Investigation of HIV-1 Gag binding with RNAs and Lipids using Atomic Force Microscopy

Atomic Force Microscopy was utilized to study the morphology of Gag, {\Psi}RNA, and their binding complexes with lipids in a solution environment with 0.1{\AA} vertical and 1nm lateral resolution. TARpolyA RNA was used as a RNA control. The lipid used was phospha-tidylinositol-(4,5)-bisphosphate (PI(4,5)P2). The morphology of specific complexes Gag-{\Psi}RNA, Gag-TARpolyA RNA, Gag-PI(4,5)P2 and PI(4,5)P2-{\Psi}RNA-Gag were studied. They were imaged on either positively or negatively charged mica substrates depending on the net charges carried. Gag and its complexes consist of monomers, dimers and tetramers, which was confirmed by gel electrophoresis. The addition of specific {\Psi}RNA to Gag is found to increase Gag multimerization. Non-specific TARpolyA RNA was found not to lead to an increase in Gag multimerization. The addition PI(4,5)P2 to Gag increases Gag multimerization, but to a lesser extent than {\Psi}RNA. When both {\Psi}RNA and PI(4,5)P2 are present Gag undergoes comformational changes and an even higher degree of multimerization

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Identification of Circular RNA-MicroRNA-Messenger RNA Regulatory Network in Atrial Fibrillation by Integrated Analysis

Background. Circular RNA (circRNA) is a noncoding RNA that forms a closed-loop structure, and its abnormal expression may cause disease. We aimed to find potential network for circRNA-related competitive endogenous RNA (ceRNA) in atrial fibrillation (AF). Methods. The circRNA, miRNA, and mRNA expression profiles in the heart tissue from AF patients were retrieved from the Gene Expression Omnibus database and analyzed comprehensively. Differentially expressed circRNAs (DEcircRNAs), differentially expressed miRNAs (DEmiRNAs), and differentially expressed mRNAs (DEmRNAs) were identified, followed by the establishment of DEcircRNA-DEmiRNA-DEmRNA regulatory network. Functional annotation analysis of host gene of DEcircRNAs and DEmRNAs in ceRNA regulatory network was performed. In vitro experiment and electronic validation were used to validate the expression of DEcircRNAs, DEmiRNAs, and DEmRNAs. Results. A total of 1611 DEcircRNAs, 51 DEmiRNAs, and 1250 DEmRNAs were identified in AF. The DEcircRNA-DEmiRNA-DEmRNA network contained 62 circRNAs, 14 miRNAs, and 728 mRNAs. Among which, two ceRNA regulatory pairs of hsa-circRNA-100053-hsa-miR-455-5p-TRPV1 and hsa-circRNA-005843-hsa-miR-188-5p-SPON1 were identified. In addition, six miRNA-mRNA regulatory pairs including hsa-miR-34c-5p-INMT, hsa-miR-1253-DDIT4L, hsa-miR-508-5p-SMOC2, hsa-miR-943-ACTA1, hsa-miR-338-3p-WIPI1, and hsa-miR-199a-3p-RAP1GAP2 were also obtained. MTOR was a significantly enriched signaling pathway of host gene of DEcircRNAs. In addition, arrhythmogenic right ventricular cardiomyopathy, dilated cardiomyopathy, and hypertrophic cardiomyopathy were remarkably enriched signaling pathways of DEmRNAs in DEcircRNA-DEmiRNA-DEmRNA regulatory network. The expression validation of hsa-circRNA-402565, hsa-miR-34c-5p, hsa-miR-188-5p, SPON1, DDIT4L, SMOC2, and WIPI1 was consistent with the integrated analysis. Conclusion. We speculated that hsa-circRNA-100053-hsa-miR-455-5p-TRPV1 and hsa-circRNA-005843-hsa-miR-188-5p-SPON1 interaction pairs may be involved in AF

Left ventricular function during acute high-altitude exposure in a large group of healthy young Chinese men.

OBJECTIVE:The purpose of this study was to observe left ventricular function during acute high-altitude exposure in a large group of healthy young males. METHODS:A prospective trial was conducted in Szechwan and Tibet from June to August, 2012. By Doppler echocardiography, left ventricular function was examined in 139 healthy young Chinese men at sea level; within 24 hours after arrival in Lhasa, Tibet, at 3700 m; and on day 7 following an ascent to Yangbajing at 4400 m after 7 days of acclimatization at 3700 m. The resting oxygen saturation (SaO2), heart rate (HR) and blood pressure (BP) were also measured at the above mentioned three time points. RESULTS:Within 24 hours of arrival at 3700 m, the HR, ejection fraction (EF), fractional shortening (FS), stroke volume (SV), cardiac output (CO), and left ventricular (LV) Tei index were significantly increased, but the LV end-systolic dimension (ESD), end-systolic volume (ESV), SaO2, E/A ratio, and ejection time (ET) were significantly decreased compared to the baseline levels in all subjects. On day 7 at 4400 m, the SV and CO were significantly decreased; the EF and FS Tei were not decreased compared with the values at 3700 m; the HR was further elevated; and the SaO2, ESV, ESD, and ET were further reduced. Additionally, the E/A ratio was significantly increased on day 7 but was still lower than it was at low altitude. CONCLUSION:Upon acute high-altitude exposure, left ventricular systolic function was elevated with increased stroke volume, but diastolic function was decreased in healthy young males. With higher altitude exposure and prolonged acclimatization, the left ventricular systolic function was preserved with reduced stroke volume and improved diastolic function

LogD7.4 prediction enhanced by transferring knowledge from chromatographic retention time, microscopic pKa and logP

Abstract Lipophilicity is a fundamental physical property that significantly affects various aspects of drug behavior, including solubility, permeability, metabolism, distribution, protein binding, and toxicity. Accurate prediction of lipophilicity, measured by the logD7.4 value (the distribution coefficient between n-octanol and buffer at physiological pH 7.4), is crucial for successful drug discovery and design. However, the limited availability of data for logD modeling poses a significant challenge to achieving satisfactory generalization capability. To address this challenge, we have developed a novel logD7.4 prediction model called RTlogD, which leverages knowledge from multiple sources. RTlogD combines pre-training on a chromatographic retention time (RT) dataset since the RT is influenced by lipophilicity. Additionally, microscopic pKa values are incorporated as atomic features, providing valuable insights into ionizable sites and ionization capacity. Furthermore, logP is integrated as an auxiliary task within a multitask learning framework. We conducted ablation studies and presented a detailed analysis, showcasing the effectiveness and interpretability of RT, pKa, and logP in the RTlogD model. Notably, our RTlogD model demonstrated superior performance compared to commonly used algorithms and prediction tools. These results underscore the potential of the RTlogD model to improve the accuracy and generalization of logD prediction in drug discovery and design. In summary, the RTlogD model addresses the challenge of limited data availability in logD modeling by leveraging knowledge from RT, microscopic pKa, and logP. Incorporating these factors enhances the predictive capabilities of our model, and it holds promise for real-world applications in drug discovery and design scenarios. Graphical Abstrac

Altitude ascent profile of participants from plain to plateau.

<p>All subjects ascended to 3700 m (Lhasa in Tibet) in 2.5 hours by plane from 500 m (Chengdu in Sichuan province). After they acclimatized at 3700 m for a week, the subjects traveled by motorcar and arrived in Yangbajing (in Tibet, at 4400 m) within 3 hours; they in Yangbajing for 7 days. For all participants, the starting data collection point was in Chengdu (500 m), the second data collection point was in Lhasa (3700 m) within 24 h of arrival, and the third data collection was on the 7^th day in Yangbajing (4400 m).</p

Left ventricular size and function at low and high altitude.

<p>Normally distributed data are presented as the means ± standard deviations.</p><p>**P<0.01, compared with 500 m;</p><p>^†P < 0.05,</p><p>^‡P < 0.01, compared with 3700 m. EDD, end-diastolic dimension; ESD, end-systolic dimension; EDV, end-diastolic volume; ESV, end-systolic volume; EF, ejection fraction; FS, fractional shortening; SV, stroke volume; SVI, stroke volume index; CO, cardiac output; and CI, cardiac index.</p><p>Left ventricular size and function at low and high altitude.</p

Physiologic parameters at low and high altitude.

<p>Normally distributed data are presented as the means ± standard deviations.</p><p>*P<0.05,</p><p>**P<0.01, compared with 500 m;</p><p>^†P < 0.05,</p><p>^‡P < 0.01, compared with 3700 m. SaO₂, oxygen saturation; HR, heart rate; SBP, systolic blood pressure; DBP, diastolic blood pressure; MAP, mean arterial pressure.</p><p>Physiologic parameters at low and high altitude.</p

Illustration of a pulsed Doppler diagram showing the measurement of each parameter for calculating the Tei index.

<p>a = isovolumetric contraction time (ICT) + ejection time (ET) + isovolumetric relaxation time (IRT); b = ET. Tei index = (ICT+IRT)/ET = (a-b)/b.</p