Rock Crack Recognition Technology Based on Deep Learning.

The changes in cracks on the surface of rock mass reflect the development of geological disasters, so cracks on the surface of rock mass are early signs of geological disasters such as landslides, collapses, and debris flows. To research geological disasters, it is crucial to swiftly and precisely gather crack information on the surface of rock masses. Drone videography surveys can effectively avoid the limitations of the terrain. This has become an essential method in disaster investigation. This manuscript proposes rock crack recognition technology based on deep learning. First, images of cracks on the surface of a rock mass obtained by a drone were cut into small pictures of 640 × 640. Next, a VOC dataset was produced for crack object detection by enhancing the data with data augmentation techniques, labeling the image using Labelimg. Then, we divided the data into test sets and training sets in a ratio of 2:8. Then, the YOLOv7 model was improved by combining different attention mechanisms. This study is the first to combine YOLOv7 and an attention mechanism for rock crack detection. Finally, the rock crack recognition technology was obtained through comparative analysis. The results show that the precision of the improved model using the SimAM attention mechanism can reach 100%, the recall rate can achieve 75%, the AP can reach 96.89%, and the processing time per 100 images is 10 s, which is the optimal model compared with the other five models. The improvement is relative to the original model, in which the precision was improved by 1.67%, the recall by 1.25%, and the AP by 1.45%, with no decrease in running speed. This proves that rock crack recognition technology based on deep learning can achieve rapid and precise results. It provides a new research direction for identifying early signs of geological hazards.

Comprehensive Analyses of Stromal-Immune Score-Related Competing Endogenous RNA Networks In Colon Adenocarcinoma.

Although recent clinical investigations emphasize the roles of myriad diversities of RNAs in stromal and immune components in the tumor microenvironment, especially in colon adenocarcinoma, however, analyses of "competing endogenous RNAs (ceRNA)" network in association with stromal and immune scores have yet to be determined. This study was conducted to explore the regulatory mechanisms of a stromal-immune score-based ceRNA network in colon adenocarcinoma. Stromal and immune scores of colon adenocarcinoma tumor samples were calculated by using the ESTIMATE algorithm. Differential expression analysis between samples with high/low stromal and immune scores was performed, followed by functional annotation for the overlapping DEmRNAs. The ceRNA network was constructed by differential expression analysis, prediction of RNA-RNA interaction, and correlation with clinicopathological parameters of the patients, which were further verified by external datasets and experiments. Colon adenocarcinoma patients having higher immune scores exhibited prolonged overall survival. RNA dataset analyses from TCGA revealed aberrant expressions of a total of 2052 mRNAs, 108 lncRNAs, and 70 miRNAs between high and low stromal/immune groups. Functional annotation mapped the differentially overexpressed mRNAs for immune-associated GO terms. To construct the ceRNA network, a total of 48 lncRNAs, 40 miRNAs, and 199 mRNAs were sorted out. A dysregulated ceRNA network consisting of 6 lncRNAs, 11 miRNAs, and 39 mRNAs was constructed by comparing RNA expressions between cancer as well as adjacent normal tissues. The ceRNA regulatory axis "MIAT/miR-532-3p/STC1" was regarded as a potential hit by the comprehensive analysis. The RT-qPCR assay showed upregulation of MIAT and STC1 while downregulation of hsa-miR-532-3p expression in cancer. Thus, our study highlights the potential role of a stromal-immune score-based ceRNA network in the colon adenocarcinoma microenvironment. The ceRNA axis MIAT/miR-532-3p/STC1 could serve as a promising therapeutic target for colon adenocarcinoma.

ATAD2 drives colorectal cancer progression by regulating TRIM25 expression via a positive feedback loop with E2F transcriptional factors.

ATPase family AAA domain-containing protein 2 (ATAD2) is highly expressed in a variety of cancer types, and acts as a co-activator of androgen and estrogen receptors, as well as MYC and E2F transcription factors, to promote tumor cell proliferation. However, the regulation of ATAD2 and its related mechanisms are still elusive. Here, we show that ATAD2 protein was stabilized during DNA damage response in colorectal cancer (CRC) cells. TRIM25, an oncogenic ubiquitin E3 ligase, can interact with ATAD2 and stabilize ATAD2 upon genotoxic insult. We further demonstrated that ATAD2 played a tumor promoting role in CRC and acted as a transcriptional co-activator of E2Fs to promote the expression of TRIM25. Thus, our results revealed an unknown ATAD2-E2Fs-TRIM25 positive feedback loop that drove CRC progression.

Laboratory Exercise to Measure Plasmid Copy Number by qPCR.

Quantitative PCR (qPCR) has numerous applications in biology. In an educational setting, qPCR provides students an opportunity to better understand the PCR mechanism by providing both quantitative information about the reactions and also data to troubleshoot PCRs (e.g., melt curves). Here, we present a relatively short (2-h) laboratory activity to demonstrate qPCR to quantify plasmid copy number (CN) by measuring the cycle threshold (CT ) values for a genomic gene and a plasmid gene using transformed cells as a template. The activity can be combined with additional laboratory exercises, including bacterial transformation, to create the template to be used in the qPCRs. This lab activity is ideal for undergraduate laboratory courses that include recombinant DNA technology. (This work was presented at the 2020 Biomedical Engineering Society annual meeting).

The association between serum selenium concentration and prognosis in patients with heart failure in a Chinese population.

Whether Selenium (Se) deficiency relates with adverse prognosis in Chinese patients with heart failure (HF) is still unknown. This study aimed to investigate the association of serum Se level and the outcomes of patients with HF in a Chinese population. Patients with HF and serum Se examination were retrospectively included. Baseline information were collected at patient's first admission. The primary and secondary outcomes were all-cause mortality and rehospitalization for HF during follow-up, respectively. The study participants were divided into quartiles according to their serum Se concentrations. The Cox proportional hazard models were adopted to estimate the association of serum Se levels with observed outcomes. A total of 411 patients with HF with a mean age of 62.5 years were included. The mean serum level of Se was 68.3 ± 27.7 µg/L. There was nonsignificant difference of baseline characterizes between the four quartile groups. In comparison with patients in the highest quartile, those with the lowest quartile (17.40-44.35 µg/L) were associated with increased risk of all-cause mortality [adjusted hazard ratios (95% CI) 2.32 (1.43-3.77); Ptrend = 0.001]. Our study suggested that a lower serum Se level was significantly associated with increased risk of all-cause mortality in patients with HF.

LncRNA KCNQ1OT1 as a miR-26a-5p sponge regulates ATG12-mediated cardiomyocyte autophagy and aggravates myocardial infarction.

BACKGROUND: As a dominant cardiovascular disease, myocardial infarction (MI) causes a considerable mortality globally. KCNQ1 overlapping transcript 1 (KCNQ1OT1) was reported to be overexpressed in MI patients. However, the detailed mechanisms remain unclear. METHODS: We analyzed the expression of KCNQ1OT1 in the serum of MI patients, and built ischemia/reperfusion (I/R) mouse and H/R-induced cell model. TTC staining was used to evaluate infarct size in mice. TUNEL was employed to assess cell apoptosis. QRT-PCR was performed to detect the expression of KCNQ1OT1 and miR-26a-5p. The formation of autophagosomes in cells was detected by immunofluorescence. Caspase3 activity was detected by the Caspase-3 Assay Kit. Autophagy and apoptosis-related proteins were assessed by western blotting. Luciferase reporter assay was used to assess the binding relationship of KCNQ1OT1 and miR-26a-5p and miR-20a-5p/ATG12. RESULTS: KCNQ1OT1 was up-regulated while miR-26a-5p was decreased in MI patients, I/R mouse and H/R-induced cell model. KCNQ1OT1 knockdown inhibited cell autophagy and protected cardiomyocytes from apoptosis by up-regulating miR-26a-5p. Either KCNQ1OT1 knockdown or miR-26a-5p mimics caused inhibition of autophagy related 12 homolog (ATG12), which was the direct target of miR-26a-5p. In vivo, KCNQ1OT1 promoted cardiomyocytes apoptosis via miR-26a-5p/ATG12 pathway. CONCLUSION: KCNQ1OT1/miR-26a-5p/ATG12 axis regulated cardiomyocyte autophagy and apoptosis, both in vivo and in vitro. These data supported that KCNQ1OT1 inhibition might be a promising therapeutic option for protection after MI.