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Significant physiological changes occur in both the fetus and the mother during pregnancy. Urine proteins have been shown to reflect a wide range of physiological and pathological changes in the body. This study employed low-abundance protein-enriched magnetic nanobeads to conduct an in-depth analysis of the daily changes in urine proteins throughout the entire pregnancy of rats. Based on the 3455 identified urine proteins, fetal and maternal dynamic changes were observed in the pregnancy group compared to the control group, including blastocyst formation and cell division in the early stage of pregnancy. In addition, the morphogenesis- and development-related organs and tissues are significantly enriched at different stages of pregnancy. The 9th day after pregnancy is the stage when organ development is most concentrated, especially the nervous system and vasculature development. During the late stage of pregnancy, maternal-specific changes were observed, such as lactation. These results indicate that urine protein can reflect the fetal and maternal dynamic physiological alterations during pregnancy, which suggests the potential value of urine protein analysis in pregnancy health monitoring. It is emphasized that the analysis focuses on the daily variations in the urine proteins, as these daily changes are expected to reveal more dynamic and detailed information about the physiological processes during pregnancy.

Land use change is the second largest source of greenhouse gas emissions after fossil combustion, which can hurt ecological environment severely. Intensive study on land use carbon emissions is of great significance to alleviate environmental pressure, formulate carbon emission reduction policy, and protect ecological development. The lower Yellow River area is an important area of economic development, grain cultivation, and agricultural production in China. Land use change has significant economic, environmental, and ecological impacts in this region. Deep study of land used carbon emissions and its influencing factors in the lower Yellow River area is not only of great significance to the environmental improvement in the Yellow River basin, but also can provide references for the research of other basins. Based on this, this paper studies the land use carbon emissions of 20 cities in the lower Yellow River area from 1995 to 2018. The results showed that from 1995 to 2018, the land use change was characterized by the decrease of the ecological land and the increase of the built-up land significantly. The overall carbon emission of the lower Yellow River area is increasing, and the built-up land is the main factor that leads to the increase of carbon emission, which can be also proven by the analysis of the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model. The economic contributive coefficient (ECC) and ecological support coefficient (ESC) of carbon emission in the lower Yellow River area show a trend of high in Zhengzhou, Jinan, and Zibo and low in Zhoukou, Shangqiu, and Heze, and there was no significant changes during the study period, which indicates that each city did not achieve the coordinated development of the ecological economy. Finally, analysis results of the STIRPAT model indicated that the area of built-up land had the greatest impact on land use carbon emissions, followed by tertiary industry, whereas per capita gross domestic product (GDP) had the smallest impact. For every 1% increase in the area of built-up land, carbon emissions increased by 1.024%. By contrast, for every 1% increase in the contribution of tertiary industry to the GDP and per capita GDP, carbon emissions decreased by 0.051% and 0.034%, respectively. According to the study, there are still many problems in the coordinated development of economy and ecology in the lower Yellow River area. The lower Yellow River area should control the expansion of built-up land, afforestation, development of technology, reduction of carbon emissions, and promotion of the high-quality development of the Yellow River Basin.

Background This study discusses the effectiveness of a 12-week intervention aimed at improving squat jump and sprint performance among second-year sports students. Methods The students were randomly divided into experimental ( n  = 89) and control ( n  = 92) groups. In addition to gym training, students of the experimental group also underwent online PE training. The students’ performance in Squat Jumps, 30 m sprint, and Progressive Aerobic Cardiovascular Endurance Run (PACER), as well as their situational motivation, were assessed before and after the intervention. Furthermore, the students assessed their physical activity weekly using self-reports. Results The implementation of online training has positively impacted intrinsic and identified motivation, as well as external regulation; however, it was less effective in reducing amotivation compared to traditional gym-based training. Conclusions The findings of the study contribute to the data synthesis on the expediency of using modern software in physical education.

Vaccinations are widely credited with reducing death rates from COVID-19, but the underlying host-viral mechanisms/interactions for morbidity and mortality of SARS-CoV-2 infection remain poorly understood. Acute respiratory distress syndrome (ARDS) describes the severe lung injury, which is pathologically associated with alveolar damage, inflammation, non-cardiogenic edema, and hyaline membrane formation. Because proteostatic pathways play central roles in cellular protection, immune modulation, protein degradation, and tissue repair, we examined the pathological features for the unfolded protein response (UPR) using the surrogate biomarker glucose-regulated protein 78 (GRP78) and co-receptor for SARS-CoV-2. At autopsy, immunostaining of COVID-19 lungs showed highly elevated expression of GRP78 in both pneumocytes and macrophages compared with that of non-COVID control lungs. GRP78 expression was detected in both SARS-CoV-2-infected and un-infected pneumocytes as determined by multiplexed immunostaining for nucleocapsid protein. In macrophages, immunohistochemical staining for GRP78 from deceased COVID-19 patients was increased but overlapped with GRP78 expression taken from surgical resections of non-COVID-19 controls. In contrast, the robust in situ GRP78 immunostaining of pneumocytes from COVID-19 autopsies exhibited no overlap and was independent of age, race/ethnicity, and gender compared with that from non-COVID-19 controls. Our findings bring new insights for stressresponse pathways involving the proteostatic network implicated for host resilience and suggest that targeting of GRP78 expression with existing therapeutics might afford an alternative therapeutic strategy to modulate host-viral interactions during SARS-CoV-2 infections.

Gene expression profiling data with long-term clinical follow-up information are great resources to screen, develop, evaluate and validate prognostic biomarkers in translational cancer research. However, an easy-to-use interactive online tool is needed to analyze these profiling and clinical data. In the current work, we developed OSacc (Online consensus Survival analysis of ACC), a web tool that provides rapid and user-friendly survival analysis based on seven independent transcriptomic profiles with long-term clinical follow-up information of 259 ACC patients gathered from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. OSacc allows researchers and clinicians to evaluate the prognostic value of genes of interest by Kaplan-Meier (KM) survival plot with hazard ratio (HR) and log-rank test in ACC. OSacc is freely available at Keywords: ACC, prognostic marker, over survival, web tool, KM plot

Human coronavirus disease 2019 (COVID-19) is a life-threatening and highly contagious disease caused by coronavirus SARS-CoV-2. Sensitive and specific detection of SARS-CoV-2 viral proteins in tissues and cells of COVID-19 patients will support investigations of the biologic behavior and tissue and cell tropism of this virus. We identified commercially available affinity-purified polyclonal antibodies raised against nucleocapsid and spike proteins of SARS-CoV-2 that provide sensitive and specific detection of the virus by immunohistochemistry in formalin-fixed, paraffin-embedded tissue. Two immunohistochemistry protocols are presented that are mutually validated by the matched detection patterns of the two distinct viral antigens in virus-infected cells within autopsy lung tissue of COVID-19 deceased patients. Levels of nucleocapsid protein in the lungs of COVID-19 decedents, as measured by quantitative histo-cytometry of immunohistochemistry images, showed an excellent log–linear relationship with levels of viral nucleocapsid RNA levels, as measured by qRT-PCR. Importantly, since the nucleocapsid protein sequence is conserved across all known viral strains, the nucleocapsid immunohistochemistry protocol is expected to recognize all common variants of SARS-CoV-2. Negative controls include autopsy lung tissues from patients who died from non-COVID-19 respiratory disease and control rabbit immunoglobulin. Sensitive detection of SARS-CoV-2 in human tissues will provide insights into viral tissue and cell distribution and load in patients with active infection, as well as provide insight into the clearance rate of virus in later COVID-19 disease stages. The protocols are also expected to be readily transferable to detect SARS-CoV-2 proteins in tissues of experimental animal models or animals suspected to serve as viral reservoirs.

Unfair nature of doping practises adopted by dishonest sportsmen to increase their performance is posing a challenge to sports administrators worldwide. This involves giving them blood transfusions, using anabolic steroids, or even taking hormone-based medications like erythropoietin to improve their performance by increasing their strength, stamina, and endurance. Even while erythropoietin may be directly detected and identified in athlete blood samples, not all doping instances are easily identifiable, and certain tests are too expensive to perform on every sample. This makes it necessary to create an indirect technique based on many blood biomarkers to identify erythropoietin in blood samples. This study suggests a unique method for detecting steroids in athletes by combining machine learning models with quantum computing-based photon analysis. The information is gathered through medical examinations of athletes, after which photonic analysis is performed and the blood samples are categorised for steroid detection. Regressive Gaussian neural networks based on active equalisation are used to analyse the blood sample. The accuracy, mean average precision, F-1 score, positive predictive value, and mean average precision are all measured throughout the experimental study. The most significant injury risk variables may be found and players at high injury risk can be identified using current machine learning techniques. The proposed technique accuracy 97%, mean average precision 93%, positive predictive value 83%, F-1 score 89%.

To develop a free and quick analysis online tool that allows users to easily investigate the prognostic potencies of interesting genes in kidney renal clear cell carcinoma (KIRC). A total of 629 KIRC cases with gene expression profiling data and clinical follow-up information are collected from public Gene Expression Omnibus and The Cancer Genome Atlas databases. One web application called Online consensus Survival analysis for KIRC (OSkirc) that can be used for exploring the prognostic implications of interesting genes in KIRC was constructed. By OSkirc, users could simply input the gene symbol to receive the Kaplan–Meier survival plot with hazard ratio and log-rank p-value. OSkirc is extremely valuable for basic and translational researchers to screen and validate the prognostic potencies of genes for KIRC, publicly accessible at

MAIN CONCLUSION : This work demonstrated that a cold-induced DEAD-box RNA helicase, CbDRH, is also post-transcriptionally regulated upon cold stress, and it interacts with a cold-responsive, glycine-rich, RNA-binding protein, CbGRP. Chorispora bungeana (C. bungeana) is a representative alpine subnival plant species that shows strong tolerance to multiple abiotic stresses, especially cold stress. DEAD-box RNA helicases are implicated in almost all RNA metabolic processes and participate in multiple abiotic stress responses. Here, we characterized a cold-induced DEAD-box RNA helicase gene from C. bungeana. We cloned the full-length cDNA of the gene by RACE and called it C. bungeana DEAD-box RNA Helicase (CbDRH). Structurally, CbDRH possesses all nine conserved motifs characteristic of DEAD-box protein family members in its central region, and the N- and C- terminal extensions both harbor a glycine-rich region containing several RGG-box motifs. The CbDRH gene produces two forms of transcripts, CbDRH.2 and CbDRH.1, by alternative splicing. CbDRH.2 comes from the complete excision of all the nine introns, while CbDRH.1 results from the use of an alternative 5′ splice site in the eighth intron, retaining part of the intron (the first 260 bp) with an early stop codon. Semi-quantitative RT-PCR analysis showed that CbDRH.2, but not CbDRH.1, is up-regulated by cold stress. However, the abundance of CbDRH.1 transcript can be elevated by cycloheximide (an inhibitor of nonsense-mediated decay) treatment, indicating that CbDRH.1 is targeted to nonsense-mediated decay (NMD). A subcellular localization analysis showed that CbDRH.2 protein is located in the nuclei. Further investigation suggested that CbDRH.2 can interact with a cold-responsive, glycine-rich, RNA-binding protein, CbGRP (Chorispora bungeana glycine-rich, RNA-binding protein). These data suggest that the cold-induced CbDRH is also post-transcriptionally regulated under cold stress and that CbDRH.2 may function together with the glycine-rich, RNA-binding protein, CbGRP, in the cold stress response.