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In order to give full play to the advantages of shared energy storage in improving economy and energy utilization, while considering the role of multi-energy complementation and coupling of integrated energy microgrids in active distribution networks, a multi-objective optimal allocation strategy of shared energy storage is proposed for the active distribution network connected with integrated energy microgrid. First, the optimization objectives of the economy and voltage stability of the distribution network and the configuration capacity of the shared energy storage are analyzed, the coordinated operation of the source-net-load side multi-flexible resources of the active distribution network is considered, and the active distribution network and the integrated energy microgrid are modeled. Then, the model is solved based on the Pareto optimal multi-objective particle swarm algorithm. Finally, the optimization algorithm of shared energy storage configuration is established in conjunction with the IEEE 33-node distribution system to verify the effectiveness of the proposed configuration strategy.

Aiming at the uncertainty of the source and load in micro energy grid, a robust optimal scheduling model considering multi-interval uncertainty set of source-load and integrated demand response is proposed. First, considering the uncertainty of wind power, photovoltaic output and electric, and thermal and cooling loads in the micro energy grid, a multi-interval uncertainty set of source-load is established. Then, in order to fully tap the potential of load side dispatching, an integrated demand response model is established, which includes reducible electric load, transferable electric load, flexible cooling, heating load, and replaceable load, based on which, the uncertainty of integrated demand response is considered. Afterwards, with the lowest dispatching cost of micro energy grid as the objective function, a two-stage robust optimal scheduling model of micro energy network is constructed, which considers the multi-interval uncertainty set of source load and the integrated demand response. The model is solved by the column and constraint generation algorithm, the strong duality theory, and the large M method. Finally, the rationality and effectiveness of the proposed model are verified through the analysis of numerical examples.

Abstract The complexity of brain activity reflects its ability to process information, adapt to environmental changes, and transition between states. However, it remains unclear how schizophrenia (SZ) affects brain activity complexity, particularly its dynamic changes. This study aimed to investigate the abnormal patterns of brain activity complexity in SZ, their relationship with cognitive deficits, and the impact of antipsychotic medication. Forty-four drug-naive first-episode (DNFE) SZ patients and thirty demographically matched healthy controls (HC) were included. Functional MRI-based sliding window analysis was utilized for the first time to calculate weighted permutation entropy to characterize complex patterns of brain activity in SZ patients before and after 12 weeks of risperidone treatment. Results revealed reduced complexity in the caudate, putamen, and pallidum at baseline in SZ patients compared to HC, with reduced complexity in the left caudate positively correlated with Continuous Performance Test (CPT) and Category Fluency Test scores. After treatment, the complexity of the left caudate increased. Regions with abnormal complexity showed decreased functional connectivity, with complexity positively correlated with connectivity strength. We observed that the dynamic complexity of the brain exhibited the characteristic of spontaneous, recurring “complexity drop”, potentially reflecting transient state transitions in the resting brain. Compared to HC, patients exhibited reduced scope, intensity, and duration of complexity drop, all of which improved after treatment. Reduced duration was negatively correlated with CPT scores and positively with clinical symptoms. The results suggest that abnormalities in brain activity complexity and its dynamic changes may underlie cognitive deficits and clinical symptoms in SZ patients. Antipsychotic treatment partially restores these abnormalities, highlighting their potential as indicators of treatment efficacy and biomarkers for personalized therapy.

Obesity-induced chronic inflammation exacerbates multiple types of tissue/organ deterioration and stem cell dysfunction; however, the effects on skeletal tissue and the underlying mechanisms are still unclear. Here, we show that obesity triggers changes in the microRNA profile of macrophage-secreted extracellular vesicles, leading to a switch in skeletal stem/progenitor cell (SSPC) differentiation between osteoblasts and adipocytes and bone deterioration. Bone marrow macrophage (BMM)-secreted extracellular vesicles (BMM-EVs) from obese mice induced bone deterioration (decreased bone volume, bone microstructural deterioration, and increased adipocyte numbers) when administered to lean mice. Conversely, BMM-EVs from lean mice rejuvenated bone deterioration in obese recipients. We further screened the differentially expressed microRNAs in obese BMM-EVs and found that among the candidates, miR-140 (with the function of promoting adipogenesis) and miR-378a (with the function of enhancing osteogenesis) coordinately determine SSPC fate of osteogenic and adipogenic differentiation by targeting the Pparα-Abca1 axis. BMM miR-140 conditional knockout mice showed resistance to obesity-induced bone deterioration, while miR-140 overexpression in SSPCs led to low bone mass and marrow adiposity in lean mice. BMM miR-378a conditional depletion in mice led to obesity-like bone deterioration. More importantly, we used an SSPC-specific targeting aptamer to precisely deliver miR-378a-3p-overloaded BMM-EVs to SSPCs via an aptamer-engineered extracellular vesicle delivery system, and this approach rescued bone deterioration in obese mice. Thus, our study reveals the critical role of BMMs in mediating obesity-induced bone deterioration by transporting selective extracellular-vesicle microRNAs into SSPCs and controlling SSPC fate.

A droop-free distributed energy storage control strategy based on the diffusion algorithm is proposed to address the inability of droop control to simultaneously achieve bus voltage stability and accurate power distribution among energy storage systems when the line impedance is mismatched and bus voltage is inconsistent. First, the diffusion algorithm is applied to the distributed estimation of direct current (DC) microgrid to obtain the global average, and the difference between the voltage rating and the average voltage is used as a compensation term to restore the bus voltage deviation. Then, in order to achieve the accurate distribution of power between energy storage systems with different rated capacities and different states of charge (SOC), a standard power of energy storage is designed and the difference between the standard power and the average standard power is used as a compensation term for the equilibrium of SOC between energy storage systems. Finally, a model based on RT-LAB is built to verify the effectiveness of the designed control strategy in four different operating modes. The experimental results show that the proposed control strategy can achieve the bus voltage recovery and the accurate distribution of energy storage power in the isolated DC microgrid.

ObjectiveThis study examines biosafety management practices in a psychiatric hospital’s laboratory in China, focusing on how outdated information technology impacts the hospital’s ability to respond to public health emergencies. The goal is to enhance the hospital’s emergency response capabilities by updating risk assessments, biosafety manuals, and implementing a comprehensive quality management system alongside a specialized infection control system for significant respiratory diseases.MethodsWe utilized an integrated research approach, expanding the scope of risk assessments, updating the biosafety manual according to the latest international standards, and implementing a quality management system. A specialized infection control system for significant respiratory diseases was introduced to improve emergency response capabilities.ResultsUpdated risk assessments and a new biosafety manual have significantly improved the identification and management of biosafety threats. Implementing new quality management and infection control systems has enhanced response efficiency and operational standardization.ConclusionThe measures taken have strengthened the biosafety management and emergency response capabilities of the laboratory department, highlighting the importance of information technology in biosafety management and recommending similar strategies for other institutions.

Abstract Lower-grade gliomas (LGGs) exhibit highly variable clinical behaviors, while classic histology characteristics cannot accurately reflect the authentic biological behaviors, clinical outcomes, and prognosis of LGGs. In this study, we carried out analyses of whole exome sequencing, RNA sequencing and DNA methylation in primary vs. recurrent LGG samples, and also combined the multi-omics data to construct a prognostic prediction model. TCGA-LGG dataset was searched for LGG samples. 523 samples were used for whole exome sequencing analysis, 532 for transcriptional analysis, and 529 for DNA methylation analysis. LASSO regression was used to screen genes with significant association with LGG survival from the frequently mutated genes, differentially expressed genes, and differentially methylated genes, whereby a prediction model for prognosis of LGG was further constructed and validated. The most frequently mutated diver genes in LGGs were IDH1 (77%), TP53 (48%), ATRX (37%), etc. Top significantly up-regulated genes were C6orf15, DAO, MEOX2, etc., and top significantly down-regulated genes were DMBX1, GPR50, HMX2, etc. 2077 genes were more and 299 were less methylated in recurrent vs. primary LGG samples. Thirty-nine genes from the above analysis were included to establish a prediction model of survival, which showed that the high-score group had a very significantly shorter survival than the low-score group in both training and testing sets. ROC analysis showed that AUC was 0.817 for the training set and 0.819 for the testing set. This study will be beneficial to accurately predict the survival of LGGs to identify patients with poor prognosis to take specific treatment as early, which will help improve the treatment outcomes and prognosis of LGG.

TP53, a guardian of the genome, suppresses or enhances tumors through various regulatory pathways. However, the role of p53-related long non-coding RNAs (lncRNAs) in immune regulation of tumor microenvironment and prognosis of gastric cancer (GC) is so far unelucidated. We analyzed the role of TP53-associated lncRNAs (obtained from the TP53LNC-DB database) in immune regulation, immune cell infiltration and RNA modification in gastric cancer. Firstly, using multivariate COX regression analysis, we identified eight lncRNAs related to the prognosis of GC. Furthermore, based on the expression of the lncRNA signature and risk score, the GC patients were divided into high-risk and low-risk groups. We found that M2-macrophages have significantly higher infiltration in the high-risk group. Similarly, significant differences in immune function (APC_co_stimulation, CCR, and checkpoint) and m6A modification (FTO, ZC3H13, YTHDC1, and RBM15), and m5C modification (NOP2 and TET1) between both groups were also observed. These signature lncRNAs were also positively associated with oxidative stress-related genes (MPO, MAPK14, HMOX1, and APP). Additionally, we found that high expression of GAS5 and low expression of MALAT1 in Helicobacter pylori (H-pylori) positive GC patients. Finally, GC patients in the low-risk group showed higher resistance to immunotherapy while patients in the high-risk group were more sensitive to various chemotherapy drugs. Based on these findings, we conclude that p53-associated lncRNAs signature could potentially predict the immune status and overall survival, and may also be used for risk management and planning immunotherapy for gastric cancer patients.

Sun-induced chlorophyll fluorescence (SIF) has been a promising indicator of plants’ physiological status, but its response to physiological changes under the verticillium wilt (VW) stress of cotton plants is complicated by concurrent nonphysiological changes. The relative contributions of the above two components to SIF variations are unclear at different VW stress severities, hindering the accurate diagnosis of VW levels. Therefore, the objective of this study is to investigate the dynamic responses of SIF, physiological and nonphysiological factors, and to evaluate the contributions of the two factors to SIF variations under different VW stress degrees of cotton. We continuously observed the diurnal variation of the top-of-canopy reflectance and SIF on healthy and VW-infected cotton during the peak incidence period of VW disease. To accurately quantify the relative contribution of each component to SIF, we proposed a practical strategy to estimate unmeasurable parameter when using Lindeman, Merenda, and Gold method. The results demonstrated the dominant role of physiological factors in SIF with an arch diurnal change pattern at the early stages of VW development. As the VW severity increased, the contribution of physiological components declined, with the maximum contribution decreasing by 47.7%, and the diurnal pattern was disrupted, with the diurnal variation amplitude of the parameter declining by 63.4%, followed by a shift in the regulatory role toward nonphysiological factors. This study contributes to a further understanding of the roles of physiological and nonphysiological components in SIF variations of cotton under VW stress, thus advancing the accurate monitoring of VW stress severity.

Abstract Skeletal stem/progenitor cell (SSPC) senescence is a major cause of decreased bone regenerative potential with aging, but the causes of SSPC senescence remain unclear. In this study, we revealed that macrophages in calluses secrete prosenescent factors, including grancalcin (GCA), during aging, which triggers SSPC senescence and impairs fracture healing. Local injection of human rGCA in young mice induced SSPC senescence and delayed fracture repair. Genetic deletion of Gca in monocytes/macrophages was sufficient to rejuvenate fracture repair in aged mice and alleviate SSPC senescence. Mechanistically, GCA binds to the plexin-B2 receptor and activates Arg2-mediated mitochondrial dysfunction, resulting in cellular senescence. Depletion of Plxnb2 in SSPCs impaired fracture healing. Administration of GCA-neutralizing antibody enhanced fracture healing in aged mice. Thus, our study revealed that senescent macrophages within calluses secrete GCA to trigger SSPC secondary senescence, and GCA neutralization represents a promising therapy for nonunion or delayed union in elderly individuals.

In response to the defects of the traditional centralized economic dispatching strategy which needs to obtain global information and cannot adapt to the flexible topology of the system, and considering the coexistence of energy in the form of electricity and heat, a completely distributed cogeneration economic dispatching strategy based on the consistency algorithm is proposed. The incremental cost of electricity price and heat price of each unit in the cogeneration system is taken as the consistent variable to conduct the iterative calculation until the incremental cost converges to achieve the economic optimum of the system. In addition, the case of individual unit transmitting to neighboring units with deviating incremental cost values in order to enhance their own interests is also analyzed, and an incremental cost compensation term is designed to eliminate the impact of this selfish behavior. The simulation results indicate that the proposed strategy is effective and viable in the solution of the cogeneration economic dispatching problems.

Nitrogen fertilizer levels significantly affect crop growth and development, necessitating precision management. Most studies focus on nitrogen nutrient estimation using vegetation indices and textural features, overlooking the diagnostic potential of color features. Hence, we investigated cotton nitrogen nutrition status using unmanned aerial vehicle (UAV) image features and the nitrogen nutrient index (NNI). Random frog algorithm - and random forest-screened image feature sets significantly correlated with the NNI, which were substituted into four machine learning algorithms for NNI estimation modeling. The composite scores (F) of optimal image feature sets were calculated using the coefficient of variation method for comprehensive cotton nitrogen nutrient diagnosis. Validation of the model for determining the critical nitrogen concentration in cotton yielded a coefficient of determination R2 = 0.89, root mean square error RMSE = 0.50 g (100 g)-1, and mean absolute error MAE = 0.44, demonstrating improved performance. Additionally, our novel NNI estimation model constructed based on the optimal image feature sets exhibited R2c = 0.97, RMSEc = 0.02, MAEc = 0.02, R2v = 0.85, RMSEv = 0.05, and MAEv = 0.04. Polynomial fitting of the composite index with NNI indicated that the model was reliable and yielded the following diagnostic criterion: 0.48 < F2 < 0.67 indicated nitrogen overapplication, whereas F2 < 0.48 or F2 > 0.67 indicated nitrogen deficiency. This study demonstrates the superior effectiveness of using UAV RGB image feature sets for NNI estimation and the quick, accurate diagnosis of cotton nitrogen levels, which will help guide nitrogen fertilizer application.

This case report documents the first instance of Penicillin-Susceptible Methicillin-Resistant Staphylococcus aureus (PS-MRSA) in a Chinese psychiatric hospital. The strain was isolated from a patient with Alzheimer’s disease who had a lower respiratory tract infection. Clinical and laboratory analyses, including mass spectrometry, antibiotic susceptibility testing, and whole-genome sequencing, confirmed the PS-MRSA strain. In this case, we systematically introduce the clinical symptoms, laboratory findings, and treatment responses associated with this PS-MRSA strain. This discovery offers a new perspective on our understanding of resistance mechanisms and expands our considerations for existing antibiotic treatments. It may fill a gap in the classification of MRSA strains, enhance the spectrum of MRSA resistance, and complete the therapeutic strategies for MRSA.

Abstract Background Schizophrenia is a common mental disorder that seriously affects patients’ daily lives and brings heavy psychological and economic burdens to their families and society. The oral problems of patients with schizophrenia are gradually gaining attention, among which dental caries are among the most common oral diseases. Sex differences may be related not only to the various clinical symptoms of schizophrenia but also to different oral hygiene statuses; therefore, the main purpose of this paper is to investigate sex differences related to influencing factors for dental caries in patients with schizophrenia. Method Inpatients with schizophrenia over 18 years old were included in this study, and multidimensional indicators such as demographics, symptom and cognitive impairment assessments, medications, and the caries index of decayed, missing, and filled teeth (DMFT) were collected. An analysis of sex-based influential factors for dental caries in schizophrenia patients was performed. Results Four-hundred and ninety-six patients with schizophrenia were included, with a mean age of 46.73 ± 12.23 years, of which 142 were females and 354 were males. The mean DMFT was significantly higher in males (8.81 ± 8.50) than in females (5.63 ± 6.61, p

Nitrogen (N) is an essential macronutrient for plant growth and productivity. Leguminous plants establish symbiotic relationships with nitrogen-fixing rhizobial bacteria to use atmospheric dinitrogen gas to meet high N demand under low-N conditions. Nodule formation and N fixation are energy-consuming processes and are inhibited by nitrate present in the environment. Previous studies in model leguminous plants characterized NIN-LIKE PROTEIN (NLP) proteins that mediate nitrate control of root nodule symbiosis, but the mechanism by which nitrate regulates soybean root nodules via NLP remains unclear. In the soybean genome we found four homologs of AtNLP7, named GmNLP7a–GmNLP7d. We showed that the expression of GmNLP7s is responsive to nitrate but not to rhizobial infection and localized GmNLP7a to the nucleus. Downregulation of GmNLP7s increased nodule number, and overexpression of GmNLP7a (GmNLP7aOE) reduced nodule number regardless of nitrate availability, suggesting a negative role for GmNLP7s in nodulation. Nitrogenase activity in the GmNLP7aOE line was comparable to that of the wild type, indicating that GmNLP7a does not affect mature nodule activity. Overexpression of GmNLP7a downregulated the expression of GmNIN1a and GmENOD40-1. GmNLP7a interacted with GmNIN1a via the PB1 domain. Our results reveal a new regulator of GmNLP7 in nodulation and a molecular mechanism by which nitrate affects nodule number in soybean.

Abstract Purpose For postoperative vaginal brachytherapy (POVBT), the diversity of applicators complicates the creation of a generalized auto‐segmentation model, and creating models for each applicator seems difficult due to the large amount of data required. We construct an auto‐segmentation model of POVBT using small data via domain‐adversarial neural networks (DANNs). Methods CT images were obtained postoperatively from 90 patients with gynaecological cancer who underwent vaginal brachytherapy, including 60 and 30 treated with applicators A and X, respectively. A basal model was devised using data from the patients treated with applicator A; next, a DANN model was constructed using these same 60 patients as well as 10 of those treated with applicator X through transfer learning techniques. The remaining 20 patients treated with applicator X comprised the validation set. The model's performance was assessed using objective metrics and manual clinical evaluation. Results The DANN model outperformed the basal model on both objective metrics and subjective evaluation (p

Aimed at the impact of extreme weather on the stable operation of microgrid, an optimal configuration strategy of microgrid based on fuzzy scene clustering is proposed. Using historical weather data, a fuzzy scene clustering method is used to deal with the problem of new energy output fluctuations caused by random weather on the source side, and a robust optimization model is established on the load side to deal with load fluctuations within a certain range. Using scenes of 8 760 hours in a year, typical scenes and extreme scenes are obtained by distinguishing the unique membership characteristics of fuzzy scene clusters. Considering the impact of extreme scenarios on the optimal configuration of the microgrid, a two-stage robust model with the smallest comprehensive cost is established, which is decomposed by the column and constraint method, and is finally solved iteratively by Cplex solver. The effectiveness and feasibility of the proposed optimal configuration strategy are verified by simulation analysis.

Abstract Background Increasing body fat or decreasing muscle and bone mass were associated with worse health outcomes in the adult population. The effects of nickel exposure on body composition are not known. The aim of the current study was to investigate the relationship between urinary nickel levels and body compositions. Materials and methods Two thousand seven hundred sixty-two participants were included in the analysis from the National Health and Nutrition Examination Surveys of 2017–2018 after excluding participants who have missing data on urinary nickel and those with missing all body mass component data. We used weighted generalized linear models to explore the relationship between urinary nickel and body mass components under interpolating missing covariable values. Simultaneously, sensitivity analyses and subgroup analysis were conducted to verify stability of analysis result. Curve fitting and saturation effect analysis were used to explore the possible nonlinear relationship between urine nickel and body compositions. Results Among the 2,762 participants, the average urinary nickel level was 1.58 ug/L. The weighted generalized linear models, the sensitivity analyses and subgroup analyses found no significant linear relationship between urinary nickel and body compositions. For body weight, BMI, TLM, ALM, TRF, TOF and BMC, the urine nickel saturation effect values were 0.76, 0.74, 0.5, 0.67, 0.64, 0.48, and 0.45 ug/L, respectively. For each 1 ug/L rise in urinary nickel levels at levels below the turning point, body weight increases (β = 9.06, 95% CI = 2.75, 15.36, p = 0.01), BMI increases (β = 3.20, 95% CI = 1.36, 5.05, p =

Verticillium wilt (VW) is a common soilborne disease of cotton. It occurs mainly in the seedling and boll-opening stages and severely impairs the yield and quality of the fiber. Rapid and accurate identification and evaluation of VW severity (VWS) forms the basis of field cotton VW control, which has great significance to cotton production. Cotton VWS values are conventionally measured using in-field observations and laboratory test diagnoses, which require abundant time and professional expertise. Remote and proximal sensing using imagery and spectrometry have great potential for this purpose. In this study, we performed in situ investigations at three experimental sites in 2019 and 2021 and collected VWS values, in situ images, and spectra of 361 cotton canopies. To estimate cotton VWS values at the canopy scale, we developed two deep learning approaches that use in situ images and spectra, respectively. For the imagery-based method, given the high complexity of the in situ environment, we first transformed the task of healthy and diseased leaf recognition to the task of cotton field scene classification and then built a cotton field scenes (CFS) dataset with over 1000 images for each scene-unit type. We performed pretrained convolutional neural networks (CNNs) training and validation using the CFS dataset and then used the networks after training to classify scene units for each canopy. The results showed that the DarkNet-19 model achieved satisfactory performance in CFS classification and VWS values estimation (R2 = 0.91, root-mean-square error (RMSE) = 6.35%). For the spectroscopy-based method, we first designed a one-dimensional regression network (1D CNN) with four convolutional layers. After dimensionality reduction by sensitive-band selection and principal component analysis, we fitted the 1D CNN with varying numbers of principal components (PCs). The 1D CNN model with the top 20 PCs performed best (R2 = 0.93, RMSE = 5.77%). These deep learning-driven approaches offer the potential of assessing crop disease severity from spatial and spectral perspectives.

Introduction: Although previous studies investigated the potential adverse effects of endocrine-disrupting chemicals (EDCs) on biological age acceleration and aging-related diseases, the mixed effect of multiple types of EDCs on biological age acceleration, including its potential underlying mechanism, remains unclear. Methods: Data from the National Health and Nutrition Examination Survey (NHANES) were used to analyze biological age measures, including Klemera-Doubal method biological age (KDM-BA), phenotypic age, and homeostatic dysregulation (HD). Weight quantile sum (WQS) regression was performed to screen biological age-related EDCs (BA-EDCs) and assess the mixed effect of BA-EDCs on biological age acceleration and aging-related disease. Targets of BA-EDCs were obtained from three databases, while heart aging-related genes were obtained from the Aging Anno database. Protein–protein interaction (PPI) network and MCODE algorithm were applied to identify potential interactions between BA-EDC targets and heart aging-related genes. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed to identify related pathways. Results: This cross-sectional study included 1,439 participants. A decile increase in BA-EDCs co-exposure was associated with 0.31 years and 0.17 years of KDM-BA and phenotypic age acceleration, respectively. The mixed effect of BA-EDCs was associated with an increased prevalence of atherosclerotic cardiovascular disease (ASCVD). Vitamins C and E demonstrated a significant interaction effect on the association between BA-EDCs and KDM-BA acceleration. PPI network and functional enrichment analysis indicated that the AGE-RAGE signaling pathway in diabetic complications was significantly enriched. Conclusion: Our results showed that the co-exposure effect of BA-EDCs was associated with biological age acceleration and ASCVD, with the AGE-RAGE signaling pathway being the underlying mechanism. Vitamins C and E may also be an actionable target for preventing EDC-induced biological aging.

This study aimed to explore the feasibility of applying Generative Adversarial Networks (GANs) for the diagnosis of Verticillium wilt disease in cotton and compared it with traditional data augmentation methods and transfer learning. By designing a model based on small-sample learning, we proposed an innovative cotton Verticillium wilt disease diagnosis system. The system uses Convolutional Neural Networks (CNNs) as feature extractors and applies trained GAN models for sample augmentation to improve classification accuracy. This study collected and processed a dataset of cotton Verticillium wilt disease images, including samples from normal and infected plants. Data augmentation techniques were used to expand the dataset and train the CNNs. Transfer learning using InceptionV3 was applied to train the CNNs on the dataset. The dataset was augmented using GAN algorithms and used to train CNNs. The performances of the data augmentation, transfer learning, and GANs were compared and analyzed. The results have demonstrated that augmenting the cotton Verticillium wilt disease image dataset using GAN algorithms enhanced the diagnostic accuracy and recall rate of the CNNs. Compared to traditional data augmentation methods, GANs exhibit better performance and generated more representative and diverse samples. Unlike transfer learning, GANs ensured an adequate sample size. By visualizing the images generated, GANs were found to generate realistic cotton images of Verticillium wilt disease, highlighting their potential applications in agricultural disease diagnosis. This study has demonstrated the potential of GANs in the diagnosis of cotton Verticillium wilt disease diagnosis, offering an effective approach for agricultural disease detection and providing insights into disease detection in other crops.

Abstract Background This study aimed to investigate the correlation between enlarged perivascular space (EPVS) and white matter hyperintensities (WMH) at different locations in patients with recent small subcortical infarct (RSSI). Methods Data were collected from patients with RSSI who were hospitalized at Changzhou Second People's Hospital between October 2020 and December 2021. All patients underwent cranial magnetic resonance imaging, and the grades of EPVS and WMH were assessed, including basal ganglia EPVS (BG‐EPVS), centrum semiovale EPVS (CSO‐EPVS), deep WMH (DWMH), and periventricular WMH (PWMH). The volumes of EPVS and WMH at different locations were quantified using 3D Slicer software. Patients were grouped according to the severity of BG‐EPVS and CSO‐EPVS. Univariate and multivariate analyses were used to analyze the relationship between EPVS and WMH. Results A total of 215 patients with RSSI were included in the analysis. Patients with moderate‐to‐severe BG‐EPVS had higher DWMH and PWMH severity than those with mild BG‐EPVS, both in terms of volume and grade. There was no significant difference in WMH severity between patients with mild CSO‐EPVS and those with moderate‐to‐severe CSO‐EPVS. Multivariate analysis indicated that after adjustments were made for confounding factors, DWMH volume (β = 0.311; 95% CI, 0.089–0.400; p = .002) and PWMH volume (β = 0.296; 95% CI, 0.083–0.424; p = .004) were independently associated with BG‐EPVS. Pearson correlation showed that PWMH volume (r = .589; p

Abstract Background Using nanotechnology to improve the efficiency of tumor treatment represents a major research interest in recent years. However, there are paradoxes and obstacles in using a single nanoparticle to fulfill all the requirements of complex tumor treatment. Results In this paper, a programmed-triggered nanoplatform (APP NPs), which is sequentially responsive to light and hypoxia, is rationally integrated for photoacoustic (PA) imaging-guided synergistic cancer photo-chemotherapy. The nanoplatform is constructed by in situ hybridization of dopamine monomer in the skeleton of PCN-224 and loading prodrug banoxantrone (AQ4N). Upon first-stage irradiation with a 660 nm laser, cellular internalization was effectively promoted by a photosensitizer-mediated photochemical effect. Furthermore, under second-stage irradiation, APP NPs exhibit a notably high photothermal conversion efficiency and sufficient reactive oxygen species (ROS) production for photothermal therapy (PTT) and photodynamic therapy (PDT), respectively, which not only triggers rapid intercellular drug release but also consequently aggravates tumor hypoxia levels, and aggravated hypoxia can further active the cytotoxicity of AQ4N for chemotherapy. Both in vitro and in vivo studies confirm that the dual-stage light guided photo-chemotherapy strategy exhibits a greatly enhanced anticancer effects and superior therapeutic safety. Conclusion This work represents a versatile strategy to construct a dual-stage light induced PDT/PTT and hypoxia-activated chemotherapy nanoplatform and will be promising for the development of multistimuli-responsive nanosystems with programmable functions for precise cancer therapy.

Abstract Background Bisphenol A (BPA) exposure and its structural analogs (BPS and BPF) might cause endocrine alterations and adverse physiological effects. Few studies to date have directly explored the association between its structural analogs (BPS, BPF) and sex hormones in adult male participants. Therefore, we aimed to assess the associations between BPA, BPS, BPF, and sex hormones in American adult men. Methods We used data from the U.S. National Health and Nutrition Examination Survey 2011–2016. We excluded participants without data available on sex hormones and urinary bisphenols. Furthermore, participants consuming sex hormone medications were excluded. Multivariable regression models were performed to assess the association between bisphenols and sex hormones. Results In this study, 2367 participants were included. Of 2367, in 1575 participants, the data on BPS and BPF were available. We found that a per unit increase in BPF was associated with 0.575 ng/dL higher total testosterone (TT) (Model 2: 95% CI: 0.047, 1.103, P = 0.033). However, there was no significant association between BPA or BPS and TT. Furthermore, increased BPA and BPS levels were associated with higher levels of sex hormone-binding globulin (SHBG) (Model 2: β = 0.364, 95% CI: 0.158, 0.571; β = 0.25, 95% CI: 0.071, 0.429, respectively). Additionally, participants in the highest BPA exposure quartile (quartile 4) had 4.072 nmol/L higher levels of SHBG than those in quartile 1 (Model 2: 95% CI: 0.746, 7.397, P = 0.017; P for trend =0.005). Both BPA and BPS were negatively associated with free testosterone (FT, nmol/L) after full adjustment (Model 2, β = − 0.01%, P = 0.0211, P = 0.0211; Model 2, β = − 0.01%, P = 0.0258, respectively). However, BPF was positively associated with FT (Model 2, β = 0.0029%, P = 0.0028). Conclusion Our study indicated that exposure to both BPA and its substitutions could alter sex hormone levels. This finding supports the possibility that human exposure to bisphenols at environmental levels might affect the endogenous hormone balance.

We fabricated an ultrasound activated ‘nanobomb’ as a noninvasive and targeted physical therapeutic strategy for sonodynamic therapy and priming cancer immunotherapy. This ‘nanobomb’ was rationally designed via the encapsulation of indocyanine green (ICG) and perfluoropentane (PFP) into cRGD peptide-functionalized nano-liposome. The resulting Lip-ICG-PFP-cRGD nanoparticle linked with cRGD peptide could actively targeted ID8 and TC-1 cells and elicits ROS-mediated apoptosis after triggered by low-intensity focused ultrasound (LIFU). Moreover, the phase change of PFP (from droplets to microbubbles) under LIFU irradiation can produce a large number of microbubbles, which act as intra-tumoral bomber and can detonate explode tumor cells by acoustic cavitation effect. Instant necrosis of tumor cells further induces the release of biologically active damage-associated molecular patterns (DAMPs) to facilitate antitumor immunity. More important, the ‘nanobomb’ in combination with anti-PD-1checkpoint blockade therapy can significantly improve the antitumor efficacy in a subcutaneous model. In addition, the liposomes may also be used as an imaging probe for ultrasound (US) imaging after being irradiated with LIFU. In summary, the US imaging-guided, LIFU activated ROS production and explosion ‘nanobomb’ might significantly improve the antitumor efficacy and overcome drug resistance through combination of SDT and immunotherapy, we believe that this is a promising approach for targeted therapy of solid tumor including ovarian cancer.

Safe, efficacious, and deployable vaccines are urgently needed to control COVID-19 in the large-scale vaccination campaigns. We report here the preclinical studies of an approved protein subunit vaccine against COVID-19, ZF2001, which contains tandem-repeat dimeric receptor-binding domain (RBD) protein with alum-based adjuvant. We assessed vaccine immunogenicity and efficacy in both mice and non-human primates (NHPs). ZF2001 induced high levels of RBD-binding and SARS-CoV-2 neutralizing antibody in both mice and non-human primates, and elicited balanced TH1/TH2 cellular responses in NHPs. Two doses of ZF2001 protected Ad-hACE2-transduced mice against SARS-CoV-2 infection, as detected by reduced viral RNA and relieved lung injuries. In NHPs, vaccination of either 25 μg or 50 μg ZF2001 prevented infection with SARS-CoV-2 in lung, trachea, and bronchi, with milder lung lesions. No evidence of disease enhancement was observed in both animal models. ZF2001 has been approved for emergency use in China, Uzbekistan, Indonesia, and Columbia. The high safety, immunogenicity, and protection efficacy in both mice and NHPs found in this preclinical study was consistent with the results in human clinical trials.

Abstract Islet β cell dysfunction and insulin resistance are the main pathogenesis of type 2 diabetes (T2D), but the mechanism remains unclear. Here we identify a rs3819316 C > T mutation in lncRNA Reg1cp mainly expressed in islets associated with an increased risk of T2D. Analyses in 16,113 Chinese adults reveal that Mut-Reg1cp individuals had higher incidence of T2D and presented impaired insulin secretion as well as increased insulin resistance. Mice with islet β cell specific Mut-Reg1cp knock-in have more severe β cell dysfunction and insulin resistance. Mass spectrometry assay of proteins after RNA pulldown demonstrate that Mut-Reg1cp directly binds to polypyrimidine tract binding protein 1 (PTBP1), further immunofluorescence staining, western blot analysis, qPCR analysis and glucose stimulated insulin secretion test reveal that Mut-Reg1cp disrupts the stabilization of insulin mRNA by inhibiting the phosphorylation of PTBP1 in β cells. Furthermore, islet derived exosomes transfer Mut-Reg1cp into peripheral tissue, which then promote insulin resistance by inhibiting AdipoR1 translation and adiponectin signaling. Our findings identify a novel mutation in lncRNA involved in the pathogenesis of T2D, and reveal a new mechanism for the development of T2D.

Cotton yield estimation is of great practical significance to producers, allowing them to make rational management decisions. At present, crop yield estimation methods mainly comprise traditional agricultural yield estimation methods, which have many shortcomings. As an ideal “probe” for detecting crop photosynthesis, sun-induced chlorophyll fluorescence (SIF) can directly reflect the dynamics of actual crop photosynthesis and has the potential to predict crop yield, in order to realize cotton yield estimation based on canopy SIF. In this study, we set up field trials with different nitrogen fertilizer gradients. The changes of canopy SIF and the physiological parameters of cotton in different growth periods were analyzed. To investigate the effects of LAI and AGB on canopy SIF estimation of cotton yield, four algorithms, Ada Boost (Adaptive Boosting), Bagging (Bootstrap Aggregating), RF (Random Forest), and BPNN (Backpropagation Neural Network), were used to construct cotton yield estimation models based on the SIF and SIFy (the normalization of SIF by incident photosynthetically active radiation) for different time and growth periods. The results include the following: (1) The effects of the leaf area index (LAI) and aboveground biomass (AGB) on cotton canopy SIF and cotton yield were similar. The correlation coefficients of LAI and AGB with cotton yield and SIF were significantly positively correlated with each other starting from the budding period, reaching the maximum at the flowering and boll period, and decreasing at the boll period; (2) In different monitoring time periods, the R2 of the cotton yield estimation model established based on SIF and SIFy showed a gradual increase from 10:00 to 14:00 and a gradual decrease from 15:00 to 19:00, while the optimal observation time was from 14:00 to 15:00. The R2 increased with the progression of growth from the budding period to the flowering and boll period and decreased at the boll period, while the optimum growth period was the flowering and boll period; (3) Compared to SIF, SIFy has a superior estimation of yield. The best yield estimation model based on the RF algorithm (R2 = 0.9612, RMSE = 66.27 kg·ha−1, RPD = 4.264) was found in the canopy SIFy of the flowering and boll period at 14:00–15:00, followed by the model utilizing the Bagging algorithm (R2 = 0.8898) and Ada Boost algorithm (R2 = 0.8796). In summary, SIFy eliminates the effect of PAR (photosynthetically active radiation) on SIF and can further improve the estimation of SIF production. This study provides empirical support for SIF estimation of cotton yield and methodological and modeling support for the accurate estimation of cotton yield.

Abstract Background Fever of unknown origin (FUO) has been difficult to diagnose in pediatric clinical practice. With the gradual change in the disease spectrum, genetic factors have received increasing attention. Limited studies have shown an association between FUO and chromosomal abnormalities. In this study, we investigated the clinical and genetic characteristics of patients with FUO presenting with chromosomal abnormalities in a Chinese pediatric cohort. Results Chromosomal abnormalities were detected in 5.5% (8/145) of the patients with FUO. Six patients with inflammatory fever presented with pharyngitis/amygdalitis (4/6), oral aphthous ulcer (2/6), digestive symptoms (3/6), developmental delay (4/6) and elevated C-reactive protein levels (6/6) during fever. These patients were often considered to have systemic inflammatory diseases, such as Behcet’s disease or systemic juvenile idiopathic arthritis. Trisomy 8, 7q11.23 dup, 3p26.3-p26.1 del/17q12 dup, 22q11.21 del, and 6q23.3-q24.1 del were identified in patients with inflammatory fever. The TNFAIP3 gene was included in the 6q23.3-q24.1 deletion fragment. Two patients with central fever were characterized by facial anomalies, developmental delay, seizures and no response to antipyretic drugs and were identified as carrying the de novo 18q22.3-q23 del. By performing a literature review, an additional 19 patients who had FUO and chromosomal abnormalities were identified. Trisomy 8, 6q23.2-q24.3 del and 18q22.3-q23 del were reported to present as fever, similar to the findings of our study. Conclusions We emphasized the important role of detecting chromosomal abnormalities in patients with FUO, especially in patients with systemic inflammatory manifestations or developmental delay. Identifying chromosomal abnormalities may change the diagnosis and management of patients with FUO.

Abstract A specific bone capillary subtype, namely type H vessels, with high expression of CD31 and endomucin, was shown to couple angiogenesis and osteogenesis recently. The number of type H vessels in bone tissue declines with age, and the underlying mechanism for this reduction is unclear. Here, we report that microRNA-188-3p (miR-188-3p) involves this process. miRNA-188-3p expression is upregulated in skeletal endothelium and negatively regulates the formation of type H vessels during ageing. Mice with depletion of miR-188 showed an alleviated age-related decline in type H vessels. In contrast, endothelial-specific overexpression of miR-188-3p reduced the number of type H vessels, leading to decreased bone mass and delayed bone regeneration. Mechanistically, we found that miR-188 inhibits type H vessel formation by directly targeting integrin β3 in endothelial cells. Our findings indicate that miR-188-3p is a key regulator of type H vessel formation and may be a potential therapeutic target for preventing bone loss and accelerating bone regeneration.

The surface relaxivity for tight cores is commonly determined by the methods of average pore radius (ARS) or surface-to-volume ratio (SVR). The ARS method is time-consuming, and permanent damage to core samples will occur due to the injection of mercury. In this study, a non-destructive method is proposed, instead of the ARS method, to calculate the surface relaxivity of tight core samples based on T2 cut-off value. Firstly, surface relaxivity is calculated using the new method (pseudo T2 cut-off, PTC). Secondly, the calculated surface relaxivity of ARS and SVR methods are compared. Thirdly, the T2 spectrum is converted into pore diameter distribution by choosing appropriate surface relaxivity. Finally, residual oil distribution can be obtained. The ultimate surface relaxivity values for tight sandstone core samples are 5.85, 2.98, 4.66, and 2.17 μm/s. Moreover, we obtained the pore diameter distribution in mesopores and macropores by jointly using these three methods. Residual oil is mainly distributed in micropores and mesopores. The new method proposed in this study is nondestructive and is helpful to quickly and efficiently determine the surface relaxivity of tight cores.

In order to investigate the flavour characteristics of aromatic, glutinous, and nonaromatic rice, gas chromatography–ion mobility spectrometry (GC-IMS) was used to analyse the differences in volatile organic compounds (VOCs) amongst different rice varieties. The results showed that 103 signal peaks were detected in these rice varieties, and 91 volatile flavour substances were identified. Amongst them, 28 aldehydes (28.89~31.17%), 24 alcohols (34.85~40.52%), 14 ketones (12.26~14.74%), 12 esters (2.30~4.15%), 5 acids (7.80~10.85%), 3 furans (0.30~0.68%), 3 terpenes (0.34~0.64%), and 2 species of ethers (0.80~1.78%) were detected. SIMCA14.1 was used to perform principal component analysis (PCA) and orthogonal partial least squares discriminant analysis, and some potential character markers (VIP > 1) were further screened out of the 91 flavour substances identified based on the variable important projections, including ethanol, 1-hexanol, hexanal, heptanal, nonanal, (E)-2-heptenal, octanal, trans-2-octenal, pentanal, acetone, 6-methyl-5-hepten-2-one, ethyl acetate, propyl acetate, acetic acid, and dimethyl sulphide. Based on the established fingerprint information, combined with principal component analysis and orthogonal partial least squares discriminant analysis, different rice varieties were also effectively classified, and the results of this study provide data references for the improvement in aromatic rice varieties.

IntroductionAfter adulthood, as a person grows older, the secretion of sex hormones in the body gradually decreases, and the risk of periodontitis increases. But the relationship between sex hormones and periodontitis is still controversial.MethodsWe investigated the association between sex hormones and periodontitis among Americans over 30 years old. 4,877 participants containing 3,222 males and 1,655 postmenopausal females who had had periodontal examination and detailed available sex hormone levels, were included in our analysis from the 2009-2014 National Health and Nutrition Examination Surveys cycles. We applied multivariate linear regression models to estimate the connection between sex hormones and periodontitis after converting sex hormones into categorical variables through tertile. Additionally, to ensure the stability of the analysis results, we carried out a trend test, subgroup analysis, and interaction test. ResultsAfter fully adjusting the covariates, estradiol levels were not associated with periodontitis in both males and females with a P for trend = 0.064 and 0.064, respectively. For males, we found that sex hormone-binding globulin was positively associated with periodontitis (tertile3 vs tertile1: OR=1.63, 95% CI=1.17-2.28, p = 0.004, P for trend = 0.005). Congruously, free testosterone (tertile3 vs tertile1: OR=0.60, 95% CI=0.43-0.84, p = 0.003), bioavailable testosterone (tertile3 vs tertile1: OR=0.51, 95% CI=0.36-0.71, p < 0.001), and free androgen index (tertile3 vs tertile1: OR=0.53, 95% CI=0.37-0.75, p < 0.001) was found to be negatively associated with periodontitis. Moreover, subgroup analysis of age found a closer relationship between sex hormones and periodontitis in those younger than 50 years.ConclusionOur research suggested that males with lower bioavailable testosterone levels affected by sex hormone-binding globulin were at a higher risk of periodontitis. Meanwhile, estradiol levels were not associated with periodontitis in postmenopausal women.

BackgroundSex differences may be presented in the clinical features or symptoms of schizophrenia patients but also affect the occurrence of hospital-acquired pneumonia (HAP). Modified electroconvulsive therapy (mECT) is a common treatment method for schizophrenia, used in combination with antipsychotics. This retrospective research explores the sex difference in HAP affecting patients with schizophrenia who have received mECT treatment during hospitalization.MethodsWe included schizophrenia inpatients treated with mECT and antipsychotics between January 2015 and April 2022. Blood-related and demographic data collected on admission were analyzed. Influencing factors of HAP in male and female groups were assessed separately.ResultsA total of 951 schizophrenia patients treated with mECT were enrolled in the study, including 375 males and 576 females, of which 62 patients experienced HAP during hospitalization. The risk period of HAP in these patients was found to be the first day after each mECT treatment and the first three sessions of mECT treatment. Statistically significant differences in the incidence of HAP were identified in male vs. female groups, with an incidence in men about 2.3 times higher than that in women (P < 0.001). Lower total cholesterol (Z = −2.147, P = 0.032) and the use of anti-parkinsonian drugs (χ2 = 17.973, P < 0.001) were found to be independent risk factors of HAP in male patients, while lower lymphocyte count (Z = −2.408, P = 0.016), hypertension (χ2 = 9.096, P = 0.003), and use of sedative-hypnotic drugs (χ2 = 13.636, P < 0.001) were identified in female patients.ConclusionInfluencing factors of HAP in schizophrenia patients treated with mECT have gender differences. The first day after each mECT treatment and the first three sessions of mECT treatment were identified to have the greatest risk for HAP development. Therefore, it would be imperative to monitor clinical management and medications during this period according to these gender differences.

BackgroundHospital-acquired pneumonia (HAP) has a significant and detrimental impact on schizophrenia patients. Non-antipsychotic medicines and modified electroconvulsive therapy (MECT) are frequently used in conjunction with antipsychotics to treat schizophrenia. Whether non-antipsychotic medicines or MECT are risk factors for HAP in schizophrenia treated with antipsychotics is still unknown.MethodsPatients with schizophrenia who were admitted to the Fourth People's Hospital of Chengdu between January 2015 and April 2022 were included in this retrospective cohort study. Individuals with HAP were 1:1 matched to individuals without HAP (non-HAP) using propensity score matching (PSM). The risk factors for HAP were analyzed by comparing the two groups.ResultsA total of 7,085 schizophrenia patients were included in this study, with a mean age of 39.77 ± 14.45 years. 193 patients developed HAP on an average of 22.26 ± 21.68 days after admission with an incidence of 2.73%. After 1:1 PSM, 192 patients from each group (HAP and non-HAP) were included. The HAP group had significantly more patients with MECT and taking benzodiazepines, antidepressants, mood stabilizers, and anti-parkinsonians both before and after PSM by Bonferroni correction (P < 0.001). Multivariate logistic regression analysis showed that, combined with antipsychotics, non-antipsychotic medicines including benzodiazepines (OR = 3.13, 95%CI = 1.95-5.03, P < 0.001), mood stabilizers (OR =3.33, 95%CI =1.79–6.20, P < 0.001) and MECT (OR =2.58, 95%CI =1.49–4.46, P = 0.001) were associated with a significantly increased incidence of HAP.ConclusionThe incidence of HAP in schizophrenia patients in our cohort was 2.73%. MECT and non-antipsychotic medicines, including benzodiazepines and mood stabilizers were risk factors for HAP in schizophrenia patients treated with antipsychotics.

Urban rail traffic is an important part of modern transportation infrastructure.As a new generation of mobile communication technology, 5G can provide high data rate and low latency wireless transmission, which helps to improve the efficiency and service quality of urban rail traffic system.Due to the complexity of urban rail traffic scenarios, accurate communication scenario classification, channel characterization and channel models are required to provide theoretical support for the design of urban rail traffic 5G communication systems.The classification of 5G urban rail traffic radio propagation scenarios to support channel measurements and modeling was proposed.Current status of urban rail traffic channel measurements and modeling was shown, and the current challenges were analyzed.The applications of artificial intelligence in channel feature extraction and channel modeling were discussed, and the 5G urban rail traffic channels by considering reconfigurable intelligent surface and unmanned aerial vehicle were analyzed.Finally, the research on 5G urban rail traffic channel modeling at millimeter wave frequency band was described.

Abstract Background Cryptococcosis is a major opportunistic invasive mycosis in immunocompromised patients, but it is also increasingly seen in immunocompetent patients. In the early stages of cryptococcosis, limitations of the detection method may hinder the diagnosis. A molecular diagnostic technique based on nucleic acid sequence-based amplification (NASBA) method was developed to fulfil the need for efficient diagnosis of cryptococcosis. Methods We compared the diagnostic performance of NASBA, PCR and cryptococcal antigen (CrAg) test (colloidal gold method) in clinical samples from 25 cryptococcosis patients (including 8 cryptococcal meningoencephalitis and 17 pulmonary cryptococcosis) who were categorized as proven cases (n = 10) and probable cases (n = 15) according to the revised EORTC/MSG definitions. 10 patients with non-Cryptococcus infection and 30 healthy individuals were categorized as control group. Results The lowest detection limit of NASBA was 10 CFU/mL, and RNA of non-target bacteria or fungi was not amplified. The sensitivity of NASBA, PCR and colloidal gold method was 92.00% (95% CI 72.50–98.60%), 64.00% (95% CI 42.62–81.29%), 100.00% (95% CI 83.42–100.00%), and the specificity was 95.00% (95% CI 81.79–99.13%), 80.00% (95% CI 63.86–90.39%) and 82.50% (95% CI 66.64–92.11%) respectively. The highest specificity (97.50%), accuracy (95.38%) and k value (0.90) were achieved when both NASBA and colloidal gold results were positive. Conclusions NASBA is a new alternative detection method for cryptococcosis which is both accurate and rapid without expensive equipment and specialised personnel. It may be used as a tool for confirming current infection as well as monitoring the effectiveness of antifungal treatment. The use of NASBA to detect Cryptococcus RNA in blood samples is of great significance for the diagnosis of pulmonary cryptococcosis. The combination of NASBA and colloidal gold can improve the diagnostic accuracy of cryptococcosis.

The early and accurate monitoring of crop yield is important for field management, storage needs, and cash flow budgeting. Traditional cotton yield measurement methods are time-consuming, labor-intensive, and subjective. Chlorophyll fluorescence signals originate from within the plant and have the advantages of being fast and non-destructive, and the relevant parameters can reflect the intrinsic physiological characteristics of the plant. Therefore, in this study, the top four functional leaves of cotton plants at the beginning of the flocculation stage were used to investigate the pattern of the response of chlorophyll fluorescence parameters (e.g., F0, Fm, Fv/F0, and Fv/Fm) to nitrogen, and the cumulative fluorescence parameters were constructed by combining them with the leaf area index to clarify the correlation between chlorophyll fluorescence parameters and cotton yield. Support vector machine regression (SVM), an artificial neural network (BP), and an XGBoost regression tree were used to establish a cotton yield prediction model. Chlorophyll fluorescence parameters showed the same performance as photosynthetic parameters, which decreased as leaf position decreased. It showed a trend of increasing and then decreasing with increasing N application level, reaching the maximum value at 240 kg·hm-2 of N application. The correlation between fluorescence parameters and yield in the first, second, and third leaves was significantly higher than that in the fourth leaf, and the correlation between fluorescence accumulation and yield in each leaf was significantly higher than that of the fluorescence parameters, with the best performance of Fv/Fm accumulation found in the second leaf. The correlation between Fv/Fm accumulation and yield in the top three leaves combined was significantly higher than that in the top four leaves. The correlation coefficient between Fv/Fm accumulation and yield was the highest, indicating the feasibility of applying chlorophyll fluorescence to estimate yield. Based on the machine learning algorithm used to construct a cotton yield prediction model, the estimation models of Fv/F0 accumulation and yield of the top two leaves combined as well as top three leaves combined were superior. The estimation model coefficient of determination of the top two leaves combined in the BP algorithm was the highest. In general, the Fv/F0 accumulation of the top two leaves combined could more reliably predict cotton yield, which could provide technical support for cotton growth monitoring and precision management.

Talaromyces marneffei (T. marneffei) is an opportunistic pathogen. Patients with inborn errors of immunity (IEI) have been increasingly diagnosed with T. marneffei in recent years. The disseminated infection of T. marneffei can be life-threatening without timely and effective antifungal therapy. Rapid and accurate pathogenic microbiological diagnosis is particularly critical for these patients. A total of 505 patients with IEI were admitted to our hospital between January 2019 and June 2022, among whom T. marneffei was detected in 6 patients by metagenomic next-generation sequencing (mNGS), and their clinical and immunological characteristics were summarized. We performed a systematic literature review on T. marneffei infections with published immunodeficiency-related gene mutations. All patients in our cohort were confirmed to have genetic mutations in IL12RB1, IFNGR1, STAT1, STAT3, and CD40LG. T. marneffei was detected in both the blood and lymph nodes of P1 with IL12RB1 mutations, and the clinical manifestations were serious and included recurrent fever, weight loss, severe anemia, splenomegaly and lymphadenopathy, all requiring long-term antifungal therapy. These six patients received antifungal treatment, which relieved symptoms and improved imaging findings. Five patients survived, while one patient died of sepsis after hematopoietic stem cell transplantation. The application of mNGS methods for pathogen detection in IEI patients and comparison with traditional diagnosis methods were investigated. Traditional diagnostic methods and mNGS tests were performed simultaneously in 232 patients with IEI. Compared to the traditional methods, the sensitivity and specificity of mNGS in diagnosing T. marneffei infection were 100% and 98.7%, respectively. The reporting time for T. marneffei detection was approximately 26 hours by mNGS, 3-14 days by culture, and 6-11 days by histopathology. T. marneffei infection was first reported in IEI patients with IL12RB1 gene mutation, which expanded the IEI lineage susceptible to T. marneffei. For IEI patients with T. marneffei infection, we highlight the application of mNGS in pathogenic detection. mNGS is recommended as a front-line diagnostic test for rapidly identifying pathogens in complex and severe infections.

Under the background of drastic global climate change, the evolution law of groundwater resources in the northeastern margin of the Tibetan Plateau presents new characteristics, and the groundwater is gradually becoming more complicated, diversified and disordered. In this study, cross-correlation analysis, wavelet analysis and cross-wavelet transform were used to explore the response mechanism and time delay effect of groundwater, exploitation amount, rainfall and surface runoff in the northeastern margin of the Tibetan Plateau. The results show that the groundwater depth increased with the increase in the exploitation amount and decreased with the increase in the rainfall-to-exploitation ration and the surface runoff-to-exploitation ratio from 1980 to 2020. On the annual scale, groundwater, rainfall and surface runoff had a strong cohesiveness period of 12a. On the monthly scale, groundwater lagged behind rainfall and surface runoff for 3 months and 2 months, respectively. The above conclusions provide a scientific theoretical basis for deepening the characteristics of groundwater endowment, the evolution law of water cycle elements and the theory of the hydrological cycle in the northeastern margin of the Tibetan Plateau.

FOXP2, cognitive deficits, and schizophrenia are associated with neurodegenerative pathophyisiology. Mounting evidence suggests that body mass index (BMI) and FOXP2 may contribute to cognitive deficits in schizophrenia. However, the sex difference in the contribution of FOXP2 and BMI, as well as their potential interaction with cognitive deficits in schizophrenia, have not been investigated. A total of 867 schizophrenia patients and 402 controls were recruited. Cognitive function was assessed using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). The polymorphism rs10447760 of the FOXP2 gene was genotyped. Male schizophrenia patients had superior language performance compared to female patients (F = 17.83; pBonferroni < 0.0001). BMI was positively associated with language scores in male patients with schizophrenia (ß = 0.60, t = 3.30, p = 0.001), as well as in patients with schizophrenia who carried the FOXP2 rs10447760 CC genotype (ß = 0.53, t = 3.16, p = 0.002). Interestingly, this association was only found in male patients with schizophrenia who also carried the FOXP2 rs10447760 CC genotype (ß = 0.63, t = 3.44, p = 0.001). Our study reveals a sex difference in the language deficits of schizophrenia patients and shows sexual dimorphism in the contribution of FOXP2, BMI, and their interaction to cognitive deficits in patients with schizophrenia.

Background Long noncoding RNA Gm31629 can regulate hypothalamic neural stem cells (htNSCs) senescence and the aging process. However, the effect of Gm31629 on the senescence of bone marrow mesenchymal stem cells (BMSCs) and bone regeneration is unclear. In the present study, we investigated the effects of Gm31629 on the senescence of BMSCs and bone regeneration. Methods Gm31629 knockout (Gm31629-KO) and wild-type (WT) mice were used to establish a bone regeneration model. The Brdu labelling, CCK8 assay, wound healing assay, β-gal staining and osteogenic differentiation assay were used to assess the effects of Gm31629 on the functions of BMSCs. Micro-computed tomography (CT), histochemical and immunohistochemical staining were used to evaluate the ability of bone regeneration. The mimic of Gm31629, theaflavin 3-gallate, was used to investigate its role on the senescence of BMSCs and bone regeneration. Results The expression of Gm31629 reduced in BMSCs of middle-aged mice was compared with that of young mice. The deletion of Gm31629 was sufficient to drive the senescence of BMSCs, resulting in impaired bone regeneration in mice. Mechanistically, Gm31629 could interact with Y-box protein 1(YB-1) and delay its degradation, decreasing the transcription of p16INK4A of BMSCs. We also found that theaflavin 3-gallate could alleviate the senescence of BMSCs and promote bone regeneration in middle-aged mice. Conclusion These results indicated that Gm31629 played an important role on BMSCs senescence and bone regeneration and provided a therapeutic target to promote bone regeneration.

Abstract Background Irradiation has emerged as a valid tool for nasopharyngeal carcinoma (NPC) in situ treatment; however, NPC derived from tissues treated with irradiation is a main cause cancer-related death. The purpose of this study is to uncover the underlying mechanism regarding tumor growth after irradiation and provided potential therapeutic strategy. Methods Fibroblasts were extracted from fresh NPC tissue and normal nasopharyngeal mucosa. Immunohistochemistry was conducted to measure the expression of α-SMA and FAP. Cytokines were detected by protein array chip and identified by real-time PCR. CCK-8 assay was used to detect cell proliferation. Radiation-resistant (IRR) 5-8F cell line was established and colony assay was performed to evaluate tumor cell growth after irradiation. Signaling pathways were acquired via gene set enrichment analysis (GSEA). Comet assay and γ-H2AX foci assay were used to measure DNA damage level. Protein expression was detected by western blot assay. In vivo experiment was performed subcutaneously. Results We found that radiation-resistant NPC tissues were constantly infiltrated with a greater number of cancer-associated fibroblasts (CAFs) compared to radiosensitive NPC tissues. Further research revealed that CAFs induced the formation of radioresistance and promoted NPC cell survival following irradiation via the IL-8/NF-κB pathway to reduce irradiation-induced DNA damage. Treatment with Tranilast, a CAF inhibitor, restricted the survival of CAF-induced NPC cells and attenuated the of radioresistance properties. Conclusions Together, these data demonstrate that CAFs can promote the survival of irradiated NPC cells via the NF-κB pathway and induce radioresistance that can be interrupted by Tranilast, suggesting the potential value of Tranilast in sensitizing NPC cells to irradiation.

Abstract Background We aimed to report the clinical characteristics, immunological features, and treatment of one patient with a de novo STAT3 gain-of-function mutation identified by next generation sequencing. We investigated the efficacy of tocilizumab therapy in immune dysregulation diseases caused by STAT3 mutation. Results The patient was a 16-year-old girl. She presented with recurrent respiratory infections and chronic diarrhea after birth. She had life-threatening autoimmune pancytopenia at 14 years old. After receiving glucocorticoid therapy, she developed diabetes. However, her pancytopenia relapsed when the glucocorticoid was tapered. Next-generation sequencing showed a de novo heterozygous mutation in the STAT3 gene, c.1261G > A (p. G421R), which was previously described as a gain-of-function mutation. After tocilizumab therapy, her pancytopenia fully resolved, and insulin and glucocorticoid therapies were gradually discontinued within 12 months. She had lymphopenia and an inverted CD4/CD8 ratio before therapy. Lymphocyte subpopulation analysis indicated an expansion of effector memory CD4+, effector memory CD8+ and central memory CD4+ T cells. The proportions of memory B cells and naive CD4+ T cells were decreased, and the proportion of naïve B cells was increased. None of the abnormal lymphocytic changes improved significantly. STAT3 GOF mutations were identified by next gene sequencing in those with early-onset multi-organ autoimmunity. Including our patient, 13 patients with STAT3 GOF mutations received targeted treatment. Twelve of them were treated with tocilizumab alone or combination tocilizumab with JAK inhibitor, and ten patients improved. Conclusions Gene sequencing should be performed for patients with early-onset refractory or multiorgan immune dysregulation diseases. Targeted drugs can effectively improve the clinical problems associated with STAT3 gain-of-function mutations, while nontargeted immunosuppressive therapy is usually insufficient.

Abstract Routine prophylaxis for venous thromboembolism (VTE) in Asian IBD patients has been controversial. We aimed to estimate the risk of VTE of Asian patients at different phases of IBD by incorporating patient-specific risk factors. In this cohort study, we analyzed the National Health Insurance claims data between 2012 and 2016 for the entire Korean population. We calculated incidence rates and hazard ratios for VTE. The overall VTE risk was higher in patients with IBD [adjusted hazard ratio (aHR), 2.06; 95% confidence interval (CI), 1.66–2.55], than in controls. When we compare the risk of VTE by different disease phases, the risk of VTE was the highest during post-operation period after IBD-related bowel surgery (aHR, 39.7; 95% CI 9.87–159.3), followed by during hospitalized periods with flare (aHR, 27.2; 95% CI 14.9–49.65) and during hospitalized periods with non-flare (aHR, 16.23; 95% CI 10.71–24.58). The incidence rate (per 1000 person-years) was 15.26 during hospitalized periods with a flare and 9.83 during hospitalized periods with non-flare. According to age groups, the incidence rate (per 1000 person-years) during hospitalized periods with flare was 14.53 in young patients (20–39 years) and 34.58 in older patients (60–80 years). During hospitalized periods with non-flare, the incidence rate was 3.55 in young patients and 23.61 in older patients. The prophylaxis of VTE for Asian patients with IBD should be recommended in older patients admitted to hospital and be considered in young patients who are hospitalized with a flare.

To investigate the effects of dietary betaine supplementation on the growth performance, digestive function, intestinal integrity, immunity, and antioxidant capacity of yellow-feathered broilers, a total of 400 one-day-old female yellow-feathered broilers were randomly allocated into 5 dietary treatments with 8 replicates of 10 chicks each, and fed a basal diet supplemented with 0 (control group), 125, 250, 500 and 1000 mg/kg betaine for 74 days, respectively. During the 1–37 days and 1–74 days, betaine linearly increased (p

Mucosal healing is a key treatment goal for inflammatory bowel disease, and adequate epithelial regeneration is required for an intact gut epithelium. However, the underlying mechanism for mucosal healing is unclear. Long noncoding RNAs (lncRNAs) have been reported to be involved in the development of inflammatory bowel disease. Here, we report that a lncRNA named Gm31629 decreased in intestinal epithelial cells in response to inflammatory stimulation. Gm31629 deficiency led to exacerbated intestinal inflammation and delayed epithelial regeneration in dextran sulfate sodium–induced (DSS-induced) colitis model. Mechanistically, Gm31629 promoted E2F pathways and cell proliferation by stabilizing Y-box protein 1 (YB-1), thus facilitating epithelial regeneration. Genetic overexpression of Gm31629 protected against DSS-induced colitis in vivo. Theaflavin 3-gallate, a natural compound mimicking Gm31629, alleviated DSS-induced epithelial inflammation and mucosal damage. These results demonstrate an essential role of lncRNA Gm31629 in linking intestinal inflammation and epithelial cell proliferation, providing a potential therapeutic approach to inflammatory bowel disease.

Summary: Background: Ultrasound is a critical non-invasive test for preoperative diagnosis of ovarian cancer. Deep learning is making advances in image-recognition tasks; therefore, we aimed to develop a deep convolutional neural network (DCNN) model that automates evaluation of ultrasound images and to facilitate a more accurate diagnosis of ovarian cancer than existing methods. Methods: In this retrospective, multicentre, diagnostic study, we collected pelvic ultrasound images from ten hospitals across China between September 2003, and May 2019. We included consecutive adult patients (aged ≥18 years) with adnexal lesions in ultrasonography and healthy controls and excluded duplicated cases and patients without adnexa or pathological diagnosis. For DCNN model development, patients were assigned to the training dataset (34 488 images of 3755 patients with ovarian cancer, 541 442 images of 101 777 controls). For model validation, patients were assigned to the internal validation dataset (3031 images of 266 patients with ovarian cancer, 5385 images of 602 with benign adnexal lesions), external validation datasets 1 (486 images of 67 with ovarian cancer, 933 images of 268 with benign adnexal lesions), and 2 (1253 images of 166 with ovarian cancer, 5257 images of 723 benign adnexal lesions). Using these datasets, we assessed the diagnostic value of DCNN, compared DCNN with 35 radiologists, and explored whether DCNN could augment the diagnostic accuracy of six radiologists. Pathological diagnosis was the reference standard. Findings: For DCNN to detect ovarian cancer, AUC was 0·911 (95% CI 0·886–0·936) in the internal dataset, 0·870 (95% CI 0·822–0·918) in external validation dataset 1, and 0·831 (95% CI 0·793–0·869) in external validation dataset 2. The DCNN model was more accurate than radiologists at detecting ovarian cancer in the internal dataset (88·8% vs 85·7%) and external validation dataset 1 (86·9% vs 81·1%). Accuracy and sensitivity of diagnosis increased more after DCNN-assisted diagnosis than assessment by radiologists alone (87·6% [85·0–90·2] vs 78·3% [72·1–84·5], p

Radiation enteritis is one of the main adverse effects of radiotherapy, presenting with a poorly understood etiology and limited options for therapy. Intestinal inflammation and ischemia are the core mechanisms of radiation enteritis. Suppressor of cytokine signaling 3 (SOCS3) is an endogenous “inflammation brake.” We hypothesized that paeoniflorin, a pinane monoterpene bitter glycoside, could increase SOCS3 expression to reduce inflammation and ischemia and improve enteritis in mice. Laser Doppler flowmetry was used to detect changes in intestinal blood flow. RAW264.7 and human umbilical vein endothelial cells were used to investigate the mechanism of action of paeoniflorin. It was observed that radiation caused high mortality, intestinal inflammatory responses, and low blood flow in mice. Paeoniflorin effectively alleviated intestinal atrophy, prevented thrombosis, improved radiation enteritis, and reduced mortality in mice undergoing radiotherapy. In addition, paeoniflorin increased the release of growth arrest-specific gene 6 (Gas6) and phosphorylation of the Axl receptor, subsequently inducing the expression of SOCS3 and inhibiting the expression of p-apoptosis signal-regulating kinase 1 and tissue factor in vivo and in vitro. Based on our findings, we suggest that paeoniflorin is potentially effective in alleviating radiation enteritis via the activation of the Gas6/Axl/SOCS3 axis and subsequent reduction in intestinal inflammation and ischemia.

Abstract Background Spectrin repeat containing nuclear envelope family member 3 (SYNE3) encodes an essential component of the linker of the cytoskeleton and nucleoskeleton (LINC) complex, namely nesprin-3. In a tumor, invasiveness and metastasis rely on the integrity of the LINC complex, while the role of SYNE3/nesprin-3 in cancer is rarely studied. Methods Here, we explored the expression pattern, prognostic value, and related mechanisms of SYNE3 through both experimental and bioinformatic methods. We first detected SYNE3 in BALB/c mice, normal human tissues, and the paired tumor tissues, then used bioinformatics databases to verify our results. We further analyzed the prognostic value of SYNE3. Next, we predicted miRNA targeting SYNE3 and built a competing endogenous RNA (ceRNA) network and a transcriptional network by analyzing data from the cancer genome atlas (TCGA) database. Interacting genes of SYNE3 were predicted, and we further performed GO and KEGG enrichment analysis on these genes. Besides, the relationship between SYNE3 and immune infiltration was also investigated. Results SYNE3 exhibited various expressions in different tissues, mainly located on nuclear and in cytoplasm sometimes. SYNE3 expression level had prognostic value in tumors, possibly by stabilizing nucleus, promoting tumor cells apoptosis, and altering tumor microenvironment. Additionally, we constructed a RP11-2B6.2-miR-149-5p-/RP11-67L2.2-miR-330-3p-SYNE3 ceRNA network and a SATB1-miR-149-5p-SYNE3 transcriptional network in lung adenocarcinoma to support the tumor-suppressing role of SYNE3. Conclusions Our study explored novel anti-tumor functions and mechanisms of SYNE3, which might be useful for future cancer therapy.