Search

Abstract Whole-genome duplication (WGD) in plants triggers profound morphological and physiological changes, with DNA modification being a key epigenetic factor that helps neo-polyploids overcome challenges and gain adaptive advantages. Tetraploids were previously mined from diploid citrus seedlings, showing enhanced environmental adaptability and potential as rootstocks. These tetraploids exhibited increased leaf and cell wall thickness compared to their diploid counterparts. To explore the impact of WGD, transcriptomic and whole-genome bisulfite sequencing (WGBS) were conducted on two pairs of citrus tetraploids and their diploid controls, revealing significant molecular changes. Notably, tetraploid citrus displayed lower CG methylation levels in gene and transposable element (TE) bodies relative to diploids. Differentially methylated genes (DMGs) between tetraploids and diploids were primarily associated with immune stress, organ development, metabolic pathways, and secondary metabolism. In Trifoliate orange (Poncirus trifoliata L. Raf.) and Ziyang Xiangcheng (Citrus junos Sieb. ex Tanaka), only 150 and 58 differentially expressed genes (DEGs) were identified, respectively, with enrichment in critical cellular processes such as cell wall synthesis, plastid development, and pathways modulating chloroplasts and plasma membranes. A total of 70 genes showed both differential methylation and expression, including ACN1, Nac036, and ASMT1, which are involved in stomatal development, leaf morphology, and melatonin synthesis, respectively, offering insight into the regulatory mechanisms of phenotype alterations after polyploidization. These findings reveal the epigenetic modifications in polyploid citrus and highlight the role of polyploidization-induced methylation in driving phenotypic changes.

Abstract The fundamental principle of satellite/node-based positioning involves triangulating the receiver’s coordinates through the intersection of spatial distances. Advancements in hybrid wireless networks have yielded high-precision positioning at decimeter-level (wavelength-level), approaching the resolution limits in free space. Here we present a 3D super-resolution positioning paradigm in free space by utilizing a kind of topologically structured pulses, toroidal electromagnetic pulses. We demonstrate that the space-time nonseparability and skyrmion topology inherent in toroidal pulses can be harnessed to achieve freespace microwave 3D positioning with super-resolution accuracy, reaching the centimeter level, using a single emitting antenna. This work opens up avenues for exploring the potential applications of topological electromagnetic pulses including but not limited to positioning, imaging and sensing technologies.

Abstract Neuroendocrine neoplasms (NENs) are highly heterogeneous and potentially malignant tumors arising from secretory cells of the neuroendocrine system. Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) are the most common subtype of NENs. Historically, GEP-NENs have been regarded as infrequent and slow-growing malignancies; however, recent data have demonstrated that the worldwide prevalence and incidence of GEP-NENs have increased exponentially over the last three decades. In addition, an increasing number of studies have proven that GEP-NENs result in a limited life expectancy. These findings suggested that the natural biology of GEP-NENs is more aggressive than commonly assumed. Therefore, there is an urgent need for advanced researches focusing on the diagnosis and management of patients with GEP-NENs. In this review, we have summarized the limitations and recent advancements in our comprehension of the epidemiology, clinical presentations, pathology, molecular biology, diagnosis, and treatment of GEP-NETs to identify factors contributing to delays in diagnosis and timely treatment of these patients.

Abstract Background Patient involvement is crucial to the success of kidney transplants. This study aimed to investigate the knowledge, attitude, and practice (KAP) toward postoperative self-management among kidney transplant recipients. Methods A web-based cross-sectional study was conducted in Ruijin Hospital (Shanghai, China) between March 24, 2023, and April 15, 2023 in kidney transplant recipients. A questionnaire was designed to collect data about the characteristics of the participants and their KAP toward postoperative self-management. KAP scores were calculated based on participants' responses, using predefined scoring criteria tailored to evaluate each dimension of KAP effectively. Results A total of 483 valid questionnaires were collected, including 189 (39.13%) participants aged between 46 and 60 years. The mean score of knowledge, attitude and practice were 23.44 ± 4.87 (possible range: 0–28), 43.59 ± 2.65 (possible range: 10–50), 52.52 ± 4.64 (possible range: 0–58), respectively. The multivariate analysis showed knowledge scores (OR = 1.15, 95% CI = 1.10–1.20, p

Abstract Cancer treatment continues to shift from utilizing traditional therapies to targeted ones, such as protein kinase inhibitors and immunotherapy. Mobilizing dendritic cells (DC) and other myeloid cells with antigen presenting and cancer cell killing capacities is an attractive but not fully exploited approach. Here, we show that PIKFYVE is a shared gene target of clinically relevant protein kinase inhibitors and high expression of this gene in DCs is associated with poor patient response to immune checkpoint blockade (ICB) therapy. Genetic and pharmacological studies demonstrate that PIKfyve ablation enhances the function of CD11c+ cells (predominantly dendritic cells) via selectively altering the non-canonical NF-κB pathway. Both loss of Pikfyve in CD11c+ cells and treatment with apilimod, a potent and specific PIKfyve inhibitor, restrained tumor growth, enhanced DC-dependent T cell immunity, and potentiated ICB efficacy in tumor-bearing mouse models. Furthermore, the combination of a vaccine adjuvant and apilimod reduced tumor progression in vivo. Thus, PIKfyve negatively regulates the function of CD11c+ cells, and PIKfyve inhibition has promise for cancer immunotherapy and vaccine treatment strategies.

Abstract Background This study aimed to examine the reporting quality of existing economic evaluations for negotiated glucose-lowering drugs (GLDs) included in China National Reimbursement Drug List (NRDL) using the Consolidated Health Economic Evaluation Reporting Standards 2013 (CHEERS 2013). Methods We performed a systematic literature research through 7 databases to identify published economic evaluations for GLDs included in the China NRDL up to March 2021. Reporting quality of identified studies was assessed by two independent reviewers based on the CHEERS checklist. The Kruskal–Wallis test and Mann–Whitney U test were performed to examine the association between reporting quality and characteristics of the identified studies. Results We have identified 24 studies, which evaluated six GLDs types. The average score rate of the included studies was 77.41% (SD:13.23%, Range 47.62%-91.67%). Among all the required reporting items, characterizing heterogeneity (score rate = 4.17%) was the least satisfied item. Among six parts of CHEERS, results part scored least at 0.55 (score rate = 54.79%) because of the incompleteness of characterizing uncertainty. Results from the Kruskal–Wallis test and Mann–Whitney U test showed that model choice, journal type, type of economic evaluations, and study perspective were associated with the reporting quality of the studies. Conclusions There remains room to improve the reporting quality of economic evaluations for GLDs in NRDL. Checklists such as CHEERS should be widely used to improve the reporting quality of economic researches in China.

Abstract Background Chondrosarcoma (CHS), a bone malignancy, poses a significant challenge due to its heterogeneous nature and resistance to conventional treatments. There is a clear need for advanced prognostic instruments that can integrate multiple prognostic factors to deliver personalized survival predictions for individual patients. This study aimed to develop a novel prediction tool based on recursive partitioning analysis (RPA) to improve the estimation of overall survival for patients with CHS. Methods Data from the Surveillance, Epidemiology, and End Results (SEER) database were analyzed, including demographic, clinical, and treatment details of patients diagnosed between 2000 and 2018. Using C5.0 algorithm, decision trees were created to predict survival probabilities at 12, 24, 60, and 120 months. The performance of the models was assessed through confusion scatter plot, accuracy rate, receiver operator characteristic (ROC) curve, and area under ROC curve (AUC). Results The study identified tumor histology, surgery, age, visceral (brain/liver/lung) metastasis, chemotherapy, tumor grade, and sex as critical predictors. Decision trees revealed distinct patterns for survival prediction at each time point. The models showed high accuracy (82.40%–89.09% in training group, and 82.16%–88.74% in test group) and discriminatory power (AUC: 0.806–0.894 in training group, and 0.808–0.882 in test group) in both training and testing datasets. An interactive web‐based shiny APP (URL: https://yangxg1209.shinyapps.io/chondrosarcoma_survival_prediction/) was developed, simplifying the survival prediction process for clinicians. Conclusions This study successfully employed RPA to develop a user‐friendly tool for personalized survival predictions in CHS. The decision tree models demonstrated robust predictive capabilities, with the interactive application facilitating clinical decision‐making. Future prospective studies are recommended to validate these findings and further refine the predictive model.

Abstract Background Gasdermin D (GSDMD)-mediated pyroptotic cell death is implicated in the pathogenesis of cognitive deficits in sepsis-associated encephalopathy (SAE), yet the underlying mechanisms remain largely unclear. Dynamin-related protein 1 (Drp1) facilitates mitochondrial fission and ensures quality control to maintain cellular homeostasis during infection. This study aimed to investigate the potential role of the GSDMD/Drp1 signaling pathway in cognitive impairments in a mouse model of SAE. Methods C57BL/6 male mice were subjected to cecal ligation and puncture (CLP) to establish an animal model of SAE. In the interventional study, mice were treated with the GSDMD inhibitor necrosulfonamide (NSA) or the Drp1 inhibitor mitochondrial division inhibitor-1 (Mdivi-1). Surviving mice underwent behavioral tests, and hippocampal tissues were harvested for histological analysis and biochemical assays at corresponding time points. Haematoxylin-eosin staining and TUNEL assays were used to evaluate neuronal damage. Golgi staining was used to detect synaptic dendritic spine density. Additionally, transmission electron microscopy was performed to assess mitochondrial and synaptic morphology in the hippocampus. Local field potential recordings were conducted to detect network oscillations in the hippocampus. Results CLP induced the activation of GSDMD, an upregulation of Drp1, leading to associated mitochondrial impairment, neuroinflammation, as well as neuronal and synaptic damage. Consequently, these effects resulted in a reduction in neural oscillations in the hippocampus and significant learning and memory deficits in the mice. Notably, treatment with NSA or Mdivi-1 effectively prevented these GSDMD-mediated abnormalities. Conclusions Our data indicate that the GSDMD/Drp1 signaling pathway is involved in cognitive deficits in a mouse model of SAE. Inhibiting GSDMD or Drp1 emerges as a potential therapeutic strategy to alleviate the observed synaptic damages and network oscillations abnormalities in the hippocampus of SAE mice.

Abstract Chloroplast genomes, pivotal for understanding plant evolution, remain unexplored in Rutaceae, a family with key perennial crops like citrus. Leveraging next-generation sequencing data from 509 Rutaceae accessions across 15 species, we conducted a de novo assembly of 343 chloroplast genomes, unveiling a chloroplast variation map highlighting the heterogeneous evolution rates across genome regions. Notably, differences in chloroplast genome size primarily originate from large single-copy and small single-copy regions. Structural variants predominantly occurred in the single-copy region, with two insertions located at the single-copy and inverted repeat region boundary. Phylogenetic analysis, principal component analysis, and population genetic statistics confirmed the cohesive clustering of different Citrus species, reflecting evolutionary dynamics in Citrus diversification. Furthermore, a close chloroplast genetic affinity was revealed among Atalantia (previously regarded as primitive citrus), Clausena, and Murraya. Zanthoxylum formed a distinct group with heightened genetic diversity. Through expanding our analysis to include 34 published chloroplast genomes, we explored chloroplast gene selection, revealing divergent evolutionary trends in photosynthetic pathways. While Photosystem I and Photosystem II exhibited robust negative selection, indicating stability, the Nicotinamide adenine dinucleotide (NADH) dehydrogenase pathway demonstrated rapid evolution, which was indicative of environmental adaptation. Finally, we discussed the effects of gene length and GC content on chloroplast gene evolution. In conclusion, our study reveals the genetic characterization of chloroplast genomes during Rutaceae diversification, providing insights into the evolutionary history of this family.

The patterns of material accumulation in buildings and infrastructure accompanied by rapid urbanization offer an important, yet hitherto largely missing stock perspective for facilitating urban system engineering and informing urban resources, waste, and climate strategies. However, our existing knowledge on the patterns of built environment stocks across and particularly within cities is limited, largely owing to the lack of sufficient high spatial resolution data. This study leveraged multi-source big geodata, machine learning, and bottom-up stock accounting to characterize the built environment stocks of 50 cities in China at 500 m fine-grained levels. The per capita built environment stock of many cities (261 tonnes per capita on average) is close to that in western cities, despite considerable disparities across cities owing to their varying socioeconomic, geomorphology, and urban form characteristics. This is mainly owing to the construction boom and the building and infrastructure-driven economy of China in the past decades. China’s urban expansion tends to be more “vertical” (with high-rise buildings) than “horizontal” (with expanded road networks). It trades skylines for space, and reflects a concentration–dispersion–concentration pathway for spatialized built environment stocks development within cities in China. These results shed light on future urbanization in developing cities, inform spatial planning, and support circular and low-carbon transitions in cities.

Rapid urbanization has led to the emergence of urban–rural fringes, complex transitional zones that challenge traditional urban–rural dichotomies. While these areas play a crucial role in urban development, their precise identification remains a significant challenge. Existing methods often rely on single-dimensional metrics or administrative boundaries, failing to capture the multi-faceted nature of these zones. This study introduces a novel “Scene–Object–Economy” (SOE) framework to address these limitations and enhance the precision of urban–rural fringe identification. Our approach integrates multisource geospatial big data, including remote sensing imagery, nightlight data, buildings, and Points of Interest (POI), leveraging machine learning techniques. The SOE framework constructs feature from three dimensions: scene (image features), object (buildings), and economy (POIs). This multidimensional methodology allows for a more comprehensive and nuanced mapping of urban–rural fringes, overcoming the constraints of traditional methods. The study demonstrates the effectiveness of the SOE framework in accurately delineating urban–rural fringes through multidimensional validation. Our results reveal distinct spatial patterns and characteristics of these transitional zones, providing valuable insights for urban planners and policymakers. Furthermore, the integration of dynamic population data as a separate layer of analysis offers a unique perspective on population distribution patterns within the identified fringes. This research contributes to the field by offering a more robust and objective approach to urban–rural fringe identification, laying the groundwork for improved urban management and sustainable development strategies. The SOE framework presents a promising tool for future studies in urban spatial analysis and planning.

In recent years, numerous studies highlighted the crucial role of the soil–structure interaction (SSI) in the seismic performance of basement structures. However, there remains a limited understanding of how this interaction affects buildings with basement structures under varying site conditions. Based on the three-dimensional (3D) numerical analysis method, the influence of the SSI on the seismic response of high-rise steel frame–core wall (SFCW) structures situated on shallow-box foundations were investigated in this study. To further investigate the effects of the SSI and site conditions, three types of soil profiles—soft, medium, and hard—were considered, along with a fixed-foundation model. The results were compared in terms of the maximum lateral displacement, inter-story drift ratio (IDR), acceleration amplification coefficient, and tensile damage for the SFCW structure under different site conditions, with both fixed-base and shallow-box foundation configurations. The findings highlight that the site conditions significantly affected the seismic performance of the SFCW structure, particularly in the soft soil, which increased the lateral deflection and inter-story drift. Moreover, compared with non-pulse-like ground motion, pulse-like ground motion resulted in a higher acceleration amplification coefficient and greater structural response in the SFCW structure. The RC core wall–basement slab junction was a critical region of stress concentration that exhibited a high sensitivity to the site conditions. Additionally, the maximum IDRs showed a more significant variation at incidence angles between 20 and 30 degrees, with a more pronounced effect at a seismic input intensity of 0.3 g than at 0.2 g.

Basalt fiber-reinforced polymer (BFRP) has high mechanical strengths as a repairing material but exhibits low ductility. This paper investigates the damage process of reinforced concrete beams repaired using BFRP sheets, aimed at understanding the underlying mechanisms of achieving structural ductility when BFRP sheets are used. The damage process was assessed using digital image correlation (DIC) and acoustic emission (AE) techniques applied to monitor surface and internal damages of three full-scale concrete beams subjected to four-point bending. A beam was first loaded to crack, then repaired with BFRP sheets, and finally reloaded to failure. Surface strain fields and cracks were monitored using a DIC method, and cracking events were monitored using AE sensors deployed at different positions of the beams. The AE signals were analyzed to assess the damage process. The test results indicated that (1) tensile cracks predominated throughout the loading process; (2) the BFRP sheets hindered the widening of cracks and promoted the generation of fine cracks; and (3) the development of concrete cracks promoted interfacial debonding at steel-concrete and BFRP-concrete interfaces. A combination of different types of cracks and interfacial debonding helped the repaired beam achieve ductile flexural behaviors.

The surging accumulation of trajectory data has yielded invaluable insights into urban systems, but it has also presented challenges for data storage and management systems. In response, specialized storage systems based on non-relational databases have been developed to support large data quantities in distributed approaches. However, these systems often utilize storage by point or storage by trajectory methods, both of which have drawbacks. In this study, we evaluate the effectiveness of segmented trajectory data storage with HBase optimizations for spatio-temporal queries. We develop a prototype system that includes trajectory segmentation, serialization, and spatio-temporal indexing and apply it to taxi trajectory data in Beijing. Our findings indicate that the segmented system provides enhanced query speed and reduced memory usage compared to the Geomesa system.

Abstract In China, coal miners are the primary workforce in coal mining, and among all patients with occupational diseases, 90% suffer from pneumoconiosis. Therefore, the psychological problems resulting from the dual pressures of occupational stress and the high risk of occupational diseases among coal miners are significant factors that affect the development of physical and mental health and even production safety. The Crown–Crisp Experience Index (CCEI) is a multidimensional questionnaire that assesses the psychological state of patients. This study aims to test reliability and validity of Chinese version of the CCEI questionnaire using factor analysis, and apply it to coal miners. We recruited a total of 900 participants from different occupational stages in coal mining, including active miners, Coal Workers’ Pneumoconiosis (CWP) patients, and retired miners, to evaluate the reliability and validity of the Chinese version of the CCEI questionnaire. A questionnaire survey was conducted on three groups of 1000 individuals each, including active coal miners, retired coal miners, and pneumoconiosis patients, to determine the detection rate of psychological problems in each group. An analysis was performed for each group to explore the primary factors influencing anxiety. The exploratory factor analysis yielded six principal components that accounted for a total of 79.389% of variances. The confirmatory factor analysis showed that the Chi-square freedom ratio (χ 2 /df) was 1.843, the root mean square error approximation was less than 0.044, and the comparative fit index was 0.938 and Tucker–Lewis index (TLI) was 0.934. The Cronbach's alpha coefficient was 0.948, and the scale-level content validity index (S-CVI) was 0.88. Effective questionnaires were obtained from 98.5%, 96.9%, to 91.0% of pneumoconiosis patients, active miners, and retired miners, respectively, with the incidence rates of psychological problems being 21%, 35.8%, and 13.6%, respectively. Compared with retired miners, active miners showed higher levels of psychological problems in the dimensions of depressive symptoms, free-floating anxiety and somatic symptoms, whereas pneumoconiosis patients had higher levels of psychological problems in the dimensions of phobic anxiety and somatic symptoms. This study demonstrates that the Chinese version of the CCEI is highly reliable and valid and can be used as a screening tool to measure patients' anxiety and fear levels in coal minders. Miners face distinct psychological challenges at different stages and require targeted screening and interventions.

As crucial water conservancy projects, ship locks play a key role in flood control, shipping, water resource allocation, and promoting regional economic development, making them an indispensable part of the modern water transportation system. Utilizing satellite remote sensing for lock extraction can significantly reduce manual workload and costs, assist in the daily dynamic maintenance of lock hubs, and provide more comprehensive data support for the construction and management of water transport infrastructure. In this context, this paper proposes a new method for ship lock object extraction. Leveraging fuzzy theory and prior knowledge of locks, the extraction of lock objects is achieved from Gaofen-1 (GF-1) high-resolution remote sensing images. The experimental results demonstrate that the proposed algorithm can effectively extract small lock objects in remote sensing images, achieving an average extraction accuracy of 80.9% in the study area.

Abstract Objective To identify risk factors for infection complications in patients with gastrointestinal diffuse large B-cell lymphoma (GI-DLBCL) and nodal DLBCL (N-DLBCL) during treatment, respectively. Methods Total 51 GI-DLBCL patients and 80 N-DLBCL patients were included after retrieving clinical data from a single medical center in the past ten years. Logistic regression analysis was utilized to analyze patients’ data, including baseline demographics, treatments and laboratory values, to determine independent risk factors of infection in these patients. Results Total 28 of 51 patients (54.9%) in the GI-DLBCL group and 52 of 80 patients (65%) in the N-DLBCL group were observed infection events during treatment. A multivariate logistic regression model revealed that Ann-arbor stage IV (P = 0.034; odds ratio [OR]: 10.635; 95% confidence interval [CI]: 1.152-142.712), extra-nodal lesions ≥ 2 (P = 0.041; OR: 23.116; 95%CI: 1.144-466.949) and high serum lactate dehydrogenase (LDH) at the time of diagnosis (LDH > 252U/L; P = 0.033; OR: 6.058; 95%CI: 1.159–31.659) were independent risk factors for the development of infection in patients with GI-DLBCL after systemic treatment. In the N-DLBCL group, high serum C-reactive protein (CRP) (P = 0.027; OR: 1.104; 95%CI: 1.011–1.204) and a low platelet count (P = 0.041; OR: 0.991; 95%CI: 0.982-1.000) at routine blood tests just before infection occurred were identified as significant risk factors related to infection events during treatment. Conclusions Discordant independent risk factors induced infection may be present during the treatment in patients with GI-DLBCL and N-DLBCL. Close monitoring these risk factors is likely an effective strategy to prevent microbial infections in these patients.

Abstract Increasing evidence suggests that chronic inflammation plays an important role in the pathogenesis of age-related macular degeneration (AMD); however, the precise pathogenic stressors and sensors, and their impact on disease progression remain unclear. Several studies have demonstrated that type I interferon (IFN) response is activated in the retinal pigment epithelium (RPE) of AMD patients. Previously, we demonstrated that human RPE cells can initiate RNA-mediated type I IFN responses through RIG-I, yet are unable to directly sense and respond to DNA. In this study, we utilized a co-culture system combining primary human macrophage and iPS-derived RPE to study how each cell type responds to nucleic acids challenges and their effect on RPE barrier function in a homotypic and heterotypic manner. We find that DNA-induced macrophage activation induces an IFN response in the RPE, and compromises RPE barrier function via tight-junction remodeling. Investigation of the secreted cytokines responsible for RPE dysfunction following DNA-induced macrophages activation indicates that neutralization of macrophage-secreted TNFα, but not IFNβ, is sufficient to rescue RPE morphology and barrier function. Our data reveals a novel mechanism of intercellular communication by which DNA induces RPE dysfunction via macrophage-secreted TNFa, highlighting the complexity and potential pathological relevance of RPE and macrophage interactions.

Abstract Renal cancer is a common malignancy of the urinary system, and renal clear cell carcinoma (RCCC) is the most common pathological type. Transmembrane channel-like (TMC) protein is an evolutionarily conserved gene family containing 8 members, however there is still a lack of comprehensive analysis about TMC family members in RCCC. In this study, we analyzed the expression of TMC family members in RCCC from TCGA and investigated the prognosis values and immune infiltration of TMC family members in RCCC. We found that TMC2, TMC3, TMC5, TMC7 and TMC8 were significantly related with overall survival (OS) of RCCC patients. TMC3, TMC6, and TMC8 was positively correlated with the degree of immune infiltration in RCCC. TMC2, TMC6, TMC7, and TMC8 were positively correlated with immune checkpoint genes, whereas TMC4 was negative. According to KEGG and GO analysis, almost all TMCs except TMC4 were involved in the immune response. Thus, we may regard the TMC family members as novel biomarkers to predict potential prognosis and immunotherapeutic response in RCCC patients.

The retinal pigment epithelium (RPE) is essential to maintain retinal function, and RPE cell death represents a key pathogenic stage in the progression of several blinding ocular diseases, including age-related macular degeneration (AMD). To identify pathways and compounds able to prevent RPE cell death, we developed a phenotypic screening pipeline utilizing a compound library and high-throughput screening compatible assays on the human RPE cell line, ARPE-19, in response to different disease relevant cytotoxic stimuli. We show that the metabolic by-product of the visual cycle all-trans-retinal (atRAL) induces RPE apoptosis, while the lipid peroxidation by-product 4-hydroxynonenal (4-HNE) promotes necrotic cell death. Using these distinct stimuli for screening, we identified agonists of the aryl hydrocarbon receptor (AhR) as a consensus target able to prevent both atRAL mediated apoptosis and 4-HNE-induced necrotic cell death. This works serves as a framework for future studies dedicated to screening for inhibitors of cell death, as well as support for the discussion of AhR agonism in RPE pathology.

Machine learning has exhibited high efficiency in designing concrete. However, collecting the dataset for training machine learning models is challenging. To address this challenge, this paper develops an approach to collect concrete design data automatically based on information extraction techniques. The approach enables machine learning models to automatically track, extract, and learn knowledge embedded in data from relevant publications. The approach has been incorporated into AI-assisted design of low-carbon cost-effective ultra-high-performance concrete (UHPC) via integrating the capabilities of automatically collecting and processing data, predicting UHPC properties, and optimizing UHPC properties regarding the material cost, carbon footprint, and compressive strength. A self-updating mechanism is imparted to continuously learn available data. Such a mechanism enables the self-updatable automatic discovery of low-carbon cost-effective UHPC. The results showed increasing prediction accuracy and optimization performance of the proposed approach over time when more knowledge was learned from new data, therefore accelerating the design of UHPC.

BackgroundWhile dietary factors have shown an association with Parkinson’s disease (PD), the available data remains a subject of ongoing debate and controversy.AimWe sought to evaluate potential relationships between dietary consumption of nutrients and micronutrients and risk of PD in a large sample.MethodsCross-sectional data were retrospectively analyzed for 10,651 adults aged 40–80 years that had been collected in the US between 2007 and 2016 as a component of the nationwide National Health and Nutrition Examination Survey. Aspects of dietary intake were compared between those who reported having specific PD medication regimens or not when they completed the survey, and potential associations between diet and risk of PD were explored using binomial logistic regression. We employed Propensity Score Matching (PSM) to minimize the impact of potential confounding factors, thus enhancing the reliability of the results. Additionally, subgroup analysis based on gender and age was conducted to investigate these relationships.ResultsHigher dietary intake of iron was linked to greater PD risk [odds ratio (OR) 1.065, 95% confidence interval (CI) 1.019–1.114, p = 0.006], whereas risk decreased with higher intake of vitamin K (OR 0.999, 95% CI 0.998–1.000, p = 0.024) or vitamin C (OR 0.998, 95% CI 0.996–0.999, p = 0.039). Even after applying PSM, the connection between dietary iron intake and dietary vitamin C intake with PD risk remained substantial. Subgroup analysis results revealed a significant positive association between dietary intake of iron from food and the PD risk, which was evident among individuals under 60 years of age and among males.ConclusionThe intake of micronutrients can influence risk of PD, which should be verified and explored further in prospective samples with other dietary habits and ethnic backgrounds.

Abstract In China, among all patients with occupational diseases, 90% have pneumoconiosis. The disease, which leads to psychological problems, seriously affects patients’ lives. The Crown-Crisp Experience Index (CCEI) is a multidimensional questionnaire to assess patients’ psychological conditions. Yet there is no Chinese version of CCEI. This study, therefore, aims to develop a Chinese CCEI, in line with standard localization procedures, by translating, back-translating, and culturally adapting the original English version. The final Chinese version comprises 47 items in six dimensions. The reliability and validity of the Chinese CCEI were tested by analyzing the data collected from 1,000 pneumoconiosis patients from an occupational disease prevention and treatment hospital. A rank sum test was carried out to compare the phobic anxiety (PHO) between pneumoconiosis patients and retired miners. The results of exploratory factor analysis show six principal components, which explain a total of 78.246% variances. Confirmatory factor analysis shows that the Chi-square freedom ratio (χ 2 /df) were less than 3, the root mean square error approximation (RMSEA) were less than 0.05, comparative fit Index(CFI) and incremental fit index (IFI) were greater than 0.9, average variance extracted(AVE) in six dimensions were less than 0.5, residual variances(CR) were greater than 0.8, Cronbach’s alpha coefficient 0.839, Omega ω coefficient 0.889, and S-CVI 0.88. The PHO of pneumoconiosis patients was significantly higher than that of retired miners exemplified by a statistical difference (P

Objective To summarize the clinical and imaging features of patients with posterior cortical atrophy (PCA). Methods and Results Five patients with PCA admitted in West China Hospital, Sichuan University from April to June 2021 were included. All of them showed spatial perception disorder, simultaneous agnosia, miscalculation, agraphia, structural apraxia, environmental agnosia. Apraxia of dressing and agnosia of left and right were found in 3 cases. One case had facial agnosia, visual ataxia and object perception disorder. Cerebrospinal fluid (CSF) biomarker determination: amyloid β⁃protein 42 (Aβ42) decreased in 3 cases, the ratio of Aβ42/amyloid β⁃protein 40 (Aβ40) decreased significantly in 2 cases, the content of total tau protein (t ⁃ tau) increased in all 5 cases, phosphorylated tau 181 protein (p ⁃ tau181) increased in 3 cases. Neuropsychological tests showed that: 1) Five patients all had different degrees of cognitive dysfunction and impairment of activities of daily living, as well as impairment of visuospatial ability, visual memory and attention. 2) Three cases had anxiety and depression, language and executive function were impaired in 3 cases, and verbal memory was impaired in 2 cases. Head MRI examination all indicated different degrees of parieto ⁃ occipital ⁃temporal cortical atrophy. Hypometabolism in posterior regions involving parietal and temporal cortex was observed in one case with 18F⁃FDG PET. Three cases completed the visual field examination, including 5 cases of binocular vision loss, one case of complete visual field defect, 2 cases of partial visual field defect. Except one case lost to follow⁃up, other 4 cases were followed up for 20-22 months. Two cases of cognitive function, visuospatical ability decline, of which one case could not take care of themselves most of the life. Cognitive function and visuospatial ability improved in one case. There was no significant change in cognitive function and visuospatial ability in one case. Conclusions PCA should be considered in patients with relatively early⁃onset of agnosia, visual field defect and visuospatial impairment. Comprehensive neuropsychological tests related to visual function, brain MRI, 18F⁃FDG PET and CSF biomarkers would be helpful for accurate diagnosis.