Digital transformation is a major trend in educational development. Ethnic minority regions, considering their geographical characteristics, actively promote the digital transformation of education. ...However, this process still faces numerous challenges. In view of this, this article proposes the following strategies: promoting the digital transformation and intelligent upgrading of the education system through the construction of an educational dedicated network to support the high-quality development of education; addressing issues in the construction of the "Internet + Education" platform and implementing the Smart Education Platform Construction Project; advocating the "Platform + Education" service model, establishing a "1+6+N" education digital platform system, and accelerating the digital transformation of education across the region.
Obtaining the most Stimulated Reservoir Volume (SRV) by forming a complex fracture network is the prerequisite for shale gas hydraulic fracturing. In this paper, a coupled DFN–DEM model is presented ...based on a realistic discrete fracture network from fracturing treatment, to simulate the complex interactions between a created hydraulic fracture and a natural fracture system in shale. The sensitivity analysis of numerical simulation was performed to investigate the effects of hydraulic fracture length, multi‐fracture spacing, and internal friction angle on the stimulation reservoir area. The simulation results revealed that regardless of the DFN distribution and the length of hydraulic fracture, shear failure always tracked on the existing natural fracture plane. The amount and depth of the natural fracture shear into formation increased as the hydraulic fracture grew in length. Moreover, the actual dynamic morphology of fracture network was the radial or dendritic. A drastic change of permeability along the distance from injection may stimulate the fracture networks especially near the wellbore. For the multi‐fracture, the opening of the second fracture was able to stabilize the sheared fractures at the tip of the initial fracture. The shear failure area around the second fracture tended to increase with the growth of the length of the second fracture. Fracture network connectivity in the system is better for the optimal fracture spacing, and then fluid penetration during injection will influence the permeability evolution during stimulation. The stimulation reservoir area of the fracture network and the natural fracture friction angle had a quadratic relationship. Finally, the results by the data from field measurement in Sichuan, China verified that the proposed coupled DFN–DEM model had an accuracy up to 91.7%. The research results provide a reference for predicting the development of fracture network far away for multistage fracturing treatment.
A coupled DFN–DEM model is presented based on a realistic discrete fracture network from fracturing treatment, to simulate the complex interactions between a created hydraulic fracture and a natural fracture system in shale. The sensitivity analysis of numerical simulation was performed to investigate the effects of hydraulic fracture length, multi‐fracture spacing, and internal friction angle on the stimulation reservoir area.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
When identifying differentially expressed genes between two conditions using human population RNA-seq samples, we found a phenomenon by permutation analysis: two popular bioinformatics methods, ...DESeq2 and edgeR, have unexpectedly high false discovery rates. Expanding the analysis to limma-voom, NOISeq, dearseq, and Wilcoxon rank-sum test, we found that FDR control is often failed except for the Wilcoxon rank-sum test. Particularly, the actual FDRs of DESeq2 and edgeR sometimes exceed 20% when the target FDR is 5%. Based on these results, for population-level RNA-seq studies with large sample sizes, we recommend the Wilcoxon rank-sum test.
The diffuse-type gastric cancer (DGC) is a subtype of gastric cancer with the worst prognosis and few treatment options. Here we present a dataset from 84 DGC patients, composed of a proteome of ...11,340 gene products and mutation information of 274 cancer driver genes covering paired tumor and nearby tissue. DGC can be classified into three subtypes (PX1-3) based on the altered proteome alone. PX1 and PX2 exhibit dysregulation in the cell cycle and PX2 features an additional EMT process; PX3 is enriched in immune response proteins, has the worst survival, and is insensitive to chemotherapy. Data analysis revealed four major vulnerabilities in DGC that may be targeted for treatment, and allowed the nomination of potential immunotherapy targets for DGC patients, particularly for those in PX3. This dataset provides a rich resource for information and knowledge mining toward altered signaling pathways in DGC and demonstrates the benefit of proteomic analysis in cancer molecular subtyping.
Estimating and accounting for hidden variables is widely practiced as an important step in molecular quantitative trait locus (molecular QTL, henceforth "QTL") analysis for improving the power of QTL ...identification. However, few benchmark studies have been performed to evaluate the efficacy of the various methods developed for this purpose.
Here we benchmark popular hidden variable inference methods including surrogate variable analysis (SVA), probabilistic estimation of expression residuals (PEER), and hidden covariates with prior (HCP) against principal component analysis (PCA)-a well-established dimension reduction and factor discovery method-via 362 synthetic and 110 real data sets. We show that PCA not only underlies the statistical methodology behind the popular methods but is also orders of magnitude faster, better-performing, and much easier to interpret and use.
To help researchers use PCA in their QTL analysis, we provide an R package PCAForQTL along with a detailed guide, both of which are freely available at https://github.com/heatherjzhou/PCAForQTL . We believe that using PCA rather than SVA, PEER, or HCP will substantially improve and simplify hidden variable inference in QTL mapping as well as increase the transparency and reproducibility of QTL research.
•Children and adolescents are vulnerable groups during the COVID-2019 pandemic.•Children and adolescents may be experiencing symptoms for PTSD and GAD.•Comorbidity patterns of the symptoms for PTSD ...and GAD vary.•Perceived threat and stigma are risk factors related to PTSD and GAD.
The present study aims to examine the comorbidity patterns of the symptoms (intrusion and avoidance) for posttraumatic stress disorder (PTSD) and generalized anxiety disorder (GAD) and the role of perceived threat and courtesy stigma in distinguishing specific patterns of the symptoms for PTSD and GAD among children and adolescents who are susceptible to coronavirus disease 2019 (COVID-19) in Hubei, China. A total of 1172 (683 female and 489 male) children and adolescents aged 8–18 years were involved in completing the measurements of PTSD, GAD, perceived threat of COVID-19, and COVID-19-related courtesy stigma. The Latent Profile Analysis identified the three profiles of the symptoms for PTSD and GAD which were labeled as Moderate PTSD, Mild Comorbidity, and Severe Comorbidity. The scores of the symptoms for PTSD, GAD, perceived threat, and stigma were different among the three profiles. The risk factors (i.e., perceived threat and stigma) that are related to comorbidity patterns were examined through a three-step method. The possibility of entry into the Severe Comorbidity Profile increased with increasing perceived threat and stigma. The mental health care interventions for children and adolescents who are susceptible to COVID-19 can be developed to reduce perceived threat and stigma.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Metastasis is the leading cause of melanoma-related mortality. Current therapies are rarely curative for metastatic melanoma, revealing the urgent need to identify more effective preventive and ...therapeutic targets. This study aimed to screen the core genes and molecular mechanisms related to melanoma metastasis. A gene expression profile, GSE8401, including 31 primary melanoma and 52 metastatic melanoma clinical samples, was downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) between melanoma metastases and primary melanoma were screened using GEO2R tool. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) analyses of DEGs were performed using the Database for Annotation Visualization and Integrated Discovery (DAVID). The Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape with Molecular Complex Detection (MCODE) plug-in tools were utilized to detect the protein-protein interaction (PPI) network among DEGs. The top 10 genes with the highest degrees of the PPI network were defined as hub genes. In the results, 425 DEGs, including 60 upregulated genes and 365 downregulated genes, were identified. The upregulated genes were enriched in ECM-receptor interactions and the regulation of actin cytoskeleton, while 365 downregulated genes were enriched in amoebiasis, melanogenesis, and ECM-receptor interactions. The defined hub genes included
,
,
,
,
,
,
,
,
, and
. In addition, the mRNA and protein levels of the hub genes during melanoma metastasis were verified in the TCGA database and paired post- and premetastatic melanoma cells, respectively. Finally,
-specific siRNAs were utilized to reduce the
expression in melanoma A375 cells. An MTT assay and a colony formation assay showed that
knockdown significantly promoted the proliferation of A375 cells. A Transwell assay further suggested that
knockdown significantly increased the cell migration and cell invasion of A375 cells. This bioinformatics study provided a deeper understanding of the molecular mechanisms of melanoma metastasis. The in vitro experiments showed that
played the inhibitory effects on melanoma metastasis. Therefore,
may serve important roles in melanoma metastasis.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Limited studies have reported the relationship between intestinal flora dysbiosis and clinical characteristics in polycystic ovary syndrome (PCOS). However, the structure and characteristics of gut ...microbiota in PCOS have not been fully elucidated.
To analyze the composition of the Intestinal flora population in normal-weight women with PCOS and insulin resistance(IR) compared to PCOS alone and healthy women.
A total of 14 PCOS patients with insulin resistant(PCOS-IR) and 12 PCOS alone (PCOS-NIR), and 10 age- and body mass index-matched healthy control women (HC). BMI: 18.5-23.9 kg/m
. The bacterial 16 S rDNA V3-V4 fragment was amplified and sequenced. Then, the sequencing data were analyzed for species annotation, community diversity, and inter-group differences, to explore gut microbial characteristics of the subjects and their correlation with clinical parameters.
No significant difference in diversity was observed between PCOA and sample cluster analysis among the three groups (Beta-diversity) and Alpha-diversity. The relative abundance of Rothia, Ruminococcus, and Enterococcus was significantly higher in the PCOS-IR group than in the other two groups (P < 0.05), while that of Prevotella was dramatically decreased (P < 0.05). The abundance of Enterococcus was positively correlated with waist circumference, hip circumference, diastolic blood pressure, and insulin resistance index. Meanwhile, Rothia abundance is positively associated with waist circumference and free fatty acids.
The gut microbial composition of PCOS patients with insulin resistance is different from that of PCOS alone and healthy women. The difference is correlated with the clinical characteristics of PCOS, with regards to insulin resistance, abdominal obesity, free fatty acids, and other indicators. PCOS-IR patients have an increased abundance of Enterococcus which potentially the intestinal environment of the host by enriching the metabolic pathways related to insulin resistance, causing the occurrence and development of PCOS.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
The origin of millet from Neolithic China has generally been accepted, but it remains unknown whether common millet (Panicum miliaceum) or foxtail millet (Setaria italica) was the first species ...domesticated. Nor do we know the timing of their domestication and their routes of dispersal. Here, we report the discovery of husk phytoliths and biomolecular components identifiable solely as common millet from newly excavated storage pits at the Neolithic Cishan site, China, dated to between ca. 10,300 and ca. 8,700 calibrated years before present (cal yr BP). After ca. 8,700 cal yr BP, the grain crops began to contain a small quantity of foxtail millet. Our research reveals that the common millet was the earliest dry farming crop in East Asia, which is probably attributed to its excellent resistance to drought.
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BFBNIB, NMLJ, NUK, PNG, SAZU, UL, UM, UPUK
The ability to detect, respond and adapt to mitochondrial stress ensures the development and survival of organisms. Caenorhabditis elegans responds to mitochondrial stress by activating the ...mitochondrial unfolded protein response (UPR
) to buffer the mitochondrial folding environment, rewire the metabolic state, and promote innate immunity and lifespan extension. Here we show that HDA-1, the C. elegans ortholog of mammalian histone deacetylase (HDAC) is required for mitochondrial stress-mediated activation of UPR
. HDA-1 interacts and coordinates with the genome organizer DVE-1 to induce the transcription of a broad spectrum of UPR
, innate immune response and metabolic reprogramming genes. In rhesus monkey and human tissues, HDAC1/2 transcript levels correlate with the expression of UPR
genes. Knocking down or pharmacological inhibition of HDAC1/2 disrupts the activation of the UPR
and the mitochondrial network in mammalian cells. Our results underscore an evolutionarily conserved mechanism of HDAC1/2 in modulating mitochondrial homeostasis and regulating longevity.
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