Integrated gene co-expression network analysis and experimental validation revealed potential targets of human urine extract CDA-II in treating chronic myeloid leukemia.

BACKGROUND: Cell differentiation agent II (CDA-II) exhibits potent anti-proliferative and apoptosis-inducing properties against a variety of cancer cells. However, its mechanism of action in chronic myeloid leukemia (CML) remains unclear. METHODS: Cell counting Kit 8 (CCK-8) and flow cytometry were used to investigate the effects of CDA-II on the biological characteristics of K562 cells. Gene (mRNA and lncRNA) expression profiles were analyzed by bioinformatics to screen differentially expressed genes and to perform enrichment analysis. The Pearson correlation coefficients of lncRNAs and mRNAs were calculated using gene expression values, and a lncRNA/mRNA co-expression network was constructed. The MCODE and cytoHubba plugins were used to analyze the co-expression network. RESULTS: The Results, derived from CCK-8 and flow cytometry, indicated that CDA-II exerts dual effects on K562 cells: it inhibits their proliferation and induces apoptosis. From bioinformatics analysis, we identified 316 mRNAs and 32 lncRNAs. These mRNAs were predominantly related to the meiotic cell cycle, DNA methylation, transporter complex and peptidase regulator activity, complement and coagulation cascades, protein digestion and absorption, and cell adhesion molecule signaling pathways. The co-expression network comprised of 163 lncRNA/mRNA interaction pairs. Notably, our analysis results implicated clustered histone gene families and five lncRNAs in the biological effects of CDA-II on K562 cells. CONCLUSION: This study highlights the hub gene and lncRNA/mRNA co-expression network as crucial elements in the context of CDA-II treatment of CML. This insight not only enriches our understanding of CDA-II's mechanism of action but also might provide valuable clues for subsequent experimental studies of CDA-II, and potentially contribute to the discovery of new therapeutic targets for CML.

Visual analysis of the research literature on extracorporeal membrane oxygenation-assisted support for respiratory failure based on CiteSpace and VOSviewer: a 20-year study.

Background: This study aims to visually assess the bibliometric status, current hotspots, and development trends in the field of extracorporeal membrane oxygenation (ECMO)-assisted support for respiratory failure through an examination of articles pertaining to ECMO-assisted support for respiratory failure. Methods: A search was conducted on pertinent literature in the domain of ECMO-assisted support for respiratory failure published from 2003 to 2023, utilizing the Web of Science Core Collection (WOSCC) database. A bibliometric analysis was conducted using CiteSpace and VOSviewer visualization software to identify and assess associations between keywords, countries, institutions, authors, journals, and references. Results: The present study incorporated a compilation of 1,901 pertinent articles. The United States published the maximum number of research articles in this field, and was closely followed by Germany and China. Furthermore, the University of Michigan was the leading institution in ECMO research. In this context, Daniel Brodie, an American expert, significantly contributed to this field and had published 107 related articles on the subject. Concurrently, active collaboration among ECMO researchers was also observed. Asaio Journal was the most prolific contributor, and Giles J. Peek, 2009, published in Lancet, comprised the most cited article in the field. Additionally, the analysis of keywords could be divided into three categories: (I) neonatal ECMO; (II) complications of ECMO; (III) ECMO application in coronavirus disease 2019 (COVID-19); (IV) application of point-of-care ultra sound in ECMO. Conclusions: This study employed CiteSpace and VOSviewer to conduct a systematic literature review on ECMO-assisted support for respiratory failure from 2003 to 2023 in the Web of Science core database. The research outcomes in this domain were presented, offering researchers references for them to gain an accurate understanding of the current state of research and emerging trends in this field.

Numerical Study of the Time-Periodic Electroosmotic Flow of Viscoelastic Fluid through a Short Constriction Microchannel.

Electroosmotic flow (EOF) is of utmost significance due to its numerous practical uses in controlling flow at micro/nanoscales. In the present study, the time-periodic EOF of a viscoelastic fluid is statistically analyzed using a short 10:1 constriction microfluidic channel joining two reservoirs on either side. The flow is modeled using the Oldroyd-B (OB) model and the Poisson-Boltzmann model. The EOF of a highly concentrated polyacrylamide (PAA) aqueous solution is investigated under the combined effects of an alternating current (AC) electric field and a direct current (DC) electric field. Power-law degradation is visible in the energy spectra of the velocity fluctuations over a wide frequency range, pointing to the presence of elastic instabilities in the EOF. The energy-spectra curves of the velocity fluctuations under a DC electric field exhibit peaks primarily beneath 20 Hz, with the greatest peak being observed close to 6 Hz. When under both DC and AC electric fields, the energy spectra of the velocity fluctuations exhibit a peak at the same frequency as the AC electric field, and the highest peak is obtained when the frequency of the AC electric field is near 6 Hz. Additionally, the frequency of the AC electric field affects how quickly the viscoelastic EOF flows. Higher flow rates are obtained at relatively low frequencies compared to under the DC electric field, and the greatest flow rate is found close to 6 Hz. But as the frequency rises further, the flow rate falls. The flow rate falls to a level below the DC electric field when the frequency is sufficiently high.

Diagnosis of leptospira by metagenomics next-generation sequencing with extracorporeal membrane oxygenation support: a case report.

BACKGROUND: Leptospirosis is an infectious disease caused by pathogenic Leptospira spp., which could result in severe illnesses. Indirect contact with these pathogens is more common. Individuals could contract this disease through contact with contaminated water or during floods. In this case, we present the details of a 40-year-old male pig farmer who suffered from severe pulmonary hemorrhagic leptospirosis and multiple organ failure. The diagnosis of leptospirosis was confirmed through metagenomics next-generation sequencing (mNGS) while the patient received extracorporeal membrane oxygenation (ECMO) support, and antibiotic treatment was adjusted accordingly. The patient underwent comprehensive treatment and rehabilitation in the intensive care unit. CONCLUSION: This case illustrates the importance of early diagnosis and treatment of leptospirosis. While obtaining the epidemiological history, second-generation metagenomics sequencing was utilized to confirm the etiology. The prompt initiation of ECMO therapy provided a crucial window of opportunity for addressing the underlying cause. This case report offers valuable insights for diagnosing patients with similar symptoms.

Electroosmotic Flow of Viscoelastic Fluid through a Constriction Microchannel.

Electroosmotic flow (EOF) has been widely used in various biochemical microfluidic applications, many of which use viscoelastic non-Newtonian fluid. This study numerically investigates the EOF of viscoelastic fluid through a 10:1 constriction microfluidic channel connecting two reservoirs on either side. The flow is modelled by the Oldroyd-B (OB) model coupled with the Poisson-Boltzmann model. EOF of polyacrylamide (PAA) solution is studied as a function of the PAA concentration and the applied electric field. In contrast to steady EOF of Newtonian fluid, the EOF of PAA solution becomes unstable when the applied electric field (PAA concentration) exceeds a critical value for a fixed PAA concentration (electric field), and vortices form at the upstream of the constriction. EOF velocity of viscoelastic fluid becomes spatially and temporally dependent, and the velocity at the exit of the constriction microchannel is much higher than that at its entrance, which is in qualitative agreement with experimental observation from the literature. Under the same apparent viscosity, the time-averaged velocity of the viscoelastic fluid is lower than that of the Newtonian fluid.

Multi-Vehicle Cooperative Target Tracking with Time-Varying Localization Uncertainty via Recursive Variational Bayesian Inference.

Cooperative target tracking by multiple vehicles connected through inter-vehicle communication is a promising way to improve the estimation of target state. The effectiveness of cooperative tracking closely depends on the accuracy of relative localization between host and cooperative vehicles. However, the localization signal usually provided by the satellite-based navigation system is rather susceptible to dynamic driving environment, thus influencing the effectiveness of cooperative tracking. In order to implement reliable cooperative tracking, especially when the statistical characteristic of the relative localization noise is time-varying and uncertain, this paper presents a recursive Bayesian framework which jointly estimates the state of the target and the cooperative vehicle as well as the localization noise parameter. An online variational Bayesian inference algorithm is further developed to achieve efficient recursive estimate. The simulation results verify that our proposed algorithm can effectively boost the accuracy of target tracking when the localization noise dynamically changes over time.

Robust Cooperative Multi-Vehicle Tracking with Inaccurate Self-Localization Based on On-Board Sensors and Inter-Vehicle Communication.

The fusion of on-board sensors and transmitted information via inter-vehicle communication has been proved to be an effective way to increase the perception accuracy and extend the perception range of connected intelligent vehicles. The current approaches rely heavily on the accurate self-localization of both host and cooperative vehicles. However, such information is not always available or accurate enough for effective cooperative sensing. In this paper, we propose a robust cooperative multi-vehicle tracking framework suitable for the situation where the self-localization information is inaccurate. Our framework consists of three stages. First, each vehicle perceives its surrounding environment based on the on-board sensors and exchanges the local tracks through inter-vehicle communication. Then, an algorithm based on Bayes inference is developed to match the tracks from host and cooperative vehicles and simultaneously optimize the relative pose. Finally, the tracks associated with the same target are fused by fast covariance intersection based on information theory. The simulation results based on both synthesized data and a high-quality physics-based platform show that our approach successfully implements cooperative tracking without the assistance of accurate self-localization.