Drug repositioning for SARS-CoV-2 by Gaussian kernel similarity bilinear matrix factorization

Coronavirus disease 2019 (COVID-19), a disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is currently spreading rapidly around the world. Since SARS-CoV-2 seriously threatens human life and health as well as the development of the world economy, it is very urgent to identify effective drugs against this virus. However, traditional methods to develop new drugs are costly and time-consuming, which makes drug repositioning a promising exploration direction for this purpose. In this study, we collected known antiviral drugs to form five virus-drug association datasets, and then explored drug repositioning for SARS-CoV-2 by Gaussian kernel similarity bilinear matrix factorization (VDA-GKSBMF). By the 5-fold cross-validation, we found that VDA-GKSBMF has an area under curve (AUC) value of 0.8851, 0.8594, 0.8807, 0.8824, and 0.8804, respectively, on the five datasets, which are higher than those of other state-of-art algorithms in four datasets. Based on known virus-drug association data, we used VDA-GKSBMF to prioritize the top-k candidate antiviral drugs that are most likely to be effective against SARS-CoV-2. We confirmed that the top-10 drugs can be molecularly docked with virus spikes protein/human ACE2 by AutoDock on five datasets. Among them, four antiviral drugs ribavirin, remdesivir, oseltamivir, and zidovudine have been under clinical trials or supported in recent literatures. The results suggest that VDA-GKSBMF is an effective algorithm for identifying potential antiviral drugs against SARS-CoV-2

DECtp: Calling Differential Gene Expression Between Cancer and Normal Samples by Integrating Tumor Purity Information

Identifying differentially expressed genes (DEGs) between tumor and normal samples is critical for studying tumorigenesis, and has been routinely applied to identify diagnostic, prognostic, and therapeutic biomarkers for many cancers. It is well-known that solid tumor tissue samples obtained from clinical settings are always mixtures of cancer and normal cells. However, the tumor purity information is more or less ignored in traditional differential expression analyses, which might decrease the power of differential gene identification or even bias the results. In this paper, we have developed a novel differential gene calling method called DECtp by integrating tumor purity information into a generalized least square procedure, followed by the Wald test. We compared DECtp with popular methods like t-test and limma on nine simulation datasets with different sample sizes and noise levels. DECtp achieved the highest area under curves (AUCs) for all the comparisons, suggesting that cancer purity information is critical for DEG calling between tumor and normal samples. In addition, we applied DECtp into cancer and normal samples of 14 tumor types collected from The Cancer Genome Atlas (TCGA) and compared the DEGs with those called by limma. As a result, DECtp achieved more sensitive, consistent, and biologically meaningful results and identified a few novel DEGs for further experimental validation

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γδ T cells have been recognized as effectors with immunomodulatory functions in cellular immunity. These abilities enable them to interact with other immune cells, thus having the potential for treatment of various immune-mediated diseases with adoptive cell therapy. So far, the interactions between γδ T cell and other immune cells have not been well defined. Here we will discuss the interactivities among them and the perspective on γδ T cells for their use in immunotherapy could be imagined. The understanding of the crosstalk among the immune cells in immunopathology might be beneficial for the clinical application of γδ T cell

A novel approach for denoising electrocardiogram signals to detect cardiovascular diseases using an efficient hybrid scheme

BackgroundElectrocardiogram (ECG) signals are inevitably contaminated with various kinds of noises during acquisition and transmission. The presence of noises may produce the inappropriate information on cardiac health, thereby preventing specialists from making correct analysis.MethodsIn this paper, an efficient strategy is proposed to denoise ECG signals, which employs a time-frequency framework based on S-transform (ST) and combines bi-dimensional empirical mode decomposition (BEMD) and non-local means (NLM). In the method, the ST maps an ECG signal into a subspace in the time frequency domain, then the BEMD decomposes the ST-based time-frequency representation (TFR) into a series of sub-TFRs at different scales, finally the NLM removes noise and restores ECG signal characteristics based on structural self-similarity.ResultsThe proposed method is validated using numerous ECG signals from the MIT-BIH arrhythmia database, and several different types of noises with varying signal-to-noise (SNR) are taken into account. The experimental results show that the proposed technique is superior to the existing wavelet based approach and NLM filtering, with the higher SNR and structure similarity index measure (SSIM), the lower root mean squared error (RMSE) and percent root mean square difference (PRD).ConclusionsThe proposed method not only significantly suppresses the noise presented in ECG signals, but also preserves the characteristics of ECG signals better, thus, it is more suitable for ECG signals processing

Surficial geologic map of the Des Moines Lobe of Iowa, Phase 5: Polk County

https://ir.uiowa.edu/igs_ofm/1030/thumbnail.jp

Thermal ablation as an alternative to liver transplantation for hepatocellular carcinoma with clinically significant portal hypertension: propensity score matching study

PurposeThe objectives were to investigate the safety and efficacy of thermal ablation as an alternative to liver transplantation for hepatocellular carcinoma patients with clinically significant portal hypertension (CSPH).Materials and MethodsFrom July 2016 to September 2019, hepatocellular carcinoma patients with CSPH treated by liver transplantation (N=37) or thermal ablation (N=114) were enrolled. Cumulative intrahepatic recurrence, overall survival and major complications were compared by propensity score matching.ResultsIn the two matched groups, the 1-, 2-, and 3-year intrahepatic recurrence rates for the ablation group (22.3%, 50.0%, and 50.0%, respectively) were significantly higher than those for the transplantation group (4.5%, 4.5%, and 4.5%, respectively) (P=0.016). The 1-, 2-, and 3-year overall survival rates were comparable between the two groups [96.1%, 88.7%, and 88.7%, respectively (ablation group) vs. 84.6%, 76.2%, and 76.2%, respectively (transplantation group)] (P=0.07). The major complication rate for the ablation group [4.8% (3/62)] was significantly lower than that for the transplantation group [36.0% (9/25)] (P<0.001).ConclusionsThermal ablation is a safe and effective alternative for hepatocellular carcinoma patients with CSPH

Enhancing bioavailability of natural extracts for nutritional applications through dry powder inhalers (DPI) spray drying: technological advancements and future directions

Natural ingredients have many applications in modern medicine and pharmaceutical projects. However, they often have low solubility, poor chemical stability, and low bioavailability in vivo. Spray drying technology can overcome these challenges by enhancing the properties of natural ingredients. Moreover, drug delivery systems can be flexibly designed to optimize the performance of natural ingredients. Among the various drug delivery systems, dry powder inhalation (DPI) has attracted much attention in pharmaceutical research. Therefore, this review will focus on the spray drying of natural ingredients for DPI and discuss their synthesis and application

Cryopreservation of bioflavonoid-rich plant sources and bioflavonoid-microcapsules: emerging technologies for preserving bioactivity and enhancing nutraceutical applications

Bioflavonoids are natural polyphenolic secondary metabolites that are medicinal. These compounds possess antitumor, cardioprotective, anti-inflammatory, antimicrobial, antiviral, and anti-psoriasis properties to mention a few. Plant species that contain bioflavonoids should be preserved as such. Also, the bioactivity of the bioflavonoids as neutraceutical compounds is compromised following extraction due to their sensitivity to environmental factors like light, pH, and temperature. In other words, the bioflavonoids’ shelf-life is affected. Scientists noticed that bioflavonoids have low solubility properties, poor absorption, and low bioavailability following consumption. Researchers came up with methods to encapsulate bioflavonoids in order to circumvent the challenges above and also to mask the unpleasant order these chemicals may have. Besides, scientists cryopreserve plant species that contain bioflavonoids. In this review, we discuss cryopreservation and bioflavonoid microencapsulation focusing mainly on vitrification, slow freezing, and freeze-drying microencapsulation techniques. In addition, we highlight bioflavonoid extraction techniques, medicinal properties, challenges, and future perspectives of cryopreservation and microencapsulation of bioflavonoids. Regardless of the uniqueness of cryopreservation and microencapsulation as methods to preserve bioflavonoid sources and bioflavonoids’ bioactivity, there are challenges reported. Freeze-drying technology is costly. Cryoprotectants damage the integrity of plant cells, to say the least. Researchers are working very hard to overcome these challenges. Encapsulating bioflavonoids via coaxial electrospray and then cryopreserving the micro/nanocapsules produced can be very interesting

Unveiling the causal link between metabolic factors and ovarian cancer risk using Mendelian randomization analysis

BackgroundMetabolic abnormalities are closely tied to the development of ovarian cancer (OC), yet the relationship between anthropometric indicators as risk indicators for metabolic abnormalities and OC lacks consistency.MethodThe Mendelian randomization (MR) approach is a widely used methodology for determining causal relationships. Our study employed summary statistics from the genome-wide association studies (GWAS), and we used inverse variance weighting (IVW) together with MR-Egger and weighted median (WM) supplementary analyses to assess causal relationships between exposure and outcome. Furthermore, additional sensitivity studies, such as leave-one-out analyses and MR-PRESSO were used to assess the stability of the associations.ResultThe IVW findings demonstrated a causal associations between 10 metabolic factors and an increased risk of OC. Including “Basal metabolic rate” (OR= 1.24, P= 6.86×10-4); “Body fat percentage” (OR= 1.22, P= 8.20×10-3); “Hip circumference” (OR= 1.20, P= 5.92×10-4); “Trunk fat mass” (OR= 1.15, P= 1.03×10-2); “Trunk fat percentage” (OR= 1.25, P= 8.55×10-4); “Waist circumference” (OR= 1.23, P= 3.28×10-3); “Weight” (OR= 1.21, P= 9.82×10-4); “Whole body fat mass” (OR= 1.21, P= 4.90×10-4); “Whole body fat-free mass” (OR= 1.19, P= 4.11×10-3) and “Whole body water mass” (OR= 1.21, P= 1.85×10-3).ConclusionSeveral metabolic markers linked to altered fat accumulation and distribution are significantly associated with an increased risk of OC

Raindrop Size Distribution Retrieval Using Joint Dual-Frequency and Dual-Polarization Microwave Links

Estimation of raindrop size distribution (DSD) is essential in many meteorological and hydrologic fields. This paper proposes a method for retrieving path-averaged DSD parameters using joint dual-frequency and dual-polarization microwave links of the telecommunication system. Detailed analyses of the rain-induced attenuation calculation are performed based on the T-matrix method. A forward model is established for describing the relation between the DSD and the rain-induced attenuation. Then, the method is proposed to retrieve propagation path DSD parameters based on Levenberg–Marquardt optimization algorithm. The numerical simulation for path-averaged DSD retrieval shows that the RMSEs of three gamma DSD parameters are 0.34 mm−1, 0.81, and 3.21×103 m−3·mm−1, respectively, in rainfall intensity above 30 mm/h. Meanwhile, the method can retrieve the rainfall intensity without the influence of variational DSD. Theoretical analyses and numerical simulations confirm that the method for retrieving path-averaged DSD parameters is promising. The method can complement existing DSD monitoring systems such as the disdrometer and provide high-resolution rainfall measurements with widely distributed microwave links without additional cost