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Background: The placental pathological changes in hypertensive disorders of pregnancy (HDP) starts early in pregnancy, the deep convolutional neural networks (CNN) can identify these changes before its clinical manifestation. Objective: To compare the placental quantitative ultrasound image texture of women with HDP to those with the normal outcome. Methods: The cases were enrolled in the first trimester of pregnancy, good quality images of the placenta were taken serially in the first, second, and third trimester of pregnancy. The women were followed till delivery, those with normal outcomes were controls, and those with HDP were cases. The images were processed and classified using validated deep learning tools. Results: Total of 429 cases were fully followed till delivery, 58 of them had HDP (13.5%). In the first trimester, there was a significant difference in the placental length (p = .033), uterine artery PI (p = .019), biomarkers PAPP-A (p = .001) PlGF (p = .013) and placental image texture (p = .001) between the cases and controls. In the second trimester the uterine artery PI, serum PAPPA (p = .010) and PlGF (p = .005) levels were significantly low among women who developed hypertension later on pregnancy. The image texture disparity between the two groups was highly significant (p < .001). The model "resnext 101_32x8d" had Cohen kappa score of 0.413 (moderate) and the accuracy score of 0.710 (good). In the first trimester the best sensitivity and specificity was observed for abnormal placental image texture (70.6% and 76.6%, respectively) followed by PlGF (64% and 50%, respectively), in the second trimester the abnormal image texture had the highest sensitivity and specificity (60.4% and 73.3%, respectively) followed by uterine artery PI (58.6% and 54.7%, respectively). Similarly in the third trimester, uterine artery PI had sensitivity and specificity of 60.3% and specificity of 50.7%, whereas the abnormal image texture had sensitivity and specificity of 83.5%. Conclusion: Ultrasound placental analysis using artificial intelligence (UPAAI) is a promising technique, would open avenues for more research in this field. [ABSTRACT FROM AUTHOR]

The article highlights several studies which shows stripes as an architectural feature of three-dimensional chromatin and found stripes connected to epigenetic regulation of transcription. It discusses StripeDiff showed performance in both simulation data analysis and real Hi-C data analysis; applying StripeDiff to 12 sets of Hi-C data showed insights into connection between change of chromatin stripe and change of chromatin modification, transcriptional regulation, and cell differentiation.

[Display omitted] • Aging features breakage of RNA homeostasis. • We propose a score to measure the balance between spliced and unspliced RNA from scRNA-Seq data. • We report a set of genes undergoing homeostatic breakdown during pancreatic aging. • Analysis suggests the existence of transcripitional restoration as a potential anti-aging mechanism. Age-dependent dysregulation of transcription regulatory machinery triggers modulations in the gene expression levels leading to the decline in cellular fitness. Tracking of these transcripts along the temporal axis in multiple species revealed a spectrum of evolutionarily conserved pathways, such as electron transport chain, translation regulation, DNA repair, etc. Recent shreds of evidence suggest that aging deteriorates the transcription machinery itself, indicating the hidden complexity of the aging transcriptomes. This reinforces the need for devising novel computational methods to view aging through the lens of transcriptomics. Here, we present Homeostatic Divergence Score (HDS) to quantify the extent of messenger RNA (mRNA) homeostasis by assessing the balance between spliced and unspliced mRNA repertoire in single cells. We validated its utility in two independent aging datasets, and identified sets of genes undergoing age-related breakdown of transcriptional homeostasis. Moreover, testing of our method on a subpopulation of human embryonic stem cells revealed a set of differentially processed transcripts segregating these subpopulations. Our preliminary analyses in this direction suggest that mRNA processing level information offered by single-cell RNA sequencing (scRNA-seq) data is a superior determinant of chronological age as compared to transcriptional noise. [ABSTRACT FROM AUTHOR]

Background: The hearing threshold of more than 25 decibels (dB) at the frequencies (500, 1000, 2000 and 4000 Hertz) which are important for speech recognition can result in significant auditory deficits. Hearing loss can be slight, moderate, severe or profound hearing loss based on the average threshold. Objective: to determine the incidence, associated risk factors hearing impairment in a population of neonates seeking care at Rohilkhand Medical College and Hospital, Bareilly. Methods: The present descriptive exploratory study was conducted among200 neonate who are born or admitted in Rohilkhand Medical College and Hospital, Bareilly over a period of 12 months. Results: The first otoacoustic emission (OAE) screening was done on infants at the time of discharge from the NICU. Eighty-three infants (55.33%) had "refer" on the first OAE and the remaining 67 (44.67%) were passed results at the time of discharge. At 21 DAYS of life, on repeat screening with a second OAE test, 36% "refer" on the first screen had a "refer" result on the second DPOAE. However, 4.4% "pass" on the first screen turned out to be "refer" on the second screen. These 33 infants who had "refer" results on the second screen were subjected to testing. At 3 MONTHS of life, BERA was performed on 33 infants. 11 infants out of 33 had sensorineural hearing loss (SNHL) on AABR. Conclusions: Two-stage OAE done prior to BERA is helpful in the early detection of hearing loss. Our study demonstrates the use of a combination of OAE and BERA testing ensures high sensitivity and acceptable specificity, and predict the incidence of hearing impairment in Neonates Our efforts identified 11 Neonates with auditory neuropathy who hopefully will benefit from early remediation of their hearing deficit. [ABSTRACT FROM AUTHOR]

Odorant receptors (ORs) obey mutual exclusivity and monoallelic mode of expression. Efforts are ongoing to decipher the molecular mechanism that drives the 'one-neuron-one-receptor' rule of olfaction. Recently, single-cell profiling of olfactory sensory neurons (OSNs) revealed the expression of multiple ORs in the immature neurons, suggesting that the OR gene choice mechanism is much more complex than previously described by the silence-all-and-activate-one model. These results also led to the genesis of two possible mechanistic models i.e. winner-takes-all and stochastic selection. We developed Reverse Cell Tracking (RCT), a novel computational framework that facilitates OR-guided cellular backtracking by leveraging Uniform Manifold Approximation and Projection embeddings from RNA Velocity Workflow. RCT-based trajectory backtracking, coupled with statistical analysis, revealed the OR gene choice bias for the transcriptionally advanced (highest expressed) OR during neuronal differentiation. Interestingly, the observed selection bias was uniform for all ORs across different spatial zones or their relative expression within the olfactory organ. We validated these findings on independent datasets and further confirmed that the OR gene selection may be regulated by Upf3b. Lastly, our RNA dynamics-based tracking of the differentiation cascade revealed a transition cell state that harbors mixed molecular identities of immature and mature OSNs, and their relative abundance is regulated by Upf3b. [ABSTRACT FROM AUTHOR]

We investigated the effect of two dosing regimens of oral iron on iron status and hematological parameters in patients with CKD. In this single center, open label, randomized, active controlled clinical trial, stable adult patients with CKD stage G3–4 with percentage transferrin saturation (%TSAT) ≤ 30% and serum ferritin ≤ 500 ng/ml were eligible. Participants were randomized to receive either 100 mg of ferrous ascorbate once daily (OD group) or 100 mg of ferrous ascorbate twice daily (BD group, total daily dose 200 mg). The primary outcome was change in %TSAT between groups over 12 weeks. The secondary outcomes were changes in other iron status and hematological parameters, serum interleukin-6 (IL-6) and hepcidin. 80 participants were enrolled out of which 76 completed the study. Change in %TSAT was not significantly different between groups (β = − 1.43, 95% CI − 3.99 to 1.12, BD group as reference). The rise in serum ferritin was less in the OD group as compared to BD group (β = − 0.36, 95% CI − 0.61 to − 0.10) whereas MCHC increased in the OD group as compared to decrease in the BD group (β = 0.37, 95% CI 0.067–0.67). These observations need exploration to ascertain the impact of different oral iron dosing strategies in CKD. [ABSTRACT FROM AUTHOR]

Dramatic genomic alterations, either inducible or in a pathological state, dismantle the core regulatory networks, leading to the activation of normally silent genes. Despite possessing immense therapeutic potential, accurate detection of these transcripts is an ever-challenging task, as it requires prior knowledge of the physiological gene expression levels. Here, we introduce EcTracker, an R-/Shiny-based single-cell data analysis web server that bestows a plethora of functionalities that collectively enable the quantitative and qualitative assessments of bona fide cell types or tissue-specific transcripts and, conversely, the ectopically expressed genes in the single-cell ribonucleic acid sequencing datasets. Moreover, it also allows regulon analysis to identify the key transcriptional factors regulating the user-selected gene signatures. To demonstrate the EcTracker functionality, we reanalyzed the CRISPR interference (CRISPRi) dataset of the human embryonic stem cells differentiated into endoderm lineage and identified the prominent enrichment of a specific gene signature in the SMAD2 knockout cells whose identity was ambiguous in the original study. The key distinguishing features of EcTracker lie within its processing speed, availability of multiple add-on modules, interactive graphical user interface and comprehensiveness. In summary, EcTracker provides an easy-to-perform, integrative and end-to-end single-cell data analysis platform that allows decoding of cellular identities, identification of ectopically expressed genes and their regulatory networks, and therefore, collectively imparts a novel dimension for analyzing single-cell datasets. [ABSTRACT FROM AUTHOR]

The molecular mechanisms of olfaction, or the sense of smell, are relatively underexplored compared with other sensory systems, primarily because of its underlying molecular complexity and the limited availability of dedicated predictive computational tools. Odorant receptors (ORs) allow the detection and discrimination of a myriad of odorant molecules and therefore mediate the first step of the olfactory signaling cascade. To date, odorant (or agonist) information for the majority of these receptors is still unknown, limiting our understanding of their functional relevance in odor-induced behavioral responses. In this study, we introduce OdoriFy, a Web server featuring powerful deep neural network-based prediction engines. OdoriFy enables (1) identification of odorant molecules for wildtype or mutant human ORs (Odor Finder); (2) classification of user-provided chemicals as odorants/nonodorants (Odorant Predictor); (3) identification of responsive ORs for a query odorant (OR Finder); and (4) interaction validation using Odorant-OR Pair Analysis. In addition, OdoriFy provides the rationale behind every prediction it makes by leveraging explainable artificial intelligence. This module highlights the basis of the prediction of odorants/nonodorants at atomic resolution and for the ORs at amino acid levels. A key distinguishing feature of OdoriFy is that it is built on a comprehensive repertoire of manually curated information of human ORs with their known agonists and nonagonists, making it a highly interactive and resource-enriched Web server. Moreover, comparative analysis of OdoriFy predictions with an alternative structure-based ligand interaction method revealed comparable results. OdoriFy is available freely as a web service at https://odorify.ahujalab.iiitd.edu.in/olfy/. [ABSTRACT FROM AUTHOR]

Background: Cardiovascular disease is the leading cause of morbidity and mortality in children with chronic kidney disease (CKD). We aim to estimate the prevalence of cardiac abnormalities in children up to age 16 years with CKD and their association with various risk factors.Methods: This cross-sectional observational study was conducted on 107 CKD children. We assessed the systolic and diastolic function using 2D echocardiographic evaluation and M-mode measurements of the left ventricle (LV) indexed for BSA and z-scores were calculated. Results were compared with age, sex, stage of CKD, anaemia, estimated glomerular filtration rate (eGFR) and various laboratory parameters.Results: LV diastolic dysfunction was seen in 88%, followed by increased LV dimensions in 33.6%, LV systolic dysfunction in 16%, right ventricle systolic dysfunction in 11.2% while increased pulmonary artery (PA) systolic pressure was seen in 9.3% of cases. LV dimensions correlated directly with parathormone levels and inversely with eGFR, serum calcium and haemoglobin levels. Left ventricular hypertrophy correlated directly with parathormone while inversely with eGFR, serum calcium and haemoglobin. Ejection fraction directly correlated to eGFR and serum calcium while inversely related to parathormone. Left PA pressure directly correlated with age and inversely with eGFR. Right ventricular systolic function assessed by tricuspid annular plane systolic excursion correlated inversely with haemoglobin.Conclusion: LV diastolic dysfunction and increased LV dimensions were the most common cardiac abnormality in children with CKD. LV dimensions correlated directly with parathormone levels and inversely with eGFR, serum calcium and haemoglobin. Diastolic dysfunction positively correlated with serum creatinine and parathormone levels. [ABSTRACT FROM AUTHOR]