Magnetic nano-sized solid acid catalyst bearing sulfonic acid groups for biodiesel synthesis and oxidation of sulfides.

In this study, the AlFeO@n-Pr@Et-SOH heterogeneous catalyst was successfully synthesized and utilized to produce biodiesel from oleic acid through an esterification process and to oxidize sulfides. To examine the physicochemical characteristics of the AlFeO@n-Pr@Et-SOH nanomaterial, a variety of advanced techniques were employed, including Fourier Transform infrared spectroscopy (FT-IR), Field emission scanning electron microscopy (FE-SEM), Energy dispersive X-ray spectroscopy (EDX), Vibrating sample magnetometer (VSM), Elemental Mapping, Transmission electron microscopy (TEM), Inductively coupled plasma (ICP), and X-ray diffraction (XRD). The AlFeO@n-Pr@Et-SOH materials demonstrated excellent performance in both the esterification of oleic acid and the oxidation of sulfides.

Machine learning-based estimation of crude oil-nitrogen interfacial tension.

Accurate estimation of interfacial tension (IFT) between nitrogen and crude oil during nitrogen-based gas injection into oil reservoirs is imperative. The previous research works dealing with prediction of IFT of oil and nitrogen systems consider synthetic oil samples such n-alkanes. In this work, we aim to utilize eight machine learning methods of Decision Tree (DT), AdaBoost (AB), Random Forest (RF), K-nearest Neighbors (KNN), Ensemble Learning (EL), Support Vector Machine (SVM), Convolutional Neural Network (CNN) and Multilayer Perceptron Artificial Neural Network (MLP-ANN) to construct data-driven intelligent models to predict crude oil - nitrogen IFT based upon experimental data of real crude oils samples encountered in underground oil reservoirs.

From diagnosis to therapy: The role of LncRNA GAS5 in combatting some cancers affecting women.

Long non-coding RNAs (lncRNAs) are a collection of non-coding RNA molecules that consist of more than 200 nucleotides. In human malignancies, these lncRNAs exhibit abnormal expression patterns and play a significant role in either suppressing or promoting tumor growth. They achieve this by modulating various functions and mechanisms within cancer cells, including proliferation, invasion, metastasis, apoptosis, and resistance to different therapeutic approaches.

Sentiment analysis of tweets employing convolutional neural network optimized by enhanced gorilla troops optimization algorithm.

Sentiment analysis has become a difficult and important task in the current world. Because of several features of data, including abbreviations, length of tweet, and spelling error, there should be some other non-conventional methods to achieve the accurate results and overcome the current issue. In other words, because of those issues, conventional approaches cannot perform well and accomplish results with high efficiency.

Computational evaluation of micropores wetting effect on the removal process of CO through the membrane contactor.

In the current years, gas-liquid membrane contactors (GLMCs) have been introduced as a promising, versatile and easy-to-operate technology for mitigating the emission of major greenhouse contaminants (i.e., CO and HS) to the ecosystem.

Kaempferol: Unveiling its anti-inflammatory properties for therapeutic innovation.

Inflammation, driven by various stimuli such as pathogens, cellular damage, or vascular injury, plays a central role in numerous acute and chronic conditions. Current treatments are being re-evaluated, prompting interest in naturally occurring compounds like kaempferol, a flavonoid prevalent in fruits and vegetables, for their anti-inflammatory properties. This study explores the therapeutic potential of kaempferol, focusing on its ability to modulate pro-inflammatory cytokines and its broader effects on inflammatory signaling pathways.

A cutting-edge investigation of the multifaceted role of SOX family genes in cancer pathogenesis through the modulation of various signaling pathways.

This detailed study examines the complex role of the SOX family in various tumorigenic contexts, offering insights into how these transcription factors function in cancer. As the study progresses, it explores the specific contributions of each SOX family member. The significant roles of the SOX family in the oncogenic environment are well-recognized, highlighting a range of regulatory mechanisms that influence tumor progression.

Optimizing concrete crack detection an echo state network approach with improved fish migration optimization.

There are numerous reasons for concrete buildings cracks, like stress loads, material flaws, and environmental impacts. It is important to find and investigate the concrete cracks during analyzing the safety and structural soundness of buildings, bridges, and other infrastructure. However, there are many models available for concrete crack detection, an efficient approach is needed because the existing methods often have flaws like overfitting, high computational complexity, and noise sensitivity, which can lead to accurate crack detection and classification.

Enhanced capsule neural network with advanced triangulation topology aggregation optimizer for music genre classification.

Music genres classification poses a formidable challenge as it necessitates capturing the intricate and varied characteristics of musical signals. In this study, an innovative approach is presented to classify the music genres using the Capsule Neural Network (CapsNet). The CapsNet model optimized by an advanced version of Triangulation Topology Aggregation Optimizer (ATTAO).

Exploring the role of exosomal lncRNA in cancer immunopathogenesis: Unraveling the immune response and EMT pathways.

Exosomes are membrane-bound vesicles secreted by diverse cell types, serving as crucial mediators in intercellular communication and significantly influencing cancer development. Exosomes facilitate complex signaling processes in the tumor microenvironment for immunomodulation, metastasis, angiogenesis, and treatment resistance. Notably, long non-coding RNAs (lncRNAs), a class of non-coding RNAs, engage with mRNA, DNA, proteins, and miRNAs to modulate gene expression through multiple mechanisms, including transcriptional, post-transcriptional, translational, and epigenetic pathways.

First-episode mild depression in young adults is a pre-proatherogenic condition even in the absence of subclinical metabolic syndrome: lowered lecithin-cholesterol acyltransferase as a key factor.

Background: Major depression is classified into distinct subtypes: simple (SDMD) and major dysmood disorder (MDMD). MDMD patients exhibit elevated atherogenicity and decreased reverse cholesterol transport (RCT). However, comprehensive data regarding lipid metabolism is absent in first episode (FE)-SDMD.

Are abnormalities in lipid metabolism, together with adverse childhood experiences, the silent causes of immune-linked neurotoxicity in major depression?

Background: Severe or recurring major depression is associated with increased adverse childhood experiences (ACEs), heightened atherogenicity, and immune-linked neurotoxicity (INT). Nevertheless, the interconnections among these variables in outpatient major depression (OMDD) have yet to be determined. We aim to determine the correlations among INT, atherogenicity, and ACEs in OMDD patients compared to normal controls.

Urban Water-Energy consumption Prediction Influenced by Climate Change utilizing an innovative deep learning method.

The growing global demand for water and energy has created an urgent necessity for precise forecasting and management of these resources, especially in urban regions where population growth and economic development are intensifying consumption. Shenzhen, a rapidly expanding megacity in China, exemplifies this trend, with its water and energy requirements anticipated to rise further in the upcoming years. This research proposes an innovative Convolutional Neural Network (CNN) technique for forecasting water and energy consumption in Shenzhen, considering the intricate interactions among climate, socio-economic, and demographic elements.

Advanced music classification using a combination of capsule neural network by upgraded ideal gas molecular movement algorithm.

Music genres classification has long been a challenging task in the field of Music Information Retrieval (MIR) due to the intricate and diverse nature of musical content. Traditional methods have struggled to accurately capture the complex patterns that differentiate one genre from another. However, recent advancements in deep learning have presented new opportunities to tackle this challenge.

LncRNA CRNDE and HOTAIR: Molecules behind the scenes in the progression of gastrointestinal cancers through regulating microRNAs.

Gastrointestinal (GI) cancers, such as gastric cancer, hepatocellular carcinoma, colorectal cancer, and esophageal cancer, pose a significant medical and economic burden globally, accounting for the majority of new cancer cases and deaths each year. A lack of knowledge about the molecular mechanisms of GI cancers is reflected in the low efficacy of treatment for individuals with late stage and recurring illness. Understanding the molecular pathways that promote the growth of GI cancers may open doors for their therapy.

Dysregulation of GAS5-miRNA-Mediated Signaling Pathways in Cancer Pathobiology: A Comprehensive Exploration of Pathways Influenced by this Axis.

The long non-coding RNA Growth Arrest-Specific 5 (GAS5) is pivotal in modulating key signaling pathways by functioning as a molecular sponge for microRNAs (miRNAs). GAS5 is notably recognized for its antitumor properties, primarily through its ability to sequester oncogenic miRNAs, thereby influencing critical pathways such as p53, Wnt/β-catenin, and PI3K/Akt, all of which are integral to cell proliferation, apoptosis, and metastasis. The disruption of GAS5-miRNA interactions has been implicated in various malignancies, reinforcing its potential as both a biomarker and a therapeutic target.

Pathological roles of lncRNA HOTAIR in liver cancer: An updated review.

Liver cancer ranks as the sixth most prevalent form of cancer and stands as the fourth leading cause of cancer-related fatalities on a global scale. The two primary types of liver cancer are hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC). While ICC originates from the bile ducts, HCC develops from hepatocytes, which are the primary functional cells of the liver.

Decoding the complex web: Cellular and molecular interactions in the lung tumor microenvironment.

The lung tumor microenvironment (TME) or stroma is a dynamic space of numerous cells and their released molecules. This complicated web regulates tumor progression and resistance to different modalities. Lung cancer cells in conjunction with their stroma liberate a wide range of factors that dampen antitumor attacks by innate immunity cells like natural killer (NK) cells and also adaptive responses by effector T cells.

Targeting breast tumor extracellular matrix and stroma utilizing nanoparticles.

Breast cancer is a complicated malignancy and is known as the most common cancer in women. Considerable experiments have been devoted to explore the basic impacts of the tumor stroma, particularly the extracellular matrix (ECM) and stromal components, on tumor growth and resistance to treatment. ECM is made up of an intricate system of proteins, glycosaminoglycans, and proteoglycans, and maintains structural support and controls key signaling pathways involved in breast tumors.

Furan- and Furopyrimidine-Based Derivatives: Synthesis, VEGFR-2 Inhibition, and Cytotoxicity.

New derivatives -, , -, -, , , , -, -, and were synthesized and evaluated for their VEGFR-2 inhibition. Compounds , , and showed remarkable enzyme inhibition IC = 57.1, 42.

Recent advances in carbon-based materials derived from diverse green biowaste for sensing applications: a comprehensive overview from the perspective of synthesis method and application.

The rapid increase in global waste, driven by population growth, has raised significant environmental concerns. Among different types of wastes, green biowastes (BWs) containing organic matter have attracted considerable attention. The conversion of BW, particularly from herbaceous and animal sources, to carbon-based materials (CBMs) introduces a suitable platform for waste management and resource recovery.

Effect of soluble fiber supplementation on lipid parameters in subjects with type 2 diabetes: A systematic review and meta-analysis of randomized controlled trials.

Background: There is no consensus in the existing literature regarding the effect of soluble fiber on the lipid profile of patients with type 2 diabetes mellitus (T2DM). This systematic review and meta-analysis of randomized controlled trials aimed to assess the effect of soluble fiber on triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) in T2DM patients.

Methods: PubMed/MEDLINE, Scopus, and ISI Web of sciences were searched for RCTs up to 4 May 2024.

The Effects of Chia Seed (Salvia hispanica L.) Consumption on Blood Pressure and Body Composition in Adults: A Systematic Review and Meta-analysis of Randomized Controlled Trials.

Purpose: Growing evidence has suggested that the consumption of chia seed can decrease blood pressure and obesity in adults. However, even studies have reported uncertain findings. The current meta-analysis aimed to assess the findings of randomized controlled trials (RCTs) on the efficacy of chia seed supplementation on blood pressure (systolic blood pressure [SBP], diastolic blood pressure [DBP]) and body composition (waist circumference [WC], weight, body mass index [BMI]) in adults.