Role of Predictive Modeling in Healthcare Research: A Scoping Review

The huge preponderance of inferences drawn in empirical medical research follows from model-based relations (e.g. regression). Here, we described the role of predictive modeling as a complement to this approach. Predictive models are usually probabilistic model which gives a good quality fit to our data. In medical research, it’s very common to use regression models for predictive purposes. Here in this article, we described the types of predictive modeling (Linear and Non-linear) used in medical research and how effectively the researchers take decisions based on predictive modeling, and what precautions, we have to take while building a predictive model. Finally, we consider a working example to illustrate the effectiveness of the predictive model in healthcare

Impact of Machine Learning and Prediction Models in the Diagnosis of Oral Health Conditions

Introduction: Recent developments in data science and the employment of machine learning algorithms (ML) have revolutionized health sciences in the prediction of diseases using laboratory data. Oral diseases are observed in all age groups and are estimated to affect about a 3.5billion people as per WHO 2022 statistics. Using the existing diagnostic data and taking advantage of ML and prediction models would benefit developing a prediction model for diagnosing oral diseases. Hence, it is quite essential to understand the basic terminologies used in the prediction model. Methods: We retrieve various research papers using Scopus, PubMed, and google scholar databases, where prediction models were used in dentistry. The idea of this review is to explore current models, model validation, discrimination, calibration, and bootstrapping methods used in prediction models for oral diseases. Results: The current advancement of ML techniques plays a significant task in the diagnosis and prognosis of oral diseases. Conclusion: The use of prediction models using ML techniques can improve the accuracy of the treatment methods in oral health. This article aims to provide the required framework, data sets, and methodology to build ML and prediction models for oral diseases

‘TRAIL’ of targeted colorectal cancer therapy

TRAIL, a tumor necrosis factor-related apoptosis-inducing ligand is a member of the tumor necrosis factor (TNF) superfamily, which is a cytokine that has shown a particularly precise and selective affinity towards death receptors that are overexpressed in cancer cells. While leaving the normal cells intact and unharmed, due to this property it has been the ligand of choice for highly precise cancer chemotherapeutic delivery system development. On numerous occasions, TRAIL has been used singularly and in combination with other drugs. It was observed that TRAIL had a tendency to be susceptible in terms of the cancer cells developing resistance against it. So TRAIL monotherapy was a bit of a rough patch for the molecule to become successful in the chemotherapy universe, however the conjugations and synergistic actions of TRAIL opened up new horizons which are discussed in this review with specific interest on colorectal cancer (CRC)

Comparison of Some Prediction Models and their Relevance in the Clinical Research

In healthcare research, predictive modeling is commonly utilized to forecast risk variables and enhance treatment procedures for improved patient outcomes. Enormous quantities of data are being created as a result of recent advances in research, clinical trials, next-generation genomic sequencing, biomarkers, and transcriptional and translational studies. Understanding how to handle and comprehend scientific data to offer better treatment for patients is critical. Currently, multiple prediction models are being utilized to investigate patient outcomes. However, it is critical to recognize the limitations of these models in the research design and their unique benefits and drawbacks. In this overview, we will look at linear regression, logistic regression, decision trees, and artificial neural network prediction models, as well as their advantages and disadvantages. The two most perilous requirements for building any predictive healthcare model are feature selection and model validation. Typically, feature selection is done by a review of the literature and expert opinion on that subject. Model validation is also an essential component of every prediction model. It characteristically relates to the predictive model's performance and accuracy. It is strongly recommended that all clinical parameters should be thoroughly examined before using any prediction model

In-vivo Hepatoprotective Evaluation of Sicyos edulis on Wistar Albino Rats

The liver is known for synthesising enzymes, metabolism, and excretion of drugs and food. However, during biological processes, the abnormality occurs in the liver, which becomes a significant global health burden in humans, characterised by loss of synthetic function, breakdown of blood, irregular vitamin K, and localised, permanent changes to parenchymal cells. The study was designed to research the Phytochemical and biological screening of Sicyos edulis leaf for hepatoprotective activity on laboratory animals using paracetamol and methotrexate model for acute incidence. The study evaluated liver toxicity in healthy Wistar albino rats using two in vivo models. Each study group consists of six animals. In the first model, paracetamol p.o. for seven days. Similarly, in the second model, methotrexate was administered (single dose treatment) to animals with 20mg/kg, b.w., p.o. Both models were challenged with methanolic extract of Sicyos edulis leaf (MESEL) of doses 100mg/kg (low) and 200 mg/kg (high) p.o. for seven days, respectively. On day 8th, the blood samples were collected from the tail vein and analysed for various biochemical parameters. MESEL successfully restored the elevated serum biomarker levels in our study. The decrease in aspartate aminotransferase was observed by removing toxic metabolites, the reduction in alanine aminotransferase was due to an increase in ATP synthesis in mitochondria, thereby modulating the balance of liver energy metabolism, and the decrease in alkaline phosphates is due to tissue regeneration, an increase in total protein denotes the restoration of protein imbalance from acute liver injury. At different concentrations, all these effects strengthen the liver, regulate body metabolism, and ultimately inhibit further liver cell damage in favour of their regeneration. Our study also evidences the protective action of MESEL in rats against the Paracetamol and methotrexate model. The study reveals hepatocyte regeneration followed by hepatic restoration in pre-clinical settings. Keywords: Acute liver disease, Sicyos edulis, Silymarin, Methotrexate, Liver enzyme

Moringa oleifera and its application in dental conditions: A systematic review and meta-analysis

Moringa oleifera is a considerable ethnomedical herb with various bioactive compounds. This study aimed to analyze the efficacy of M. oleifera in the prevention and management of various oral conditions. A thorough search was conducted on the Web of Science, Scopus, PubMed, and PubMed Central databases. After screening the data on the basis of inclusion and exclusion criteria, 9 studies were considered for further meta-analysis. The analysis was performed on R programming software (version R-4.0.2) and the results were represented by a forest plot. The estimate obtained via common and random effects model for in vitro studies was statistically insignificant (I2 test P > 0.05) with risk ratios of 8.25 (95% CI: 3.76-18.08) and 7.98 (95% CI: 3.64-17.50) and for in vivo studies were statistically significant (I2 test P )0.05 < with risk ratios of 1.12 (95% CI: 0.90-1.40) and 0.97 (95% CI: 0.71-1.32), indicating the efficacy of M. oleifera in oral diseases on animal and clinical trials, whereas it failed to report the efficacy on in vitro level. Future research has to be done to come up with new and more phytoactive compounds from all parts of the plant with proper extraction procedures. The effectiveness of the compounds has to be validated first on in vitro scale followed by clinical trials so that M. oleifera can be used as therapy in preventing and managing oral ailments

Cellular and molecular mechanisms, genetic predisposition and treatment of diabetes-induced cardiomyopathy

Diabetes mellitus is a common disease affecting millions of people worldwide. This disease is not limited to metabolic disorders but also affects several vital organs in the body and can lead to major complications. People with diabetes mellitus are subjected to cardiovascular complications, such as cardiac myopathy, which can further result in major complications such as diabetes-induced cardiac failure. The mechanism underlying diabetes-induced cardiac failure requires further research; however, several contributing factors have been identified to function in tandem, such as reactive oxygen species production, inflammation, formation of advanced glycation end-products, altered substrate utilisation by mitochondria, activation of the renin–angiotensin–aldosterone system and lipotoxicity. Genetic factors such as microRNAs, long noncoding RNAs and circular RNAs, as well as epigenetic processes such as DNA methylation and histone modifications, also contribute to complications. These factors are potential targets for developing effective new therapies. This review article aims to facilitate in depth understanding of these contributing factors and provide insights into the correlation between diabetes mellitus and cardiovascular complications. Some alternative targets with therapeutic potential are discussed to indicate favourable targets for the management of diabetic cardiomyopathy

‘TRAIL’ of targeted colorectal cancer therapy

95-98TRAIL, a tumor necrosis factor-related apoptosis-inducing ligand is a member of the tumor necrosis factor (TNF) superfamily, which is a cytokine that has shown a particularly precise and selective affinity towards death receptors that are overexpressed in cancer cells. While leaving the normal cells intact and unharmed, due to this property it has been the ligand of choice for highly precise cancer chemotherapeutic delivery system development. On numerous occasions, TRAIL has been used singularly and in combination with other drugs. It was observed that TRAIL had a tendency to be susceptible in terms of the cancer cells developing resistance against it. So TRAIL monotherapy was a bit of a rough patch for the molecule to become successful in the chemotherapy universe, however the conjugations and synergistic actions of TRAIL opened up new horizons which are discussed in this review with specific interest on colorectal cancer (CRC)

Ms DIFFERENT ULTRAVIOLET SPECTROSCOPIC METHODS: A RETROSPECTIVE STUDY ON ITS APPLICATION FROM THE VIEWPOINT OF ANALYTICAL CHEMISTRY

 In routine practice, some simple and rapid analytical methods are needed for the assessment of formulations containing multiple elements, complex matrix system and for biotherapeutic products. There are several methods available for ultraviolet (UV) spectrophotometry that rely on the concept of absorbance difference, absorbance spectra, and additivity, also included in the list are simultaneous equation method, Q-absorbance ratio method, derivative spectrophotometry, ratio derivative spectra, successive ratio-derivative spectra, absorption and absorptivity factor method, and difference spectrophotometry along with multivariate chemometric methods. In this review, emphasis has been given to the theories, mathematical context, advantages, and disadvantages along with the vast applications of UV spectrophotometry. The findings further highlighted that for the analysis of drugs, UV spectrophotometry remains as one of the most simple, cheap, and promising option for routine practice in the field of pharmaceuticals

Cardioprotective effects of Rhododendron arboreum leaf extract against Doxorubicin-induced cardiotoxicity in Wistar rats by modulating electrocardiographic and cardiac biomarkers

Abstract Background Cardiotoxicity and related complications are well-known adverse effects of anticancer drugs like doxorubicin (DOX). A medicinal plant called Rhododendron arboreum is used by traditional healers of Sikkim in the treatment of heart ailments and has also been reported for widespread therapeutic effects in many clinical studies. Thus the present study has been designed to evaluate the protective effects of Rhododendron arboreum leaf extract (RALE) against DOX-induced cardiotoxicities. Methods Commencement of research with the collection of the Rhododendron arboreum leaves and drying it in the shade, the extraction was performed using the Soxhlet method with an ethanolic solvent. The phytoconstituents of the RALE were then quantified and qualitatively evaluated. Doxorubicin-induced cardiotoxicity was carried out using four groups consisting of six animals each. Doxorubicin was administered with a dose of 3 mg/kg injected intraperitoneally (i.p.) on the 1st,7th,14th,21st and 28th day of cumulative dose of 15 mg/kg throughout the experimental period with RALE treatment (250 mg/kg and 100 mg/kg) orally for 28 days. The influence of the treatment was analyzed by quantification of cardiac biomarkers and electrocardiographic method. Results The serum levels of cardiac biomarkers such as Lactate Dehydrogenase (LDH), Creatine kinase-N-acetyltransferase (CK-NAC), Creatine kinase-MB (CK-MB), Aspartate Transaminase (AST), Alanine Transaminase (ALT), which were elevated due to DOX-induced cardiotoxicity were significantly reduced in all RALE (250 mg/kg and 100 mg/kg) treated groups. Similarly, the electrocardiographic changes like prolonged QT interval, widening of QRS complex amplitude, undefined ST segment, arrhythmias and increased heart rate were also restored close to normal in all treated groups compared to the DOX control group. Conclusion Following the data observed during the study, results reported that R. arboreum possesses the free radical scavenging property, improved cardiotoxic laboratory parameters and restored reversible cellular injury due to existing of the principle constituent’s impact on proinflammatory mediators