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Abstract Background The DELLA proteins, a class of GA signaling repressors, belong to the GRAS family of plant-specific nuclear proteins. Members of DELLA gene family encode transcriptional regulators with diverse functions in plant development and abiotic stress responses. To date, DELLAs have been identified in various plant species, such as Arabidopsis thaliana, Malus domestica, Populus trichocarpa, and other land plants. Most information of DELLA family genes was obtained from A. thaliana, whereas little is known about the DELLA gene family in blueberry. Results In this study, we identified three DELLA genes in blueberry (Vaccinium darrowii, VdDELLA) and provided a complete overview of VdDELLA gene family, describing chromosome localization, protein properties, conserved domain, motif organization, and phylogenetic analysis. Three VdDELLA members, containing two highly conserved DELLA domain and GRAS domain, were distributed across three chromosomes. Additionally, cis-acting elements analysis indicated that VdDELLA genes might play a critical role in blueberry developmental processes, hormone, and stress responses. Expression analysis using quantitative real-time PCR (qRT-PCR) revealed that all of three VdDELLA genes were differentially expressed across various tissues. VdDELLA2 was the most highly expressed VdDELLA in all denoted tissues, with a highest expression in mature fruits. In addition, all of the three VdDELLA genes actively responded to diverse abiotic stresses. Based on qRT-PCR analysis, VdDELLA2 might act as a key regulator in V. darrowii in response to salt stress, whereas VdDELLA1 and VdDELLA2 might play an essential role in cold stress response. Under drought stress, all of three VdDELLA genes were involved in mediating drought response. Furthermore, their transiently co-localization with nuclear markers in A. thaliana protoplasts demonstrated their transcriptional regulator roles. Conclusions In this study, three VdDELLA genes were identified in V. darrowii genome. Three VdDELLA genes were closely related to the C. moschata DELLA genes, S. lycopersicum DELLA genes, and M. domestica DELLA genes, respectively, indicating their similar biological functions. Expression analysis indicated that VdDELLA genes were highly efficient in blueberry fruit development. Expression patterns under different stress conditions revealed the differentially expressed VdDELLA genes responding to salt, drought, and cold stress. Overall, these results enrich our understanding of evolutionary relationship and potential functions of VdDELLA genes, which provide valuable information for further studies on genetic improvement of the plant yield and plant resistance.

Abstract Innate lymphoid cells (ILCs) are a heterogeneous population that play diverse roles in airway inflammation after exposure to allergens and infections. However, how ILCs respond after exposure to environmental toxins is not well understood. Here we show a novel method for studying the heterogeneity of rare lung ILC populations by magnetic enrichment for lung ILCs followed by particle-templated instant partition sequencing (PIP-seq). Using this method, we were able to identify novel group 1 and group 2 ILC subsets that exist after exposure to both fungal allergen and burn pit-related constituents (BPC) that include dioxin, aromatic hydrocarbon, and particulate matter. Toxin exposure in combination with fungal allergen induced activation of specific ILC1/NK and ILC2 populations as well as promoted neutrophilic lung inflammation. Oxidative stress pathways and downregulation of specific ribosomal protein genes (Rpl41 and Rps19) implicated in anti-inflammatory responses were present after BPC exposure. Increased IFNγ expression and other pro-neutrophilic mediator transcripts were increased in BPC-stimulated lung innate lymphoid cells. Further, the addition of BPC induced Hspa8 (encodes HSC70) and aryl hydrocarbon transcription factor activity across multiple lung ILC subsets. Overall, using an airway disease model that develops after occupational and environmental exposures, we demonstrate an effective method to better understand heterogenous ILC subset activation.

Abstract Observational studies have suggested the potential benefits of several medications for Parkinson’s disease (PD) and their potential for repurposing. However, the conclusions drawn from these studies are not entirely consistent. To address this inconsistency, we used the two-sample Mendelian randomization (MR) method to explore the putative causal relationships between 23 medications and the risk and progression of PD. We applied inverse-variance weighted meta-analysis (IVW) to combine MR estimates. Additionally, sensitivity analyses were conducted to evaluate the robustness of the results. Our genetic evidence suggests that thyroid preparations and calcium channel blockers reduce the risk of PD, and salicylic acid and derivatives slow the progression of PD motor symptoms. Additionally, genetic evidence also suggests that four medications were associated with PD risk or progression, but the sensitivity analysis revealed that three of the medications may have interference caused by reverse causality. Our findings suggest that there are weak causal relationships between several medications and the risk or progression of PD. Though further replication studies are needed to verify these findings, these new insights may help in understanding the etiology of the disease, generate new clues related to drug discovery, and quantify the risk of future drug intake.

Abstract Aims/Introduction The aim of the present study was to evaluate the status of glycemic control, and assess the effects of the disease course and comprehensive management measures on the blood glucose level in children and adolescents with type 2 diabetes mellitus. Materials and Methods The study collected the clinical data of type 2 diabetes patients in Beijing Children's Hospital from January 2015 to September 2020. Patients were grouped based on the disease course to compare their glycated hemoglobin (HbA1c) level, islet β‐cell function, insulin resistance and comprehensive management measures. Results Of the 170 participants, the median disease course was 2.0 years (interquartile range [IQR] 1.0–4.0 years). The baseline HbA1c was 11.2% (IQR 9.2–12.4%). According to the grouping by the disease course, the median HbA1c was the lowest (5.7% [IQR 5.3–6.1%]) in the half‐year course group and the highest in the 4‐year course group (9.0 [IQR 6.8%–11.3%]). Compared with the group with a disease duration 4 years group had a lower proportion of patients with HbA1c

Abstract Background Adenomyosis is a commonly observed benign gynecological disease that affects the quality of life and social psychology of women of childbearing age. However, because of the unknown etiology and incidence of adenomyosis, its pathophysiological mechanism remains unclear; further, because no noninvasive, accurate, and individualized diagnostic methods are available, treatment and efficacy evaluations are limited. Notably, the interaction between the changes in the microecological environment of the female reproductive tract and human immunity, endocrine, and other links leads to the occurrence and development of diseases. In addition, the vaginal microbiome differs in different menstrual cycles; therefore, assessing the differences between the microbiomes of patients with adenomyosis and healthy individuals in different menstrual cycles will improve the understanding of the disease and provide references for the search for noninvasive diagnosis and individualized precision treatment of adenomyosis. This study aimed to explored the data of individuals in different menstrual cycles. Results Differences in the vaginal microbiome between patients with adenomyosis and healthy individuals were observed. At phylum level, the relative abundance of Firmicutes in the adenomyosis group was higher than that in the control group, which contributed the most to the species difference between the two groups. At the genus level, Lactobacillus was the most dominant in both groups, Alpha-diversity analysis showed significant differences in the adenomyosis and control group during luteal phase (Shannon index, p = 0.0087; Simpson index, p = 0.0056). Beta-diversity index was significantly different between the two groups (p = 0.018). However, based on Weighted Unifrac analysis, significant differences were only observed throughout the luteal phase (p = 0.0146). Within the adenomyosis group, differences between women with different menstrual cycles were also observed. Finally, 50 possible biomarkers including were screened and predicted based on the random forest analyse. Conclusions The vaginal microbiome of patients with adenomyosis and healthy individuals differed during menstrual periods, especially during the luteal phase. These findings facilitate the search for specific biological markers within a limited range and provide a more accurate, objective, and individualized diagnostic and therapeutic evaluation method for patients with adenomyosis, compared to what is currently available.

Abstract Remote sensing scene images contain numerous feature targets with unrelated semantic information, so how to extract to the local key information and semantic features of the image becomes the key to achieving accurate classification. Existing Convolutional Neural Networks (CNNs) mostly concentrate on the global representation of an image and lose the shallow features. To overcome these issues, this paper proposes LPNet for remote sensing scene image classification. First, LPNet employs LKConv to extract the semantic features in the image, while using standard convolution to extract local key information in the image. Additionally, the LPNet applies a shortcut residual concatenation branch to reuse features. Then, parameter fusion combines parameters from previous branches, improving the capacity of the model to obtain a more comprehensive and rich feature representation of the image. Finally, considering the relationship between the classification ability of the model and the depth of feature extraction, the Feature Mixture (FM) Block is used to deepen the model for feature extraction. Comparative experiments on four publicly available datasets show that LPNet provides comparable results to other state‐of‐the‐art methods. The effectiveness of LPNet is further demonstrated by visualizing the effective receptive fields (ERFs).

Abstract Background Epstein-Barr virus-associated lymphoproliferative disorders (EBV-LPDs) are a group of disorders involving lymphoid tissues or lymphocytes. The epidemiology and economic burden of hospitalized children with EBV-LPDs in China have not been well studied. This study aimed to reveal the epidemic characteristics and disease burden of EBV-LPDs among the Chinese hospitalized children, providing strategies for the prevention and management. Methods This study was based on the FUTang Updating medical REcords (FUTURE) database of China and collected the medical records from 27 tertiary children’s hospitals between January 2016 and December 2021 in China, counting five types of EBV-LPDs, namely EBV-positive T-cell lymphoproliferative disease, NK/T cell lymphoma, extranodal NK/T-cell lymphoma (nasal type), systemic EBV-positive T-cell lymphoproliferative disease of childhood and posttransplant lymphoproliferative disorders. We conducted a retrospective syhthesis and analysis of the epidemiological characteristics, expenses, length of stay (LOS), as well as complications among hospitalized children diagnosed with five types of EBV-LPDs and compared parameters using appropriate statistical tests. Results The study described 153 children aged 0–18 years hospitalized with EBV-LPDs from 2016 to 2021 in the FUTURE database. The male-to-female ratio was 1.10:1, and more than half of the age distribution was in the 6–12 y group. Among EBV-LPDs cases, EBV+ T-LPD accounted for the largest proportion (65.36%). Complications were presented in 93 children with EBV-LPDs, mainly hemophagocytic lymphohistiocytosis (HLH). The median LOS of NKTL was 26.5 days [interquartile range (IQR) = 3–42], which was the longest among EBV-LPDs. The median hospitalization cost of PTLD was 10 785.74 United States dollars (IQR = 7 329.38–16 531.18), which was the heaviest among EBV-LPDs. Conclusions Compared with the total number of hospitalized children in China during the same period and in the same age group, the proportion of EBV-LPD is very low. EBV-LPD can develop in all age groups, but it is more common in school-age children. Among 5 EBV-LPDs, the disease with the highest proportion is EBV+ T-LPD. The overall disease burden of EBV-LPD was heavy, especially the economic burden. HLH was one of the most common complications, which could directly affect the burden of patients because of prolonged hospitalization. These data are taken from a very large database, illustrating the epidemiological and economic burden of EBV-LPDs hospitalized children in China, which enriched the existing epidemiological and disease burden content of EBV-LPDs.

Abstract Background Multiple epiphyseal dysplasia-4 (MED-4, MIM 226900) is a rare autosomal recessive disease characterized by disproportionate height and early onset osteoarthritis of the lower limbs. MED-4 is caused by homozygous or compound heterozygous pathogenic variants in the SLC26A2 gene. However, the underlying pathogenic mechanisms in chondrocytes remains unknown. This study aimed to identify the pathogenic variants within a MED-4 family and explore the molecular etiology of this condition in human primary chondrocyte cells. Methods Clinical data were recorded and peripheral blood samples were collected for analysis. Whole exome sequencing (WES) and bioinformatic analyses were performed to determine causative variants. Wild-type SLC26A2 and corresponding mutant expression plasmids were constructed and transfected into human primary chondrocytes. The expression and subcellular distribution of SLC26A2 protein in chondrocytes were detected by immunoblotting and immunofluorescence. Effects of these variants on chondrocytes viability and apoptosis were measured by Cell Counting Kit-8 (CCK-8) assay. Expression of genes related to cartilage homeostasis was subsequently analyzed by quantitative real-time polymerase chain reaction (qRT-PCR). Results We identified two compound heterozygous variants c.1020_1022delTGT(p.Val341del) and c.1262 T > C(p.Ile421Thr) in the SLC26A2 gene in the patients. Mutant SLC26A2Val341del and SLC26A2Ile421Thr proteins were distributed in relatively few cells and were observed only within the nucleus. The viability of chondrocytes with the SLC26A2 variant group was similar to the wild-type (WT) group. However, the protein expressions of SLC26A2Val341del and SLC26A2Ile421Thr were decreased compared with SLC26A2WT. Expression levels of matrix metallopeptidase 13 (MMP13), α-1 chain of type X collagen (COL10A1), and Runt-related transcription factor 2 (RUNX2) were significantly decreased in the variant group. However, aggrecan (ACAN) expression was higher in the variant group than the WT group. Conclusions Overall, our data demonstrate that the variants p.Val341del and p.Ile421Thr in SLC26A2 cause MED-4 and that these two variants promote chondrocyte proliferation while inhibiting chondrocyte differentiation.

Erdheim-Chester Disease (ECD) is a rare form of histiocytosis characterized by xanthomatous infiltration of affected organs. We present a case of a 62-year-old man with ECD initially presenting with constrictive pericarditis. Comprehensive imaging revealed systemic involvement, including the skeleton, orbit, pituitary, lung, kidney, and retroperitoneum, despite the absence of related symptoms. The diagnosis of ECD was eventually confirmed through histopathological evidence from a CT-guided biopsy. The patient responded well to interferon-α2b treatment, with gradual symptom amelioration and improvement in imaging and laboratory findings over a 5-month follow-up period. This case highlights the importance of considering ECD in the differential diagnosis of constrictive pericarditis and the utility of multimodal imaging for accurate diagnosis and management of this rare disease. The patient's positive response to treatment also highlights the potential for effective management of ECD, particularly with early diagnosis and intervention.

ABSTRACTSoybean is one of the important oil crops and a major source of protein and lipids. Drought can cause severe soybean yields. Dehydrin protein (DHN) is a subfamily of LEA proteins that play an important role in plant responses to abiotic stresses. In this study, the soybean GmDHN9 gene was cloned and induced under a variety of abiotic stresses. Results showed that the GmDHN9 gene response was more pronounced under drought induction. Subcellular localization results indicated that the protein was localized in the cytoplasm. The role of transgenic Arabidopsis plants in drought stress response was further studied. Under drought stress, the germination rate, root length, chlorophyll, proline, relative water content, and antioxidant enzyme content of transgenic Arabidopsis thaliana transgenic genes were higher than those of wild-type plants, and transgenic plants contained less O2−, H2O2 and MDA contents. In short, the GmDHN9 gene can regulate the homeostasis of ROS and enhance the drought resistance of plants.

In recent years, DNA origami-based nanocarriers have been extensively utilized for efficient cancer therapy. However, developing a nanocarrier capable of effectively protecting cargos such as RNA remains a challenge. In this study, we designed a compact and controllable DNA tubular origami (DTO) measuring 120 nm in length and 18 nm in width. The DTO exhibited appropriate structural characteristics for encapsulating and safeguarding cargo. Inside the DTO, we incorporated 20 connecting points to facilitate the delivery of cargoes to various ovarian and normal epithelial cell lines. Specifically, fluorescent-labeled DNA strands were attached to these sites as cargoes. The DTO was engineered to open upon encountering miR-21 through RNA/DNA strand displacement. Significantly, for the first time, we inhibited fluorescence using the compact DNA nanotube and observed dynamic fluorescent signals, indicating the controllable opening of DTO through live-cell imaging. Our results demonstrated that the DTO remained properly closed, exhibited effective internalization in ovarian cancer cells in vitro, showcasing marked differential expression of miR-21, and efficiently opened with short-term exposure to miR-21. Leveraging its autonomous behavior and compact design, the DTO emerges as a promising nanocarrier for various clinically relevant materials. It holds significant application prospects in anti-cancer therapy and the development of flexible biosensors.

Owing to the integration of energy digitization and artificial intelligence technology, smart energy grids can realize the stable, efficient and clean operation of power systems. However, the emergence of cyber-physical attacks, such as dynamic load-altering attacks (DLAAs) has introduced great challenges to the security of smart energy grids. Thus, this study developed a novel cyber-physical collaborative security framework for DLAAs in smart energy grids. The proposed framework integrates attack prediction in the cyber layer with the detection and localization of attacks in the physical layer. First, a data-driven method was proposed to predict the DLAA sequence in the cyber layer. By designing a double radial basis function network, the influence of disturbances on attack prediction can be eliminated. Based on the prediction results, an unknown input observer-based detection and localization method was further developed for the physical layer. In addition, an adaptive threshold was designed to replace the traditional precomputed threshold and improve the detection performance of the DLAAs. Consequently, through the collaborative work of the cyber-physics layer, injected DLAAs were effectively detected and located. Compared with existing methodologies, the simulation results on IEEE 14-bus and 118- bus power systems verified the superiority of the proposed cyber-physical collaborative detection and localization against DLAAs.

Cutaneous neurofibroma (cNF) is a prevalent clinical manifestation of neurofibromatosis type 1, significantly affecting the well-being and quality of life of the affected individuals. The adoption of reliable and reproducible volumetric measurement techniques is essential for precisely evaluating tumor burden and plays a critical role in the development of effective treatments for cNF. This study focuses on widely used volumetric measurement techniques, including vernier calipers, ultrasound, computed tomography, magnetic resonance imaging, and three-dimensional scanning imaging. It outlines the merits and drawbacks of each technique in assessing the cNF load, providing an overview of their current applications and ongoing research advancements in this domain.

Abstract Background There is no individualized prediction model for intensive care unit (ICU) admission on patients with community-acquired pneumonia (CAP) and connective tissue disease (CTD) so far. In this study, we aimed to establish a machine learning-based model for predicting the need for ICU admission among those patients. Methods This was a retrospective study on patients admitted into a University Hospital in China between November 2008 and November 2021. Patients were included if they were diagnosed with CAP and CTD during admission and hospitalization. Data related to demographics, CTD types, comorbidities, vital signs and laboratory results during the first 24 h of hospitalization were collected. The baseline variables were screened to identify potential predictors via three methods, including univariate analysis, least absolute shrinkage and selection operator (Lasso) regression and Boruta algorithm. Nine supervised machine learning algorithms were used to build prediction models. We evaluated the performances of differentiation, calibration, and clinical utility of all models to determine the optimal model. The Shapley Additive Explanations (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME) techniques were performed to interpret the optimal model. Results The included patients were randomly divided into the training set (1070 patients) and the testing set (459 patients) at a ratio of 70:30. The intersection results of three feature selection approaches yielded 16 predictors. The eXtreme gradient boosting (XGBoost) model achieved the highest area under the receiver operating characteristic curve (AUC) (0.941) and accuracy (0.913) among various models. The calibration curve and decision curve analysis (DCA) both suggested that the XGBoost model outperformed other models. The SHAP summary plots illustrated the top 6 features with the greatest importance, including higher N-terminal pro-B-type natriuretic peptide (NT-proBNP) and C-reactive protein (CRP), lower level of CD4 + T cell, lymphocyte and serum sodium, and positive serum (1,3)-β-D-glucan test (G test). Conclusion We successfully developed, evaluated and explained a machine learning-based model for predicting ICU admission in patients with CAP and CTD. The XGBoost model could be clinical referenced after external validation and improvement.

Abstract Tumorigenesis is a multistep process, with oncogenic mutations in a normal cell conferring clonal advantage as the initial event. However, despite pervasive somatic mutations and clonal expansion in normal tissues, their transformation into cancer remains a rare event, indicating the presence of additional driver events for progression to an irreversible, highly heterogeneous, and invasive lesion. Recently, researchers are emphasizing the mechanisms of environmental tumor risk factors and epigenetic alterations that are profoundly influencing early clonal expansion and malignant evolution, independently of inducing mutations. Additionally, clonal evolution in tumorigenesis reflects a multifaceted interplay between cell-intrinsic identities and various cell-extrinsic factors that exert selective pressures to either restrain uncontrolled proliferation or allow specific clones to progress into tumors. However, the mechanisms by which driver events induce both intrinsic cellular competency and remodel environmental stress to facilitate malignant transformation are not fully understood. In this review, we summarize the genetic, epigenetic, and external driver events, and their effects on the co-evolution of the transformed cells and their ecosystem during tumor initiation and early malignant evolution. A deeper understanding of the earliest molecular events holds promise for translational applications, predicting individuals at high-risk of tumor and developing strategies to intercept malignant transformation.

Abstract Rock abrasivity is one of the main factors affecting the wear of rock-cutting tools, which is usually quantified by the CERCHAR Abrasivity Index (CAI). Researchers and engineers study tool wear and predict tool life based on the CAI of rocks. However, there is still a lack of a dataset on rock properties, especially the abrasivity of various rocks. This paper reports the abrasive dataset of 10 kinds of rocks, including sedimentary rocks, metamorphic rocks, and igneous rocks, with the aid of the CERCHAR Abrasivity Test and digital measurement techniques. The dataset comprises rock abrasivity data, point cloud data for visualization, scratch photos, CERCHAR Abrasivity Test force data, and mechanical properties (uniaxial compressive strength) of rock samples. This dataset facilitates future research on rock abrasivity and rock-cutting tool wear.

To investigate the effects of different brine and fermentation methods on the quality characteristics of fermented chili peppers, this study employed four different fermentation methods: Natural fermentation with sterile water, co-inoculation fermentation (Lactiplantibacillus plantarum KUST-D1303:Pichia manshurica KUST-F1705=1:1) with sterile water, natural fermentation with aged brine and co-inoculation fermentation with aged brine. The quality characteristics of the fermented chili peppers were compared and analyzed. Results showed that compared to other fermentation methods, co-inoculation fermentation with aged brine significantly (P

Abstract Background The filamentous temperature-sensitive H protease (ftsH) gene family belongs to the ATP-dependent zinc metalloproteins, and ftsH genes play critical roles in plant chloroplast development and photosynthesis. Results In this study, we performed genome-wide identification and a systematic analysis of soybean ftsH genes. A total of 18 GmftsH genes were identified. The subcellular localization was predicted to be mainly in cell membranes and chloroplasts, and the gene structures, conserved motifs, evolutionary relationships, and expression patterns were comprehensively analyzed. Phylogenetic analysis of the ftsH gene family from soybean and various other species revealed six distinct clades, all of which showed a close relationship to Arabidopsis thaliana. The members of the GmftsH gene family were distributed on 13 soybean chromosomes, with intron numbers ranging from 3 to 15, 13 pairs of repetitive segment. The covariance between these genes and related genes in different species of Oryza sativa, Zea mays, and Arabidopsis thaliana was further investigated. The transcript expression data revealed that the genes of this family showed different expression patterns in three parts, the root, stem, and leaf, and most of the genes were highly expressed in the leaves of the soybean plants. Fluorescence-based real-time quantitative PCR (qRT-PCR) showed that the expression level of GmftsH genes varied under different stress treatments. Specifically, the genes within this family exhibited various induction levels in response to stress conditions of 4℃, 20% PEG-6000, and 100 mmol/L NaCl. These findings suggest that the GmftsH gene family may play a crucial role in the abiotic stress response in soybeans. It was also found that the GmftsH7 gene was localized on the cell membrane, and its expression was significantly upregulated under 4 ℃ treatment. In summary, by conducting a genome-wide analysis of the GmftsH gene family, a strong theoretical basis is established for future studies on the functionality of GmftsH genes. Conclusions This research can potentially serve as a guide for enhancing the stress tolerance characteristics of soybean.

Abstract Background Transport accidents are one of the leading causes of child morbidity and mortality worldwide and represent a significant public health burden. This study aimed to investigate the hospitalization information and burden of pediatric inpatients in transport accidents in China. Methods In this study, we collected the cover page of the medical records of pediatric inpatients in transport accidents using the Futang Research Center of Pediatric Development (FRCPD) database from January 1, 2016 to December 31, 2021. Then, we extracted the epidemiological characteristics, including demographic characteristics, cases distribution, disease information, and hospitalization burden. Results Among 36,455 included inpatients, males, aged 1–3 years, East China, July were dominant in different subgroups. In transport accidents, pedestrians were the most frequently type of injury (65.69%). Of all known lesions, craniocerebral/nerve injury was the more common results in pediatric inpatients in transport accidents (33.93%). In addition to pedal cyclists more susceptible to sport system injury, other types of injured person with transport accidents were mainly craniocerebral/nerve injury. In terms of the type of discharge, occupant of heavy transport vehicle or bus and people with craniocerebral/nerve injury had the highest mortality rate after hospitalization in all type and lesion of injured person groups, respectively. The largest hospitalization burden in the type of injured person was occupant of heavy transport vehicle or bus. Conclusions This study revealed that epidemiological characteristics and the main factor influencing the hospitalization information and burden of children with traffic accidents in China.

Abstract Background Phytophthora sojae, a soil-borne oomycete pathogen, has been a yield limiting factor for more than 60 years on soybean. The resurgence of P. sojae (Phytophthora sojae) is primarily ascribed to the durable oospores found in soil and remnants of the disease. P. sojae is capable of infesting at any growth periods of the soybean, and the succeed infestation of P. sojae is predominantly attributed to long-lived oospores present in soil. Comprehending the molecular mechanisms that drive oospores formation and their significance in infestation is the key for effective management of the disease. However, the existing challenges in isolating and extracting significant quantities of oospores pose limitations in investigating the sexual reproductive stages of P. sojae. Results The study focused on optimizing and refining the culture conditions and extraction process of P. sojae, resulting in establishment of an efficient and the dependable method for extraction. Novel optimized approach was yielded greater quantities of high-purity P. sojae oospores than traditional methods. The novel approach exceeds the traditional approaches with respect to viability, survival ability, germination rates of new oospores and the pathogenicity of oospores in potting experiments. Conclusion The proposed method for extracting P. sojae oospores efficiently yielded a substantial quantity of highly pure, viable, and pathogenic oospores. The enhancements in oospores extraction techniques will promote the research on the sexual reproductive mechanisms of P. sojae and lead to the creation of innovative and effective approaches for managing oomycete diseases.

Abstract Background In this era of rapid technological development, medical schools have had to use modern technology to enhance traditional teaching. Online teaching was preferred by many medical schools. However due to the complexity of intracranial anatomy, it was challenging for the students to study this part online, and the students were likely to be tired of neurosurgery, which is disadvantageous to the development of neurosurgery. Therefore, we developed this database to help students learn better neuroanatomy. Main body The data were sourced from Rhoton’s Cranial Anatomy and Surgical Approaches and Neurosurgery Tricks of the Trade in this database. Then we designed many hand gesture figures connected with the atlas of anatomy. Our database was divided into three parts: intracranial arteries, intracranial veins, and neurosurgery approaches. Each section below contains an atlas of anatomy, and gestures represent vessels and nerves. Pictures of hand gestures and atlas of anatomy are available to view on GRAVEN ( www.graven.cn ) without restrictions for all teachers and students. We recruited 50 undergraduate students and randomly divided them into two groups: using traditional teaching methods or GRAVEN database combined with above traditional teaching methods. Results revealed a significant improvement in academic performance in using GRAVEN database combined with traditional teaching methods compared to the traditional teaching methods. Conclusion This database was vital to help students learn about intracranial anatomy and neurosurgical approaches. Gesture teaching can effectively simulate the relationship between human organs and tissues through the flexibility of hands and fingers, improving anatomy interest and education.

Abstract Detecting early-stage esophageal squamous cell carcinoma (ESCC) and precancerous lesions is critical for improving survival. Here, we conduct whole-genome bisulfite sequencing (WGBS) on 460 cfDNA samples from patients with non-metastatic ESCC or precancerous lesions and matched healthy controls. We develop an expanded multimodal analysis (EMMA) framework to simultaneously identify cfDNA methylation, copy number variants (CNVs), and fragmentation markers in cfDNA WGBS data. cfDNA methylation markers are the earliest and most sensitive, detectable in 70% of ESCCs and 50% of precancerous lesions, and associated with molecular subtypes and tumor microenvironments. CNVs and fragmentation features show high specificity but are linked to late-stage disease. EMMA significantly improves detection rates, increasing AUCs from 0.90 to 0.99, and detects 87% of ESCCs and 62% of precancerous lesions with >95% specificity in validation cohorts. Our findings demonstrate the potential of multimodal analysis of cfDNA methylome for early detection and monitoring of molecular characteristics in ESCC.

Abstract Transformers may suffer multiple short‐circuit impacts during long‐term operation, and axial instability is one of the typical types of serious accidents caused by short‐circuit faults. The axial instability form of the winding‐block structure is analysed, and the dynamic solution of the winding short‐circuit electromagnetic force is obtained by establishing the three‐dimensional magnetic‐circuit‐force multi‐physical field coupling simulation model. The influence of strain rate on the cushion block constitutive equation is corrected, and the modified model is verified by short‐circuit impact test and quasi‐static test. The research results show that for 110 kV 31.5 MVA transformers, the maximum electromagnetic axial resultant force of winding is 363.16 kN, and the ultimate tilt force is 1214.2 kN. The pre‐tightening force configuration is accordingly recommended to range from 363.16 to 608.28 kN, which is narrowed by 18.49% compared with the static calculation method; Meanwhile, adding a logarithmic strain rate correction term to the classical constitutive equation of the cushion block can achieve a good correction of the stress‐strain relationship with the coefficient of determination above 0.99, and the cushion block has a larger elastic modulus under high strain rate load. The research results provide an important theoretical reference for the axial stability structure of transformers.

Abstract Purpose This study aimed to investigate the effects of two different positions on lower extremity hemodynamics during robot-assisted laparoscopic radical prostatectomy (RARP) for prostate cancer. Methods A total of 196 patients who underwent RARP in our hospital from February 2020 to March 2022 were included in this study. Among them, 98 patients who underwent surgery with the Trendelenburg position and split-leg position with calf reverse arch from March 2021 to March 2022 were assigned to the observation group, while 98 patients who underwent surgery with the Trendelenburg position and low lithotomy position from February 2020 to February 2021 were assigned to the control group. Using an ultrasound diagnostic instrument to detect the internal diameter, mean blood flow velocity, and mean blood flow volume of the left deep femoral vein at different times, such as the supine position (T0), after 5 minutes of placing the patient in the leg spilt or low lithotomy position (T1), after 5 minutes of pneumoperitoneum (T2), after 5 minutes of head-down tilt or head-down tilt and calf reverse arch (T3), 1.5 hours after the start of surgery (T4), before the removal of CO2 gas (T5), and before the patient left the operating room (T6). As well as the patency of deep venous blood flow in both lower extremities before leaving the operating room, Results After establishment of pneumoperitoneum, the internal diameter of the deep femoral vein increased significantly, while the mean blood flow velocity and mean blood flow volume decreased significantly in both groups(T0) (P

Abstract Background Recently, carbon quantum dots (CQDs) have been widely used in various fields, especially in the diagnosis and therapy of neurological disorders, due to their excellent prospects. However, the associated inevitable exposure of CQDs to the environment and the public could have serious severe consequences limiting their safe application and sustainable development. Results In this study, we found that intranasal treatment of 5 mg/kg BW (20 µL/nose of 0.5 mg/mL) CQDs affected the distribution of multiple metabolites and associated pathways in the brain of mice through the airflow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI) technique, which proved effective in discovery has proven to be significantly alerted and research into tissue-specific toxic biomarkers and molecular toxicity analysis. The neurotoxic biomarkers of CQDs identified by MSI analysis mainly contained aminos, lipids and lipid-like molecules which are involved in arginine and proline metabolism, biosynthesis of unsaturated fatty acids, and glutamine and glutamate metabolism, etc. as well as related metabolic enzymes. The levels or expressions of these metabolites and enzymes changed by CQDs in different brain regions would induce neuroinflammation, organelle damage, oxidative stress and multiple programmed cell deaths (PCDs), leading to neurodegeneration, such as Parkinson’s disease-like symptoms. This study enlightened risk assessments and interventions of QD-type or carbon-based nanoparticles on the nervous system based on toxic biomarkers regarding region-specific profiling of altered metabolic signatures. Conclusion These findings provide information to advance knowledge of neurotoxic effects of CQDs and guide their further safety evaluation.

Abstract This study involved the production of 20 biochar samples derived from secondary medicinal residues of Snow Lotus Oral Liquid, processed within the temperature range of 200–600 °C. Additionally, four medicinal residues, including dissolved organic matter (DOM), from 24 samples obtained using the shaking method, served as the primary source material. The investigation focused on two key factors: the modifier and preparation temperature. These factors were examined to elucidate the spectral characteristics and chemical properties of the pharmaceutical residues, biochar, and DOM. To analyze the alterations in the spectral attributes of biochar and medicinal residues, we employed near-infrared spectroscopy (NIR) in conjunction with Fourier-infrared one-dimensional and two-dimensional correlation spectroscopy. These findings revealed that modifiers enhanced the aromaticity of biochar, and the influence of preparation temperature on biochar was diminished. This observation indicates the stability of the aromatic functional group structure. Comparative analysis indicated that Na2CO3 had a more pronounced structural effect on biochar, which is consistent with its adsorption properties. Furthermore, we utilized the fluorescence indices from UV–visible spectroscopy and excitation-emission-matrix spectra with the PARAFAC model to elucidate the characteristics of the fluorescence components in the DOM released from the samples. The results demonstrated that the DOM released from biochar primarily originated externally. Aromaticity reduction and increased decay will enhance the ability of the biochar to bind pollutants. Those results confirmed the link between the substantial increase in the adsorption performance of the high-temperature modified charcoal in the previous study and the structural changes in the biochar. We investigated the structural changes of biochar and derivative DOM in the presence of two perturbing factors, modifier and preparation temperature. Suitable modifiers were selected. Preparation for the study of adsorption properties of snow lotus medicinal residues.

Abstract Background To investigate the potential of Native T1-mapping in predicting the prognosis of patients with chronic kidney disease (CKD). Methods We enrolled 119 CKD patients as the study subjects and included 20 healthy volunteers as the control group, with follow-up extending until October 2022. Out of these patients, 63 underwent kidney biopsy measurements, and these patients were categorized into high (25–50%), low (

Introduction: Ovarian steroidogenesis not only affects the embryonic development and pregnancy outcome, but also associates with many diseases in mammals and women. Exploring the nutrients and mechanisms influencing ovarian steroidogenesis is critical to maintaining the optimal reproductive performance, as well as guaranteeing body health. Objectives: This research aimed to explore the effect of retinol metabolism on ovarian steroidogenesis and the underlying mechanisms. Methods: Comparative transcriptomic analysis of ovaries from normal and low reproductive performance sows were performed to identify the main causes leading to low fertility. The metabolites regulating steroid hormones synthesis were investigated in ovarian granulosa cells. Gene interference, overexpression, dual-luciferase reporter assays, chromatin immunoprecipitation and transcriptome analysis were further conducted to explore the underlying mechanisms of Aldh1a1 mediating ovarian steroidogenesis. Results: Transcriptome analysis of ovaries from normal and low reproductive performance sows showed the significant differences in both retinol metabolism and steroid hormones synthesis, indicating retinol metabolism probably influenced steroid hormones synthesis. The related metabolite retinoic acid was furtherly proven a highly active and potent substance strengthening estrogen and progesterone synthesis in ovarian granulosa cells. For the first time, we revealed that retinoic acid synthesis in porcine and human ovarian granulosa cells was dominated by Aldh1a1, and required the assistance of Aldh1a2. Importantly, we demonstrated that Aldh1a1 enhanced the proliferation of ovarian granulosa cells by activating PI3K-Akt-hedgehog signaling pathways. In addition, Aldh1a1 regulated the expression of transcription factor MESP2, which targeted the transcription of Star and Cyp11a1 through binding to corresponding promoter regions. Conclusion: Our data identified Aldh1a1 modulates ovarian steroidogenesis through enhancing granulosa cell proliferation and MESP2/STAR/CYP11A1 pathway. These findings provide valuable clues for improving ovarian health in mammals.

Drug conjugates are obtained from tumor-located vectors connected to cytotoxic agents via linkers, which are designed to deliver hyper-toxic payloads directly to targeted cancer cells. These drug conjugates include antibody-drug conjugates (ADCs), peptide-drug conjugates (PDCs), small molecule-drug conjugates (SMDCs), nucleic acid aptamer-drug conjugates (ApDCs), and virus-like drug conjugate (VDCs), which show great therapeutic value in the clinic. Drug conjugates consist of a targeting carrier, a linker, and a payload. Payloads are key therapy components. Cytotoxic molecules and their derivatives derived from natural products are commonly used in the payload portion of conjugates. The ideal payload should have sufficient toxicity, stability, coupling sites, and the ability to be released under specific conditions to kill tumor cells. Microtubule protein inhibitors, DNA damage agents, and RNA inhibitors are common cytotoxic molecules. Among these conjugates, cytotoxic molecules of natural origin are summarized based on their mechanism of action, conformational relationships, and the discovery of new derivatives. This paper also mentions some cytotoxic molecules that have the potential to be payloads. It also summarizes the latest technologies and novel conjugates developed in recent years to overcome the shortcomings of ADCs, PDCs, SMDCs, ApDCs, and VDCs. In addition, this paper summarizes the clinical trials conducted on conjugates of these cytotoxic molecules over the last five years. It provides a reference for designing and developing safer and more efficient conjugates.

The delicate plateau lake ecosystem has been further damaged by extensive human construction projects, leading to water pollution in Lake Dianchi, China. This serves as a prominent example of urbanization and human interference, drawing global scholarly interest. Restoring Lake Dianchi’s water quality remains a global challenge despite 40 years of treatment, with unclear links to surrounding land development. Therefore, this study constructed a GIS database, combined with 2013–2023 landsat-8/MODIS, Land Use/Land Cover (LULC) remote sensing data and multi-year water quality monitoring, to conduct a multi-scale analysis of the plateau Lake Dianchi and its surrounding land, and implemented it through a Self-Organizing Map (SOM). The classification of lakeshore pollution source clusters was further analyzed through Redundancy Analysis to explore the interaction and future trends between lake water quality and land development in the lakeshore zone. Research indicates the following: (1) According to cluster analysis, water quality in semi-urban lakeside areas (cluster 2) had the highest correlation with lakeside land use, followed by urban areas (cluster 1) and rural areas (cluster 3); (2) Lake water pollution was difficult to improve through the optimization of land development in the lakeshore zone. Combined with the results from (1), although semi-urban areas had a certain impact on water quality, over time, there was a trend of decorrelation between the steady state of water quality pollution and the development of urban construction. This trend indicates that urban development consistently contributes to single pollution sources in water quality; (3) At different scales, the water pollution index in semi-urban areas responded significantly to construction activities, indicating signs of tele-coupling; the response to farmland was complex, while the response to green space was small; (4) In the process of decorrelation between lake water quality and land development, the rate in urban areas (cluster 1) and rural areas (cluster 3) was faster than that in semi-urban lakeside areas (cluster 2). To sum up, it is difficult to restore the water quality of Lake Dianchi through optimizing urban land layout. Meanwhile, it is necessary to further prevent and control the impact of remote pollution sources on the water quality of Lake Dianchi. Protection of the plateau lake environment cannot remain at the optimization level; it should further realize the principles of multi-dimensional governance. This is also the key to addressing the lack of results in Lake Dianchi management for many years.

Abstract Background Tumor mutation burden (TMB) and VHL mutation play a crucial role in the management of patients with clear cell renal cell carcinoma (ccRCC), such as guiding adjuvant chemotherapy and improving clinical outcomes. However, the time‐consuming and expensive high‐throughput sequencing methods severely limit their clinical applicability. Predicting intratumoral heterogeneity poses significant challenges in biology and clinical settings. Our aimed to develop a self‐supervised attention‐based multiple instance learning (SSL‐ABMIL) model to predict TMB and VHL mutation status from hematoxylin and eosin‐stained histopathological images. Methods We obtained whole slide images (WSIs) and somatic mutation data of 350 ccRCC patients from The Cancer Genome Atlas for developing SSL‐ABMIL model. In parallel, 163 ccRCC patients from Clinical Proteomic Tumor Analysis Consortium cohort was used as independent external validation set. We systematically compared three different models (Wang‐ABMIL, Ciga‐ABMIL, and ImageNet‐MIL) for their ability to predict TMB and VHL alterations. Results We first identified two groups of populations with high‐ and low‐TMB (cut‐off point = 0.9). In two independent cohorts, the Wang‐ABMIL model achieved the highest performance with decent generalization performance (AUROC = 0.83 ± 0.02 and 0.8 ± 0.04 in predicting TMB and VHL, respectively). Attention heatmaps revealed that the Wang‐ABMIL model paid the highest attention to tumor regions in high‐TMB patients, while in VHL mutation prediction, non‐tumor regions were also assigned high attention, particularly the stromal regions infiltrated by lymphocytes. Conclusions Our results indicated that SSL‐ABMIL can effectively extract histological features for predicting TMB and VHL mutation, demonstrating promising results in linking tumor morphology and molecular biology.

ABSTRACT Objective Construction nomogram was to effectively predict long‐term prognosis in patients with non‐small cell lung cancer (NSCLC). Materials and Methods The nomogram is developed by a retrospective study of 347 patients with NSCLC who underwent cardiopulmonary exercise testing (CPET) before surgery from May 2019 to February 2022. Cross‐validation divided the data into a training cohort and validation cohort. The discrimination and accuracy ability of the nomogram were proofed by concordance index (C‐index), calibration curve, receiver operating characteristic (ROC) curve, the area under the curve (AUC), and time‐dependent ROC in validation cohort. Results Age, intraoperative blood loss, VO2 peak, and VE/VCO2 slope were included in the model of nomogram. The model demonstrated good discrimination and accuracy with C‐index of 0.770 (95% CI: 0.712–0.822). AUC of 6 (AUC: 0.789, 95% CI: 0.726–0.851) and 12 months (AUC: 0.787, 95% CI: 0.724–0.850) were shown in ROC. Time‐independent ROC maintains a good effect within 12 months. Conclusion We developed a nomogram based on CPET. This model has a good ability of discrimination and accuracy. It could help clinicians to make treatment decision in clinical decision.

BackgroundIn recent years, the impact of the COVID-19 pandemic and various public crises has highlighted the importance of cultivating high-quality public health talents, especially those with innovative capabilities. This study focuses on the academic innovation ability of public health postgraduate students, which can provide important theoretical support for the cultivation of more public health workers with high innovative capabilities.MethodsFrom May to October 2022, a cluster sampling method was used to select 1,076 public health postgraduate students from five universities in Shandong Province. A self-designed questionnaire survey was conducted. A chi-square test and binary logistic regression analysis were used to analyze the influencing factors of students’ academic innovation ability. Based on these factors, a nomogram was constructed to intuitively demonstrate the impact of these complex factors on students’ innovation ability.ResultsThe results showed that gender, whether serving as a student leader, teacher-student relationship, academic motivation, learning style, academic environment, and teaching mode were the influencing factors of postgraduate students’ academic innovation ability. The column-line diagram (AUC = 0.892, 95% CI = 0.803 ~ 0.833) constructed based on the above influencing factors has good differentiation. The area under the ROC curve is 0.892 (95% CI = 0.803 ~ 0.833), and the calibration curve shows that the predicted value is the same as the measured value.ConclusionThe nomogram constructed in this study can be used to predict the academic innovation level of public health graduate students, which is helpful for university education administrators to evaluate students’ academic innovation ability based on nomogram scores and carry out accurate and efficient training.

The regulation of gene expression is crucial for biological plant growth and development, with transcription factors (TFs) serving as key switches in this regulatory mechanism. GOLDEN2-LIKE (GLK) TFs are a class of functionally partially redundant nuclear TFs belonging to the GARP superfamily of MYB TFs that play a key role in regulating genes related to photosynthesis and chloroplast biogenesis. Here, we summarized the current knowledge of the pleiotropic roles of GLKs in plants. In addition to their primary functions of controlling chloroplast biogenesis and function maintenance, GLKs have been proven to regulate the photomorphogenesis of seedlings, metabolite synthesis, flowering time, leaf senescence, and response to biotic and abiotic stress, ultimately contributing to crop yield. This review will provide a comprehensive understanding of the biological functions of GLKs and serve as a reference for future theoretical and applied studies of GLKs.

Osteoarthritis (OA) is a prevalent chronic degenerative disease that affects the bones and joints, particularly in middle-aged and elderly individuals. It is characterized by progressive joint pain, swelling, stiffness, and deformity. Notably, treatment with a heat shock protein 90 (HSP90) inhibitor has significantly curtailed cartilage destruction in a rat model of OA. Although the monoclonal antibody 9B8 against HSP90 is recognized for its anti-tumor properties, its potential therapeutic impact on OA remains uncertain. This study investigated the effects of 9B8 on OA and its associated signaling pathways in interleukin-1β (IL-1β)−stimulated human chondrocytes and a rat anterior cruciate ligament transection (ACLT) model. A specific concentration of 9B8 preserved cell viability against IL-1β−induced reduction. In vitro, 9B8 significantly reduced the expression of extracellular matrix-degrading enzyme such as disintegrin and metallopeptidase-4 (ADAMTS4) of thrombospondin motifs, matrix metalloproteinase-13 (MMP-13), as well as cellular inflammatory factors such as tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6), which were upregulated by IL-1β.In vivo, 9B8 effectively protected the articular cartilage and subchondral bone of the rat tibial plateau from ACLT-induced damage. Additionally, gene microarray analysis revealed that IL-1β substantially increased the expression of SLC2A1, PFKP, and ENO2 within the HIF-1 signaling pathway, whereas 9B8 suppressed the expression of these genes. Thus, 9B8 effectively mitigates ACLT-induced osteoarthritis in rats by modulating the HIF-1 signaling pathway, thereby inhibiting overexpression involved in glycolysis.These results collectively indicate that 9B8 is a promising novel drug for the prevention and treatment of OA.

Abstract Copper‐catalyzed C─H oxygenation has drawn considerable attention in mechanistic studies. However, a comprehensive investigation combining radical pathways with a metal‐catalytic cycle is challenged by the intricate organic radicals and metallic intermediates. Herein, an online coupled EPR/UV–vis/near‐IR detecting method is developed to simultaneously monitor both reactive radical species and copper complex intermediates during the reaction. Focusing on copper‐catalyzed phenol oxygenation with cumene hydroperoxide, the short‐lived alkylperoxyl radical (EPR signal at g = 2.0143) as well as the unexpected square planar Cu(II)‐alkoxyl radical complex (near‐IR signal at 833 nm) are unveiled during the reaction, in addition to the observable phenoxyl radical in EPR, quinone product in UV–vis, and Cu(II) center in EPR. With a comprehensive picture of diverse intermediates evolving over the same timeline, a novel Cu(I)/Cu(II) proposed relay‐catalyzed sequential radical pathway. In this sequence, Cu(II) activates hydroperoxide through Cu(II)‐OOR into the alkylperoxide radical, while the reaction between Cu(I) and hydroperoxide leads to Cu(II)(•OR)OH with high H‐atom abstracting activity. These results provide a thorough understanding of the Cu(I)/Cu(II) relay catalysis for phenol oxygenation, setting the stage for mechanistic investigations into intricate radical reactions promoted by metallic complexes.

Glycogen Storage Disease Type VII (GSD VII) is a rare glycogen metabolism disorder resulting from mutations in the PFKM gene, inherited in an autosomal recessive manner. It is characterized by exercise intolerance, muscle cramps, myoglobinuria, compensatory hemolysis, and later onset de novo myasthenia and mild myopathy, contributing to its clinical heterogeneity and diagnostic challenges. Here, we report a rare case of a 17-year-old Chinese woman exhibiting substantial muscle weakness and compensated hemolysis. Muscle biopsies showed glycogen deposition, and blood tests showed hyperuricemia and significantly elevated creatine kinase. Whole genome sequencing (WGS) and whole exome sequencing (WES) identified two compound heterozygous mutations in the PFKM (NM_000289.6) gene: c.626G>A and c.1376G>A in exons 7 and 15, respectively. According to the clinical presentation, diagnostic examination, and WES results, the patient was finally diagnosed with GSDVII. The discovery of these two new PFKM mutations expands the genetic spectrum, and understanding the clinical manifestations of these mutations is critical to preventing diagnostic delays and timely intervention and treatment.

Background: Osteoarthritis (OA) is a common chronic joint disease. This study aimed to investigate possible OA diagnostic biomarkers and to verify their significance in clinical samples. Methods: We exploited three datasets from the Gene Expression Omnibus (GEO) database, serving as the training set. We first determined differentially expressed genes and screened candidate diagnostic biomarkers by applying three machine learning algorithms (Random Forest, Least Absolute Shrinkage and Selection Operator logistic regression, Support Vector Machine-Recursive Feature Elimination). Another GEO dataset was used as the validation set. The test set consisted of RNA-sequenced peripheral blood samples collected from patients and healthy donors. Blood samples and chondrocytes were collected for quantitative real-time PCR to confirm expression levels. Receiver operating characteristic curves were generated for individual and combined biomarkers. Results: In total, 251 DEGs were screened, where B3GALNT1, SCRG1 and ZNF423 were screened by all three algorithms. The area under the curve (AUC) of various biomarkers in our test set did not reach as high as that in public datasets. GRB10 exhibited highest AUC of 0.947 in the training set but 0.691 in our test set, while the favorable combined model comprising B3GALNT1, GRB10, KLF9 and SCRG1 demonstrated an AUC of 0.986 in the training set, 1.000 in the validation set and 0.836 in our test set. Conclusion: We identified a combined model for early diagnosis of OA that includes B3GALNT1, GRB10, KLF9 and SCRG1. This finding offers new avenues for further exploration of mechanisms underlying OA.

Background: Observational studies have reported associations between air pollutants and brain imaging-derived phenotypes (IDPs); however, whether this relationship is causal remains uncertain. Methods: We conducted bidirectional two-sample Mendelian randomization (MR) analyses to explore the causal relationships between 5 types of air pollutants (N=423,796 to 456,380 individuals) and 587 reliable IDPs (N=33,224 individuals). Two-step MR was also conducted to assess whether the identified effects are mediated through the modulation of circulating cytokines (N=8293). Results: We found genetic evidence supporting the association of nitrogen oxides (NOx) with mean intra-cellular volume fraction (ICVF) in the left uncinate fasciculus (IVW β=-0.42, 95 % CI −0.62 to −0.23, P=1.51×10−5) and mean fractional anisotropy (FA) in the left uncinate fasciculus (IVW β=-0.42, 95 % CI −0.62 to −0.21, P=4.89×10−5). In further two-step MR analyses, we did not find evidence that genetic predictions of any circulating cytokines mediated the association between NOx and IDPs. Conclusion: This study provides evidence for the association between air pollutants and brain IDPs, emphasizing the importance of controlling air pollution to improve brain health.

As the physical power information system undergoes continual advancement, mobile energy storage has become a pivotal component in the planning and orchestration of multi-component distribution networks. Furthermore, the evolution and enhancement of big data technologies have significantly contributed to enhancing the rationality and efficacy of various distribution network planning and layout approaches. At the same time, multi-distribution networks have also confronted numerous network attacks with increasing probability and severity. In this study, a Petri net is initially employed as a modeling technique to delineate the network attack flow within the distribution network. Subsequently, the data from prior network attacks are consolidated and scrutinized to evaluate the vulnerability of the cyber-physical system (CPS), thereby identifying the most critical network attack pattern for a multi-component distribution network. Following this, the defender–attacker–defender planning methodology is applied for scale modeling, incorporating rapidly evolving mobile energy storage into the pre-layout, aiming to mitigate the detrimental impact of network attacks on the power grid. Ultimately, the column and constraint generation (C&CG) algorithm is utilized to simulate and validate the proposed planning strategy in a 33-node system with multiple control groups established to demonstrate the viability and merits of the proposed strategy.

BackgroundSarcopenia is linked to an unfavorable prognosis in individuals with rheumatoid arthritis (RA). Early identification and treatment of sarcopenia are clinically significant. This study aimed to create and validate a nomogram for predicting sarcopenia risk in RA patients, providing clinicians with a reliable tool for the early identification of high-risk patients.MethodsPatients with RA diagnosed between August 2022 and January 2024 were included and randomized into training and validation sets in a 7:3 ratio. Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis and multifactorial logistic regression analysis were used to screen the risk variables for RA-associated muscle loss and to create an RA sarcopenia risk score. The predictive performance and clinical utility of the risk model were evaluated by plotting the receiver operating characteristic curve and calculating the area under the curve (AUC), along with the calibration curve and clinical decision curve (DCA).ResultsA total of 480 patients with RA were included in the study (90% female, with the largest number in the 45–59 age group, about 50%). In this study, four variables (body mass index, disease duration, hemoglobin, and grip strength) were included to construct a nomogram for predicting RA sarcopenia. The training and validation set AUCs were 0.915 (95% CI: 0.8795–0.9498) and 0.907 (95% CI: 0.8552–0.9597), respectively, proving that the predictive model was well discriminated. The calibration curve showed that the predicted values of the model were basically in line with the actual values, demonstrating good calibration. The DCA indicated that almost the entire range of patients with RA can benefit from this novel prediction model, suggesting good clinical utility.ConclusionThis study developed and validated a nomogram prediction model to predict the risk of sarcopenia in RA patients. The model can assist clinicians in enhancing their ability to screen for RA sarcopenia, assess patient prognosis, make early decisions, and improve the quality of life for RA patients.

BackgroundThis study aimed to investigate the clinical characteristics of pediatric patients hospitalized with community-acquired pneumonia (CAP) and concomitant cytomegalovirus (CMV) infection.MethodsThis cross-sectional study enrolled consecutive pediatric patients admitted with CAP who tested positive for CMV DNA in bronchoalveolar lavage fluid (BALF). Flexible fiberoptic bronchoscopy was performed when routine treatment for CAP proved ineffective. The study participants were further stratified into two groups based on CMV serological test results: recent CMV infection group and CMV replication group. Clinical characteristics were compared between these two groups.ResultsAmong 124 patients aged 1–11 months included in this study, 80 (64.5%) patients were categorized as having recent CMV infection, and 44 (35.5%) tested positive for CMV replication. Co-infection with other pathogens was detected more frequently in the CMV replication group (n = 29, 65.9%) than in the recent CMV infection group (n = 35, 43.7%; P = 0.018). Patients with recent CMV infection were younger and exhibited higher levels of alanine transaminase (ALT) and aspartate aminotransferase compared to those with CMV replication (all P

ObjectiveThe causal relationship between type 2 diabetes mellitus (T2DM) and osteoporosis (OS) remains unclear. This study aims to investigate the causal relationship and explore the potential metabolic mechanism and its mediating role.MethodsWe conducted a comprehensive study, gathering data on 490,089 T2DM patients from the genome-wide association study (GWAS) database and selecting OS data from FinnGen and MRC-IEU sources, including 212,778 and 463,010 patients, respectively, for causal analysis. Simultaneously, we explored the potential roles of three obesity traits and 30 metabolic and inflammation-related mediating variables in the causal relationship.ResultsThere is a strong causal relationship between T2DM and OS. The data from our two different database sources appeared in the same direction, but after correcting for body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR), the direction became the same. T2DM may increase the risk of OS [odds ratio (OR) > 1.5, p < 0.001]. Steiger’s test results show that there is no reverse causality. No risk factors related to glycolipid metabolism, amino acid metabolism, and inflammation were found to mediate the causal relationship.ConclusionThis study’s findings indicate a robust causal relationship between T2DM and OS, influenced by relevant factors such as BMI. Our results shed light on the pathogenesis of OS and underscore the importance for clinicians to treat metabolic disorders to prevent osteoporosis.

Colorectal cancer (CRC) is one of the most common gastrointestinal malignancies in the world. With the rapid pace of life and changes in diet structure, the incidence and mortality of CRC increase year by year posing a serious threat to human health. As the most complex and largest microecosystem in the human body, intestinal microecology is closely related to CRC. It is an important factor that affects and participates in the occurrence and development of CRC. Advances in next-generation sequencing technology and metagenomics have provided new insights into the ecology of gut microbes. It also helps to link intestinal flora with CRC, and the relationship between intestinal flora and CRC can be continuously understood from different levels. This paper summarizes the relationship between intestinal flora and CRC and its potential role in the diagnosis of CRC providing evidence for early screening and treatment of CRC.

Purkinje cell cytoplasmic antibody type 2 (PCA-2), identified in 2000, targets the widely distributed microtubule-associated protein 1B in the central and peripheral nervous systems, leading to diverse clinical phenotypes of neurological disorders. We report two cases of PCA-2-associated encephalitis, each presenting with distinct onset forms and clinical manifestations, thereby illustrating the phenotypic variability of PCA-2-related diseases. The first patient was diagnosed with PCA-2-associated autoimmune cerebellitis and undifferentiated small cell carcinoma with metastasis in mediastinal lymph nodes of unknown primary origin. The second patient was diagnosed with PCA-2-associated limbic encephalitis. Our findings underscore the superior sensitivity of positron emission tomography-computed tomography over brain magnetic resonance imaging in the early detection of PCA-2-associated encephalitis. Given the high risk of relapse and suboptimal response to traditional immunotherapy in PCA-2-related neurological disorders, this study highlights the need for a deeper understanding of their pathogenesis to develop more effective treatments to control symptoms and improve patient prognosis.

Parkinson's disease (PD) is a severe neurodegenerative disease that disturbs human health. In the laboratory researches about PD, the mice model induced by intraperitoneal injection of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) was widely used. However, there has been controversy about the model effectiveness to simulate PD symptoms and pathology, and the time-varying development of behavioral and pathological characteristic after MPTP treatment remains unclear. In order to solve these problems, we designed a series of experiments to evaluate this PD model at different time points. We constructed the subacute PD mouse model by intraperitoneal injection of MPTP for 5 consecutive days. The rotarod test, open field test and the immunohistochemical staining of tyrosine hydroxylase were conducted at −5, 1, 5, 7, 14, 21 and 28 days after the last injection of MPTP. The results showed that 5 days after the last MPTP administration, typical motor disorders with significant balance function damage in rotarod test began to appear and remained stable throughout the entire experiment. Simultaneously, we also observed the loss of tyrosine hydroxylase (TH) positive cells in the substantia nigra compacta and reduction of TH content in the striatum but this pathological change in the substantia nigra compacta reversed 21 days after injection. Besides, the spontaneous movement of mice in open field test remained unchanged by MPTP. This research indicated the time-dependence of MPTP neurotoxicity that impair the motor function and histological features and confirmed the symptom occurrence time after MPTP injection, which provides a reference for the future research about MPTP-induced PD.

The lymphatic system, alongside blood circulation, is crucial for maintaining bodily equilibrium and immune surveillance. Despite its importance, lymphatic imaging techniques lag behind those for blood circulation. Fluorescence imaging, particularly in the near-infrared-II (NIR-II) region, offers promising capabilities with centimeter-scale tissue penetration and micron-scale spatial resolution, sparking interest in visualizing the lymphatic system. Although indocyanine green (ICG) has been approved by the Food and Drug Administration (FDA) for use as a near-infrared-I (NIR-I) region fluorescent dye, its limitations include shallow penetration depth and low signal-to-noise ratio. Research suggests that ICG’s fluorescence emission tail in the second near-infrared window holds potential for high-quality NIR-II imaging. However, challenges like short circulation half-life and concentration-dependent aggregation hinder its wider application. Here we developed HA@ICG nanoparticles (NPs), a superior ICG-based NIR-II fluorescent probe with excellent biocompatibility, prolonging in vivo imaging, and enhancing photostability compared to ICG alone. Leveraging LYVE-1, a prominent lymphatic endothelial cell receptor that binds specifically to hyaluronic acid (HA), our nanoprobes exhibit exceptional performance in targeting lymphatic system imaging. Moreover, our findings demonstrate the capability of HA@ICG NPs for capillary imaging, offering a means to assess local microcirculatory blood supply. These compelling results underscore the promising potential of HA@ICG NPs for achieving high-resolution bioimaging of nanomedicines in the NIR-II window.

This paper presents a structure for designing Junction Termination Extension (JTE) in Silicon Carbide (SiC) power devices, particularly for Schottky Barrier Diodes (SBD). The P-type island composite multi-step JTE configuration has been developed by optimizing the number, length, and thickness of JTE steps. The JTE with step number of 4 and step length of 8 μm (SBD-n4L8) achieved a breakdown voltage of 1626 V at the same drift layer thickness of 10 μm, outperforming other step-based JTE structures. At reverse voltage of 1200 V, the SBD-n4L8 demonstrates a decrease in reverse leakage current with a uniform step-like current distribution profile. Subsequent analysis of the underlying mechanisms showed that, with step thickness of 2 μm, the SBD-n5L8 located at the corner and edge of the terminal region significantly reduced the peak electric field by more than 12.6 %.

Abstract In the study of singularly perturbed boundary problems with turning points, the solution undergoes sharp changes near these points and exhibits various interior phenomena. We employ the matching asymptotic expansion method to analyze and solve a singularly perturbed boundary and interior layers problem with multiple turning points, resulting in a composite expansion that fits well with the numerical solution. The solution demonstrates a strong association with special functions, which is verified by the theory of differential inequalities.

Abstract Despite prolonged surveillance and interventions, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza viruses continue to pose a severe global health burden. Thus, we developed a chimpanzee adenovirus-based combination vaccine, AdC68-HATRBD, with dual specificity against SARS-CoV-2 and influenza virus. When used as a standalone vaccine, intranasal immunization with AdC68-HATRBD induced comprehensive and potent immune responses consisting of immunoglobin (Ig) G, mucosal IgA, neutralizing antibodies, and memory T cells, which protected the mice from BA.5.2 and pandemic H1N1 infections. When used as a heterologous booster, AdC68-HATRBD markedly improved the protective immune response of the licensed SARS-CoV-2 or influenza vaccine. Therefore, whether administered intranasally as a standalone or booster vaccine, this combination vaccine is a valuable strategy to enhance the overall vaccine efficacy by inducing robust systemic and mucosal immune responses, thereby conferring dual lines of immunological defenses for these two viruses.