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Abstract Oncolytic virotherapy is emerging as a promising therapeutic avenue for cancer treatment, harnessing both innate and tumor-specific immune responses for targeted tumor elimination. In this study, we present a novel oncolytic virus (oHSV1-IL15B) derived from herpes simplex virus-1 (HSV-1), armed with IL-15/IL-15Rα complex, with a focus on treating colon cancer combined with oncolytic HSV-1 expressing anti-PD-1 antibody (oHSV1-aPD1). Results from our study reveal that recombinant oHSV-1 virus equipped with IL-15/IL-15Rα complex exhibited significant anti-tumor effects in a murine CT26 colon adenocarcinoma model. Notably, oHSV1-IL15B combined with oHSV-1-aPD1 demonstrates superior tumor inhibition and prolonged overall survival compared to oHSV1-mock and monotherapy groups. Further exploration highlights the impact of oHSV1-IL15B, oHSV-1-aPD1 and combined group on antitumor capacity, revealing a substantial increase in CD8+ T and CD4+ T cell proportions of CT26-bearing BALB/c mice and promoting apoptosis in tumor tissue. The study emphasizes the pivotal role of cytotoxic CD8+T cells in oncolytic virotherapy, demonstrating that recombinant oHSV1-IL15B combined with oncolytic HSV-1-aPD1 induces a robust tumor-specific T cell response. RNA sequence analysis highlighted oHSV1-IL15B combined with oHSV1-aPD1 improved tumors immune microenvironment on immune response, antiviral response-related genes and apoptosis-related genes, which contributed to anti-tumor immunotherapy. The findings underscore the promising antitumor activity achieved through the combination of IL-15/IL-15Rα complex and anti-PD-1 antibody with oHSV-1. This research opens avenues for diverse therapeutic strategies, suggesting the potential of synergistically utilizing cytokines and anti-PD-1 antibody with oncolytic viruses to enhance immunotherapy for cancer management.

Industrial Internet combines the industrial system with Internet connectivity to build a new manufacturing and service system covering the entire industry chain and value chain. Its highly heterogeneous network structure and diversified application requirements call for the applying of network slicing technology. Guaranteeing robust network slicing is essential for Industrial Internet, but it faces the challenge of complex slice topologies caused by the intricate interaction relationships among Network Functions (NFs) composing the slice. Existing works have not concerned the strengthening problem of industrial network slicing regarding its complex network properties. Towards this end, we aim to study this issue by intelligently selecting a subset of most valuable NFs with the minimum cost to satisfy the strengthening requirements. State-of-the-art AlphaGo series of algorithms and the advanced graph neural network technology are combined to build the solution. Simulation results demonstrate the superior performance of our scheme compared to the benchmark schemes.

Abstract Background Sexual differences across molecular levels profoundly impact cancer biology and outcomes. Patient gender significantly influences drug responses, with divergent reactions between men and women to the same drugs. Despite databases on sex differences in human tissues, understanding regulations of sex disparities in cancer is limited. These resources lack detailed mechanistic studies on sex-biased molecules. Methods In this study, we conducted a comprehensive examination of molecular distinctions and regulatory networks across 27 cancer types, delving into sex-biased effects. Our analyses encompassed sex-biased competitive endogenous RNA networks, regulatory networks involving sex-biased RNA binding protein-exon skipping events, sex-biased transcription factor-gene regulatory networks, as well as sex-biased expression quantitative trait loci, sex-biased expression quantitative trait methylation, sex-biased splicing quantitative trait loci, and the identification of sex-biased cancer therapeutic drug target genes. All findings from these analyses are accessible on SexAnnoDB ( https://ccsm.uth.edu/SexAnnoDB/ ). Results From these analyses, we defined 126 cancer therapeutic target sex-associated genes. Among them, 9 genes showed sex-biased at both the mRNA and protein levels. Specifically, S100A9 was the target of five drugs, of which calcium has been approved by the FDA for the treatment of colon and rectal cancers. Transcription factor (TF)-gene regulatory network analysis suggested that four TFs in the SARC male group targeted S100A9 and upregulated the expression of S100A9 in these patients. Promoter region methylation status was only associated with S100A9 expression in KIRP female patients. Hypermethylation inhibited S100A9 expression and was responsible for the downregulation of S100A9 in these female patients. Conclusions Comprehensive network and association analyses indicated that the sex differences at the transcriptome level were partially the result of corresponding sex-biased epigenetic and genetic molecules. Overall, SexAnnoDB offers a discipline-specific search platform that could potentially assist basic experimental researchers or physicians in developing personalized treatment plans.

Abstract Background Since May 2022, mpox outbreaks have been occurring in non-mpox endemic areas, with the main population affected being men who have sex with men (MSM). Outbreak prevention and control depend not only on the effectiveness of vaccines but also on people’s willingness to receive these vaccines. Currently, there is lack of synthesis on the overall rates and influence factors of MSMs’ willingness to vaccinate against mpox. Therefore, we systematically reviewed studies that assessed the willingness of MSM to receive mpox vaccine. Methods Studies reporting mpox vaccination intentions among MSM were included by searching five databases (PubMed, Web of Science, EMBASE, CINAHL, and SCOPUS) from inception to May 12, 2024. The quality of the included literature was assessed using Joanna Briggs Institute’s critical appraisal tool. The data analysis software is Stata17. The systematic review has been registered with Prospero (registration ID: CRD42023452357). Results Twenty cross-sectional studies were included in the review. Meta-analysis results showed that the pooled willingness rate of vaccinate against mpox was 77.0% (95% CI: 73-81%, I2 = 99.4%). According to subgroup analysis, study countries (P = 0.002), research sample size (P = 0.001), and whether participants were infected with HIV (P = 0.002) may be sources of heterogeneity. The results of the meta-analysis of influencing factors showed that more number of sexual partners (OR: 2.24, 95%CI: 1.86–2.69), pre-exposure prophylaxis use (OR: 6.04, 95%CI: 4.80–7.61), history of sexually transmitted infections (OR: 2.96, 95%CI: 2.33–3.76), confidence in the vaccine’s effectiveness (OR: 2.79, 95%CI: 2.04–3.80) and safety (OR: 10.89, 95%CI: 5.22–22.72), fear of mpox infection (OR: 2.47, 95%CI: 2.11–2.89) and epidemics (OR: 2.87, 95%CI: 2.22–3.70), high mpox knowledge (OR: 2.35, 95%CI: 1.51–3.66), and the belief that people at high risk should be prioritized for vaccination (OR: 3.09, 95%CI: 1.40–6.84) were the facilitators of vaccine willingness. In addition, as a secondary outcome, meta-analysis results showed a pooled unwillingness rate of 16% (95% CI: 13-20%, I2 = 98.1%, 9 studies). Conclusion Willingness to vaccinate mpox was high among MSM, but some participants still had negative attitudes towards vaccination. Therefore, the Ministry of Public Health should develop targeted and effective strategies against those influencing factors to prevent and manage mpox outbreaks.

Abstract Rhizome rot is a destructive soil-borne disease of Polygonatum kingianum and adversely affects the yield and sustenance of the plant. Understanding how the causal fungus Fusarium oxysporum infects P. kingianum may suggest effective control measures against rhizome rot. In germinating conidia of infectious F. oxysporum, expression of the zinc finger transcription factor gene Zfp1, consisting of two C2H2 motifs, was up-regulated. To characterize the critical role of ZFP1, we generated independent deletion mutants (zfp1) and complemented one mutant with a transgenic copy of ZFP1 (zfp1 tZFP1). Mycelial growth and conidial production of zfp1 were slower than those of wild type (ZFP1) and zfp1 tZFP1. Additionally, a reduced inhibition of growth suggested zfp1 was less sensitive to conditions promoting cell wall and osmotic stresses than ZFP1 and zfp1 tZFP1. Furthermore pathogenicity tests suggested a critical role for growth of zfp1 in infected leaves and rhizomes of P. kingianum. Thus ZFP1 is important for mycelial growth, conidiation, osmoregulation, and pathogenicity in P. kingianum.

Abstract The construction of an ecologically livable rural environment requires treating rural domestic waste. Farmers, as key participants in rural domestic waste disposal, can improve the rural environment by disposing of domestic waste in an environmentally friendly manner. Few studies have examined the cadre–farmer relationship and its impact on rural waste pollution. Using a questionnaire survey of farmers in Shaanxi Province, China, this study estimates the effect of cadre–farmer relationship on their willingness to treat domestic waste. The findings indicate that a positive cadre–farmer relationship significantly increases farmers’ willingness to treat domestic waste. This positive relationship can also strengthen the positive effects of institutional rules on waste treatment willingness. Further mechanism analysis shows that a good cadre–farmer relationship mobilizes farmers to protect the environment and to comply with national ecological laws and regulations, enhancing their willingness to treat domestic waste. These findings enrich research on rural domestic waste management.

Dendrobium is a precious Chinese herbal medicine, which belongs to the genus Orchidaceae. Ancient records and modern pharmacological research show that Dendrobium has pharmacological effects such as anti-tumor, antioxidant regulating immunity and blood glucose, and anti-aging. Dendrobium contains polysaccharides, alkaloids, bibenzyl, sesquiterpenes, phenanthrene, polyphenols and other types of chemicals. Its pharmacological activity is closely related to these chemical components. For example, dendrobium extracts can achieve anti-tumor effects by inhibiting tumor cell proliferation and metastasis, promoting cell apoptosis and ferroptosis, or increasing cell sensitivity to chemotherapy drugs. It enhances immunity by regulating immune cell activity or cytokine release. In addition, it can alleviate neurodegenerative diseases by protecting nerve cells from apoptotic damage. In recent years, research reports on biologically active compounds in Dendrobium have shown a blowout growth, which makes us realize that it is meaningful to continuously update the research progress on the components and pharmacological regulatory mechanism of this traditional Chinese medicine. By classifying the collected chemical components according to different chemical structures and summarizing their pharmacological mechanisms, we investigated the current research progress of Dendrobium and provide a more comprehensive scientific foundation for the further development and clinical transformation of Dendrobium in the future.

Abstract Clarifying migration timing and its link with underlying drivers is fundamental to understanding the evolution of bird migration. However, previous studies have focused mainly on environmental drivers such as the latitudes of seasonal distributions and migration distance, while the effect of intrinsic biological traits remains unclear. Here, we compile a global dataset on the annual cycle of migratory birds obtained by tracking 1531 individuals and 177 populations from 186 species, and investigate how body mass, a key intrinsic biological trait, influenced timings of the annual cycle using Bayesian structural equation models. We find that body mass has a strong direct effect on departure date from non-breeding and breeding sites, and indirect effects on arrival date at breeding and non-breeding sites, mainly through its effects on migration distance and a carry-over effect. Our results suggest that environmental factors strongly affect the timing of spring migration, while body mass affects the timing of both spring and autumn migration. Our study provides a new foundation for future research on the causes of species distribution and movement.

Background This study aimed to analyse the expression of microRNA-223 (miR-223) in embryo culture medium and its correlation with pregnancy outcomes.Methods Two hundred and two patients undergoing in vitro fertilisation/intracytoplasmic sperm injection (IVF/ICSI) were divided into clinical pregnancy group (n = 101) and non-pregnant group (n = 101). The baseline data, clinical indicators, and the expression level of miR-223 in the embryo medium were compared between the two groups. Logistic regression analysis was used to analyse the relationship between each index and the pregnancy outcome. Receiver operator characteristic curve was carried out to evaluate the differential ability of miR-223 in pregnancy status. Bioinformatics methods were used to identify the target genes of miR-223 and elucidate their functions.Results Compared with pregnancy group, the non-pregnancy group exhibited a reduction in miR-223 expression (p

Abstract In recent years, the integration of single‐cell multi‐omics data has provided a more comprehensive understanding of cell functions and internal regulatory mechanisms from a non‐single omics perspective, but it still suffers many challenges, such as omics‐variance, sparsity, cell heterogeneity, and confounding factors. As it is known, the cell cycle is regarded as a confounder when analyzing other factors in single‐cell RNA‐seq data, but it is not clear how it will work on the integrated single‐cell multi‐omics data. Here, a cell cycle‐aware network (CCAN) is developed to remove cell cycle effects from the integrated single‐cell multi‐omics data while keeping the cell type‐specific variations. This is the first computational model to study the cell‐cycle effects in the integration of single‐cell multi‐omics data. Validations on several benchmark datasets show the outstanding performance of CCAN in a variety of downstream analyses and applications, including removing cell cycle effects and batch effects of scRNA‐seq datasets from different protocols, integrating paired and unpaired scRNA‐seq and scATAC‐seq data, accurately transferring cell type labels from scRNA‐seq to scATAC‐seq data, and characterizing the differentiation process from hematopoietic stem cells to different lineages in the integration of differentiation data.

Summary: Platinum-based chemo-resistance is the major issue for the treatment of small cell lung cancer (SCLC). The integrative analysis of multi-omics data is a reliable approach for discovering novel biomarkers associated with chemo-resistance. Here, multi-omics integrative analysis and Cox regression found that higher expression of PCDHB4 was associated with poorer survival of SCLC patients who received chemotherapy. PCDHB4 gene was hypomethylated and upregulated in SCLC, which was validated in the levels of promoter methylation, mRNA, and protein expression. Mechanistically, using bulk RNA-seq data, functional enrichment analysis indicated that higher PCDHB4 expression was associated with lower immune infiltration. The analysis of single-cell RNA-seq (scRNA-seq) found that SCLC cells with PCDHB4 expression exhibited the characteristics of stemness and EMT. In addition, the high expression and hypomethylation of PCDHB4 were also significantly associated with poor survival in lung squamous cell carcinoma. In summary, PCDHB4 is a potential prognostic biomarker of platinum-based chemotherapy in SCLC.

This study investigated the synergistic potential of an oncolytic herpes simplex virus armed with interleukin 12 (VT1092M) in combination with immune checkpoint inhibitors for enhancing antitumor responses. The potential of this combination treatment to induce systemic antitumor immunity was assessed using bilateral subcutaneous tumor and tumor re-challenge mouse models. The antitumor efficacy of various OV and ICI treatment combinations and the underlying mechanisms were explored through diverse analytical techniques, including flow cytometry and RNA sequencing. Using VT1092M, either alone or in combination with an anti-PD-L1 antibody, significantly reduced the sizes of both the injected and untreated abscopal tumors in a bilateral tumor mouse model. The combination therapy demonstrated superior antitumor efficacy to the other treatment conditions tested, which was accompanied by an increase in T cell numbers and CD8+ T cell activation. Results from the survival and tumor re-challenge experiments showed that the combination therapy elicited long-term, tumor-specific immune responses, which were associated with tumor clearance and prolonged survival. Immune cell depletion assays identified CD8+ T cells as the crucial mediators of systemic antitumor immunity during combination therapy. In conclusion, the combination of VT1092M and PD-L1 blockade emerged as a potent inducer of antitumor immune responses, surpassing the efficacy of each monotherapy. This synergistic approach holds promise for achieving robust and sustained antitumor immunity, with potential implications for preventing tumor metastasis in patients with cancer.

Objective To investigate the effects of 12-week weight-bearing dance aerobics (WBDA) on muscle morphology, strength and functional fitness in older women. Methods This controlled study recruited 37 female participants (66.31y ± 3.83) and divided them into intervention and control groups according to willingness. The intervention group received 90-min WBDA thrice a week for 12 weeks, while the control group maintained normal activities. The groups were then compared by measuring muscle thickness, fiber length and pennation angle by ultrasound, muscle strength using an isokinetic multi-joint module and functional fitness, such as 2-min step test, 30-s chair stand, chair sit-and-reach, TUG and single-legged closed-eyed standing test. The morphology, strength, and functional fitness were compared using ANCOVA or Mann-Whitney U test to study the effects of 12 weeks WBDA. Results Among all recruited participants, 33 completed all tests. After 12 weeks, the thickness of the vastus intermedius (F = 17.85, P < 0.01) and quadriceps (F = 15.62, P < 0.01) was significantly increased in the intervention group compared to the control group, along with a significant increase in the torque/weight of the knee flexor muscles (F = 4.47, P = 0.04). Similarly, the intervention group revealed a significant improvement in the single-legged closed-eyed standing test (z = −2.16, P = 0.03) compared to the control group. Conclusion The study concluded that compared to the non-exercising control group, 12-week WBDA was shown to thicken vastus intermedius, increase muscle strength, and improve physical function in older women. In addition, this study provides a reference exercise program for older women.

Background: The KCa3.1 channel (KCNN4) is extensively investigated as an oncogene in human cancers. The current study aimed to explore the clinicopathological significance of KCNN4 expression in patients with primary adult-type diffuse gliomas. Methods: Demographic, RNA-seq, and follow-up data of 477 patients were retrospectively reviewed. Patients were divided into the experimental and validation groups (278 and 199). KCNN4-related genes were determined by Pearson correlation analysis, and enrichment analyses and tumor-infiltrating immune cell assessments were applied to explore the potential mechanisms of KCNN4 involving glioma progression. The Kaplan-Meier method and the Cox regression analysis were used to evaluate the prognostic value of KCNN4 expression. Results: KCNN4 showed significantly higher expression level in glioblastoma, IDH-wildtype, followed by astrocytoma, IDH-mutant and oligodendroglioma, IDH-mutant and 1p/19q-codeleted (p < 0.001). Enrichment analyses and tumor-infiltrating immune cell assessments suggested that KCNN4 could involve glioma progression through extracellular regulation, affecting immune response, and modulating subcellular trafficking. At last, the Kaplan-Meier analysis showed that high KCNN4 expression was significantly correlated with poor progression-free and overall survival (p < 0.001 for both). While multivariate Cox regression analysis obtained an insignificant result. Conclusions: KCNN4 was identified to be overexpressed in glioma cells and its expression level is positively related to tumor malignancy. It potentially participates in glioma biology by affecting extracellular regulation, subcellular trafficking, and immune escape. Additionally, high KCNN4 expression was correlated with poor survival outcomes of patients. The results can shed new light on the mechanisms of glioma progression, and provide a potential therapeutic target for treating gliomas.

Abstract The Alectoris Chukar (chukar) is the most geographically widespread partridge species in the world, demonstrating exceptional adaptability to diverse ecological environments. However, the scarcity of genetic resources for chukar has hindered research into its adaptive evolution and molecular breeding. In this study, we have sequenced and assembled a high-quality, phased chukar genome that consists of 31 pairs of relatively complete diploid chromosomes. Our BUSCO analysis reported a high completeness score of 96.8% and 96.5%, with respect to universal single-copy orthologs and a low duplication rate (0.3% and 0.5%) for two assemblies. Through resequencing and population genomic analyses of six subspecies, we have curated invaluable genotype data that underscores the adaptive evolution of chukar in response to both arid and high-altitude environments. These data will significantly contribute to research on how chukars adaptively evolve to cope with desertification and alpine climates.

Human curve skeleton extraction is an important research topic in computer vision. In this paper, we propose a 3D human curve skeleton extraction method for point cloud, unlike the skeleton extraction methods in the literature that use an omnidirectional scanned point cloud for processing, the point cloud used in this paper is solid-state LiDAR scanning data with a fixed distance range. First, the human body point cloud is extracted by using geometry constraints. Next, the human body point cloud is contracted using point cloud normal vectors to increase the separability of data from different parts of the body. Then, the point cloud is projected to the image plane for image skeleton extraction and back-projected to the human point cloud to obtain the initial skeleton. Lastly, the final curve skeleton is further optimized using the Laplacian contraction method. The proposed method is faster than other contraction method, and the experimental results on real captured data demonstrate that the proposed method achieves better performance compared to the existing algorithms.

Abstract Background Commonly clinically diagnosed with relapsing polychondritis (RP), vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic syndrome (VEXAS) is a recently identified autoinflammatory disease caused by UBA1 somatic mutations. The low frequency and dynamic changes challenge the accurate detection of somatic mutations. The present study monitored these mutations in Chinese patients with RP. We included 44 patients with RP. Sanger sequencing of UBA1 was performed using genomic DNA from peripheral blood. Droplet digital polymerase chain reaction (ddPCR) was performed to screen low-prevalence somatic variants. Results Multiple ddPCR detections were performed using available blood samples collected at different follow-up time points. Three male patients were UBA1 somatic mutation carriers. Sanger sequencing detected the somatic UBA1 variant c.122T > C (p.Met41Thr) in two male patients. Initial ddPCR confirmed the variant in the two patients, with allele fractions of 73.75% and 88.46%, respectively, while yielding negative results in other patients. Subsequent ddPCR detected the somatic variant (c.122T > C) with low prevalence (1.02%) in another male patient from blood samples collected at a different time point, and confirmed dynamically fractional abundance in one patient with VEXAS, with allele fractions of 73.75%, 61.28%, 65.01%, and 73.75%. Nine patients assessed by ddPCR at different time points remained negative. Conclusion We report UBA1 variants in patients with RP in the Chinese population for the first time. Multiple ddPCR detections from samples collected at different time points can enhance sensitivity and should be considered for patients with initial negative ddPCR results.

The developments of communication technologies, Internet of Things (IoT), and Artificial Intelligence (AI) have significantly accelerated the advancement of Intelligent Transportation Systems (ITS) and Autonomous Driving (AD) in recent years. The exchange of sensed information by widely deployed radars, cameras, and other sensors on vehicles and roadside infrastructure can improve the traffic awareness of drivers and pedestrians. However, wireless data transmission in vehicular networks is challenged by highly dynamic path loss due to utilized frequency bands, weather conditions, traffic overheads, and geographical conditions. In this paper, we propose an Integrated Sensing and Communication System (ISAC) based path loss prediction approach to improve the knowledge of wireless data transmissions in vehicular networks, which utilizes multi-modal data collected by millimeter-wave (mmWave) radars, laser radars, and cameras to forecast the end-to-end path loss distribution. By leveraging a generative adversarial network for parameter initialization coupled with fine-tuning through supervised learning, the model's accuracy can be significantly improved. To increase the model's scalability, the effects of weather conditions, geographical conditions, traffic overheads, and frequency bands are all analyzed. According to the simulation results, our model achieves excellent accuracy with Mean Squared Error (MSE) of the predicted path loss distribution below $3e^{-3}$ across five different scenarios.

Simultaneous Localization and Mapping (SLAM) is one of the key issues for mobile robots to achieve true autonomy. The implementations of SLAM could rely on a variety of sensors. Among many types of them, the laser-based SLAM approach is widely used owing to its high accuracy, even in poor lighting conditions. However, when in structure-less environments, laser modules will fail due to a lack of sufficient geometric features. Besides, motion estimation by moving lidar has the problem of distortion since range measurements are received continuously. To solve these problems, we propose a tightly-coupled SLAM integrating LiDAR and an integrated navigation system (INS) for unmanned vehicle navigation in campus environments. On the basis of feature extraction, a constraint equation for inter-frame point cloud features is constructed, and the pose solution results of the INS are added as a priori data for inter-frame point cloud registration. The Levenberg-Marquardt nonlinear least square method is used to solve the constraint equation to obtain inter-frame pose relationships. Map matching and loop closure detection methods are used to optimize the odometer, and the optimal pose information is obtained. The proposed SLAM algorithm is evaluated by comparing with the classic open-source laser SLAM algorithms on the campus dataset. Experimental results demonstrate that our proposed algorithm has certain advantages in estimating the trajectory error of the unmanned vehicle and has higher mapping performance.

Previous epidemiologic studies have shown a close association between type 1 diabetes mellitus (T1DM), hyperlipidemia, and inflammatory bowel disease (IBD), but the causal relationship has not been established. In the current study the causal relationships between T1DM and hyperlipidemia with IBD were assessed using Mendelian randomization (MR) analysis. A two-sample MR study was conducted utilizing accessible genome-wide association study data from public sources with the selection of suitable instrumental variables adhering to the principles of MR analysis. The primary technique utilized was the inverse variance weighted method, complemented by additional methods, such as MR-Egger regression, weighted median, simple mode, weighted mode, and the MR pleiotropy residual sum and outlier approach. Genetically determined T1DM had no causal relationship with IBD or IBD subtypes based on MR analysis. These findings were consistent across all supplementary methods used. In addition, genetically determined hyperlipidemia had no causal relationship with IBD or IBD subtypes, even after increasing the number of instrumental variables used. Our study supports the notion that there is no causal relationship between T1DM and IBD, as well as hyperlipidemia and IBD, which contradicts most observational studies.

Neurodegeneration with brain iron accumulation (NBIA) is a clinically and genetically heterogeneous disease characterized by increased iron deposition in the basal ganglia and progressive degeneration of the nervous system in adulthood. However, in early childhood, there were no characteristic features to perform early diagnosis. In our study, a female child exhibited global developmental delay, intellectual disability, and febrile seizure without other distinct clinical phenotypes. Through whole exome sequencing (WES), a de novo nonsense mutation (c.726C > G, p. Tyr242Ter) of WDR45 gene was identified in this child. She was finally diagnosed as β‐propeller protein-associated neurodegeneration (BPAN), one of the recently identified subtypes of NBIA. This mutation could act as a premature stop codon (PSC) which rendered the mutated transcripts to be degraded by nonsense-mediated mRNA decay (NMD), leading to decreased levels of PSC-containing mRNAs. Additionally, through mini-gene splicing assays, this mutation could result in an unprecedented novel transcript with the exon 9 of WDR45 excluded by nonsense-associated splicing alteration (NASA). Transcriptome sequencing (RNA-seq) on total RNAs from PBMCs of the trio revealed three types of alternative splicing events in the patient. Further research implied that downregulation of iron transport genes (TFRC, TFR2, SCARA5) might be the underlying mechanism for the iron accumulation in patients with deficient WDR45. This is the first report about NASA happening in WDR45. It implies that nonsense mutations approximal to splicing sites could affect the disease pathogenesis through more than one molecular mechanism and should be taken into consideration when conducting genetic counseling.

Background: Traumatic brain injury (TBI) is the major reason for the death of young people and is well known for its high mortality and morbidity. This paper aim to predict the 24h survival of patients with TBI. Methods: A total of 1224 samples were involved in this analysis, and the clinical indicators involved included age, gender, blood pressure, MGAP and other fields, among which the target variable was “outcome”, which was a binary variable. The methods mainly involved in this paper include data visualization analysis, single factor analysis, feature engineering analysis, random forest model (RF), K-Nearst Neighbors (KNN) model, and so on. Logistic regression model (LR) and deep neural network model (DNN). We will oversample the training set using the SMOTE method because of the very unbalanced labeling of the sample itself. Results: Although the accuracy of all models is very high, the recall rate is relatively low. The DNN model with the best performance only reaches 0.17, and the corresponding AUC is 0.80. After resampling, we find that the recall rate of positive samples of all models has increased a lot, but the AUC of some models has decreased. Finally, the optimal model is LR, whose positive sample recall rate is 0.67 and AUC is 0.82. Conclusion: Through resampling, we obtained that the best model is the RF model, whose recall rate and AUC are the best, and the AUC level is about 0.87, indicating that the accuracy performance of the model is still good.

In recent years, a surge in malicious network incidents and instances of network information theft has taken place, with malware identified as the primary culprit. The primary objective of malware is to disrupt the normal functioning of computers and networks, all the while surreptitiously gathering users’ private and sensitive information. The formidable concealment and latency capabilities of malware pose significant challenges to its detection. In light of the operational characteristics of malware, this paper conducts an initial analysis of prevailing malware detection schemes. Subsequently, it extracts fuzzy features based on the distinct characteristics of malware traffic. The approach then integrates traffic detection techniques with Type II fuzzy recognition theory to effectively monitor malware-related traffic. Finally, the paper classifies the identified malware instances according to fuzzy association rules. Experimental results showcase that the proposed method achieves a detection accuracy exceeding 90%, with a remarkably low false alarm rate of approximately 5%. This method adeptly addresses the challenges associated with malware detection, thereby making a meaningful contribution to enhancing our country’s cybersecurity.

Background The presence of mental health conditions is pervasive in patients who experienced acute myocardial infarction (AMI), significantly disrupting their recovery. Providing timely and easily accessible psychological interventions using virtual reality-based cognitive–behavioural therapy (VR-CBT) could potentially improve both acute and long-term symptoms affecting their mental health.Aims We aim to examine the effectiveness of VR-CBT on anxiety symptoms in patients with AMI who were admitted to the intensive care unit (ICU) during the acute stage of their illness.Methods In this single-blind randomised clinical trial, participants with anxiety symptoms who were admitted to the ICU due to AMI were continuously recruited from December 2022 to February 2023. Patients who were Han Chinese aged 18–75 years were randomly assigned (1:1) via block randomisation to either the VR-CBT group to receive VR-CBT in addition to standard mental health support, or the control group to receive standard mental health support only. VR-CBT consisted of four modules and was delivered at the bedside over a 1-week period. Assessments were done at baseline, immediately after treatment and at 3-month follow-up. The intention-to-treat analysis began in June 2023. The primary outcome measure was the changes in anxiety symptoms as assessed by the Hamilton Anxiety Rating Scale (HAM-A).Results Among 148 randomised participants, 70 were assigned to the VR-CBT group and 78 to the control group. The 1-week VR-CBT intervention plus standard mental health support significantly reduced the anxiety symptoms compared with standard mental health support alone in terms of HAM-A scores at both post intervention (Cohen’s d=−1.27 (95% confidence interval (CI): −1.64 to −0.90, p

Erianin is an important bibenzyl compound in dendrobium and has a wide spectrum of pharmacological properties. Since Erianin was discovered, abundant results have been achieved in the in vitro synthesis, structural modification, and pharmacological mechanism research. Researchers have developed a series of simple and efficient in vitro synthesis methods to improve the shortcomings of poor water solubility by replacing the chemical structure or coating it in nanomaterials. Erianin has a broad anti-tumor spectrum and significant anti-tumor effects. In addition, Erianin also has pharmacological actions like immune regulation, anti-inflammatory, and anti-angiogenesis. A comprehensive understanding of the synthesis, metabolism, structural modification, and pharmacological action pathways of Erianin is of great value for the utilization of Erianin. Therefore, this review conducts a relatively systematic look back at Erianin from the above four aspects, to give a reference for the evolvement and further appliance of Erianin.

Introduction Acute kidney injury (AKI) is a critical condition with a complex aetiology and different outcomes, where haemodynamic dysfunction, renal hypoperfusion and inflammation serve as key contributors to its development and progression. Early and accurate diagnosis is vital for initiating targeted treatments like fluid resuscitation, vasoactive agents or steroid therapy, which are essential for improving patient outcomes. Intravoxel incoherent motion (IVIM) MRI assesses both capillary perfusion and tissue water diffusion, while arterial spin labelling (ASL) MRI measures renal blood flow without the need for contrast. Research on combined use of IVIM and ASL MRI in patients with AKI is rare. This study aims to investigate the MRI characteristics of IVIM and ASL in patients with tubulointerstitial nephritis (TIN) and to explore their relationship with pathological findings and renal recovery.Methods and analysis Single-centre, prospective, observational cohort study of 30 patients with biopsy-proven TIN. Participants will undergo renal IVIM and ASL MRI within 7 days post-biopsy. The pathological assessments of active and chronic tubulointerstitial injuries will be semiscored using modified Banff criteria. The estimated glomerular filtration rate (eGFR) during follow-up and prevalence of chronic kidney disease at 3 and 6 months will be reported. An eGFR below 45 mL/min is considered a poor renal outcome.Ethics and dissemination The study has been reviewed and approved by the Ethics Committee of Peking University First Hospital and written informed consent will be obtained from all participants (2022Y503). The study results will be disseminated through publication in a relevant peer-reviewed journal and presentation at academic meetings to increase awareness and share findings with the scientific community.

Rational fertilization is the main measure to improve crop yield, but there are differences in the optimal effects of nitrogen (N), phosphorus (P) and potassium (K) rationing exhibited by the same crop species in different regions and soil conditions. In order to determine the optimum fertilization ratio for high yield of Sapindus mukorossi in western Fujian to provide scientific basis. We carried out the experimental design with different ratios of N, P and K to investigate the effects of fertilization on the yield. and leaf physiology of Sapindus mukorossiand soil properties. Results showed that the yield of Sapindus mukorossi reached the highest value (1464.58 kg ha-1) at N2P2K2 treatment, which increased to 1056.25 kg ha-1 compared with the control. There were significant differences in the responses of soil properties and leaf physiological factors to fertilization treatments. Factor analysis showed that the integrated scores of soil factors and leaf physiological characteristic factors of Sapindus mukorossi under N2P2K2 fertilization treatment were the highest, which effectively improved the soil fertility and leaf physiological traits. The yield of Sapindus mukorossi showed a highly significant linear positive correlation with the integrated scores (r=0.70, p

Alzheimer’s disease is a neurodegenerative disorder characterized by cognitive dysfunction and behavioral abnormalities. Neuroinflammatory plaques formed through the extracellular deposition of amyloid-β proteins, as well as neurofibrillary tangles formed by the intracellular deposition of hyperphosphorylated tau proteins, comprise two typical pathological features of Alzheimer’s disease. Besides symptomatic treatment, there are no effective therapies for delaying Alzheimer’s disease progression. MicroRNAs (miR) are small, non-coding RNAs that negatively regulate gene expression at the transcriptional and translational levels and play important roles in multiple physiological and pathological processes. Indeed, miR-146a, a NF-κB-regulated gene, has been extensively implicated in the development of Alzheimer’s disease through several pathways. Research has demonstrated substantial dysregulation of miR-146a both during the initial phases and throughout the progression of this disorder. MiR-146a is believed to reduce amyloid-β deposition and tau protein hyperphosphorylation through the TLR/IRAK1/TRAF6 pathway; however, there is also evidence supporting that it can promote these processes through many other pathways, thus exacerbating the pathological manifestations of Alzheimer’s disease. It has been widely reported that miR-146a mediates synaptic dysfunction, mitochondrial dysfunction, and neuronal death by targeting mRNAs encoding synaptic-related proteins, mitochondrial-related proteins, and membrane proteins, as well as other mRNAs. Regarding the impact on glial cells, miR-146a also exhibits differential effects. On one hand, it causes widespread and sustained inflammation through certain pathways, while on the other hand, it can reverse the polarization of astrocytes and microglia, alleviate neuroinflammation, and promote oligodendrocyte progenitor cell differentiation, thus maintaining the normal function of the myelin sheath and exerting a protective effect on neurons. In this review, we provide a comprehensive analysis of the involvement of miR-146a in the pathogenesis of Alzheimer’s disease. We aim to elucidate the relationship between miR-146a and the key pathological manifestations of Alzheimer’s disease, such as amyloid-β deposition, tau protein hyperphosphorylation, neuronal death, mitochondrial dysfunction, synaptic dysfunction, and glial cell dysfunction, as well as summarize recent relevant studies that have highlighted the potential of miR-146a as a clinical diagnostic marker and therapeutic target for Alzheimer’s disease.

Abstract Background Several factors can influence the risk of dental caries, among which dietary factors have a significance impact on the occurrence of dental caries. The limitation of current studies is that they only focus on the influence of individual foods on the risk of dental caries. This study use cluster analysis to examine the relationship between dietary patterns and dental caries experience among adolescents aged 12–15. Methods Based on data from the first oral epidemic survey in Shanxi Province, a cross-sectional study was conducted among 11,351 adolescents aged 12–15 in Shanxi Province through oral examination and questionnaires. The questionnaire included the intake frequency of seven types of food. Descriptive statistics, cluster analysis, and multinomial logistic regression were used to analyze the association between dietary patterns and dental caries experience. Results The prevalence rate of caries was 44.57% and the mean DMFT score was 0.98 ± 1.49 in adolescents aged 12–15 in Shanxi Province. The caries rate was higher in females than males (X 2 = 103.59, P

Abstract Background Premature loss of primary molars can be treated with a band loop space maintainer (SM). However, fabricating a conventional band loop SM requires multiple clinical and laboratory procedures, which can potentially affect the accuracy of the SM. Moreover, the conventional SM is unable to fully restore masticatory function and maintain the vertical dimension of the edentulous space. In this current study, a fully digital workflow to fabricate a semi-rigid bridge SM made from polyetheretherketone (PEEK) has been described and evaluated for its clinical effectiveness. Methods A total of 15 children (eight males and seven females) between the ages of 4–8 years, who experienced the premature loss of a single primary molar, were included in this study. Digital impressions were taken using the CEREC CAD/CAM chair system and imported into CAD software to design the semi-rigid bridge SM, which was fabricated using PEEK block as the maintainer material. The digital SM was tried-in and bonded to the abutment with resin cement. The edentulous space was measured immediately after bonding (T0) and 1 month (T1), 3 months (T2), and 6 months (T3) after treatment. The periodontal condition and mobility of the SM and abutment were also examined. Results The use of digital impressions resulted in a decreased occurrence of the pharyngeal reflex. The digital semi-rigid bridge SM, fabricated with PEEK, was both convenient and aesthetically pleasing, and successfully restored the anatomy and masticatory function of the missing primary molar. None of the 15 semi-rigid bridge SMs or abutments became loose or fell off during the study, and only one child presented with gingivitis. Furthermore, the difference in the edentulous space at T0, T1, T2, and T3 was not statistically significant (all P > 0.05). Conclusions The digital semi-rigid bridge SM fabricated with PEEK was clinically effective in maintaining the missing space and had advantages over the traditional band/crown loop SM.

Objective: To explore the antioxidant mechanism of Shanxi aged vinegar on rats induced by high fat diet based on PI3K/AKT1 pathway. Methods: Thirty SPF male Wistar rats were randomly divided into 5 groups: Normal group (C, conventional diet), high fat model group (M, high fat emulsion), low (LV), medium (MV) and high (HV) Shanxi aged vinegar intervention groups (1.35, 2.7, 5.4 g/(kg·bw)). Modeling (5 weeks) at the same time given Shanxi aged vinegar intervention, the aged vinegar intervention continued for 5 weeks. Serum lipid content, liver injury index and antioxidant enzyme activity were detected. The histopathological status of liver was observed by HE staining. The mRNA and protein levels of PIK3CA and AKT1 in rat liver were detected by qRT-PCR and Western blotting, and the localization was analyzed by immunohistochemistry. Results: Compared with group C, liver steatosis was severe in group M, serum lipid content and degree of liver injury were significantly increased (P

The expression of robot arm morphology is a critical foundation for achieving effective motion planning and collision avoidance in robotic systems. Traditional geometry-based approaches usually suffer from the contradiction between the high demand for computing resources for fine expression and the insufficient detail expression caused by the pursuit of efficiency. The signed distance function addresses these drawbacks due to its ability to handle complex and arbitrary shapes and lower computational requirements. However, conventional robotic morphology methods based on the signed distance function often face challenges when the robot moves dynamically, since robots with different postures are modeled as independent individuals but the postures of robots are infinite. In this paper, we introduce RobotSDF, an implicit morphology modeling approach that can express the robot shape of arbitrary posture precisely. Instead of depicting a whole model of the robot arm, RobotSDF models the robot morphology as integrated implicit joint models driven by joint configurations. In this approach, the dynamic shape change process of the robot is converted into the coordinate transformations of query points within each joint’s coordinate system. Experimental results with the Elfin robot demonstrate that RobotSDF can accurately depict robot shapes across different postures up to the millimeter level, which exhibits 38.65% and 66.24% improvement over the Neural-JSDF and configuration space distance field algorithms, respectively, in representing robot morphology. We further verified the efficiency of RobotSDF through collision avoidance in both simulation and actual human–robot collaboration experiments.

Data-driven fault diagnosis, identifying abnormality causes using collected industrial data, is one of the challenging tasks for intelligent industry safety management. It is worth noting that practical industrial data are usually related to a mixture of several physical attributes, such as the operating environment, product quality and working conditions. However, the traditional models may not be sufficient to leverage the coherent information for diagnostic performance enhancement, due to their shallow architecture. This paper presents a hierarchical matrix factorization (HMF) that relies on a succession of matrix factoring to find an efficient representation of industrial data for fault diagnosis. Specifically, HMF consecutively decomposes data into several hierarchies. The intermediate hierarchies play the role of analysis operators which automatically learn implicit characteristics of industrial data; the final hierarchy outputs high-level and discriminative features. Furthermore, HMF is also extended in a nonlinear manner by introducing activation functions, referred as NHMF, to deal with nonlinearities in practical industrial processes. The applications of HMF and NHMF to fault diagnosis are evaluated by the multiple-phase flow process. The experimental results show that our models achieve competitive performance against the considered shallow and deep models, consuming less computing time than deep models.

The present study aimed to investigate the variations in the nutritional composition, antioxidant capacity, and metabolite profile of lilies subjected to different drying treatments, including vacuum freeze drying (VFD), hot air drying (HAD), vacuum drying (VD), and infrared drying (ID). The results show that VFD provided better preservation of the original coloration and displayed the highest levels of total amino acid content, total phenolic content, total flavonoid content, and polysaccharide and alkaloid content. Our results reveal that VFD treatment can be employed to obtain high-quality lilies with desirable appearance characteristics and nutrient compositions. Metabolomics analysis identified a total of 464 metabolites from various dried lilies. Differential metabolite screening found 150 differential metabolites across all pairwise comparisons. Hierarchical clustering analysis (HCA) indicated that lilies subjected to VFD treatment exhibited a higher abundance of steroids, saponin, flavonoids, and phenolic glycoside, whereas those subjected to HAD, VD, or ID treatments showed relatively elevated levels of specific amino acids or derivatives. This study elucidates the significant impact of various drying treatments on the quality and metabolic profile of lilies, thereby providing valuable insights for enhancing the nutritional quality of processed lilies.

Erianin, a bibenzyl compound found in dendrobium extract, has demonstrated broad anticancer activity. However, its mechanism of action in gastric cancer (GC) remains poorly understood. LKB1 is a tumor-suppressor gene, and its mutation is an important driver of various cancers. Yet some studies have reported contradictory findings. In this study, we combined bioinformatics and in vitro and in vivo experiments to investigate the effect and potential mechanism of Erianin in the treatment of GC. The results show that LKB1 was highly expressed in patients’ tumor tissues and GC cells, and it was associated with poor patient prognosis. Erianin could promote GC cell apoptosis and inhibit the scratch repair, migration, invasion, and epithelial–mesenchymal transition (EMT) characteristics. Erianin dose-dependently inhibited the expression of LKB1, SIK2, SIK3, and PARD3 but had no significant effect on SIK1. Erianin also inhibited tumor growth in CDX mice model. Unexpectedly, 5-FU also exhibited a certain inhibitory effect on LKB1. The combination of Erianin and 5-FU significantly improved the anti-tumor efficacy of 5-FU in the growth of GC cells and xenograft mouse models. In summary, Erianin is a potential anti-GC compound that can inhibit GC growth and EMT properties by targeting the LKB1-SIK2/3-PARD3-signaling axis. The synergistic effect of Erianin and 5-FU suggests a promising therapeutic strategy for GC treatment.

Abstract A comprehensive quantification of global forest fragmentation is urgently required to guide forest protection, restoration and reforestation policies. Previous efforts focused on the static distribution patterns of forest remnants, potentially neglecting dynamic changes in forest landscapes. Here, we map global distribution of forest fragments and their temporal changes between 2000 and 2020. We find that forest landscapes in the tropics were relatively intact, yet these areas experienced the most severe fragmentation over the past two decades. In contrast, 75.1% of the world’s forests experienced a decrease in fragmentation, and forest fragmentation in most fragmented temperate and subtropical regions, mainly in northern Eurasia and South China, declined between 2000 and 2020. We also identify eight modes of fragmentation that indicate different recovery or degradation states. Our findings underscore the need to curb deforestation and increase connectivity among forest fragments, especially in tropical areas.

ObjectiveWhile growing psychological health issues among pregnant women during the COVID-19 pandemic have been clearly validated, most research was conducted in countries with relatively lax quarantine measures. This study aimed to compare the prevalence of prenatal depression among pre-, peak-, and post-COVID-19 in Beijing, the region with a stringent response policy in China. We also explore predictors of prenatal depression throughout the outbreak.MethodsWe investigated prenatal depression among 742 pregnant women who received antenatal checkups in Beijing from March 28, 2019 to May 07, 2021 using the Edinburgh Postnatal Depression Scale and associative demographic, pregnancy-related, and psychosocial characteristics were measured. The phase was divided into pre-, peak-, and post-COVID-19 in light of the trajectory of COVID-19. Pearson's Chi-square test was used after the examination of confounders homogeneity. The bivariable and multivariable logistic regression was conducted to explore predictors.ResultsThe pooled prevalence of prenatal depression was 11.9% throughout the COVID-19 pandemic. Rates at different phases were 10.6%, 15.2%, and 11.1% respectively and no significant difference was observed. Multivariable logistic regression revealed that history of mental illness, number of boy-preference from both pregnant women and husband's family, social support, occupation, and living space were independent predictors of prenatal depression in Beijing.ConclusionOur data suggested that the impact of this pandemic on prenatal depression in Beijing appears to be not significant, which will strengthen confidence in adhering to current policy for decision-makers and provide important guidance for the development of major outbreak control and management policies in the future. Our findings may also provide a more efficient measure to identify high-risk pregnant women for professionals and help raise gender equity awareness of pregnant women and their husbands' families. Future studies should focus on the value of targeted care and family relations on the mental health of pregnant women.

Summary: In plant roots, the identity of the stem cell niche (SCN) is maintained by an auxin gradient with its maximum in the quiescent center (QC). Optimal levels of auxin signaling are essential for root SCN identity, but the regulatory mechanisms that control this pathway in root are largely unknown. Here, we find that the zinc finger transcription factor sensitive to proton rhizotoxicity 1 (STOP1) regulates root SCN identity by negative feedback of auxin signaling in root tips. Mutation and overexpression of STOP1 both affect QC cell division and distal stem cell differentiation in the root. We find that auxin treatment stabilizes STOP1 via MPK3/6-dependent phosphorylation. Accumulating STOP1 can compete with AUX/IAAs to interact with, and enhance the repressive activity of, auxin-repressive response factor ARF2. Overall, we show that the MPK3/6-STOP1-ARF2 module prevents excessive auxin signaling in the presence of auxin to maintain root SCN identity.

AbstractThe landslide morphology is quickly and accurately extracted from Unmanned Air Vehicle (UAV) images. It is of great significance for emergency rescue and quantitative evaluation of landslide disasters. However, due to the complexity of landslide morphology, choosing the reasonable extraction thresholds is a challenging issue. A threshold selection method of Topographic Profile along the Direction of Slope Movement (TP-DSM) was proposed. Firstly, a hierarchical extraction rule sets for landslide morphology was constructed by integrating multi-feature information such as spectral, texture, geometry, topography and space of UAV images. Second, TP-DSM was proposed to select the optimal elevation thresholds for classifying different landslide morphology. Finally, the thresholds were introduced into the rule sets to achieve effective extraction of landslide morphology. This study uses Digital Orthophoto Map (DOM) and Digital Elevation Model (DEM) generated by UAV images as data sources, and the landslide in Luquan County, Yunnan Province, China as the Study area, the results show that the overall accuracy (OA) of landslide morphology extraction was 89.58%, and the Kappa coefficient was 0.88, which is effective and more consistent with the reality. The proposed method can also be applied to other potential locations.

Abstract As a core step of obstacle avoidance and path planning, dynamic obstacle detection is critical for autonomous driving. This study aimed to propose a dynamic obstacle detection method based on U–V disparity and residual optical flow for autonomous driving. First, a drivable area of an unmanned vehicle was detected using U–V disparity images. Then, obstacles in the drivable area were detected using U–V disparity images and the geometric relationship between obstacle size and its disparity. Finally, the motion likelihood of each obstacle was estimated by compensating the camera ego-motion. The innovation of the proposed method was that the searching range of the moving obstacles was greatly narrowed by detecting the obstacles in the drivable area, which greatly improved not only the moving obstacle detection efficiency but also the detection accuracy. Datasets from the KITTI benchmark and our self-acquired campus scene data were chosen as testing samples. The experimental results showed that our method could achieve high detection precision, low missed detection rate and less time consumption.

Abstract Rationale Chinese women topped the list of new breast cancers, the first diagnosed gastric metastasis and bone metastasis is extremely infrequent. The clinical and pathological diagnosis of metastatic breast cancer is difficult. To our knowledge, this is the first reported case of the first diagnosis of breast cancer with both gastric metastasis and bone metastasis. Case report The female patient was found to have abdominal distension for 15 days with nausea and vomiting. The patient underwent a gastroscopy at an outside hospital 4 days ago, showing: duodenal bulb changes, gastric retention and chronic non-atrophic gastritis. Gastroscopic biopsy showed chronic inflammation and edema of the duodenal mucosa with glandular hyperplasia. Conservative treatment was given with no relief of symptoms. She was seen in our hepatobiliary and pancreatic surgery department. After admission, palliative surgery was performed, and the swelling and surrounding involved tissues were taken for examination during surgery. The rapid pathological return could not exclude tumor lesions, and the postoperative pathology confirmed the diagnosis of invasive lobular carcinoma of the breast with gastric metastases, and the systemic examination revealed combined bone metastases. Diagnosis Pathology and immunohistochemistry(IHC), a whole-body bone scan confirmed the first diagnosis of breast cancer with both gastric and bone metastases. Interventions Palliative treatment with bisphosphonates and CDK4/6i (Palbociclib) in combination with AI (Exemestane) was administered. Outcomes The patient is currently under regular evaluation and is being followed up.

Nowadays, metal oxide semiconductor gas sensors have diverse applications ranging from human health to smart agriculture with the development of Internet of Things (IoT) technologies. However, high operating temperatures and an unsatisfactory detection capability (high sensitivity, fast response/recovery speed, etc.) hinder their integration into the IoT. Herein, a ternary heterostructure was prepared by decorating WO3 nanoplates with Au and SnO2 nanoparticles through a facial photochemical deposition method. This was employed as a sensing material for 3-hydroxy-2-butanone (3H-2B), a biomarker of Listeria monocytogenes. These Au/SnO2–WO3 nanoplate-based sensors exhibited an excellent response (Ra/Rg = 662) to 25 ppm 3H-2B, which was 24 times higher than that of pure WO3 nanoplates at 140 °C. Moreover, the 3H-2B sensor showed an ultrafast response and recovery speed to 25 ppm 3H-2B as well as high selectivity. These excellent sensing performances could be attributed to the rich Au/SnO2–WO3 active interfaces and the excellent transport of carriers in nanoplates. Furthermore, a wireless portable gas sensor equipped with the Au/SnO2–WO3 nanoplates was assembled, which was tested using 3H-2B with known concentrations to study the possibilities of real-time gas monitoring in food quality and safety.

Polygonati Rhizoma (PR) has certain neuroprotective effects as a homology of medicine and food. In this study, systematic pharmacology, molecular docking, and in vitro experiments were integrated to verify the antidepressant active ingredients in PR and their mechanisms. A total of seven compounds in PR were found to be associated with 45 targets of depression. Preliminarily, DFV docking with cyclooxygenase 2 (COX2) showed good affinity. In vitro, DFV inhibited lipopolysaccharide (LPS)-induced inflammation of BV-2 cells, reversed amoeba-like morphological changes, and increased mitochondrial membrane potential. DFV reversed the malondialdehyde (MDA) overexpression and superoxide dismutase (SOD) expression inhibition in LPS-induced BV-2 cells and decreased interleukin-1β (IL-1β), tumor necrosis factor-α (TNF-α), and IL-6 mRNA expression levels in a dose-dependent manner. DFV inhibited both mRNA and protein expression levels of COX2 induced by LPS, and the activation of NACHT, LRR, and PYD domains-containing protein 3 (NLRP3) and caspase1 was suppressed, thus exerting an antidepressant effect. This study proves that DFV may be an important component basis for PR to play an antidepressant role.

Polyether ether ketone (PEEK) is esteemed as a high-performance engineering polymer renowned for its exceptional mechanical properties and thermal stability. Nonetheless, the majority of polymer-based lubricating materials fail to meet the contemporary industrial demands for motion components regarding high speed, heavy loading, temperature resistance, and precise control. Utilizing 3D printing technology to design and fabricate intricately structured components, developing high-performance polymer self-lubricating materials becomes imperative to fulfill the stringent operational requirements of motion mechanisms. This study introduces a novel approach employing 3D printing technology to produce PEEK with varying filling densities and conducting in situ synthesis of zeolitic imidazolate framework (ZIF-8) nanomaterials on its surface to enhance PEEK’s frictional performance. The research discusses the synthetic methodology, characterization techniques, and tribological performance evaluation of in situ synthesized ZIF-8 nanomaterials on PEEK surfaces. The findings demonstrate a significant enhancement in frictional performance of the composite material under low-load conditions, achieving a minimum wear rate of 4.68 × 10−6 mm3/N·m compared to the non-grafted PEEK material’s wear rate of 1.091 × 10−5 mm3/N·m, an approximately 1.3 times improvement. Detailed characterization and analysis of the worn surface of the steel ring unveil the lubrication mechanism of the ZIF-8 nanoparticles, thereby presenting new prospects for the diversified applications of PEEK.

High-energy-density liquid fuels (HED fuels) are essential for volume-limited aerospace vehicles and could serve as energetic additives for conventional fuels. Terpene-derived HED biofuel is an important research field for green fuel synthesis. The direct extraction of terpenes from natural plants is environmentally unfriendly and costly. Designing efficient synthetic pathways in microorganisms to achieve high yields of terpenes shows great potential for the application of terpene-derived fuels. This review provides an overview of the current research progress of terpene-derived HED fuels, surveying terpene fuel properties and the current status of biosynthesis. Additionally, we systematically summarize the engineering strategies for biosynthesizing terpenes, including mining and engineering terpene synthases, optimizing metabolic pathways and cell-level optimization, such as the subcellular localization of terpene synthesis and adaptive evolution. This article will be helpful in providing insight into better developing terpene-derived HED fuels.

Tricyclene, a tricyclic monoterpene naturally occurring in plant essential oils, holds potential for the development of medicinal and fuel applications. In this study, we successfully synthesized tricyclene in E. coli by introducing the heterologous mevalonate (MVA) pathway along with Abies grandis geranyl diphosphate synthase (GPPS) and Nicotiana sylvestris tricyclene synthase (TS) XP_009791411. Initially, the shake-flask fermentation at 30 ◦C yielded a tricyclene titer of 0.060 mg/L. By increasing the copy number of the TS-coding gene, we achieved a titer of 0.103 mg/L. To further enhance tricyclene production, optimal truncation in the N-terminal region of TS XP_009791411 resulted in an impressive highest titer of 47.671 mg/L, approximately a 794.5-fold improvement compared to its wild-type counterpart. To the best of our knowledge, this is the highest titer of the heterologous synthesis of tricyclene in E. coli. The SDS-PAGE analysis revealed that lowering induction temperature and truncating the random coil N-terminal region effectively improved TS solubility, which was closely associated with tricyclene production levels. Furthermore, by truncating other TSs, the titers of tricyclene were improved to different degrees.

Among broilers, the main pathogen that leads to swollen head syndrome (SHS) is the subgroup C avian metapneumovirus (aMPV-C). The aMPV-C infection can lead to an upsurge in the rate of soft-shell eggs, resulting in reduced egg production and seriously affecting the economy of the livestock industry. Therefore, a rapid method for aMPV-C detection needs to be invented. According to the N gene of aMPV-C, we designed the specific probe and primer and created a reverse transcription recombinase-aided amplification assay (RT-RAA) for the detection of aMPV-C. aMPV-C could be detected quickly and specifically by this method at 41 °C for 30 min. The sensitivity assay inferred that the minimum detection threshold of RT-RAA was 3.38 × 101 copies/μL. A specificity assay showed that the RT-RAA method did not cross-react with other subgroups (aMPV-A, aMPV-B, aMPV-D) or other viruses (H9N2, NDV, IBV, IBDV). Forty samples of known clinical background were tested by RT-RAA and RT-qPCR. The two approaches had a 100% correlation rate. In conclusion, this research successfully created an RT-RAA assay for aMPV-C.

Background and Aims: Poor ovarian response (POR) is a pathological condition characterized by a reduced ovarian response to gonadotropin stimulation. This condition presents with a low number of developed follicles during the ovulation induction cycle, low blood estradiol (E2) peak, high gonadotropin dosage, fewer retrieved oocytes, increased cycle cancellation rate, and low clinical pregnancy rate. POR is a significant challenge in assisted reproductive technology. Autologous platelet-rich plasma (PRP) has emerged as a potential therapy for POR, but its efficacy remains controversial. This meta-analysis aims to determine the effect of intraovarian infusion of PRP on ovarian reserve and pregnancy outcomes in patients with POR. Methods: This study was designed as a Meta-analysis. Women diagnosed with POR based on POSEIDON or Bologna criteria were included. Primary outcomes included anti-Müllerian hormone (AMH), antral follicle count (AFC), follicle-stimulating hormone (FSH), luteinizing hormone (LH), and E2 levels, while secondary outcomes were the number of retrieved oocytes and embryo quality. Results: Seven prospective cohort studies involving 202 participants were included. Intra-ovarian infusion of autologous PRP significantly increased AMH (SMD: 0.20, 95% CI: 0.05–0.36; P=0.01), AFC (SMD: 0.92, 95% CI: 0.59–1.25, P

Background: The internationalization of higher education has stimulated an ever-increasing demand for English for Medical Purposes (EMP) courses for nursing undergraduates in China. EMP courses are designed to provide learner-centered language instruction to satisfy students’ English communication needs in the future workplace. To date, far too little attention has been paid to developing a well-rounded and theory-guided nurse–patient communication teaching model based on target needs analysis in nurse–patient communication. Objective: To develop an EMP teaching framework to improve Chinese nursing undergraduates’ nurse–patient communicative competence in clinical settings based on target situation needs analysis. Methods: A survey of nurses' target situation needs analysis in clinical nurse–patient communication was conducted among nurses in five teaching hospitals in China. A teaching model was developed based on the survey analysis to improve nursing undergraduates’ nurse–patient communicative competence. Results: A total of 411 nurses participated in this study. There were no significant differences in the overall satisfaction in target-situation communication and self-assessment in three-aspect communicative competence in clinical communication among nurses with different sociodemographic characteristics. Nurses with better self-assessment in the three-aspect communicative competence are more likely to satisfy their needs of nurse–patient clinical communication in target situation. Nurses self-reported the tasks and language skills commonly involved in nurse–patient clinical communication. A four-step teaching model was developed to respond to the findings of the target situation needs analysis. Conclusion: This study provides important insights into the essential role of employing and integrating a language communicative competence framework and a target-situation analysis framework in formulating a needs-driven and tailor-made EMP teaching model. Based on the previous framework, the teaching model is adapted and characterized by systematic and interconnected teaching steps, core target-situation topics, and a complete set of task forms, providing EMP instructors with operable scaffolds to help nursing students observe, analyze, practice, and assess nurse–patient communication. The study will be of significance for EMP researchers and instructors simulated to conduct further research and practice in English communication in the wider medical field.

Objectives Although lymphocyte-monocyte ratio (LMR) is a potential prognostic biomarker in many tumor indications, a doubt occurs around its association with head and neck squamous cell carcinoma (HNSCC). We aimed to evaluate the predictive value of LMR in patients with HNSCC. Methods We searched PubMed, Web of Science, EMBASE, and the Cochrane database from inception to May 8, 2023 for systematic review and meta-analysis on LMR and outcomes related to HNSCC development. STATA software was used to estimate the correlation between LMR and prognosis. The risk ratio (hazard ratio, HR) and 95% confidence interval l (CI) for overall survival (OS), disease-free survival (DFS), cancer-specific survival (CSS), and progression-free survival (PFS) were calculated, and the association between LMR and OS was further validated by subgroup analysis. The source of heterogeneity with the results of subgroup analysis was analyzed by meta-regression analysis. This meta-analysis was registered at PROSPERO (CRD42023418766). Results After a comprehensive exploration, the results of 16 selected articles containing 5,234 subjects were evaluated. A raised LMR was connected to improved OS (HR = 1.36% CI [1.14–1.62] P = 0.018), DFS (HR = 0.942, 95% CI [0.631–1.382], P = 0.02), and PFS (HR = 0.932, 95% CI [0.527–1.589], P < 0.022). Subgroup analysis indicated that patients with a low LMR level had a poor prognosis with a critical value of ≥4. The LMR was found to be prognostic for cases with an LMR of