K2-79b and K2-222b: Mass Measurements of Two Small Exoplanets with Periods beyond 10 days that Overlap with Periodic Magnetic Activity Signals

We present mass and radius measurements of K2-79b and K2-222b, two transiting exoplanets orbiting active G-type stars observed with HARPS-N and K2. Their respective 10.99 day and 15.39 day orbital periods fall near periods of signals induced by stellar magnetic activity. The two signals might therefore interfere and lead to an inaccurate estimate of exoplanet mass. We present a method to mitigate these effects when radial velocity (RV) and activity-indicator observations are available over multiple observing seasons and the orbital period of the exoplanet is known. We perform correlation and periodogram analyses on subsets composed of each target's two observing seasons, in addition to the full data sets. For both targets, these analyses reveal an optimal season with little to no interference at the orbital period of the known exoplanet. We make a confident mass detection of each exoplanet by confirming agreement between fits to the full RV set and the optimal season. For K2-79b, we measure a mass of 11.8 ± 3.6 M ⊕ and a radius of 4.09 ± 0.17 R ⊕. For K2-222b, we measure a mass of 8.0 ± 1.8 M ⊕ and a radius of 2.35 ± 0.08 R ⊕. According to model predictions, K2-79b is a highly irradiated Uranus analog and K2-222b hosts significant amounts of water ice. We also present a RV solution for a candidate second companion orbiting K2-222 at 147.5 days.

Intracardiac Mass Detection and Classification Using Double Convolutional Neural Network Classifier

Intracardiac masses identification in the images of echocardiogram images in one of the most essential tasks in making the diagnosis of cardiac disease. For making the improvement in accuracy over the diagnosis as a new complete method of classifying the echocardiogram images automatically which is based on robust back propagation neural network algorithm in being proposed for distinguishing intracardiac thrombi and tumor. Initially, the cropping over the specific region is done in order to make the definition of the mass area. Later on, as the second step the processing of globally unique denoising technique is being implied for the removal of speckle and in order to make the preservation of anatomical structured component in the image. This is defined in terms of preprocessing and it is carried out by Patch-based sparse representation. Subsequently the description of the mass contour and its interconnected wall of the artery are being done by the segmentation mechanism denoted as Linear Iterative Vessel Segmentation model. As the prefinal stage, the processing of boundary, texture and the motion features are being carried out through the processing by double convolutional neural network (DCNN) classifier in order to determine the classification of two different masses. Totally 108 cardiac masses images are being collected for accessing the effectiveness of the classifier. It is also realized with the various state of the art classifiers as projected the demonstration of the greatest performance that has been disclosed with an achievement of 98.98% of accuracy, 98.89% of sensitivity and 99.16% of specificity that has been resulted for DCNN classifier. It determines the explication that the proposed method is capable of performing the classification of intracardiac thrombi and tumors in the echocardiography and ensures for potentially assisting the medical doctors who are in the clinical practice.

Supervised Statistical Learning Prediction of Soybean Varieties and Cultivation Sites Using Rapid UPLC-MS Separation, Method Validation, and Targeted Metabolomic Analysis of 31 Phenolic Compounds in the Leaves

Soybean (Glycine max; SB) leaf (SL) is an abundant non-conventional edible resource that possesses value-adding bioactive compounds. We predicted the attributes of SB based on the metabolomes of an SL using targeted metabolomics. The SB was planted in two cities, and SLs were regularly obtained from the SB plant. Nine flavonol glycosides were purified from SLs, and a validated simultaneous quantification method was used to establish rapid separation by ultrahigh-performance liquid chromatography-mass detection. Changes in 31 targeted compounds were monitored, and the compounds were discriminated by various supervised machine learning (ML) models. Isoflavones, quercetin derivatives, and flavonol derivatives were discriminators for cultivation days, varieties, and cultivation sites, respectively, using the combined criteria of supervised ML models. The neural model exhibited higher prediction power of the factors with high fitness and low misclassification rates while other models showed lower. We propose that a set of phytochemicals of SL is a useful predictor for discriminating characteristics of edible plants.

Anti-Fatigue Peptides from the Enzymatic Hydrolysates of Cervus elaphus Blood

Red deer (Cervus elaphus) blood is widely used as a health product. Mixed culture fermentation improves the flavor and bioavailability of deer blood (DB), and both DB and its enzymatic hydrolysates exhibit anti-fatigue activities in vivo. To elucidate the bioactive ingredients, enzymatic hydrolysates were fractioned into different peptide groups using reversed phase resin chromatography, and then evaluated using an exhaustive swimming mice model to assess swimming time and biochemical parameters. The structures of the bioactive peptides were elucidated by high performance liquid chromatography with tandem mass detection. Thirty-one compounds were identified as glutamine or branched-chain amino acids containing short peptides, of which Val-Ala-Asn, Val-Val-Ser-Ala, Leu(Ile)-Leu(Ile)-Val-Thr, Pro-His-Pro-Thr-Thr, Glu-Val-Ala-Phe and Val-Leu(Ile)-Asp-Ala-Phe are new peptides. The fractions containing glutamine or valine short peptides, Ala-Gln, Val-Gln, Val-Val-Ser-Ala, Val-Leu(Ile)-Ser improved exercise endurance by increasing hepatic glycogen (HG) storage. The peptides group containing Leu(Ile)-Leu(Ile), Asp-Gln, Phe- Leu(Ile), Val-Val-Tyr-Pro contributed to decreased muscle lactic acid (MLA)accumulation and to an increase in HG. The anti-fatigue activities of DB hydrolysates were attributed to the synergistic effects of different types of peptides.

Development of a Method for the Measurement of Human Scent Samples Using Comprehensive Two-Dimensional Gas Chromatography with Mass Detection

Every human body is a source of a unique scent, which can be used for medical or forensic purposes. Human skin scent is a complex mixture of more or less volatile compounds with different chemical and physical properties, which often differ significantly in their concentrations. The most efficient technique for separating such complex samples is comprehensive two-dimensional gas chromatography (GC × GC). This work aimed to find the optimal arrangement of a two-dimensional chromatographic system and define a suitable chromatographic method for non-targeted analysis of human scent samples. Four different chromatographic columns (non-polar Rxi-5MS and TG-5HT, medium polar Rxi-17Sil MS and Rtx-200MS) and their different configurations were tested. The best system was the 30 m primary column Rtx-200MS (with the 2 m pre-column Rtx-200MS) and the 1 m secondary column TG-5HT in a reverse configuration. This system achieved the highest theoretical and conditional peak capacities, optimal resolution, and the lowest number of coelutions.

Possibility of Detection of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) through Wastewater in Developing Countries

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) was detected in Wuhan, China. The clinical manifestation of COVID-19 varies from asymptomatic to severe infection. The World Health Organization has reported over 248 million cases and more than 5 million deaths worldwide due to COVID-19. Additionally, developing countries are still struggling to achieve the rapid diagnosis of suspected cases to break the chain of transmission of COVID-19. There may be undiagnosed or missing cases in these countries. Various studies have reported that the SARS-CoV-2 can be discharged in the stool and other bodily fluids. Moreover, it is possible that SARS-CoV-2 can be transmitted in the environment via municipal wastewater. In developing countries, such as Nepal, the molecular-based diagnosis of SARS-CoV-2 for the entire population is not practical owing to insufficient diagnostic material and budgetary constraints. Wastewater-based epidemiology (WBE) is a promising public health surveillance tool for the early warning of disease outbreaks and the understanding the prevalence of viruses for the development of intervention measures. This study highlights the importance of the utilization of WBE as an alternative tool for the mass detection of SARS-CoV-2 RNA in wastewater.

m6A target microRNAs in serum for cancer detection

Recent studies have revealed the significant dysregulation of m6A level in peripheral blood in several cancer types and its value in diagnosis. Nonetheless, a biomarker for accurate screening of multiple cancer types has not been established based on the perspective of m6A modification. In this study, we aimed to develop a serum diagnostic signature based on the m6A target miRNAs for the mass detection of cancer. A total of 14965 serum samples with 12 cancer types were included. Based on training cohort (n=7299), we developed the m6A-miRNAs signature using a support vector machine algorithm for cancer detection. The m6A-miRNAs signature showed high accuracy, and its area under the curve (AUC) in the training, internal validation and external validation cohort reached 0.979 (95%CI 0.976 - 0.982), 0.976 (95%CI 0.973 - 0.979) and 0.936 (95%CI 0.922 - 0.951), respectively. In the performance of distinguishing cancer types, the m6A-miRNAs signature showed superior sensitivity in each cancer type and presented a satisfactory AUC in identifying lung cancer, gastric cancer and hepatocellular carcinoma. Additionally, the diagnostic performance of m6A-miRNAs was not interfered by the gender, age and benign disease. In short, this study revealed the value of serum circulating m6A miRNAs in cancer detection and provided a new direction and strategy for the development of novel biomarkers with high accuracy, low cost and less invasiveness for mass cancer screening, such as RNA modification.

ADAPTING THE METHODOLOGY FOR THE QUANTITATIVE DETERMINATION OF SQUALENE IN SUNFLOWER OIL DISTILLATION CHASES

Погоны дистилляции растительных масел являются перспективным вторичным сырьем для получения сквалена, обладающего широким спектром физиологической активности и являющегося ценным компонентом пищевых продуктов функционального и специализированного назначения, фармпрепаратов и коcметических средств. В настоящее время в Российской Федерации отсутствуют стандартизированные методы количественного определения сквалена в липидных матрицах, в том числе в погонах дистилляции растительных масел, что делает актуальным проведение исследований по адаптации существующих методик для решения данной проблемы. Целью исследования является выбор и адаптация эффективного и доступного метода идентификации и количественного определения сквалена в погонах дистилляции растительных масел. Задачи исследования состоят в разработке методики пробоподготовки, а также в адаптации метода газовой хроматографии для идентификации и количественного определения сквалена в погонах дистилляции растительных масел. В статье рассмотрены природные источники сквалена и основные методы его определения. Предложена методика пробоподготовки и адаптирован метод газовой хроматографии с масс-детектированием для количественного определения сквалена в погонах дистилляции растительных масел. Проведена верификация и определены основные метрологические характеристики метода. Установлено, что предлагаемый метод позволяет определять сквален в погонах дистилляции растительных масел в диапазоне концентраций от 0,1 до 5% с погрешностью не более ± 0,012%. Distillation straps of vegetable oils are a promising secondary raw material for the production of squalene, which has a wide spectrum of physiological activity and is a valuable component of food products for functional and specialized purposes, pharmaceuticals and cosmetics. Currently, in the Russian Federation there are no standardized methods for the quantitative determination of squalene in lipid matrices, including in the distillation strands of vegetable oils, which makes it urgent to carry out studies on the adaptation of existing methods to solve this problem. The aim of the study is to select and adapt an effective, fairly simple and accessible method for the identification and quantitative determination of squalene in distillation strains of vegetable oils. The objectives of the study are to develop a method for sample preparation, as well as to adapt the gas chromatography method for the identification and quantitative determination of squalene in distillation strands of vegetable oils. A method for sample preparation is proposed and the method of gas chromatography with mass detection is adapted for the quantitative determination of squalene in distillation strands of vegetable oils. Verification was carried out and the main metrological characteristics of the method were determined. It has been established that the proposed method makes it possible to determine squalene in distillation straps of vegetable oils in the concentration range from 0,1 to 5% with an error of no more than ± 0,012%.

Novel hydrophilic-phase extraction, HILIC and high-resolution MS quantification of an RNA oligonucleotide in plasma

Aim: In the theme of quantitative LC–MS bioanalysis of oligonucleotides free of ion-pairing, a 22-mer RNA oligonucleotide took center stage. The focus was on a unique polar-based retention scheme to produce a high-recovery extraction presenting a high-performance alternative extraction means, also there was the opportunity to involve hydrophilic-interaction liquid chromatography and contemporary high-resolution MS as the end point. Results: Original LC–MS methodology was developed for the oligonucleotide and the performance was robust for both nominal and accurate mass detection, the latter affording 10× improvement in sensitivity and 4000-fold linear dynamic range, 500 pM to 2000 nM. Conclusion: A novel means of solid-phase extraction is exhibited within a robust pair-free methodology, reaching pM sensitivity with the demonstrably beneficial accurate mass platform.