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Abstract The rail profile milling process allows considerable thickness to be removed in a single pass. However, the residual waviness formation law after milling and its subsequent effect on rail performance remains uncertain. In this paper, the wavelength and wave height of the residual waviness are identified as the key characteristics. The relationship between milling speed and residual waviness is determined, and a numerical model of the residual waviness formed on the surface after milling is established based on the commonly used three milling speeds of 300, 600, and 1000 m/h, and its accuracy is verified using the parameters of the residual waviness detected by the milling experiments. A three-dimensional finite element analysis model of wheel-rail contact was employed to analyze the contact stresses and low fatigue cycles at a wheel load of 11.5 tons with no residual waviness on the rail profile surface and with three types of residual waviness, respectively. The results show that the residual waviness changes the wheel-rail contact position and the morphology of the contact area, reduces the maximum contact stress and increases the strain fatigue cycles. The application of elevated milling speeds reduces the wheel-rail contact stresses after milling, thereby increasing the low fatigue cycles.

Abstract Neoadjuvant therapy (NAT) is an important treatment for patients with resectable locally advanced esophageal squamous cell carcinoma (ESCC), but neoadjuvant resistance affects the overall treatment outcome. Therefore, it is particularly important to accurately screen the population for NAT and explore the mechanism of resistance. Usually, different chemotherapy regimens cause different drug resistance mechanisms. Prior to combining immunotherapy with chemotherapy, extensive research has been conducted on previous drug resistance mechanisms. Currently, the mainstream NAT for ESCC involves chemotherapy combined with immunotherapy. We have witnessed the remarkable effect of this combination therapy; however, there are still a considerable number of patients whose tumor tissues show no change or even progress after NAT, and their drug resistance mechanisms remain unclear. Hence, we aim to identify relevant evidence that can distinguish and predict the effectiveness of NAT from a clinical perspective in order to provide a clinical basis for future screening of suitable populations for NAT and discovery of drug resistance mechanisms. This study is based in China's high incidence area of esophageal cancer, where enrolled patients all receive the current mainstream NAT regimen resulting in more reliable outcomes.

Abstract Telemedicine and video-based diagnosis have raised significant concerns regarding the protection of facial privacy. Effective de-identification methods require the preservation of diagnostic information related to normal and pathological facial movements, which play a crucial role in the diagnosis of various movement, neurological, and psychiatric disorders. In this work, we have developed FaceMotionPreserve , a deep generative model-based approach that transforms patients’ facial identities while preserving facial dynamics with a novel face dynamic similarity module to enhance facial landmark consistency. We collected test videos from patients with Parkinson’s disease recruited via telemedicine for evaluation of model performance and clinical applicability. The performance of FaceMotionPreserve was quantitatively evaluated based on neurologist diagnostic consistency, critical facial behavior fidelity, and correlation of general facial dynamics. In addition, we further validated the robustness and advancements of our model in preserving medical information with clinical examination videos from a different cohort of patients. FaceMotionPreserve is applicable to real-time integration, safeguarding facial privacy while retaining crucial medical information associated with facial movements to address concerns in telemedicine, and facilitating safer and more collaborative medical data sharing.

Abstract The Qinghai-Tibet Plateau is a valuable genetic resource pool, and the high-altitude adaptation of Tibetan pigs is a classic example of the adaptive evolution of domestic animals. Here, we report the presence of Darwinian positive selection signatures in Tibetan pigs (TBPs) using 348 genome-wide datasets (127 whole-genome sequence datasets (WGSs) and 221 whole-genome single-nucleotide polymorphism (SNP) chip datasets). We characterized a high-confidence list of genetic signatures related response to high-altitude adaptation in Tibetan pigs, including 4,598 candidate SNPs and 131 candidate genes. Functional annotation and enrichment analysis revealed that 131 candidate genes are related to multiple systems and organs in Tibetan pigs. Notably, eight of the top ten novel genes, RALB, NBEA, LIFR, CLEC17A, PRIM2, CDH7, GK5 and FAM83B, were highlighted and associated with improved adaptive heart functions in Tibetan pigs high-altitude adaptation. Moreover, genome-wide association analysis revealed that 29 SNPs were involved in 13 candidate genes associated with at least one adaptive trait. In particular, among the top ten candidate genes, CLEC17A is related to a reduction in hemoglobin (HGB) in Tibetan pigs. Overall, our study provides a robust SNP/gene list involving genetic adaptation for Tibetan pig high-altitude adaptation, and it will be a valuable resource for future Tibetan pig studies.

Abstract This research delves into the transfer and loss of energy in a discrete mass when subjected to forced vibration. Using discrete element method (DEM), we analyzed the dynamic behavior of regular spherical granular assemblies and the energy distribution characteristics under different excitation frequencies and reduced accelerations. Moreover, the energy transfer and dissipation process of granular assemblies under different vibration states are studied using an experimental method. The results show that the granular assemblies will produce collision energy dissipation, thermal energy dissipation, acoustic energy dissipation and other forms of energy dissipation in the forced vibration state and the proportion of different energy dissipation under different excitation is given. The collision and friction of granular assemblies are the key to affecting other forms of energy dissipation. When the excitation increases, the energy dissipation forms are generated inside the granular assemblies, and the proportion of collision energy dissipation of the granular assemblies increases. The acoustic energy above 20 kHz occupies the main part of the acoustic energy dissipation. Thermal energy consumption always exists, which takes a long time to play a role. The granular also have other forms of energy loss, which is hard to be measured, including Rayleigh waves generated by granular collision. In this study, the relationship between the forced vibration state of the granular assemblies and the energy loss distribution is established. Various types of energy transfer and conversion distribution which further enriches the energy dissipation of discrete element calculation of the granular assemblies is discussed and provides a reference for the energy loss analysis of the granular assemblies.

Abstract Cuproptosis is a newly defined form of programmed cell death that relies on mitochondria respiration. Long noncoding RNAs (lncRNAs) play crucial roles in tumorigenesis and metastasis. However, whether cuproptosis-related lncRNAs are involved in the pathogenesis of diffuse large B cell lymphoma (DLBCL) remains unclear. This study aimed to identify the prognostic signatures of cuproptosis-related lncRNAs in DLBCL and investigate their potential molecular functions. RNA-Seq data and clinical information for DLBCL were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Cuproptosis-related lncRNAs were screened out through Pearson correlation analysis. Utilizing univariate Cox, least absolute shrinkage and selection operator (Lasso) and multivariate Cox regression analysis, we identified seven cuproptosis-related lncRNAs and developed a risk prediction model to evaluate its prognostic value across multiple groups. GO and KEGG functional analyses, single-sample GSEA (ssGSEA), and the ESTIMATE algorithm were used to analyze the mechanisms and immune status between the different risk groups. Additionally, drug sensitivity analysis identified drugs with potential efficacy in DLBCL. Finally, the protein–protein interaction (PPI) network were constructed based on the weighted gene co-expression network analysis (WGCNA). We identified a set of seven cuproptosis-related lncRNAs including LINC00294, RNF139-AS1, LINC00654, WWC2-AS2, LINC00661, LINC01165 and LINC01398, based on which we constructed a risk model for DLBCL. The high-risk group was associated with shorter survival time than the low-risk group, and the signature-based risk score demonstrated superior prognostic ability for DLBCL patients compared to traditional clinical features. By analyzing the immune landscapes between two groups, we found that immunosuppressive cell types were significantly increased in high-risk DLBCL group. Moreover, functional enrichment analysis highlighted the association of differentially expressed genes with metabolic, inflammatory and immune-related pathways in DLBCL patients. We also found that the high-risk group showed more sensitivity to vinorelbine and pyrimethamine. A cuproptosis-related lncRNA signature was established to predict the prognosis and provide insights into potential therapeutic strategies for DLBCL patients.

Abstract Establish a new classification system of distal radius fracture based on computed tomographic (CT), and evaluate its reliability and reproducibility preliminarily, and provide a new theoretical reference for clinicians to use the clinical classification system. The imaging data and clinical data of 204 inpatients with distal radius fracture during 6 years from January 1, 2014 to January 1, 2019 in orthopaedic department were analyzed retrospectively and classified based on CT. Three observers evaluated the image data of 48 randomly selected cases based on CT at different time nodes of T1 and T2. Cohen's kappa was used to calculate the consistency. At the last follow-up, patients' Disabilities of the Arm, Shoulder and Hand (DASH), Patient Rated Wrist Evaluation (PRWE), and VAS scores were collected. Among 204 cases, there were 12 cases of type 1, including 6 cases of type 1-D, 4 cases of type 1-V and 2 cases of type 1-R. There were 6 cases of type 2, including 2 cases of type 2-DV, 2 cases of type 2-DR and 2 cases of type 2-VR. There were 186 cases of type 3, including 32 cases of type 3–0, 127 cases of type 3–1 and 27 cases of type 3–2. There was no significant difference in DASH, PRWE and VAS scores among all types (P > 0.05). The results of interobserver reproducibility were kappa = 0.985, ICC = 0.984 in the first evaluation, kappa = 0.986, ICC = 0.986 in the second evaluation. The results of intraobserver reproducibility were O1 = 0.991, O2 = 0.991, O3 = 0.989 respectively. The new classification system of distal radius fracture based on CT has theoretical and practical significance for incision selection, fracture reduction and internal fixation. 123 classification system is clear, comprehensive, easy to understand and remember. Moreover, it has higher interobserver reliability and intraobserver reproducibility than other systems reported at present.

Abstract Global climate change, with warming as its main feature, has altered the spatial-temporal evolution of factors such as precipitation and temperature that can cause meteorological disasters. The complex and changeable climate has led to frequent natural disasters, while the frequency and intensity of extreme climate events have also significantly increased, posing an enormous threat to societal production and human life. As the most important geoecological transitional zone of mainland China, the stability of agricultural production in China’s north–south transitional zone is crucial for ensuring food security under climate change. With the use of daily precipitation and potential evapotranspiration data from 1961 to 2018, this study focused on analysing disturbances such as extreme precipitation and drought disasters at different time scales during the winter wheat and summer maize growing seasons in the north–south transitional zone of China from an agricultural production perspective and attempted to answer the following questions: first, from an agricultural production perspective, what are the temporal and spatial distribution patterns of extreme precipitation and arid climate events in the north–south transitional zone? Second, which areas are at high risk of being disturbed by different types of meteorological disasters and require increased attention? The results indicated that (1) in terms of the overall temporal variation, the degree of extreme precipitation and drought stress faced by agricultural production in the region is decreasing. However, the temporal variation at each station in the north–south transitional zone was not completely consistent with the overall trend, and both increasing and decreasing trends were observed. The sites exhibiting an increase overlapped with typical regions of the north–south transitional zone to varying degrees, indicating that the typical regions represented not only theoretical potential risk areas under climate change but also suffered from meteorological disaster disturbances. (2) The precipitation distribution during the winter wheat growth period in the south–north transitional zone was uneven and varied significantly. High values of extreme precipitation indices during the winter wheat growth period were mainly concentrated in the southern part of the eastern section of the north‒south transitional zone. The precipitation distribution during the summer maize growth period significantly differed, with the highest amount of heavy rain and largest number of rainstorm days concentrated in the southeastern part of the north‒south transitional zone. The spatial distribution of the drought frequency in the north–south transitional zone, as indicated by the monthly standardized precipitation evapotranspiration index (SPEI1), showed that the areas with high total drought frequencies were mainly concentrated in northeast Jiangsu, southeast Henan, and north Anhui, which primarily experienced light drought. The central part of Jiangsu Province exhibited a high frequency of moderate drought, while southern Jiangsu Province and southwestern Shaanxi Province were prone to severe drought. Additionally, southeastern Hebei and eastern Henan were identified as areas with a high frequency of extreme drought. Finally, the central region of Sichuan Province was characterized by both severe and extreme drought conditions. Based on the SPEI12-derived spatial distribution of the drought frequency in the north–south transitional zone, the areas with a high total drought frequency were mainly concentrated in central and eastern Henan, southeast Shaanxi, southeast Shandong, and central Sichuan, which primarily experienced light to moderate drought. The northwestern part of Jiangsu, the southern part of Hebei, and the western part of Shandong are regions with a high frequency of severe drought, while the eastern part of Henan is an area with high frequencies of both severe and extreme drought. (3) High-value areas of extreme precipitation and drought disturbance in the north–south transitional zone overlapped with the edge of the transitional zone to varying degrees. Approximately 63.58% of the north‒south transitional zone of China was characterized by moderate or high stress levels, primarily concentrated along the southern boundary and central core area, and nearly 39.5% of all counties experienced two or more types of disaster stresses.

Abstract REBCO has been used extensively as coated conductors applied to superconducting magnets due to its exceptional superconducting properties. As a REBCO superconductor, YbBa2Cu3O7−y (Yb123) has a low melting temperature, making it suitable for use as an intermediate medium connector while preparing the superconducting joint. However, there is still uncertainty about the formation mechanism of Yb123 and the synthesis of this superconductor has not been fully understood. Therefore, this study systematically investigated the phase transformation process of Yb123 during heat treatment in flowing oxygen. The results indicated that Yb123 sample with the highest phase purity could be obtained by annealing at 927 °C or 937 °C but not in between, respectively. Furthermore, a quantitative phase analysis revealed that the sample annealed at 937 °C had a phase purity greater than 80 wt%. Additionally, a strong c-axis texture was observed in the bulk Yb123 superconductor prepared at 937 °C. Meanwhile, the superconducting results revealed that the bulk sample’s Tc was 89.9 K, and its self-field critical current densities at 4.2 K and 77 K were 1.3 × 105 A/cm2 and 5.0 × 103 A/cm2, respectively. Based on the results mentioned above, the phase transformation process and formation mechanism of Yb123 in flowing oxygen were elaborated.

Abstract This study aims to explore the correlation between the CT-L1 and L3 body composition parameters and analyze the relationship between L1 body composition and hematologic toxicity in luminal-type breast cancer patients undergoing neoadjuvant chemotherapy. Data from 140 luminal-type breast cancer patients who underwent surgical treatment after neoadjuvant chemotherapy were analyzed retrospectively. Spearman analysis was used to assess the correlation between CT-L1 and CT-L3 body composition parameters pre-neoadjuvant chemotherapy. Additionally, univariate and multivariate logistic regression analyses were performed to identify factors influencing hematologic toxicity. CT-L1 body composition parameters were positively correlated with CT-L3 body composition parameters in 34 patients. Severe hematological toxicity occurred in 46 cases among the patient cohort. A skeletal muscle index (SMI) of

Abstract To figure out how does SARS-CoV-2 affect sperm parameters and what influencing factors affect the recovery of sperm quality after infection? We conducted a prospective cohort study and initially included 122 men with SARS-CoV-2 infection. The longest time to track semen quality after infection is 112 days and 58 eligible patients were included in our study eventually. We subsequently exploited a linear mixed-effects model to statistically analyze their semen parameters at different time points before and after SARS-CoV-2 infection. Semen parameters were significantly reduced after SARS-CoV-2 infection, including total sperm count (211 [147; 347] to 167 [65.0; 258], P

Abstract Post-COVID-19 syndrome may be associated with the abnormal immune status. Compared with the unexposed age-matched elder group, PD-1 in the CD8+ T cells from recovered COVID-19 patients was significantly lower. IFN-γ in the plasma of COVID-19 convalescent patients was increased, which inhibited PD-1 expression in CD8+ T cells from COVID-19 convalescent patients. scRNA-seq bioinformatics analysis revealed that AKT/GSK3β may regulate the INF-γ/PD-1 axis in CD8+ T cells from COVID-19 convalescent patients. In parallel, an IFN-γ neutralizing antibody reduced AKT and increased GSK3β in PBMCs. An AKT agonist (SC79) significantly decreased p-GSK3β. Moreover, AKT decreased PD-1 on CD8+ T cells, and GSK3β increased PD-1 on CD8+ T cells according to flow cytometry analysis. Collectively, we demonstrated that recovered COVID-19 patients may develop long COVID. Increased IFN-γ in the plasma of recovered Wuhan COVID-19 patients contributed to PD-1 downregulation on CD8+ T cells by regulating the AKT/GSK3β signaling pathway.

Abstract The mood index $$r$$ r was used to describe evaluator attitudes regarding the progress of a project that formed the basis of a construction period prediction model. The degrees of pessimism $$\alpha$$ α and optimism $$\beta$$ β were introduced, and an analysis model was established using $$\alpha$$ α and $$\beta$$ β to predict the construction period and completion probability Firstly, the absolute construction period of each process of tunnel No. 2 can be obtained according to the measured daily average footage of each process of tunnel No. 1. Secondly, the probability of the stoppage caused by different factors can be obtained after the statistical analysis of the factors responsible for the stoppage of tunnel No. 1. Finally, the expected construction period and completion probability of tunnel No. 2 under different pessimism and optimism conditions are obtained by using the progress risk analysis theory of emotional models and the program evaluation and review technique method. An engineering application showed that the expected construction period increased, and the completion probability decreased considerably with increasing pessimism; the opposite trend occurred as optimism increased. During the process of risk management and control, the prediction model can be used to perform precise quantitative analysis of the expected construction period and completion probability, reduce the blindness of construction management, control decisions of complex giant tunnel projects, and provide a more accurate basis for decision makers to judge risks. The findings of this study can be applied to hydraulic tunnels and can provide a reference for traffic tunnels, railway tunnels, and other similar projects.

Abstract To explore the relationship between quantitative perfusion histogram parameters of dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) with the expression of tumor tissue epidermal growth factor receptor (EGFR), vascular endothelial growth factor (VEGF) and EGFR gene mutations in non-small cell lung cancer (NSCLC). A total of 44 consecutive patients with known NSCLC were recruited from March 2018 to August 2021. Histogram parameters (mean, uniformity, skewness, energy, kurtosis, entropy, percentile) of each (Ktrans, Kep, Ve, Vp, Fp) were obtained by Omni Kinetics software. Immunohistochemistry staining was used in the detection of the expression of VEGF and EGFR protein, and the mutation of EGFR gene was detected by PCR. Corresponding statistical test was performed to compare the parameters and protein expression between squamous cell carcinoma (SCC) and adenocarcinoma (AC), as well as EGFR mutations and wild-type. Correlation analysis was used to evaluate the correlation between parameters with the expression of VEGF and EGFR protein. Fp (skewness, kurtosis, energy) were statistically significant between SCC and AC, and the area under the ROC curve were 0.733, 0.700 and 0.675, respectively. The expression of VEGF in AC was higher than in SCC. Fp (skewness, kurtosis, energy) were negatively correlated with VEGF (r = − 0.527, − 0.428, − 0.342); Ktrans (Q50) was positively correlated with VEGF (r = 0.32); Kep (energy), Ktrans (skewness, kurtosis) were positively correlated with EGFR (r = 0.622, r = 0.375, 0.358), some histogram parameters of Kep, Ktrans (uniformity, entropy) and Ve (kurtosis) were negatively correlated with EGFR (r = − 0.312 to − 0.644). Some perfusion histogram parameters were statistically significant between EGFR mutations and wild-type, they were higher in wild-type than mutated (P

Abstract Doxorubicin (DOX) is an effective anticancer drug with potent antitumour activity. However, the application of DOX is limited by its adverse reactions, such as depression. Taurine can alleviate depression induced by multiple factors. However, it is still unclear whether and how taurine improves DOX-induced depression. To address this question, the aim of this study was to explore the potential mechanism by which taurine protects against DOX-induced depression. Mice were randomly divided into three groups (n = 8): (1) the control group, (2) the DOX group, and (3) the DOX + taurine group. The open field test (OFT), elevated plus maze test, and forced swim test (FST) were first performed to assess the effects of DOX and taurine on the behaviour of mice. Next, a combined transcriptomic and metabolomic analysis was performed to analyse the possible antidepressive effect of taurine. Taurine pretreatment increased the total distance travelled and speed of mice in the OFT, increased the number of entries into the open arm and the time spent in the open arm, and reduced the immobility time in the FST. In addition, 179 differential genes and 51 differentially abundant metabolites were detected in the DOX + taurine group compared to the DOX group. Furthermore, differential genes and differentially abundant metabolites were found to be jointly involved in 21 pathways, which may be closely related to the antidepressant effect of taurine. Taurine alleviated DOX-induced depressive behaviour. The various pathways identified in this study, such as the serotonergic synapse and the inflammatory mediator regulation of TRP channels, may be key regulatory pathways related to depression and antidepressant effects.

Abstract Multiple myeloma (MM) is a distinguished hematologic malignancy, with existing studies elucidating its interaction with neutrophil extracellular traps (NETs), which may potentially facilitate tumor growth. However, systematic investigations into the role of NETs in MM remain limited. Utilizing the single-cell dataset GSE223060, we discerned active NET cell subgroups, namely neutrophils, monocytes, and macrophages. A transcriptional trajectory was subsequently constructed to comprehend the progression of MM. Following this, an analysis of cellular communication in MM was conducted with a particular emphasis on neutrophils, revealing an augmentation in interactions albeit with diminished strength, alongside abnormal communication links between neutrophils and NK cells within MM samples. Through the intersection of differentially expressed genes (DEGs) between NET active/inactive cells and MM versus healthy samples, a total of 316 genes were identified. This led to the development of a 13-gene risk model for prognostic prediction based on overall survival, utilizing transcriptomics dataset GSE136337. The high-risk group manifested altered immune infiltration and heightened sensitivity to chemotherapy. A constructed nomogram for predicting survival probabilities demonstrated encouraging AUCs for 1, 3, and 5-year survival predictions. Collectively, our findings unveil a novel NET-related prognostic signature for MM, thereby providing a potential avenue for therapeutic exploration.

Abstract Early identification is crucial to effectively intervene in individuals at high risk of developing pre-diabetes. This study aimed to create a personalized nomogram to determine the 5-year risk of pre-diabetes among Chinese adults. This retrospective cohort study included 184,188 participants without prediabetes at baseline. Training cohorts (92,177) and validation cohorts (92,011) were randomly assigned (92,011). We compared five prediction models on the training cohorts: full cox proportional hazards model, stepwise cox proportional hazards model, multivariable fractional polynomials (MFP), machine learning, and least absolute shrinkage and selection operator (LASSO) models. At the same time, we validated the above five models on the validation set. And we chose the LASSO model as the final risk prediction model for prediabetes. We presented the model with a nomogram. The model's performance was evaluated in terms of its discriminative ability, clinical utility, and calibration using the area under the receiver operating characteristic (ROC) curve, decision curve analysis, and calibration analysis on the training cohorts. Simultaneously, we also evaluated the above nomogram on the validation set. The 5-year incidence of prediabetes was 10.70% and 10.69% in the training and validation cohort, respectively. We developed a simple nomogram that predicted the risk of prediabetes by using the parameters of age, body mass index (BMI), fasting plasma glucose (FBG), triglycerides (TG), systolic blood pressure (SBP), and serum creatinine (Scr). The nomogram's area under the receiver operating characteristic curve (AUC) was 0.7341 (95% CI 0.7290–0.7392) for the training cohort and 0.7336 (95% CI 0.7285–0.7387) for the validation cohort, indicating good discriminative ability. The calibration curve showed a perfect fit between the predicted prediabetes risk and the observed prediabetes risk. An analysis of the decision curve presented the clinical application of the nomogram, with alternative threshold probability spectrums being presented as well. A personalized prediabetes prediction nomogram was developed and validated among Chinese adults, identifying high-risk individuals. Doctors and others can easily and efficiently use our prediabetes prediction model when assessing prediabetes risk.

Abstract As of 2021, over 2.8 million small-incision lenticule extraction (SMILE) procedures have been performed in China. However, knowledge regarding the selection of intraocular lens (IOL) power calculation formula for post-SMILE cataract patients remains limited. This study included 52 eyes of 26 myopic patients from northern China who underwent SMILE at Tianjin Eye Hospital from September 2022 to February 2023 to investigate the suitability of multiple IOL calculation formulas in post-SMILE patients using a theoretical surgical model. We compared the postoperative results obtained from three artificial intelligence (AI)-based formulas and six conventional formulas provided by the American Society of Cataract and Refractive Surgery (ASCRS). These formulas were applied to calculate IOL power using both total keratometry (TK) and keratometry (K) values, and the results were compared to the preoperative results obtained from the Barrett Universal II (BUII) formula for the SMILE patients. Among the evaluated formulas, the results obtained from the Emmetropia Verifying Optical 2.0 Formula with TK (EVO-TK) (0.40 ± 0.29 D, range 0–1.23 D), Barrett True K with K formula (BTK-K, 0.41 ± 0.26 D, range 0.01–1.19 D), and Masket with K formula (Masket-K, 0.44 ± 0.33 D, range 0.02–1.39 D) demonstrated the closest proximity to BUII. Notably, the highest proportion of prediction errors within 0.5 D was observed with the BTK-K (71.15%), EVO-TK (69.23%), and Masket-K (67.31%), with the BTK-K showing a significantly higher proportion than the Masket-K (p

Abstract Prophylactic pharmacotherapy for health care in patients with high risk of cardiac arrest (CA) is an elusive and less explored strategy. Melatonin has possibilities used as a daily nutraceutical to trigger the cellular adaptation. We sought to find the effects of long-term daily prophylactic supplement with melatonin on the victim of CA. Rats were divided into sham, CA, and melatonin + CA (Mel + CA) groups. The rats in the Mel + CA group received daily IP injection of melatonin 100 mg/kg for 14 days. CA was induced by 8 min asphyxia and followed by manual cardiopulmonary resuscitation. The endpoint was 24 h after resuscitation. Survival, neurological outcome, and hippocampal mitochondrial integrity, dynamics and function were assessed. Survival was significantly higher in the Mel + CA group than the CA group (81 vs. 42%, P = 0.04). Compared to the CA group, neurological damage in the CA1 region and the level of cytochrome c, cleaved caspase-3 and caspase-9 in the Mel + CA group were decreased (P

Abstract Scribble is a master scaffold protein in apical-basal polarity. Current knowledge about the biological function of Scribble in colonic epithelial plasticity/regeneration during intestinal inflammation is limited. Here, we showed that the level of Scribble is decreased in inflammatory bowel disease (IBD) patients and mice with DSS-induced colitis. ScribΔIEC mice develops severe acute colitis with disrupted epithelial barrier integrity and impaired crypt stem cell’s function. Mechanistically, Scribble suppressed the process of autophagy by modulating the stability of caspase-dependent degradation of Atg16L1 by directly interacting with Atg16L1 in a LRR domain-dependent manner in IECs and led to an accumulation of ROS both in intestinal stem cells and epithelial cells. In addition, further study indicates that dietary sphingomyelin alleviates DSS-induced colitis by increase the expression of Scribble, which suggests that Scribble may be the critical marker of IBD. Our study shows that Scribble deficiency is associated with the dysregulated autophagy and impaired maintenance of colonic stemness, and it may be a target for diagnosis and treatment of IBD.

Abstract The single-component colistin E2, with superior antibacterial activity and lower toxicity, was being developed as the latest generation of polymyxin drugs. However, colistin E2 has not been tested quantitatively in biological matrices. In this study, based on the quantitative detection of colistin methanesulphonate (CMS) and colistin by Zhao et al., 15N-labeled colistin E2 was used as an internal standard (IS) for a more accurate quantitative detection of CMS E2 in human plasma. A rapid ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC–MS/MS) assay method was developed for determination of CMS E2 and colistin E2 in human plasma. After pretreatment of plasma samples by 96-well SPE Supra-Clean Weak Cation Exchange (WCX) plate, the formed colistin E2 was detected and quantified by UHPLC–MS/MS system. All plasma lots were found to be free of interferences with the analyte. The matrix has no effect on the quantitation of the analyte. No significant effect of the carryover was observed. The dilution integrity was demonstrated in plasma samples without the loss of accuracy and precision. The lower limit of quantification (LLOQ) was 0.0300 mg/L for colistin E2 in plasma with accuracy (relative error, 5.1–12.7%) and precision (relative standard deviation, − 5.7–9.3%). Stability of CMS E2 and colistin E2 was demonstrated in biological samples before and during sample treatment, and in the extract. Furthermore, this method was successfully applied to the analysis of plasma samples obtained from Chinese healthy volunteers receiving a single intravenous CMS E2 dose of 5 mg/kg. In conclusion, the detection method was characterized by speed and high accuracy, which laid a solid foundation for the subsequent development of CMS E2 drug.

Abstract The overcrowding of scenic spots not only threatens tourists’ safety but also affects the travel experience. Traditional methods for addressing tourist overload have involved limited access and guided evacuation. While limited access has been effective, it often results in a diminished tourist experience. Moreover, the existing guided evacuation rarely considers the impact on tourists’ experience, resulting in a low willingness to cooperate and making it difficult to estimate evacuation effort efficiency. To solve these problems, this paper proposed a tourist evacuation route recommendation algorithm based on a graph neural network considering the similarity of tourism styles (PER-GCN) and designed a visualization system to simulate and analyse evacuation efficiency. First, the interaction matrix of tourists and scenic spots was constructed using graph mining to extract the high-order interaction information. In the output layer, the similarity between scenic spots and tourism styles was calculated to further improve the accuracy of scenic spot recommendations. Second, due to route complexity and the real-time carrying capacity of scenic spots, the researchers optimized the evacuation routes. Finally, taking the West Lake spot as the case study, the effectiveness of PER-GCN was verified. Additionally, a visualization system was designed to monitor tourist flow in real time and analyse tourist portraits according to the clustering results of scenic spot styles. In addition, the evacuation efficiency of scenic spots was analysed by adjusting the parameters of tourists’ willingness to cooperate, evacuation batch, and the weight of route complexity and scenic spot carrying capacity.