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Acute viral encephalitis is one of the serious infectious diseases. In order to analyze the diagnostic efficacy of serum procalcitonin (PCT), C-reactive protein (CRP), and S100B protein in acute viral encephalitis, a total of 100 children with acute viral encephalitis from July 2019 to December 2021 are selected and included in the viral encephalitis group. The results show that S100B protein model has high specificity and sensitivity and is simple to operate. It provides new ideas and directions for differential diagnosis, improvement, and optimization of relevant clinical diagnosis and treatment schemes and has high clinical value.

International Journal of Sociologies and Anthropologies Science Reviews, 3, 3, 203-216

Spinal cord injury (SCI) is a disastrous situation that affects many patients worldwide. A profound understanding of the pathology and etiology of SCI is of great importance in inspiring new therapeutic concepts and treatment. In recent years, exosomes, which are complex lipid membrane structures secreted nearly by all kinds of plants and animal cells, can transport their valuable cargoes (e.g., proteins, lipids, RNAs) to the targeted cells and exert their communication and regulation functions, which open up a new field of treatment of SCI. Notably, the exosome's advantage is transporting the carried material to the target cells across the blood–brain barrier and exerting regulatory functions. Among the cargoes of exosomes, microRNAs, through the modulation of their mRNA targets, emerges with great potentiality in the pathological process, diagnosis and treatment of SCI. In this review, we discuss the role of miRNAs transported by different cell-derived exosomes in SCI that are poised to enhance SCI-specific therapeutic capabilities of exosomes.

Novel geminal dinitro ester energetic plasticizers (DNEPs) were designed with different alkane lengths in the mainchain, namely 2,2-dinitropropyl acetate (DNPAc), 2,2-dinitropropyl propionate (DNPPc), and 2,2-dinitropropyl propionate (DNPBc). Due to the incorporation of ester and dinitro groups, these three DNEPs were expected to possess high heat of formations and thermal decomposition temperatures (Tₚ) and lower glass transition temperatures (Tg). Likewise, their impact sensitivities were all measured as higher than 25.2 J. Due to the maximum alkane length of DNPBc, DNPBc possesses the highest Tₚ and the lowest Tg. As plasticizers for glycidyl azide polymer (GAP), DNEPs significantly improve the viscosity and Tg of GAP. Particularly, the plasticizing efficiency of DNPBc is higher than that of the reported N-butyl nitroxyethyl nitramine (BuNENA). Likewise, the specific impulses of GAP/HMX based compositions with DNEPs as energetic plasticizers were all slightly higher than that of BuNENA. Therefore, these DNEPs (especially DNPBc) exhibit promising potential as candidates for replacement of BuNENA in GAP based propellants.

Rationale and Objectives To evaluate the noninvasive predictive performance of deep learning features based on staging CT for sentinel lymph node (SLN) metastasis of breast cancer. Materials and Methods A total of 348 breast cancer patients were enrolled in this study, with their SLN metastases pathologically confirmed. All patients received contrast-enhanced CT preoperative examinations and CT images were segmented and analyzed to extract deep features. After the feature selection, deep learning signature was built with the selected key features. The performance of the deep learning signatures was assessed with respect to discrimination, calibration, and clinical usefulness in the primary cohort (184 patients from January 2016 to March 2017) and then validated in the independent validation cohort (164 patients from April 2017 to December 2018). Results Ten deep learning features were automatically selected in the primary cohort to establish the deep learning signature of SLN metastasis. The deep learning signature shows favorable discriminative ability with an area under curve of 0.801 (95% confidence interval: 0.736–0.867) in primary cohort and 0.817 (95% confidence interval: 0.751–0.884) in validation cohort. To further distinguish the number of metastatic SLNs (1–2 or more than two metastatic SLN), another deep learning signature was constructed and also showed moderate performance (area under curve 0.770). Conclusion We developed the deep learning signatures for preoperative prediction of SLN metastasis status and numbers (1–2 or more than two metastatic SLN) in patients with breast cancer. The deep learning signature may potentially provide a noninvasive approach to assist clinicians in predicting SLN metastasis in patients with breast cancer.

Objectives To develop a sensitive monoclonal antibody-based sandwich enzyme-linked immunosorbent assay (ELISA) to detect Vip3Aa in genetically modified (GM) crops and their products. Results Vegetative insecticidal proteins (Vips) are secreted by Bacillus thuringiensis (Bt) and are known to be toxic to Lepidoptera species. Vip3Aa family proteins, Vip3Aa19 and Vip3Aa20, were successfully applied in GM crops to confer an effective and persistent insecticidal resistance. A sensitive monoclonal antibody-based sandwich ELISA was developed to detect Vip3Aa in GM crops and their products. Two monoclonal antibodies were raised against the overexpressed and purified His-Vip3Aa20, were purified from mouse ascites and characterized. A sandwich ELISA method was developed using the 2G3-1D7 monoclonal antibody for capture and the biotin-labeled 1F9-1F5 monoclonal antibody for detection of Vip3Aa20. The linear detection range of the method was found to be approximately 31.25–500 pg/ml, with a sensitivity of 10.24 pg/ml. Conclusions The established ELISA was effective for detecting Vip3Aa family proteins other than Vip3Aa8, and was successfully applied in the detection of Vip3Aa20 and Vip3Aa19 expressed in transgenic maize and cotton.

Nowadays, metal oxide semiconductors (MOS)-reduced graphene oxide (rGO) nanocomposites have attracted significant research attention for gas sensing applications. Herein, a novel composite material is synthesized by combining two p-type semiconductors, i.e., Cu2O and rGO, and a p-p-type gas sensor is assembled for NO2 detection. Briefly, polypyrrole-coated cuprous oxide nanowires (PPy/Cu2O) are prepared via hydrothermal method and combined with graphene oxide (GO). Then, the nanocomposite (rGO/PPy/Cu2O) is obtained by using high-temperature thermal reduction under Ar atmosphere. The results reveal that the as-prepared rGO/PPy/Cu2O nanocomposite exhibits a maximum NO2 response of 42.5% and is capable of detecting NO2 at a low concentration of 200 ppb. Overall, the as-prepared rGO/PPy/Cu2O nanocomposite demonstrates excellent sensitivity, reversibility, repeatability, and selectivity for NO2 sensing applications.

Sports dance originated from the international standard national standard dance. Since China formally established the “China International Ballroom Dance Association” in 1986, it has developed rapidly. At the same time, related research on sports dancers has become a hot spot. However, most of the current researches are limited to athletes’ physical training and competitive skills, and the research on athletes’ dietary nutrition and athletic ability is still blank. In response to this situation, this paper presents a study on the relationship between nutritional diet and athletic ability of sports dancers based on image analysis of visual sensors. This article is mainly divided into three parts. The first part is the basic theories and core concepts of related research. This part introduces the modes and algorithms of visual sensors, analyzes the specific problems of current sports dance athletes in my country in terms of dietary nutrition, and continues with the adverse effects. It affects the athlete’s athletic ability and even threatens the athlete’s health. Improving the diet of athletes and establishing healthy dietary standards are of great significance to the development of this field. The second part is the establishment method of the nutritional intervention experiment model, which gives the principle and specific operation steps of the experiment design in detail. The third part is a comparative test. To further confirm the influence of nutrition on dance performance in athletes, this article conducted a number of comparative studies such as immunoglobulin conversion after intervention, changes in the indicators of lipid metabolism after intervention, and dietary mineral intake. Through the analysis of experimental data, it can be seen that reasonable dietary supplementation has a positive effect on the recovery of athletes’ physical fitness, which can enhance the body’s immunity while improving athletic ability.

Unintended effects of genetically modified (GM) crops may pose safety issues. Omics techniques provide researchers with useful tools to assess such unintended effects. Proteomics and metabolomics analyses were performed for three GM maize varieties, 2A-7, CC-2, and 2A-7×CC-2 stacked transgenic maize, and the corresponding non-GM parent Zheng58. Proteomics revealed 120, 271 and 135 maize differentially expressed proteins (DEPs) in the 2A-7/Zheng58, CC-2/Zheng58 and 2A-7×CC-2/Zheng58 comparisons, respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showed that most DEPs participated in metabolic pathways and the biosynthesis of secondary metabolite. Metabolomics revealed 179, 135 and 131 differentially accumulated metabolites (DAMs) in the 2A-7/Zheng58, CC-2/Zheng58 and 2A-7×CC-2/Zheng58 comparisons, respectively. Based on KEGG enrichment analysis, most DAMs are involved in the biosynthesis of secondary metabolite and metabolic pathways. According to integrated proteomics and metabolomics analysis, the introduction of exogenous EPSPS did not affect the expression levels of six other enzymes or the abundance of seven metabolites involved in the shikimic acid pathway in CC-2 and 2A-7×CC-2 seeds. Six co-DEPs annotated by integrated proteomics and metabolomics pathway analysis were further analyzed by qRT-PCR. This study successfully employed integrated proteomic and metabolomic technology to assess unintended changes in maize varieties. The results suggest that GM and gene stacking do not cause significantly unintended effects.

The continuous advancement of analytical technology has provided methods with increasing sensitivity and precision to detect genetically modified organisms (GMOs). Novel analytical strategy-based detection methods are alternatives to conventional polymerase chain reaction (PCR)-mediated assays, which are still the gold standard in this field. However, PCR primers and probes cannot be reused, which makes the technique uneconomical. Surface plasmon resonance (SPR) is an optical and label-free technique for studying ligand-analyte interactions, especially for DNA hybridization, and several SPR biosensors have been described for the detection of nucleic acids. Here, a multiplexed, regenerable and real-time SPR biosensor for the detection of GMOs is described. A biosensor was constructed for qualitative detection of T-nos, CaMV35S and cry1A and had good specificity and sensitivity. The limit of detection (LOD) of this biosensor was 0.1 nM without any signal amplification. Furthermore, our biosensor could be stably regenerated more than 100 times over at least 20 days and showed good reproducibility. This nucleic acid SPR biosensor has potential for application in other types of biological detection.

Background Intervertebral disc degeneration (IVDD) is a commonly occurring musculoskeletal disorder, which is closely associated with low back pain. Accumulating evidence has demonstrated that dysregulated genes expression profiles play important roles in pathogenesis of IVDD. Hence, the current study was aimed to identify key genes to understand underlying mechanisms and therapeutic targets of IVDD. Methods Microarray datasets of GSE34095, GSE63492 and GSE45856 were downloaded to identify the hub genes that participate in the IVDD pathogenesis. After establishment of rat IVDD models, the expressions of NDC80, BUB1B and RAD21 in rat IVDD samples were evaluated by reverse transcription quantitative PCR (RT-qPCR) and immunochemistry. Subsequently, we assessed the proliferation, cycle and apoptosis of nucleus pulposus (NP) cells that transfected with siRNA-NDC80, siRNA-BUB1B and siRNA-RAD21. Results Our results showed indicated that NDC80, BUB1B and RAD21 were the key pathogenic genes with higher expression in IVDD rats, and silencing of NDC80, BUB1B and RAD21 gene could promote the aggrecan and collagen II synthesis, cell cycle and proliferation of NP cells, and inhibit NP cells apoptosis. Conclusion Our study suggests that silencing NDC80, RAD21 and BUB1B genes ameliorates intervertebral disc degeneration by promoting proliferation and inhibiting apoptosis of nucleus pulposus cells.

Objective To evaluate the human epidermal growth factor receptor 2 (HER2) status in patients with breast cancer using multidetector computed tomography (MDCT)-based handcrafted and deep radiomics features. Methods This retrospective study enrolled 339 female patients (primary cohort, n=177; validation cohort, n=162) with pathologically confirmed invasive breast cancer. Handcrafted and deep radiomics features were extracted from the MDCT images during the arterial phase. After the feature selection procedures, handcrafted and deep radiomics signatures and the combined model were built using multivariate logistic regression analysis. Performance was assessed by measures of discrimination, calibration, and clinical usefulness in the primary cohort and validated in the validation cohort. Results The handcrafted radiomics signature had a discriminative ability with a C-index of 0.739 [95% confidence interval (95% CI): 0.661-0.818] in the primary cohort and 0.695 (95% CI: 0.609-0.781) in the validation cohort. The deep radiomics signature also had a discriminative ability with a C-index of 0.760 (95% CI: 0.690-0.831) in the primary cohort and 0.777 (95% CI: 0.696-0.857) in the validation cohort. The combined model, which incorporated both the handcrafted and deep radiomics signatures, showed good discriminative ability with a C-index of 0.829 (95% CI: 0.767-0.890) in the primary cohort and 0.809 (95% CI: 0.740-0.879) in the validation cohort. Conclusions Handcrafted and deep radiomics features from MDCT images were associated with HER2 status in patients with breast cancer. Thus, these features could provide complementary aid for the radiological evaluation of HER2 status in breast cancer.

Graphene is a promising material for gas sensing, but high-performance gas sensors often require a robust structural design in order to endow the resultant sensing devices with batch uniformity, good response, sensitivity, and selectivity. In this study, a novel gas sensor based on assembled porous reduced graphene oxide (rGO) multilayer frameworks was designed and fabricated for gas sensing. To this end, negatively charged holey graphene oxide (GO) and positively charged holey graphene oxide (rGO) were assembled on gold (Au) electrodes through electrostatic interactions to form a porous structural framework. A reduction process was then performed to ensure the formation of a porous framework composed of the r(GO/rGO)n multilayers. The combined chemical assembly, etching and modification methods resulted in porous r(GO/rGO)n multilayers with an increased specific surface area. This improved the gas sensor response towards dimethyl methylphosphonate (DMMP) vapour at room temperature. The sensor that was assembled with 12 layers of porous graphene (r(GO/rGO)12) showed a resistance change reaching 8.95% in the presence of 50 ppm DMMP vapour. This value was 3-fold higher than that obtained with the sensor constructed with one-layered graphene. At the low DMMP vapour concentration of 1 ppm, the resistance change in (r(GO/rGO)12) reached a substantial 2.21%. Furthermore, the assembled porous r(GO/rGO)12 sensor showed good repeatability, excellent stability, good uniformity, and elevated selectivity towards DMMP vapour. Overall, the proposed concept looks promising for the design of future high-performance gas sensing devices with broad applications.

High levels of autophagy exist in Leydig cells of the testis, but its physiological function is unknown. Gao et al. now show that autophagy promotes uptake of cholesterol, an essential precursor for testosterone synthesis, by removing the NHERF2 negative regulator of the high-density lipoprotein receptor SR-BI., Testosterone is indispensable for sexual development and maintaining male characteristics, and deficiency of this hormone results in primary or late-onset hypogonadism (LOH). Testosterone is primarily produced in Leydig cells, where autophagy has been reported to be extremely active. However, the functional role of autophagy in testosterone synthesis remains unknown. In this study, we show that steroidogenic cell–specific disruption of autophagy influenced the sexual behavior of aging male mice because of a reduction in serum testosterone, which is similar to the symptoms of LOH. The decline in testosterone was caused mainly by a defect in cholesterol uptake in autophagy-deficient Leydig cells. Further studies revealed that once autophagic flux was disrupted, Na+/H+ exchanger regulatory factor 2 (NHERF2) accumulated in Leydig cells, resulting in the down-regulation of scavenger receptor class B, type I (SR-BI) and eventually leading to insufficient cholesterol supply. Collectively, these results reveal that autophagy promotes cholesterol uptake into Leydig cells by eliminating NHERF2, suggesting that dysfunction of autophagy might be causal in the loss of testosterone production in some patients.

Meiosis is a specific type of cell division that is essential for sexual reproduction in most eukaryotes. Mitochondria are crucial cellular organelles that play important roles in reproduction, though the detailed mechanism by which the mitochondrial respiratory chain functions during meiosis remains elusive. Here, we show that components of the respiratory chain (Complexes I–V) play essential roles in meiosis initiation during the sporulation of budding yeast, Saccharomyces cerevisiae. Any functional defects in the Complex I component Ndi1p resulted in the abolishment of sporulation. Further studies revealed that respiratory deficiency resulted in the failure of premeiotic DNA replication due to insufficient IME1 expression. In addition, respiration promoted the expression of RIM101, whose product inhibits Smp1p, a negative transcriptional regulator of IME1, to promote meiosis initiation. In summary, our studies unveiled the close relationship between mitochondria and sporulation, and uncover a novel meiosis initiation pathway that is regulated by the respiratory chain.

Aims Many studies have demonstrated that circRNAs are closely associated with human diseases. Nonetheless, the potential mechanism by which circRNAs impacts spinal cord injury (SCI) is not fully understood. The aim of this study was to explore the regulatory roles of circRNAs in SCI. Main methods The sequencing data of circRNA, miRNA and mRNA were obtained from Gene Expression Omnibus (GEO) datasets. Candidates were identified to construct a circRNA-miRNA-mRNA network based on circRNA-miRNA interactions and miRNA-mRNA interactions. Protein-protein interactions (PPI) analysis was performed to determine hub genes, and a connectivity map (CMap) analysis was applied to determine potential therapeutic targets for SCI. Key findings A total of 1656 differentially expressed circRNAs (DEcircRNAs), 71 differentially expressed miRNAs (DEmiRNAs) and 2782 differentially expressed mRNAs (DEmRNAs) were identified. We integrated four overlapped circRNAs, six miRNAs and 101 target mRNAs into a circRNA–miRNA–mRNA network. We next identified two hub genes (DDIT4, EZR) based on the PPI network and identified five circRNA-miRNA-hub gene regulatory axes. In addition, we discovered three chemicals (tanespimycin, fulvestrant, carbamazepine) as potential treatment options for SCI. Significance Our study suggests a regulatory role for circRNAs in the pathogenesis and treatment of SCI from the view of a competitive endogenous RNA (ceRNA) network.

ObjectivesIn this study, we aim to determine the effect of metformin on osteoarthritis (OA) development and progression.MethodsDestabilisation of the medial meniscus (DMM) surgery was performed in 10-week-old wild type and AMP-activated protein kinase (AMPK)α1 knockout (KO) mice. Metformin (4 mg/day in drinking water) was given, commencing either 2 weeks before or 2 weeks after DMM surgery. Mice were sacrificed 6 and 12 weeks after DMM surgery. OA phenotype was analysed by micro-computerised tomography (μCT), histology and pain-related behaviour tests. AMPKα1 (catalytic alpha subunit of AMPK) expression was examined by immunohistochemistry and immunofluorescence analyses. The OA phenotype was also determined by μCT and MRI in non-human primates.ResultsMetformin upregulated phosphorylated and total AMPK expression in articular cartilage tissue. Mild and more severe cartilage degeneration was observed at 6 and 12 weeks after DMM surgery, evidenced by markedly increased Osteoarthritis Research Society International scores, as well as reduced cartilage areas. The administration of metformin, commencing either before or after DMM surgery, caused significant reduction in cartilage degradation. Prominent synovial hyperplasia and osteophyte formation were observed at both 6 and 12 weeks after DMM surgery; these were significantly inhibited by treatment with metformin either before or after DMM surgery. The protective effects of metformin on OA development were not observed in AMPKα1 KO mice, suggesting that the chondroprotective effect of metformin is mediated by AMPK signalling. In addition, we demonstrated that treatment with metformin could also protect from OA progression in a partial medial meniscectomy animal model in non-human primates.ConclusionsThe present study suggests that metformin, administered shortly after joint injury, can limit OA development and progression in injury-induced OA animal models.

Rationale and Objectives Ki-67 is one of the most important biomarkers of breast cancer traditionally measured invasively via immunohistochemistry. In this study, deep learning based radiomics models were established for preoperative prediction of Ki-67 status using multiparametric magnetic resonance imaging (mp-MRI). Materials and Methods Total of 328 eligible patients were retrospectively reviewed [training dataset (n = 230) and a temporal validation dataset (n = 98)]. Deep learning imaging features were extracted from T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and contrast enhanced T1-weighted imaging (T1+C). Transfer learning techniques constructed four feature sets based on the individual three MR sequences and their combination (i.e., mp-MRI). Multilayer perceptron classifiers were trained for final prediction of Ki-67 status. Mann-Whitney U test compared the predictive performance of individual models. Results The area under curve (AUC) of models based on T2WI,T1+C,DWI and mp-MRI were 0.727, 0.873, 0.674, and 0.888 in the training dataset, respectively, and 0.706, 0.829, 0.643, and 0.875 in the validation dataset, respectively. The predictive performance of mp-MRI classification model in the AUC value was significantly better than that of the individual sequence model (all p Conclusion In clinical practice, a noninvasive approach to improve the performance of radiomics in preoperative prediction of Ki-67 status can be provided by extracting breast cancer specific structural and functional features from mp-MRI images obtained from conventional scanning sequences using the advanced deep learning methods. This could further personalize medicine and computer aided diagnosis.

To investigate the unintended effects of genetically modified (GM) crops, an isobaric tags for relative and absolute quantitation (iTRAQ)-based comparative proteomic analysis was performed with seed cotyledons of two GM soybean lines, MON87705 and MON87701×MON89788, and the corresponding non-transgenic isogenic variety A3525. Thirty-five differentially abundant proteins (DAPs) were identified in MON87705/A3525, 27 of which were upregulated and 8 downregulated. Thirty-eight DAPs were identified from the MON87701×MON89788/A3525 sample, including 29 upregulated proteins and 9 downregulated proteins. Pathway analysis showed that most of these DAPs participate in protein processing in endoplasmic reticulum and in metabolic pathways. Protein–protein interaction analysis of these DAPs demonstrated that the main interacting proteins are associated with post-translational modification, protein turnover, chaperones and signal transduction mechanisms. Nevertheless, these DAPs were not identified as new unintended toxins or allergens and only showed changes in abundance. All these results suggest that the seed cotyledon proteomic profiles of the two GM soybean lines studied were not dramatically altered compared with that of their natural isogenic control.