Effect of regionalized structures on rock fracture process.

The structure of rocks plays a crucial role in their failure process. However, it is ignored that the interactions between rock internal structure and the effect of its own evolution on the rock fracture process. To investigate the effect between the evolution law of rock regionalized structures and their interaction relationships during failure. We conducted an experiment using visual acoustic imaging monitoring to study rock failure, introducing a new concept of characteristics of rock structure-regionalized structures. The findings reveal three main types of regionalized structures in rocks: skeleton regions, variable regions, and damage regions. These structures combine to form four categories of complex rock structures: block-type support skeletons, point column-type support skeletons, suspension-type weak support skeletons, and no skeletons. During the failure process, we found that these regionalized structures worked together synergistically to control rock failure. Although the evolutionary relationships among the structures show some similarities, the final fracture states vary significantly. Stress and strain distribution patterns clearly demonstrate that variations in the force capacities and roles of the regionalized structures influence the synergistic evolutionary relationships, ultimately impacting the mode of rock failure. This work provides new insights for further research on rock failure mechanisms and can significantly contribute to preventing rock engineering disasters related to regionalized structures.

Repression of LSD1/KDM1A activity improves the response of liver cancer cells to the lenvatinib.

BACKGROUND/AIM: Lenvatinib, a multikinase inhibitor, has become a second-line treatment option for unresectable liver cancer, while its monotherapy response rate is limited. Hence, we aim to investigate whether one of the epigenetic inhibitors will be synthetic lethal with Lenvatinib in liver cancer cells. MATERIALS AND METHODS: We performed high-throughput drug screening in combination with Lenvatinib. And we employed CCK-8-based Bliss Synergy Score analysis, colony formation and western blotting to confirm our screening results in both HepG2 and HCCC9810 cells. RESULTS: We identified that LSD1 inhibitor Pulrodemstat in combination with Lenvatinib dramatically suppressed the PI3K-AKT signaling and induced a more significant activation of Caspase3 compared to Lenvatinib monotherapy. CONCLUSION: Pulrodemstat synergized with Lenvatinib based on suppression of PI3K-AKT signaling and activation of apoptotic signaling.

Comprehensive intratumoral heterogeneity landscaping of liver hepatocellular carcinoma and discerning of APLP2 in cancer progression.

INTRODUCTION: As the sixth most common type of cancer worldwide, liver hepatocellular carcinoma (LIHC) emerges as grave public health danger owing to its chemotherapy-resistant feature. Disulfidoptosis is a newly discovered programmed cell death process affecting the normal actin cytoskeleton structure. METHODS: Single-cell RNA (scRNA)-seq data were procured from GSE149614 and GSE202642 datasets. We utilized uniform manifold approximation and projection and clustering algorithm Louvian for dimensionality reduction and FindAllMarkers function for determining the differentially expressed genes (DEGs). Monocle2 and SCENIC were utilized to perform pseudo-time series and transcription factor analysis for selected subgroups. A series of in vitro experiments, including colony formation assay (CFA), flow cytometry targeting apoptosis and cell cycle, was applied to investigate how APLP2 regulated the LIHC progression. Two cell lines of LIHC cells, HepG2, and Huh7, were used for si-APLP2 transfection. RESULTS: Tumor heterogeneity landscape of LIHC was depicted by detailed subgroup analysis. We found T and B cells were enriched with POU2F1 and HES1 activity. Inflammatory cancer-associated fibroblasts interacted with the cancer cells, uniquely through COL1A1/SDC1, COL1A2/SDC1 and LUM/ITGB1 pathways. The transformation from normal hepatocytes to malignant cells was displayed by cell trajectory analysis. State4, which was determined as malignant cells, was enriched in PI3K, hypoxia, and Epidermal growth factor receptor pathway, and enriched with Nuclear Receptor Subfamily 2 Group F Member 1 transcription factor activity. We observed an intense communication from the cancer cells to endothelial cells, mainly through the Vitronectin (VTN) to Kinase Insert Domain Receptor (KDR) pathway. A prognostic model targeting LIHC was constructed based on the disulfidoptosis-based DEGs, namely APLP2, PDIA6, YBX1, SPP1, whose accuracy was validated in multiple cohorts. Knockdown of APLP2 significantly increased the apoptosis and delayed cell cycle progression of LIHC cell line. CONCLUSION: A prognostic model targeting LIHC was constructed based on the disulfidoptosis-related DEGs, which displayed high stability and accuracy in multiple cohorts. APLP2 played an active role in the carcinogenesis of LIHC by regulating the apoptosis and cell cycle.

Long non-coding RNA CDKN2B-AS1 promotes hepatocellular carcinoma progression via E2F transcription factor 1/G protein subunit alpha Z axis.

BACKGROUND: A series of long non-coding RNAs (lncRNAs) have been reported to play a crucial role in cancer biology. Some previous studies report that lncRNA CDKN2B-AS1 is involved in some human malignancies. However, its role in hepatocellular carcinoma (HCC) has not been fully deciphered. AIM: To decipher the role of CDKN2B-AS1 in the progression of HCC. METHODS: CDKN2B-AS1 expression in HCC was detected by quantitative real-time polymerase chain reaction. The malignant phenotypes of Li-7 and SNU-182 cells were detected by the CCK-8 method, EdU method, and flow cytometry, respectively. RNA immunoprecipitation was executed to confirm the interaction between CDKN2B-AS1 and E2F transcription factor 1 (E2F1). Luciferase reporter assay and chromatin immunoprecipitation were performed to verify the binding of E2F1 to the promoter of G protein subunit alpha Z (GNAZ). E2F1 and GNAZ were detected by western blot in HCC cells. RESULTS: In HCC tissues, CDKN2B-AS1 was upregulated. Depletion of CDKN2B-AS1 inhibited the proliferation of HCC cells, and the depletion of CDKN2B-AS1 also induced cell cycle arrest and apoptosis. CDKN2B-AS1 could interact with E2F1. Depletion of CDKN2B-AS1 inhibited the binding of E2F1 to the GNAZ promoter region. Overexpression of E2F1 reversed the biological effects of depletion of CDKN2B-AS1 on the malignant behaviors of HCC cells. CONCLUSION: CDKN2B-AS1 recruits E2F1 to facilitate GNAZ transcription to promote HCC progression.

Real-Time Recognition Method for Key Signals of Rock Fracture Acoustic Emissions Based on Deep Learning.

The characteristics of acoustic emission signals generated in the process of rock deformation and fission contain rich information on internal rock damage. The use of acoustic emissions monitoring technology can analyze and identify the precursor information of rock failure. At present, in the field of acoustic emissions monitoring and the early warning of rock fracture disasters, there is no real-time identification method for a disaster precursor characteristic signal. It is easy to lose information by analyzing the characteristic parameters of traditional acoustic emissions to find signals that serve as precursors to disasters, and analysis has mostly been based on post-analysis, which leads to poor real-time recognition of disaster precursor characteristics and low application levels in the engineering field. Based on this, this paper regards the acoustic emissions signal of rock fracture as a kind of speech signal generated by rock fracture uses this idea of speech recognition for reference alongside spectral analysis (STFT) and Mel frequency analysis to realize the feature extraction of acoustic emissions from rock fracture. In deep learning, based on the VGG16 convolutional neural network and AlexNet convolutional neural network, six intelligent real-time recognition models of rock fracture and key acoustic emission signals were constructed, and the network structure and loss function of traditional VGG16 were optimized. The experimental results show that these six deep-learning models can achieve the real-time intelligent recognition of key signals, and Mel, combined with the improved VGG16, achieved the best performance with 87.68% accuracy and 81.05% recall. Then, by comparing multiple groups of signal recognition models, Mel+VGG-FL proposed in this paper was verified as having a high recognition accuracy and certain recognition efficiency, performing the intelligent real-time recognition of key acoustic emission signals in the process of rock fracture more accurately, which can provide new ideas and methods for related research and the real-time intelligent recognition of rock fracture precursor characteristics.

Alive but not well: The neglected cost of air pollution.

Besides medical expenses, hospitalizations associated with air pollution will incur the welfare loss due to activity restrictions and the wage loss due to inability to work. We fill in the gap in the literature by examining the impact of air pollution on volume and intensity of hospitalizations, which allows us to incorporate the welfare loss and the wage loss. Using a data set that covers most of the inpatients in a major Chinese city during 2015-16, we find that worse air quality causes more hospital admissions, more total inpatient days, and higher total inpatient expenditure for various diseases, particularly diseases of the respiratory and circulatory systems. We also find that there would be an underestimate of the loss from air pollution if we had ignored the loss associated with activity restrictions and the wage loss during hospitalization.

Differential impacts of vaccine scandal by ethnic and socioeconomic factors: Evidence from China.

Widespread vaccination against important diseases plays a key role for global health security, particularly in the context of the COVID-19 pandemic. However, building and maintaining trust in immunization services remains challenging because of doubts about quality and safety of vaccines. China has periodically faced mounting pressure and even public outrage triggered by incidents of poor-quality vaccines. We aimed to evaluate the impact of the diphtheria, pertussis, and tetanus (DPT) vaccine scandal of 2018 in China and the ensuing misinformation on vaccination, and investigate differential responses to the scandal by ethnic and socioeconomic factors. With data from January 2017 to December 2018 in Sichuan province, China, we used a difference-in-differences (DID) method to compare the changes in the county-level monthly DPT vaccinations against the hepatitis B vaccinations, both before and after the DPT vaccine scandal. We found that the number of DPT vaccinations decreased by 14.0 percent in response to the vaccine scandal and ensuing misinformation. The number of vaccinations in minority regions, under-developed regions, and regions with poor medical resources decreased more than in non-minority regions, developed regions, and regions with good medical resources (24.5 versus 10.1 percent, 17.3 versus 8.3 percent, and 17.0 versus 8.7 percent, respectively). People did more online searching for "Substandard vaccine" and "DPT vaccine" after the scandal, with the socioeconomically advantaged group searching more compared with the socioeconomically disadvantaged group. The results suggest the urgent need to make true information about the vaccine easily accessible over the internet, especially for the socioeconomically disadvantaged groups. Our findings for China can also have implications for immunization service planning for better safeguarding public health in other countries, particularly developing ones.

The emergence of complex adaptive response networks in China: A case study of four disasters.

This study aims to identify the driving forces behind interorganizational networks in China following disasters. Using the theory of complex adaptive systems, we identified the self-organization process of disaster response as the network formation process. We identified interorganizational networks that emerged in response to two natural hazards and two technical disasters by collecting data from multiple sources. The exponential random model analysis is performed to analyze the effects of structures and organizational attributes on network formation. In structuring networks for disaster response, findings demonstrate that bonding structures take precedence over bridging structures for organizations. Meanwhile, the sector and jurisdiction-based homophily effects facilitate network formation in disaster response. On the basis of research findings, five propositions describing the network formation process in China's disaster response are proposed. Such a theoretical model is essential for advancing research and practice in complex disaster network management.

Durable Clinical Response of Advanced Lung Adenocarcinoma Harboring EGFR-19del/T790M/BRAFV600E Mutations After Treating with Osimertinib and Dabrafenib Plus Trametinib: A Case Report.

EGFR-T790M and BRAFV600E are the common resistance mechanisms to EGFR-tyrosine kinase inhibitors (TKIs). Standard treatment for the triple mutations of EGFR-19del, T790M, and BRAFV600E is still under debate. Herein, we present a case of therapeutic efficacy of osimertinib and dabrafenib plus trametinib on a 63-year-old man with advanced lung adenocarcinoma. This patient reached a remarkable progression-free survival of 9 months without any serious adverse reaction. At the progression of the disease, C797S mutation in cis was detected by liquid biopsy. Subsequently, brigatinib with cetuximab was administered but no curative effect was observed. Then, therapy was changed to apatinib combined with osimertinib. The subsequent CT scan showed that the lesions reached stable disease (SD), and the survival benefit has been evaluated. This case showed that the combination treatment of osimertinib and dabrafenib plus trametinib might be a great treatment option for NSCLC patients with triple mutations (EGFR-19del/T790M/BRAFV600E).

Deep Learning Method on Target Echo Signal Recognition for Obscurant Penetrating Lidar Detection in Degraded Visual Environments.

With the rapid development of autonomous vehicles and mobile robotics, the desire to advance robust light detection and ranging (Lidar) detection methods for real world applications is increasing. However, this task still suffers in degraded visual environments (DVE), including smoke, dust, fog, and rain, as the aerosols lead to false alarm and dysfunction. Therefore, a novel Lidar target echo signal recognition method, based on a multi-distance measurement and deep learning algorithm is presented in this paper; neither the backscatter suppression nor the denoise functions are required. The 2-D spectrogram images are constructed by using the frequency-distance relation derived from the 1-D echo signals of the Lidar sensor individual cell in the course of approaching target. The characteristics of the target echo signal and noise in the spectrogram images are analyzed and determined; thus, the target recognition criterion is established accordingly. A customized deep learning algorithm is subsequently developed to perform the recognition. The simulation and experimental results demonstrate that the proposed method can significantly improve the Lidar detection performance in DVE.

The beneficial effects of postconditioning on no-reflow phenomenon after percutaneous coronary intervention in patients with ST-elevation acute myocardial infarction.

No-reflow phenomenon is a serious complication of percutaneous coronary intervention (PCI) which is closely related to the incidence of major adverse cardiovascular events. It has been demonstrated that Postconditioning (PostC) during primary PCI confers protection against ischemia-reperfusion injury and thus might reduce infarct size. However, whether PostC may exert its beneficial effects on acute myocardial infarction (AMI) patients by reducing no-reflow phenomenon is still unknown. Sixty two patients diagnosed with ST-elevation AMI were randomly assigned to study group (n = 32) or control group (n = 30). Blood samples were obtained and assayed for creatine kinase MB (CK-MB) and high-sensitive C-reactive protein (hs-CRP). Determinants of reflow, including final thrombolysis in myocardial infarction (TIMI) grade-3 flow, ST-segment resolution (STR), myocardial blush grades-3 (MBG-3) and corrected thrombolysis in myocardial infarction frame count (cTFC), were comparative between the two groups. Compared with control group, more patients in study group were identified as the final TIMI grade-3 flow (81.3 vs. 56.7%, P = 0.036), MBG-3 (23 vs. 14%, P = 0.043) and STR ≥50% (93.8 vs. 73.3%, P = 0.029), while patients in study group had less cTFC (28.5 ± 9.1 vs. 37.4 ± 12.4, P = 0.002) After PCI, study group was associated with lower levels of CK-MB (2,397.6 ± 470.2 vs. 2,159.9 ± 485.5, P = 0.028), Troponin-I (197.5 ± 32.5 vs. 154 ± 43.1, P = 0.041) and hs-CRP (5.5 ± 4.5 vs. 9.5 ± 5.2 mg/L, P = 0.019) in comparison with control group. Left ventricle ejection fraction was better in the study group than in the control group (55.1 ± 9.8 vs. 42.9 ± 10.7, P = 0.042). PostC could improve myocardial reperfusion in patients with ST-elevation AMI undergoing PCI by reducing no-reflow. However, due to the limited sample size, the results of our study should not be considered conclusive.

Association between local interleukin-6 levels and slow flow/microvascular dysfunction.

We aimed to investigate the association between local interleukin-6 (IL-6) levels at the infarct-related artery and the risk of slow flow/microvascular dysfunction after PCI in ST-elevation acute myocardial infarction (AMI) patients treated by successful primary PCI. 56 eligible ST-elevation AMI patients (34 male/22 female, mean age: 63.5 ± 10.3 years), undergoing successful primary PCI, were included in the current study. Blood samples were obtained from the extraction catheter placed distal to the lesion before PCI. Plasma IL-6 levels were determined by immunoassay method. Slow flow/microvascular dysfunction was observed in 21 patients (37.5%). Using multiple logistic regression analysis, local IL-6 levels (OR 1.592, CI 1.135-2.268; P = 0.007) were found to be a significant risk factor of slow flow/microvascular dysfunction together with diabetes mellitus (OR = 8.065, CI 1.244-52.632; P = 0.029) and thrombus score (OR = 12.500, CI 1.100-142.857; P = 0.042). Receiver operating characteristic (ROC) curve analysis revealed that local IL-6 (ROC area 0.824, OR 1.704, CI 1.274-2.281, P < 0.001; optimal threshold ≥11.3 pg/ml) had a predictive value of slow flow/microvascular dysfunction with sensitivity of 73% and specificity of 71%. Our study indicated that inflammatory response as presented by local IL-6 levels was associated with slow flow/microvascular dysfunction in patients with ST-elevation AMI after successful primary PCI.

Tumor necrosis factor-alpha G-308 A polymorphism and risk of coronary heart disease and myocardial infarction: A case-control study and meta-analysis.

OBJECTIVES: The tumor necrosis factor-alpha (TNF-α) gene may play an important role in coronary heart disease (CHD) and myocardial infarction (MI) risk. Recently, controversial results regarding the association of the G-308 A (rs1800629)polymorphism of the TNF-α gene with CHD/MI have been reported. We herein examine a possible association between the G-308 A (rs1800629)polymorphism of the TNF-α gene and CHD/MI in a sample of the Chinese Han population. MATERIALS AND METHODS: We determined the genotypes of TNF-α G-308 A (rs1800629) in 535 unrelated Chinese patients with CHD, 420 patients with MI, and 1020 coronary artery disease-free controls. Additionally, a meta-analysis of all previous studies on the TNF-α G-308 A polymorphism and the risk of CHD and MI was performed. RESULTS: AA genotypes in the G-308 A (rs1800629)polymorphism of the TNF-α gene did not occur more frequently in CHD/MI patients than in controls; odds ratios (95% confidence intervals) were 1.743 (0.325 to 1.423) for CHD and 1.731 (0.442 to 1.526) for MI, after adjusting for conventional risk factors. Further stratification for age, gender, and other cardiovascular risk factors did not alter the prior negative findings. Pooled meta-analysis of 23 studies also found no statistically significant associations between the TNF-α polymorphism and CHD/MI risk in the genetic additive, dominant, and recessive models. Subgroup analyses showed no association between the TNF-α polymorphism and CHD/MI in Asian and Caucasian populations. CONCLUSION: Our study showed no association between the G-308 A (rs1800629) polymorphism of the TNF-α gene (presence of A allele) and CHD/MI in the Chinese Han population. There was no evidence of a difference in risk effects of rs1800629 between Caucasians and Asians.

Associations between CYP11B2 gene -344T/C polymorphism and essential hypertension in the Han nationality in Shandong province.

OBJECTIVE: To investigate whether the -344T/C polymorphism of CYP11B2 gene is associated with essential hypertension in the Hans in Shandong province. METHODS: Plasma renin activity (PRA) and plasma aldosterone concentration (PAC) were measured with radioimmunoassays; the hypertensives were classified as low-renin and normal- or high-renin group by PAC/PRA ratio. -344T/C polymorphism was determined by polymerase chain reaction-restricted fragment length polymorphism (PCR-RFLP) in controls and hypertensives. RESULTS: No significant differences were found in genotype distribution or allele frequency between groups of control and primary hypertension or between groups of control and normal- or high-renin hypertension. The C allele frequency in low-renin hypertension group was significantly higher than that in normotensives and normal- or high-renin hypertension group (P < 0.05). CONCLUSION: These results suggest that -344T/C polymorphism of CYP11B2 gene may be associated with low-renin essential hypertension in the Han nationality in Shandong province.