Asymptomatic bacteriuria among pregnant women attending antenatal clinic at a tertiary care centre

Background: The term asymptomatic bacteriuria is defined as the presence of > 100,000 colonies of a single bacterial species per millilitre of urine (105 cfu /mL), cultured from clean catch midstream sample in the absence of declared symptoms. The aim of this study was to know the incidence of asymptomatic bacteriuria in pregnancy and the various factors influencing it, to identify the pathogens and their antibiotic susceptibility patterns.Methods: Clean catch mid-stream urine samples were collected from 3000 pregnant women (all trimesters) aged between 18-35 years of age attending the antenatal OPD in GMCH, Guwahati for a period of one year (July 2018-June2019).  Identification of organisms and antibiotic sensitivity tests were performed as per standard methods.Results: In our study, incidence of asymptomatic bacteriuria was found to be 12.1%. Most women (52.89%) were in the age group of (20-30) years, mostly in second trimester (47.1%). Gram negative organisms were the commonest organisms isolated; among which Escherichia coli (56.75%) was the principal urinary pathogen followed by Klebsiella sp (14.33%) and Staphylococcus saprophyticus (12.67%). The isolates were most sensitive to Nitrofurantoin (87.88%).Conclusions: Asymptomatic bacteriuria is common in pregnancy. Once ASB is recognized during pregnancy, it should be appropriately treated with antibiotics and promptly followed up

Assessment of Doppler velocimetry versus nonstress test in antepartum surveillance of high risk pregnancy

Background: High risk pregnancies increase the maternal and fetal morbidity and mortality; and there is a need for appropriate investigation which can diagnose it early and predicts the morbidity and mortality. The objectives of this study were to compare the efficacy of Doppler velocimetry studies and NST in predicting fetal compromise in utero and compare their ability in predicting the perinatal outcome in cases of high risk pregnancies.Methods: It was a prospective cross-sectional hospital based study conducted at Central Referral Hospital (CRH) which is a teaching hospital of Sikkim Manipal Institute of Medical Sciences (SMIMS). The study was conducted over a period of eighteen months between November 2012 and April 2014. One hundred consecutive cases of high risk pregnancies were enrolled into the study and investigated with NST (non-stress test) and Doppler velocimetry and results were correlated with perinatal outcome. In all cases, accurate gestational age was established from detailed menstrual history and ultrasonographic evidence of gestational age. Detailed examination, history and investigation were undertaken in each patient. Inclusion criteria were patients with singleton pregnancy beyond 34 weeks having one or more high risk factors. In these patients antenatal surveillance was done by Doppler and NST and results of these tests were correlated with perinatal outcome. Based on the Doppler velocimetry and NST results, the study population was divided in to four groups. Pregnant women below 34 weeks, multiple pregnancy and women with no risk factors were excluded from the study.Results: Maximum (63%) patients belonged to pregnancy induced hypertension (PIH) group, followed by oligohydramnios (11%), and gestational diabetes mellitus (GDM). The study showed that patients with both NST and Doppler waveform abnormal (group D) had the highest percentage of neonatal complication, NICU admissions and perinatal deaths. Even those patients with NST normal but Doppler velocimetry abnormal (group B) had comparatively higher neonatal complications. However, in group with NST abnormal and Doppler velocimetry normal (group C) had no fetal compromise. It was observed that normal NST and normal Doppler velocimetry were not statistically different in predicting fetal compromise and prediction value was low. But abnormal Doppler had statistically significant (p value = 0.021) predictive value in detecting fetal compromise. In cases with abnormal Doppler and fetal compromise, NST was still normal showing that abnormal Doppler waveform was better in predicting the bad perinatal outcome. Three out of 100 cases had absent end diastolic flow (AEDF) and all 3 were associated with perinatal morbidity with 2 perinatal deaths. Cerebroplacental ratio was < 1.08 in seven cases and all seven had neonatal complications including 3 neonatal deaths which also had AEDF. Thus, cerebroplacental ratio was better in detecting fetal compromise as compared to NST.Conclusions: Doppler velocimetry was better in predicting fetal compromise in comparison to NST in high risk pregnancies. Normal NST and normal Doppler velocimetry were not significantly different in prediction of fetal outcome. Abnormal Doppler value was better in predicting fetal compromise in comparison to abnormal NST

XPS evidence for molecular charge-transfer doping of graphene

By employing x-ray photoelectron spectroscopy (XPS), we have been able to establish the occurrence of charge-transfer doping in few-layer graphene covered with electron acceptor (TCNE) and donor (TTF) molecules. We have performed quantitative estimates of the extent of charge transfer in these complexes and elucidated the origin of unusual shifts of their Raman G bands and explained the differences in the dependence of conductivity on n- and p-doping. The study unravels the cause of the apparent difference between the charge-transfer doping and electrochemical doping.Comment: 15 pages, 5 figure

Constraining the reionization and thermal history of the Universe using a semi-numerical photon-conserving code SCRIPT

Given that the reionization history of cosmic hydrogen is yet to be stringently constrained, it is worth checking the prospects of doing so using physically motivated models and available observational data. For this purpose, we use an extended version of the explicitly photon-conserving semi-numerical model of reionization, $\texttt{SCRIPT}$, which also includes thermal evolution of the intergalactic medium (IGM). The model incorporates the effects of inhomogeneous recombination and radiative feedback self-consistently and is characterized by five free parameters (two for the redshift-dependent ionization efficiency, two for the ionizing escape fraction, and another for reionization temperature increment). We constrain these free parameters by simultaneously matching with various observational probes, e.g., estimates of the ionized hydrogen fraction, the CMB scattering optical depth and the galaxy UV luminosity function. In addition, we include the low-density IGM temperature measurements obtained from Lyman-$\alpha$ absorption spectra at $z \sim 5.5$, a probe not commonly used for Bayesian analysis of reionization parameters. We find that the interplay of the various data sets, particularly inclusion of the temperature data, leads to tightening of the parameter constraints. Our default models prefer a late end of reionization (at $z \lesssim 6$), in agreement with other recent studies. We can also derive constraints on the duration of reionization, $\Delta z=1.81^{+0.51}_{-0.67}$ and the midpoint of reionization, $z_{\mathrm{mid}}=7.0^{+0.30}_{-0.40}$. The constraints can be further tightened by including other available and upcoming data sets.Comment: Accepted for publication in MNRA

A fast method of reionization parameter space exploration using GPR trained SCRIPT

Efficient exploration of parameter spaces is crucial to extract physical information about the Epoch of Reionization from various observational probes. To this end, we propose a fast technique based on Gaussian Process Regression (GPR) training applied to a semi-numerical photon-conserving reionization model, SCRIPT. Our approach takes advantage of the numerical convergence properties of SCRIPT and constructs a training set based on low-cost, coarse-resolution simulations. A likelihood emulator is then trained using this set to produce results in approximately two orders of magnitude less computational time than a full MCMC run, while still generating reasonable 68% and 95% confidence contours. Furthermore, we conduct a forecasting study using simulated data to demonstrate the applicability of this technique. This method is particularly useful when full MCMC analysis is not feasible due to expensive likelihood computations.Comment: Submitted to MNRA