnected themes that align with behavior theory concepts. Based on these themes, the force-resource model was developed to explore the underlying causes of attrition and guide the design and implementation of future interventions from a behavior theory perspective. ConclusionsHigh attrition rates are a significant issue in digital dietary interventions. The developed framework conceptualizes attrition through the interaction between the driving force system and the supporting resource system, providing a nuanced understanding of participant attrition, summarized as insufficient motivation and inadequate or poorly matched resources. It underscores the critical necessity for digital dietary interventions to balance motivational components with available resources dynamically. Key recommendations include user-friendly design, behavior-factor activation, literacy training, force-resource matching, social support, personalized adaptation, and dynamic follow-up. Expanding these strategies to a population level can enhance digital health equity. Further empirical validation of the framework is necessary, alongside the development of behavior theory–guided guidelines for digital dietary interventions. Trial RegistrationPROSPERO CRD42024512902; https://tinyurl.com/3rjt2df9

Abstract The sensitivity of tree growth to precipitation regulates their responses to drought, and is a crucial metric for predicting ecosystem dynamics and vulnerability. Sensitivity may be changing with continuing climate change, yet a comprehensive assessment of its change is still lacking. We utilized tree ring measurements from 3,044 sites, climate data and CO2 concentrations obtained from monitoring stations, combined with dynamic global vegetation models to investigate spatiotemporal changes in the sensitivity over the past century. We observed an increasing sensitivity since around 1950. This increased sensitivity was particularly pronounced in arid biomes due to the combined effect of increased precipitation and elevated CO2. While elevated CO2 reduced the sensitivity of the humid regions, the intensified water pressure caused by decreased precipitation still increased the sensitivity. Our findings suggest an escalating vulnerability of tree growth to precipitation change, which may increase the risk of tree mortality under future intensified drought.

IntroductionPlanting without mulching can eliminate the residual film pollution caused by the long-term use of plastic film covers, but it will increase soil moisture evaporation and heat loss and severely reduce water use efficiency and cotton productivity in cotton (Gossypium hirsutum L.) fields in arid regions. It is unclear whether the advantages of subsurface drip irrigation and nighttime irrigation can be leveraged to reduce the amount of irrigation applied in fields, improve the soil and leaf hydrothermal environments, and increase the synchronicity of yield and water use efficiency (WUE).MethodsTherefore, in a two-year field experiment (2019-2020), cotton was grown under different irrigation treatments (I5, 3753 m3 ha-1; I4, 3477 m3 ha-1; I3, 3201 m3 ha-1; I2, 2925 m3 ha-1; and I1, 2649 m3 ha-1). The soil volumetric moisture content, soil temperature, leaf relative water content (RWC), daily changes in gas exchange parameters, lint yield, and WUE were evaluated.Results and discussionThe results showed that reducing irrigation can reduce the soil volumetric moisture content (0-40 cm soil layer), increase the soil temperature and soil temperature conductivity, and increase the leaf temperature, intercellular carbon dioxide concentration (Ci), and WUE; however, reducing irrigation is not conducive to increasing the leaf RWC, net photosynthetic rate (Pn), stomatal conductance (Gs), or transpiration rate (Tr). There was no significant difference in WUE between the I3 and I4 treatments from 8:00 to 20:00, but the lint yield in these treatments increased by 2.8-12.2% compared to that in the I5 treatment, with no significant difference between the I3 and I4 treatments. In addition, a related analysis revealed that the positive effects of the leaf hydrothermal environment on the Pn and soil temperature on the WUE occurs during the same period (10:00-16:00). Overall, an irrigation amount of 3201-3477 m3 ha-1 applied with a subsurface nighttime irrigation system without mulching can enhance the soil moisture content and soil temperature, maintain a high photosynthetic capacity, and increase the lint yield and WUE. These results revealed that the negative impacts of plastic film contamination in arid areas can be alleviated.

BackgroundIntermediate-stage (BCLC-B) hepatocellular carcinoma (HCC) beyond the up-to-11 criteria represent a significant therapeutic challenge due to high and heterogeneous tumor burden. This study evaluated the effectiveness and safety of transarterial chemoembolization (TACE) in combination with lenvatinib and tislelizumab for these patients.MethodsIn this retrospective cohort study, patients with unresectable intermediate-stage HCC beyond the up-to-11 criteria were enrolled and divided into TACE monotherapy (T), TACE combined with lenvatinib (TL), or TACE plus lenvatinib and tislelizumab (TLT) group based on the first-line treatment, respectively. The primary endpoint was overall survival (OS). The secondary outcomes included progression-free survival (PFS), tumor response according to RESIST1.1 and modified RECIST, and adverse events (AEs).ResultsThere were 38, 45, and 66 patients in the T, TL, and TLT groups, respectively. The TLT group exhibited significantly higher ORR and DCR than the other two groups, as assessed by either mRECIST or RECIST 1.1 (all P

Abstract Background This study aimed to establish a predictive model to estimate the postoperative prognosis of patients with extrahepatic cholangiocarcinoma (ECC) based on preoperative clinical and MRI features. Methods A total of 104 patients with ECC confirmed by surgery and pathology were enrolled from January 2013 to July 2021, whose preoperative clinical, laboratory, and MRI data were retrospectively collected and examined, and the effects of clinical and imaging characteristics on overall survival (OS) were analyzed by constructing Cox proportional hazard regression models. A nomogram was constructed to predict OS, and calibration curves and time-dependent receiver operating characteristic (ROC) curves were employed to assess OS accuracy. Results Multivariate regression analyses revealed that gender, DBIL, ALT, GGT, tumor size, lesion’s position, the signal intensity ratio of liver to paraspinal muscle (SIRLiver/Muscle), and the signal intensity ratio of spleen to paraspinal muscle (SIRSpleen/Muscle) on T2WI sequences were significantly associated with OS, and these variables were included in a nomogram. The concordance index of nomogram for predicting OS was 0.766, and the AUC values of the nomogram predicting 1-year and 2-year OS rates were 0.838 and 0.863, respectively. The calibration curve demonstrated good agreement between predicted and observed OS. 5-fold and 10-fold cross-validation show good stability of nomogram predictions. Conclusions Our nomogram based on clinical, laboratory, and MRI features well predicted OS of ECC patients, and could be considered as a convenient and personalized prediction tool for clinicians to make decisions.

Abstract In coastal seas, the role of atmospheric deposition and river runoff in dissolved organic phosphorus (DOP) utilization is not well understood. Here, we address this knowledge gap by combining microcosm experiments with a global approach considering the relationship between the activity of alkaline phosphatases and changes in phytoplankton biomass in relation to the concentration of dissolved inorganic phosphorus (DIP). Our results suggest that the addition of aerosols and riverine water stimulate the biological utilization of DOP in coastal seas primarily by depleting DIP due to increasing nitrogen concentrations, which enhances phytoplankton growth. This “Anthropogenic Nitrogen Pump” was therefore identified to make DOP an important source of phosphorus for phytoplankton in coastal seas but only when the ratio of chlorophyll a to DIP [Log10 (Chl a / DIP)] is larger than 1.20. Our study therefore suggests that anthropogenic nitrogen input might contribute to the phosphorus cycle in coastal seas.

Abstract Abnormal expression of Cylindromatosis (CYLD), a tumor suppressor molecule, plays an important role in tumor development and treatment. In this work, we found that CYLD binds to class I histone deacetylases (HDAC1 and HDAC2) through its N-terminal domain and inhibits HDAC1 activity. RNA sequencing showed that CYLD-HDAC axis regulates cellular antioxidant response via Nrf2 and its target genes. Then we revealed a mechanism that class I HDACs mediate redox abnormalities in CYLD low-expressing tumors. HDACs are central players in the DNA damage signaling. We further confirmed that CYLD regulates radiation-induced DNA damage and repair response through inhibiting class I HDACs. Furthermore, CYLD mediates nasopharyngeal carcinoma cell radiosensitivity through class I HDACs. Thus, we identified the function of the CYLD-HDAC axis in radiotherapy and blocking HDACs by Chidamide can increase the sensitivity of cancer cells and tumors to radiation therapy both in vitro and in vivo. In addition, ChIP and luciferase reporter assays revealed that CYLD could be transcriptionally regulated by zinc finger protein 202 (ZNF202). Our findings offer novel insight into the function of CYLD in tumor and uncover important roles for CYLD-HDAC axis in radiosensitivity, which provide new molecular target and therapeutic strategy for tumor radiotherapy.

ObjectiveTo comprehensively assess rural environmental sanitation of 25 prefectures/counties/districts in and outside the Yellow River Basin, Shandong province for developing strategies on improvement of rural environmental sanitation. MethodsWe collected monitoring data of 2021 on rural environment sanitation of 25 prefectures/counties/districts of Shandong province; the 13 regions located at the Yellow River Basin were set as cases and the 12 regions outside the basin as controls. Principal component analysis and technique for order preference by similarity to an ideal solution (TOPSIS) analysis was adopted in the assessment. Nine positive high performance indicators were introduced to fit the evaluation model. Regional-specific standardized distance between the scores of each of the nine indicators and optimal ideal solution was utilized to evaluate rural environment sanitation of the 25 prefectures/counties/districts and comprehensive evaluation index was calculated for each of the 25 regions using Euclidean distance approximation method to determine ideal points through TOPSIS. ResultsThe nine core indicators included in the principal component analysis were region-specific annual net income per capita for farmers, annual net income per capital for all rural residents, county-level investment in rural environmental health, construction rate of comprehensive improvement projects for rural sanitation, construction rate of environment sanitation management system, prevalence of sanitary toilet, coverage of centralized rural water supply, transfer ratio of solid waste in rural areas, and transfer ratio of domestic sewage in rural areas. The three identified principal components for rural environment sanitation evaluation were economic condition, sanitation management, and primary health facilities, with the eigenvalues of 2.109, 2.076, and 1.349 and a cumulative contribution rate of 61.485%. Among the top five prefectures/counties/districts with higher values of comprehensive evaluation index, two were located in the Yellow River Basin (Huantai county and Shouguang prefecture, with the scores of 0.705 and 0.665) and three were outside of the basin (Rongcheng, Yanzhou and Gaomi prefectures, with the scores of 0.758, 0.687, and 0.662, respectively). Among the three identified principal components, the score for economic conditions showed the highest coefficient of variation (CV, 0.481) for the regions in the Yellow River Basin; while, the score for rural environmental sanitation management showed the lowest CV (0.114). ConclusionIn rural Shandong, the sanitation management and primary health facilities are better in the regions in the Yellow River Basin but the contribution of the economic situation to the comprehensive index for environment sanitation evaluation is relatively low compared to those in the regions outside of the basin.

A green chemical shear-thickening polishing (GC-STP) method was studied to improve the surface precision and processing efficiency of monocrystalline silicon. A novel green shear-thickening polishing slurry composed of silica nanoparticles, alumina abrasive, sorbitol, plant ash, polyethylene glycol, and deionized water was formulated. The monocrystalline silicon was roughly ground using a diamond polishing slurry and then the GC-STP process. The material removal rate (MRR) during GC-STP was 4.568 μmh−1. The material removal mechanism during the processing of monocrystalline silicon via GC-STP was studied using elemental energy spectroscopy and FTIR spectroscopy. After 4 h of the GC-STP process, the surface roughness (Ra) of the monocrystalline silicon wafer was reduced to 0.278 nm, and an excellent monocrystalline silicon surface quality was obtained. This study shows that GC-STP is a green, efficient, and low-damage polishing method for monocrystalline silicon.

Fresh raspberries are highly perishable, but lactic acid bacteria fermentation offers a favourable method for developing healthy products. This study investigated the effects of Lacticaseibacillus paracasei fermentation on the nutrients and phytochemicals of red raspberry nectar using widely targeted metabolomics, as well as its antioxidant activity. The fermentation notably disrupted the raspberry tissue structure, reshaped its non-volatile composition, and increased its DPPH and hydroxyl free radical scavenging abilities. A total of 261 compounds showed significant differences, with 198 upregulated and 63 downregulated. Among these, certain flavonoid glucosides (e.g., pelargonid-in-3-O-rutinoside, delphinidin-3-O-rutinoside-7-O-glucoside, and kaempferol-3-O-glucoside) were significantly downregulated, while some bioactive phenolic acids (e.g., 3-(4-Hydroxyphenyl)-propionic acid and DL-3-phenyllactic acid), alkaloids (e.g., deoxymutaaspergillic acid and indole-3-lactic acid), amino acids (e.g., L-phenylalanine and L-glutamine), and B vitamins (e.g., VB6, VB7, and VB3) were substantially upregulated. Furthermore, the Kyoto Encyclopedia of Genes and Genomes (KEGG) annotation and enrichment analysis revealed that metabolic pathways and the biosynthesis of secondary metabolites contributed significantly to the new profile of fermented red raspberry nectar. These findings provide valuable insights for developing fermented raspberry products using Lacticaseibacillus paracasei, which can help minimise fresh raspberry loss and enhance their valorisation.