Effect of home exercise rehabilitation on cardiopulmonary function in patients with varying degrees of coronary revascularization

Objective To investigate the effect of home exercise rehabilitation on cardiopulmonary function in patients with varying degrees of coronary revascularization. Methods A total of 93 patients who were diagnosed with acute coronary syndrome and underwent percutaneous coronary intervention from September 2020 to September 2022 and received home exercise rehabilitation were selected from the database of Cardiac Rehabilitation Center. According to the residual syntax score (rSS), the patients were divided into rSS<8 group with 51 patients and rSS≥8 group with 42 patients. The cardiopulmonary function exercise test (CPET) was used to evaluate cardiopulmonary function, and the two groups were compared in terms of the changes in CPET parameters after 6 months of home exercise rehabilitation. Results After 6 months of home exercise rehabilitation, both groups had significant increases in oxygen uptake at anaerobic threshold, peak oxygen uptake, oxygen pulse rate at anaerobic threshold, and peak oxygen pulse rate (t=-2.953--5.483,P<0.05). There were significant differences in the changes of carbon dioxide ventilation efficiency at anaerobic threshold and peak carbon dioxide ventilation efficiency after home exercise rehabilitation between the two groups (Z=-2.046,-2.206,P<0.05). Conclusion Home exercise rehabilitation can improve the cardiopulmonary function of patients with acute coronary syndrome after percutaneous coronary intervention and bring more benefits for cardiac function in patients with rSS≥8

Generation of a human iPSC line from a patient with Marfan syndrome caused by mutation in FBN1

Marfan syndrome (MFS) is a heritable connective tissue disease caused by mutations in FBN1, encoding the extracellular matrix protein fibrillin-1. In this study, we generated human induced pluripotent stem cells (iPSCs) from dermal fibroblasts of an MFS patient with the p. E2130K (c. 6388G > A) mutation. The generated hiPSC line had a normal karyotype, showed robust expression of pluripotency markers and was able to differentiate into all three germ layers in vivo. This cell line can provide a platform for understanding the pathogenic mechanisms of MFS related to FBN1 mutations.Resource table.Unlabelled TableUnique stem cell identifierCMUi001-AAlternative name(s) of stem cell lineFBN1-E2130K-iPSCInstitutionAnzhen Hospital, Capital Medical UniversityContact information of [email protected] of cell lineiPSCOriginHumanAdditional origin infoAge: 25Sex: maleEthnicity: Han nationalityCell sourcePatient derived fibroblastsClonalityClonalMethod of reprogrammingSendai virus. Oct4, Sox2, cMyc, Klf4Genetic modificationNOType of modificationN/AAssociated diseaseMarfan syndrome (aortic root aneurysm)Gene/locusGene: FBN1Locus: 15q21.1Mutation: heterozygote c.6388G > A (p.E2130K)Method of modificationN/AName of transgene or resistanceN/AInducible/constitutive systemN/AData archived/stock date02/2018Cell line repository/bankN/AEthical approvalEthics Committee of Anzhen Hospital, Capital Medical University(#134/18

Experimental platform for coal gangue sorting robot based on image detection

Currently, coal gangue pre-sorting is still mostly done manually, with high labor intensity, low sorting efficiency, and safety hazards. Using coal gangue sorting robots to replace manual coal gangue pre-sorting is an effective way to ensure the health and safety of workers and improve work efficiency. However, the existing coal gangue sorting robots have poor performance in situations such as low light intensity and coal gangue surface covered with coal powder. To solve the above problems, an experimental platform for coal gangue sorting robot based on image detection is proposed. This experimental platform collects coal gangue images through industrial cameras. The platform uses ResNet18-YOLOv3 deep learning algorithm to identify the coal gangue in the images. The platform uses TCP communication to provide the position information of the gangue to the coal gangue sorting module for trajectory planning, then controls the manipulator to clamp the gangue and completes the gangue sorting operation. The platform uses the Halcon calibration method for hand-eye calibration of the experimental platform, in order to achieve the conversion of camera pixel coordinates and manipulator spatial coordinates. The positioning error of the experimental platform is calibrated. For coal gangue samples with sizes above 50 mm, the positioning error should not exceed 9 mm. The experimental results show that the recognition accuracy of the experimental platform for coal gangue under strong lighting conditions is 99%. The recognition accuracy of coal gangue under weak lighting conditions is 95%. The recognition accuracy of coal gangue under pulverized coal adhesion conditions is not less than 82%. The accuracy of coal gangue sorting is 82%

Radiogenomics for predicting microsatellite instability status and PD-L1 expression with machine learning in endometrial cancers: A multicenter study

Purpose: To evaluate the effectiveness of machine learning model based on magnetic resonance imaging (MRI) in identifying microsatellite instability (MSI) status and PD-L1 expression in endometrial cancer (EC). Methods: This retrospective study included 82 EC patients from 2 independent centers. Radiomics features from the intratumoral and peritumoral regions, obtained from four conventional MRI sequences (T2-weighted images; contrast-enhanced T1-weighted images; diffusion-weighted images; apparent diffusion coefficient), were combined with clinicopathologic characteristics to develop machine learning model for predicting MSI status and PD-L1 expression. 60 patients from center 1 were used as the training set for model construction, while 22 patients from center 2 were used as an external validation set for model evaluation. Results: For predicting MSI status, the clinicopathologic model, radscore model, and combination model achieved area under the curves (AUCs) of 0.728, 0.833, and 0.889 in the training set, respectively, and 0.595, 0.790, and 0.848 in the validation set, respectively. For predicting PD-L1 expression, the clinicopathologic model, radscore model, and combination model achieved AUCs of 0.648, 0.814, and 0.834 in the training set, respectively, and 0.660, 0.708, and 0.764 in the validation set, respectively. Calibration curve analysis and decision curve analysis demonstrated good calibration and clinical utility of the combination model. Conclusion: The machine learning model incorporating MRI-based radiomics features and clinicopathologic characteristics could be a potential tool for predicting MSI status and PD-L1 expression in EC. This approach may contribute to precision medicine for EC patients

Numerical simulation on concentration distribution law of oil and gas in tank farm during leakage diffusion

The leakage of tank oils, once occurred, will bring about adverse effect to ambient environment, social economy and safety of tank farm, and even cause safety accident. Herein, the leakage diffusion process of oil and gas was simulated with the improved Gaussian puff model to find out the concentration distribution law of oil and gas in tank farm under different environmental wind speeds and atmospheric stability. Meanwhile, the tank farm was divided into the explosive hazardous area, flash fire hazardous area and suffocation hazardous area according to the risk level of oil and gas concentration. By analyzing the influence of environmental wind speed and atmospheric stability on migration and diffusion of oil and gas puff, the influence law of environmental conditions of tank farm on concentration distribution of oil and gas, as well as the scope of hazardous area, was obtained. Specifically, the migration and diffusion of oil and gas puff is intensified with the increasing of environmental wind speed, but the concentration of oil and gas in the tank farm is reduced, and the hazardous areas of different grades are reduced accordingly. With the increase of atmospheric stability, the diffusion of oil and gas puff becomes weaker, the influence range of concentration along the downwind direction increases, but the influence range along the crosswind direction decreases. Because of the fluctuation of wind speed, the oil and gas puff may gather and form an oil and gas accumulation area at high concentration. Generally, the lower the environmental wind speed and the more stable the atmosphere, the easier the oil and gas puff to gather. The improved Gaussian puff model may more accurately reflect the leakage diffusion law of oil and gas, and predict the concentration distribution of oil and gas, which could provide guidance to the safe operation and management of tanks

Inhibitory effect of microRNA-608 on lung cancer cell proliferation, migration, and invasion by targeting BRD4 through the JAK2/STAT3 pathway

Lung cancer is the leading cause of cancer-related mortality around the world. This malignancy has a 5-year survival rate of 21%, because most of the patients are diagnosed in the middle or late stage of the disease when local metastasis and tumor invasion have already progressed. Therefore, the investigation of the pathogenesis of lung cancer is an issue of crucial importance. MicroRNAs (miRNAs) seem to be involved in the evolution and development of lung cancer. MicroRNA-608 is likely to be downregulated in lung cancer tissues. Regarding this, the current study involved the determination of the fundamental mechanism of microRNA-608 in the development of lung cancer. Based on the results of quantitative reverse transcription polymerase chain reaction (RT-qPCR), the expression level of microRNA-608 was downregulated in 40 lung cancer tissues, compared to that in the adjacent normal tissues. The results of dual-luciferase reporter assay revealed that bromodomain-containing protein 4 (BRD4) was the direct target of microRNA-608. Accordingly, the lung cancer tissues had an elevated expression level of BRD4, in contrast to the adjacent normal tissues. The results of Cell Counting Kit 8 assay demonstrated that the high expression of microRNA-608 notably restrained lung cancer cell proliferation. The scratch wound and transwell assays showed that the upregulation of microRNA-608 suppressed the migration and invasion of lung cancer cells. Finally, the western blot assay showed that in the microRNA-608 mimics group, the expression levels of BRD4, p-JAK2, p-STATA3, CD44, and MMP9 were significantly decreased, compared with those in the negative control miRNA mimics group. Our results indicate that high expression of microRNA-608 inhibits the proliferation, migration, and invasion of lung cancer cells by targeting BRD4 via the JAK2/STAT3 pathway

Suppression of soil-borne Fusarium pathogens of peanut by intercropping with the medicinal herb Atractylodes lancea

Abstract Intercropping has historically been employed as an efficient management strategy to prevent disease outbreaks. Our previous studies indicated that intercropping of peanut with the Chinese medicinal herb, Atractylodes lancea effectively suppressed soil-borne peanut diseases, resulting in increased peanut yields. However, the underlying mechanism is unknown. In this study, the below ground effects of A. lancea on both fungal and bacterial communities in the peanut rhizosphere were investigated using pyrosequencing of the internal transcribed spacer (ITS1) and16S rRNA gene amplicons, respectively. Closed cultivation systems were constructed to investigate the role of volatiles and exudates originating from rhizomes and roots of A. lancea on fungal and bacterial communities. Intercropping with A. lancea significantly altered fungal community composition in the peanut rhizosphere, coinciding with decline of Fusarium root rot and improvement of peanut growth. Volatiles originating from A. lancea rhizome material had more effects on fungal communities than on bacterial communities, and significantly suppressed F. oxysporum growth. Root exudates of A. lancea had no apparent inhibitory effect on F. oxysporum. Gas chromatography–mass spectrometry (GC-MS) analysis revealed 21 volatiles originating from A. lancea rhizome material and terpenes and aromatic hydrocarbons were the most common types. Our results suggest that A. lancea suppressed pathogenic Fusarium populations by means of volatiles from the rhizome. Our results support the idea that intercropping with A. lancea or use of its effective components has a strong potential for managing soil-borne fungal diseases

Characteristics and achievements of the Xin'an Medical School

The Xin'an Medical School began in the Jin Dynasty (266–420), developed in the Song Dynasty (960–1279), prospered in the Ming and Qing dynasties (1368–1911), and has been passed down to the modern era. As a school of medicine with distinct regional characteristics, it has contributed to the development of traditional Chinese medicine and exerted far-reaching influence, mainly in literature resources, medical theory, clinical application, and spiritual culture. This paper intends to discuss its academic characteristics and contribution to the development of traditional Chinese medicine, focusing on its formation, academic inheritance and innovation, overseas popularization, and integration of Confucianism, Taoism, and Buddhism in medicine. Keywords: Xin'an Medical School, Regional medical schools, Ancient Huizhou, Achievements and characteristic