The Details Exploration of Intangible Cultural Heritage From the Perspective of Cultural Tourism Industry: A Case Study of Hohhot City in China

the intangible cultural heritage is an important part of the cultural tourism industry marketing.As the cultural element ,the intangible cultural heritage can impel the main cultural tourism industry become more diversified and more extensively involved of public.Intangible cultural heritage can enhance the experience of tourists in culture . The intangible cultural heritage of Hohhot has an important value ,. keeping up with the times and has gone through long history, it is synchronic,all this can increase the value of tourism destination by explorating the innovation of intangible cultural heritage.With the help of real drama culture, the local brand value of intangible cultural heritage can be created. And it can realize the endorsement value of the people speaker.  This article explores the intangible cultural heritage from the perspective of cultural tourism in order to promote the tourism development in Hohhot.

TARGETING THE EPIGENETIC MECHANISM IN ACUTE MYELOID LEUKAEMIA

Ph.DPHD IN CANCER BIOLOG

Inhibitors of the renin–angiotensin system: The potential role in the pathogenesis of COVID-19

Coronavirus disease 2019 (COVID-19), which initially began in China, has spread to other countries of Asia, Europe, America, Africa and Oceania, with the number of confirmed cases and suspected cases increasing each day. According to recently published research, it was found that the majority of the severe cases were elderly, and many of them had at least one chronic disease, especially cardiovascular diseases. Angiotensin-converting enzyme inhibitors/angiotensin receptor blockers (ACEIs/ARBs) are the most widely used drugs for cardiovascular diseases. The clinical effect of ACEIs/ARBs on patients with COVID-19 is still uncertain. This paper describes their potential role in the pathogenesis of COVID-19, which may provide useful in the advice of cardiologists and physicians

Human ApoE ε2 promotes regulatory mechanisms of bioenergetic and synaptic function in female brain: a focus on V-type H+-ATPase

Humans possess three major isoforms of the apolipoprotein E (ApoE) gene encoded by three alleles: ApoE ε2 (ApoE2), ApoE ε3 (ApoE3), and ApoE ε4 (ApoE4). It is established that the three ApoE isoforms confer differential susceptibility to Alzheimer’s disease (AD); however, an in-depth molecular understanding of the underlying mechanisms is currently unavailable. In this study, we examined the cortical proteome differences among the three ApoE isoforms using 6-month-old female, human ApoE2, ApoE3, and ApoE4 gene-targeted replacement mice and two-dimensional proteomic analyses. The results reveal that the three ApoE brains differ primarily in two areas: cellular bioenergetics and synaptic transmission. Of particular significance, we show for the first time that the three ApoE brains differentially express a key component of the catalytic domain of the V-type H+-ATPase (Atp6v), a proton pump that mediates the concentration of neurotransmitters into synaptic vesicles and thus is crucial in synaptic transmission. Specifically, our data demonstrate that ApoE2 brain exhibits significantly higher levels of the B subunit of Atp6v (Atp6v1B2) when compared to both ApoE3 and ApoE4 brains, with ApoE4 brain exhibiting the lowest expression. Our additional analyses show that Atp6v1B2 is significantly impacted by aging and AD pathology and the data suggest that Atp6v1B2 deficiency could play a role in the progressive loss of synaptic integrity during early development of AD. Collectively, our findings indicate that human ApoE isoforms differentially modulate regulatory mechanisms of bioenergetic and synaptic function in female brain. A more efficient and robust status in both areas could serve as a potential mechanism contributing to the neuroprotective and cognition-favoring properties associated with the ApoE2 genotype

Using random forest algorithm for glomerular and tubular injury diagnosis

ObjectivesChronic kidney disease (CKD) is a common chronic condition with high incidence and insidious onset. Glomerular injury (GI) and tubular injury (TI) represent early manifestations of CKD and could indicate the risk of its development. In this study, we aimed to classify GI and TI using three machine learning algorithms to promote their early diagnosis and slow the progression of CKD.MethodsDemographic information, physical examination, blood, and morning urine samples were first collected from 13,550 subjects in 10 counties in Shanxi province for classification of GI and TI. Besides, LASSO regression was employed for feature selection of explanatory variables, and the SMOTE (synthetic minority over-sampling technique) algorithm was used to balance target datasets, i.e., GI and TI. Afterward, Random Forest (RF), Naive Bayes (NB), and logistic regression (LR) were constructed to achieve classification of GI and TI, respectively.ResultsA total of 12,330 participants enrolled in this study, with 20 explanatory variables. The number of patients with GI, and TI were 1,587 (12.8%) and 1,456 (11.8%), respectively. After feature selection by LASSO, 14 and 15 explanatory variables remained in these two datasets. Besides, after SMOTE, the number of patients and normal ones were 6,165, 6,165 for GI, and 6,165, 6,164 for TI, respectively. RF outperformed NB and LR in terms of accuracy (78.14, 80.49%), sensitivity (82.00, 84.60%), specificity (74.29, 76.09%), and AUC (0.868, 0.885) for both GI and TI; the four variables contributing most to the classification of GI and TI represented SBP, DBP, sex, age and age, SBP, FPG, and GHb, respectively.ConclusionRF boasts good performance in classifying GI and TI, which allows for early auxiliary diagnosis of GI and TI, thus facilitating to help alleviate the progression of CKD, and enjoying great prospects in clinical practice

Theoretical Study on Relaxed Surrounding Rock Pressure on Shallow Bias Neighborhood Tunnels under Seismic Load

To study the distribution of relaxed surrounding rock pressure on the shallow bias neighborhood tunnels under the combined action of horizontal and vertical earthquake force, finite element software was used for failure mode analysis. Moreover, with the pseudo-static method, the calculation formula for the relaxed pressure on the shallow bias neighborhood tunnels was derived and used to analyze the variation of the rupture angle of these tunnels under the action of the seismic force. The study shows that: shallow bias neighborhood tunnels basically follow a “W” failure pattern under the combined action of horizontal and vertical seismic force, and the failure scope of the surrounding rock is controlled by four rupture angles. Rupture angles β2 and β3 between the deep and shallow tunnels of the shallow bias neighborhood tunnels are not affected by the surface slope. For tunnels with the same grade of the surrounding rock, the greater the seismic intensity, the smaller the value of β2, and the greater the value of β3. While at the same seismic intensity, the higher the grade of the surrounding rock, the smaller the β2 and β3. Ruptures angles β1 and β4 are influenced by the surface slope, seismic intensity and surrounding rock grades. A steeper surface slope leads to a smaller β1 and a greater β4; β1 increase and β4 decrease with increasing seismic intensity; while, β1 and β4 both show a decreasing trend with an increasing rock grade

Routes of administration for adeno-associated viruses carrying gene therapies for brain diseases

Gene therapy is a powerful tool to treat various central nervous system (CNS) diseases ranging from monogenetic diseases to neurodegenerative disorders. Adeno-associated viruses (AAVs) have been widely used as the delivery vehicles for CNS gene therapies due to their safety, CNS tropism, and long-term therapeutic effect. However, several factors, including their ability to cross the blood&ndash;brain barrier, the efficiency of transduction, their immunotoxicity, loading capacity, the choice of serotype, and peripheral off-target effects should be carefully considered when designing an optimal AAV delivery strategy for a specific disease. In addition, distinct routes of administration may affect the efficiency and safety of AAV-delivered gene therapies. In this review, we summarize different administration routes of gene therapies delivered by AAVs to the brain in mice and rats. Updated knowledge regarding AAV-delivered gene therapies may facilitate the selection from various administration routes for specific disease models in future research. &nbsp;</p

DEqMS : A Method for Accurate Variance Estimation in Differential Protein Expression Analysis

Quantitative proteomics by mass spectrometry is widely used in biomarker research and basic biology research for investigation of phenotype level cellular events. Despite the wide application, the methodology for statistical analysis of differentially expressed proteins has not been unified. Various methods such as t test, linear model and mixed effect models are used to define changes in proteomics experiments. However, none of these methods consider the specific structure of MS-data. Choices between methods, often originally developed for other types of data, are based on compromises between features such as statistical power, general applicability and user friendliness. Furthermore, whether to include proteins identified with one peptide in statistical analysis of differential protein expression varies between studies. Here we present DEqMS, a robust statistical method developed specifically for differential protein expression analysis in mass spectrometry data. In all data sets investigated there is a clear dependence of variance on the number of PSMs or peptides used for protein quantification. DEqMS takes this feature into account when assessing differential protein expression. This allows for a more accurate data-dependent estimation of protein variance and inclusion of single peptide identifications without increasing false discoveries. The method was tested in several data sets including E. coli proteome spike-in data, using both label-free and TMT-labeled quantification. Compared with previous statistical methods used in quantitative proteomics, DEqMS showed consistently better accuracy in detecting altered protein levels compared with other statistical methods in both label-free and labeled quantitative proteomics data. DEqMS is available as an R package in Bioconductor.Peer reviewe

Basalt-polypropylene fiber reinforced concrete for durable and sustainable pipe production. Part 1: experimental program

This is the peer reviewed version of the following article: [ Deng, Z, Liu, X, Chen, P, et al. Basalt-polypropylene fiber reinforced concrete for durable and sustainable pipe production. Part 1: Experimental program. Structural Concrete. 2022; 23: 311– 327. https://doi.org/10.1002/suco.202000759], which has been published in final form at https://onlinelibrary.wiley.com/doi/abs/10.1002/suco.202000759. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.An experimental program consisting in producing and testing reinforced concrete pipes (RCPs) under the three-edge bearing tests considering different types of reinforcement was carried out. Four types of RCPs were produced, these reinforced with: (1) polypropylene macrofibers; (2) basalt microfibers; (3) combination of both (hybrid reinforcement); and (4) plain concrete. The analysis of the crack patterns and both service and ultimate mechanical responses allowed concluding that the use of fibers do not lead to an effective increase of the first cracking load; however, both types of fibers allowed a better crack width control respect to the standard RCP. In this regard, basalt microfiber reinforced concrete led to a better response caused by concentrated loads (jacketing) whilst polypropylene macrofibers increased the concrete pipe performance in terms of bearing capacity and flexural crack control. The hybrid fiber reinforced concrete was found to be the most suitable alternative for increasing the load bearing capacity and the crack width control for service loads. These incipient experimental results permit to conclude that this type of hybrid basalt-polypropylene fiber reinforced concretes are an interesting alternative to traditional steel-cage RCPs.This work is supported by the National Key Research and Development Program of China (2018YFC1504802), Natural Science Foundation Project of Chongqing, Chongqing Science and Technology Commission (cstc2018jscxmszdX0071), Postgraduate Research Innovation Project of Chongqing (CYS19005, CYS18026). In addition, Prof. Albert de la Fuente also wants to express his gratitude to the Spanish Ministry of Science and Innovation for the financial support received under the scope of the project CREEF (PID2019-108978RB-C32).Peer ReviewedPostprint (author's final draft

A novel machine learning-derived four-gene signature predicts STEMI and post-STEMI heart failure

High mortality and morbidity rates associated with ST-elevation myocardial infarction (STEMI) and post-STEMI heart failure (HF) necessitate proper risk stratification for coronary artery disease (CAD). A prediction model that combines specificity and convenience is highly required. This study aimed to design a monocyte-based gene assay for predicting STEMI and post-STEMI HF. A total of 1,956 monocyte expression profiles and corresponding clinical data were integrated from multiple sources. Meta-results were obtained through the weighted gene co-expression network analysis (WGCNA) and differential analysis to identify characteristic genes for STEMI. Machine learning models based on the decision tree (DT), support vector machine (SVM), and random forest (RF) algorithms were trained and validated. Five genes overlapped and were subjected to the model proposal. The discriminative performance of the DT model outperformed the other two methods. The established four-gene panel (HLA-J, CFP, STX11, and NFYC) could discriminate STEMI and HF with an area under the curve (AUC) of 0.86 or above. In the gene set enrichment analysis (GSEA), several cardiac pathogenesis pathways and cardiovascular disorder signatures showed statistically significant, concordant differences between subjects with high and low expression levels of the four-gene panel, affirming the validity of the established model. In conclusion, we have developed and validated a model that offers the hope for accurately predicting the risk of STEMI and HF, leading to optimal risk stratification and personalized management of CAD, thereby improving individual outcomes