Liquid chromatography-high-resolution mass spectrometry-based metabolomics revealing the effects of zearalenone and alpha-zearalenol on human endometrial cancer cells.

Human exposure to mycotoxins through food involve a mixture of compounds, which can be harmful to human health. The Fusarium fungal species are known to produce zearalenone (ZEN), a non-steroidal estrogenic mycotoxin, and its metabolite alpha-zearalenol (α-ZEL), both of which possess endocrine-disruptive properties. Given their potential harm to human health through food exposure, investigating the combined effects of ZEN and α-ZEL becomes crucial.

Prediction for chronic kidney disease by categorical and non_categorical attributes using different machine learning algorithms.

Chronic kidney disease (CKD) is a common disease as it is difficult to diagnose early due to its lack of symptoms. The main goal is to first diagnose kidney failure, which is a requirement for dialysis or a kidney transplant. This model teaches patients how to live a healthy life, helps doctors identify the risk and severity of disease, and how plan future treatments.

Antimicrobial peptide moricin induces ROS mediated caspase-dependent apoptosis in human triple-negative breast cancer via suppression of notch pathway.

Background: Breast cancer is the world's most prevalent cancer among women. Microorganisms have been the richest source of antibiotics as well as anticancer drugs. Moricin peptides have shown antibacterial properties; however, the anticancer potential and mechanistic insights into moricin peptide-induced cancer cell death have not yet been explored.

Improved detection of dry age-related macular degeneration from optical coherence tomography images using adaptive window based feature extraction and weighted ensemble based classification approach.

Background: Dry Age-related macular degeneration (AMD), which affects the older population, can lead to blindness when left untreated. Preventing vision loss in elderly needs early identification. Dry-AMD diagnosis is still time-consuming and very subjective, depending on the ophthalmologist.

Improved detection accuracy of red lesions in retinal fundus images with superlearning approach.

Background: Diabetic Retinopathy (DR) is a serious consequence of diabetes that can result to permanent vision loss for a person. Diabetes-related vision impairment can be significantly avoided with timely screening and treatment in its initial phase. The earliest and the most noticeable indications on the surface of the retina are micro-aneurysm and haemorrhage, which appear as dark patches.

Exploring the Role of Glycolytic Enzymes PFKFB3 and GAPDH in the Modulation of Aβ and Neurodegeneration and Their Potential of Therapeutic Targets in Alzheimer's Disease.

Alzheimer's disease (AD) is presently the 6th major cause of mortality across the globe. However, it is expected to rise rapidly, following cancer and heart disease, as a leading cause of death among the elderly peoples. AD is largely characterized by metabolic changes linked to glucose metabolism and age-induced mitochondrial failure.

Serum and urine metabolomics analysis reveals the role of altered metabolites in patulin-induced nephrotoxicity.

Various studies have identified the kidney as a target organ for patulin (PAT)-induced toxicity. However, detailed mechanistic insights into PAT-induced nephrotoxicity had not yet been done. Therefore, along with classical toxicological parameters, liquid chromatography-high resolution massed spectrometry (LC-HRMS) based metabolomics has been carried out to delineate the mechanism(s) of PAT-induced nephrotoxicity.

Ochratoxin A treated rat derived urinary exosomes enhanced cell growth and extracellular matrix production in normal kidney cells through modulation of TGF-β/smad2/3 signaling pathway.

Aims: Kidney is the main target organ for ochratoxin A (OTA) toxicity; however, the mechanism(s) involved in OTA-induced nephrotoxicity is not fully understood. Recently, exosomes, nano-sized vesicles have been found to play an important role in promotion and progression of disease as well as environmental toxicant-induced patho-physiology of toxicity. Hence, we aimed to investigate the role of exosomes in OTA-mediated nephrotoxicity.

Transcriptomic and proteomic insights into patulin mycotoxin-induced cancer-like phenotypes in normal intestinal epithelial cells.

Patulin (PAT) is a natural contaminant of fruits (primarily apples) and their products. Significantly, high levels of contamination have been found in fruit juices all over the world. Several in vitro studies have demonstrated PAT's ability to alter intestinal structure and function.

DNA Methylation Biomarkers-Based Human Age Prediction Using Machine Learning.

Purpose: Age can be an important clue in uncovering the identity of persons that left biological evidence at crime scenes. With the availability of DNA methylation data, several age prediction models are developed by using statistical and machine learning methods. From epigenetic studies, it has been demonstrated that there is a close association between aging and DNA methylation.

TGF-β/Smad signaling pathway plays a crucial role in patulin-induced pro-fibrotic changes in rat kidney via modulation of slug and snail expression.

Patulin (PAT) is a mycotoxin that contaminates a variety of food and foodstuffs. Earlier in vitro and in vivo findings have indicated that kidney is one of the target organs for PAT-induced toxicity. However, no study has evaluated the chronic effects of PAT exposure at environmentally relevant doses or elucidated the detailed mechanism(s) involved.

Learner question's correctness assessment and a guided correction method: enhancing the user experience in an interactive online learning system.

In an interactive online learning system (OLS), it is crucial for the learners to form the questions correctly in order to be provided or recommended appropriate learning materials. The incorrect question formation may lead the OLS to be confused, resulting in providing or recommending inappropriate study materials, which, in turn, affects the learning quality and experience and learner satisfaction. In this paper, we propose a novel method to assess the correctness of the learner's question in terms of syntax and semantics.

Study of a modified non-contact Hall sensor-based flow transducer using centrifugal and momentum force principle.

The paper describes a modified non-contact Hall sensor based centrifugal and momentum force type flow transducer with simple design, low cost and rugged construction. In this transducer two identical permanent magnets are fixed on the two ends of the common balance lever on which sensing U-tube and dummy U-tube are placed at equal distances from the pivot. The movement of lever ends with variation of flow rate, changes the magnet positions with respect to the two identical Hall sensors fixed at two locations just below the magnets.

COVID-19 Pandemic: ARIMA and Regression Model-Based Worldwide Death Cases Predictions.

COVID-19 has now taken a frightening form. As the days pass, it is becoming more and more widespread and now it has become an epidemic. The death rate, which was earlier in the hundreds, changed to thousands and then progressed to millions.

Acoustic feature based unsupervised approach of heart sound event detection.

This paper represents an unsupervised approach to detect the positions of S1, S2 heart sound events in a Phonocardiogram (PCG) recording. Insufficiency of correctly annotated heart sound database drives us to investigate unsupervised techniques. Gammatone filter bank features are used to characterize the spectral pattern of fundamental heart sound events from noise contaminated PCG data.

Prediction of Skin Disease with Three Different Feature Selection Techniques Using Stacking Ensemble Method.

Skin disease is the most common problem between people. Due to pollution and deployment of ozone layer, harmful UV rays of sun burn the skin and develop various types of skin diseases. Nowadays, machine learning and deep learning algorithms are generally used for diagnosis for various kinds of diseases.

A novel approach towards non-obstructive detection and classification of COPD using ECG derived respiration.

The alarming rate of mortality and disability due to Chronic Obstructive Pulmonary Disease (COPD) has become a serious health concern worldwide. The progressive nature of this disease makes it inevitable to detect this disease in its early stages, leads to a greater demand for developing non-obstructive and reliable technology for COPD detection. The use of highly patient-effort dependent, time-consuming, and expensive methods are some major inherent limitations of previous techniques.

Prediction of Skin Disease Using Ensemble Data Mining Techniques and Feature Selection Method-a Comparative Study.

Nowadays, skin disease is a major problem among peoples worldwide. Different machine learning techniques are applied to predict the various classes of skin disease. In this research paper, we have applied six different machine learning algorithm to categorize different classes of skin disease using three ensemble techniques and then a feature selection method to compare the results obtained from different machine learning techniques.

Classification of Skin Disease using Ensemble Data Mining Techniques.

Objective: Skin diseases are a major global health problem associated with high number of people. With the rapid development of technologies and the application of various data mining techniques in recent years, the progress of dermatological predictive classification has become more and more predictive and accurate. Therefore, development of machine learning techniques, which can effectively differentiate skin disease classification, is of vast importance.

To Generate an Ensemble Model for Women Thyroid Prediction Using Data Mining Techniques.

Objective: The main objective of this paper is to easily identify thyroid symptom for treatment. Methods: In this paper two main techniques are proposed for mining the hidden pattern in the dataset. Ensemble-I and Ensemble- II both are machine learning techniques.

Alternariol induced proliferation in primary mouse keratinocytes and inflammation in mouse skin is regulated via PGE/EP2/cAMP/p-CREB signaling pathway.

Alternariol (AOH) is a mycotoxin that contaminates various food stuffs as well as animal feed and may cause toxicity after consumption. However, a dermal toxic potential of AOH has not been explored so far. In the present study, skin toxicity after topical exposure of AOH and the involved mechanism/s are revealed.

COX-2/EP2-EP4/β-catenin signaling regulates patulin-induced intestinal cell proliferation and inflammation.

Patulin (PAT), a mycotoxin, is a natural contaminant that is produced by certain species of Penicillium, Aspergillus and Byssochlamys. The major contamination of PAT is in apple and apple based products. PAT is known to cause glutathione depletion, oxidative DNA damage and cell proliferation.

Toxicological effects of patulin mycotoxin on the mammalian system: an overview.

The mycotoxin PAT (4-hydroxy-4-furo[3,2]pyran-2[6]-one) is a secondary metabolic product of molds such as , , and species. PAT is a common contaminant of fruit and vegetable based products, most notably apples. Despite PAT's original discovery as an antibiotic, it has come under heavy scrutiny for its potential to impart negative health effects.

Arduino-based noise robust online heart-rate detection.

This paper introduces a noise robust real time heart rate detection system from electrocardiogram (ECG) data. An online data acquisition system is developed to collect ECG signals from human subjects. Heart rate is detected using window-based autocorrelation peak localisation technique.