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This paper summarized the effect of prone position ventilation and nursing management for a patient with respiratory distress syndrome caused by COVID-19. The compressive nursing assessment, airway management and tube fixation were conducted before using prone position ventilation for therapy. After implementation of prone position ventilation for therapy, efforts had been made to enhance the vital signs monitoring, tube maintenance, airway management, nutrition support and prevention of pressure injuries. (本文总结1例新型冠状病毒感染致呼吸窘迫综合征患者俯卧位通气法的应用效果及护理体会。操作前系统评估患者和完善物品准备, 保持气道通畅和妥善固定管道; 操作后密切监测患者生命体征, 加强导管维护、呼吸道护理和营养支持, 积极预防压力性损伤。)

to summarize a case of acute myocardial infarction (Ami) who was treated with emergency PCI after intravenous thrombolytic therapy. During the treatment, nursing intervention was carried out for the patients with severe pain due to myocardial ischemia, to enhance the patient’s own comfort. And the implementation of patients with cardiac rehabilitation care, so as to ease the patients during the treatment of excessive reaction to improve the treatment effect. This article reviews the first aid measures and nursing measures of 1 patient with acute myocardial infarction, and summarizes the relevant nursing experience (本文总结1例急性心肌梗死(AMI)静脉溶栓患者的护理经验, 包括饮食干预、健康宣教等常规护理以及疼痛干预、溶栓治疗不同阶段的护理措施, 通过快速正确诊断、密切观察病情变化、及时治疗和精心护理, 提高AMI患者生存率和生命质量。)

The risk of medical disputes is relatively high in the Emergency Department. Issues of nurse-patient communication, triage, nursing records, quality of care are influencing factors of nursing risk. Identification of high-risk patients, high-risk nurses, high-risk working periods and optimizing the hospital visiting constitute the precondition of reducing risk in emergency care. By implementing risk management, improving nursing level and social positive interaction, the incidence of nursing risk events can be reduced and the safety of patients, medical staff and family members can be ensured. (急诊科是医疗纠纷的高风险科室。护患沟通、分诊、护理记录、护理质量是引发护理风险的相关因素, 准确识别高危患者、高危护士、高危时段, 优化就诊环节是降低急诊护理风险的前提。通过实施纠纷风险管理、提高护理水平、社会良性互动, 有助于降低护理风险事件的发生率, 保证患者及医护等人员的安全。)

In the process of plunge cylindrical grinding, it is difficult to directly measure the contact stiffness between the grinding wheel and the workpiece. In order to solve this problem, a simplified method for qualitatively determining the contact stiffness between the grinding wheel and the workpiece is proposed, and the grinding parameters are optimized. Based on the dynamic model of plunge cylindrical grinding process, the transfer function of grinding process is deduced, and the mathematical model of the time constant and contact stiffness is established. A simplified method for qualitative determination of grinding contact stiffness is proposed. Further, multiple tests are conducted by controlling the wheel feed speed and the workpiece speed. According to the experimental results, the variation of the system time constant and the grinding force with the grinding parameters are analyzed. The relationship model between the contact stiffness and the grinding parameters is established by regression analysis, and the optimal values of the wheel feed speed and the workpiece speed in the specific grinding process are determined under the condition of meeting the machining requirements.

This paper focus on Mckean-Vlasov stochastic differential equations (SDEs) with two-time-scale Markov switching. These stochastic processes include the microcosmic location, the macrocosmic distribution of particles and the discrete event. Under appropriate conditions, by using martingale method, we prove that the original system will weakly converge to the corresponding limit system as ε → 0. Finally, an example is given to illustrate our results and the conclusion and future works are presented. [ABSTRACT FROM AUTHOR]

Captive and free-living wildlife serve as significant hosts for Giardia duodenalis. Asiatic black bears, valued for their economic and medicinal importance, are extensively farmed in China and also prevalent in zoos. However, studies on G. duodenalis in these animals in China are limited. Here, 218 feces samples of Asiatic black bears were collected: 36 from a zoo in Heilongjiang Province, and 182 from a farm in Fujian Province. Nested PCR of the SSU rRNA gene, followed by sequencing, was employed to determine the frequency and assemblage distribution of G. duodenalis. Positive samples underwent further analysis through multilocus genotyping (MLG) by amplifying the genes for glutamate dehydrogenase (gdh), β-giardin (bg), and triosephosphate isomerase (tpi). Of the 218 samples, G. duodenalis was detected in 22 cases at the SSU rRNA gene locus, including three from Heilongjiang and 19 from Fujian. Three assemblages were identified: A (n = 1), B (n = 16), and E (n = 2) in Fujian; and B (n = 3) in Heilongjiang. Out of the 22 positive samples, 20, 19, and 9 were effectively amplified and sequenced across the tpi, gdh, and bg loci, respectively. Seven samples were genotyped successfully at all three loci, identifying MLG-B1 (n = 1), MLG-B2 (n = 1), and MLG-B3 (n = 1), MLG-B4 (n = 1), MLG-B5 (n = 2), and MLG-B6 (n = 1) as the six assemblage B MLGs. This study marks the first documentation of G. duodenalis in Asiatic black bears in captivity in Fujian and Heilongjiang. The identification of zoonotic assemblages A and B, along with E, underscores potential public health concerns.

Rationale: Lung cancer is the leading cause of cancer death worldwide, and treatment options are limited to mainly cytotoxic agents. Here we reveal a novel role of miR-150 in non-small cell lung cancer (NSCLC) development and seek potential new therapeutic targets. Methods: The miR-150-mediated autophagy dysfunction in NSCLC cells were examined using molecular methods in vitro and in vivo. The upstream regulatory element and downstream target of miR-150 were identified in vitro and validated in vivo. Potential therapeutic methods (anti-c-myc or anti-miR-150) were tested in vitro and in vivo. Clinical relevance of the c-myc/miR-150/EPG5 axis in NSCLC was validated in human clinical samples and large genomics database. Results: miR-150 blocked the fusion of autophagosomes and lysosomes through directly repressing EPG5. The miR-150-mediated autophagy defect induced ER stress and increased cellular ROS levels and DNA damage response, and promoted NSCLC cell proliferation and tumor growth. Knockdown of EPG5 promoted NSCLC cell proliferation, and attenuated the effects of miR-150. c-myc gene was identified as a miR-150 transcriptional factor which increased miR-150 accumulation, therefore pharmacologically or genetically inhibiting c-myc/miR-150 expression significantly inhibited NSCLC cell growth in vitro and in vivo. Both c-myc and miR-150 were significantly over-expressed in NSCLC, while EPG5 was down-regulated in NSCLC. Expression levels of these molecules were well correlated, and also well correlated with patient survival. Conclusions: Our findings suggest that c-myc/miR-150/EPG5 mediated dysfunction of autophagy contributes to NSCLC development, which may provide a potential new diagnostic and therapeutic target in NSCLC.

In solving the boundary conditions of a hydrostatic motorized spindle, there are some certain errors between the boundary conditions calculated by the traditional empirical formula and the actual conditions. In order to solve this problem, an optimization algorithm based on response surface is proposed in this paper, which is based on the idea of composite experimental design. The mathematical models of air gap heat transfer coefficient between stator and rotor, forced convection heat transfer coefficient of spindle inner hole and temperature are established, which is also called the mathematical model of temperature field. By using ANSYS Workbench simulation analysis software, load the optimized convective heat transfer coefficient into the simulation model to solve the temperature field of the hydrostatic motorized spindle to solve the temperature field of the hydrostatic motorized spindle. After selecting the sensor measuring points for temperature measurement, the results are compared with the simulation results. The results show that: the maximum error between the front bearing simulation temperature measurement point and the experimental temperature point is only 9.41%, and the maximum error between the rear bearing measurement point and the experimental temperature point is 3.09%. And it verifies the effectiveness and reliability of the method to improve the simulation accuracy of the hydrostatic motorized spindle.

Research on cell differentiation facilitates a deeper understanding of the fundamental processes of life, elucidates the intrinsic mechanisms underlying diseases such as cancer, and advances the development of therapeutics and precision medicine. Existing methods for inferring cell differentiation trajectories from single-cell RNA sequencing (scRNA-seq) data primarily rely on static gene expression data to measure distances between cells and subsequently infer pseudotime trajectories. In this work, we introduce a novel method, scGRN-Entropy, for inferring cell differentiation trajectories and pseudotime from scRNA-seq data. Unlike existing approaches, scGRN-Entropy improves inference accuracy by incorporating dynamic changes in gene regulatory networks (GRN). In scGRN-Entropy, an undirected graph representing state transitions between cells is constructed by integrating both static relationships in gene expression space and dynamic relationships in the GRN space. The edges of the undirected graph are then refined using pseudotime inferred based on cell entropy in the GRN space. Finally, the Minimum Spanning Tree (MST) algorithm is applied to derive the cell differentiation trajectory. We validate the accuracy of scGRN-Entropy on eight different real scRNA-seq datasets, demonstrating its superior performance in inferring cell differentiation trajectories through comparative analysis with existing state-of-the-art methods. Author summary: It is very important to study cell differentiation because it can help us understand the fundamental processes of life, elucidates the intrinsic mechanisms underlying diseases such as cancer, and advances the development of therapeutics and precision medicine. However, the existed methods for this usually much more rely on static gene expression data. They ignore the dynamical behavior of it. In this paper, we introduce method named scGRN-Entropy for inferring cell differentiation trajectories and pseudotime from scRNA-seq data. Our method divides cellular differentiation relationships into static and dynamic types. Static relationships are calculated based on gene expression levels, while dynamic relationships are derived from the similarity of cellular GRNs. We obtain the GRN from ordinary differential equations of gene expression, reflecting the internal dynamic regulatory relationships within cells. Incorporating GRNs into trajectory inference considers both biological reality and real datasets, it shows that our method can infer the cell differentiation trajectories much more accurately. [ABSTRACT FROM AUTHOR]

Luteolin is a natural flavonoid, which exists in many plants, including onions, broccoli, carrots, peppers, celery, olive oil, and mint. Luteolin is a dietary flavonoid with potent uric acid‐lowering and antioxidant bioactivities. To date, the mechanism by which luteolin alleviates hyperuricemia nephropathy (HN) still needs to be better defined. This study aims to evaluate the therapeutic efficacy of luteolin in a preclinical mouse model and in vitro. Luteolin was administered in the HN mice induced by the combination of potassium oxonate and hypoxanthine to evaluate the potential renoprotective effects in vivo. The NRK‐52E cells were stimulated with adenosine for in vitro evaluation. Hematoxylin and eosin staining, biochemical analysis, immunoblotting, immunofluorescence, and immunohistochemistry were performed for the histopathologic and mechanistic investigations. The results suggest that luteolin attenuated tubular dilation and epithelial atrophy in the renal tissue of HN mice. Further, luteolin improved biochemical indicators concerning renal functions and oxidative stress in vivo. Mechanistically, luteolin reduced the renal expressions of KIM‐1 and caspase‐3. Luteolin activated renal SIRT1/6 cascade and its downstream Nrf2‐mediated antioxidant pathway. Furthermore, luteolin elevated the renal expressions of ATP‐binding cassette subfamily G isoform 2 protein (ABCG2) and organic anion/cation transporters. In addition, livers of luteolin‐treated HN mice exhibited robust inhibition of xanthine oxidase. Together, our study shows that luteolin alleviates renal injury in the HN mice by activating urate excretion and Nrf2/HO‐1/NQO1 antioxidant pathways and inhibiting liver xanthine oxidase activity. Thus, luteolin may be a potential agent for the treatment of HN. [ABSTRACT FROM AUTHOR]

Genetically identical cell populations growing in the same environment show a large degree of heterogeneity in gene expression profiles, resulting in significant phenotypic consequences. One of the important sources of this heterogeneity is transcriptional bursting. In recent years, single cell transcriptome sequencing (scRNA-seq) data have been widely used to infer the kinetics of transcriptional bursting. Moreover, the increasing evidence showed that genes are jointly regulated by several competitive pathways when activated by external signals, and there is molecular memory in the process of gene state switching. Therefore, a gene expression model considering both gene activation pathway and molecular memory can better reflect the nature of transcriptional bursting. In this paper, we used an approximate Bayesian computation algorithm called ABC-PRC combined with a gene expression model that considered crosstalk and memory, to infer the kinetics of transcriptional bursting. We analyze the internal relationship between transcriptional bursting and gene expression using scRNA-seq data obtained from mouse embryonic stem cells and mouse embryonic fibroblasts. Both model analysis and data simulations demonstrate that the bimodal coefficient increases with the increase of burst size, and the noise intensity decreases with the increase of burst frequency. Additionally, we show that some previously proposed models can be simplified as special cases of the gene expression model and inference algorithm proposed here under certain circumstances. 1. Genome-wide transcriptional bursting kinetics are inferred by approximate Bayesian algorithm ABC-PRC both from scRNA-seq data and gene expression models. 2. This article uses a combination of data-driven and model-driven methods to study the intrinsic relationship between transcriptional bursting and gene expression. 3. The model and inference process used in this article can be simplified and widely applied to the classical telegraph model and the generalized telegraph model. [ABSTRACT FROM AUTHOR]

Cell trajectory inference is very important to understand the details of tissue cell development, state differentiation and gene dynamic regulation. However, due to the high noise and heterogeneity of the single-cell data, it is challenging to infer cell trajectory in complex biological processes. Here, we proposed a new trajectory inference method, called Metric Learning Bhattacharyya Kernel Feature Decomposition (MLBKFD). In MLBKFD, a statistical model was used to infer cell trajectory by calculating the Markov transition matrix and Bhattacharyya kernel matrix between cells. Before that, to expedite the matrix calculation in the statistical model, a deep feedforward neural network was used to perform dimensionality reduction on single-cell data. The MLBKFD was evaluated on four typical datasets as well as seven recent human fetal lung datasets. Comparisons with the two outstanding methods (i.e., DTFLOW and MARGARET) demonstrate that the MLBKFD is capable of accurately inferring cell development and differentiation trajectories from single-cell data with different sizes and sources. Notably, MLBKFD exhibits nearly twice the speed of DTFLOW while maintaining high precision, particularly when dealing with large datasets. MLBKFD provides accurate and efficient trajectory inference, empowering researchers to gain deeper insights into the complex dynamics of cell development and differentiation. 1. MLBKFD is a powerful probabilistic model to effectively infer cell pseudo trajectories from single-cell data by calculating the Markov transition matrix and Bhattacharyya kernel matrix between cells. 2. MLBKFD exhibits fast speed and excellent visualization effects on cell trajectory inference, by utilizing a deep feedforward neural networks for dimensionality reduction of single-cell data. 3. By iteratively refining cell labels in the deep neural networks, MLBKFD can achieve excellent cell clustering results, enabling it to infer cell trajectories without relying on true cell labels. [ABSTRACT FROM AUTHOR]

To increase the hit efficiency and lethality of a flight vehicle, it is necessary to consider the vehicle's guidance law concerning both impact time and angle constraints. In this study, a novel and straightforward impact time and angle control guidance law that is independent of time-to-go and small angle approximations is proposed with two stages using a data-driven method and proportional navigation guidance. First, a proportional navigation guidance-based impact angle control guidance law is designed for the second stage. Second, from various initial conditions on the impact angle control guidance simulation with various initial conditions, the input and output datasets are obtained to build a mapping network. Using the neural network technique, a mapping network model that can output the ideal flight path angle in flight is constructed for impact time control in the first stage. The proposed impact time and angle control guidance law reduces to the proportional navigation guidance law when the flight path angle error converges to zero. The simulation results show that the proposed guidance law delivers excellent performance under various conditions (including cooperative attack) and features better acceleration performance and less control energy than does the comparative impact time and angle control guidance law. The results of this research are expected to supplement those exploring various paradigms to solve the impact time and angle control guidance problem, as concluded in the current literature. [ABSTRACT FROM AUTHOR]

AIM: To investigate the effects of sodium hydrosulfide (NaHS) on hexokinase 2 (HK2)-nucleo-tide-binding oligomerization domain-like receptor protein 3 (NLRP3)-gasdermin D (GSDMD) pathway and pyroptosis induced by lung ischemia/reperfusion (I/R) in rats. METHODS: Male Sprague-Dawley rats were divided into 6 groups: control group, control+NaHS group, I/R group, low-dose NaHS+I/R (L+I/R) group, medium-dose NaHS+I/R (M+I/R) group, and high-dose NaHS+I/R (H+I/R) group, with 6 rats in each group. The NaHS was administered via intraperitoneal injection at 1.5 mL, 30 min before modeling. The left lung tissues were collected 30 min after ischemia and 1 h after reperfusion, and the wet/dry weight ratio and total lung water content were recorded. Hematoxylin-eosin (HE) staining was used to examine lung tissue morphological changes. The levels of malondialdehyde (MDA), myeloper oxidase (MPO) and lactate in lung tissues were measured with test kits. ELISA was employed to determine the levels of interleukin-1p (IL-1p) and IL-18. The expression of glycolysis- and pyroptosis-related indicators was analyzed by Western blot, qRT-PCR and immunofluorescence staining. RESULTS: Compared with control group, the rats in NaHS group showed no significant differences in all laboratory tests (P>0. 05). The rats in I/R group exhibited significant lung injury, oxidative stress, increased lactate level, and up-regulated glycolysis and pyroptosis (P<0. 05 or P<0. 01). Compared with I/R group, the indicators in L+I/R group showed a downward trend (P<0. 01) or no difference (P>0. 05), while those in M+I/R group displayed a significant reduction (P<0. 05 or P<0. 01). However, the indexes in H+I/R group exhibited no significant differences in these tests (all P>0. 05). CONCLUSION: A moderate dose (56 xmol"L-1-kg-1) of NaHS mitigated the occurrence of pyroptosis by inhibiting the HK2-NLRP3-GSDMD pathway, thus contributing to the attenuation of lung I/R injury in rats. [ABSTRACT FROM AUTHOR]