Serum Chemerin Levels Correlate With Severity of Dysglycemia in Young Adult Women With Polycystic Ovary Syndrome.

Context: A subset of polycystic ovary syndrome (PCOS) individuals also have type 2 diabetes (T2D); an unmet need to identify this subgroup exists. Objective: We looked at the potential role of serum chemerin, a proinflammatory adipokine, in identifying dysglycemic PCOS. Methods: A total of 93 PCOS and 33 healthy controls were classified, based on fasting and 2-hour plasma glucose levels (2hPGPG) and glycated hemoglobin A1c (HbA1c) (%) into normoglycemic (n = 34), dysglycemic (n = 33), and T2D (n = 26). Serum chemerin were measured by enzyme-linked immunosorbent assay. Homeostatic model 2 assessment of insulin resistance (HOMA-2IR) and homeostatic model 2 assessment of ß-cell function (HOMA-2ß) were computed using serum C-peptide. Results: Metabolic syndrome was present in 9.7% (National Cholesterol Education Program) of PCOS. Waist circumference, body fat (%), 2hPGPG, and HbA1c levels were significantly higher in T2D group. Serum triglycerides/high-density lipoprotein cholesterol (TGs/HDL-c) ratio was increased in PCOS individuals with T2D; no significant changes in total cholesterol and LDL-c levels were seen. Serum chemerin levels were significantly higher (P < .001) in the PCOS group. Total body fat (%), 2hPGPG, HbA1c, and TG/HDL-c ratio correlated positively with chemerin levels. Serum chemerin levels correlated positively with HOMA2IR and negatively with HOMA-2ß. On receiver operating characteristic curve analysis, a serum chemerin cutoff level of greater than 309.3 ng/mL differentiated PCOS individuals with dysglycemia from those without (sensitivity 85.71%, specificity 89.47%). The Cohen kappa test revealed a substantial agreement (P < .001) between chemerin cutoff and 2hPGPG levels greater than 200 mg/dL. The present study is arguably the first ever to define a serum chemerin cutoff to distinguish PCOS individuals with T2D from those without. Conclusion: Elevated serum chemerin levels reliably identify PCOS individuals with dysglycemia. Further, longitudinal studies with larger samples are required to confirm this association.

Epidemiological challenges in pandemic coronavirus disease (COVID-19): Role of artificial intelligence.

World is now experiencing a major health calamity due to the coronavirus disease (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus clade 2. The foremost challenge facing the scientific community is to explore the growth and transmission capability of the virus. Use of artificial intelligence (AI), such as deep learning, in (i) rapid disease detection from x-ray or computed tomography (CT) or high-resolution CT (HRCT) images, (ii) accurate prediction of the epidemic patterns and their saturation throughout the globe, (iii) forecasting the disease and psychological impact on the population from social networking data, and (iv) prediction of drug-protein interactions for repurposing the drugs, has attracted much attention. In the present study, we describe the role of various AI-based technologies for rapid and efficient detection from CT images complementing quantitative real-time polymerase chain reaction and immunodiagnostic assays. AI-based technologies to anticipate the current pandemic pattern, prevent the spread of disease, and face mask detection are also discussed. We inspect how the virus transmits depending on different factors. We investigate the deep learning technique to assess the affinity of the most probable drugs to treat COVID-19. This article is categorized under:Application Areas > Health CareAlgorithmic Development > Biological Data MiningTechnologies > Machine Learning.

Decreased Levels of miR-126 and miR-132 in Plasma and Vitreous Humor of Non-Proliferative Diabetic Retinopathy Among Subjects with Type-2 Diabetes Mellitus.

PURPOSE: Diabetic retinopathy (DR), the leading cause of blindness among working adults, is an urgent public health problem as diabetes mellitus (DM) is increasing at an alarming rate. Hyperglycemia-induced endothelial dysfunction is the principal contributing factor leading to the development of microangiopathy. Altered levels of microRNA (miR), the negative regulator of protein-coding genes, have been observed and considered to be markers for DR. Present study aimed to find out whether miR levels in plasma could be effective biomarkers to differentiate between type 2 diabetes mellitus (T2DM) with non-proliferative retinopathy (NPDR) from T2DM with no-DR (DNR). METHODS: We recruited 50 T2DM subjects comprising 31 NPDR and 19 DNR individuals. Surrogate markers of systemic oxidative stress and vascular endothelial growth factor (VEGF) were measured in plasma. Levels of miR-126 and miR-132 were determined in plasma and vitreous fluid using real-time PCR. RESULTS: We observed that levels of miR-126 and miR-132 were decreased in NPDR subjects in comparison to DNR. Plasma levels of miRs were inversely correlated with secreted levels of VEGF and oxidative stress marker. The levels of these miRs showed discriminating ability between NPDR and DNR. CONCLUSION: Circulating miRs 126 and 132 in plasma or vitreous may serve as biomarkers for early diabetic retinopathy risk prediction, provided validated in a larger cohort and other forms of retinal vasculopathy or retinopathy in the future.

Co-Regulation of Protein Coding Genes by Transcription Factor and Long Non-Coding RNA in SARS-CoV-2 Infected Cells: An In Silico Analysis.

Altered expression of protein coding gene (PCG) and long non-coding RNA (lncRNA) have been identified in SARS-CoV-2 infected cells and tissues from COVID-19 patients. The functional role and mechanism (s) of transcriptional regulation of deregulated genes in COVID-19 remain largely unknown. In the present communication, reanalyzing publicly available gene expression data, we observed that 66 lncRNA and 5491 PCG were deregulated in more than one experimental condition. Combining our earlier published results and using different publicly available resources, it was observed that 72 deregulated lncRNA interacted with 3228 genes/proteins. Many targets of deregulated lncRNA could also interact with SARS-CoV-2 coded proteins, modulated by IFN treatment and identified in CRISPR screening to modulate SARS-CoV-2 infection. The majority of the deregulated lncRNA and PCG were targets of at least one of the transcription factors (TFs), interferon responsive factors (IRFs), signal transducer, and activator of transcription (STATs), NFκB, MYC, and RELA/p65. Deregulated 1069 PCG was joint targets of lncRNA and TF. These joint targets are significantly enriched with pathways relevant for SARS-CoV-2 infection indicating that joint regulation of PCG could be one of the mechanisms for deregulation. Over all this manuscript showed possible involvement of lncRNA and mechanisms of deregulation of PCG in the pathogenesis of COVID-19.

In silico analysis of altered expression of long non-coding RNA in SARS-CoV-2 infected cells and their possible regulation by STAT1, STAT3 and interferon regulatory factors.

Altered expression of long noncoding RNA (lncRNA), longer than 200 nucleotides without potential for coding protein, has been observed in diverse human diseases including viral diseases. It is largely unknown whether lncRNA would deregulate in SARS-CoV-2 infection, causing ongoing pandemic COVID-19. To identify, if lncRNA was deregulated in SARS-CoV-2 infected cells, we analyzed in silico the data in GSE147507. It was revealed that expression of 20 lncRNA like MALAT1, NEAT1 was increased and 4 lncRNA like PART1, TP53TG1 was decreased in at least two independent cell lines infected with SARS-CoV-2. Expression of NEAT1 was also increased in lungs tissue of COVID-19 patients. The deregulated lncRNA could interact with more than 2800 genes/proteins and 422 microRNAs as revealed from the database that catalogs experimentally determined interactions. Analysis with the interacting gene/protein partners of deregulated lncRNAs revealed that these genes/proteins were associated with many pathways related to viral infection, inflammation and immune functions. To find out whether these lncRNAs could be regulated by STATs and interferon regulatory factors (IRFs), we used ChIPBase v2.0 that catalogs experimentally determined binding from ChIP-seq data. It was revealed that any one of the transcription factors IRF1, IRF4, STAT1, STAT3 and STAT5A had experimentally determined binding at regions within -5kb to +1kb of the deregulated lncRNAs in at least 2 independent cell lines/conditions. Our analysis revealed that several lncRNAs could be regulated by IRF1, IRF4 STAT1 and STAT3 in response to SARS-CoV-2 infection and lncRNAs might be involved in antiviral response. However, these in silico observations are necessary to be validated experimentally.

A Tripartite Interaction among the Basidiomycete Rhodotorula mucilaginosa, N2-Fixing Endobacteria, and Rice Improves Plant Nitrogen Nutrition.

Nitrogen (N) limits crop yield, and improvement of N nutrition remains a key goal for crop research; one approach to improve N nutrition is identifying plant-interacting, N2-fixing microbes. Rhodotorula mucilaginosa JGTA-S1 is a basidiomycetous yeast endophyte of narrowleaf cattail (Typha angustifolia). JGTA-S1 could not convert nitrate or nitrite to ammonium but harbors diazotrophic (N2-fixing) endobacteria (Pseudomonas stutzeri) that allow JGTA-S1 to fix N2 and grow in a N-free environment; moreover, P. stutzeri dinitrogen reductase was transcribed in JGTA-S1 even under adequate N. Endobacteria-deficient JGTA-S1 had reduced fitness, which was restored by reintroducing P. stutzeri JGTA-S1 colonizes rice (Oryza sativa), significantly improving its growth, N content, and relative N-use efficiency. Endofungal P. stutzeri plays a significant role in increasing the biomass and ammonium content of rice treated with JGTA-S1; also, JGTA-S1 has better N2-fixing ability than free-living P. stutzeri and provides fixed N to the plant. Genes involved in N metabolism, N transporters, and NODULE INCEPTION-like transcription factors were upregulated in rice roots within 24 h of JGTA-S1 treatment. In association with rice, JGTA-S1 has a filamentous phase and P. stutzeri only penetrated filamentous JGTA-S1. Together, these results demonstrate an interkingdom interaction that improves rice N nutrition.

A unique life-strategy of an endophytic yeast Rhodotorula mucilaginosa JGTA-S1-a comparative genomics viewpoint.

Endophytic yeasts of genus Rhodotorula are gaining importance for their ability to improve plant growth. The nature of their interaction with plants, however, remains unknown. Rhodotorula mucilaginosa JGTA-S1 was isolated as an endophyte of Typha angustifolia and promoted growth in the host. To investigate the life-strategy of the yeast from a genomics perspective, we used Illumina and Oxford Nanopore reads to generate a high-quality annotated draft assembly of JGTA-S1 and compared its genome to three other Rhodotorula yeasts and the close relative Rhodosporidium toruloides. JGTA-S1 is a haploid yeast possessing several genes potentially facilitating its endophytic lifestyle such as those responsible for solubilizing phosphate and producing phytohormones. An intact mating-locus in JGTA-S1 raised the possibility of a yet unknown sexual reproductive cycle in Rhodotorula yeasts. Additionally, JGTA-S1 had functional anti-freezing genes and was also unique in lacking a functional nitrate-assimilation pathway-a feature that is associated with obligate biotrophs. Nitrogen-fixing endobacteria were found within JGTA-S1 that may circumvent this defective N-metabolism. JGTA-S1 genome data coupled with experimental evidence give us an insight into the nature of its beneficial interaction with plants.

Author Correction: An Endophytic Bacterial Consortium modulates multiple strategies to improve Arsenic Phytoremediation Efficacy in Solanum nigrum.

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An Endophytic Bacterial Consortium modulates multiple strategies to improve Arsenic Phytoremediation Efficacy in Solanum nigrum.

Endophytic microbes isolated from plants growing in contaminated habitats possess specialized properties that help their host detoxify the contaminant/s. The possibility of using microbe-assisted phytoremediation for the clean-up of Arsenic (As) contaminated soils of the Ganga-Brahmaputra delta of India, was explored using As-tolerant endophytic microbes from an As-tolerant plant Lantana camara collected from the contaminated site and an intermediate As-accumulator plant Solanum nigrum. Endophytes from L. camara established within S. nigrum as a surrogate host. The microbes most effectively improved plant growth besides increasing bioaccumulation and root-to-shoot transport of As when applied as a consortium. Better phosphate nutrition, photosynthetic performance, and elevated glutathione levels were observed in consortium-treated plants particularly under As-stress. The consortium maintained heightened ROS levels in the plant without any deleterious effect and concomitantly boosted distinct antioxidant defense mechanisms in the shoot and root of As-treated plants. Increased consortium-mediated As(V) to As(III) conversion appeared to be a crucial step in As-detoxification/translocation. Four aquaporins were differentially regulated by the endophytes and/or As. The most interesting finding was the strong upregulation of an MRP transporter in the root by the As + endophytes, which suggested a major alteration of As-detoxification/accumulation pattern upon endophyte treatment that improved As-phytoremediation.

Split-ubiquitin yeast two-hybrid interaction reveals a novel interaction between a natural resistance associated macrophage protein and a membrane bound thioredoxin in Brassica juncea.

Natural resistance associated macrophage proteins (NRAMPs) are evolutionarily conserved metal transporters involved in the transport of essential and nonessential metals in plants. Fifty protein interactors of a Brassica juncea NRAMP protein was identified by a Split-Ubiquitin Yeast-Two-Hybrid screen. The interactors were predicted to function as components of stress response, signaling, development, RNA binding and processing. BjNRAMP4.1 interactors were particularly enriched in proteins taking part in photosynthetic or light regulated processes, or proteins predicted to be localized in plastid/chloroplast. Further, many interactors also had a suggested role in cellular redox regulation. Among these, the interaction of a photosynthesis-related thioredoxin, homologous to Arabidopsis HCF164 (High-chlorophyll fluorescence164) was studied in detail. Homology modeling of BjNRAMP4.1 suggested that it could be redox regulated by BjHCF164. In yeast, the interaction between the two proteins was found to increase in response to metal deficiency; Mn excess and exogenous thiol. Excess Mn also increased the interaction in planta and led to greater accumulation of the complex at the root apoplast. Network analysis of Arabidopsis homologs of BjNRAMP4.1 interactors showed enrichment of many protein components, central to chloroplastic/cellular ROS signaling. BjNRAMP4.1 interacted with BjHCF164 at the root membrane and also in the chloroplast in accordance with its proposed function related to photosynthesis, indicating that this interaction occurred at different sub-cellular locations depending on the tissue. This may serve as a link between metal homeostasis and chloroplastic/cellular ROS through protein-protein interaction.

Early changes in shoot transcriptome of rice in response to Rhodotorula mucilaginosa JGTA-S1.

Yeasts of Rhodotorula genus have been reported to show endophytic colonization in different plants. Some of the Rhodotorula species are found to exhibit plant growth promoting activities and also have been reported to protect plants against invading pathogens. A yeast strain closely related to Rhodotorula mucilaginosa was isolated from the endosphere of Typha angustifolia collected from a Uranium mine. A microarray analysis was performed to investigate the early changes in rice shoot transcripts in response to this yeast (R. mucilaginosa JGTA-S1). Transcriptional changes were monitored in 6 h and 24 h treated rice plant shoots as compared to 0 h control. The microarray data has been submitted to the NCBI GEO repository under the accession number of GSE64321.

Isolation and expression analysis of partial sequences of heavy metal transporters from Brassica juncea by coupling high throughput cloning with a molecular fingerprinting technique.

Heavy metal transporters play a key role in regulating metal accumulation and transport in plants. These are important candidate genes to study in metal tolerant and accumulator plants for their potential use in environmental clean up. We coupled a degenerate primer-based RT-PCR approach with a molecular fingerprinting technique based on amplified rDNA restriction analysis (ARDRA) to identify novel ESTs corresponding to heavy metal transporters from metal accumulator Brassica juncea. We utilized this technique to clone several family members of natural resistance-associated macrophage proteins (NRAMP) and yellow stripe-like proteins (YSL) in a high throughput manner to distinguish between closely related isoforms and/or allelic variants from the allopolyploid B. juncea. Partial clones of 23 Brassica juncea NRAMPs and 27 YSLs were obtained with similarity to known Arabidopsis thaliana and Noccaea (Thlaspi) caerulescens NRAMP and YSL genes. The cloned transporters showed Brassica-specific changes in domains, which can have important functional consequences. Semi-quantitative RT-PCR-based expression analysis of chosen members indicated that even closely related isoforms/allelic variants of BjNRAMP and BjYSL have distinct tissue-specific and metal-dependent expressions which might be essential for adaptive fitness and heavy metal tolerance. Consistent to this, BjYSL6.1 and BjYSL5.8 were found to show elevated expressions specifically in cadmium-treated shoots and lead-treated roots of B. juncea, respectively.