Preclinical Development of Novel Chemotherapeutic Agent AC1LPSZG: Formulation Optimization, in Vitro Characterization, and in Vivo Pharmacokinetics

Preclinical development of novel chemotherapeutic agent AC1LPSZG, a mammalian target of rapamycin (mTOR) inhibitor, involved development of sensitive reverse-phase ultra-performance liquid chromatography (UPLC) and LC-MS/MS methods for quantification of AC1LPSZG in in vitro study samples and rat plasma, respectively. Pharmacokinetic studies were done in SD rats after intravenous injection of cosolvent formulations. The resulting pharmacokinetic parameters were analyzed using non-compartmental analysis (NCA) and two-compartmental modeling. Poly (D, L-lactic-co-glycolic acid) (PLGA) is most used biodegradable synthetic polymer for nano drug delivery due to its non-toxic and biodegradable nature, and tunable release properties. PLGA nanoparticles (NPs) were prepared by ‘nanoprecipitation’ technique using a nonionic surfactant poloxamer P188. The particle size, size distribution, and zeta potential of prepared nanoparticles were analyzed using dynamic light scattering (DLS). The drug entrapment efficiency (%EE) was accessed by ultra-sonication of lyophilized NPs with acetonitrile and analyzing the drug content using UPLC. Design of Experiments (DoE) strategy using Design Expert® software (version 13) was successfully used to optimize PLGA (50:50) based NPs of AC1LPSZG. Optimized batch was prepared using 5 mg drug and 4 mL aqueous phase volume with EE of 41.2%, NP size of 124 nm, drug load of 2.6% and zeta potential of – 15 mV. We conclude similar DOE approaches can help to understand and optimize innovative manufacturing processes, needed for the quality by design (QbD) preparation of other nano-formulations. The in vitro drug release was tested in phosphate buffer pH 6.8 for 72 hours, employing USP-4 apparatus CE7-smart (SOTAX®) incorporated with Float-A-Lyzer dialysis cells at 300 kDa molecular weight cut–off (MWCO), flow rate 16 mL/min and temperature 37°C. Different surfactants were explored to enhance the drug solubility and accelerate the in vitro drug release. The influence of three different surfactants: SLS (Sodium Lauryl Sulfate-anionic), Tween 80 (non-ionic) and CTAB (Cetyltrimethylammonium bromide- cationic) on drug solubility, sink conditions and dissolution behavior was demonstrated. The solubility improvement was in the order of SLS \u3e Tween80 \u3e CTAB and dissolution efficiency was improved with the increase of surfactant concentration. The developed in vitro drug release method was able to discriminate among different release profiles. In brief, similar discriminatory test method can be used as a quality control tool to identify critical formulation and process parameters and can also be used as a surrogate for bioequivalence studies if a predictive IVIVC (In vitro In vivo correlation) is obtained

Study of intrauterine fetal death cases in a tertiary care center

Background: The death of a fetus is a tragic event not only for the parents but also a great cause of stress for the caregiver. It is thus vital to identify specific probable causes of fetal death to determine the risk of recurrence, prevention or corrective action.Methods: This retrospective observational study was carried out in department of obstetrics and gynaecology, Jhalawar Medical College, Jhalawar, from July 2019 to October 2019. Intrauterine fetal death was confirmed either with ultrasound or on clinical examination. The details of complaints, obstetrics history, examination findings, mode of delivery, fetal outcomes and investigation reports were recorded.Results: A total of 114 intrauterine fetal deaths were reported amongst 2982 deliveries conducted during the study period. The incidence rate of IUFD was 38.22/1000 live births. 85.96% deliveries were unbooked. 59.64% belonged to rural population. 59.64% fetal deaths occurred in women between 20 to 25 years of age. 45.61% women were primigravida. 41.2% IUFD occurred between 26 to 31 weeks of gestation. Among the identifiable cause’s hypertensive disorders (23.68) and placental causes (19.29%) were most common.Conclusions: Unexplained causes, PIH and abruptio placentae were major causes of IUFD. Majority of fetal wastage can be prevented with universal and improved antenatal care

Feto-maternal outcome in second versus first stage caesarean delivery in a tertiary medical care centre

 Background: The aim is to study neonatal and maternal outcomes of the caesarean sections performed in first stage versus second stage of labour. Methods: The retrospective analysis of data were done of caesarean section done at Department of Obstetrics and Gynaecology at ESI PGIMSR Basaidarapur New Delhi between January 2016 to December 2016. 45 women, who underwent second stage caesarean section were studied. For each case, two consecutive cases, who underwent caesarean delivery during the first stage of labour were taken as control for the study. Primary maternal outcomes of interest were uterine atonia, transfusion requirement, urinary system injury and postoperative complications. Results: Out of 4477 deliveries, 1466 had caesarean section with a rate of 32%. The rate of second stage caesarean section was 3% of total caesarean section and 1% of total deliveries. Second stage caesarean section had higher maternal and perinatal morbidity like atonic PPH (33.3%), lower uterine segment extension (7%), febrile morbidity (10%), and need for blood transfusion (15%). There were 15.5% NICU admission in second stage caesarean group while none in first stage group. Conclusions: Caesarean section in the second stage of the labour is associated with increased maternal and neonatal morbidities. Special attention is required to the patients undergoing caesarean section in the second stage of the labour. They should be handled by senior and experienced obstetrician. Neonatologist should be present for every second stage caesarean section

Integrating Machine Learning and Mathematical Programming for Optimisation of Electric Discharge of Machining Techniques

This study explores the combination of machine guidance and several developing approaches to enhance both precision and effectiveness during Electricity-discharged Machining (EDM) business operations. The studies on quality control, energy efficiency, sustainable development, mathematical modelling within EDM optimization, and machine learning applications in EDM optimisation are all examined in this study. It highlights significant gaps in scientific knowledge, providing a pathway for the development of state-of-the-art EDM methods. The outcomes show that material decrease, energy efficiency, along EDM technique optimisation can all be enhanced. This study offers valuable information for future research within the field and contributes to the ongoing conversation about advanced manufacturing techniques. This project intends to revolutionise EDM by merging mathematical programming and machine learning. Three primary topics are investigated machining parameter optimisation, efficiency improvement using machine learning and environmental effect assessment. The goals of the study are met by using the deductive method, which gives a formal setting in which to examine hypotheses. Descriptive research designs allow for in-depth analyses of previously published works, mathematical models and automated learning programs. Finding commonalities and trends in qualitative data is the goal of the thematic data analysis technique. The results of this study provide useful resources, standards and sustainable perspectives for enhancing EDM procedures in manufacturing settings

Application of the multivariate skew normal mixture model with the EM Algorithm to Value-at-Risk

Since returns of financial assets generally exhibit skewness and kurtosis, modelling returns using a distribution with the ability to capture both of these statistical aspects will increase the accuracy of risk forecasts based on these distributions. The authors propose the use of the multivariate skew normal (MVSN) mixture model to fit asset returns in order to increase the accuracy of Value-at-Risk (VaR) estimates. This paper presents a novel application of the MVSN mixture model to estimate VaR. There is generally no explicit analytical solution for the parameters of the MVSN mixture model via maximum likelihood estimation (MLE), therefore the use of the Expectation Maximization (EM) Algorithm is proposed in order to find the parameter estimates of the model. The example provided in this paper consists of a portfolio of monthly returns of six shares listed on the Australian Securities Exchange (ASX). The shares are BHP Billiton Limited (BHP), Commonwealth Bank of Australia (CBA), Cochlear Limited (COH), News Corporation (NWS), Origin Energy (ORG), and Wesfarmers Limited (WES). Hence, the dimensionality, p, of this portfolio is six. The period of analysis for the data is 01/01/1998 - 01/04/2011. This paper models the MVSN mixture model with a number of mixtures ranging from one to four. A mixture of multivariate normal densities is modelled for comparison to the MVSN mixture model. We find that for one to three mixtures, the MVSN mixture model provides an improved fit. The improved fit of the MVSN mixture model is translated to the performance of the VaR models, where the results show that for one to three numbers of mixtures, the VaR model using the MVSN mixture model assumption indicates improved risk forecasts when compared to the mixture of multivariate normal densities. Furthermore, for the example examined, we find that the model which incorporates the skewness parameter (MVSN mixture model) requires a fewer number of mixtures when compared to a mixture of normal densities. This is an interesting result as reduced model complexity requires less computational ability, computation time, and will results in decreased computational anomalies

Evaluating Financial Planning Advertisements for Retirement in India: A Content Analysis

For Indians, retirement is neither a formal stage of life nor an issue that people dwell upon while planning their future. Despite the lack of preparation for retirement, a burgeoning population indicates a huge mass of retirees in the coming decades. These statistics trigger the need for individuals to prepare for their retirement appropriately, while accounting for factors like inflation. To highlight the significance of retirement planning and create awareness among the masses, pre-requisites to retirement planning should be effectively communicated. Extant literature suggests advertising to be one such measure of effective communication. This study intended to capture the extent and method of retirement advertisement in the Indian context using 40 television advertisements (ads) of financial institutions focusing on retirement plans. A content analysis revealed that 61% of the ads were non-informative and filled with emotional content. Though celebrity endorsements have effective impact on the Indian audience, only five advertisements used a celebrity to voice their messages. It was concluded that retirement ads need greater focus in India due to the expansive retiring population and the changing family structure in India. The study concluded that financial institutions and banks should focus on this segment and promote their product appropriately

A Study on Hybrid DC Micro-Grid System

With the growing demand of electricity, deployment of microgrid is becoming an attractive option to meet the energy demands. At present, large-scale wind/solar hybrid system is of great potential for development. The large-scale wind/solar hybrid system is of higher reliability compared with wind power generation alone and solar power generation alone However, a grid connected microgrid suffers a crucial stability issues during a fault in utility grid. For stable operation of microgrid during fault in grid. In this paper transient stability of the microgrid is studied during fault in utility grid. This research work presents the design and implementation of a hybrid renewable energy system that allows a cost-efficient and sustainable energy supply of the loads. The integration of the solar system with the network is rather complex and expensive. With this construction proposal, however, it is not only possible to create an economical and simple hybrid system, but also a reliable, efficient and economical system

An algorithm for piece-wise indefinite quadratic programming problem

An indefinite quadratic programming problem is a mathematical programming problem which is a product of two linear factors. In this paper, the piecewise indefinite quadratic programming problem (PIQPP) is considered. Here, the objective function is a product of two continuous piecewise linear functions defined on a non-empty and compact feasible region. In the present paper, the optimality criterion is derived and explained in order to solve PIQPP. While solving PIQPP, we will come across certain variables which will not satisfy the optimality condition. For these variables, cases have been elaborated so as to move from one basic feasible solution to another till we reach the optimality. An algorithmic approach is proposed and discussed for the PIQPP problem. A numerical example is presented to decipher the tendered method