Metagenomic exploration and computational prediction of novel enzymes for polyethylene terephthalate degradation.

As a global environmental challenge, plastic pollution raises serious ecological and health concerns owing to the excessive accumulation of plastic waste, which disrupts ecosystems, harms wildlife, and threatens human health. Polyethylene terephthalate (PET), one of the most commonly used plastics, has contributed significantly to this growing crisis. This study offers a solution for plastic pollution by identifying novel PET-degrading enzymes.

Highly sensitive and selective detection of SARS-CoV-2 spike protein S1 using optically-active nanocomposite-coated melt-blown masks.

Detection of viruses, including coronavirus (SARS-CoV-2), via facile, fast, and optical methods is highly important to control pandemics. In this regard, optically-active nanomaterials and nanoparticles (NPs) are a wise choice due to their long-term stability, ease of functionalization, and modifications. In this work, a nanocomposite based on NiFe layered double hydroxide (LDH) and ZIF-67 metal-organic framework (MOF) was designed and synthesized, and decorated on the surface of the melt-blown mask.

Porous Materials for Early Diagnosis of Neurodegenerative Diseases.

Neurodegenerative diseases, particularly Alzheimer's disease and Parkinson's disease, present formidable challenges in modern medicine due to their complex pathologies and the absence of curative treatments. Despite advances in symptomatic management, early diagnosis remains essential for mitigating disease progression and improving patient outcomes. Traditional diagnostic methods, such as MRI, PET, and cerebrospinal fluid biomarker analysis, are often inadequate for the early detection of these diseases.

Comprehensive Multi-Omics Analysis Reveals NPC2 and ITGAV Genes as Potential Prognostic Biomarkers in Gastrointestinal Cancers.

Background: Gastrointestinal cancers (GICs) continue to dominate in terms of both incidence and mortality worldwide. Due to the absence of efficient and accurate prognostic biomarkers, the prognosis and treatment outcomes of many GICs are poor. Identifying biomarkers to predict individual clinical outcomes efficiently is a fundamental challenge in clinical oncology.

An exploration into the diagnostic capabilities of microRNAs for myocardial infarction using machine learning.

Background: MicroRNAs (miRNAs) have shown potential as diagnostic biomarkers for myocardial infarction (MI) due to their early dysregulation and stability in circulation after MI. Moreover, they play a crucial role in regulating adaptive and maladaptive responses in cardiovascular diseases, making them attractive targets for potential biomarkers. However, their potential as novel biomarkers for diagnosing cardiovascular diseases requires systematic evaluation.

Transcriptomic analysis reveals role of lncRNA LOC100257036 to regulate AGAMOUS during cluster compactness of Vitis vinifera cv. sistan yaghooti.

Yaghooti grape, as the earliest grape variety in Iran, is considered as more resistant to heat, drought, and salinity than other cultivars. Cluster compactness is regarded as an inappropriate feature for the productivity of Yaghooti grape as a critical commercial and nutritional product. In plants, lncRNAs play a critical role in regulating biological processes related to growth and development.

Leveraging ML for profiling lipidomic alterations in breast cancer tissues: a methodological perspective.

In this study, a comprehensive methodology combining machine learning and statistical analysis was employed to investigate alterations in the metabolite profiles, including lipids, of breast cancer tissues and their subtypes. By integrating biological and machine learning feature selection techniques, along with univariate and multivariate analyses, a notable lipid signature was identified in breast cancer tissues. The results revealed elevated levels of saturated and monounsaturated phospholipids in breast cancer tissues, consistent with external validation findings.

Docking-Based Virtual Screening Method for Selecting Natural Compounds with Synergistic Inhibitory Effects Against Cancer Signalling Pathways Using a Multi-Target Approach.

Objectives: This study aims to introduce a methodology for identifying medicinal plants that contain effective natural compounds with the most possible synergistic effects to inhibit cancer survival and proliferation in a multi-targeted manner.

Materials And Methods: To select targets, the signaling pathways involved in cancer development were defined from the KEGG database, and the protein-protein interactions (PPIs) of genes within these pathways were investigated using the STRING software. Then 14 proteins with the highest degree were identified as targets.

Comparative Atlas of SARS-CoV-2 Substitution Mutations: A Focus on Iranian Strains Amidst Global Trends.

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a new emerging coronavirus that caused coronavirus disease 2019 (COVID-19). Whole-genome tracking of SARS-CoV-2 enhanced our understanding of the mechanism of the disease, control, and prevention of COVID-19.

Methods: we analyzed 3368 SARS-CoV-2 protein sequences from Iran and compared them with 15.

Revolutionizing protein hydrolysis in wastewater: Innovative immobilization of metagenome-derived protease in periodic mesoporous organosilica with imidazolium framework.

This research focused on utilizing periodic mesoporous organosilica with imidazolium framework (PMO-IL), to immobilize a metagenome-sourced protease (PersiProtease1), thereby enhancing its functional efficiency and catalytic effectiveness in processing primary proteins found in tannery wastewater. The successful immobilization of enzyme was confirmed through the use of N adsorption-desorption experiment, XRD, FTIR, TEM, FESEM, EDS and elemental analytical techniques. The immobilized enzyme exhibited greater stability in the presence of various metal ions and inhibitors compared to its free form.

Novel crossover and recombination hotspots massively spread across primate genomes.

Background: The recombination landscape and subsequent natural selection have vast consequences forevolution and speciation. However, most of the crossover and recombination hotspots are yet to be discovered. We previously reported the relevance of C and G trinucleotide two-repeat units (CG-TTUs) in crossovers and recombination.

Comparative analysis of feature selection techniques for COVID-19 dataset.

In the context of early disease detection, machine learning (ML) has emerged as a vital tool. Feature selection (FS) algorithms play a crucial role in ensuring the accuracy of predictive models by identifying the most influential variables. This study, focusing on a retrospective cohort of 4778 COVID-19 patients from Iran, explores the performance of various FS methods, including filter, embedded, and hybrid approaches, in predicting mortality outcomes.

PEGylated Pemetrexed and PolyNIPAM Decorated Gold Nanoparticles: A Biocompatible and Highly Stable CT Contrast Agent for Cancer Imaging.

This study describes a multifunctional nanoparticle platform for targeted CT imaging and therapy of cancers. Pemetrexed (conjugated with polyethylene glycol, MW 2000 Da) and polyNIPAM (PEGylated) were designed for targeted delivery to folate receptors and thermally ablated tumors, respectively. These moieties were coated on gold nanoparticles (7 and 30 nm), and the prepared compounds were characterized using H NMR, FT-IR, CHNS, DLS, TEM, TGA, and UV-vis.

In-vitro cytotoxicity of biosynthesized nanoceria using Eucalyptus camaldulensis leaves extract against MCF-7 breast cancer cell line.

Cerium oxide nanoparticles possess unique properties that make them promising candidates in various fields, including cancer treatment. Among the proposed synthesis methods for CNPs, biosynthesis using natural extracts, offers an eco-friendly and convenient approach for producing CNPs, particularly for biomedical applications. In this study, a novel method of biosynthesis using the aqueous extract of Eucalyptus camaldulensis leaves was used to synthesize CNPs.

Synthesis, Radiolabeling, and Biodistribution Study of a Novel DOTA-Peptide for Targeting Vascular Endothelial Growth Factor Receptors in the Molecular Imaging of Breast Cancer.

As angiogenesis plays a pivotal role in tumor progression and metastasis, leading to more cancer-related deaths, the angiogenic process can be considered as a target for diagnostic and therapeutic applications. The vascular endothelial growth factor receptor-1 (VEGR-1) and VEGFR-2 have high expression on breast cancer cells and contribute to angiogenesis and tumor development. Thus, early diagnosis through VEGFR-1/2 detection is an excellent strategy that can significantly increase a patient's chance of survival.

Changes in the transcriptomic profile of cumulus cells under the influence of cumulus-oocytes complex pre-incubation.

Pre-incubation of the cumulus-oocyte complex (COCs) may lead to better function of cumulus cells (CCs) and higher oocyte quality by changing the transcriptomic profile of CCs. 140 cumulus cell samples were isolated from 12 participants and divided into two groups based on pre-incubation time. In the T0 group, the COCs were immediately dissected to separate the CCs from around the oocytes.

Novel Gd-DTPA-peptide for targeted breast tumor magnetic resonance imaging.

The prevalence of breast cancer underscores the imperative for early diagnosis in guiding treatment decisions. This study introduces a novel contrast agent, Gd-DTPA-VGB3, derived from the peptide VGB3 targeting vascular endothelial growth factor receptor-1 (VEGFR1) and VEGFR2, to enhance the contrast of conventional drug Magnevist in breast tumor MRI. The MRI contrast agent was synthesized on rink amide resin via Fmoc strategy, incorporating amino acids, and coupling to diethylenetriaminepentaacetic acid (DTPA).