Morphological, Biochemical, and Molecular Characterization of Orange-Fleshed Sweet Potato (Ipomoea batatas [L.] Lam) Germplasms

The sweet potato is considered as an excellent source of β-carotene and anthocyanins and has a considerable value in the functional food market. In this report, 21 sweet potato (Ipomoea batatas [L.] Lam) germplasms were evaluated for genetic diversity using morphological and biochemical and molecular markers. Ten morphological traits were studied, and the mean squares due to germplasm were highly significant for storage root number per plant, individual root weight, storage root (fresh) per plant, storage root (dry) per plant, storage root yield, and storage root length. UPGMA cluster analysis based on morphological traits separated the germplasm into three groups. The similarity coefficient ranged from 0.00 to 0.50 with an average of 0.176. Biochemical analysis, viz. total phenol and antioxidant, was performed to find out superior genotype at biochemical level under given conditions. Maximum total phenol was observed in the genotype “V-12” (1.39 mg), whereas maximum total antioxidant was observed in “Samrat” (0.30 mg). RAPD analysis was carried out, and out of 15 RAPD primers, 10 primers produced 96 reproducible and polymorphic bands. UPGMA cluster analysis based on RAPD data also separated the genotypes into three clusters. The results of the present study can be used for sweet potato crop improvement through molecular breeding and marker-assisted selection for desired traits in future

Real-Time Volatile Metabolomics Analysis of Dendritic Cells.

Dendritic cells (DCs) actively sample and present antigen to cells of the adaptive immune system and are thus vital for successful immune control and memory formation. Immune cell metabolism and function are tightly interlinked, and a better understanding of this interaction offers potential to develop immunomodulatory strategies. However, current approaches for assessing the immune cell metabolome are often limited by end-point measurements, may involve laborious sample preparation, and may lack unbiased, temporal resolution of the metabolome. In this study, we present a novel setup coupled to a secondary electrospray ionization-high resolution mass spectrometric (SESI-HRMS) platform allowing headspace analysis of immature and activated DCs in real-time with minimal sample preparation and intervention, with high technical reproducibility and potential for automation. Distinct metabolic signatures of DCs treated with different supernatants (SNs) of bacterial cultures were detected during real-time analyses over 6 h compared to their respective controls (SN only). Furthermore, the technique allowed for the detection of 13C-incorporation into volatile metabolites, opening the possibility for real-time tracing of metabolic pathways in DCs. Moreover, differences in the metabolic profile of naı̈ve and activated DCs were discovered, and pathway-enrichment analysis revealed three significantly altered pathways, including the TCA cycle, α-linolenic acid metabolism, and valine, leucine, and isoleucine degradation

Rapid detection of Staphylococcus aureus and Streptococcus pneumoniae by real-time analysis of volatile metabolites

Early detection of pathogenic bacteria is needed for rapid diagnostics allowing adequate and timely treatment of infections. In this study, we show that secondary electrospray ionization-high resolution mass spectrometry (SESI-HRMS) can be used as a diagnostic tool for rapid detection of bacterial infections as a supportive system for current state-of-the-art diagnostics. Volatile organic compounds (VOCs) produced by growing S. aureus or S. pneumoniae cultures on blood agar plates were detected within minutes and allowed for the distinction of these two bacteria on a species and even strain level within hours. Furthermore, we obtained a fingerprint of clinical patient samples within minutes of measurement and predominantly observed a separation of samples containing live bacteria compared to samples with no bacterial growth. Further development of this technique may reduce the time required for microbiological diagnosis and should help to improve patient's tailored treatment. Keywords: Applied microbiology; Biological sciences tools; Diagnostics; Microbiology

Alcoholic Extract of Eclipta alba

As per WHO estimates, 80% of people around the world use medicinal plants for the cure and prevention of various diseases including cancer owing to their easy availability and cost effectiveness. Eclipta alba has long been used in Ayurveda to treat liver diseases, eye ailments, and hair related disorders. The promising medicinal value of E. alba prompted us to study the antioxidant, nontoxic, and anticancer potential of its alcoholic extract. In the current study, we evaluated the in vitro cytotoxic and antioxidant effect of the alcoholic extract of Eclipta alba (AEEA) in multiple cancer cell lines along with control. We have also evaluated its effect on different in vivo toxicity parameters. Here, we found that AEEA was found to be most active in most of the cancer cell lines but it significantly induced apoptosis in human breast cancer cell lines by disrupting mitochondrial membrane potential and DNA damage. Moreover, AEEA treatment inhibited migration in both MCF 7 and MDA-MB-231 cells in a dose dependent manner. Further, AEEA possesses robust in vitro antioxidant activity along with high total phenolic and flavonoid contents. In summary, our results indicate that Eclipta alba has enormous potential in complementary and alternative medicine for the treatment of cancer

Putative amniotic fluid stem (AFS) cells express transcription factor Oct-4 in goat (Capra aegagrus hircus)

Abstract The current study was carried out to isolate, culture, characteriz

An interoperability framework for multicentric breath metabolomic studies

Exhaled breath contains valuable information at the molecular level and offers promising potential for precision medicine. However, few breath tests transition to routine clinical practice, partly because of the missing validation in multicenter trials. Therefore, we developed and applied an interoperability framework for standardized multicenter data acquisition and processing for breath analysis with secondary electrospray ionization-high resolution mass spectrometry. We aimed to determine the technical variability and metabolic coverage. Comparison of multicenter data revealed a technical variability of ∼20% and a core signature of the human exhaled metabolome consisting of ∼850 features, corresponding mainly to amino acid, xenobiotic, and carbohydrate metabolic pathways. In addition, we found high inter-subject variability for certain metabolic classes (e.g., amino acids and fatty acids), whereas other regions such as the TCA cycle were relatively stable across subjects. The interoperability framework and overview of metabolic coverage presented here will pave the way for future large-scale multicenter trials

Metabolic trajectories of diabetic ketoacidosis onset described by breath analysis

PurposeThis feasibility study aimed to investigate the use of exhaled breath analysis to capture and quantify relative changes of metabolites during resolution of acute diabetic ketoacidosis under insulin and rehydration therapy.MethodsBreath analysis was conducted on 30 patients of which 5 with DKA. They inflated Nalophan bags, and their metabolic content was subsequently interrogated by secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS).ResultsSESI-HRMS analysis showed that acetone, pyruvate, and acetoacetate, which are well known to be altered in DKA, were readily detectable in breath of participants with DKA. In addition, a total of 665 mass spectral features were found to significantly correlate with base excess and prompt metabolic trajectories toward an in-control state as they progress toward homeostasis.ConclusionThis study provides proof-of-principle for using exhaled breath analysis in a real ICU setting for DKA monitoring. This non-invasive new technology provides new insights and a more comprehensive overview of the effect of insulin and rehydration during DKA treatment

CRP Gene Polymorphism and Their Risk Association With Type 2 Diabetes Mellitus

BACKGROUND: C-reactive protein (CRP) is an inflammatory marker associated with T2DM, obesity, insulin resistance, and cardiovascular disease. AIM: The present study evaluates the association of CRP +1059 G/C polymorphism of the CRP gene in 100 T2D cases and 100 healthy controls. METHODS: Present study was done by allele specific PCR method to study the CRP gene polymorphism in study subjects. RESULTS: Study found that CRP (+1059 G/C) genotype distribution among case and controls was found to be significant (p=0.001), Higher CRP C allele frequency (0.16) was observed compared to controls (0.04). CRP +1059 GC and CC had 2.72 (1.12-6.61), 20.56 (1.16-362.1) risk for T2D. It has been observed, HTN, Obesity, Smoking and alcoholism was found to be associated with increased risk of T2D, and a significant difference was observed in biochemical parameters. CONCLUSION: Study concluded that CRP gene polymorphism was found to be associated with risk of Type 2 Diabetes and risk was linked with heterozygosity and mutant homozygosity. Hypertension, Obesity, Smoking and alcoholism increases the risk of occurrence of Type 2 Diabetes

Identification of potential therapeutic targets for COVID-19 through a structural-based similarity approach between SARS-CoV-2 and its human host proteins

Background: The COVID-19 pandemic caused by SARS-CoV-2 has led to millions of deaths worldwide, and vaccination efficacy has been decreasing with each lineage, necessitating the need for alternative antiviral therapies. Predicting host–virus protein–protein interactions (HV-PPIs) is essential for identifying potential host-targeting drug targets against SARS-CoV-2 infection.Objective: This study aims to identify therapeutic target proteins in humans that could act as virus–host-targeting drug targets against SARS-CoV-2 and study their interaction against antiviral inhibitors.Methods: A structure-based similarity approach was used to predict human proteins similar to SARS-CoV-2 (“hCoV-2”), followed by identifying PPIs between hCoV-2 and its target human proteins. Overlapping genes were identified between the protein-coding genes of the target and COVID-19-infected patient’s mRNA expression data. Pathway and Gene Ontology (GO) term analyses, the construction of PPI networks, and the detection of hub gene modules were performed. Structure-based virtual screening with antiviral compounds was performed to identify potential hits against target gene-encoded protein.Results: This study predicted 19,051 unique target human proteins that interact with hCoV-2, and compared to the microarray dataset, 1,120 target and infected group differentially expressed genes (TIG-DEGs) were identified. The significant pathway and GO enrichment analyses revealed the involvement of these genes in several biological processes and molecular functions. PPI network analysis identified a significant hub gene with maximum neighboring partners. Virtual screening analysis identified three potential antiviral compounds against the target gene-encoded protein.Conclusion: This study provides potential targets for host-targeting drug development against SARS-CoV-2 infection, and further experimental validation of the target protein is required for pharmaceutical intervention

Meeting the Radio Frequency Identification mandate

Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2004.Includes bibliographical references.Various retailers like Wal-Mart, Target, and Albertsons have announced their mandates asking their top suppliers to become RFID enabled beginning 2005. Meeting the mandate has become a sort of cost of doing business with Wal-Mart for suppliers. The objective of this thesis is to look for ways of meeting the mandate and preventing it from just becoming a cost of doing business with Wal-Mart. The thesis explores the various options available to suppliers and identifies the cost and benefit associated with each option and develops an evaluation methodology for the various options.by Kapil Dev Singh.M.Eng.in Logistic