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Paeniclostridium sordellii is an opportunistic pathogen that can occur and be fatal in women undergoing abortion or childbirth. The pathogenesis of a hemorrhagic toxin, TcsH, produced by this bacteria, remains unknown. Here, authors carry out genome-wide screens to identify pathologically relevant host factors of TcsH.

Abstract Background The FAST study identified claudin-18 (CLDN18.2) as a promising novel therapeutic target for gastric cancer (GC). However, the tumor immune microenvironment and clinicopathological features of CLDN18.2-positive GC are unclear, making it difficult to develop and optimize CLDN18.2-targeted treatments. Methods This study included 80 GC patients, 60 of whom received anti-PD-1/PD-L1 treatment. CD4/CD8/CD20/CD66b/CD68/CD163/PD-1/PD-L1/TIM-3/LAG-3/FoxP3/CTLA-4/HLA-DR/STING, and CLDN18.2 were labeled using multiplex immunohistochemistry (m-IHC) to decipher the rate and spatial distribution of T cells, B cells, macrophages, and neutrophils in formalin-fixed, paraffin-embedded tumor tissues isolated from these patients. Tumor immune-microenvironmental features and patient survival stratified by CLDN18.2 expression were analyzed using two independent-sample t-tests and log-rank tests, respectively. Results We considered moderate-to-strong CLDN18.2 expression ≥ 40% of tumor cells as the cut-off for positivity. The proportion of CD8+PD-1−, CD8+LAG-3−, and CD8+TIM-3− T cells was significantly higher in CLDN18.2-positive tumors than in negative tumors (0.039 vs. 0.026, P = 0.009; 0.050 vs.0.035, P = 0.024; 0.045 vs. 0.032, P = 0.038, respectively). In addition, the number of neutrophils (CD66b+) was higher in the CLDN18.2-positive group than in the negative group (0.081 vs. 0.055, P = 0.031, respectively), while the rates of M1 (CD68+CD163−HLA-DR+), M2 macrophages (CD68+CD163+HLA-DR−), and B cells (CD20+) were comparable between the CLDN18.2-positive and negative groups. The average numbers of CD8+PD-1−, CD8+LAG-3−, and CD8+TIM-3−T cells surrounding tumor cells within a 20-μm range were higher in CLDN18.2-positive tumors than in the CLDN18.2-negative tumors (0.16 vs. 0.09, P = 0.011; 0.20 vs. 0.12, P = 0.029; 0.18 vs. 0.12, P = 0.047, respectively). In addition, in the CLDN18.2-positive group, tumor cells surrounded by CD8+PD-1−, CD8+LAG-3− T cells, or M1 macrophages within a 20-μm range accounted for a higher proportion of all tumor cells than those in the CLDN18.2-negative group (10.79% vs. 6.60%, P = 0.015; 12.68% vs. 8.70%, P = 0.049; 9.08% vs. 6.56%, P = 0.033, respectively). These findings suggest that CLDN18.2-positive GC harbors complex immune-microenvironmental features. Additionally, CLDN18.2-positive group had shorter OS and irOS than CLDN18.2-negative group (median OS: 23.33 vs.36.6 months, P

IntroductionThe biological function and prognosis roles of thymosin β(TMSB) 10 are still unclear in pan-cancer. MethodsWe retrieved The Cancer Genome Atlas and Genotype-tissue expression datasets to obtain the difference of TMSB10 expression between pan-cancer and normal tissues, and analyzed the biological function and prognosis role of TMSB10 in pan-cancer by using cBioPortal Webtool. ResultsThe expression of TMSB10 in tumor tissues was significantly higher than normal tissues, and showed the potential ability to predict the prognosis of patients in Pan-cancer. It was found that TMSB10 was significantly correlated with tumor microenvironment, immune cell infiltration and immune regulatory factor expression. TMSB10 is involved in the regulation of cellular signal transduction pathways in a variety of tumors, thereby mediating the occurrence of tumor cell invasion and metastasis. Finally, TMSB10 can not only effectively predict the anti-PD-L1 treatment response of cancer patients, but also be used as an important indicator to evaluate the sensitivity of chemotherapy. In vitro, low expression of TMSB10 inhibited clonogenic formation ability, invasion, and migration in glioma cells. Furthermore, TMSB10 may involve glioma immune regulation progression by promoting PD-L1 expression levels via activating STAT3 signaling pathway.ConclusionsOur results show that TMSB10 is abnormally expressed in tumor tissues, which may be related to the infiltration of immune cells in the tumor microenvironment. Clinically, TMSB10 is not only an effective prognostic factor for predicting the clinical treatment outcome of cancer patients, but also a promising biomarker for predicting the effect of tumor immune checkpoint inhibitors (ICIs) and chemotherapy in some cancers.

ObjectiveUrsodeoxycholic acid (UDCA) may reduce susceptibility to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection by downregulating angiotensin-converting enzyme 2 (ACE2), based on recent experimental investigation. This study aimed to determine the potential protective effect of UDCA against SARS-CoV-2 infection in patients with chronic liver disease.MethodsPatients with chronic liver disease receiving UDCA (taking UDCA ≥1 month) at Beijing Ditan Hospital between January 2022 and December 2022 were consecutively enrolled. These patients were matched in a 1:1 ratio to those with liver disease not receiving UDCA during the same period by using a propensity score matching analysis with nearest neighbor matching algorithm. We conducted a phone survey of coronavirus disease 2019 (COVID-19) infection during the early phase of the pandemic liberation (from 15 December 2022 to 15 January 2023). The risk of COVID-19 was compared in two matched cohorts of 225 UDCA users and 225 non-UDCA users based on patient self-report.ResultsIn the adjusted analysis, the control group was superior to the UDCA group in COVID-19 vaccination rates and liver function indicators, including γ-glutamyl transpeptidase and alkaline phosphatase (p < 0.05). UDCA was associated with a lower incidence of SARS-CoV-2 infection (UDCA 85.3% vs. control 94.2%, p = 0.002), more mild cases (80.0% vs. 72.0%, p = 0.047), and shorter median time from infection to recovery (5 vs. 7 days, p < 0.001). Logistic regression analysis showed that UDCA was a significant protective factor against COVID-19 infection (OR: 0.32, 95%CI: 0.16–0.64, p = 0.001). Furthermore, diabetes mellitus (OR: 2.48, 95%CI: 1.11–5.54, p = 0.027) and moderate/severe infection (OR: 8.94, 95%CI: 1.07–74.61, p = 0.043) were more likely to prolong the time from infection to recovery.ConclusionUDCA therapy may be beneficial in reducing COVID-19 infection risk, alleviating symptoms, and shortening the recovery time in patients with chronic liver disease. However, it should be emphasized that the conclusions were based on patient self-report rather than classical COVID-19 detection by experimental investigations. Further large clinical and experimental studies are needed to validate these findings.

Exosomes are tiny vesicles released by cells that carry communications to local and distant locations. Emerging research has revealed the role played by integrins found on the surface of exosomes in delivering information once they reach their destination. But until now, little has been known on the initial upstream steps of the migration process. Using biochemical and imaging approaches, we show here that exosomes isolated from both leukemic and healthy hematopoietic stem/progenitor cells can navigate their way from the cell of origin due to the presence of sialyl Lewis X modifications surface glycoproteins. This, in turn, allows binding to E-selectin at distant sites so the exosomes can deliver their messages. We show that when leukemic exosomes were injected into NSG mice, they traveled to the spleen and spine, sites typical of leukemic cell engraftment. This process, however, was inhibited in mice pre-treated with blocking E-selectin antibodies. Significantly, our proteomic analysis found that among the proteins contained within exosomes are signaling proteins, suggesting that exosomes are trying to deliver active cues to recipient cells that potentially alter their physiology. Intriguingly, the work outlined here also suggests that protein cargo can dynamically change upon exosome binding to receptors such as E-selectin, which thereby could alter the impact it has to regulate the physiology of the recipient cells. Furthermore, as an example of how miRNAs contained in exosomes can influence RNA expression in recipient cells, our analysis showed that miRNAs found in KG1a-derived exosomes target tumor suppressing proteins such as PTEN.

In the manufacturing process of optical lenses, the lack of monitoring and detection of the central processing process leads to low processing efficiency and difficulty in ensuring product consistency. We propose a digital twin system for alignment processing to address this issue. The system adopts a hierarchical architecture based on the digital twin five-dimensional model, aiming to improve the fidelity and interactivity of the virtual model of the centring lathe by combining dimension-driven virtual models with integrated data and physical models of the turning mechanism. We have successfully achieved the semantic and physical fusion of multi-source heterogeneous data during centring processing using information models and OPC UA-based data interaction methods. In addition, we adopted the VMD-GRU method based on feature fusion for real-time monitoring of critical components of the centring lathe. Finally, we validated the feasibility and effectiveness of the digital twin system for the central lathe through development examples. The application of this system is expected to promote the digital and intelligent development of high-precision optical component processing, providing references including references for related manufacturing fields. In summary, we propose a digital monitoring and detection system for the centring process of optical lens manufacturing. The application of this system will help improve product consistency and processing efficiency while reducing risks and costs in the manufacturing process.

The application of sericin hydrogels is limited mainly due to their poor mechanical strength, tendency to be brittle and inconvenient sterilization. To address these challenges, a sericin hydrogel exhibiting outstanding physical and chemical properties along with cytocompatibility was prepared through crosslinking genipin with degraded sericin extracted from fibroin deficient silkworm cocoons by the high temperature and pressure method. Our reported sericin hydrogels possess good elasticity, injectability, and robust behaviors. The 8% sericin hydrogel can smoothly pass through a 16 G needle. While the 12% sericin hydrogel remains intact until its compression ratio reaches 70%, accompanied by a compression strength of 674 kPa. 12% sericin hydrogel produce a maximum stretch of 740%, with breaking strength and tensile modulus of 375 kPa and 477 kPa respectively. Besides that, the hydrogel system demonstrated remarkable cell-adhesive capabilities, effectively promoting cell attachment and, proliferation. Moreover, the swelling and degradation behaviors of the hydrogels are pH responsiveness. Sericin hydrogel releases drugs in a sustained manner. Furthermore, this study addresses the challenge of sterilizing sericin hydrogels (sterilization will inevitably lead to the destruction of their structures). In addition, it challenges the prior notion that sericin extracted under high temperature and pressure is difficult to directly cross-linked into a stable hydrogel. This developed hydrogel system in this study holds promise to be a new multifunctional platform expanding the application area scope of sericin.

Galeruca daurica (Joannis) is a pest species with serious outbreaks in the Inner Mongolian grasslands in recent years, and its larvae and eggs are extremely cold-tolerant. To gain a deeper understanding of the molecular mechanism of its cold-tolerant stress response, we performed de novo transcriptome assembly of G. daurica via RNA-Seq and compared the differentially expressed genes (DEGs) of first- and second-instar larvae grown and developed indoors and outdoors, respectively. The results show that cold tolerance in G. daurica is associated with changes in gene expression mainly involved in the glycolysis/gluconeogenesis pathway, the fatty acid biosynthesis pathway and the production of heat shock proteins (HSPs). Compared with the control group (indoor), the genes associated with gluconeogenesis, fatty acid biosynthesis and HSP production were up-regulated in the larvae grown and developed outdoors. While the changes in these genes were related to the physiological metabolism and growth of insects, it was hypothesized that the proteins encoded by these genes play an important role in cold tolerance in insects. In addition, we also investigated the expression of genes related to the metabolic pathway of HSPs, and the results show that the HSP-related genes were significantly up-regulated in the larvae of G. daurica grown and developed outdoors compared with the indoor control group. Finally, we chose to induce significant expression differences in the Hsp70 gene (Hsp70A1, Hsp70-2 and Hsp70-3) via RNAi to further illustrate the role of heat stress proteins in cold tolerance on G. daurica larvae. The results show that separate and mixed injections of dsHSP70A1, dsHsp70-2 and dsHsp70-3 significantly reduced expression levels of the target genes in G. daurica larvae. The super-cooling point (SCP) and the body fluid freezing point (FP) of the test larvae were determined after RNAi using the thermocouple method, and it was found that silencing the Hsp70 genes significantly increased the SCP and FP of G. daurica larvae, which validated the role of heat shock proteins in the cold resistance of G. daurica larvae. Our findings provide an important theoretical basis for further excavating the key genes and proteins in response to extremely cold environments and analyzing the molecular mechanism of cold adaptation in insects in harsh environments.

The quality of lamb meat is positively correlated with intramuscular fat content. In recent years, a large number of studies have shown that miRNAs play an important role in the proliferation and differentiation of adipocytes. In this study, we aimed to explore the effect of miR-92a-3p on the differentiation of goat intramuscular preadipocytes. The results showed that the expression level of miR-92a-3p was low in the early stage of differentiation, reached the highest level on the third day of differentiation, and then decreased. And miR-92a-3p can inhibit the accumulation of lipid droplets and down-regulate the determinants of adipogenic differentiation. Mechanistically, by predicting target genes, we found that miR-92a-3p affects the differentiation of goat intramuscular preadipocytes and the accumulation of lipid droplets by regulating the expression of goat gene APOL6. This study provides important new information to better understand the relationship between miRNAs and the differentiation of goat intramuscular preadipocytes, thus providing a new reference for goat intramuscular adipogenesis.

Background: Accurate detection of atrial fibrillation (AF) recurrence after catheter ablation is crucial. In this study, we aimed to conduct a systematic review of machine-learning-based recurrence detection in the relevant literature. Methods: We conducted a comprehensive search of PubMed, Embase, Cochrane, and Web of Science databases from 1980 to December 31, 2022 to identify studies on prediction models for AF recurrence risk after catheter ablation. We used the prediction model risk of bias assessment tool (PROBAST) to assess the risk of bias, and R4.2.0 for meta-analysis, with subgroup analysis based on model type. Results: After screening, 40 papers were eligible for synthesis. The pooled concordance index (C-index) in the training set was 0.760 (95% confidence interval [CI] 0.739 to 0.781), the sensitivity was 0.74 (95% CI 0.69 to 0.77), and the specificity was 0.76 (95% CI 0.72 to 0.80). The combined C-index in the validation set was 0.787 (95% CI 0.752 to 0.821), the sensitivity was 0.78 (95% CI 0.73 to 0.83), and the specificity was 0.75 (95% CI 0.65 to 0.82). The subgroup analysis revealed no significant difference in the pooled C-index between models constructed based on radiomics features and those based on clinical characteristics. However, radiomics based showed a slightly higher sensitivity (training set: 0.82 vs. 0.71, validation set: 0.83 vs. 0.73). Logistic regression, one of the most common machine learning (ML) methods, exhibited an overall pooled C-index of 0.785 and 0.804 in the training and validation sets, respectively. The Convolutional Neural Networks (CNN) models outperformed these results with an overall pooled C-index of 0.862 and 0.861. Age, radiomics features, left atrial diameter, AF type, and AF duration were identified as the key modeling variables. Conclusions: ML has demonstrated excellent performance in predicting AF recurrence after catheter ablation. Logistic regression (LR) being the most widely used ML algorithm for predicting AF recurrence, also showed high accuracy. The development of risk prediction nomograms for wide application is warranted.

Goat intramuscular fat (IMF) deposition is precisely regulated by many key genes as well as transcription factors. Nevertheless, the potential of the regulators of goat IMF deposition remains undefined. In this work, we reported that the transcription factor FOS is expressed at a low level at the early differentiation stage and at a high level in late differentiation. The overexpression of FOS inhibited intramuscular adipocyte lipid accumulation and significantly downregulated the expressions of PPARγ, C/EBPβ, C/EBPα, AP2, SREBP1, FASN, ACC, HSL, and ATGL. Consistently, the knockdown of FOS, facilitated by two distinct siRNAs, significantly promoted intramuscular adipocyte lipid accumulation. Moreover, our analysis revealed multiple potential binding sites for FOS on the promoters of PPARγ, C/EBPβ, and C/EBPα. The expression changes in PPARγ, C/EBPβ, and C/EBPα during intramuscular adipogenesis were opposite to that of FOS. In summary, FOS inhibits intramuscular lipogenesis in goats and potentially negatively regulates the expressions of PPARγ, C/EBPβ, and C/EBPα genes. Our research will provide valuable data for the underlying molecular mechanism of the FOS regulation network of intramuscular lipogenesis.

Background and aims: Childhood and adolescence are critical periods for linear growth and preventing stunting. Current evidence indicates that dietary protein intake in children and adolescents is often two to three times higher than the recommendations in many regions worldwide. However, few studies have focused on the association between high protein intake and linear growth and stunting in this population. We aim to investigate this association in children and adolescents aged 6 to 18 years in a population with relatively high protein consumption. Methods: We conducted a large cross-sectional study involving 3299 participants from Shenzhen, a modern metropolis of China. Protein intake, including total protein, animal protein, and plant protein, was evaluated by a food-frequency questionnaire and expressed as grams per kilogram of body weight per day (g·kg−1·d−1) and as a percentage of total energy intake (%E). The primary outcomes were body height and height-for-age Z score (HAZ). Generalized linear models and logistic regression analyses were employed to examine the associations between protein intake and outcomes. We also conducted stratified analyses across different genders and pubertal stages in the aforementioned associations. Results: The mean protein intake was 1.81 g·kg−1·d−1 (17% E). After adjusting for serum calcium, zinc, vitamin D3, vitamin A levels, birth outcomes, lifestyle, and parental characteristics, each standard deviation increase of 1 in protein intake (0.64 kg−1·d−1) is found to be associated with a −5.78 cm change in body height (95% CI: −6.12, −5.45) and a −0.79 change in HAZ (95% CI: −0.84, −0.74). Consistent results were observed when protein intake was expressed as %E or specifically as animal or plant protein. Moreover, the relationship between protein intake and linear growth remained consistent across genders in different pubertal stages, similar to that of the overall participants. Conclusions: Our findings highlight the potential hazards of high protein intake on linear growth in children and adolescents. Caution should be exercised when promoting increased protein consumption in children and adolescents who already have a high intake of protein.

In earthquake-prone areas, pile-anchor structures are widely employed for slope reinforcement due to their reliable performance. Current research has primarily focused on static and quasi-static analyses of slopes reinforced by using pile-anchor structures, with limited investigation into their dynamic response. In this work, the finite element method (FEM) is used to study the dynamic behavior of a pile-anchor slope system, and the extended finite element method (XFEM) is used to simulate the progressive failure processes of piles. Three different reinforcement schemes, which include no support, pile support, and pile-anchor support, are considered to examine the performance of the pile-anchor structure. The simulation results suggest that the pile-anchor structure displays a reduction of 39.6% and 40.6% in the maximum shear force and bending moment of the piles, respectively, compared to the pile structure. The XFEM is utilized to model the progressive failure process of the piles subjected to seismic loading. We find that crack initiation in the pile body near the slip surface, for both the pile supported and the pile-anchor supported conditions, occurs when the peak ground acceleration arrives. Crack growth in the piles completes in a very short period, with two distinct increments of crack area observed. The first increment occurs when the peak ground acceleration arrives and is significantly larger than the second increment. Consequently, for the seismic design of piles, it is necessary to strengthen the pile body around slip surfaces. The novelty of this paper is that we realize the simulation of crack initiation and propagation in piles subjected to seismic loading.

Abstract Different argumentative discourse styles will have different effects on science learning. Some researchers proposed that two learners’ individual characteristics, including achievement goals and personality traits, could be potential factors that induce different argumentative discourse styles. However, the related empirical evidence revealing how the achievement goals and personality traits are related to discourse styles is limited. Therefore, the current study attempted to fill in this gap by conducting a self-designed collaborative scientific argumentation activity and 40 undergraduates participated. Students were arranged into ten groups with four based on their standpoints of the topic, and each team had two supporters and two opponents. Students’ achievement goals and personality traits were obtained through questionnaires, and their argumentative discourse styles were characterized by the actual argumentative moves they made during the collaborative argumentation. Through correlation analysis and stepwise regression analysis, the findings reveal that achievement goals could positively and negatively predict different types of argumentative discourse styles while the personality traits could positively predict three types of argumentative discourse styles. Pedagogical implications and future research are discussed at the end of this paper.

The neutral point clamped (NPC) three-level grid-tied converter is the key equipment connecting renewable energy and power grids. The current sensor fault caused by harsh environment may lead to the split of renewable energy. The existing sensor fault-tolerant methods will reduce the modulation ratio index of the converter system. To ensure continuous operation of the converter system and improve the modulation index, a model predictive control method based on reconstructed current is proposed in this paper. According to the relationship between fault phase current and a voltage vector, the original voltage vector is combined and classified. To maintain the stable operation of the converter and improve the utilization rate of DC voltage, two kinds of fault phase current are reconstructed with DC current, normal phase current and predicted current, respectively. Based on reconstructed three-phase current, a current predictive control model is designed, and a model predictive control method is proposed. The proposed method selects the optimal voltage vector with the cost function and reduces time delay with the current reconstruction sector. The simulation and experimental results showthat the proposed strategy can keep the NPC converter running stably with one AC sensor, and the modulation index is increased from 57.7% to 100%.

Abstract The density‐based spatial clustering of application with noise (DBSCAN) algorithm has good robustness and is widely employed to cluster vehicle trajectories for vehicle movement pattern recognition. However, the distance or similarity between two trajectories varies from tens to hundreds of thousands, and there is no effective method for determining the values of the hyperparameters eps and MinPts of DBSCAN. In addition, with increasing sizes of trajectory datasets, some trajectory clustering methods that directly analyse points and line segments incur large computational costs and time overhead. To solve these two dilemmas, the authors propose an effective trajectory dimensionality reduction method and a DBSCAN hyperparameter initial value setting method. The trajectory dimensionality reduction algorithm processes trajectories with different lengths into the same dimensionality (the same number of feature points). The reserved points preserve the spatial and temporal information of these trajectories as much as possible. The DBSCAN hyperparameter initial value setting algorithm obtains the effective initial values of eps and MinPts for facilitating subsequent adjustments. Finally, we validate these proposed methods on two trajectory datasets collected from two real‐world scenes, and the experimental results are promising and effective.

Abstract Neuropathic pain is one of the common surgical diseases, which leads to abnormal chronic pain and pain hypersensitivity reaction. Microglia are important glial cells in the spinal cord, which are conducive to sensitization and maintenance of chronic pain. Recently, Senkyunolide H (SNH) has been reported to play an anti‐inflammatory and antioxidant role. However, the mechanisms by which SNH improves neuropathic pain symptoms remain unknown. This study aimed to evaluate and identify the role of SNH in lipopolysaccharide (LPS)‐mediated neuroinflammation and oxidative stress in BV2. Western blot and immunostaining assays revealed that SNH treatment attenuated LPS‐mediated activation of BV2 in a dose‐dependent manner. Flow cytometry further verified that BV2 microglial cells gradually shifted from an M1 (pro‐inflammatory) phenotype to an M2 (anti‐inflammatory) phenotype after SNH administration. Furthermore, quantitative real‐time polymerase chain reaction and ELISA assays demonstrated that SNH treatment attenuated LPS‐mediated neuroinflammation and oxidative stress in BV2 microglial cells. Lastly, western blot assays suggested that SHN could inactivate the ERK and NF‐κB signaling pathways. Altogether, our findings have demonstrated that SNH could reverse LPS‐mediated activation of microglia, LPS‐mediated neuroinflammation and oxidative stress in BV2 via regulating the ERK and NF‐κB pathways.

Education research is increasingly focused on fostering self-regulated learning (SRL) and socially shared regulation of learning (SSRL) among students. However, previous meta-analyses have rarely focused on the specific types of regulated learning scaffolding. Therefore, this meta-analysis examines the effects of different types of regulated learning scaffolding on regulation strategies and academic performance. A total of 46 articles met the inclusion criteria and were included in the final analysis. The findings showed that overall, regulated learning scaffolding had a moderate effect (g = 0.587). In addition, moderation analyses were performed using a random effects model that focused on four types of scaffolding. The results showed that overall, composite tools had the greatest effect, while the most useful scaffolding for SRL and SSRL were group awareness tools (g = 0.61) and composite tools (g = 0.53), respectively. In terms of learning outcomes, composite tools had the greatest effect on regulation strategies, while intelligent pedagogical agents had the greatest effect on academic performance. We also performed a meta-regression analysis to identify the moderators that had the greatest influence on the effects of regulated learning scaffolding. The results showed that grade level, academic subject, and cooperation all had a significant impact. In conclusion, these findings provide evidence for validating the effectiveness of four regulated learning scaffolding and for discovering their function for SSRL, and presented some practical implications of our findings.

Background: Rhesus macaques and humans are closely related genetically and share similar physiological and pathological characteristics. Exploring the impact of diet on the early establishment of gut microbiota in non-human primates can provide relevant clinical models for healthy infant growth and development. At present, few writers have focused on the composition and changes of the intestinal microbes of infant rhesus macaques throughout their progression from birth to formula feeding after weaning. In this study, we used 16S rRNA sequencing technology to explore the composition of the intestinal flora of rhesus macaques at different ages and analyzed the trends in the microbial changes. Results: The results showed that the relative abundance of Bifidobacterium and Lactobacillus in the intestinal flora of infant rhesus macaques significantly decreased, and Prevotella increased with age. Bifidobacterium longum and Bifidobacterium breve are effective biomarkers to predict grouping. The metabolic pathways enriched in early life mainly concentrated in glycosphingolipid biosynthesis (lacto and neolacto series) and the degradation and metabolism of alcohols and esters. Conclusions: We found that age was an important factor that affected the changes in the intestinal flora. This study revealed the change trend of flora in breastfed and formula-fed infant rhesus monkeys in different growth months, and found that the dominant flora changed greatly. This research provides a medically relevant theoretical basis for understanding the healthy development of infants.

High temperature in summer is an unfavorable factor for passion fruit (Passiflora edulis), which can lead to restricted growth, short flowering period, few flower buds, low fruit setting rate, severe fruit drop, and more deformed fruit. To explore the molecular physiology mechanism of passion fruit responding to high-temperature stress, we use ‘Zhuangxiang Mibao’, a hybrid passion fruit cultivar, as the test material. Several physiological indicators were measured and compared between high-temperature (average temperature 38 °C) and normal temperature (average temperature 25 °C) conditions, including photosynthesis, chlorophyll fluorescence parameters, peroxidase activity (POD), superoxide dismutase activity (SOD) and malondialdehyde content. We performed RNA-seq analysis combined with biochemistry experiment to investigate the gene and molecular pathways that respond to high-temperature stress. The results showed that some physiological indicators in the high-temperature group, including the net photosynthetic rate, stomatal conductance, intercellular CO2 concentration, transpiration rate, and the maximum chemical quantum yield of photosystemII (PSII), were significantly lower than those of the control group. Malondialdehyde content was substantially higher than the control group, while superoxide dismutase and superoxide dismutase activities decreased to different degrees. Transcriptome sequencing analysis showed that 140 genes were up-regulated and 75 genes were down-regulated under high-temperature stress. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) annotation analysis of differentially expressed genes revealed many metabolic pathways related to high-temperature stress. Further investigation revealed that 30 genes might be related to high-temperature stress, such as chlorophyllide a oxygenase (CAO), glutathione (GSH), WRKY transcription factors (WRKY), and heat shock protein (HSP), which have also been reported in other species. The results of real-time fluorescence quantitative PCR and RNA-seq of randomly selected ten genes are consistent, which suggests that the transcriptome sequencing results were reliable. Our study provides a theoretical basis for the mechanism of passion fruit response to high-temperature stress. Also, it gives a theoretical basis for the subsequent breeding of new heat-resistant passion fruit varieties.

As a driving source for many nonlinear vortex phenomena, such as the generation of isolated attosecond optical vortices, terahertz vortices, etc., terawatt-class few-cycle short-wave infrared vortex lasers are now attracting widespread attention. However, because the vortex characteristics of optical vortices are difficult to maintain in the amplification and compression stages, the generation of high-intensity few-cycle vortex lasers is still in the exploratory stage. In this article, we report 20-Hz, 18.6-mJ, 60-fs, and 1.45-μm infrared vortex lasers with 1, 2, and 3 topological charges successfully generated in an optical parametric chirped pulse amplification system. A clean intensity node at the beam center is observed and highly stable propagation in free space is demonstrated. Moreover, this high-energy vortex pulse is spectrally broadened in multiple thin plates and temporally compressed to 10.59 fs (2.2 optical cycles) with chirped mirrors, corresponding to a peak power of 1.08 TW, while highly preserving the vortex information. We believe that the generated high-energy few-cycle vortex laser has important applications from vortex optics to strong-field physics.

Background. Ectodysplasin A (EDA), a member of the TNF family, plays important roles in ectodermal development, while recent studies expanded its regulatory effects on insulin resistance and lipid metabolism. This study was the first time to investigate the correlation between circulating EDA and albuminuria in patients with T2DM. Methods. A total of 189 T2DM and 59 healthy subjects were enrolled in the study. We analyzed the concentrations of EDA by ELISA. Plasma glucose, insulin, HbA1c, lipids, creatinine, BUN, and UACR were also measured. Insulin resistance and pancreatic cell function were assessed by HOMA. Results. Circulating EDA concentration was significantly increased in T2DM patients and increased with the degree of albuminuria. EDA was positively correlated with age, FIns, HOMA-IR, HOMA-β, Scr, and UACR, and negatively correlated with eGFR. Linear stepwise regression showed that FIns, HOMA-β, and UACR were independent influencing factors of EDA. Logistic regression analysis showed that EDA was independently associated with the occurrence of albuminuria in T2DM. ROC curve showed that EDA had an area under the receiver operating curve of 0.701 [95%CI=0.625−0.777, P

Combining physiological measures with observational data (e.g., video or self-reports) to further capture and understand the temporal and cyclical process of social regulation has become a trend in the field. Synchronized physiological arousal is a particularly meaningful situation in collaboration. However, little attention has been given to synchronized physiological arousal episodes and their relationship with the social regulatory process. In addition, only a few research utilized heart rate (HR) as a physiological measure in the current collaboration literature. More research is necessary to reveal the potential of HR to expand the diversity of physiological indicators in the field. Therefore, the current study aimed to explore what synchronized physiological arousal can further reveal about the social regulatory process. To achieve this goal, this study designed a collaborative argumentation (CA) activity for undergraduates (mean age 20.3). It developed an arousal-regulation analysis platform, which could automatically detect synchronized physiological arousal in HR and align them with coding challenges and social regulation based on the timeline. In total, 14 four-member groups were recruited. After analyzing both videos and HR data, several findings were obtained. First, only one-third of episodes were synchronized physiological arousal episodes, and the situations where four members were all in arousal states were rare during CA. Second, synchronized physiological arousal was more sensitive to socio-emotional aspects of collaboration as the shared physiological arousal more frequently co-occurred with socio-emotional challenges and socio-emotional regulation, while it happened the least under motivational challenges. Third, synchronized physiological arousal has also been found to be associated with the challenges being regulated. Finally, pedagogical implications were suggested.

Background Preoperative prediction of cervical lymph node metastasis in papillary thyroid carcinoma provided a basis for tumor staging and treatment decision. This study aimed to investigate the utility of machine learning and develop different models to preoperatively predict cervical lymph node metastasis based on ultrasonic radiomic features and clinical characteristics in papillary thyroid carcinoma nodules. Methods Data from 400 papillary thyroid carcinoma nodules were included and divided into training and validation group. With the help of machine learning, clinical characteristics and ultrasonic radiomic features were extracted and selected using randomforest and least absolute shrinkage and selection operator regression before classified by five classifiers. Finally, 10 models were built and their area under the receiver operating characteristic curve, accuracy, sensitivity, specificity, positive predictive value and negative predictive value were measured. Results Among the 10 models, RF-RF model revealed the highest area under curve (0.812) and accuracy (0.7542) in validation group. The top 10 variables of it included age, seven textural features, one shape feature and one first-order feature, in which eight were high-dimensional features. Conclusions RF-RF model showed the best predictive performance for cervical lymph node metastasis. And the importance features selected by it highlighted the unique role of higher-dimensional statistical methods for radiomics analysis.

Abstract Emerging SARS-CoV-2 variants and the gradually decreasing neutralizing antibodies over time post vaccination have led to an increase in incidents of breakthrough infection across the world. To investigate the potential protective effect of the recombinant protein subunit COVID-19 vaccine targeting receptor-binding domain (RBD) (PS-RBD) and whole inactivated virus particle vaccine (IV) against the variant strains, in this study, rhesus macaques were immunized with PS-RBD or IV vaccine, followed by a Beta variant (B.1.351) challenge. Although neutralizing activity against the Beta variant was reduced compared with that against the prototype, the decreased viral load in both upper and lower respiratory tracts, milder pathological changes, and downregulated inflammatory cytokine levels in lung tissues after challenge demonstrated that PS-RBD and IV still provided effective protection against the Beta variant in the macaque model. Furthermore, PS-RBD-induced macaque sera possessed general binding and neutralizing activity to Alpha, Beta, Delta, and Omicron variants in our study, though the neutralizing antibody (NAb) titers declined by varying degrees, demonstrating potential protection of PS-RBD against current circulating variants of concern (VOCs). Interestingly, although the IV vaccine-induced extremely low neutralizing antibody titers against the Beta variant, it still showed reduction for viral load and significantly alleviated pathological change. Other correlates of vaccine-induced protection (CoP) like antibody-dependent cellular cytotoxicity (ADCC) and immune memory were both confirmed to be existing in IV vaccinated group and possibly be involved in the protective mechanism.

Highlights Ag/BP-NS exhibit remarkable surface-enhanced Raman scattering performance with single-molecule detection ability. This remarkable enhancement can be attributed to the synergistic resonance enhancement of R6G molecular resonance, photo-induced charge transfer resonance and electromagnetic resonance. A new polarization-mapping method was proposed, which can quickly screen out single-molecule signals and prove that the obtained spectra are emitted by single molecule. The recognition of different tumor exosomes can be realized combining the method of machine learning. Abstract Single-molecule detection and imaging are of great value in chemical analysis, biomarker identification and other trace detection fields. However, the localization and visualization of single molecule are still quite a challenge. Here, we report a special-engineered nanostructure of Ag nanoparticles embedded in multi-layer black phosphorus nanosheets (Ag/BP-NS) synthesized by a unique photoreduction method as a surface-enhanced Raman scattering (SERS) sensor. Such a SERS substrate features the lowest detection limit of 10–20 mol L−1 for R6G, which is due to the three synergistic resonance enhancement of molecular resonance, photo-induced charge transfer resonance and electromagnetic resonance. We propose a polarization-mapping strategy to realize the detection and visualization of single molecule. In addition, combined with machine learning, Ag/BP-NS substrates are capable of recognition of different tumor exosomes, which is meaningful for monitoring and early warning of the cancer. This work provides a reliable strategy for the detection of single molecule and a potential candidate for the practical bio-application of SERS technology.

Abstract Using the Chinese Glioma Genome Atlas (training dataset) and The Cancer Genome Atlas (validation dataset), we found that low-grade gliomas can be divided into two molecular subclasses based on 30 pyroptosis genes. Cluster 1 presented higher immune cell and immune function scores and poorer prognosis than Cluster 2. We established a prognostic model based on 10 pyroptosis genes; the model could predict overall survival in glioma and was well validated in an independent dataset. The high-risk group had relatively higher immune cell and immune function scores and lower DNA methylation levels in pyroptosis genes than the low-risk group. There were no marked differences in pyroptosis gene alterations between the high- and low-risk groups. The competing endogenous RNA (ceRNA) regulatory network uncovered the lncRNA–miRNA–mRNA regulation patterns of the different risk groups in low-grade glioma. Five pairs of target genes and drugs were identified. In vitro, CASP8 silencing inhibited the migration and invasion of glioma cells. The expression of pyroptosis genes can reflect the molecular biological and clinical features of low-grade glioma subclasses. The developed prognostic model can predict overall survival and distinguish molecular alterations in patients. Our integrated analyses could provide valuable guidelines for improving risk management and therapy for low-grade glioma patients.

As cancer is increasingly considered a metabolic disorder, it is postulated that serum metabolite profiling can be a viable approach for detecting the presence of cancer. Here, the authors report a machine learning model using mass spectrometry-based liquid biopsy data for pan-cancer screening and classification.

Abstract Variants are globally emerging very quickly following pandemic prototypic SARS-CoV-2. To evaluate the cross-protection of prototypic SARS-CoV-2 vaccine against its variants, we vaccinated rhesus monkeys with three doses of prototypic SARS-CoV-2 inactivated vaccine, followed by challenging with emerging SARS-CoV-2 variants of concern (VOCs). These vaccinated animals produced neutralizing antibodies against Alpha, Beta, Delta, and Omicron variants, although there were certain declinations of geometric mean titer (GMT) as compared with prototypic SARS-CoV-2. Of note, in vivo this prototypic vaccine not only reduced the viral loads in nasal, throat and anal swabs, pulmonary tissues, but also improved the pathological changes in the lung infected by variants of Alpha, Beta, and Delta. In summary, the prototypic SARS-CoV-2 inactivated vaccine in this study protected against VOCs to certain extension, which is of great significance for prevention and control of COVID-19.

In order to meet the rapid growth of railway transportation demand, the technology that can improve its capacity has been widely concerned. Virtual Coupling (VC) is a new technology to improve capacity by decreasing headways between successive trains. Its basic principle is to control the train formation operation in coordination with the goal of keeping the same speed under the support of data transmission technology such as train-to-train communication. Our paper first reviews the existing theoretical research on train formation operation control, which is divided into four categories: train following, feedback control, optimal control and computational intelligent method. Secondly, by reviewing the related projects in Europe and China, based on the scenario analysis method, five general scenarios and two emergency scenarios in the whole process of VC operation are sorted out. Then, an original, complete list of performance indicators (PIs) is proposed for evaluating the performance of VC in different scenarios. Additionally, the paper gives a brief insight into VC operation by providing an adequate context to understand the proposed PIs.

The cell cycle is the fundamental cellular process of eukaryotes. Although cell-cycle-related genes have been identified in microalgae, their cell cycle progression differs from species to species. Cell enlargement in microalgae is an essential biological trait. At the same time, there are various causes of cell enlargement, such as environmental factors, especially gene mutations. In this study, we first determined the phenotypic and biochemical characteristics of a previously obtained enlarged-cell-size mutant of Nannochloropsis oceanica, which was designated ECS. Whole-genome sequencing analysis of the insertion sites of ECS indicated that the insertion fragment is integrated inside the 5′-UTR of U/P-type cyclin CYCU;1 and significantly decreases the gene expression of this cyclin. In addition, the transcriptome showed that CYCU;1 is a highly expressed cyclin. Furthermore, cell cycle analysis and RT-qPCR of cell-cycle-related genes showed that ECS maintains a high proportion of 4C cells and a low proportion of 1C cells, and the expression level of CYCU;1 in wild-type (WT) cells is significantly increased at the end of the light phase and the beginning of the dark phase. This means that CYCU;1 is involved in cell division in the dark phase. Our results explain the reason for the larger ECS size. Mutation of CYCU;1 leads to the failure of ECS to fully complete cell division in the dark phase, resulting in an enlargement of the cell size and a decrease in cell density, which is helpful to understand the function of CYCU;1 in the Nannochloropsis cell cycle.

Current COVID-19 vaccines are effective countermeasures to control the SARS-CoV-2 virus pandemic by inducing systemic immune responses through intramuscular injection. However, respiratory mucosal immunization will be needed to elicit local sterilizing immunity to prevent virus replication in the nasopharynx, shedding, and transmission. In this study, we first compared the immunoprotective ability of a chimpanzee replication–deficient adenovirus–vectored COVID-19 vaccine expressing a stabilized pre–fusion spike glycoprotein from the ancestral SARS-CoV-2 strain Wuhan–Hu–1 (BV-AdCoV-1) administered through either aerosol inhalation, intranasal spray, or intramuscular injection in cynomolgus monkeys and rhesus macaques. Compared with intranasal administration, aerosol inhalation of BV-AdCoV-1 elicited stronger humoral and mucosal immunity that conferred excellent protection against SARS-CoV-2 infection in rhesus macaques. Importantly, aerosol inhalation induced immunity comparable to that obtained by intramuscular injection, although at a significantly lower dose. Furthermore, to address the problem of immune escape variants, we evaluated the merits of heterologous boosting with an adenovirus–based Omicron BA.1 vaccine (C68–COA04). Boosting rhesus macaques vaccinated with two doses of BV-AdCoV-1 with either the homologous or the heterologous C68–COA04 vector resulted in cross–neutralizing immunity against WT, Delta, and Omicron subvariants, including BA.4/5 stronger than that obtained by administering a bivalent BV-AdCoV-1/C68–COA04 vaccine. These results demonstrate that the administration of BV-AdCoV-1 or C68–COA04 via aerosol inhalation is a promising approach to prevent SARS-CoV-2 infection and transmission and curtail the pandemic spread.

The nonstationary characteristics caused by significant variation in hydrometeorological series in the context of climate change inevitably have a certain impact on the selection of an optimal gauging network. This study proposes an entropy-based, multi-objective, rain gauge network optimization method to facilitate the design of a 43 stations-based network in Huaihe River Basin (HRB), China. The first goal of this study is to improve the accuracy of gauge-related information estimation through the selection and comparison of discretization methods. The second goal of this study is to quantify the impact of trend-caused nonstationarity on optimal network design using the sliding window method. This study compares the divergence of three kinds of discretization methods, including the floor function-based approach, Scott’s equal bin width histogram (EWH-Sc) approach, and Sturges’s equal bin width histogram (EWH-St) approach. The matching degree of the variance and marginal entropy of the observed series is computed to select the most suitable of the above three discretization methods. The trend-caused nonstationarity in 75% of all stations in the HRB could definitely influence the final results of the optimal rain-gauge network design using the sliding window method. Therefore, in future studies of rain-gauge network optimization, it is necessary to carry out uncertainty research according to local conditions in view of climate change and human activities.

Deep rock formations in extreme environments are characterized by complex working conditions, various structures, high hardness, and high resistance to compression. However, existing coring techniques leave the cores of deep rock formations vulnerable to residual stresses, resulting in poor fidelity during deep coring. This paper develops a rock-breaking model for the structural parameters of drill bits. It proposes that a drill bit’s structural parameters in terms of back-rake and side-rake angles will affect the core’s fidelity performance. In addition, the core’s mechanical specific energy and maximum stress will reflect the fidelity effect. The accuracy of the theoretical model was verified via simulation analysis. The simulation results show that the tool’s average cutting force and Standard deviation of cutting force increase as the drill bit’s back-rake and side-rake angles vary. This leads to increased shear friction on the core, which affects the maximum stress and mechanical specific energy, and, subsequently, the fidelity of the core. The back-rake angles ranged from 15° to 25°, with the optimum back-rake angle of 21° producing a maximum stress and a mechanical specific energy that were 0.69 and 0.85 times higher than the highest point, respectively. The side-rake angles range from 5° to 15°, with the optimum side-rake angle of 10° producing a maximum stress and a mechanical specific energy that were 0.76 and 0.96 times higher than the highest point, respectively. The finite element method error was 1.21%. This work’s main results will help reveal the fidelity mechanisms of the drilling process and contribute to the development of fidelity drill bits for complex surface drilling processes.

Abstract To address the problem of insufficient system inertia and improve the power quality of grid-connected inverters, and to enhance the stability of the power system, a method to control a virtual synchronous generator (VSG) output voltage based on model predictive control (MPC) is proposed. Parameters of the inductors, capacitors and other components of the VSG can vary as the temperature and current changes. Consequently the VSG output voltage and power control accuracy using the conventional MPC method may be reduced. In this paper, to improve the parameter robustness of the MPC method, a new weighted predictive capacitor voltage control method is proposed. Through detailed theoretical analysis, the principle of the proposed method to reduce the influence of parameter errors on voltage tracking accuracy is analyzed. Finally, the effectiveness and feasibility of the proposed method are verified by experimental tests using the Typhoon control hardware-in-the-loop experimental platform.

Abstract Background Pancreatic cancer is one of the most common malignancies worldwide. In recent years, specific metabolic activities, which involves the development of tumor, caused wide public concern. In this study, we wish to explore the correlation between metabolism and progression of tumor. Methods A retrospective analysis including 95 patients with pancreatic ductal adenocarcinoma (PDAC) and PDAC patients from The Cancer Genome Atlas (TCGA), the International Cancer Genome Consortium (ICGC), and The Gene Expression Omnibus (GEO) database were involved in our study. Multivariate Cox regression analysis was used to construct the prognosis model. The potential connection between metabolism and immunity of PDAC was investigated through a weighted gene co-expression network analysis (WGCNA). 22 types of Tumor-infiltrating immune cells (TIICs) between high-risk and low-risk groups were estimated through CIBERSORT. Moreover, the potential immune-related signaling pathways between high-risk and low-risk groups were explored through the gene set enrichment analysis (GSEA). The role of key gene GMPS in developing pancreatic tumor was further investigated through CCK-8, colony-information, and Transwell. Results The prognostic value of the MetS factors was analyzed using the Cox regression model, and a clinical MetS-based nomogram was established. Then, we established a metabolism-related signature to predict the prognosis of PDAC patients based on the TCGA databases and was validated in the ICGC database and the GEO database to find the distinct molecular mechanism of MetS genes in PDAC. The result of WGCNA showed that the blue module was associated with risk score, and genes in the blue module were found to be enriched in the immune-related signaling pathway. Furthermore, the result of CIBERSORT demonstrated that proportions of T cells CD8, T cells Regulatory, Tregs NK cells Activated, Dendritic cells Activated, and Mast cells Resting were different between high-risk and low-risk groups. These differences are potential causes of different prognoses of PDAC patients. GSEA and the protein–protein interaction network (PPI) further revealed that our metabolism-related signature was significantly enriched in immune‐related biological processes. Moreover, knockdown of GMPS in PDAC cells suppressed proliferation, migration, and invasion of tumor cells, whereas overexpression of GMPS performed oppositely. Conclusion The results shine light on fundamental mechanisms of metabolic genes on PDAC and establish a reliable and referable signature to evaluate the prognosis of PDAC. GMPS was identified as a potential candidate oncogene with in PDAC, which can be a novel biomarker and therapeutic target for PDAC treatment.

In this paper, the authors describe a method for exploring the feasibility of using Natural Language Processing (NLP) and Machine Learning (ML) techniques to analyze patient safety incident database reports for themes. We developed a novel thematic analysis strategy to automatically detect keywords and latent themes that describe HIT-related patient safety incidents. The strategy was applied to patient safety reports to test the approach. The efforts by the automated strategy were compared to the efforts by analysts who manually reviewed and identified key words, topics, and themes for the same reports. The computer-based error themes were also compared to the human-determined themes for crosschecking. The manual thematic analysis took about 150 hours to complete on the patient safety reports. The semi-automated approach took only 10% of that time. 95% of the themes extracted from the automated method were aligned with the themes from the manual process. The findings underscore the utility of NLP and ML in identifying thematic patterns embedded in large numbers of unstructured data. The NLP-ML method therefore represents a valuable addition to the tools of detecting and understanding HIT-related errors.

To test whether praseodymium (Pr) regulates cadmium (Cd) tolerance, we explored the effects of Pr on enzymatic activities in the regeneration and biosynthetic pathways of ascorbate and glutathione in maize seedlings under Cd stress. The findings demonstrated that Cd stress increased enzymatic activities in the regeneration pathway (ascorbate peroxidase (APX), dehydroascorbate reductase (DHAR), glutathione reductase (GR), monodehydroascorbate reductase (MDHAR)) and in the biosynthetic pathway of ascorbate and glutathione (γ-ECS and GalLDH), as well as ascorbate (AsA) and glutathione (GSH) contents. However, Cd stress significantly decreased AsA/dehydroascorbic acid (DHA) ratio and GSH/oxidised glutathione (GSSG) ratio, net photosynthetic rate (Pn), chlorophylls (Chl) and carotenoids (Car) contents, maximum photochemical efficiency of PSII (Fv/Fm), photochemical quenching (qP) and quantum efficiency of PSII photochemistry (ΦPSII), as well as plant height and biomass. Application of Pr to Cd-stressed seedlings enhanced above enzymatic activities, AsA and GSH contents, AsA/DHA and GSH/GSSG ratios, Pn, Chl and Car contents, Fv/Fm, qP and ΦPSII, as well as plant height and biomass. Meanwhile, the application of Pr to Cd-stressed seedlings reduced malondialdehyde (MDA) content and electrolyte leakage. The above results indicated

How to identify deformed landslides in advance and conduct early risk assessments on them has become a research hotspot in the field of geological disaster prevention and control. In response to the above problems, the Jiangdingya landslide in the Bailong River Basin in Zhouqu is taken as a back analysis case, and a comprehensive study of the early identification and risk assessment of the landslide is carried out. In this paper, a full-process analysis method is proposed, which combine the small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) technology interpretation, geo-mechanical analysis and dynamic process simulation. The research results show that the SABS-InSAR technology interpretation can effectively identify the range of the Jiangdingya landslide and its early deformation. It may be preliminarily determined that the failure mode of the Jiangdingya landslide is trailed and the plane characteristics of the landslide body is generally about 680 m in length and 210 m in width. Based on the early identification information and through geo-mechanical analysis, it is finally identified that the instability problem of the Jiangdingya landslide is a typical deformation problem of the front edge of the old accumulation layer landslide. The failure mode is the traction slip failure, the average thickness of the landslide body is in about 35 m, the overall slope of the sliding bed is relatively slow, and the moving speed is not large after instability. On the basis of the above analyses, a Coulomb friction model that conformed to the sliding friction characteristics of the Jiangdingya landslide body is selected. Based on the depth integral continuum equation, the dynamic process of the Jiangdingya landslide body is calculated and the speed of the landslide body is monitored. In terms of velocity monitoring curves and accumulation pattern, the sliding velocity of the landslide body is not large, the maximum value is about 2.2 m/s, the overall performance is pushing the Bailong River channel, and the possibility of blocking the river is relatively small. In addition, when the displacement of the front edge of the Jiangdingya landslide body is completed, the speed of the landslide body from the front edge to the rear edge quickly drope to zero, and the movement process is characterized by the traction movement. The analysis results of the Jiangdingya landslide in this paper are consistent with the actual event of the Jiangdingya landslide. The comprehensive analysis method and research model can provide a good reference for the early identification and risk assessment of similar landslides in the Bailong River Basin in Zhouqu county.

Abstract A novel night‐time image enhancement approach was proposed in this paper to address the problems of low contrast and poor details of low‐illumination images captured at night. To begin with, the luminance component V was extracted that was irrelevant to the colour information of the image upon converting the image to the HSV space from the RGB space. Then, by converting the luminance component V of the image into the probability space, the image was divided into a small‐probability grey‐scale area and a normal area based on the theory of probability. Moreover, pixels were transferred from the small probability area to the normal area of the image according to the nearest attribution principle that was established. Lastly, the contrast enhancement of the image was realized thanks to lossless mapping functions without losing the number of grey levels of the image. As can be observed from experimental results, the proposed method is superior to the most advanced algorithm in visual quality and quantitative measurement.

Abstract Background We aimed to investigate the predictive value of recently updated ACEF II score on major adverse cardiac and cerebrovascular events (MACCE) in patients with multi-vessel coronary artery disease (MVCAD) undergoing one-stop hybrid coronary revascularization (HCR). Methods Patients with MVCAD undergoing one-stop HCR were retrospectively recruited from March 2018 to September 2020. Several prediction risk models, including ACEF II score, were calculated for each patient. Kaplan-Meier curve was used to evaluate freedom from cardiac death and MACCE survival rates. Differences of prediction performance among risk scores for predicting MACCE were compared by receiver operating characteristic (ROC) curve. Results According to the ACEF II score, a total of 120 patients undergoing one-stop HCR were assigned to low-score group (80 cases) and high-score group (40 cases). During the median follow-up time of 18 months, the incidence of MACCE in the low-score group and high-score group were 8.8 % and 37.5 %, respectively (p

Purpose: To identify the characteristics and subtypes of depressive symptoms and explore the relationship between depressive subtypes and age among Chinese female breast cancer patients. Method: In this cross-sectional study, 566 breast cancer patients were recruited from three tertiary comprehensive hospital in Shandong Province, China through convenient sampling from April 2013 to June 2019. Depressive symptoms were measured using the Patient Health Questionnaire-9 (PHQ-9). Data analyses included descriptive analyses, latent class analysis. Results: There were significant differences in specific depressive symptoms by age group, but no significant difference in total scores on PHQ-9. The depressive subtypes were severe (Class 4), relatively severe (Class 3; with lower psychomotor agitation/retardation and suicidal ideation), moderate (Class 2; with higher psychomotor agitation/retardation and suicidal ideation), and mild depressive symptoms (Class 1). The distribution of depression subtypes is different in various age groups. In the 45–59 age groups, severe symptoms subtype showed the highest ratios (i.e. 50.3%). Conclusion: This is the first study that analyses depressive symptom characteristics and identifies depressive subtypes in Chinese women with breast cancer across ages to explore symptom heterogeneity. Our findings can contribute to identifying the mechanisms behind these relationships and developing targeted interventions for patients with specific depressive subtypes.

In recent years, the leaf beetle Galeruca daurica has broken out in the northern grasslands of Inner Mongolia, its management still mainly depends on chemical control using traditional insecticides or with novel action. The study was aim to identify mutation locus associated with resistance to diamide insecticides in field population of G. daurica, to provide a reference for rational selection of insecticides and to avoid the rapid resistance development to diamide insecticides. We cloned the full length of the ryanodine receptor gene of G. daurica (GdRyR), constructed 3D model and transmembrane regions by homologous modeling based on deduced amino acid sequence. Two potential mutation loci (Gly4911Glu and Ile4754Met) and allelic mutation frequencies were detected in individuals of G. daurica. In addition, their binding patterns to two diamide insecticides (chlorantraniliprole, cyantraniliprole) were analyzed separately using a molecular docking method. The full-length cDNA sequence of GdRyR (GenBank accession number: OP828593) was obtained by splicing and assembling, which is 15,399 bp in length and encodes 5,133 amino acids. The amino acid similarity of GdRyR with that of other Coleopteran insects were 86.70%–91.33%, which possessed the typical structural characteristics. An individual resistance allelic mutation frequency test on fifty field leaf beetles has identified 12% and 32% heterozygous individuals at two potential mutation loci Gly4911Glu and Ile4754Met, respectively. The affinity of the I4754M mutant model of GdRyR for chlorantraniliprole and cyantraniliprole was not significantly different from that of the wild type, and all had non-covalent interactions such as hydrogen bonding, hydrophobic interactions and π-cation interactions. However, the G4911E mutant model showed reduced affinity and reduced mode of action with two diamide insecticides, thus affecting the binding stability of the ryanodine receptor to the diamide insecticides. In conclusion, the G4911E mutation in GdRyR may be a potential mechanism for the development of resistance to diamide insecticides on G. daurica and should be a key concern for resistance risk assessment and reasonable applications of diamide insecticides for control in future. Moreover, this study could provide a reference for ryanodine receptor structure-based insecticides design.

Although massive open online courses (MOOCs) increase the number of choices in higher education and enhance learning, their low completion rate remains problematic. Previous studies have shown that learning engagement is a crucial factor influencing learning success and learner retention. However, few literature reviews on learning engagement in MOOCs have been conducted, and specific data analysis methods are lacking. Moreover, the internal and external factors that affect learning engagement have not been fully elucidated. Therefore, this systematic literature review summarized articles pertaining to learning engagement in MOOCs published from 2015 to 2022. Thirty articles met the inclusion and quality assurance criteria. We found that (1) learning engagement can be measured through analysis of log, text, image, interview, and survey data; (2) measures that have been used to analyze learning engagement include self-report (e.g., the Online Learning Engagement Scale, Online Student Engagement Questionnaire, and MOOC Engagement Scale) and automatic analysis methods [e.g., convolutional neural network (CNN), bidirectional encoder representations from transformers-CNN, K-means clustering, and semantic network analysis]; and (3) factors affecting learning engagement can be classified as internal (learning satisfaction, etc.) or external (curriculum design, etc.). Future research should obtain more diverse, multimodal data pertaining to social engagement. Second, researchers should employ automatic analysis methods to improve measurement accuracy. Finally, course instructors should provide technical support (“scaffolding”) for self-regulated learning to enhance student engagement with MOOCs.

IntroductionTrace element metabolism disorders are often secondary to disorders of glucose metabolism in diabetes. Although 1α,25-dihydroxyvitamin D3 [1,25(OH)2D3] could ameliorate abnormal glucose metabolism in the development of diabetes, the effect on trace element metabolism is unclear. The objective of this study was to evaluate the influence of 1,25(OH)2D3 on urinary excretions of trace elements in Zucker diabetic fatty (ZDF) rats.MethodsAt 6 weeks of age, male ZDF (n = 40) rats were subdivided into four groups: diabetic model (ZDF), low-dose (ZDF + VL, 2 μg/kg⋅bw), middle-dose (ZDF + VM, 8 μg/kg⋅bw) and high-dose (ZDF + VH, 16 μg/kg⋅bw) 1,25(OH)2D3 groups. Another 10 Zucker lean (ZL) rats served as a control group. All rats were given vitamin D deficient Purina #5008 chow and the intervention groups were given the corresponding dose of 1,25(OH)2D3 by gavage on alternate days for 7 weeks. Microalbuminuria (MALB) and urinary creatinine concentration were detected by a biochemical autoanalyzer. Urine trace element concentrations were measured using inductively coupled plasma mass spectrometry (ICP-MS) and were corrected by urinary creatinine.ResultsThroughout the intervention phase, MALB, UACR and urinary creatinine levels in the ZDF group were significantly higher than those in the ZL group, and showed a gradual increase with the prolongation of the intervention time. These changes were reversed in a dose-dependent manner after 1,25(OH)2D3 intervention (P < 0.05). Correspondingly, most of the urinary trace element excretions in the ZDF rats were significantly increased compared with the ZL group, and 1,25(OH)2D3 intervention significantly reduced the urinary copper (Cu), zinc (Zn), selenium (Se) and molybdenum (Mo) levels in the ZDF rats (P < 0.05), especially in the medium and high dose groups.Conclusion1,25(OH)2D3 had improvement effects on urinary Cu, Zn, Se, and Mo excretions in ZDF rats, suggesting that it may be related to the reduction of diabetic renal impairment and renal oxidative damage.

Determining the amount of a drug transferred into breast milk is critical for benefit-risk analysis of breastfeeding when a lactating mother takes medications. In this study, we developed a human mammary epithelial cell (MEC)-based permeability assay to assess drug permeability across the mammary epithelium. Human MEC cell MCF10F formed tight junctions when cultured on Transwells with culture medium containing insulin, hydrocortisone and epidermal growth factor (EGF). Formation of integral cell barrier and morphology of the cells were confirmed by assessing trans-epithelial electrical resistance (TEER), flux of fluorescent tracers and imaging with transmission electron microscopy (TEM). MCF10F cells showed consistent P-glycoprotein (P-gp) transporter expression when culturing on Transwell inserts versus on petri dish. A few P-gp transporter drug substrates were used to estimate the permeability from this assay. Human plasma and breast milk were used as incubation medium in basolateral and apical chambers respectively to mimic physiological conditions. The predicted milk to plasma (M/P) ratios were reasonably good. The current effort to develop the MEC-based permeability assay to facilitate M/P ratio prediction showed promising results. This assay may have a potential to be developed as a useful in vitro technique for determining the transfer of small-molecule therapeutic drugs into breast milk.

The quadrivalent human papillomavirus (4vHPV) vaccine has shown confirmative effectiveness in preventing HPV-related diseases among women and men around the globe. The phase III, randomized, double-blind efficacy study (Base study, NCT00834106) conducted in China showed 100% efficacy against HPV 16/18-related cervical intraepithelial neoplasia and efficacy against HPV persistent infection for 78 months. Participants aged 20–45 years who received three doses of 4vHPV vaccine or placebo during the base study were selected and invited for this long-term follow-up (LTFU) study to assess the long-term effectiveness of the 4vHPV vaccine in preventing HPV-related diseases. A total of 368 participants were included in this LTFU study with a median follow-up of 94 months. Among 27 participants (Vaccine vs. Placebo: 8 vs. 19) who underwent colposcopy and biopsy due to cervical cytological abnormalities or HPV infection, no HPV-16/18-related cases of cervical intraepithelial neoplasia (CIN), vulvar intraepithelial neoplasia (VIN), or vaginal intraepithelial neoplasia (VaIN) was observed in the vaccine group while two HPV-16-related cases (CIN1/VaIN) were observed in the placebo group. There were another two HPV-related cases (non-vaccine HPV types) found in the placebo group. Consistent with the findings from global studies that suggested long-term efficacy of 4vHPV vaccine, our study showed continued protective effect of 4vHPV vaccine against HPV-related precancerous diseases through a median follow-up time of 94 months with the longest follow-up time of 125 months after completing three doses of vaccination among Chinese women 20–45 years of age.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignant tumors with a poor prognosis. Type X collagen α 1 chain (COL10A1), a member of the collagen family, is a gene associated with the progression of a variety of human tumors, but the specific function and molecular mechanism of COL10A1 in pancreatic cancer remain unclear. Our study found that COL10A1 is highly expressed in pancreatic cancer cells and tissues, and its high expression is related to poor prognosis and some clinicopathological features, such as tumor size and differentiation. Biological functional experiments showed that overexpression of COL10A1 enhanced the proliferation and migration of PDAC cells. Interestingly, discoid protein domain receptor 2 (DDR2), the receptor of COL10A1, is regulated by COL10A1. We found that the COL10A1-DDR2 axis activates the mitogen-activated protein kinase (MEK)/extracellular signal-regulated kinase (ERK) pathway, which leads to epithelial-mesenchymal transformation (EMT) and accelerates the progression of pancreatic cancer. In summary, COL10A1 regulates PDAC cell proliferation and MEK/ERK signaling pathways by binding to DDR2 to promote migration, invasion and EMT. Our study suggested that COL10A1 might be a critical factor in promoting PDAC progression. More research is needed to confirm COL10A1 as a potential biomarker and therapeutic target for PDAC.