Delivery of doxorubicin by FeO nanoparticles, reduces multidrug resistance gene expression in ovarian cancer cells.

Background: Ovarian cancer is one of the most common malignancy in women with significant mortality rate due to the resistance to chemotherapy drugs. Doxorubicin (DOX) is a chemotropic agent in ovarian cancer treatment. Overexpression of multidrug resistance (MDR) genes, such as ABCB1, in cancer cells after chemotherapy is one of main problems in clinical applications.

Transcriptomic signature of cancer cachexia by integration of machine learning, literature mining and meta-analysis.

Background: Cancer cachexia is a severe metabolic syndrome marked by skeletal muscle atrophy. A successful clinical intervention for cancer cachexia is currently lacking. The study of cachexia mechanisms is largely based on preclinical animal models and the availability of high-throughput transcriptomic datasets of cachectic mouse muscles is increasing through the extensive use of next generation sequencing technologies.

Crosstalk between short- and long-term calorie restriction transcriptomic signatures with anxiety-like behavior, aging, and neurodegeneration: implications for drug repurposing.

Calorie restriction (CR) is considered an effective intervention for anxiety, aging, and obesity. We investigated the effects of short- and long-term CR on behavior as well as transcriptome profiles in the hypothalamus, amygdala, prefrontal cortex, pituitary, and adrenal glands of Hooded Wistar and Long Evans male rats. A reduction in anxiety-like behavior, as assessed via the elevated plus maze, was observed in both short- and long-term CR.

Splice-disrupt genomic variants in prostate cancer.

Background: Splice-disrupt genomic variants are one of the causes of cancer-causing errors in gene expression. Little is known about splice-disrupt genomic variants.

Methods And Results: Here, pattern of splice-disrupt variants was investigated using 21,842,764 genomic variants in different types of prostate cancer.

Fast school closures correspond with a lower rate of COVID-19 incidence and deaths in most countries.

School closures have been used as one of the main nonpharmaceutical interventions to overcome the spread of SARS-CoV-2. Different countries use this intervention with a wide range of time intervals from the date of the first confirmed case or death. This study aimed to investigate whether fast or late school closures affect the cumulative number of COVID-19 cases or deaths.

Evaluation of the Effectiveness of Herbal Components Based on Their Regulatory Signature on Carcinogenic Cancer Cells.

Predicting cancer cells' response to a plant-derived agent is critical for the drug discovery process. Recently transcriptomes advancements have provided an opportunity to identify regulatory signatures to predict drug activity. Here in this study, a combination of meta-analysis and machine learning models have been used to determine regulatory signatures focusing on differentially expressed transcription factors (TFs) of herbal components on cancer cells.

Alternative RNA splicing in stem cells and cancer stem cells: Importance of transcript-based expression analysis.

Alternative ribonucleic acid (RNA) splicing can lead to the assembly of different protein isoforms with distinctive functions. The outcome of alternative splicing (AS) can result in a complete loss of function or the acquisition of new functions. There is a gap in knowledge of abnormal RNA splice variants promoting cancer stem cells (CSCs), and their prospective contribution in cancer progression.

Advances in understanding the specificity function of transporters by machine learning.

Understanding the underlying molecular mechanism of transporter activity is one of the major discussions in structural biology. A transporter can exclusively transport one ion (specific transporter) or multiple ions (general transporter). This study compared categorical and numerical features of general and specific calcium transporters using machine learning and attribute weighting models.

Rule Discovery in Milk Content towards Mastitis Diagnosis: Dealing with Farm Heterogeneity over Multiple Years through Classification Based on Associations.

Subclinical mastitis, an economically challenging disease of dairy cattle, is associated with an increased use of antimicrobials which reduces milk quantity and quality. It is more common than clinical mastitis and far more difficult to detect. Recently, much attention has been paid to the development of machine-learning expert systems for early detection of subclinical mastitis from milking features.

A Transcription Regulatory Sequence in the 5' Untranslated Region of SARS-CoV-2 Is Vital for Virus Replication with an Altered Evolutionary Pattern against Human Inhibitory MicroRNAs.

Our knowledge of the evolution and the role of untranslated region (UTR) in SARS-CoV-2 pathogenicity is very limited. Leader sequence, originated from UTR, is found at the 5' ends of all encoded SARS-CoV-2 transcripts, highlighting its importance. Here, evolution of leader sequence was compared between human pathogenic and non-pathogenic coronaviruses.

Genomic analysis of fluoroquinolone-susceptible phylogenetic group B2 extraintestinal pathogenic Escherichia coli causing infections in cats.

Extraintestinal pathogenic Escherichia coli (ExPEC) can cause urinary tract and other types of infection in cats, but the relationship of cat ExPEC to human ExPEC remains equivocal. This study investigated the prevalence of ExPEC-associated sequence types (STs) from phylogenetic group B2 among fluoroquinolone-susceptible cat clinical isolates. For this, 323 fluoroquinolone-susceptible cat clinical E.

MicroRNA-based regulatory circuit involved in sperm infertility.

miRNAs (MicroRNAs), known as noncoding and important endogenous factors regulating the expression protein-coding genes, are vital regulators in each biological process. Thus, this study aims to explore the key role of four microRNAs in regulating the spermatogenesis. To conduct this experiment, 55 infertile and fertile men provided the study with the sperm and testicular tissue samples.

Comprehensive analysis of machine learning models for prediction of sub-clinical mastitis: Deep Learning and Gradient-Boosted Trees outperform other models.

Sub-clinical bovine mastitis decreases milk quality and production. Moreover, sub-clinical mastitis leads to the use of antibiotics with consequent increased risk of the emergence of antibiotic-resistant bacteria. Therefore, early detection of infected cows is of great importance.

Non-coding and coding genomic variants distinguish prostate cancer, castration-resistant prostate cancer, familial prostate cancer, and metastatic castration-resistant prostate cancer from each other.

A considerable number of deposited variants has provided new possibilities for knowledge discovery in different types of prostate cancer. Here, we analyzed variants located on 3'UTR, 5'UTR, CDs, Intergenic, and Intronic regions in castration-resistant prostate cancer (8496 variants), familial prostate cancer (3241 variants), metastatic castration-resistant prostate cancer (3693 variants), and prostate cancer (16599 variants). Chromosome regions 10p15-p14 and 2p13 were highly enriched (P < 0.

Tissue-specific transcriptional biomarkers in medicinal plants: Application of large-scale meta-analysis and computational systems biology.

Biosynthesis of secondary metabolites in plant is a complex process, regulated by many genes and influenced by several factors. In recent years, the next-generation sequencing (NGS) technology and advanced statistical analysis such as meta-analysis and computational systems biology have provided novel opportunities to overcome biological complexity. Here, we performed a meta-analysis on publicly available transcriptome datasets of twelve economically significant medicinal plants to identify differentially expressed genes (DEGs) between shoot and root tissues and to find the key molecular features which may be effective in the biosynthesis of secondary metabolites.

Unified Transcriptomic Signature of Arbuscular Mycorrhiza Colonization in Roots of by Integration of Machine Learning, Promoter Analysis, and Direct Merging Meta-Analysis.

Plant root symbiosis with Arbuscular mycorrhizal (AM) fungi improves uptake of water and mineral nutrients, improving plant development under stressful conditions. Unraveling the unified transcriptomic signature of a successful colonization provides a better understanding of symbiosis. We developed a framework for finding the transcriptomic signature of Arbuscular mycorrhiza colonization and its regulating transcription factors in roots of .

Computational systems biology analysis of biomarkers in lung cancer; unravelling genomic regions which frequently encode biomarkers, enriched pathways, and new candidates.

Exponentially growing scientific knowledge in scientific publications has resulted in the emergence of a new interdisciplinary science of literature mining. In text mining, the machine reads the published literature and transfers the discovered knowledge to mathematical-like formulas. In an integrative approach in this study, we used text mining in combination with network discovery, pathway analysis, and enrichment analysis of genomic regions for better understanding of biomarkers in lung cancer.

Novel approach for identification of influenza virus host range and zoonotic transmissible sequences by determination of host-related associative positions in viral genome segments.

Background: Recent (2013 and 2009) zoonotic transmission of avian or porcine influenza to humans highlights an increase in host range by evading species barriers. Gene reassortment or antigenic shift between viruses from two or more hosts can generate a new life-threatening virus when the new shuffled virus is no longer recognized by antibodies existing within human populations. There is no large scale study to help understand the underlying mechanisms of host transmission.

Root and shoot parts of strawberry: factories for production of functional human pro-insulin.

Diabetes, a disease caused by excessive blood sugar, is caused by the lack of insulin. For commercial production, insulin is made in bacteria or yeast by protein recombinant technology. The focus of this research is evaluating another resource and producing of recombinant insulin protein in as strawberry as this plant has high potential in production of pharmaceutical proteins.

Soybean SAT1 (Symbiotic Ammonium Transporter 1) encodes a bHLH transcription factor involved in nodule growth and NH4+ transport.

Glycine max symbiotic ammonium transporter 1 was first documented as a putative ammonium (NH4(+)) channel localized to the symbiosome membrane of soybean root nodules. We show that Glycine max symbiotic ammonium transporter 1 is actually a membrane-localized basic helix-loop-helix (bHLH) DNA-binding transcription factor now renamed Glycine max bHLH membrane 1 (GmbHLHm1). In yeast, GmbHLHm1 enters the nucleus and transcriptionally activates a unique plasma membrane NH4(+) channel Saccharomyces cerevisiae ammonium facilitator 1.

Indirect somatic embryogenesis from petal explant of endangered wild population of Fritillaria imperialis.

Fritillaria imperialis is an endangered bulbous plant and therefore in vitro micropropagation of this plant will have a great importance for germplasm conservation and commercial production. Petal explants, for the first time, were cultured on media containing various concentrations of plant growth regulators. In addition, the effects of cold pretreatment and light on induction and regeneration of somatic embryogenesis trough callus were studied in detail.