COVID-19 symptoms-does pregnancy alter the course of the disease

Background: COVID-19 or corona virus 2 is a widespread pandemic taking a huge toll on the world population.it has a varied presentation in different age groups. Similarly, it has a poorer outcome in the elderly with various comorbidities and those who are immunocompromised. Though pregnancy is a relatively immunocompromised state studies have found that pregnant women have a less severe presentation. We have tried to assess this aspect of COVID-19 in pregnant women.Methods: We evaluated the records of 158 pregnant women who presented to our hospital from April 2020 till September 2020.Their symptoms at presentation were evaluated. we also noted the outcome of these pregnancies.Results: 16% of these were more than 34 weeks of period of gestation. 65.19% presented without any symptoms. 15.19% presented with fever. 10.75% presented with cough. 8.22% presented with headache. 5.69% presented with sore throat alone. 3.16% presented with breathlessness. 0.63% presented with anosmia alone, loss of taste, severe acute respiratory infection, vomiting, sore throat and breathlessness respectively. 54 patients delivered of which 7 delivered vaginally and there were 47 caesareans. Remaining patients after cure were discharged. There were 3 miscarriages. Two babies were found to be COVID-19 positive from nasopharyngeal swab taken on day 1, however this was a small number to indicate vertical transmission.Conclusion: Our study showed that a large proportion of pregnant patients presented without symptoms.it remains to be evaluated why this is so.it may provide us with clues on how to deal with disease in the general population

Covid 19, the Kerala experience: an observational, single centre retrospective study of outcome in covid positive pregnancies

Background: Covid 19 has spread across the world at an alarming rate. Approximately 4.05 million people have got infected worldwide resulting in around 279,000 deaths. Over 1 million people have recovered worldwide. Aim of this study was to determine whether course and severity of covid 19 is altered in pregnant women and whether covid 19 seemed to worsen the prognosis in pregnant women.Methods: Around 50 covid positive patients were admitted to this study hospital, a tertiary care referral hospital and medical college, between march and May 2020, 11 were pregnant. Authors collected their data retrospectively to understand the course of their disease till the period of recovery.Results: There were 6 patients above 31 weeks of whom one had elective repeat caesarean section, one had full term vaginal delivery, one is under follow up. Three patients had foetal distress necessitating emergency caesarean section. Of the remaining 5 patients with periods of gestation between 9-13 weeks, 1 of 24 weeks, 6 patients above 31 weeks, one had a miscarriage. Rest pregnancies are continuing and under follow up. 6 women had been symptomatic at admission, with mild symptoms of low-grade fever, sore throat and rhinitis. All were treated with hydroxychloroquine (HCQs). Those with respiratory symptoms like cough were also treated with oseltamivir. In view of high prevalence of H1N1 in the region. None of the women developed severe disease. The disease did not appear to worsen prognosis in pregnant women. The rate of recovery in pregnant women was similar to that seen in non-pregnant women and also men under the age of 40 years admitted in this study hospital.Conclusions: Covid 19 did not seem to worsen the prognosis in pregnant individuals when compared to rest of the population. The foetal outcomes also seemed favorable. However larger studies are required before concrete guidelines could be formulated for management of the disease in pregnancy

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Study of Interface Charge Densities for ZrO 2

A thickness-dependent interfacial distribution of oxide charges for thin metal oxide semiconductor (MOS) structures using high-k materials ZrO2 and HfO2 has been methodically investigated. The interface charge densities are analyzed using capacitance-voltage (C-V) method and also conductance (G-V) method. It indicates that, by reducing the effective oxide thickness (EOT), the interface charge densities (Dit) increases linearly. For the same EOT, Dit has been found for the materials to be of the order of 1012 cm−2 eV−1 and it is originated to be in good agreement with published fabrication results at p-type doping level of 1×1017 cm−3. Numerical calculations and solutions are performed by MATLAB and device simulation is done by ATLAS

Effect of silver incorporation on the structural and morphological characteristics of RF sputtered indium oxide films.

Radio frequency (RF) magnetron sputtered silver incorporated indium oxide thin films were prepared and their structural and morphological properties were studied using micro- Raman spectroscopy, Atomic Force Microscopy (AFM), Field Emission Scanning Electron Microscopy (FESEM) and Energy Dispersive Spectroscopy (EDS). Raman modes corresponding to the cubic bixbyite phase of indium oxide were obtained through micro-Raman spectroscopy. AFM images exhibited dense distribution of grains. Elemental analysis using EDS spectra confirmed the presence of indium, silver and oxygen in the prepared films

Observation of room temperature photoluminescence from asymmetric CuGaO2/ZnO/ZnMgO multiple quantum well structures

Asymmetric (CuGaO2/ZnO/ZnMgO) and symmetric (ZnMgO/ZnO/ZnMgO) multiple quantum well (MQW) structures were successfully fabricated using pulsed laser deposition (PLD) and their comparison were made. Efficient room temperature photoluminescent (PL) emission was observed from these MQWs and temperature dependent luminescence of asymmetric and symmetric MQWs can be explained using the existing theories. A systematic blue shift was observed in both MQWs with decrease in the confinement layer thickness which could be attributed to the quantum confinement effects. The PL emission from asymmetric and symmetric MQW structures were blue shifted compared to 150 nm thick ZnO thin film grown by PLD due to quantum confinement effects

Genetic analysis of variation in human meiotic recombination

The number of recombination events per meiosis varies extensively among individuals. This recombination phenotype differs between female and male, and also among individuals of each gender. In this study, we used high-density SNP genotypes of over 2,300 individuals and their offspring in two datasets to characterize recombination landscape and to map the genetic variants that contribute to variation in recombination phenotypes. We found six genetic loci that are associated with recombination phenotypes. Two of these (RNF212 and an inversion on chromosome 17q21.31) were previously reported in the Icelandic population, and this is the first replication in any other population. Of the four newly identified loci (KIAA1462, PDZK1, UGCG, NUB1), results from expression studies provide support for their roles in meiosis. Each of the variants that we identified explains only a small fraction of the individual variation in recombination. Notably, we found different sequence variants associated with female and male recombination phenotypes, suggesting that they are regulated by different genes. Characterization of genetic variants that influence natural variation in meiotic recombination will lead to a better understanding of normal meiotic events as well as of non-disjunction, the primary cause of pregnancy loss. © 2009 Chowdhury et al

Comparison of Illumina and 454 Deep Sequencing in Participants Failing Raltegravir-Based Antiretroviral Therapy

Background: The impact of raltegravir-resistant HIV-1 minority variants (MVs) on raltegravir treatment failure is unknown. Illumina sequencing offers greater throughput than 454, but sequence analysis tools for viral sequencing are needed. We evaluated Illumina and 454 for the detection of HIV-1 raltegravir-resistant MVs. Methods: A5262 was a single-arm study of raltegravir and darunavir/ritonavir in treatment-naïve patients. Pre-treatment plasma was obtained from 5 participants with raltegravir resistance at the time of virologic failure. A control library was created by pooling integrase clones at predefined proportions. Multiplexed sequencing was performed with Illumina and 454 platforms at comparable costs. Illumina sequence analysis was performed with the novel snp-assess tool and 454 sequencing was analyzed with V-Phaser. Results: Illumina sequencing resulted in significantly higher sequence coverage and a 0.095% limit of detection. Illumina accurately detected all MVs in the control library at ≥0.5% and 7/10 MVs expected at 0.1%. 454 sequencing failed to detect any MVs at 0.1% with 5 false positive calls. For MVs detected in the patient samples by both 454 and Illumina, the correlation in the detected variant frequencies was high (R2 = 0.92, P<0.001). Illumina sequencing detected 2.4-fold greater nucleotide MVs and 2.9-fold greater amino acid MVs compared to 454. The only raltegravir-resistant MV detected was an E138K mutation in one participant by Illumina sequencing, but not by 454. Conclusions: In participants of A5262 with raltegravir resistance at virologic failure, baseline raltegravir-resistant MVs were rarely detected. At comparable costs to 454 sequencing, Illumina demonstrated greater depth of coverage, increased sensitivity for detecting HIV MVs, and fewer false positive variant calls

MTar: a computational microRNA target prediction architecture for human transcriptome

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) play an essential task in gene regulatory networks by inhibiting the expression of target mRNAs. As their mRNA targets are genes involved in important cell functions, there is a growing interest in identifying the relationship between miRNAs and their target mRNAs. So, there is now a imperative need to develop a computational method by which we can identify the target mRNAs of existing miRNAs. Here, we proposed an efficient machine learning model to unravel the relationship between miRNAs and their target mRNAs.</p> <p>Results</p> <p>We present a novel computational architecture MTar for miRNA target prediction which reports 94.5% sensitivity and 90.5% specificity. We identified 16 positional, thermodynamic and structural parameters from the wet lab proven miRNA:mRNA pairs and MTar makes use of these parameters for miRNA target identification. It incorporates an Artificial Neural Network (ANN) verifier which is trained by wet lab proven microRNA targets. A number of hitherto unknown targets of many miRNA families were located using MTar. The method identifies all three potential miRNA targets (5' seed-only, 5' dominant, and 3' canonical) whereas the existing solutions focus on 5' complementarities alone.</p> <p>Conclusion</p> <p>MTar, an ANN based architecture for identifying functional regulatory miRNA-mRNA interaction using predicted miRNA targets. The area of target prediction has received a new momentum with the function of a thermodynamic model incorporating target accessibility. This model incorporates sixteen structural, thermodynamic and positional features of residues in miRNA: mRNA pairs were employed to select target candidates. So our novel machine learning architecture, MTar is found to be more comprehensive than the existing methods in predicting miRNA targets, especially human transcritome.</p