Our experience of laparoscopic vesicovaginal fistula repair in a tertiary care center.

Objective: Laparoscopic repair of vesicovaginal fistula (VVF) is gaining popularity day by day, but we have limited literature on it. This study is to evaluate the safety, feasibility, and outcomes of laparoscopic VVF repair in a tertiary care center in Eastern India.

Subjects And Methods: This study is a single-center retrospective study in which 11 patients of supratrigonal VVF were evaluated who underwent laparoscopic repair.

Comparative Study of the Outcome of Buccal Mucosa Graft Urethroplasty and Preputial Flap Urethroplasty for Anterior Urethral Stricture: A Prospective Randomized Study.

Background: Urethroplasty using a buccal mucosa graft (BMG) and a preputial skin flap (PSF) are two common techniques used for the treatment of anterior urethral stricture. The present study compared the efficacy of these two techniques on the basis of success rate, preservation of sexual function, and complications.

Materials And Methods: This prospective, randomized, interventional study was conducted on adult male patients diagnosed with non-obliterative anterior urethral strictures of length >2 cm from August 2021 to December 2022.

Assessment of Pre-operative Factors Associated With Blood Loss in Patients Undergoing Percutaneous Nephrolithotomy: A Prospective Study.

Background One of the main risks associated with percutaneous nephrolithotomy (PCNL) is bleeding. In the present study, efforts are made to evaluate the pre-operative predictive factors contributing to bleeding due to the procedure of PCNL. Materials and methods From December 2019 to November 2021, data were collected prospectively from 193 patients undergoing PCNL procedures at Indira Gandhi Institute of Medical Sciences, Patna, India.

Pharmaceutically active micropollutants: origin, hazards and removal.

Pharmaceuticals, recognized for their life-saving potential, have emerged as a concerning class of micropollutants in the environment. Even at minute concentrations, chronic exposure poses a significant threat to ecosystems. Various pharmaceutically active micropollutants (PhAMP), including antibiotics, analgesics, and hormones, have been detected in underground waters, surface waters, seawater, sewage treatment plants, soils, and activated sludges due to the absence of standardized regulations on pharmaceutical discharge.

Urinary Tract Infections in Patients Undergoing Invasive Urodynamic Study: A Prospective Observational Study at a Tertiary Care Centre in Eastern India.

Objective: The aim of the study was to find the estimate of the prevalence of urinary tract infections following invasive urodynamic studies (UDS) in a hospital setup and to identify the risk factors related to it.

Method: A total of 100 patients were enrolled in this prospective observational study after standard preoperative work, which included both urine analysis and culture procedure. The study was carried out from April 2022 to April 2023 at the Department of Urology, Indira Gandhi Institute of Medical Sciences, India.

Effect of Smartphone Use on Sleep in Undergraduate Medical Students: A Cross-Sectional Study.

Smartphone use, particularly at night, has been shown to provoke various circadian sleep-wake rhythm disorders such as insomnia and excessive daytime tiredness. This relationship has been mainly scrutinized among patient groups with higher rates of smartphone usage, particularly adolescents and children. However, it remains obscure how smartphone usage impacts sleep parameters in adults, especially undergraduate college students.

The spectrum and etiologies of lower urinary tract symptoms in postmenopausal women.

Background: Although the prevalence of lower urinary tract symptoms (LUTS) is high in the female population, it is even higher in postmenopausal females. The frequency, severity, and etiology of LUTS vary among populations and individuals. This study aimed to define the characteristics of LUTS in postmenopausal women and their underlying etiologies.

Salinity Alleviation and Reduction in Oxidative Stress by Endophytic and Rhizospheric Microbes in Two Rice Cultivars.

Increased soil salinity poses serious limitations in crop yield and quality; thus, an attempt was made to explore microbial agents to mitigate the ill effects of salinity in rice. The hypothesis was mapping of microbial induction of stress tolerance in rice. Since the rhizosphere and endosphere are two different functional niches directly affected by salinity, it could be very crucial to evaluate them for salinity alleviation.

Salinity alleviator bacteria in rice ( L.), their colonization efficacy, and synergism with melatonin.

In this study, rhizospheric and endophytic bacteria were tested for the alleviation of salinity stress in rice. Endophytic isolates were taken from previous studies based on their salt stress-alleviating traits. The rhizospheric bacteria were isolated from rice and screened based on salt tolerance and plant growth-promoting traits.

Interference of bio-control Trichoderma to enhance physical and physiological strength of sugarcane during Pokkah boeng infection.

Tremendous benefits have been derived from the use of fungicides but excessive use of chemical fungicides not only posing threat to human and animal life but also contaminates the prevailing environment. Damage by pathogenic fungi alone causes significant damage to crops like maize, rice, wheat, soybeans, and potatoes. Therefore, it becomes imperative that these diseases are checked and controlled, for which chemical pesticides are being sprayed on plants extensively.

An Artificial Intelligence-Based Reactive Health Care System for Emotion Detections.

In the past few years, remote monitoring technologies have grown increasingly important in the delivery of healthcare. According to healthcare professionals, a variety of factors influence the public perception of connected healthcare systems in a variety of ways. First and foremost, wearable technology in healthcare must establish better bonds with the individuals who will be using them.

Tuberculosis of the prostate gland masquerading prostate cancer; five cases experience at IGIMS.

Objectives: Tuberculosis (TB) of the prostate is a very rare disease. Most urologists are not familiar with it. Here, we present our experience with five cases of this disease and a review of literature.

Plant growth promoting and antifungal activity in endophytic Bacillus strains from pearl millet (Pennisetum glaucum).

Bacterial endophytes are well known inhabitants of living plant system and perform important assignments in maintaining plant growth and health. Currently, limited reports are available on the endophytes of pearl millet (Pennisetum glaucum) reflecting antagonistic and plant growth promoting (PGP) attributes. Therefore, the major objectives of current investigation were to identify antagonistic strains of endophytic Bacillus from pearl millet and further illustrate their PGP capabilities.

Status of research, regulations and challenges for genetically modified crops in India.

A large number of genetically modified (GM) crops, including both food and non-food crops carrying novel traits have been developed and released for commercial agriculture production. Soybean, maize, canola and cotton for the traits insect resistance and herbicide tolerance are the main crops under commercial cultivation worldwide. In addition, many other GM crops are under development and not yet released commercially.

Prediction of Drug-Plasma Protein Binding Using Artificial Intelligence Based Algorithms.

Aim And Objective: Plasma protein binding (PPB) has vital importance in the characterization of drug distribution in the systemic circulation. Unfavorable PPB can pose a negative effect on clinical development of promising drug candidates. The drug distribution properties should be considered at the initial phases of the drug design and development.

Prediction of Human Intestinal Absorption of Compounds Using Artificial Intelligence Techniques.

Background: Information about Pharmacokinetics of compounds is an essential component of drug design and development. Modeling the pharmacokinetic properties require identification of the factors effecting absorption, distribution, metabolism and excretion of compounds. There have been continuous attempts in the prediction of intestinal absorption of compounds using various Artificial intelligence methods in the effort to reduce the attrition rate of drug candidates entering to preclinical and clinical trials.

Promises of Machine Learning Approaches in Prediction of Absorption of Compounds.

The Machine Learning (ML) is one of the fastest developing techniques in the prediction and evaluation of important pharmacokinetic properties such as absorption, distribution, metabolism and excretion. The availability of a large number of robust validation techniques for prediction models devoted to pharmacokinetics has significantly enhanced the trust and authenticity in ML approaches. There is a series of prediction models generated and used for rapid screening of compounds on the basis of absorption in last one decade.

Measurement of Scientific Productivity in R&D Sector: Changing paradigm.

Scientific Productivity is a demand of policy makers for a judicious utilization of massive R&D budget allocated and utilized. A huge mass of intellectual assets is employed, which after investing manpower, infrastructure and lab consumables demand for a major outcome which contributes towards building nation's economy. Scientific productivity was only measured through publications or patents.

Evaluation of Renal Histopathological Changes, as a Predictor of Recoverability of Renal Function Following Pyeloplasty for Ureteropelvic Junction Obstruction.

Background: Pyeloplasty is a widely accepted treatment for ureteropelvic junction obstruction (UPJO). However, the renal function recoverability after pyeloplasty is still a matter of debate. Different parameters have been used to predict renal functional recoverability after corrective surgery, with conflicting results.

Prediction of Metabolism of Drugs using Artificial Intelligence: How far have we reached?

Information about drug metabolism is an essential component of drug development. Modeling the drug metabolism requires identification of the involved enzymes, rate and extent of metabolism, the sites of metabolism etc. There has been continuous attempts in the prediction of metabolism of drugs using artificial intelligence in effort to reduce the attrition rate of drug candidates entering to preclinical and clinical trials.

Current challenges to overcome in the management of type 2 diabetes mellitus and associated neurological disorders.

The increasing worldwide prevalence of type 2 diabetes mellitus (T2DM) and associated neurological disorders (NDs), such as Alzheimer disease and Parkinson's disease, have raised concerns about increasing health care and financial burden. Due to the overwhelming growth rate of T2DM and its strong association with NDs, there is an ever-growing and an urgent need to improve the diagnosis and management of the disease. Major hurdles in the management of T2DM comprise of striving for glycemic targets, polypharmacy, patient adherence and clinical inertia.

Can we predict blood brain barrier permeability of ligands using computational approaches?

An ideal neurotherapeutics agent for central nervous system (CNS) molecular targets should cross Blood Brain Barrier (BBB) whereas peripherally acting agent should not cross BBB to avoid CNS related side effects. Hence prediction of BBB permeability index has been proved to be an efficient tool for drug discovery and development. Various experimental and computational approaches are being used in recent past for the prediction of BBB permeability and they have been successful up to some extent.

Impact of Janani Suraksha Yojana on institutional delivery rate and maternal morbidity and mortality: an observational study in India.

The Government of India initiated a cash incentive scheme--Janani Suraksha Yojana (JSY)--to promote institutional deliveries with an aim to reduce maternal mortality ratio (MMR). An observational study was conducted in a tertiary-care hospital of Madhya Pradesh, India, before and after implementation of JSY, with a sample of women presenting for institutional delivery. The objectives of this study were to: (i) determine the total number of institutional deliveries before and after implementation of JSY, (ii) determine the MMR, and (iii) compare factors associated with maternal mortality and morbidity.

Application of microarray in breast cancer: An overview.

There are more than 1.15 million cases of breast cancer diagnosed worldwide annually. At present, only small numbers of accurate prognostic and predictive factors are used clinically for managing the patients with breast cancer.