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According to the requirements of the pre-assessment service and earthquake emergency disposal, we collected the pre-assessment survey data of Sichuan in recent ten years, and designed the database structure with deeply mining, classification and coding. At last, we established the database for pre-assessment survey data to realize fast query of pre-assessment survey data, statistics, calls and other functions, which promoting the transformation of pre-assessment achievements. And it also realizes the scientific, standardized and systematic management of pre-assessment survey data, and provides data guarantee for earthquake disaster risk management and earthquake emergency information services.

Introduction: Elevated levels of serum uric acid (SUA) are strongly associated with several components of the metabolic syndrome, particularly obesity. Previous studies have reported the correlation between SUA levels, xanthine oxidoreductase (XOR) activity, and the imbalanced adipokine levels that are characteristic of obesity. In this study, we explored the effect of febuxostat on circulating adipokine profiles in patients with overweight or obesity and asymptomatic hyperuricemia. Methods: This study was a single-center, randomized, and controlled clinical trial that enrolled 130 participants with asymptomatic hyperuricemia and obesity. One hundred seventeen participants were included in the final analysis, with 60 participants in the febuxostat group and 57 in the control group. We compared the circulating adipokine levels at 3 and 6 months, including high molecular weight (HMW) adiponectin, chemerin, omentin, monocyte chemotactic protein-1, asprosin, fibroblast growth factor 21, neuregulin-4, leptin, resistin, vaspin, visfatin, adipsin, and assessed the correlation between changes in adipokine levels (Δadipokines) and changes in XOR activity (ΔXOR) after febuxostat treatment. Results: The results showed that an increase in HMW adiponectin and omentin levels and a decrease in chemerin and asprosin levels at 3 or 6 months compared to the control group. Additionally, a positive correlation was observed between ΔXOR activity and Δasprosin. Furthermore, after adjusting for triglyceride (ΔTG) and serum uric acid (ΔSUA) in multiple linear regression analyses, we found that ΔXOR activity was independently correlated with Δasprosin. Conclusion: This study may provide important evidence that febuxostat could alleviate the imbalance in circulating adipokine levels in patients with overweight or obesity and asymptomatic hyperuricemia. Furthermore, we observed a positive correlation between changes in asprosin levels and changes in XOR activity after febuxostat treatment.

Abstract In this paper, a combination of theoretical modeling, finite element simulation, and experimental methods is employed to investigate the forming mechanism and evolutionary pattern of the stagnant region during mechanical scratching with a diamond wedge tool. The study is structured as follows: Firstly, a theoretical calculation model for the geometric parameters of the stagnant region on the formed groove surface is established based on the contact friction partition mechanism and slip-line field theory. The model indicates that the geometric parameters l B-sg , l V-sg , and ∆l sg of the stagnant region are determined by the length of the stagnant region l p-sg in the plastic flow plane and the transformation parameters. Secondly, the formation process of the stagnant region in mechanical scratching is investigated using an orthogonal cutting simulation model with a negative rake angle tool. The results reveal that the stagnant region is a plastic deformation region formed due to the geometrical characteristics of the negative front surface of the scratching tool and its excessive extrusion, which leads to the formation of adhesive friction within the material. Thirdly, the characteristics of the stagnant region are determined through scratching experiments. Compared to the material in the plastic flow region, the material within the stagnant region exhibits finer and denser microstructures, reduced surface hardening peaks and hardened layer depths, and significantly improved surface roughness. Finally, the evolutionary pattern of the stagnant region under the influence of scratching processing parameters is examined based on the theoretical calculation model of the geometric parameters and the scratching experiment. The findings indicate that as the wedge angle of the scratching tool decreases, the relief angle increases, the absolute value of the rotation angle around the Y-axis decreases, the scratching speed decreases, and the material’s plastic adherence improves, the P I/k value decreases, the l p-sg value increases, and consequently, the geometric parameters l B-sg , l V-sg , and ∆l sg of the stagnant region on the formed groove surface also increase. The deviation analysis of the geometric parameters of the stagnant region reveals a consistent trend between the theoretical and experimental values of l V-sg and ∆l sg , with maximum deviations of 15 μm and 4.13%, respectively. This study provides theoretical and experimental evidence for the establishment of the theoretical model of the stagnant region in mechanical scratching, the analysis of its forming mechanism, and the control of the stagnant region geometric parameters on the formed groove surface.

Objective:. To investigate the predictive value of carotid-femoral pulse wave velocity (cf-PWV) for assessing major adverse cardiovascular events (MACE) and all-cause mortality in different age groups of a Chinese community. Methods:. This is an observational study which enrolled 1,325 individuals from a community in Beijing from September 2007 to October 2018. They were classified based on age into 0.05). Conclusion:. cf-PWV, a measure of arterial stiffness, emerged as an independent risk factor for MACE and all-cause mortality in subjects below 65 years of age.

In vitro toxicological assessment helps explore key fractions of particulate matter (PM) in association with the toxic mechanism. Previous studies mainly discussed the toxicity effects of the water-soluble and organic-soluble fractions of PM. However, the toxicity of insoluble fractions is relatively poorly understood, and the adsorption of proteins is rarely considered. In this work, the formation of protein corona on the surface of insoluble particles during incubation in a culture medium was investigated. It was found that highly abundant proteins in fetal bovine serum were the main components of the protein corona. The adsorbed proteins increased the dispersion stability of insoluble particles. Meanwhile, the leaching concentrations of some metal elements (e.g., Cu, Zn, and Pb) from PM increased in the presence of proteins. The toxicity effects and potential mechanisms of the PM insoluble particle–protein corona complex on macrophage cells RAW264.7 were discussed. The results revealed that the PM insoluble particle–protein corona complex could influence the phagosome pathway in RAW264.7 cells. Thus, it promoted the intracellular reactive oxygen species generation and induced a greater degree of cell differentiation, significantly altering cell morphology. Consequently, this work sheds new light on the combination of insoluble particles and protein corona in terms of PM cytotoxicity assessment.

IntroductionSalt stress is one of the significant challenges in sorghum production, greatly impacting the yield of S. bicolor. L-type lectin receptor kinases (LLRKs) are essential for plant stress tolerance, yet a comprehensive genome-level analysis in this species has not been conducted.Materials and methodsMembers of the SbLLRLK gene family were identified using bioinformatics methods. Gene structures, motifs, and phylogenetic relationships were analyzed. Subsequently, expression profiles under various stress conditions were examined using transcriptome data. Furthermore, functional validation was performed through homologous gene alignment and transgenic analysis, focusing on the gene SORBI_3004G304700.ResultsThis study identified 49 SbLLRLK genes in Sorghum bicolor, categorized into four groups based on their lectin domain characteristics. Expression analyses revealed diverse patterns under salt, drought, and heat stresses. SORBI_3004G304700 was identified as a negative regulator of salt stress tolerance, with three unique haplotypes identified through haplotype analysis, suggesting a role in salt stress adaptation. Haplotype analysis of SORBI_3004G304700 revealed three unique haplotypes, with haplotype1 being the most prevalent, possibly due to selective advantages for salt stress tolerance.DiscussionThese findings offer valuable insights into the biological research on the role of the LLRLK gene family in Sorghum bicolor’s response to salt stress. The functional characterization of SORBI_3004G304700 and the identification of haplotypes associated with salt tolerance provide valuable insights for molecular breeding and genetic enhancement of sorghum.

Bovine coronavirus (BCoV), a persistent threat to global cattle industry, has caused significant economic losses worldwide. In this study, a viral strain was isolated from the intestinal content of a diseased calve, and identified by cytopathic effects observation, indirect immunofluorescence assay and electron microscopy. Results showed that BCoV NXWZ2310 belonging to the GIIb genotype and has a three-amino-acid deletion in the serine-rich region of the N gene. Importantly, the BCoV NXWZ2310 strain exhibited strong pathogenicity, causing nasal discharge and watery diarrhea in calves for 8 and 10 days, respectively. Viral shedding was detected in nasal, throat and rectal swabs at levels reaching 106.228 copies/mL, 105.0 copies /mL and 106.692 copies/mL, respectively. Pathological examination showed that NXWZ2310 resulted in parenchymal lesions of the pulmonary lobe and significant intestinal lesions. Both the lungs and intestines displayed marked microscopic lesions with clear viral antigens present. BCoV NXWZ2310 strain with N-gene deletion mutations, caused severe respiratory and digestive disease in calves. Therefore, effective strategies are needed for the prevention and control of this isolate.

Objective: Explored the composition and content of phenolic compounds in tartary buckwheat wine lees, and study their antioxidant activity. Methods: Phenolic compounds in tartary buckwheat wine lees were analyzed by HPLC and LC-MS. And evaluating its antioxidant activity. Results: 7 phenolic compounds were identified from tartary buckwheat wine lees, including 5 flavonoids, with the highest content of rutin of （9.350±0.050） mg/g, followed by quercetin, isoquercetin, kaempferol-3-o-rutoside and kaempferol of two phenolic compounds. At 0.5 mg/mL, the scavenging rates of hydroxyl free radical, ABTS+ and DPPH free radical reached （73.29±0.09）%, （96.21±0.25）% and （82.55±0.68）%, respectively, with FRAP value of （2.49±0.09） mmol/L. Conclusion: The fermented tartary buckwheat lees are rich in phenolic compounds, and the lees extracts has certain antioxidant activity. In addition, at low concentration, the tartary buckwheat wine lees also showes good scavenging effects on hydroxyl radical and ABTS+ radical.

Abstract Interleukin 12 (IL-12) is a potent immunostimulatory cytokine mainly produced by antigen-presenting cells (e.g., dendritic cells, macrophages) and plays an important role in innate and adaptive immunity against cancers. Therapies that can synergistically modulate innate immunity and stimulate adaptive anti-tumor responses are of great interest for cancer immunotherapy. Here we investigated the lipid nanoparticle-encapsulated self-replicating RNA (srRNA) encoding IL-12 (referred to as JCXH-211) for the treatment of cancers. Both local (intratumoral) and systemic (intravenous) administration of JCXH-211 in tumor-bearing mice induced a high-level expression of IL-12 in tumor tissues, leading to modulation of tumor microenvironment and systemic activation of antitumor immunity. Particularly, JCXH-211 can inhibit the tumor-infiltration of polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs). When combined with anti-PD1 antibody, it was able to enhance the recruitment of T cells and NK cells into tumors. In multiple mouse solid tumor models, intravenous injection of JCXH-211 not only eradicated large preestablished tumors, but also induced protective immune memory that prevented the growth of rechallenged tumors. Finally, intravenous injection of JCXH-211 did not cause noticeable systemic toxicity in tumor-bearing mice and non-human primates. Thus, our study demonstrated the feasibility of intravenous administration of JCXH-211 for the treatment of advanced cancers.

The unearthed artifacts from the ruins of the Weiyang Palace in the Han Dynasty’s Chang’an City include a large number of bone stick relics. The front and back of each bone stick form a pair, with similar appearances within each pair, indicating a matching relationship. However, the close resemblance in shape and complex texture features of the bone sticks make traditional image matching methods inefficient and less accurate. To address these challenges, this paper proposes a ConvNeXt-based Siamese network for bone stick image matching, utilizing feature similarity metrics. The method introduces a polarized self-attention module to enhance the model’s focus on the edges and texture features of the bone sticks, thereby improving the feature extraction capability of the ConvNeXt network. The utilization of DIS-Net for background normalization reduces noise interference, enhancing the precision of model matching. The adaptive adjustment of the learning rate using the cosine annealing algorithm accelerates network convergence. Additionally, transfer learning and contrastive learning methods are employed to pre-train the network, expediting convergence and improving matching accuracy. Experimental results demonstrate that compared to Siamese network algorithms with backbone networks such as VGG16, ResNet50, and MobileNet, the proposed method achieves an accuracy of 88.46% and 80% at Rank-10. This indicates a higher matching accuracy, providing an effective solution for automated bone stick matching.

Background: As a scaffold protein, calcium/calmodulin-dependent serine protein kinase (CASK) has been extensively studied in a variety of tissues throughout the body. The Cask gene is ubiquitous in several tissues, such as the neurons, islets, heart, kidneys and sperm, and is mostly localised in the cytoplasm adjacent to the basement membrane. CASK binds to a variety of proteins through its domains to exerting its biological activity. Scope of review: Here, we discuss the role of CASK in multiple tissues throughout the body. The role of different CASK domains in regulating neuronal development, neurotransmitter release and synaptic vesicle secretion was emphasised; the regulatory mechanism of CASK on the function of pancreatic islet β cells was analysed; the role of CASK in cardiac physiology, kidney and sperm development was discussed; and the role of CASK in different tumours was compared. Finally, we clarify the importance of the Cask gene in the body, and how deletion or mutation of the Cask gene can have adverse consequences. Major conclusions: CASK is a conserved gene with similar roles in various tissues. The function of the Cask gene in the nervous system is mainly involved in the development of the nervous system and the release of neurotransmitters. In the endocrine system, an involvement of CASK has been reported in the process of insulin vesicle transport. CASK is also involved in cardiomyocyte ion channel regulation, kidney and sperm development, and tumour proliferation. CASK is an indispensable gene for the whole body, and CASK mutations can cause foetal malformations or death at birth. In this review, we summarise the biological functions and pathological mechanisms of CASK in various systems, thereby providing a basis for further in-depth studies of CASK functions.

Background: Creating a child-friendly social environment is an important component of promoting child-friendly city development. This study aims to explore the key indicators of friendly family, school and community social environments from the perspective of children's conduct problems and prosocial behaviors. Method: The sample included grade 3–5 students from one public elementary school in the urban areas and another public elementary school in the rural areas of a Chinese city pursuing a child-friendly philosophy. A total of 418 participants were included in this study. Data on conduct problems, prosocial behaviors and the social environment were collected. To effectively select important variables and eliminate estimation bias, this study used LASSO regression to identify key indicators predicting children's conduct problems and prosocial behavior, followed by linear regression coefficient estimation and significance testing. Results: Creating a friendly family environment (ensuring family members' assistance with academic problems) and school environment (reducing cheating, fighting, and unfriendly teacher language) was associated with reduced conduct problems in children. Creating a positive family atmosphere (enhancing children's trust in family members), school environment (increasing parents' awareness of school affairs, reinforcing students' prosocial behavior, increasing extracurricular activity programs, and encouraging student engagement in academics) and community environment (respecting all children in the community) was associated with improving children's prosocial behavior. Conclusions: This study transforms the multidimensional, complex child-friendly social environment evaluation indicator system into concise and specific measurement indicators, which can provide theoretical and practical implications for government decision-making in child-friendly city development through empirical research.

Abstract Background Radiation pneumonitis (RP) is one of the common side effects after adjuvant radiotherapy in breast cancer. Irradiation dose to normal lung was related to RP. We aimed to propose an organ features based on deep learning (DL) model and to evaluate the correlation between normal lung dose and organ features. Methods Patients with pathology-confirmed invasive breast cancer treated with adjuvant radiotherapy following breast-conserving surgery in four centers were included. From 2019 to 2020, a total of 230 patients from four nationwide centers in China were screened, of whom 208 were enrolled for DL modeling, and 22 patients from another three centers formed the external testing cohort. The subset of the internal testing cohort (n = 42) formed the internal correlation testing cohort for correlation analysis. The outline of the ipsilateral breast was marked with a lead wire before the scanning. Then, a DL model based on the High-Resolution Net was developed to detect the lead wire marker in each slice of the CT images automatically, and an in-house model was applied to segment the ipsilateral lung region. The mean and standard deviation of the distance error, the average precision, and average recall were used to measure the performance of the lead wire marker detection model. Based on these DL model results, we proposed an organ feature, and the Pearson correlation coefficient was calculated between the proposed organ feature and ipsilateral lung volume receiving 20 Gray (Gy) or more (V20). Results For the lead wire marker detection model, the mean and standard deviation of the distance error, AP (5 mm) and AR (5 mm) reached 3.415 ± 4.529, 0.860, 0.883, and 4.189 ± 8.390, 0.848, 0.830 in the internal testing cohort and external testing cohort, respectively. The proposed organ feature calculated from the detected marker correlated with ipsilateral lung V20 (Pearson correlation coefficient, 0.542 with p

Mining cables are affected by the harsh environment of coal mines, and are prone to insulation degradation and sheath damage. The traditional offline diagnostic methods such as low-voltage pulse method and partial discharge method are often used for detecting mining cables. The methods are complex to operate and have low accuracy, making it difficult to meet the needs of modern coal mine production. However, the existing harmonic based cable fault diagnosis methods have problems such as bulky detection devices, low detection precision, and difficulty in application in coal mines. In order to solve the above problems, a degradation monitoring and diagnosing method of mining cables based on current harmonic features is proposed. The method extracts high-order harmonic content information in cables as fault feature vectors, normalize the feature vectors, and then import them into extreme gradient boost tree (XGBoost) model. Combined with known cable fault degradation value data, a training sample set is formed to train the XGBoost model. Finally, the method uses the constructed XGBoost model to monitor and diagnose cable degradation in real-time. The simulation results show that the relative energy of the extracted high-order harmonic vectors from different parts of the cable is significantly different. The extracted high-order harmonic vectors can characterize the operating status of different parts of the cable. The goodness of fit parameter R2 of the XGBoost model is as high as 0.93, and the error is small. The case analysis results verify that the degradation monitoring and fault diagnosis method of mining cables based on current harmonic features can provide real-time and accurate monitoring and diagnosis of the operation status and degradation faults of mining cables.

Objective To study the effect of artificial intelligence in the pathological diagnosis of periapical cysts and to explore the application of artificial intelligence in the field of oral pathology. Methods Pathological images of eighty-seven periapical cysts were selected as subjects to read, and a neural network with a U-net structure was constructed. The 87 HE images and labeled images of periapical cysts were divided into a training set (72 images) and a test set (15 images), which were used in the training model and test model, respectively. Finally, the target level index F1 score, pixel level index Dice coefficient and receiver operating characteristic (ROC) curve were used to evaluate the ability of the U-net model to recognize periapical cyst epithelium. Results The F1 score of the U-net network model for recognizing periapical cyst epithelium was 0.75, and the Dice index and the areas under the ROC curve were 0.685 and 0.878, respectively. Conclusion The U-net network model constructed by artificial intelligence has a good segmentation result in identifying periapical cyst epithelium, which can be preliminarily applied in the pathological diagnosis of periapical cysts and is expected to be gradually popularized in clinical practice after further verification with large samples.

Molten chloride salts hold significant promise as both thermal transfer and storage media for next-generation concentrated solar power (CSP) systems. However, molten chlorides pose a considerable corrosion risk to structural materials, particularly Ni-based alloys. One approach to enhancing corrosion resistance is through the optimization of grain structure; however, it remains uncertain whether increasing or decreasing grain size enhances corrosion resistance. A cellular automata (CA) program was developed to evaluate the interplay between grain size and corrosion in Ni-based alloy. Our CA program tracks alloy composition, surface roughness, and thickness loss via a graphical user interface, displaying corrosion and diffusion status, and multiple user input cards for tuning the simulation. CA simulations of Inconel 625 indicate enhanced corrosion resistance with increased grain size, with passivating oxides offering limited protection. Additionally, the temporal evolution of alloy surface roughness demonstrates notable fluctuations, with abrupt increases attributed to corrosion along vertical grain boundaries and sudden decreases to grain detachment from the protective film.

Abstract With the rapid growth of cloud computing services, the high energy consumption of cloud data centers has become a critical concern of the cloud computing society. While virtual machine (VM) consolidation is often used to reduce energy consumption, excessive VM consolidation may lead to local hot spots and increase the risk of equipment failure. One possible solution to this problem is to utilize thermal-aware scheduling, but existing approaches have trouble realizing the balance between SLA and energy consumption. This paper proposes a novel method to manage cloud data center resources based on thermal management (TM-VMC), which optimizes total energy consumption and proactively prevents hot spots from a global perspective. Its VM consolidation process includes four phases where the VMs scheduler uses an improved ant colony algorithm (UACO) to find appropriate target hosts for VMs based on server temperature and utilization status obtained in real-time. Experimental results show that the TM-VMC approach can proactively avoid data center hot spots and significantly reduce energy consumption while maintaining low Service Level Agreement (SLA) violation rates compared to existing mainstream VM consolidation algorithms with workloads from real-world data centers.

Objective To explore and construct an optimization strategy for large-scale nucleic acid collection mode in the emergency conditions of putting the makeshift COVID-19 hospitals into use. Methods A self-pre- and post- control study was conducted on 542 COVID-19 patients in the makeshift hospital located in National Exhibition and Convention Center (Shanghai) in April 2022. According to the elution period with an interval of 1 week, nucleic acid collection was carried out in red-zone package mode, in-cabin and out-cabin linkage mode and integrated precision sampling mode, and the consuming time of work was recorded. The electronic survey used to detect the satisfaction of patients. At the same time, the results of the levels of teamwork, patient cooperation and satisfaction of 106 medical staff participating in nucleic acid testing under the above different sampling modes were collected. Results The work consumption time of the integrated precision sampling mode was significantly shorter than that of the other two sampling modes (P < 0.01), the percentage patient satisfaction rate in the integrated precision sampling mode was higher than that of the other two sampling modes (P < 0.05), and the team cooperation, patient cooperation, and the percentage of satisfaction of medical staff were significantly higher than those of the other two sampling modes (P < 0.01) in the integrated precision sampling mode. Conclusion The integrated precision sampling mode can significantly shorten the sampling time in large-scale nucleic acid collection, effectively improve the degree of cooperation between doctors and patients in sampling work and increase the satisfaction of patients and medical staff during the sampling process.

The sedimentary lithology is complex in the middle sub-member of the first member of the Liushagang Formation(L1-M) of the Weizhou-11A oilfield in the southwest Weizhou depression of the Beibu Gulf Basin. The reservoir changes rapidly in both vertical and horizontal directions, and the distribution scale and connectivity are challenging to predict, which seriously affects the oilfield development effect. Through core observation and description, 3D-seismic analysis, rock grain size, lithofacies, logging facies, and modern deposit analogy analysis, it is believed that the depositional fluids control the sand bodies and reservoir types. Braided stream bottom-load deposits (St, Sp, Sr), sandy debris flow deposits (Gmg, Gn), and turbidity deposits (Fhn) can form favorable reservoirs, which are mainly distributed in the braided channel, braided flow bar, mouth bar and sheet sand microfacies of fan delta front. We discussed the spatial distribution law and geometric shape of sedimentary microfacies in four middle-term cycles and proposed five types and eight kinds of sand-body stack types and connectivity characteristics of the fan delta front. The reservoir model and the empirical values of width, thickness, and the width-to-thickness ratio of main sedimentary microfacies are established, which provide a scientific basis for the oilfield development.

Key points The U-Net model showed a good performance for prostate zonal segmentation. The U-Net model outperformed the junior radiologist in peripheral zone segmentation. Prostate morphology and MR scanner parameters may affect the model’s performance.

Bovine coronavirus (BCoV), bovine rotavirus, bovine viral diarrhea virus, and bovine astrovirus are the most common intestinal pathogenic viruses causing diarrhea in cattle. We collected 1646 bovine fecal samples from January 2020 to August 2023. BCoV was the major pathogen detected, with a positive rate of 34.02% (560/1646). Of the 670 diarrheal samples and 976 asymptomatic samples, 209 and 351 were BCoV-positive, respectively. Studying the relevance of diarrhea associated with BCoV has shown that the onset of diarrheal symptoms post-infection is strongly correlated with the cattle’s age and may also be related to the breed. We amplified and sequenced the hemagglutinin esterase (HE), spike protein, and whole genomes of the partially positive samples and obtained six complete HE sequences, seven complete spike sequences, and six whole genomes. Molecular characterization revealed that six strains were branched Chinese strains, Japanese strains, and partial American strains from the GⅡb subgroup. Strains HBSJZ2202 and JSYZ2209 had four amino acid insertions on HE. We also analyzed ORF1a and found disparities across various regions within GIIb, which were positioned on separate branches within the phylogenetic tree. This work provides data for further investigating the epidemiology of BCoV and for understanding and analyzing BCoV distribution and dynamics.

Mammalian orthoreovirus (MRV) infections are ubiquitous in multiple mammalian species including humans, and mainly causes gastroenteritis and respiratory disease. In this study, we developed a rapid and sensitive TaqMan qRT-PCR method for MRV detection based on the primers and probe designed within the conserved L1 gene. The qRT-PCR assay was evaluated for its sensitivity, specificity, efficiency and reproducibility. It was found that the detection sensitivity was equivalent to 10 DNA copies/μL, and the standard curves had a linear correlation of R2 = 0.998 with an amplification efficiency of 99.6%. The inter- and intra-assay coefficients of variation (CV%) were in the range of 0.29% to 2.16% and 1.60% to 3.60%, respectively. The primer sets specifically amplified their respective MRV segments and had the highest detection sensitivities of 100.25 TCID50/mL with amplification efficiencies of 99.5% (R2 = 0.999). qRT-PCR was used for MRV detection from samples of sheep, goats, and calves from four regions in China, and the overall MRV prevalence was 8.2% (35/429), whereas 17/429 (4.0%) were detected by RT-PCR and 14/429 (3.3%) by virus isolation. The qRT-PCR assay showed significantly higher sensitivity than RT-PCR and virus isolation. Results from an epidemiological survey indicated that the positive rate of MRV in rectal swabs from sheep and goats tested in Shaanxi, Jiangsu, and Xinjiang were 9/80 (11.3%), 12/93 (12.9%) and 14/128 (10.9%), respectively. In goats and sheep, MRV prevalence was obviously associated with season and age, with a high positive rate of more than 8% during September to April and approximately 13% in small ruminant animals under two months of age. This is the first instance of MRV infection in sheep and goats in China, thus broadening our knowledge of MRV hosts. Consequently, primer optimization for qRT-PCR should not only prioritize amplification efficiency and specificity, but also sensitivity. This assay will contribute to more accurate and rapid MRV monitoring by epidemiological investigation, viral load, and vaccination efficacy.

Objective: Non-invasive fetal ECG (NI-FECG) provides a non-invasive method to monitor the health of the fetus. However, the NI-FECG is easily interfered by noise, which makes the signal quality decline, leading to the fetal heart rate (FHR) monitoring becoming a challenging task. Methods: In this work, an algorithm for dynamic evaluation of signal quality is proposed to improve the multi-channel FHR monitoring. The innovation of the method is to assess the signal quality in the process of multi-channel fetal QRS (FQRS) complexes detection. Specifically, the detected FQRS is used as quality unit. Each quality unit can be a true R peak (TR) or a false R peak (FR). It is the basic quality information in this work. The signal quality of each channel is estimated by estimating the correctness of the detection results. Further, the TRs of all channels can be fused to obtain more reliable fetal heart rate monitoring. Main results: Analysis results demonstrate that the proposed algorithm is capable of selecting the good quality signal for FQRS detection achieving 97.40% PPV, 98.33% SE and 97.86% F1. Significance: This work sheds light on the quality assessment of fetal monitoring signal.

A large number of bone stick cultural relics have been unearthed in Weiyang Palace of Han Period Chang’an City, Xi’an City, Shaanxi Province, China. Utilizing deep learning-based image classification methods can improve the efficiency of categorizing bone stick fracture locations and colors. However, due to factors such as variations in surface texture features and different degrees of wear on the bone sticks, the classification accuracy of the model is low. To address this issue, this paper proposes a bone stick image classification method using the YOLOv5s-ViT cascade model. The method incorporates the C3CA attention module to enhance the model’s recognition of fracture areas, reduce interference from the image background, and improve the effectiveness of the Vision Transformer self-attention mechanism. Furthermore, Increase the learning rate by comparing the training data of the test to improve the training efficiency of the model. Lastly, the Batch Normalization layer is introduced to normalize the output of the encoder, suppress model training divergence, and enhance generalization ability. The experimental results show that the average recognition accuracy of the bone stick fracture region features of this paper reaches 97.6%, the average recall rate reaches 93.3%, which is 2.1% and 6.0% higher than the YOLOv5s model, respectively, and the average classification accuracy reaches 88.7%, which is 7.9% higher than the Vision Transformer model, and can effectively improve the classification accuracy of bone stick images.

A large number of bone stick fragments were unearthed at the Weiyang Palace, and the manual stitching method is inefficient and time-consuming, therefore Image Stitching Method of Bone Stick Fragment Based on Similarity Freeman code Matching is proposed by this paper to improve bone stick stitching efficiency. The Freeman code is used to represent the contour of the true color RGB image of bone stick fragments, and the direction change dense feature of the bone stick fragment fracture is fused with the Freeman code difference to represent the change direction feature to locate the fracture boundary. At the same time, the integer basic operation is used to replace the complex calculus calculation to improve the efficiency of the algorithm; The longest common subsequence algorithm is used to perform local similarity rough matching on Freeman code of the contour at the fragment fracture, and then the angle and distance error threshold is set according to the prior knowledge of manual stitching to reduce the matching error; Finally, according to the matching results, the complete bone stick contour binary image is drawn. Compared with other algorithms, the contour Cosine similarity accuracy of the bone stick image stitched by this algorithm is improved by 21.68%, which can be accurate to 97.80%; the Editing distance similarity accuracy is improved by 14.29%, which can be accurate to 91.87%;the Peak signal-to-noise ratio is improved by 83%, which can be accurate to 31.13%;the Structural Similarity is improved by 29%, which can be accurate to 0.87; the Figure of merit is improved by 39%, which can be accurate to 0.85. The experiment results show that the algorithm proposed in this paper can effectively assist the stitching work of bone stick cultural relics.

Abstract Diabetic kidney disease (DKD) is a major public health issue because of its refractory nature. Ferroptosis is a newly coined programmed cell death characterized by the accumulation of lipid reactive oxygen species (ROS). However, the prognostic and diagnostic value of ferroptosis-related genes (FRGs) and their biological mechanisms in DKD remain elusive. The gene expression profiles GSE96804, GSE30566, GSE99339 and GSE30528 were obtained and analyzed. We constructed a reliable prognostic model for DKD consisting of eight FRGs (SKIL, RASA1, YTHDC2, SON, MRPL11, HSD17B14, DUSP1 and FOS). The receiver operating characteristic (ROC) curves showed that the ferroptosis-related model had predictive power with an area under the curve (AUC) of 0.818. Gene functional enrichment analysis showed significant differences between the DKD and normal groups, and ferroptosis played an important role in DKD. Consensus clustering analysis showed four different ferroptosis types, and the risk score of type four was significantly higher than that of other groups. Immune infiltration analysis indicated that the expression of macrophages M2 increased significantly, while that of neutrophils and mast cells activated decreased significantly in the high-risk group. Our study identified and validated the molecular mechanisms of ferroptosis in DKD. FRGs could serve as credible diagnostic biomarkers and therapeutic targets for DKD.

The rejoining of bone sticks holds significant importance in studying the historical and cultural aspects of the Han Dynasty. Currently, the rejoining work of bone inscriptions heavily relies on manual efforts by experts, demanding a considerable amount of time and energy. This paper introduces a multi-scale feature fusion Siamese network guided by edge contour (MFS-GC) model. Constructing a Siamese network framework, it first uses a residual network to extract features of bone sticks, which is followed by computing the L2 distance for similarity measurement. During the extraction of feature vectors using the residual network, the BN layer tends to lose contour detail information, resulting in less conspicuous feature extraction, especially along fractured edges. To address this issue, the Spatially Adaptive DEnormalization (SPADE) model is employed to guide the normalization of contour images of bone sticks. This ensures that the network can learn multi-scale boundary contour features at each layer. Finally, the extracted multi-scale fused features undergo similarity measurement for local matching of bone stick fragment images. Additionally, a Conjugable Bone Stick Dataset (CBSD) is constructed. In the experimental validation phase, the MFS-GC algorithm is compared with classical similarity calculation methods in terms of precision, recall, and miss detection rate. The experiments demonstrate that the MFS-GC algorithm achieves an average accuracy of 95.5% in the Top-15 on the CBSD. The findings of this research can contribute to solving the rejoining issues of bone sticks.

Merging BICs with robust Q factors against fabrication imperfections can be further improved by higher-charged BICs. Moreover, higher-charged BICs offer great flexibility in realizing steerable merging BICs.

Magnolol (M), a hydroquinone containing an allyl side chain, is one of the major active components of Houpoea officinalis for antioxidation and anti-aging. To enhance the antioxidant activity of magnolol, the different sites of magnolol were structurally modified in this experiment, and a total of 12 magnolol derivatives were obtained. Based on the preliminary exploration of the anti-aging effect of magnolol derivatives in a Caenorhabditis elegans (C. elegans) model. Our results indicate that the active groups of magnolol exerting anti-aging effects were allyl groups and hydroxyl on the phenyl. Meanwhile, the anti-aging effect of the novel magnolol derivative M27 was found to be significantly superior to that of magnolol. To investigate the effect of M27 on senescence and the potential mechanism of action, we investigated the effect of M27 on senescence in C. elegans. In this study, we investigated the effect of M27 on C. elegans physiology by examining body length, body curvature and pharyngeal pumping frequency. The effect of M27 on stress resistance in C. elegans was explored by acute stress experiments. The mechanism of M27 anti-aging was investigated by measuring ROS content, DAF-16 nuclear translocation, sod-3 expression, and lifespan of transgenic nematodes. Our results indicate that M27 prolonged the lifespan of C. elegans. Meanwhile, M27 improved the healthy lifespan of C. elegans by improving pharyngeal pumping ability and reducing lipofuscin accumulation in C. elegans. M27 increased resistance to high temperature and oxidative stress in C. elegans by reducing ROS. M27 induced DAF-16 translocation from cytoplasm to nucleus in transgenic TJ356 nematodes and upregulated the expression of sod-3 (a gene downstream of DAF-16) in CF1553 nematodes. Furthermore, M27 did not extend the lifespan of daf-16, age-1, daf-2, and hsp-16.2 mutants. This work suggests that M27 may ameliorate aging and extend lifespan in C. elegans through the IIS pathway.

IntroductionChina has the largest youth population in the world. To better implement the Smoke-free School Initiative, this study aims to examine the protective and risk factors for different smoking behaviors (never smoked, experimental smoking, and current smoking) among school adolescents based on social cognitive theory.MethodsThis research was a secondary analysis of a cross-sectional survey of middle schools in Huli District of Xiamen, China. The final sample consisted of 1937 participants with an average age of 15.41 (SD = 1.64). Descriptive statistics were used to summarize the sociodemographic characteristics of the sample. Multivariate multinomial logistic regression analysis was performed using four models.ResultsOf the respondents, 1685 (86.99%) were never smokers, 210 (10.84%) were experimental smokers, and 42 (2.17%) were current smokers. Social norms, positive outcome expectations, anti-smoking self-efficacy, and attitudes toward control tobacco policies were associated with adolescents' smoking behaviors. The number of smoking family members, classmates smoking, the perception that smoking is cool and attractive, and attitudes toward control tobacco policies were the predictors of current smoking behavior (p < 0.05). In contrast, friends smoking and individual and social relationship motivation were associated with only experimental smoking (p < 0.05).DiscussionThe relationship of social norms, positive outcome expectations, anti-smoking self-efficacy, and attitudes toward control tobacco policies varied across smoking behaviors. Family, school, society and the government need to cooperate in prevention and intervention programs for adolescent smoking. The relationships between these factors and adolescents' different smoking behaviors needs to be further verified.

Abstract Background A high-quality docking method tends to yield multifold gains with half pains for the new drug development. Over the past few decades, great efforts have been made for the development of novel docking programs with great efficiency and intriguing accuracy. AutoDock Vina (Vina) is one of these achievements with improved speed and accuracy compared to AutoDock4. Since it was proposed, some of its variants, such as PSOVina and GWOVina, have also been developed. However, for all these docking programs, there is still large room for performance improvement. Results In this work, we propose a parallel multi-swarm cooperative particle swarm model, in which one master swarm and several slave swarms mutually cooperate and co-evolve. Our experiments show that multi-swarm programs possess better docking robustness than PSOVina. Moreover, the multi-swarm program based on random drift PSO can achieve the best highest accuracy of protein–ligand docking, an outstanding enrichment effect for drug-like activate compounds, and the second best AUC screening accuracy among all the compared docking programs, but with less computation consumption than most of the other docking programs. Conclusion The proposed multi-swarm cooperative model is a novel algorithmic modeling suitable for protein–ligand docking and virtual screening. Owing to the existing coevolution between the master and the slave swarms, this model in parallel generates remarkable docking performance. The source code can be freely downloaded from https://github.com/li-jin-xing/MPSOVina .

Abstract Live-attenuated vaccines (LAVs) represent a promising approach for flavivirus vaccine development. In the present study, we demonstrated a method for generating flavivirus LAVs based on breaking spatially and temporally regulated C-prM cleavage to disturb the viral assembly process, using an avian flavivirus (Tembusu virus) as the model. Using reverse genetics technology, we successfully generated two recombinant viruses (CQW1-IRES-mC and CQW1-MINI-mC) with bicistronic genomic RNA in which native capsid genes were deleted and instead expressed in the 3’UTR under the control of an internal ribosome entry site (IRES) or minimum IRES. Both viruses showed a significantly attenuated phenotype in vitro due to impaired viral assembly, and the engineered mutations were genetically stable in vitro within ten passages. Importantly, their virulence was also highly attenuated in ducklings and suckling mice and did not cause any overt clinical symptoms or mortality. In addition, a single dose of immunization with any of these mutant viruses could completely protect ducklings from a lethal challenge, and no viremia was detected after immunization and challenge, even though the viruses induced a relatively moderate immune response in terms of the T-lymphocytes proliferative response and the level of neutralization antibodies compared with that obtained with the wild-type virus. Besides, a recombinant virus ectopically expressing the prM-E protein was also generated in the present study, but this virus was too attenuated with severely decreased proliferation. Our results indicated that the use of a recombinant flavivirus that ectopically expresses structural proteins could be an effective and universal method for flavivirus LAVs development.

IntroductionWith the COVID-19 pandemic in China, a large number of mild or ordinary confirmed cases have been sent to Fangcang shelter hospitals for treatment. We aimed to investigate the mental health condition of Fangcang patients 2 years after the pandemic when patients knew more about COVID-19 and the virus was less virulent. We focused on the effect of dysfunctional beliefs and attitudes about sleep on depression, anxiety, and insomnia.MethodsA total of 1,014 patients from two large Fangcang shelter hospitals in Shanghai between 22 April and 8 May 2022 completed a set of questionnaires comprising: the Dysfunctional Beliefs and Attitudes about Sleep scale, the Generalized Anxiety Disorder scale, the Patient Health Questionnaire, and the Insomnia Severity Index scale.ResultsResults show that the positive screening rates for anxiety, depression, and insomnia among tested patients were 55.3, 27.0, and 47.8%, respectively. Patients were more likely to report higher anxiety, depression, and insomnia, and to endorse affective and sleep disorders if they were: female, aged 18–40 years, with undergraduate course or above, white-collar employees, or those who thought the pandemic would have severe economic effects. About 51.4% of the participants had dysfunctional beliefs about sleep to varying degrees. Compared with patients who had accurate beliefs about sleep, the ratios of insomnia, anxiety, and depression were significantly higher among patients with dysfunctional beliefs about sleep.DiscussionAttention should be paid to the mental health problems of patients in Fangcang shelter hospitals. The results indicate that dysfunctional beliefs about sleep significantly increased anxiety, depression, and insomnia of Fangcang patients.

Ischemic stroke is a kind of central nervous disease characterized by high morbidity, high mortality, and high disability. Inflammation and autophagy play important roles in cerebral ischemia/reperfusion (CI/R) injury. The present study characterizes the effects of TLR4 activation on inflammation and autophagy in CI/R injury. An in vivo CI/R rat injury model and an in vitro hypoxia/reoxygenation (H/R) SH-SY5Y cell model were established. Brain infarction size, neurological function, cell apoptosis, inflammatory mediators’ levels, and gene expression were measured. Infarction, neurological dysfunction, and neural cell apoptosis were induced in CI/R rats or in H/R-induced cells. The expression levels of NLRP3, TLR4, LC3, TNF-α, interleukin-1 (IL-1), interleukin-6 (IL-6), and interleukin-18 (IL-18) clearly increased in I/R rats or in H/R-induced cells, while TLR4 knockdown significantly suppressed NLRP3, TLR4, LC3, TNF-α, and interleukin-1/6/18 (IL-1/6/18) in H/R-induced cells, as well as cell apoptosis. These data indicate that TLR4 upregulation induced CI/R injury via stimulating NLRP3 inflammasome and autophagy. Therefore, TLR4, is a potential therapeutic target to improve management of ischemic stroke.

Shale oil is mainly extracted by fracturing. However, it is difficult to determine the optimum construction parameters to obtain maximum productivity. In this paper, a fuzzy comprehensive production evaluation model for fractured shale oil horizontal wells based on random forest algorithm and coordinated principal component analysis is proposed. The fracturing parameters of the target wells are optimized by combining this model with an orthogonal experimental design. The random forest algorithm was used to calculate the importance of data sample factors. The main controlling factors of the production of fractured horizontal wells in shale oil were obtained. To reduce the noise of the sample data, principal component analysis was used to reduce the dimensions of the main control factors. Furthermore, the random forest algorithm was used to determine the weight of the principal components after reducing the dimensionality. The membership function of the main control factors after reducing dimensionality was established by combining the fuzzy statistics and assignment methods. In addition, the membership matrix of the effect prediction of fractured horizontal wells in shale oil was determined. The fuzzy comprehensive evaluation method is used to score and evaluate the effect of fractured horizontal wells. Combined with the orthogonal experimental design method, the optimized parameter design of a fractured horizontal well considering the comprehensive action of multiple parameters is realized. After construction according to the optimized parameters, production following fracturing increases significantly. This verifies the rationality of the optimization method that is proposed in this paper.

Abstract Background Bovine viral diarrhea virus (BVDV) is a major pathogen that causes bovine viral diarrhea/mucosal disease (BVD-MD), which has become a global infectious disease due to its wide spread and the lack of effective treatment. The process of BVDV infection is complex. Once infected, host immune cells are activated and modulated. As a major immune cell, peripheral blood lymphocyte cells (PBLCs) are the primary target of BVDV. In order to further understand the mechanism of BVDV- host interaction, the expression profiles of host lymphocytes mRNAs associated with BVDV infection were investigated by transcriptomic sequencing analysis. Results The transcriptomic sequencing analysis was performed on bovine PBLCs infected with CP BVDV-2 GS2018 after 12 h of infection. Gene expression profiling demonstrated that 1052 genes were differentially expressed in GS2018 infected PBLCs compared with the control group. Of these genes, 485 genes were up-regulated and 567 were down-regulated. The 19 differential expressed genes (DEGs) were selected for validation using quantitative real-time PCR and the results were consistent with the results of RNA-Seq. Gene ontology enrichment and KEGG pathway analysis showed that 1052 DEGs were significantly enriched in 16 pathways, including cytokine-cytokine receptor interaction, IL17, PI3K-Akt, MAPK and TNF signaling pathway. PPI network analysis showed that IL17A, IFN-γ and TNF-α interacted with various proteins and may play crucial roles in BVDV-2 infection. Of note, we confirmed that GS2018 induced Th17 cell differentiation in PBLCs and persistently increased the expression levels of IL17A. In turn, the replication of GS2018 was inhibited by IL17A. Conclusion In this study, the transcription changes of DEGs related to host immune responses in bovine PBLCs were caused by CP BVDV-2 infection. In particular, the effector molecules IL17A of Th17 cells were significantly up-regulated, which inhibited viral replication. These results will contribute to exploration and further understanding of the host immune response mechanism and interaction between host and BVDV-2.

A method of ultra high performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) combined with modified QuEChERS purification technology was developed for the simultaneous determination of 25 veterinary medicine residues including four classes (sulfonamides, quinolones, chloramphenicols and amantidines) in chicken and egg. The samples were hydrolyzed by dilute hydrochloric acid, extracted by acetonitrile. Sodium chloride was added into the extracting solution to salt out. The acetonitrile was took out and degreased by n-hexanecyclohexane solution (1∶1,V/V) after stratification of acetonitrile and aqueous phase and concentrated to dry. The residues were dissolved with 0.2% formic acid ethyl acetate to remove the sodium chloride by filtrating and the filtrate was concentrated to dry again, then the sample was purified with a mixture of 30 mg of C18 and 60 mg PSA after adding 0.2% formic acid methanol. The target compounds were separated by ZORBAX C18 chromatography column (50 mm×2.1 mm×1.8 μm), the mass spectrometer data were acquired under multiple reaction monitoring (MRM) of positive and negative modes at the same time, and the residues were quantitated by isotope internal standard method. The results showed that the linear of 25 veterinary medicines is good in the range of 0.2~250 μg/L. The linear correlation coefficients are more than 0.99, and the detection limits are in the range of 0.1~0.9 μg/kg. The limits of quantification are 0.3~3.0 μg/kg. The average recoveries at three spiked levels (about 1, 5 and 20 folds of quantitative limits) are 79.5%~119% with the relative standard deviations of 0.9%~9.2%. The method is rapid,simple, accurate, sensitive and cheap, which is suitable for simultaneous determination of multiple vererinary medicine residues in eggs and chicken.

Abstract Background To develop a machine learning-based CT radiomics model is critical for the accurate diagnosis of the rapid spreading coronavirus disease 2019 (COVID-19). Methods In this retrospective study, a total of 326 chest CT exams from 134 patients (63 confirmed COVID-19 patients and 71 non-COVID-19 patients) were collected from January 20 to February 8, 2020. A semi-automatic segmentation procedure was used to delineate the volume of interest (VOI), and radiomic features were extracted. The Support Vector Machine (SVM) model was built on the combination of 4 groups of features, including radiomic features, traditional radiological features, quantifying features, and clinical features. By repeating cross-validation procedure, the performance on the time-independent testing cohort was evaluated by the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity. Results For the SVM model built on the combination of 4 groups of features (integrated model), the per-exam AUC was 0.925 (95% CI 0.856 to 0.994) for differentiating COVID-19 on the testing cohort, and the sensitivity and specificity were 0.816 (95% CI 0.651 to 0.917) and 0.923 (95% CI 0.621 to 0.996), respectively. As for the SVM models built on radiomic features, radiological features, quantifying features, and clinical features, individually, the AUC on the testing cohort reached 0.765, 0.818, 0.607, and 0.739, respectively, significantly lower than the integrated model, except for the radiomic model. Conclusion The machine learning-based CT radiomics models may accurately classify COVID-19, helping clinicians and radiologists to identify COVID-19 positive cases.

ABSTRACT Tembusu virus (TMUV), an avian mosquito-borne flavivirus, was first identified from Culex tritaeniorhynchus in 1955. To validate the effects of the 3′-untranslated region (3′UTR) in viral host-specific adaptation, we generated a set of chimeric viruses using CQW1 (duck strain) and MM 1775 (mosquito strain) as backbones with heterogeneous 3′UTRs. Compared with rMM 1775, rMM-CQ3′UTR (recombinant MM 1775 virus carrying the 3′UTR of CQW1) exhibited enhanced proliferation in vitro, with peak titers increasing by 5-fold in duck embryonic fibroblast (DEF) cells or 12-fold in baby hamster kidney (BHK-21) cells; however, the neurovirulence of rMM-CQ3′UTR was attenuated in 14-day-old Kunming mice via intracranial injection, with slower weight loss, lower mortality, and reduced viral loads. In contrast, rCQ-MM3′UTR showed similar growth kinetics in vitro and neurovirulence in mice compared with those of rCQW1. Then, the Stem-loop I (SLI) structure, which showed the highest variation within the 3′UTR between CQW1 and MM 1775, was further chosen for making chimeric viruses. The peak titers of rMM-CQ3′UTRSLI displayed a 15- or 4-fold increase in vitro, and the neurovirulence in mice was attenuated, compared with that of rMM 1775; rCQ-MM3′UTRSLI displayed comparable multiplication ability in vitro but was significantly attenuated in mice, in contrast with rCQW1. In conclusion, we demonstrated that the TMUV SLI structure of the 3′UTR was responsible for viral host-specific adaptation of the mosquito-derived strain in DEF and BHK-21 cells and regulated viral pathogenicity in 14-day-old mice, providing a new understanding of the functions of TMUV 3′UTR in viral host switching and the pathogenicity changes in mice. IMPORTANCE Mosquito-borne flaviviruses (MBFVs) constitute a large number of mosquito-transmitted viruses. The 3′-untranslated region (3′UTR) of MBFV has been suggested to be relevant to viral host-specific adaptation. However, the evolutionary strategies for host-specific fitness among MBFV are different, and the virulence-related structures within the 3′UTR are largely unknown. Here, using Tembusu virus (TMUV), an avian MBFV as models, we observed that the duck-derived SLI of the 3′UTR significantly enhanced the proliferation ability of mosquito-derived TMUV in baby hamster kidney (BHK-21) and duck embryonic fibroblast (DEF) cells, suggesting that the SLI structure was crucial for viral host-specific adaptation of mosquito-derived TMUVs in mammalian and avian cells. In addition, all SLI mutant viruses exhibited reduced viral pathogenicity in mice, indicating that SLI structure was a key factor for the pathogenicity in mice. This study provides a new insight into the functions of the MBFV 3′UTR in viral host switching and pathogenicity changes in mice.

One major obstacle that limits the lifespan of insulin infusion pumps is surmounting the tissue site reaction at the device implantation site. All commercial insulin formulations contain insulin phenolic preservatives (IPPs) designed to ensure insulin protein stability and prolong shelf-life. However, our laboratory demonstrated that these preservatives are cytotoxic and induce inflammation. Mature mast cells (MCs) reside in cutaneous tissue and are one of the first responders to an epidermal breach. Upon activation, MCs release proinflammatory and immunomodulatory prepacked mediators that exacerbate these inflammatory reactions. Thus, we hypothesized that once the epidermis is breached, cutaneous MCs are triggered inciting the inflammatory response to IPP-induced inflammation. This hypothesis was pursued utilizing our modified in vivo mouse air pouch model, including a c-kit dependent (C57BL/6J-kitW-sh/W-sh) and a c-kit independent (Cpa3-Cre; Mcl-1fl/fl) MC-deficient mouse model. Leukocytes were quantified in the mouse air pouch lavage fluid following flow cytometry analysis for IPP infusion under three different states, insulin-containing phenolic preservatives (Humalog®), insulin preservatives alone, and normal saline as a control. The air pouch wall was assessed using histopathological evaluations. Flow cytometry analysis demonstrated a statistically significant difference in inflammatory cell recruitment for both MC-deficient mouse models when compared to the control strain including infused control saline. Significantly less inflammation was observed at the site of infusion for the MC-deficient strains compared to the control strain. Overall, concordant results were obtained in both mouse types, C57Bl6-kitW-sh/W-sh and Cpa3-Cre; Mcl-1fl/fl. These findings in multiple model systems support the conclusion that MCs have important or possible unique roles in IPP-induced inflammation.

Objective To establish a method for determination of the azide ions in blood by gas chromatography-mass spectrometry （GC-MS） following pentafluorobenzyl derivatization. Methods A blood sample of 0.2 mL was placed into a 10 mL glass test tube, and the internal standard sodium cyanide, derivatization reagent pentafluorobenzyl bromide and catalyst tetradecyl benzyl dimethyl ammonium chloride were added in turn. After vortex mixing, the mixture was heated with low-power microwave for 3 min. After centrifugation, the organic phase was taken for GC-MS analysis. Results The azide ions in blood had a good linear relationship in the mass concentration range of 0.5 to 20 μg/mL. The lowest detection limit was 0.25 μg/mL and the relative recovery was 91.36%-94.58%. The method was successfully applied to a case of death from sodium azide poisoning. The mass concentration of azide ions in the blood of the dead was 11.11 μg/mL. Conclusion The method developed in this paper has strong specificity and is easy to operate, which is suitable for the rapid detection of azide ions in blood.

ZIF-8 attracted more attention as the carbon support for oxygen reduction reaction catalyst due to its large specific surface area and regular pore structure in recent years. A series of FeN/ZIF-8 catalysts were prepared using ZIF-8, 1,10-phenanthroline as carbon and nitrogen precursor, as well as FeSO4·7H2O, FeAc, FeCl3·6H2O and FeC10H10 were used as different iron precursors, respectively. The influence of different iron precursors on the structure and oxygen reduction reaction(ORR) activities of FeN/ZIF-8 catalysts were investigated by X-ray diffraction, specific surface area and pore size distribution measurements, transmission electron microscope, thermogravimetric analysis, and linear sweep voltammetry. The results show that the catalyst prepared with FeSO4·7H2O as iron precursor has the initial potential of about 0.93 V, and the ORR is a four-electron process, which has better oxygen reduction catalytic activity. Moderate specific surface area and pore size distribution, good crystal structure and uniform particle dispersion, as well as the presence of Fe3C are the possible reasons of resulting in better ORR activity of FeN/ZIF-8 with FeSO4·7H2O as the iron precursor.

It is widely acknowledged that casein is an important allergenic protein in milk which may cause danger to customers. The identification and confirmation of caseins through mass spectrometry requires the selection of suitable characteristic peptides. In this study, by means of matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS), the three most representative specific peptides of caseins in cow milk were screened out with mass-to-charge ratios (m/z) of 830, 1195, and 1759, respectively. By comparing 2,5-dihydroxybenzoic acid (DHB) and α-cyano-4-hydroxycinnamic acid (CHCA) MALDI matrices, it was found that DHB was more suitable for peptide detection with the limits of detection (LODs) of 0.1 mg/L for α, β-casein. Furthermore, on the basis of verifying the characteristic peptides of casein from cow milk, this protocol was applied to goat milk authentication. Cow milk addition in goat milk was investigated by using the screened specific peptides. The results showed that the adulteration could be identified when the proportion of cow milk was 1% or more. When applied to inspect adulteration in five brands of commercial goat milk, specific peptides of bovine casein were detected in four of them. The method has the advantages of strong reliability, high throughput, simple preprocessing, and fast speed, which can provide powerful help for prewarning dairy allergen.

doi：10.3969/j.issn.1672⁃6731.2021.06.010