International Journal of Life Sciences Biotechnology and Pharma Sciences
type: channel
description: • Editor- In-Chief: Dr. Mai S. Mabrouk • Title proper: International Journal of Life Sciences Biotechnology and Pharma Sciences (IJLBPS) • Subject: Biotechnology and Pharma Sciences • Publisher: Unicorn Publications • Dates of publication: 2013 • Issn: 2395-650X • Frequency: Quarterly • Language: English • Country: India • Medium: Online • Indexed by: CROSSREF • Indexed by: ROAD,THE KEEPERS • Title DOI of the Journal: http://doi.org/10.62648 /issn.2395-650X
publisher: Unicorn Publications
language: en
publication name: International Journal of Life Sciences Biotechnology and Pharma Sciences
issn: 2395-650X
items: Biomarker-Based Clinical Evaluation in Precision Medicine
items: AI-Assisted Molecular Docking for Novel Drug Discovery
items: Translational Approaches in Biopharmaceutical Development
items: In Silico Drug Repurposing Using Machine Learning Models
items: Pharmacogenomics in Personalized Medicine Approaches
items: Nanoparticle-Based Drug Delivery Systems in Targeted Therapy
items: Using homeopathic medications to treat lung cancer
items: Screening, production, optimization, characterization, pharmacological analysis and applications of Exopolysaccharide from Marine Bacteria: A Review
items: Enhancement of Solubility and Dissolution of BCS Class II Drugs Using Solid Dispersion Technique
items: Simultaneous Estimation of Antihypertensive Drugs Using Derivative Spectroscopy
items: Analysis of renal stone chemical composition
items: Inguinal hernia repair patients risk of infection and the frequency of surgical site complications necessitating intervention
items: Placebo-controlled trials on the safety and efficacy of tiotropium bromide in patients with chronic obstructive pulmonary disease and bronchitis
items: Animal feed contaminated with Salmonella and the pig industry: a comparative analysis
items: AI-DRIVEN CLOUD HEALTHCARE SYSTEM FOR PREDICTIVE ANALYSIS OF CARDIOVASCULAR DISEASES
items: Leveraging Cloud Computing and Recurrent Neural Networks for Scalable Healthcare Solutions and Resource Management
items: Healthcare Data Classification for Lung Cancer Detection Using Efficient Net with Cloud Storage
items: EFFECT OF MERCURIC SULPHATE AND CADMIUM SULPHATE ON THE OXYGEN CONSUMPTION AND RATE OF OXYGEN CONSUMPTION IN ESTUARINE CRAB SCYLLA SERRATA
items: AI-BASED CLASSIFICATION AND DETECTION OF BRAIN TUMORS IN HEALTHCARE IMAGING DATA
items: Scalable Medical Image Analysis Using CNNs and DFS with Data Sharding for Efficient Processing
items: Scalable Healthcare Analytics in the Cloud: Applying Bayesian Networks, Genetic Algorithms, and LightGBM for Pediatric Readmission Forecasting
items: Effectiveness of Combined Open and Closed Kinetic Chain Exercises for Treating Shin Splints in Football Players
items: An investigation into the prevalence of anemia in patients diagnosed with type 2 diabetes mellitus who were treated at a tertiary care hospital
items: The fruit of the plant Terminalia belerica Roxb. : a phytochemical and pharmacological assessment
items: DEVELOPMENT AND CHARACTERIZATION OF WHOLE MILK AND COCONUT MILK PANEER INCORPORATED WITH SPINACH LEAF
items: Comprehensive Strategies and Emerging Trends in the Global Fight Against Malaria
items: PHARMACOPOEIA
items: Preservatives used in Pharmaceuticals and impact on Health
items: Synthesis, Characterization and Antimicrobial Activity of Zinc Oxide Nanoparticles Synthesized From Calotropis procera
items: Synthesis, Characterization and Antimicrobial Evaluation of Some Tetrahydroquinazoline Derivatives of Benzo[b]thiophene

Biomarker-Based Clinical Evaluation in Precision Medicine
type: item
description: Biomarkers--measurable indicators of biological state, disease progression, or therapeutic response--are the operational foundation of precision medicine, enabling patient stratification, treatment selection, response monitoring, and surrogate endpoint assessment across oncology, cardiovascular disease, neurodegeneration, and autoimmunity. This study develops and validates a multi-omics biomarker panel for precision stratification and treatment response prediction in three high-burden diseases: non-small cell lung cancer (NSCLC, n=312 patients), heart failure with reduced ejection fraction (HFrEF, n=287 patients), and rheumatoid arthritis (RA, n=248 patients), across clinical sites in Austria, Estonia, and Switzerland. An integrated biomarker discovery pipeline combining liquid biopsy (circulating tumour DNA, ctDNA; cell-free RNA, cfRNA), serum proteomics (proximity extension assay, 1,472 proteins), and digital biomarkers (wearable-derived heart rate variability, physical activity) with machine learning ensemble classification (gradient boosting + penalised Cox regression) identified and validated a 12-biomarker precision panel per disease. NSCLC: the ctDNA-protein panel predicted osimertinib response with AUROC 0.924 and enabled molecular residual disease (MRD) detection at sensitivity 94.7% / specificity 91.2% in post-surgical monitoring. HFrEF: a 12-protein + HRV composite biomarker predicted 12-month MACE with AUROC 0.891, outperforming NT-proBNP alone (AUROC 0.741). RA: a serum proteomic signature predicted methotrexate non-response with AUROC 0.874 at 8 weeks, enabling early treatment switching before the standard 24-week assessment. Biomarker analytical validation confirmed clinical-grade reproducibility (CV < 10% within-run; CV < 15% between-run) for all 36 validated analytes. Health economic modelling demonstrated positive cost-effectiveness ratios for all three precision biomarker strategies relative to standard-of-care monitoring.
subject: Articles
  topic: section
subject: Biomarkers
  topic: keywords
subject: Precision medicine
  topic: keywords
subject: Liquid biopsy
  topic: keywords
subject: ctDNA
  topic: keywords
subject: Serum proteomics
  topic: keywords
creator: Hugo Novak
creator: Clara Bianchi
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2026-01-01
publication date: 2026-01-01
starting page: 19
ending page: 27
doi: 10.62648/v22.i01.2026.pp19-27

AI-Assisted Molecular Docking for Novel Drug Discovery
type: item
description: Molecular docking--the computational prediction of small molecule binding poses and affinities at protein active sites--is a cornerstone of structure-based drug discovery, yet classical docking methods suffer from limitations in scoring function accuracy, conformational sampling completeness, and computational throughput that constrain their utility for large-scale virtual screening of multi-billion-compound chemical libraries. Artificial intelligence has transformed molecular docking through deep learning scoring functions, generative molecular design, and end-to-end docking architectures that directly predict binding poses without explicit energy minimisation. This study develops and benchmarks an AI-assisted drug discovery pipeline integrating four AI components: (i) SE(3)-equivariant GNN-based binding site prediction (SiteNet); (ii) DiffDock-v2 blind docking with improved confidence calibration; (iii) a graph transformer-based scoring function (GraphDTA-v2) fine-tuned on the PDBbind 2024 dataset; and (iv) a conditional variational graph autoencoder (CVGAE) for de novo ligand generation optimised for predicted binding affinity. The pipeline was applied to three high-priority drug targets: SARS-CoV-2 main protease (Mpro), drug-resistant EGFR (T790M/C797S double mutant), and IDH1 (R132H oncogenic mutant). Against the CASF-2016 benchmark, GraphDTA-v2 achieved a Pearson correlation of 0.869 between predicted and experimental pKd values, outperforming AutoDock Vina (r=0.614) and Glide SP (r=0.703). DiffDock-v2 achieved 51.3% top-1 RMSD<2A success rate on PoseBusters v2 benchmark. CVGAE-generated ligands for Mpro demonstrated mean QED of 0.847 and predicted pKd of 8.41 (nM affinity range), with 12 of 500 generated compounds predicted with higher affinity than nirmatrelvir. Four top-ranked generated compounds were synthesised and validated by SPR, with Kd values of 47-284 nM confirming AI-predicted binding, representing successful end-to-end AI-assisted drug discovery f…
subject: Articles
  topic: section
subject: Molecular docking
  topic: keywords
subject: Deep learning
  topic: keywords
subject: DiffDock
  topic: keywords
subject: GraphDTA
  topic: keywords
subject: De novo drug design
  topic: keywords
subject: CVGAE
  topic: keywords
creator: Hugo Garcia
creator: Erik Popescu
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2026-01-01
publication date: 2026-01-01
starting page: 10
ending page: 18
doi: 10.62648/v22.i01.2026.pp10-18

Translational Approaches in Biopharmaceutical Development
type: item
description: Biopharmaceutical development--encompassing monoclonal antibodies, antibody-drug conjugates, bispecific antibodies, gene therapies, cell therapies, and RNA therapeutics--has transformed oncology, autoimmunity, and rare disease treatment over the past three decades, yet the translational gap between promising preclinical candidate and successful clinical drug remains the most formidable challenge in the field, with first-in-human to approval success rates of 11.5% overall and as low as 5.1% for oncology biologics. This review systematically analyses the translational bottlenecks at each stage of the biopharmaceutical development pipeline--from target validation and lead molecule selection, through preclinical pharmacology and toxicology, first-in-human dose selection, Phase I biomarker strategy, and late-stage adaptive trial design--and evaluates the evidence base for emerging strategies that are improving translational success rates. Key advances reviewed include: patient-derived organoid (PDO) and microphysiological system (MPS) platforms that bridge the rodent-human species gap in pharmacology prediction; quantitative systems pharmacology (QSP) modelling for human PK/PD extrapolation and clinical dose optimisation; companion diagnostic co-development strategies that enrich trial populations for responders; adaptive Bayesian phase II/III seamless trial designs that accelerate proof-of-concept decision-making; and the evolving regulatory science framework for accelerated approval pathways (Breakthrough Therapy, PRIME) that have compressed median approval timelines by 3.2 years relative to standard review. Case studies from approved biopharmaceuticals--trastuzumab deruxtecan (T-DXd), tisagenlecleucel (Kymriah), inclisiran, and nusinersen--illustrate the application of these translational principles to diverse modality classes. The review concludes by identifying artificial intelligence integration, digital biomarkers, and decentralised clinical trial models as the th…
subject: Articles
  topic: section
subject: Biopharmaceutical development
  topic: keywords
subject: Translational medicine
  topic: keywords
subject: First-in-human
  topic: keywords
subject: Organoid models
  topic: keywords
subject: Quantitative systems pharmacology
  topic: keywords
subject: Companion diagnostics
  topic: keywords
creator: Oscar Moreau
creator: Elena Silva
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2026-01-01
publication date: 2026-01-01
starting page: 01
ending page: 09
doi: 10.62648/v22.i01.2026.pp1-9

In Silico Drug Repurposing Using Machine Learning Models
type: item
description: Drug repurposing--the systematic identification of new therapeutic indications for approved or investigational drugs--offers a time- and cost-efficient alternative to de novo drug discovery, leveraging existing safety profiles and pharmacokinetic data to accelerate clinical translation. Machine learning has emerged as the dominant computational paradigm for large-scale in silico drug repurposing, enabling the integration of heterogeneous biomedical data sources--drug-target interaction networks, gene expression signatures, chemical structure fingerprints, disease-gene associations, and electronic health record phenome-wide associations--into unified predictive frameworks that can generate repurposing hypotheses across thousands of drug-disease pairs simultaneously. This study develops and benchmarks five machine learning architectures for drug repurposing prediction: a gradient boosting machine (GBM), a graph neural network (GNN) operating on drug-target-disease heterogeneous networks, a variational autoencoder (VAE) learning latent drug-disease embeddings from transcriptomic signatures, a transformer-based multi-modal fusion model integrating structure, target, and phenotype features, and a knowledge graph embedding model (TransE/RotatE). Evaluated on the Gottlieb benchmark (593 drugs, 313 diseases, 1,933 known associations) using 10-fold cross-validation, the transformer fusion model achieved the highest AUROC of 0.947 and AUPR of 0.891, outperforming GNN (AUROC 0.923), VAE (AUROC 0.908), GBM (AUROC 0.874), and TransE (AUROC 0.856). Prospective validation of the top 50 novel repurposing predictions against post-2020 clinical trial registrations confirmed 14 of 50 predictions (28%) as having entered clinical evaluation--substantially higher than the 3-5% random baseline. Highlighted top predictions include metformin for hepatocellular carcinoma (supported by GWAS and observational evidence), baricitinib for amyotrophic lateral sclerosis (now in Phase II trial), and…
subject: Articles
  topic: section
subject: Drug repurposing
  topic: keywords
subject: Machine learning
  topic: keywords
subject: Graph neural network
  topic: keywords
subject: Transformer
  topic: keywords
subject: Knowledge graph embedding
  topic: keywords
creator: Daniel Lindberg
creator: Matteo Klein
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-09-01
publication date: 2025-09-01
starting page: 19
ending page: 27
doi: 10.62648/v21.i04.2025.pp19-27

Pharmacogenomics in Personalized Medicine Approaches
type: item
description: Pharmacogenomics--the study of how genetic variation influences individual drug response in terms of efficacy, toxicity, and dosing requirements--has transitioned from a research discipline to a clinical standard of care across oncology, psychiatry, cardiology, and infectious disease over the past two decades, driven by the declining cost of genotyping and the accumulating body of clinically actionable pharmacogenomic (PGx) associations validated in prospective trials. This review comprehensively surveys the current landscape of pharmacogenomics in personalised medicine, covering: the molecular basis of PGx variation in drug-metabolising enzymes (CYP450 family, UGT1A1, TPMT, DPYD), drug transporters (SLCO1B1, ABCB1), and drug targets (VKORC1, EGFR, KRAS, HER2); clinical implementation evidence from landmark trials including CPIC guideline-supported drug-gene pairs; the expanding role of polygenic risk scores (PRS) in drug response prediction beyond single-variant pharmacogenomics; current clinical decision support integration challenges; and the regulatory and health economic framework for PGx-guided prescribing. Key clinically validated examples reviewed include: warfarin dosing guided by CYP2C9/VKORC1/CYP4F2 genotype (reducing serious bleeding events by 31-43%); clopidogrel response prediction by CYP2C19 loss-of-function alleles (associated with 3.58-fold increased MACE risk in poor metabolisers); DPYD genotyping before fluoropyrimidine chemotherapy (reducing severe toxicity from 35% to 4.7%); and HER2/KRAS/BRAF tumour genotyping directing targeted therapy selection in metastatic colorectal and breast cancer. Remaining implementation barriers including incomplete population diversity in PGx reference datasets, clinical workflow integration complexity, and reimbursement heterogeneity across European healthcare systems are critically evaluated alongside emerging opportunities from direct-to-consumer genomics, preemptive panel genotyping, and AI-guided phenotype pred…
subject: Articles
  topic: section
subject: Pharmacogenomics
  topic: keywords
subject: Personalized medicine
  topic: keywords
subject: CYP450
  topic: keywords
subject: Drug metabolism
  topic: keywords
subject: CPIC guidelines
  topic: keywords
creator: Oscar Kovacs
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-09-01
publication date: 2025-09-01
starting page: 10
ending page: 18
doi: 10.62648/v21.i04.2025.pp10-18

Nanoparticle-Based Drug Delivery Systems in Targeted Therapy
type: item
description: Nanoparticle-based drug delivery systems (NDDS) have emerged as a transformative platform for targeted cancer therapy, enabling selective accumulation of cytotoxic payloads at tumour sites while reducing systemic toxicity through passive enhanced permeability and retention (EPR) effect exploitation and active ligand-mediated receptor targeting. This study designs, synthesises, and characterises four nanoparticle platforms--PLGA polymeric nanoparticles (PNPs), PEGylated liposomes (PLips), gold nanoparticles (AuNPs), and mesoporous silica nanoparticles (MSNs)--loaded with doxorubicin (DOX) and functionalised with folate receptor-targeting ligands (folic acid, FA) for selective delivery to folate receptor-overexpressing cancer cell lines (HeLa, MCF-7, A549). Nanoparticles were comprehensively characterised by dynamic light scattering (DLS), transmission electron microscopy (TEM), zeta potential, FTIR, and XRD. In vitro drug release profiling under physiological (pH 7.4) and tumour microenvironment (pH 5.5) conditions demonstrated pH-responsive release, with MSN-DOX-FA achieving 84.7% cumulative DOX release at pH 5.5 versus 24.3% at pH 7.4 over 72 hours. Cellular uptake quantified by flow cytometry and confocal microscopy showed 3.8-4.6-fold higher uptake of folate-functionalised versus non-functionalised nanoparticles in FR-overexpressing cells. MTT cytotoxicity assays demonstrated IC50 values of 0.84-1.47 ug/mL for targeted NDDS versus 8.2-14.7 ug/mL for free DOX in HeLa, MCF-7, and A549 cells, representing 6-18-fold potency enhancement. In vivo efficacy in HeLa xenograft BALB/c nude mice showed 74.3% tumour volume reduction with MSN-DOX-FA at day 21 versus 41.8% for free DOX at equivalent dose, with significantly reduced cardiotoxicity (troponin I: 0.84 vs. 4.21 ng/mL, p < 0.001).
subject: Articles
  topic: section
subject: Nanoparticle drug delivery
  topic: keywords
subject: PLGA nanoparticles
  topic: keywords
subject: PEGylated liposomes
  topic: keywords
subject: Gold nanoparticles
  topic: keywords
subject: Mesoporous silica
  topic: keywords
creator: Lea Hansen
creator: Marco Dubois
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-09-01
publication date: 2025-09-01
starting page: 01
ending page: 09
doi: 10.62648/v21.i04.2025.pp1-9

Using homeopathic medications to treat lung cancer
type: item
description: Both in vitro and in vivo, in both people and animals, and in both lower and higher potencies, homeopathic medications have shown biological effect in the treatment of cancer. Cancer patients must make a life-or-death choice on their course of therapy. It would seem reasonable and worthwhile, even urgent, to increase research on and even the provision of homeopathic treatment for lung cancer and other diseases, since the majority of conventional treatments are still linked to serious side effects and occasionally fatal outcomes, whereas homeopathy has been found to be free of such effects.
subject: Articles
  topic: section
subject: Drugs
  topic: keywords
subject: cancer
  topic: keywords
subject: diseases
  topic: keywords
creator: Dr Vipul Avinash Shilahar
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-08-28
publication date: 2025-08-28
starting page: 33
ending page: 38

Screening, production, optimization, characterization, pharmacological analysis and applications of Exopolysaccharide from Marine Bacteria: A Review
type: item
description: Exopolysaccharides (EPS) is a group of high molecular weight biopolymers produced during the metabolic process of some microorganisms. A broad class of exopolysaccharides (EPSs) are produced by microbes in response to environmental stressors such salt, pH, temperature, and light intensity. Microbial marine exopolysaccharides (EPS) are one of the essential and functional commercial-grade products and have several biotechnological applications. Exopolysaccharides (EPSs) from microorganisms are essential harmless natural biopolymers used in applications including medications, nutraceuticals and functional foods, cosmetics, and insecticides. Isolating new EPSs with unique functionalities and unique chemical and physical characteristics is gaining attention. In this sense, a vast number of unidentified and uncultivated bacteria that are capable of producing and excreting EPSs can be found in the marine environment. The structure of EPS is complex and difficult to analyze, resulting in difficulties in investigating their structure–activity relationship, and its specific mechanism of action has not yet been revealed. . The characterization studies, structural and pharmaceutical analysis are crucially important parameters that need to be studied and those headings are discussed in this review.
subject: Articles
  topic: section
subject: Exopolysaccharide,
  topic: keywords
subject: Marine organisms
  topic: keywords
subject: Characterization technique
  topic: keywords
subject: pharmaceutical analysis
  topic: keywords
creator: Edward C
creator: Sangeetha M
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-09-08
publication date: 2025-09-08
starting page: 1
ending page: 7

Enhancement of Solubility and Dissolution of BCS Class II Drugs Using Solid Dispersion Technique
type: item
description: The purpose of this study was to develop a solvent evaporation technique for improving the solubility of poorly soluble drugs, such as fluvoxamine tablets. Fluvoxamine is an antidepressant medication that is a selective serotonin reuptake inhibitor (SSRI). The goal is to enhance the biological performance of Fluvoxamine by using a solid dispersion method since the BCS class II medication has poor oral bioavailability and low water solubility. Methodology: The medication Fluvoxamine was created utilizing the solvent evaporation process. Fluvoxamine solid dispersions were made using various carriers in PEG 6000 and mannitol ratios of 1:1, 1:2, and 1:3. Findings: Findings from Fluvoxamine solid dispersions made using the solid dispersion technique Lastly, a comparison of all the formulations reveals that formulation (SF3), which contains fluvoxamine and PEG 6000 (1:3), performs better. We came to the conclusion that the solvent evaporation solid dispersion process improves the solubility of poorly soluble drugs. We also produced six Fluvovamine formulations (FDF1–FDF6), and FDF4 exhibits the highest drug release at the end of time (98.9±0.8%).
subject: Articles
  topic: section
subject: mannitol
  topic: keywords
subject: PEG 6000
  topic: keywords
subject: fluvoxamine
  topic: keywords
subject: antidepressant
  topic: keywords
subject: solvent evaporation
  topic: keywords
subject: direct compression technique
  topic: keywords
creator: Dr. K. Gopaiah
creator: Dr. Ch. Maheshwara Reddy
creator: Dr M. Balaji Yadav
creator: Dr. V. S. N. Murthy
rights: Copyright (c) 2024 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-08-30
publication date: 2024-08-30
starting page: 6
ending page: 15

Simultaneous Estimation of Antihypertensive Drugs Using Derivative Spectroscopy
type: item
description: For the simultaneous measurement of atorvastatin calcium and amlodipine besylate, a straightforward, accurate, and precise UV spectroscopic approach has been established. The established approach of simultaneous equations is cost-effective and repeatable. 365 and 246 nm were the wavelengths used to measure the absorbance of the two medications, respectively. Amlodipine besylate and atorvastatin calcium showed linearity at their respective λmaxes of 365 and 246 nm as well as at the isoabsorptive point at 238 nm in a concentration range of 2 to 10 μg/mL. The accuracy of the approach was shown by recovery trials, which showed recovery of >99.78% for amlodipine besylate and >99.36% for atorvastatin calcium. The proposed approach is recommended for regular analysis due to its speed, ease of use, accuracy, sensitivity, and specificity. The International Council of Harmonization's (ICH) guidelines were followed for conducting the validation investigations.
subject: Articles
  topic: section
subject: UV spectroscopy
  topic: keywords
subject: atorvastatin calcium
  topic: keywords
subject: amlodipine besylate
  topic: keywords
subject: simultaneous equation approach
  topic: keywords
creator: Dr. P. Venkateswara Rao
creator: Dr. Sk. Abdul Jabbar Basha
creator: T. Raja
creator: Dr. Himaja Trivedi
rights: Copyright (c) 2024 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-07-31
publication date: 2024-07-31
starting page: 1
ending page: 5

Analysis of renal stone chemical composition
type: item
description: Context: Nephrolithiasis is a common condition that affects many people, especially those in their working years. The incidence of this condition is increasing and varies greatly throughout the world's areas. In order to determine the chemical make-up of kidney stones, the current investigation was carried out. Procedures and Supplies: For this study, 54 individuals with renal stones were chosen. The samples were first swabbed to check for microbes, then rinsed in deionized water and allowed to dry. A variety of morphological traits, such as form, color, and texture, were noted. To determine how opaque the stones were, they were X-rayed. Using a scalpel, the kidney stone's core and surface parts were sliced. In order to obtain a fine, uniform powder for qualitative measurement of different components, it was pounded using a pestle and mortar. Thirty men and twenty-four ladies made up the 54 patients. The chemical composition varied among the participants: 3 men and 2 females tested positive for inorganic compounds, 6 men and 4 females for carbonate, 4 men and 3 females for oxalate, 6 men and 5 females for phosphate, 3 men and 3 females for ammonia, 2 men and 3 females for uric acid, 4 men and 3 females for magnesium, and 2 men and 3 females for organic compounds. (P> 0.05) The disparity was not statistically significant. There were 5 males and 3 females with a sterile bacterial profile, 7 males and 6 females with a Proteus profile, 2 males and 2 females with candidain, 1 female with P aeruginosa, 2 males and 1 female with Citrobacter diversus, 2 males and 1 female with Citrobacter Freudenreichii, 6 males and 7 females with Enterobacter species, 1 male and 1 female with staphylococcus aureus, and 5 males and 2 females with contaminated results. (P> 0.05) The disparity was not statistically significant. In sum: Patients most often had Proteus spp. infections, which may result from poor urine drainage and cause persistent UTIs, as shown by the presence of MgNH4 PO4 (st…
subject: Articles
  topic: section
subject: microbes, then rinsed deionize
  topic: keywords
creator: Dr. Sai Kiran
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-06-18
publication date: 2025-06-18
starting page: 28
ending page: 31

Inguinal hernia repair patients risk of infection and the frequency of surgical site complications necessitating intervention
type: item
description: Surgical correction of inguinal hernias is a common and necessary operation for treating the protrusion of abdominal contents via a weak spot in the inguinal region. The primary goal of this research is to determine how often after inguinal hernia repairs patients have surgical site infections and how often these infections need further procedures. A total of 350 patients who had inguinal hernia repairs had their data gathered in this retrospective observational analysis. The information for the 350 patients who had inguinal hernia repairs was culled from electronic medical records (EMRs) and surgical logs. We meticulously documented patient data, including age, gender, BMI, smoking status, and the presence of comorbidities such COPD and diabetes mellitus. The results showed that out of 350 patients, 70% were male and 30% were female, with a mean age of 55 years. Patients smoked at a rate of 40% and had an average BMI of 28.5 kg/m². Half of the people in the group had diabetes, and another 15% had COPD. Twelve percent of the three hundred and fifty patients had surgery site infections (SSIs), with the rate being thirteen percent higher in the open repair group compared to the laparoscopic group (9.2%). Out of the 16 patients who had surgical site occurrences (SSOs), 8% had seromas, 5% had hematomas, and 2.8% had wound dehiscence. Researchers have shown that individuals with risk factors such diabetes mellitus, smoking, and mesh usage are more likely to get surgical site infections (SSIs) and surgical site occurrences (SSOs), which are serious problems that may occur after inguinal hernia surgery. Retrospective investigation including inguinal hernia and infections at surgery sites
subject: Articles
  topic: section
subject: electronic medical records
  topic: keywords
creator: Krishna Kumar
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-06-10
publication date: 2025-06-10
starting page: 23
ending page: 27

Placebo-controlled trials on the safety and efficacy of tiotropium bromide in patients with chronic obstructive pulmonary disease and bronchitis
type: item
description: Although asthma may strike at any age, it most often manifests in children. A person with this condition may experience wheezing and shortness of breath on a regular basis, the intensity of which might vary from person to person. As per the World Health Organization (WHO), Asthma affects an increasing global population of 100–150 million people, or about the same as the population of the Russian Federation. Over 180,000 people each year are losing their lives to this illness on a global scale. Both asthma and chronic obstructive pulmonary disease (COPD) are airway illnesses with clear clinical definitions, yet each has its own unique pathophysiology and therapeutic response. The safety profile of tiotropium is similar to that of a placebo, and it is well-tolerated. Resting bronchomotor tone in chronic obstructive pulmonary disease (COPD) is thought to be mostly caused by the parasympathetic nervous system, which is thought to play a significant role in the autonomic regulation of airways. With that in mind, we set out to compare 18mcg of tiotropium metered dose inhalation to a placebo group of individuals with chronic obstructive pulmonary disease (COPD) and bronchial asthma over the course of 14 weeks. Tiotropium, when administered once daily by dry powder inhaler at a dosage of 18 mcg, improved bronchial asthma and chronic obstructive pulmonary disease (COPD) symptoms for at least 24 hours. From a clinical and spirometric perspective, the medication is effective and safe. Reduced symptom severity, less need for rescue medicine, and fewer acute episodes were all outcomes of our research.
subject: Articles
  topic: section
subject: bronchial asthma, chronic obstructive pulmonary disease, tiotropium, PLACEBO
  topic: keywords
creator: Srinidhi
creator: Madhan Mohan
creator: Vijaya Laxmi
creator: G Raju
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-06-27
publication date: 2025-06-27
starting page: 10
ending page: 22

Animal feed contaminated with Salmonella and the pig industry: a comparative analysis
type: item
description: Animal feed account for more than 75% total cost of production in pig industry and feed spoilage is a common factor as well as disease infection. These negative factors were influenced on production process in pig industry. Hence animal feeds and faecal samples were collected from pig farms and analyzed for microbial prevalence. The results revealed that the pathogenic microorganisms that can be zoonotic in nature E. coli staphylococcus and bacillus species of microbes were most prevalent
subject: Articles
  topic: section
subject: Animal feed, Microbial prevalence, Pig industry
  topic: keywords
creator: Deepika
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-06-10
publication date: 2025-06-10
starting page: 1
ending page: 9

AI-DRIVEN CLOUD HEALTHCARE SYSTEM FOR PREDICTIVE ANALYSIS OF CARDIOVASCULAR DISEASES
type: item
description: Cardiovascular disease (CVD) is still one of the world's main reasons of mortality, imposing considerable burdens on healthcare systems and economies, and hence requiring timely and precise risk prediction for enhanced patient outcomes. The existing CVD risk assessment approaches, such as statistical models and traditional machine learning methods, have limitations like poor scalability, poor management of heterogeneous data, poor handling of timely processing, and weaknesses in data privacy, which hamper their seamless integration into clinical workflows. To bridge these loopholes, this study proposes a hybrid AI framework combining Deep Neural Networks (DNN) and XGBoost on a cloud-native platform that enables smooth processing of big data without causing non-compliance with security expectations. The originality of this approach is that it is a fusion of ensemble learning and deep learning within a cloud-based secure environment which allows for real-time model updating and individualized risk estimation. The experimental results determine greater predictive ability, 99.95% precision, F1 measure of 98.99%, and highly balanced values of recall and precision, considerably surpassing baseline models such as individual XGBoost, Random Forest and CNN-LSTM hybrids. The hybrid architecture demonstrates greater robustness, less false negative and higher clinical utility compared to existing methods. This advancement significantly enhances the feasibility of early diagnosis and facilitates scalability for deployment with flexibility across a variety of healthcare applications. Future research attempts to further minimize false negatives, include multimodal data sources, and enhance model interpretability.
subject: Articles
  topic: section
subject: CVD
  topic: keywords
subject: DNN
  topic: keywords
subject: XGBoost
  topic: keywords
subject: Cloud Healthcare
  topic: keywords
subject: Machine Learning
  topic: keywords
subject: Predictive Modelling
  topic: keywords
subject: Hybrid AI mode
  topic: keywords
creator: Sachin Kumar Agrawal
creator: Kanwarjit Zakhmi
creator: Aiswarya RS
rights: Copyright (c) 2023 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2023-07-24
publication date: 2023-07-24
starting page: 21
ending page: 31

Leveraging Cloud Computing and Recurrent Neural Networks for Scalable Healthcare Solutions and Resource Management
type: item
description: The joint efforts of Cloud Computing and Recurrent Neural Network (RNN) represent a new revolution in the healthcare sector, bringing along flexible, scalable, and affordable ways to monitor patients or manage resource usage. The cloud here would be an elastic infrastructure using which healthcare institutions can save, access, and process health data in a more secure manner with less dependence on costly hardware. It has pretty much proved only-in-human resource to be reliable for sequential data, making the patient health information time-dependent patient health information an exceptional example for this application. The RNN model achieved an 85% accuracy and 87% precision that show how efficiently it could predict diabetes. Well, this framework is said to enhance patient care due to the prediction of health outcomes and intervention in time. Data security is still a problem, and with the complexity of RNN models, advanced encryption and model simplification techniques are required. Altogether, the combination of RNNs with cloud technologies will probably add a lot to early diagnosis, patient care, and efficiency in a health-care facility, and therefore definitely address the new growing demands in health care.
subject: Articles
  topic: section
subject: Cloud Computing
  topic: keywords
subject: Recurrent Neural Network (RNN)
  topic: keywords
subject: Healthcare
  topic: keywords
subject: Scalable Infrastructure
  topic: keywords
subject: Patient Monitoring
  topic: keywords
creator: Dharma Teja Valivarthi
creator: Veerandra Kumar R
rights: Copyright (c) 2019 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2019-04-16
publication date: 2019-04-16
starting page: 31
ending page: 40

Healthcare Data Classification for Lung Cancer Detection Using Efficient Net with Cloud Storage
type: item
description: Lung carcinoma is one of the deadliest cancers globally, and early diagnosis is crucial for improving patient survival rates. This study introduces an innovative approach to detect lung cancer using a combination of Efficient Net and cloud storage, which ensures scalable and efficient processing of medical images. By leveraging deep learning and cloud computing, the system automatically analyzes CT scans and X-rays to identify potential signs of lung cancer. Efficient Net, a lightweight deep learning model, optimizes computational resources while maintaining high accuracy in image classification, thereby reducing costs. The cloud infrastructure facilitates real-time data access, allowing healthcare providers to quickly retrieve and analyze patient images from anywhere. Additionally, the cloud supports continuous model updates, ensuring that the detection system improves over time. The model's performance has been evaluated across multiple metrics, demonstrating its effectiveness as a reliable tool for early lung cancer detection, which can be integrated into clinical practices for enhanced patient outcomes.
subject: Articles
  topic: section
subject: Cloud Computing
  topic: keywords
subject: Health Care
  topic: keywords
subject: Efficient Net
  topic: keywords
creator: Madhusanka
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-01-18
publication date: 2025-01-18
starting page: 18
ending page: 30

EFFECT OF MERCURIC SULPHATE AND CADMIUM SULPHATE ON THE OXYGEN CONSUMPTION AND RATE OF OXYGEN CONSUMPTION IN ESTUARINE CRAB SCYLLA SERRATA
type: item
description: Physiological responses oxygen consumption of estuarine crab Scylla serrata were exposed to the sub-lethal concentration of cadmium sulphate and mercuric sulphate for the present investigation up to 24, 48, 72, 96, 120 hrs (17.2mg/L, 6 mg/L), respectively. The oxygen consumption was initially slight increased (24 hrs) and then decreased throughout the experiment in both the treated groups as compared with control group.
subject: Articles
  topic: section
subject: Scylla serrata
  topic: keywords
subject: Cadmium sulphate
  topic: keywords
subject: Mercuric sulphate
  topic: keywords
creator: Dr. P. P. Sawant
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-01-24
publication date: 2025-01-24
starting page: 8
ending page: 17

AI-BASED CLASSIFICATION AND DETECTION OF BRAIN TUMORS IN HEALTHCARE IMAGING DATA
type: item
description: This study proposes an AI-driven framework for brain tumour detection using explainable AI (XAI) and deep learning to enhance diagnostic accuracy and transparency in healthcare imaging. The methodology integrates cloud-hosted MRI datasets, pre-processed via Median Filtering and Contrast-Limited Adaptive Histogram Equalization (CLAHE), with an EfficientNet-based classifier optimized through compound scaling and auxiliary classifiers. SHAP (Shapley Additive Explanations) provides interpretable insights into model decisions, ensuring clinical trust. Results demonstrate high accuracy (99.0%), though lower precision (90.94%) and recall (90.55%) highlight challenges in class balance. The ROC curve’s marginal AUC (0.5439) underscores limitations in tumour vs. healthy tissue discrimination. Despite computational demands and protocol dependencies, the framework offers a scalable, privacy-preserving solution for clinical deployment, bridging gaps between AI performance and interpretability in oncology.
subject: Articles
  topic: section
subject: Contrast-Limited Adaptive Histogram Equalization(CLAHE)
  topic: keywords
subject: SHAP(Shapley Additive Explanations)
  topic: keywords
subject: Google Cloud Platform (GCP)
  topic: keywords
creator: Himabindu Chetlapalli
creator: S Bharathidasan
rights: Copyright (c) 2018 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-04-26
publication date: 2025-04-26
starting page: 18
ending page: 26

Scalable Medical Image Analysis Using CNNs and DFS with Data Sharding for Efficient Processing
type: item
description: Cloud computing essentially improves accessibility of patient records, medical images, and sensor information by enabling the effective management, processing, and storage of large amounts of medical data. However, traditional systems are often very limited in capacity, in addition to having problems about real-time processing of data, and security. This makes the management of massive health data volumes ineffective and results to delays in diagnosis. Due to limits in data administration and processing capabilities, earlier systems have a hard time ensuring high availability of and reliable interpretation of medical images. Our architecture employs a cloud-based infrastructure, which works jointly with Distributed File Systems (DFS) and data sharding strategies to facilitate scaling and optimization of resource allocation. The approach employs Convolutional Neural Networks (CNN) for medical image analysis, whereby accuracy is improved in terms of diagnostics and abnormality detection. At 95% model accuracy, precision lies at 93%, recall at 91%, and a score of 0.97 for the AUC-ROC. In addition, the throughput is improved to 5 TB per hour at a cost of $100 per TB. This study has furthered the design of a scalable, secure, and high-performing healthcare data management system with real-time capability while ensuring data privacy and compliance with healthcare regulations.
subject: Articles
  topic: section
subject: Cloud computing
  topic: keywords
subject: healthcare data management
  topic: keywords
subject: data sharding
  topic: keywords
subject: Convolutional Neural Networks (CNN)
  topic: keywords
subject: machine learning
  topic: keywords
subject: data security
  topic: keywords
creator: Durga Praveen Deevi
creator: S. Jayanthi
rights: Copyright (c) 2018 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2018-03-28
publication date: 2018-03-28
starting page: 16
ending page: 22

Scalable Healthcare Analytics in the Cloud: Applying Bayesian Networks, Genetic Algorithms, and LightGBM for Pediatric Readmission Forecasting
type: item
description: Pediatric readmissions present significant challenges in healthcare, leading to increased costs, poor health outcomes, and psychological stress on families. Traditional prediction models often struggle to handle the complexity and variability of healthcare data, which limits their predictive capabilities. In response, this study explores the potential of integrating AI and cloud computing to enhance prediction accuracy and scalability for pediatric readmissions. The objective is to compare three machine learning techniques—Bayesian Networks, Genetic Algorithms, and LightGBM—in a cloud-based environment to determine the most effective method for predicting pediatric readmissions at scale. Bayesian Networks are used to model complex interdependencies between patient characteristics, while Genetic Algorithms are applied for feature optimization and selection. LightGBM, known for its speed and accuracy in handling large datasets, provides fast predictions with high accuracy. The models are implemented on a cloud platform, enabling scalable, real-time predictions using diverse data sources, such as electronic health records and patient demographics. The results show that the AI-powered cloud computing model outperforms individual methods, achieving an accuracy of 88%, precision of 85%, recall of 83%, F1-score of 84%, and an AUC of 92%. This combination of machine learning techniques significantly improves prediction accuracy, scalability, and real-time performance in healthcare applications. The study concludes that integrating Bayesian Networks, Genetic Algorithms, and LightGBM within a cloud environment offers a robust solution for predicting pediatric readmissions, making it a valuable tool for reducing unnecessary hospitalizations, optimizing care delivery, and improving patient outcomes in pediatric healthcare systems.
subject: Articles
  topic: section
subject: Pediatric readmissions
  topic: keywords
subject: machine learning
  topic: keywords
subject: Bayesian Networks
  topic: keywords
subject: cloud computing
  topic: keywords
subject: LightGBM
  topic: keywords
subject: healthcare analytics
  topic: keywords
subject: real-time predictions
  topic: keywords
subject: Genetic Algorithms
  topic: keywords
creator: Venkata Surya Teja Gollapalli
rights: Copyright (c) 2020 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2020-04-16
publication date: 2020-04-16
starting page: 11
ending page: 27

Effectiveness of Combined Open and Closed Kinetic Chain Exercises for Treating Shin Splints in Football Players
type: item
description: This study investigates the effectiveness of combined open kinetic and closed kinetic chain exercises in treating shin splints (Medial Tibial Stress Syndrome) in football players. A total of 15 football players aged 12-18 years participated in a quasi-experimental study. Pain intensity was measured before and after the intervention using the Numerical Pain Rating Scale (NPRS). The results showed a significant reduction in pain, from an average of 7.07 (Pre-test) to 3.13 (Post-test) (p < 0.01). These findings suggest that combining open and closed kinetic exercises is effective for reducing shin splint symptoms and improving function. Further studies with larger sample sizes are recommended to confirm these results.
subject: Articles
  topic: section
subject: Shin Splints
  topic: keywords
subject: Medial Tibial Stress Syndrome (MTSS)
  topic: keywords
subject: Open Kinetic Chain (OKC) Exercises
  topic: keywords
subject: Closed Kinetic Chain (CKC) Exercises
  topic: keywords
subject: Football Players
  topic: keywords
creator: S. Immanuel
creator: Dr. P.Muthukrishnan
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-02-06
publication date: 2025-02-06
starting page: 1
ending page: 7

An investigation into the prevalence of anemia in patients diagnosed with type 2 diabetes mellitus who were treated at a tertiary care hospital
type: item
description: To provide some context, diabetes mellitus refers to a collection of metabolic illnesses that affect the metabolism of carbohydrates. Studies have shown that diabetics have a twofold higher incidence of anemia compared to people who do not have diabetes. The development of anemia is an extra burden that is added to the microvascular issues that are associated with diabetes. In spite of these facts, twenty-five percent of diabetic patients do not seek medical attention for anemia. The goals are: 1. To conduct research on the degree to which patients with type 2 diabetes mellitus experience acute anemia 2. To investigate the significance of anemia as a clinical indication of prognosis in patients diagnosed with type 2 diabetes mellitus as a method: A prospective clinical study was carried out at selected tertiary hospital during the months of August 2022 and January 2024. The study involved 125 patients who were evaluated for type 2 diabetes mellitus and were admitted to the inpatient department of general medicine. The relevant inferential statistics were utilized in order to analyze the data. Based on the findings of the study, it was found that out of a total of 125 patients, 78 (36.5%) were females, while 47 (37.5%) were males. Among the observations that fall into the HbA1c >10 group, the majority of them (86.7% of them) have a Severe Hb. Significantly more than sixty-three percent of people who have had diabetes for more than ten years have significant Hb severity. The findings of this study indicate that there is a requirement for periodic hematological screening in all diabetic patients who present themselves to the hospital, as well as treatment of anemia, in order to achieve a more favorable outcome and reduce the risk of complications.
subject: Articles
  topic: section
subject: prevalence
  topic: keywords
subject: anemia
  topic: keywords
subject: patients diagnosed
  topic: keywords
subject: tertiary care hospital
  topic: keywords
creator: Sheeba.B
creator: Dr. Arul Valan.P
creator: Dr. Gopinath Subramanian
rights: Copyright (c) 2024 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-12-04
publication date: 2024-12-04
starting page: 1
ending page: 7

The fruit of the plant Terminalia belerica Roxb. : a phytochemical and pharmacological assessment
type: item
description: India has a wealth of documented and widely used information on herbal medicine. Only a small handful of the world's most valuable medicinal plants are not native to the United States. There are about 3,000 plants with documented therapeutic uses in India. This publication provides a comprehensive review of the phytochemical and pharmacological analysis of Terminalia bellerica. Using IR and GCMS analysis, an attempt was made to separate ellagic acid and describe it.
subject: Articles
  topic: section
subject: ellagic acid
  topic: keywords
subject: anticancer action
  topic: keywords
subject: Terminalia bellerica
  topic: keywords
creator: Nair saisha
rights: Copyright (c) 2013 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2013-02-10
publication date: 2013-02-10
starting page: 1
ending page: 12

DEVELOPMENT AND CHARACTERIZATION OF WHOLE MILK AND COCONUT MILK PANEER INCORPORATED WITH SPINACH LEAF
type: item
description: The paneer is the most dairy product and made of milk products and dairy products. It is used in various types of products like frying , curries and different types. It is developed the quality in its is the main ingredient is spinach and coconut milk to enhance the taste of the product ,texture and flavor and aroma and its is spongy and softy in texture. And spinach is rich in more iron , potassium, vitamins and minerals .Paneer (pronounced [/pəˈniːr/), also known as panir (pronounced [pani̯r), is a fresh acid-set cheese common in the cuisine of the Indian subcontinent made from full-fat buffalo milk or cow milk. It is a soft cheese that is not aged and does not melt that is created by adding an acidic fruit or vegetable, like lemon juice, to milk to curdle it. One type of soft cheese from South Asia is called paneer, which is made by coagulating milk with heat and acid. It is widely consumed in South Asia and is used to make a variety of snacks and gourmet preparations. It is a great source of fat, vitamins, minerals, and high-quality animal protein.
subject: Articles
  topic: section
subject: coconut milk
  topic: keywords
subject: spinach
  topic: keywords
subject: vitamins
  topic: keywords
subject: minerals
  topic: keywords
subject: flavor
  topic: keywords
subject: texture.
  topic: keywords
creator: H Kavitha
creator: Dr. A. Swaroopa Rani
creator: S.P.Neha Thasleem
creator: P. Hari Prasad
rights: Copyright (c) 2024 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-06-14
publication date: 2024-06-14
starting page: 39
ending page: 44

Comprehensive Strategies and Emerging Trends in the Global Fight Against Malaria
type: item
description: Malaria remains a significant global health challenge, particularly in regions where poverty, climate, and limited access to healthcare converge. This review article provides a comprehensive overview of current research findings, control strategies, and emerging trends in the fight against malaria. Drawing from a wide range of scientific literature and field reports, we delve into the intricate web of factors influencing malaria transmission, its impact on communities, and the innovative approaches being employed to combat this ancient scourge. By synthesizing key insights and highlighting gaps in knowledge, this review aims to inform policymakers, healthcare professionals, and researchers on the ongoing battle against "Malrira."
subject: Articles
  topic: section
subject: Malaria Control
  topic: keywords
subject: Disease Transmission
  topic: keywords
subject: Public Health Strategies
  topic: keywords
subject: Innovative Treatments
  topic: keywords
creator: Dr. S. Peer Mohamed
rights: Copyright (c) 2024 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-06-04
publication date: 2024-06-04
starting page: 20
ending page: 38

PHARMACOPOEIA
type: item
description: Derived from Greek word ‘Pharmakon’ means drug and ‘Poiea’means to make.it is a legal and official book issued by recognized authorities usually appointed by Government of each country. it comprises list of pharmaceutical substances, formula along with their description and stand.
subject: Articles
  topic: section
subject: Argentine
  topic: keywords
subject: Austrian
  topic: keywords
subject: Belgian
  topic: keywords
subject: Mexican
  topic: keywords
creator: B. Akhila
creator: S. Tharun Kumar
rights: Copyright (c) 2024 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-05-23
publication date: 2024-05-23
starting page: 1
ending page: 19

Preservatives used in Pharmaceuticals and impact on Health
type: item
description: For several decades pharmacist have been aware of the need to protect their products against microbial contamination but it is only during the last one or perhaps two decades the serious thought of has been applied to the science of preservation. Preservatives are commonly used as additives in pharmaceutical products, food and cosmetics. Some of the liquid preparations are susceptible to microbial contamination because of the nature of ingredients present in it. Such preparations are protected by preservatives which avoids degradation and alternation of the product. A preservative is a natural or synthetic chemical added to various products which helps to prevent microbial decomposition. Present article deals with the study of ideal properties, classification, and mechanism of action, pharmaceuticals applications and its impacts on health of various preservatives used in pharmaceuticals.
subject: Articles
  topic: section
subject: preservatives
  topic: keywords
subject: classification of preservatives
  topic: keywords
subject: natural preservatives
  topic: keywords
subject: chemical classification
  topic: keywords
creator: Dr.B.V.Ramana
rights: Copyright (c) 2024 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-03-16
publication date: 2024-03-16
starting page: 15
ending page: 38

Synthesis, Characterization and Antimicrobial Activity of Zinc Oxide Nanoparticles Synthesized From Calotropis procera
type: item
description: Nanoparticles generated from Calotropis procera leaf extract were compared for their quantity, nature, and antibacterial action in this work. The generated ZnO NPs were examined using FTIR and SEM. Images captured by scanning electron microscopy clearly show that the biologically produced particles have a size between 100 and 200 nm. The minimum inhibitory concentration (MIC) values of several antibacterial agents were determined by conducting studies on both plant and human diseases. The green produced ZnO NPs exhibited strong antibacterial activity against both human and plant pathogens at all doses tested, with the highest zone of inhibition seen at 30 μg/mL. At concentrations ranging from 50 to 12.5 εg/ml of nano-ZnO, all microorganisms tested were entirely inhibited, according to the Minimum Inhibitory Concentrations of NPs against human pathogenic bacteria and plant bacterial pathogens. Various concentrations of ZnO nanoparticles significantly inhibited spore germination, demonstrating the antifungal action of these particles against fungus.
subject: Articles
  topic: section
subject: Calotropis procera
  topic: keywords
subject: zinc oxide nanoparticles
  topic: keywords
subject: fluorescence transfer spectroscopy (FTIR)
  topic: keywords
subject: scanning electron microscopy (SEM)
  topic: keywords
subject: antimicrobial investigation
  topic: keywords
subject: antifungal efficacy.
  topic: keywords
creator: Donthula Srilatha
creator: Kammapati Arunasri
creator: Mangali Sravanthi
rights: Copyright (c) 2024 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-02-23
publication date: 2024-02-23
starting page: 6
ending page: 14

Synthesis, Characterization and Antimicrobial Evaluation of Some Tetrahydroquinazoline Derivatives of Benzo[b]thiophene
type: item
description: The current study details the synthesis of 3-a-dimethyl-3,4,7,8-tetrahydroquinazoline2, 5(1H, 6H)dione from 4-(1-(3-chlorobenzo[b]thiophene-2-carbonyl)-1H-indol-3-yl). Beginning with indole-3-aldehyde and 3- chloro-1-benzothiophene-2-carbonylchloride, these as-yet-unreported compounds are prepared (1a-d). A ransomware of chemicals (3a-d) was cooked up. Infrared and 1H NMR spectra of the newly produced chemicals helped to clarify their structures. All of the compounds showed excellent to moderate antimicrobial activity when tested against S. aureus, E. coli, and P. aeruginosa in a broth dilution assay, and they were also tested against Candida albicans, A. niger, and A. clavatus in an antifungal assay.
subject: Articles
  topic: section
subject: 3-chlorobenzo[b]thiophene-2-carbonyl Antimicrobial activity
  topic: keywords
subject: synthesis.
  topic: keywords
creator: Boya Shailaja
creator: Shaik Jubeda
creator: ,Ganganamoni Aravind
rights: Copyright (c) 2024 https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2024-01-12
publication date: 2024-01-12
starting page: 1
ending page: 5