Unmasking the elusive: an early gestational age placenta accreta case series to illuminate the path towards avoiding missed diagnosis

Placenta accreta is a condition characterized by the abnormal invasion of the placenta into the uterine wall, leading to torrential hemorrhage. This case series, highlights the importance of accurate diagnosis and early detection of this life-threatening complication. The incidence of this iatrogenic complication is rising due to increased caesarean deliveries. While in advance stages of pregnancy the chances of missing accreta are less but in early pregnancy the diagnosis may be elusive. Timely detection by using imaging modalities like ultrasound both 2D and colour Doppler, provide valuable clues. Misdiagnosis may be fatal, especially in the first trimester. The present case series presents 3 cases where initial diagnosis of missed abortion followed by repeated curettage and gestational trophoblastic disease (GTD) was made respectively. The agony of suffering leads the patient to our tertiary care center where the diagnosis of accreta was made. Accurate diagnosis and early detection of placenta accreta are vital to optimize patient outcome. Detecting the nicheand an anteriorly situated low lying placenta with history of previous birth by caesarian section should raise suspicion, and vigilance on the part of treating obstetrician is must

Genome-Wide Mapping of Quantitative Trait Loci for Yield-Attributing Traits of Peanut

Peanuts (Arachis hypogaea L.) are important high-protein and oil-containing legume crops adapted to arid to semi-arid regions. The yield and quality of peanuts are complex quantitative traits that show high environmental influence. In this study, a recombinant inbred line population (RIL) (Valencia-C × JUG-03) was developed and phenotyped for nine traits under two environments. A genetic map was constructed using 1323 SNP markers spanning a map distance of 2003.13 cM. Quantitative trait loci (QTL) analysis using this genetic map and phenotyping data identified seventeen QTLs for nine traits. Intriguingly, a total of four QTLs, two each for 100-seed weight (HSW) and shelling percentage (SP), showed major and consistent effects, explaining 10.98% to 14.65% phenotypic variation. The major QTLs for HSW and SP harbored genes associated with seed and pod development such as the seed maturation protein-encoding gene, serine-threonine phosphatase gene, TIR-NBS-LRR gene, protein kinase superfamily gene, bHLH transcription factor-encoding gene, isopentyl transferase gene, ethylene-responsive transcription factor-encoding gene and cytochrome P450 superfamily gene. Additionally, the identification of 76 major epistatic QTLs, with PVE ranging from 11.63% to 72.61%, highlighted their significant role in determining the yield- and quality-related traits. The significant G × E interaction revealed the existence of the major role of the environment in determining the phenotype of yield-attributing traits. Notably, the seed maturation protein-coding gene in the vicinity of major QTLs for HSW can be further investigated to develop a diagnostic marker for HSW in peanut breeding. This study provides understanding of the genetic factor governing peanut traits and valuable insights for future breeding efforts aimed at improving yield and quality

Long non-coding RNA-mediated epigenetic response for abiotic stress tolerance in plants

Plants perceive environmental fluctuations as stress and confront several stresses throughout their life cycle individually or in combination. Plants have evolved their sensing and signaling mechanisms to perceive and respond to a variety of stresses. Epigenetic regulation plays a critical role in the regulation of genes, spatiotemporal expression of genes under stress conditions and imparts a stress memory to encounter future stress responses. It is quintessential to integrate our understanding of genetics and epigenetics to maintain plant fitness, achieve desired genetic gains with no trade-offs, and durable long-term stress tolerance. The long non-coding RNA >200 nts having no coding potential (or very low) play several roles in epigenetic memory, contributing to the regulation of gene expression and the maintenance of cellular identity which include chromatin remodeling, imprinting (dosage compensation), stable silencing, facilitating nuclear organization, regulation of enhancer-promoter interactions, response to environmental signals and epigenetic switching. The lncRNAs are involved in a myriad of stress responses by activation or repression of target genes and hence are potential candidates for deploying in climate-resilient breeding programs. This review puts forward the significant roles of long non-coding RNA as an epigenetic response during abiotic stresses in plants and the prospects of deploying lncRNAs for designing climate-resilient plants

Predictive skill of DEMETER models for wind prediction over southern subtropical Indian Ocean

62-69The ensemble mean prediction of winds at 850 hPa from individual models of DEMETER project has been compared from NCEP observation over southern subtropical Indian Ocean during summer monsoon season (JJAS) for the time domain 1980-2001. Predictability of U850 hPa (U850) and V850 hPa (V850) has been tested by different statistical approach like root mean square error (RMSE) for the region between Madagascar and western Australia in view of the importance of this region in anomalous variation of south central African rainfall variability as evidenced by some recent studies. A dichotomous forecast skill measure has been performed by calculating predictive skill measures like accuracy, bias, probability of detection (POD), false alarm ration (FAR), probability of false detection (POFD), threat score (TS), equivalent threat score (ETS) and Heidke skill score (HSS) for model produced U850 and V850 from all the individual models and multi model ensemble (MME). It has been found that the root mean square error has been reduced by applying MME but there is no effect on dichotomous predictive skill measures

Southern Indian Ocean SST indices as early predictors of Indian summer monsoon

70-76Four indices of quarterly mean sea surface temperature (SST) values extracted for Southern Indian Ocean (SIO) region for which the maximum correlation with All India Rainfall Index (AIRI) was found with a lag up to 7 seasons w.r.t. the onset of monsoon. The Artificial Neural Network (ANN) technique has been used to study the predictability of the Indian summer monsoon with four indices individually as well as in various combinations. It has been found that two combinations of SST indices of SIO region, SIOI + ACCI and CSIOI + NWAI + SIOI + ACCI, show best predictive skill when used collectively. It has been found that the performance of the ANN model is better than the corresponding regression model in the prediction of ISMR indicating that the relationship between ISMR and SST indices are non-linear in nature

Not Available

Not AvailablePolycyclic aromatic hydrocarbons (PAHs), including phenanthrene, are commonly found as pollutants in soils, estuarine, and sediments, as well as in terrestrial and other aquatic ecosystems. In this context, the phenanthrene-degrading bacteria were isolated and characterized in contaminated mangrove surface sediment, on the coast of Thane Creek, Mumbai, India by enrichment method, using phenanthrene as the sole source of carbon and energy. The phylogenetic diversity of the isolates were evaluated by 16S rRNA gene analysis and characterized as Bacillus mojavensis strain KSS001, Bacillus firmus strain KSS002, Bacillus flexus strain KSS003, Bacillus vietnamensis strain KSS004, and Bacillus amyloliquefaciens strain KSS005. Each isolate was grown on the phenanthrene up to 100 mg/L and the biodegradation ability was evidenced using a gas chromatography–flame ionization detector. Further, the mean value of phenanthrene degradation by 5 bacterial isolates after incubation in mineral salt medium for 7 days was 63% at 100 mg/L. The study reports that mangrove sediments of Thane Creek, Mumbai, contain a diverse population of phenanthrene-degrading bacteria that have the potential and capability to degrade PAHs contaminated sites, and are consequently recommended for bioremediation.Not Availabl