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Heat stress exposure in intermittent heat waves and subsequent exposure during war theaters pose a clinical challenge that can lead to multi-organ dysfunction and long-term complications in the elderly. Using an aged mouse model and high-throughput sequencing, this study investigated the molecular dynamics of the liver-brain connection during heat stress exposure. Distinctive gene expression patterns induced by periodic heat stress emerged in both brain and liver tissues. An altered transcriptome profile showed heat stress-induced altered acute phase response pathways, causing neural, hepatic, and systemic inflammation and impaired synaptic plasticity. Results also demonstrated that proinflammatory molecules such as S100B, IL-17, IL-33, and neurological disease signaling pathways were upregulated, while protective pathways like aryl hydrocarbon receptor signaling were downregulated. In parallel, Rantes, IRF7, NOD1/2, TREM1, and hepatic injury signaling pathways were upregulated. Furthermore, current research identified Orosomucoid 2 (ORM2) in the liver as one of the mediators of the liver-brain axis due to heat exposure. In conclusion, the transcriptome profiling in elderly heat-stressed mice revealed a coordinated network of liver-brain axis pathways with increased hepatic ORM2 secretion, possibly due to gut inflammation and dysbiosis. The above secretion of ORM2 may impact the brain through a leaky blood-brain barrier, thus emphasizing intricate multi-organ crosstalk.

Abstract Drug-resistant epilepsy with frequent seizures are considered to undergo surgery to become seizure-free, but seizure-free rates have not dramatically improved, partly due to imprecise intervention locations. To address this clinical need, we construct effective connectivity to reveal epilepsy brain dynamics. Based on the propagation path captured by the high order effective connectivity, calculate the control centrality evaluation scheme of the excised area. We used three datasets: simulation dataset, clinical dataset, and public dataset. The epileptogenic propagation network was quantified by calculating high-order effective connection to obtain accurate propagation path, based on this, combined with the outdegree index for virtual resection. By removing electrodes and recalculating control centrality, we quantify each electrode or region’s control centrality to evaluate the virtual resection scheme. Three datasets obtained consistent results. We track the accurate propagation path and find the obvious inflection points occurring during the excision process. The minimum intervention targets were obtained by comparing different schemes without recurrence. The clinical data with multiple seizures found that after resection, the brain reaches a stable state and is less likely to continue spreading. By quantitative analysis of control centrality to evaluate the possible excision scheme, finally we obtain the best intervention area for epilepsy, which assist in developing surgical plans.

Abstract Thyroid hormones (THs) may affect chronic thyrotoxic myopathy (CTM). The relationship between TH sensitivity and CTM is inconsistent. We aimed to investigate the associations between TH sensitivity and the risk of CTM and to screen potential CTMs with strength and function tests. A total of 162 Chinese patients (36.58% men) with Graves’ disease were enrolled and divided into CTM and non-CTM groups. TH and sensitivity indices were measured. Muscle power and function were assessed by grip, upper-limb fatigue (ULFT), lower-limb fatigue (LLFT), and squat-up (SUT) tests, and walking pace. Association between sensitivity to TH indices and the risk of developing CTM was assessed via multivariate logistic regression. The diagnostic effectiveness of muscle power and function for predicting CTM was evaluated via receiver operating characteristic (ROC) curves. Thyroid feedback quantile-based index FT3 (TFQIFT3) and the parametric TFQIFT3 (PTFQIFT3), TFQIFT4, and PTFQIFT4 were positively associated with CTM risk by using inverse probability of treatment weighting multivariate logistic regression. For each 1-SD increase in TFQIFT3 and PTFQIFT3, TFQIFT4 and PTFQIFT4, the odds ratios for CTM were 1.67 (95% CI = 1.17–2.48) ,1.64 (95% CI = 1.51–2.93), 1.60 (95%CI = 1.12–2.32), 1.58 (95%CI = 1.11–2.30), respectively. LLFT and SUT best predicted male/female CTM, respectively (AUC = 0.89/0.85). In Graves’ disease patients, TH sensitivity is associated with CTM development, which can be predicted by SUT and LLFT results.

Abstract As one of the two main histologic subtypes of gastric cancer (GC), diffuse-type gastric cancer (DGC) containing poorly cohesive gastric carcinoma (PCC) components has a worse prognosis and does not respond well to typical therapies. Despite the large number of studies revealing the complex pathogenic network of DGC, the molecular heterogeneity of DGC is still not fully understood. We obtained single-cell RNA-seq data and bulk data from the tumor immune single cell hub, the public gene expression omnibus, and the cancer genome atlas databases. A series of bioinformatics analyses were performed using R software. Immunofluorescence staining, hematoxylin and eosin staining, western blot, and functional experiments were used for experimental validation. Caudin-3, -4 and -7 were lowly expressed in DGC and their expression levels were further reduced in PCC. The PCC components were mainly located in the deeper layers of the DGC and had a high level of hypoxic Wnt/β-catenin signaling and stemness. We further identified Insulin Like Growth Factor Binding Protein 7 (IGFBP7) as a marker for PCC components in the deep layer. IGFBP7 is stimulated by hypoxia and promotes cancer cell invasiveness and reduced claudin expression. In addition, programmed death-1 ligand (PD-L1) was specifically expressed in the deep layer, reflecting deep layer-specific immunosuppression. The PCC components are predominantly situated in the deeper layers of DGC. Initial molecular characterization of these PCC components revealed distinct features, including low expression of claudin-3, -4, and -7, high expression of IGFBP7, and the presence of PD-L1. These molecular traits may partially account for the pronounced tumor heterogeneity observed in GC.

Abstract Acute pancreatitis (AP) is an inflammatory disease of the pancreas. Despite of a steadily increasing in morbidity and mortality, there is still no effective therapy. Gut microbial dysbiosis and its derived-metabolites disorder have been shown to play an important role in the development of AP, however, little is known regarding the crosstalk between gut microbiota and metabolites. In this study, we assessed the alterations in gut microbiota and metabolites by constructing three AP mouse models by means of metagenomic and metabolomic sequencing, and further clarified their relationship by correlation analysis. The results revealed that each model exhibited unique flora and metabolite profiles. KEGG analysis showed that the differential flora and metabolite-enriched pathway functions were correlated with lipid metabolism and amino acid metabolism. Moreover, two core differential bacterial species on Burkholderiales bacterium YL45 and Bifidobacterium pseudolongum along with eleven differential metabolites appeared to exert certain effects during the course of AP. In conclusion, further exploration of the crosstalk between microbiota and derived metabolites may provide novel insights and strategies into the diagnosis and treatment of AP.

Abstract Prenatal exposure to perfluoroalkyl and polyfluoroalkyl substances (PFASs) may cause adverse birth outcomes. Thyroid hormones may play a key role in mediating the effects of PFAS. We enrolled 374 mother-infant pairs from the Ezhou birth cohort study between 2019 and 2020. Eight PFASs and six thyroid hormones were measured in maternal serum during the first trimester of pregnancy. Neonatal growth metrics, including birth weight, length, head circumference, and gestational age, were acquired. Multivariate linear regression was performed to determine the associations between maternal serum PFAS and thyroid hormone levels and birth outcomes and a mediation analysis was also conducted. Except for perfluoroheptanoic acid (41.2%), the other seven PFAS detection rates were more than 85%, and the highest median concentration was observed for PFOSA with levels of 5.21 ng/mL. After controlling for typical confounders, we observed a decrease in birth length (cm) with increasing serum concentrations of perfluorononanoic acid (PFNA) (β = -0.54; 95% CI = -1.0, -0.08) and perfluorohexane sulfonate (PFHxS) (β = -0.64; 95% CI = -0.86, -0.42). Additionally, a decrease in birth head circumference was observed with increasing concentrations of perfluorooctanote (PFOA) (β = -0.73, 95% CI = -1.19, -0.27) and PFHxS (β = -0.30; 95% CI = -0.53, -0.07). Maternal free triiodothyronine (FT3) mediated 36.7% of the negative association between PFNA and birth length, and free thyroxine (FT4) mediated 30.8% of the effect of PFOA on head circumference. When performing stratified analysis by infant sex, the associations might differ between boys and girls. Our study suggested prenatal exposure to some PFASs was negatively associated with birth length and circumference, and FT3 and FT4 may partly mediate the association.

Abstract The emergence of nanogenerators, which have the ability to capture mechanical energy from the environment and to collect and transmit tiny energy, is rapidly becoming a hot research topic. The performance of electrode materials is the key to the efficiency of nanogenerators. Covalent organic skeletons (COFs), a class of crystalline organic porous materials with the advantages of large specific surface area, high porosity, tunable structure, and flexible tailorability, have very significant advantages in being used as nanogenerator materials. In this paper, we synthesised two COF materials to investigate the effect of the introduction of active metals on the friction power generation performance of COFs without changing their topology, COF-2 containing zinc ions is capable of generating a short-circuit current of 107.5 µA during friction. The porous structure increases the effective contact area to form a larger charge density, and the introduction of metal ions can accelerate the charge separation and transport. The two bidirectional synergistic effects of the materials significantly improve the output performance of the nanogenerator, and a simple and efficient method is explored for the enhancement of the output performance of COF-based triboelectric nanogenerators.

Abstract Based on the characteristics of Kummell’s disease (KD) and related anatomical structures of the thoracolumbar spine, a novel bone cement screw system has been designed to effectively avoid the cement loosening and displacement. This experiment aimed to assess the biological effects of the novel bone cement screw system in KD on fresh cadaveric thoracolumbar spine specimens, thereby discussing its potential application value and providing a foundation for clinical implementation. This study employed a total of 50 fresh female adult cadaver specimens. Each specimen underwent extraction of the T12 to L2 segment followed by the creation of an artificial KD model at the L1 segment and subsequent establishment of five distinct types of bone cement repair models. Model A represents the percutaneous vertebroplasty (PVP) model, Model B combines PVP with unilateral percutaneous pediculoplasty (PPP), Model C combines PVP with bilateral PPP, Model D introduces the novel bone cement screw combined with unilateral PVP, and Model E combines the novel screw with bilateral PVP, each group consists of 10 specimens. Subsequently, the six-axis spine robot was employed to execute cement three-dimensional biomechanical strength tests in six directions, including anterior flexion and posterior extension, left and right lateral bending, as well as left and right rotation. The novel bone cement screw, whether used unilaterally or bilaterally in combination with the PVP model, exhibits significantly reduced bone cement mobility and superior biomechanical stability during anterior flexion, posterior extension, left lateral bending, and right lateral bending (P 0.05).When comparing the novel bone cement screw combined with PVP unilaterally and bilaterally, no statistically significant difference was observed in the stability of bone cement across all six directions of motion (P>0.05). To conclude, this novel bone cement bridging screw system exhibits superior biomechanical stability compared to commonly used treatments. Furthermore, both unilateral and bilateral implementations of the novel bone cement screw system yield without significant differences observed. These findings present a reliable and innovative approach for clinical management of KD.

Abstract Accurate prediction of drug-target interactions (DTIs) is crucial for advancing drug discovery and repurposing. Computational methods have significantly improved the efficiency of experimental predictions for drug-target interactions in Western medicine. However, accurately predicting the complex relationships between Chinese medicine ingredients and targets remains a formidable challenge due to the vast number and high heterogeneity of these ingredients. In this study, we introduce the CWI-DTI method, which achieves high-accuracy prediction of DTIs using a large dataset of interactive relationships of drug ingredients or candidate targets. Moreover, we present a novel dataset to evaluate the prediction accuracy of both Chinese and Western medicine. Through meticulous collection and preprocessing of data on ingredients and targets, we employ an innovative autoencoder framework to fuse multiple drug (target) topological similarity matrices. Additionally, we employ denoising blocks, sparse blocks, and stacked blocks to extract crucial features from the similarity matrix, reducing noise and enhancing accuracy across diverse datasets. Our results indicate that the CWI-DTI model shows improved performance compared to several existing state-of-the-art methods on the datasets tested in both Western and Chinese medicine databases. The findings of this study hold immense promise for advancing DTI prediction in Chinese and Western medicine, thus fostering more efficient drug discovery and repurposing endeavors. Our model is available at https://github.com/WANG-BIN-LAB/CWIDTI .

Abstract Rejection seriously affects the success of kidney transplantations. However, the molecular mechanisms underlying this rejection remain unclear. The GSE21374 and GSE36059 datasets were downloaded from the Gene Expression Omnibus (GEO) database. Next, the Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm was used to infer the proportions of 22 immune cells. Moreover, infiltrating immune cell-related genes were identified using weighted gene co-expression network analysis (WGCNA), and enrichment analysis was conducted to observe their biological functions. Extreme Gradient Boosting (XGBoost) and Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression algorithms were used to screen hub genes. Quantitative real-time PCR was conducted to verify the number of immune cells and hub gene expression levels. The rejection and non-rejection groups showed significantly different distributions (P

Abstract This paper aims to examine the potential link between maternal COVID-19 infection during pregnancy and the increased risk of congenital heart disease (CHD) in newborns. A comparative analysis was conducted involving two groups: mothers infected with COVID-19 during pregnancy and a control group. Data on maternal characteristics, pregnancy-related complications, and newborn outcomes were collected and analyzed. Additionally, the annual incidence rates of CHD from 2020 to 2023 were evaluated to assess trends over time. No significant differences were found between the COVID-19 cases and the control group in terms of maternal age, BMI, gravidity, parity, use of assisted reproductive technology, adverse obstetric history, or complications during pregnancy, including diabetes mellitus, preeclampsia, and thyroid abnormalities. For newborn outcomes, there were no significant differences in sex distribution, rate of cesarean delivery, Apgar scores, or birth weight. However, a significantly higher prevalence of cardiac ultrasound abnormalities was observed in the COVID-19 group (10.08%) compared to the control group (4.13%, p = 0.012). Further analysis revealed that the majority of cardiac abnormalities in the COVID-19 group occurred in mothers infected before 8 weeks of pregnancy. The annual incidence rates of CHD showed a significant increase during the COVID-19 pandemic, with the highest rate in 2023 (5.46%) compared to previous years. Maternal COVID-19 infection during pregnancy may adversely affect the development of the newborn’s heart. This could be due to the inflammatory response caused by the viral infection or other pathological processes. The findings underscore the importance of vigilant prenatal care and early detection of cardiac abnormalities during the pandemic and suggest the need for further research to explore potential mechanisms and intervention strategies.

Abstract This study aimed to investigate the clinical outcomes of local muscle or myocutaneous flap transfer for emergent repair of Gustilo IIIB open tibiofibular fractures. This retrospective case series study included patients with Gustilo IIIB open tibiofibular fractures treated by local muscle or myocutaneous flap transfer in Weifang People’s Hospital between May 2016 and April 2021. Fifteenpatients (11 males aged 19–72 years) were included. The follow-up ranged from 8 to 24 months. The ranges of bone healing time and wound healing time were 6–17 months and 1–3 weeks, respectively. The length of hospital stay was 26 days (11–50 days). All patients reported acceptable functional recovery and satisfactory leg appearance, with Johner-Wruhs scores of excellent, good, and fair in 10, four, and one patients, respectively. The excellent-good rate was 93.3%. The complications included one case of infection and one case of nonunion. In conclusion, local muscle or myocutaneous flap transfer for emergent repair of Gustilo IIIB open tibiofibular fractures may be useful in providing adequate soft tissue coverage and fracture healing with low complication and infection rates.

Abstract We investigate the propagation characteristics of transverse electric (TE) and transverse magnetic (TM) modes in a semiconductor quantum plasma-filled coaxial waveguide with a Piet Hein cross-section. The unique geometry of the Piet Hein cross-section offers intriguing possibilities for tailoring modal properties and exploiting novel nonlinear phenomena. Using analytical and numerical methods, we unveil the non-monochromatic behaviour of TE and TM modes, characterized by distinct peaks and troughs in their field components. The $$E_{z}$$ E z component of the TM mode exhibits a suppressed field within the central core and higher concentration in the cladding region, potentially minimizing energy loss within the waveguide. The $$E_{\rho }$$ E ρ component exhibits pronounced oscillations near the waveguide boundaries, suggesting constructive and destructive interference patterns. The $$E_{\xi }$$ E ξ component displays a non-monotonic behaviour with multiple pits and bumps, highlighting the interplay between the TE mode, the Piet Hein geometry, and the semiconductor quantum plasma properties. The $$B_{\rho }$$ B ρ component of the TM mode exhibits a non-monochromatic behaviour with multiple maxima and minima, attributed to the complex interactions between propagating waves with different phase shifts. The $$B_{\xi }$$ B ξ component exhibits a non-uniform distribution with distinct pits and bumps, with a resurgence towards the waveguide edges potentially due to higher-order mode contributions and local field enhancement effects. Our findings pave the way for the development of novel photonic devices with enhanced functionalities based on Piet Hein semiconductor quantum plasma waveguides.

Abstract After the COVID-19 pandemic, fever clinics urgently require rapid nucleic acid tests to enhance their capacity for timely pathogen detection. This study evaluated the analytical performance and clinical utility of the Flash10 SARS-CoV-2 point-of-care test (Flash10 POCT) for detecting SARS-CoV-2 in patients with fever in the adult fever clinic in Beijing Tsinghua Changgung Hospital from August 1 to August 30, 2023. The analytical performance and clinical utility of the Flash10 POCT for detecting SARS-CoV-2 were assessed in 125 patients with fever syndrome in the adult fever clinic. The Flash10 POCT demonstrated an analytical precision of 3.1% for the Ct values of the ORF1ab gene and 2.9% for the Ct values of the N gene in SARS-CoV-2 nucleic acid testing. Furthermore, the Flash10 POCT demonstrated a lower limit of detection (LoD) of 100 copies/mL, with no detected aerosol contamination leakage. Of the 125 patients (median age 61.9 years, 52% male and 48% female), both the Flash10 POCT and RT-PCR tests yielded positive results for 100 patients and negative results for 25 patients (Fisher’s exact test, p

Abstract Cell motility increases the fitness of bacterial cells. Previous research focused on the transcriptional regulator CdsR, which represses cellular autolysis and promotes spore formation in Bacillus thuringiensis. However, the targets of CdsR are mostly unknown. Here, we reported a new function of CdsR in regulating cell motility. Mutation of cdsR results in increase of cell mobility, and a number of related genes were upregulated compared to wild type HD73. Thus, we investigated the transcription of the fla/che gene cluster, which involves in cell mobility and comprises eight operons/genes, including motAB1, cheY-yrhK, lamB-cheR, yaaR-fliG2, cheV-mogR, hag1, hag2, and yjbJ-flgG. Additionally, the motAB2 operon was discovered, which consists of homologs genes motA2 and motB2 that are like motA1 and motB1. Through promoter-lacZ fusion assays and EMSA experiments, it was discovered that CdsR directly regulates the motAB1, cheY-yrhK, lamB-cheR, yaaR-fliG2, cheV-mogR, hag1, hag2, yjbJ-flgG, and motAB2 operons by binding to their promoter regions. Importantly, it was confirmed that CdsR is a metalloregulator and the binding to promoter can be inhibited by Cu (II) ions. This research enhances our understanding of the regulation of cell mobility in B. thuringiensis.

Abstract Ferroptosis is a form of regulated cell death, characterized by excessive iron-dependent lipid peroxidation. Biochemically, ferroptosis can be selectively induced by erastin through glutathione depletion or through inhibition of glutathione peroxidase 4 by RSL3, which leads to accumulation of cytotoxic lipid reactive oxygen species (ROS). Protein disulfide isomerase (PDI) was recently shown to mediate erastin/RSL3-induced ferroptosis and thus also become a new target for protection against chemically-induced ferroptosis. The present study aims to identify endogenous compounds that can protect against erastin/RSL3-induced ferroptotic cell death. We find that 2-hydroxyestrone, 2-hydroxyestradiol, 4-hydroxyestrone and 4-hydroxyestradiol, four major endogenous catechol estrogens, are effective inhibitors of PDI, and can strongly protect against chemically-induced ferroptotic cell death in cultured HT22 mouse hippocampal neuronal cells. The CETSA assay showed that these catechol estrogens can bind to PDI in live cells. PDI knockdown attenuates the protective effect of these catechol estrogens against chemically-induced ferroptosis. Mechanistically, inhibition of PDI’s catalytic activity by catechol estrogens abrogates erastin/RSL3-induced dimerization of nitric oxide synthase, thereby preventing the subsequent accumulation of cellular nitric oxide, ROS and lipid-ROS, and ultimately ferroptotic cell death. In addition, joint treatment of cells with catechol estrogens also abrogates erastin/RSL3-induced upregulation of nitric oxide synthase protein levels, which also contributes to the cytoprotective effect of the catechol estrogens. In conclusion, the present study demonstrates that the catechol estrogens are protectors of HT22 neuronal cells against chemically-induced ferroptosis, and inhibition of PDI’s catalytic activity by these estrogens contributes to a novel, estrogen receptor-independent mechanism of cytoprotection.

Abstract The leafminer Liriomyza trifolii causes severe economic damage on ornamental and horticultural crops in China. Rapid cold hardening (RCH) is a phenomenon where cold tolerance in insects can be significantly enhanced after a short-term acclimation to low temperatures. In this study, the regulation of transcription in response to cold hardening was investigated in L. trifolii adults, and fatty acids and cryoprotectant levels were measured. The composition of fatty acids changed after RCH treatment, and glucose and trehalose levels showed significant accumulation after acclimation, thus indicating that changes in fatty acids and cryoprotectants contribute to RCH in L. trifolii. RNA-seq was used to analyze transcriptional regulation after a 4 h hardening period and showed that differentially expressed genes clustered in multiple metabolic pathways, which indicates the importance of transcriptional regulation in RCH. This study expands our knowledge of biochemical and transcriptional changes in L. trifolii during cold hardening and provides a basis for further investigations aimed at understanding thermal adaptation in insects.

Abstract Studying the effects of weathering on the mechanical properties and microscopic evolution of weathered granite soil (WGS) is essential for connecting microstructure with macroscopic behavior. This study conducts systematic monotonic and cyclic triaxial tests, along with a series of microscopic tests on WGS samples, to explore the influence of weathering on WGS mechanical properties and the mechanism of granite weathering. Results indicate that both effective internal friction angle and effective cohesion decrease progressively with increased weathering. Completely weathered granite (CWG) exhibits greater dynamic strength compared to granite residual soil (GRS). Additionally, as weathering progresses, quartz fragments are lost, while feldspar and biotite weather to form secondary minerals such as kaolinite and illite, leading to an overall enrichment in aluminum and iron in the granite. Weathering causes structural deterioration of WGS. Finally, the mechanical parameters of WGS and their chemical weathering indices show a coefficient of determination ranging from 60 to 99%. This study helps elucidate the fundamental causes of performance changes in WGS, thereby optimizing engineering design and enhancing disaster prediction accuracy, while providing new research perspectives and experimental evidence for WGS.

Abstract Water quality monitoring of rivers is necessary in order to properly manage their basins so that steps can be taken to control the amount of pollutants and bring them to the allowable level. The ARIMA (autoregressive integrated moving average) model does not consider nonlinear patterns in modeling water quality components. Also, in modeling using the MLP (Multilayer Perceptrons) model, both linear and nonlinear pattern are not controlled equally. Therefore, in the present study, linear time series models (ARIMA), MLP model, and a hybrid model of MLP and ARIMA optimized by a Grasshopper optimization algorithm are used to predict water quality components in the statistical period of 2011–2019. In the proposed hybrid method, the ability of the ARIMA and the MLP model are exploited. Observational water quality data for forecasting time series in the hybrid method include dissolved oxygen, water temperature, and boron over 108 months. Since, the hybrid model is capable of realizing the nonlinear essence of complicated time series, it makes more reliable forecasts. In the hybrid model, the correlation coefficients between the observational data and the predicted values are 0.9 for dissolved oxygen, 0.91 for water temperature, and 0.91 for boron. To compare the three ARIMA, MLP, and hybrid models, the accuracy indices of each model are calculated. The results show that the hybrid model’s higher accuracy compared with the other two models.

Abstract Proteasome inhibition emerges as a promising strategy for cancer prevention. PNO1, pivotal for colorectal cancer (CRC) progression, is involved in proteasome assembly in Saccharomyces cerevisiae. Hence, we aimed to explore the role of PNO1 in proteasome assembly and its up- and down-streams in CRC. Here, we demonstrated that PNO1 knockdown suppressed CRC cells growth, proteasome activities and assembly, as well as CDKN1B/p27Kip1 (p27) degradation. Moreover, p27 knockdown partially attenuated the inhibition of HCT116 cells growth by PNO1 knockdown. The up-stream studies of PNO1 identified miR-326 as a candidate miRNA directly targeting to CDS-region of PNO1 and its overexpression significantly down-regulated PNO1 protein expression, resulting in suppression of cell growth, decrease of proteasome activities and assembly, as well as increasing the stability of p27 in CRC cells. These findings indicated that miR-326 overexpression can suppress CRC cell growth, acting as an endogenous proteasome inhibitor by targeting PNO1.

Abstract Asymptomatic intracranial atherosclerotic stenosis (aICAS) is a major risk factor for cerebrovascular events. The study aims to construct and validate a nomogram for predicting the risk of aICAS. Participants who underwent health examinations at our center from September 2019 to August 2023 were retrospectively enrolled. The participants were randomly divided into a training set and a testing set in a 7:3 ratio. Firstly, in the training set, least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression were performed to select variables that were used to establish a nomogram. Then, the receiver operating curves (ROC) and calibration curves were plotted to assess the model’s discriminative ability and performance. A total of 2563 neurologically healthy participants were enrolled. According to LASSO-Logistic regression analysis, age, fasting blood glucose (FBG), systolic blood pressure (SBP), hypertension, and carotid atherosclerosis (CAS) were significantly associated with aICAS in the multivariable model (adjusted P

Abstract Branched-chain amino acid transaminase 2 (BCAT2) encodes a crucial protein involved in the initial catalysis of branched-chain amino acid (BCAA) catabolism, with emerging evidence suggesting its association with tumor progression. This study explores BCAT2 in a pan-cancer multi-omics context and evaluates its prognostic significance. We utilized a multi-database approach, analyzing cBioPortal for genetic alterations, RNA-Seq data from TCGA and GTEx for expression patterns, and RSEM for transcript analysis. Protein expression and interaction networks were assessed using the Human Protein Atlas, UniProt, and STRING. Prognostic value was determined through Cox regression analysis of TCGA clinical survival data, while immune cell infiltration across various cancers was examined using TCGA data and the TIMER2 platform. Our results revealed that BCAT2 alterations are primarily amplifications and is upregulated in various tumors, correlating with poor survival rates in several tumor types, including GBMLGG, LGG, and UVM. Elevated BCAT2 protein levels were common in pan-cancer, interacting with a range of metabolic enzymes. Additionally, BCAT2 expression significantly influenced CD4+ T cells, CD8+ T cells, and Treg cells infiltration, with varied correlations across cancer types. These findings indicate BCAT2 as a potential biomarker for cancer diagnosis and therapy, potentially regulating key metabolic and immune factors to mediate tumor progression and the microenvironment.

Abstract Inflammation plays a crucial role in cancer development. The neutrophil-to-lymphocyte ratio (NLR), a measure of inflammation, is obtained from a complete blood count. However, little is known about the association between NLR and cancer in the general adult population in the United States. This study aimed to evaluate whether NLR is associated with cancer in American adults. This retrospective cross-sectional study included 28,016 adult participants from the National Health and Nutrition Examination Survey (NHANES) dataset spanning 2005 to 2018. Data on demographics (age, sex, race, marital status, Poverty-Income Ratio, education level), lifestyle factors (smoking, alcohol consumption, body mass index), medical conditions (hypertension, diabetes, cardiovascular disease), and laboratory parameters (hemoglobin, platelet count, alanine aminotransferase, creatinine, albumin, and lactate dehydrogenase), were collected. Logistic regression analysis was used to investigate the research objectives. Of the total 28,016 participants, 2639 had cancer. The mean age was 49.6 ± 17.6 years, and 50% were male. A positive association between NLR and cancer risk was observed after multivariate adjustment (OR = 1.20, 95% confidence interval (CI) = 1.05–1.36, p = 0.006). Similar patterns were observed in subgroup analyses (all p-values for interaction > 0.05). A higher NLR was directly correlated with an increased risk of developing cancer in adults.

Abstract According to the World Health Organization (WHO), pneumonia kills about 2 million children under the age of 5 every year. Traditional machine learning methods can be used to diagnose chest X-rays of pneumonia in children, but there is a privacy and security issue in centralizing the data for training. Federated learning prevents data privacy leakage by sharing only the model and not the data, and it has a wide range of application in the medical field. We use federated learning method for classification, which effectively protects data security. And for the data heterogeneity phenomenon existing in the actual scenario, which will seriously affect the classification effect, we propose a method based on two-end control variables. Specifically, based on the classical federated learning FedAvg algorithm, we modify the loss function on the client side by adding a regular term or a penalty term, and add momentum after the average aggregation on the server side. The federated learning approach prevents the data privacy leakage problem compared to the traditional machine learning approach. In order to solve the problem of low classification accuracy due to data heterogeneity, our proposed method based on two-end control variables achieves an average improvement of 2% and an accuracy of 98% on average, and 99% individually, compared to the previous federated learning algorithms and the latest diffusion model-based method. The classification results and methodology of this study can be utilized by clinicians worldwide to improve the overall detection of pediatric pneumonia.

Abstract Fusing information from LiDAR and cameras can effectively enhance the overall perceptivity of autonomous vehicles in various scenarios. Despite the relatively good results achieved by point-wise fusion and Bird’s-Eye-View (BEV) fusion, they still cannot fully leverage the image information and lack of effective depth information. For any fusion methods, the multi-modal features first need to be concatenated along the channel, and then the fused features are extracted using convolutional layers. However, this type of fusion methods is effective, but too coarse which causes that the fused features cannot pay more attention to the regions with important features and suffer from severe noise. To tackle these issues, we propose in this paper a Dense Projection Fusion (DPFusion) approach. It consists of two new modules: dense depth map guided BEV transform (DGBT) module and multi-modal feature adaptive fusion (MFAF) module. The DGBT module first quickly estimates the depth of each pixel and then projects all image features to the BEV space, making full use of the image information. The MFAF module computes the image weights and point cloud weights for each channel in each BEV grid and then adaptively weights and fuses the image BEV features with the point cloud BEV features. It is worth pointing out that the MFAF module makes the fused features pay more attention to background outline and object outline. Our proposed DPFusion demonstrates competitive results in 3D object detection, achieving a mean Average Precision (mAP) of 70.4 and a nuScenes detection score (NDS) of 72.3 on the nuScenes validation set.

Abstract Male infertility is one of the most common reproductive dysfunctions. Despite oligospermia being a cause of infertility, few studies have been conducted on it. This study aimed to investigate differences in semen metabolic patterns in patients with oligospermia and to identify potential biomarkers associated with oligospermia. Semen samples from oligospermia patients (20 cases) and healthy controls (20 cases) were detected by high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS), and 72 and 89 metabolites were identified as potential markers in positive and negative ion modes, respectively. In addition, the results identified multiple metabolic pathways in patients with oligospermia, such as glycine serine and threonine metabolism, Synthesis and degradation of ketone bodies, Valine, leucine, and isoleucine degradation. These results described unique metabolic characteristics of semen in patients with oligospermia and provided novel insights into the mechanism of the semen disorder.

Abstract High-steep gently inclined mining slopes, prevalent globally, often suffer significant deformation, leading to landslides due to numerous goafs. This research investigates the critical role of goaf location in controlling deformation, failure mechanisms, and disaster evolution, vital for safe mining practices. Through field investigations and model generalization in Guizhou, a physical model test method was used to study three positions of goafs: under the shoulder and foot of the slope, under the slope shoulder, and within the slope. Findings highlight the stronger influence of the goaf’s mutual position with the slope shoulder on slope and overburden deformation and failure compared to the slope toe. Deformation and failure modes evolve from collapse toppling to collapse slip and collapse settlement as the goaf shifts from the near slope surface to inside of the slope. Statistical analysis of fracture distribution in the goaf’s overlying strata reveals damage increase with larger goafs, following a Gaussian distribution, with concentrated damage in the middle. The study identifies the maximum damage area, influenced by the horizontal distance between the goaf center and slope shoulder. These insights advance understanding of overburden rock deformation in gently inclined high-steep mining slopes.

Abstract Root rot is a serious soil-borne fungal disease that seriously affects the yield and quality of Panxa ginseng. To develop a sustainable strategy for alleviating ginseng root rot, an herb-based soil amendment is suggested in this study. Mixed powers of medicinal herbs (MP) and corn stalks (CS) were used as soil amendments, respectively, along with a control group (CK) without treatment. The application of MP and CS led to significant relief from ginseng root rot. The disease index (%) represents both the incidence rate and symptom severity of the disease. The disease index of the MP and CS group was 18.52% and 25.93%, respectively, lower than that of CK (40.74%). Correspondingly, three soil enzyme activities improved; the antifungal components in the soil increased; and the relative abundances of root rot pathogens decreased in response to MP Soil enzyme activities were negatively correlated with disease grades. MP group also led to possible interactive changes in the communities of soil fungi and chemical components. In conclusion, our results suggest that the use of herb-based soil amendments has significant potential as an ecological and effective approach to controlling root rot disease of ginseng by the changing rhizosphere fungal community and soil compositions.

Abstract Recent studies indicate that CISD3 is crucial in mitochondrial function and tumorigenesis. Using various databases, we systematically analyzed its expression, prognostic value, and immune activity. Our findings show CISD3 is mainly expressed in tumor cells across cancers, with higher mRNA but lower protein levels, degraded post-translationally via the lysosomal pathway. In certain cancers, CISD3 expression is positively correlated with tumor-infiltrating immune cells. Prognostic analysis suggests dual roles as both protective and risk factors, notably an independent prognostic predictor in renal cell carcinoma (RCC). CISD3 copy number variations are linked to homologous recombination defects and tumor-specific neoantigens, negatively correlated with methylation levels. Pathway analysis reveals CISD3 involvement in oncogenic processes, such as proliferation inhibition and epithelial-mesenchymal transition. Protein interactions underline its role in mitochondrial metabolism and redox balance. Experiments confirm low CISD3 expression in cancers, with overexpression reducing proliferation, migration, invasion, and tumor growth in mice. Mechanistic studies indicate CISD3 overexpression disrupts mitochondrial function, increases ROS levels, decreases GSH/GSSG ratios and mitochondrial membrane potential, inhibiting antioxidant activity and promoting cell damage and ferroptosis, thus impeding cancer progression. This study highlights CISD3’s potential as a prognostic biomarker and therapeutic target.

Abstract High altitude exposure negatively affects human attentional function. However, no studies have explored the regulation of attentional and physiological functions from a dietary perspective. A total of 116 Han Chinese students from Tibet University who were born and raised in a plain area and had been living in Tibet for > 2 years were recruited. All participants were male migrants. A food frequency questionnaire, complete blood count, and attention network test were performed on the participants. Pearson’s correlation was applied to assess the reliability and validity of the food frequency questionnaire. Principal component analysis was utilized to extract dietary patterns. A linear mixed model was employed to account for individual differences. The results showed that the five main dietary patterns were coarse grain, alcohol, meat, protein, and snacking dietary patterns. Furthermore, individuals who adhered to the coarse grain dietary pattern and had high mean corpuscular hemoglobin showed better attentional performance. Individuals with high alcohol consumption and systemic immune-inflammation index levels exhibited worse attentional performance. These findings imply that high-altitude migrants should include more coarse grains in their daily diet and avoid excessive alcohol consumption to improve attention.

Abstract Urolithiasis is a leading urological disorder where accurate preoperative identification of stone types is critical for effective treatment. Deep learning has shown promise in classifying urolithiasis from CT images, yet faces challenges with model size and computational efficiency in real clinical settings. To address these challenges, we developed a non-invasive prediction approach for determining urinary stone types based on CT images. Through the refinement and improvement of the self-distillation architecture, coupled with the incorporation of feature fusion and the Coordinate Attention Module (CAM), we facilitated a more effective and thorough knowledge transfer. This method circumvents the extra computational expenses and performance reduction linked with model compression and removes the reliance on external teacher models, markedly enhancing the efficacy of lightweight models. achieved a classification accuracy of 74.96% on a proprietary dataset, outperforming current techniques. Furthermore, our method demonstrated superior performance and generalizability on two public datasets. This not only validates the effectiveness of our approach in classifying urinary stones but also showcases its potential in other medical image processing tasks. These results further reinforce the feasibility of our model for actual clinical deployment, potentially assisting healthcare professionals in devising more precise treatment plans and reducing patient discomfort.

Abstract This study investigates the microstructural characteristics and mechanical properties of a laser welded AZ80 magnesium alloy. The welding process led to the formation of coarse-grained fusion zone (FZ), where a secondary phase formed continuous network. Mg17Al12 precipitation and coarsening of grain boundaries occurred in the heat affected zone. The welded joint exhibited excellent mechanical properties with a yield strength of 202 MPa and a joint efficiency of 92%. The microstructure analysis via EPMA and EBSD in conjunction with synchrotron X-ray diffraction analysis reveals that precipitates and increased dislocation density in the fusion zone are primary strengthening mechanisms for the laser welded AZ80 Mg alloy.

Abstract SHP-1, a nonreceptor protein tyrosine phosphatase encoded by ptpn6, has been regarded as a regulatory protein of hematopoietic cell biology for years. However, there is now increasing evidence to support its role in tumors. Thus, the role of ptpn6 for prognosis and immune regulation across 33 tumors was investigated, aiming to explore its functional heterogeneity and clinical significance in pan-cancer. Differential expression of ptpn6 was found between cancer and adjacent normal tissues, and its expression was significantly correlated with the prognosis of tumor patients. In most cancers, ptpn6 expression was significantly associated with immune infiltration. This was further confirmed by ptpn6-related genes/proteins enrichment analysis. Additionally, genetic alterations in ptpn6 was observed in most cancers. As for epigenetic changes, it’s phosphorylation levels significantly altered in 6 tumors, while methylation levels significantly altered in 12 tumors. Notably, the methylation levels of ptpn6 were significantly decreased in 11 tumors, accompanied by its increased expression in 8 of them, suggesting that the hypomethylation may be related to its increased expression. Our results show that ptpn6 plays a specific role in tumor immunity and exerts a pleiotropic effect in a variety of tumors. It can serve as a prognostic factor for some cancers. Especially in LGG, KIRC, UCS and TGCT, the increased expression of ptpn6 is associated with poor prognosis and high immune infiltration. This aids in understanding the role of ptpn6 in tumor biology, and can provide insight into presenting a potential biomarker for poor prognosis and immune infiltration in cancers.

Abstract Nitrogen deficiency in low organic matter soils significantly reduces crop yield and plant health. The effects of foliar applications of indole acetic acid (IAA), trehalose (TA), and nanoparticles-coated urea (NPCU) on the growth and physiological attributes of tomatoes in nitrogen-deficient soil are not well documented in the literature. This study aims to explore the influence of IAA, TA, and NPCU on tomato plants in nitrogen-deficient soil. Treatments included control, 2mM IAA, 0.1% TA, and 2mM IAA + 0.1% TA, applied with and without NPCU. Results showed that 2mM IAA + 0.1% TA with NPCU significantly improved shoot length (~ 30%), root length (~ 63%), plant fresh (~ 48%) and dry weight (~ 48%), number of leaves (~ 38%), and leaf area (~ 58%) compared to control (NPCU only). Additionally, significant improvements in chlorophyll content, total protein, and total soluble sugar, along with a decrease in antioxidant activity (POD, SOD, CAT, and APX), validated the effectiveness of 2mM IAA + 0.1% TA with NPCU. The combined application of 2mM IAA + 0.1% TA with NPCU can be recommended as an effective strategy to enhance tomato growth and yield in nitrogen-deficient soils. This approach can be integrated into current agricultural practices to improve crop resilience and productivity, especially in regions with poor soil fertility. To confirm the efficacy of 2mM IAA + 0.1% TA with NPCU in various crops and climatic conditions, additional field studies are required.

Abstract This study aims to understand the repercussions of the COVID-19 pandemic on hospitalized patients with peripheral arterial disease (PAD) in China, who did not contract SARS-CoV-2. We conducted a multicenter cross-sectional analysis comparing the characteristics and outcomes of hospitalized PAD patients across two distinct periods: Pre-pandemic (P1, from January 2018 to December 2019) and during the pandemic (P2, from January 2020 to December 2021). During P1, 762 hospitalized patients were treated, with an average age of 72.3 years, while 478 patients were treated in P2, with an average age of 65.1 years. Notably, hospitalized patients admitted during the pandemic (P2) exhibited a significantly higher incidence of chronic limb-threatening ischemia (CLTI, 70% vs 54%), diabetic foot infection (47% vs 29%), and infra-popliteal lesions (28% vs 22%). Furthermore, these patients demonstrated a marked deterioration in their Rutherford category and an increased mean score in the Wound, Ischemia, and foot Infection classification system (WIfI). Treatment during the pandemic emerged as a predictor of reduced procedural success and increased major adverse limb events. Factors such as the presence of diabetic foot infection, renal impairment, and deteriorating WIfI scores were identified as independent risk indicators for major adverse limb events. Our results demonstrate that intensive care was provided to severe cases of PAD even during the challenging circumstances of the COVID-19 pandemic. Despite the unprecedented pressures on healthcare systems, patients with severe PAD, particularly those with CLTI, continued to receive necessary in-patient care. The findings underscore the importance of timely medical interventions and extended follow-up for patients exhibiting high-risk factors.

Abstract In this study, XPS sputtering depth, SEM and electrochemical tests (CV, EIS, M-S, i-t, DPP) were used to study the structural composition and formation mechanism of surface passive film of Nb microalloyed rebar in SCPS with different pH. The results showed that after passivation for 10 d in SCPS with different pH, compared with CS rebar, the stability and compactness of surface passive film of 34Nb rebar gradually increased with the decreases of pH. Firstly, with the decreases of pH, the outer layer of surface passive film of 34Nb rebar was composed of Fe oxides and Fe hydroxides, and the inner layer was composed of Fe oxides and Nb oxides, thus increasing the mass ratio of Fe3+/Fe2+ and Nb2O5/(NbO2 + NbO). Secondly, with the decreases of pH, the addition of Nb promoted the formation of Fe oxides in 34Nb rebar, obtaining the excellent Rct, Ecorr and Ep. Finally, with the decreases of pH, the addition of Nb promoted the enrichment of Nb oxides in 34Nb rebar, inhibiting the degradation of Fe oxides, and the passive film exhibited the P-N type semiconductor, thus significantly decreasing the carrier density and enhancing the passivation rate of 34Nb rebar.

Abstract Heart sound auscultation plays a crucial role in the early diagnosis of cardiovascular diseases. In recent years, great achievements have been made in the automatic classification of heart sounds, but most methods are based on segmentation features and traditional classifiers and do not fully exploit existing deep networks. This paper proposes a cardiac audio classification method based on image expression of multidimensional features (CACIEMDF). First, a 102-dimensional feature vector is designed by combining the characteristics of heart sound data in the time domain, frequency domain and statistical domain. Based on the feature vector, a two-dimensional feature projection space is constructed by PCA dimensionality reduction and the convex hull algorithm, and 102 pairs of coordinate representations of the feature vector in the two-dimensional space are calculated. Each one-dimensional component of the feature vector corresponds to a pair of 2D coordinate representations. Finally, the one-dimensional feature component value and its divergence into categories are used to fill the three channels of a color image, and a Gaussian model is used to dye the image to enrich its content. The color image is sent to a deep network such as ResNet50 for classification. In this paper, three public heart sound datasets are fused, and experiments are conducted using the above methods. The results show that for the two-classification/five-classification task of heart sounds, the method in this paper can achieve a classification accuracy of 95.68%/94.53% when combined with the current deep network.

Abstract This report describes the development and characterization of a comprehensive collection of CHO cell glycosylation mutants with significant potential for advancing glycobiology and biotechnology. EPO-Fc and trastuzumab, two model molecules, were produced using these mutants to assess the effects of mutated glycogenes, and LC-MS/MS analysis was employed to quantitatively analyse their N-glycans. EPO-Fc exhibited exclusively homogeneous Man9 glycans only when nearly all α-mannosidases in the genome were inactivated, except lysosomal MAN2B1. Some mutants lacking GnT-I activity produce mostly Man5 N-glycans, while their O-glycan and glycolipid profiles can differ due to other mutations in the cell. GnT-II deficiency prevents GnT-V from adding GlcNAc to the core N-glycan, resulting in branches attaching solely to the α1,3-linked mannose, leaving the α1,6-linked mannose free. The mutant-produced antibody’s single-branched glycan contains more sialic acid than the dual-branched glycans produced in CHO-K1 cells. Trastuzumab produced in these mutants provided insights into how Fc N-glycans impact the antibody’s interaction with FcγR1 and FcγR2a, FcγR3a, and their influence on antibody-dependent cellular cytotoxicity (ADCC). In the study of Fc glycans in Fc-FcγR1 and FcγR2a interactions, we observed a consistent glycan-related impact on binding to both receptors, indicating a common interaction mechanism between Fc glycans and both FcγRI and FcγRIIa. CHO mutants produced trimeric gp120 demonstrated distinct reactivity with multiple broadly neutralizing anti-HIV antibodies, confirming the involvement of gp120 glycans in interactions with specific broadly neutralizing antibodies. Finally, one of the mutants produced human β-glucocerebrosidase with uniform Man5 N-glycans, showcasing its potential for glycoengineered production and enhancement in therapeutic efficacy.

Abstract DNA cleavage by nanomaterials has the potential to be utilized as an innovative tool for gene editing. Numerous nanomaterials exhibiting DNA cleavage properties have been identified and cataloged. Yet, the exploitation of property data through data-driven machine-learning approaches remains unexplored. A database was developed, compiling thirty distinctive characteristics, encompassing physical and chemical properties, as well as experimental conditions of nanomaterials that have demonstrated DNA cleavage capability such as in articles published over the past two decades. The DNA cleavage effect and efficiency of nanomaterials were predicted using machine learning algorithms such as support vector machines, deep neural networks, and random forest, and a classification accuracy of 0.93 for the cleavage effect was achieved. Moreover, the potential of utilizing larger datasets to enhance the predictive capacity of models was discussed. The findings indicate the feasibility of predicting nanomaterial properties based on experimental data. Evaluating the performance and effectiveness of the machine learning models trained using the existing data can furnish valuable insights for future materials research endeavors, especially for the design of DNA cleavage with specific sites.