Formulation and Evaluation of Acetaminophen and Diphenhydramine Hydrochloride Tablets.

The present study is to develop a pharmaceutically stable and robust formulation of Acetaminophen 500mg and Diphenhydramine Hydrochloride 25mg tablets comparable with innovator. This goal various types of superdisintegrant and excipient with different concentrations are used in various prototype trials are taken & evaluated with respect to various quality parameters like weight variation, friability, hardness, thickness and also perform various stability studies in these formulation. The formulation shall be finalized by comparing the in -vitro dissolution profile with that of the innovator in various pH media by using HPLC method and produce a desirable and stable tablet. The main objective of this study was to develop and evaluate the formulation of Acetaminophen 500mg and Diphenhydramine Hydrochloride 25 mg tablets. Several trials have been taken to optimize and develop a robust formulation. Various processing problems were encountered during the formulation development and these were overcome with proper optimization of composition of formulation ingredients and processing conditions. The reproducibility batch (T11) was taken for the finalized batch ie. T11 was charged for stability studies at accelerated and real time conditions. The stability study for 3 months shows that the formulation is stable enough at 400C/75%RH. The formulation is a robust one and the performance is less likely to be affected by the various factors studied. The stability data is found to be satisfactory and so the scale up, Exhibit as well as validation batches can be planned for further progress. So it can be concluded that the Acetaminophen 500mg and Diphenhydraminehydrochloride 25mg tablets formulation T11 is robust and stable

Numerical Simulation and Design of Ensemble Learning Based Improved Software Development Effort Estimation System

This research paper proposes a novel approach to improving software development effort estimation by integrating ensemble learning algorithms with numerical simulation techniques. The objective of this study is to design an ensemble learning-based software development effort estimation system that leverages the strengths of multiple algorithms to enhance accuracy and reliability. The proposed system combines the power of ensemble learning, which involves aggregating predictions from multiple models, with numerical simulation techniques that enable the modelling and analysis of complex software development processes. A diverse set of software development projects is collected, encompassing various domains, sizes, and complexities. Ensemble learning algorithms such as Random Forest, Gradient Boosting, Bagging, and AdaBoost are selected for their ability to capture different aspects of the data and produce robust predictions. The proposed system architecture is presented, illustrating the flow of data and components. A model training and evaluation pipeline is developed, enabling the integration of ensemble learning and numerical simulation modules. The system combines the predictions generated by the ensemble models with the simulation results to produce more accurate and reliable effort estimates. The experimental setup involves a comprehensive evaluation of the proposed system. A real-world dataset comprising historical project data is utilized, and various performance metrics, including Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE), are employed to assess the effectiveness of the system. The results and analysis demonstrate that the ensemble learning-based effort estimation system outperforms traditional techniques, showcasing its potential to enhance project planning and resource allocation

Hybrid Low Complex near Optimal Detector for Spatial Modulation

In our previous work maximum throughput in multi stream MIMO is analyzed by overcoming the inter antenna interference. To mitigate the Inter antenna interference spatial modulation can be used. Spatial Modulation(SM) aided MIMO systems are the emerging MIMO systems which are low complex and energy efficient. These systems additionally use spatial dimensions for transmitting information. In this paper a low complex detector based on matched filter is proposed for spatial modulation to achieve near maximum likelihood performance while avoiding exhaustive ML search since MF based detector exhibits a considerable reduced complexity since activated transmitting antenna and modulated amplitude phase modulation constellation are estimated separately. Simulation results show the performance of the proposed method with optimal ML detector, MRC and conventional matched filter methods

Gestational diabetes mellitus: study of prevalence using criteria of diabetes in pregnancy study group in India and its impact on maternal and fetal outcome in a rural tertiary institute

Background: Gestational diabetes mellitus ((GDM) is defined as carbohydrate intolerance of varying degree of severity with onset or first recognition during pregnancy. GDM is associated with adverse fetomaternal outcome. Its early detection and management is essential for better perinatal outcome. The objective of the study was to assess the prevalence of gestational diabetes mellitus among pregnant women of western U.P. using diabetes in pregnancy study group in India (DIPSI) criteria and further assess its impact on fetomaternal outcome.Methods: This was a prospective study conducted at UP RIMS & R, Saifai, Uttar Pradesh, India including 225 pregnant women between 24-28 weeks gestational age who attended the antenatal OPD from January 2014 to January 2015.All women were given 75 gm oral glucose irrespective of their meals. Women with blood sugar values >140mg/dl were labeled as GDM and rest as control or non GDM group. All the GDM patients were followed up either with diet or insulin therapy till delivery to study fetomaternal outcome.Results: Out of 225 Women 22 women (9.7%) were diagnosed as having GDM and among risk factors, higher BMI was shown to be significant association (p<0.05). There was also significant difference among birth weight and neonatal complications in GDM and NON-GDM group (P<0.05).Conclusions: Due to high prevalence of GDM in India in our study we concluded that screening is very essential for all pregnant women even in low-risk group. As in our study which was done by single step method of DIPSI which was easy to performed, feasible for remote population. But more studies are needed to further conclude that DIPSI is sufficient for Indian population

Rapid identification and susceptibility pattern of various Candida isolates from different clinical specimens in a tertiary care hospital in Western Uttar Pradesh

Background: Candida species are component of normal flora of human beings. Candidiasis is the commonest fungal disease affecting mucosa, skin, nails and internal organs. A variety of predisposing factors are known to cause candidiasis either by altering balance of normal microbial flora of the body or by lowering the host defence.Methods: A total of 90 specimens submitted in the department of microbiology were included in this study.  Identification of Candida species as well as antifungal sensitivity testing was performed with Vitek®2 compact (Biomerieux France) using Vitek2 cards for identification of yeast and yeast like organisms (ID-YST cards). Antifungal susceptibility testing was performed using Vitek2 fungal susceptibility card (AST YS01) kits respectively.Results: The distribution of the clinical samples were urine 53 (58.9%), sputum 14 (15.5%), blood 10 (11.1%), nail 6 (6.7%) and high vaginal swab 7 (7.8%). Among 90 clinical isolates, species obtained were C. tropicalis 53 (59%), C. albicans 23 (25.5%), C. glabrata 6 (6.7%), C. parapsilosis 4 (4.4%), C. krusei 2 (2.2%), C. pelliculosa 1 (1.1%), C. famata 1 (1.1%).Conclusions: Infections caused by non-candida albicans species have increased. Identification of Candida species and their antifungal susceptibility are important for the treatment of hospitalized patients with serious underlying disease

Performance of lactating crossbred cows fed on forage based total mixed ration

A study was conducted to evaluate the forage based total mixed ration (TMR) in crossbred lactating cows on milk production and nutrient digestibility. TMR was prepared by mixing wheat straw, chapped green forages (sorghum and rice bean in experiment I and oat and berseem in experiment II) and concentrate feed having 17 percent dietary CP. Two feeding experiments for the period of 60 days duration each during rainy (experiment I) and winter seasons (experiment II) were conducted in first lactating crossbred cows. In both the experiment six first lactating cows were taken and divided into 2 groups. Group 1 (T1)was fed TMR and in Group 2 (T2) ingredients were fed separately. The total daily dry matter intake (DMI) in cows fed TMR increased significantly (p˂0.01) by 15.92 percent in experiment I, when multi cut sorghum and rice bean used as green fodder. However, the differences were negligible in experiment II,when oat and berseem used as green fodder. The dry matter (DM) and crude protein (CP) digestibility as well as digestible energy (DE) value of ration were increased significantly (p˂0.01) in cows fed on TMR based on berseem and oat as green fodder in experiment II. However, differences were non-significant in experiment I, when multi cut sorghum and rice bean used as green fodder in TMR. The overall increase in milk production was recorded by 16.96 and 19.49 percent in cows fed TMR during experiment I and II, respectively. Similarly, an increase in milk production in cows fed different feeds separately was also recorded 10.74 and 6.41 percent,respectively during experiment I and II. Thus, it i s concluded that feeding of TMR is beneficial for proportionate intake of all feed ingredients, overall feed intake and better digestibility of nutrients resulting into higher milk production. This record was migrated from the OpenDepot repository service in June, 2017 before shutting down

RNA Interference: An Overview

In the course of transgenic experiments on the nematode Caenorhabditis elegans, RNA interference, usually abbreviated as RNAi, was discovered first. It is a gene-silencing effect and is found to be widely distributed in eukaryotes. It was observed that control injections of sense RNA were just as effective as antisense RNA, directed at specifically inhibiting target genes in C. elegans by the injection of antisense RNA during an experiment causing the reduction or elimination of expression from the gene under investigation. Subsequently, by injecting double-stranded RNA (dsRNA) corresponding to the target gene, it was discovered that the effect could be most potently elicited, and contamination of the single-stranded RNA (ssRNA; either sense or antisense) by traces of dsRNA could explain the earlier results. By post-transcriptional mechanism, substantial or complete inhibition of expression from any gene can be done using dsRNA corresponding to part or all of the mature mRNA from any given gene. An attempt was made here to describe the basic underlying molecular mechanism of RNAi, the methodology and various experimental requirements, and its advantages and disadvantages. In relation to CRISPR/Cas9 technology, the future prospects of virus-induced gene silencing (VIGS) are considered finally. For the cutting-edge CRISPR/Cas9 genome editing technology, VIGS has emerged as the preferred delivery system besides using it to overexpress or silence genes

Factors associated with neonatal deaths in Chitwan district of Nepal

Background: Neonatal mortality has remained unchanged since 2006 in Nepal. Reducing neonatal mortality is indispensable to reduce child mortality. The objective of this study was to investigate the factors associated with neonatal mortality. This study assesses socio-demographic factors, maternal health care and newborn care practices contributing to neonatal deaths in Chitwan district of Central Nepal. Methods: A case–control study was conducted during April–July 2012. The study used a mixed-method approach, in which records of neonatal deaths were obtained from the District Public Health Office and a comparison group, survivors, was obtained from the same community. A total of 198 mothers (of 99 neonatal deaths and 99 survivor neonates) were included in the survey. Focus group discussions, in-depth interviews and case studies were also conducted. Maternal characteristics were analyzed using descriptive statistics, Mc Nemar’s Chi square test and multivariable backward conditional logistic regression analysis. Qualitative data were analyzed by narrative analysis method.Results: More than four-fifth of mothers (86 %) had antenatal check-up (ANC) and the proportion of four or more ANC was 64 %. Similarly, the percentage of mothers having institutional delivery was 62 %, and postnatal check-up was received by 65 % of mothers. In multivariable analysis, low birth weight [adjusted odds ratio: 8.49, 95 % CI (3.21–22.47)], applying nothing on cord [adjusted odds ratio: 5.72, 95 % CI (1.01-32.30)], not wrapping of newborn [adjusted odds ratio: 9.54, 95 % CI (2.03–44.73)], and no schooling of mother [adjusted odds ratio: 2.09, 95 % CI (1.07–4.11)] were significantly associated with an increased likelihood of neonatal mortality after adjusting for other confounding variables. Qualitative findings suggested that bathing newborns after 24 h and wrapping in clean clothes were common newborn care practices. The mothers only attended postnatal care services if health problems appeared either in the mother or in the child. Conclusion:L Results of this study suggest that the current community based newborn survival intervention should provide an even greater focus to essential newborn care practices, low birth weight newborns, and female education