Comprehensive transcriptomic meta-analysis unveils new responsive genes to methyl jasmonate and ethylene in Catharanthusroseus.

In Catharanthus roseus, vital plant hormones, namely methyl jasmonate (MeJA) and ethylene, serve as abiotic triggers, playing a crucial role in stimulating the production of specific secondary compounds with anticancer properties. Understanding how plants react to various stresses, stimuli, and the pathways involved in biosynthesis holds significant promise. The application of stressors like ethylene and MeJA induces the plant's defense mechanisms, leading to increased secondary metabolite production. To delve into the essential transcriptomic processes linked to hormonal responses, this study employed an integrated approach combining RNA-Seq data meta-analysis and system biology methodologies. Furthermore, the validity of the meta-analysis findings was confirmed using RT-qPCR. Within the meta-analysis, 903 genes exhibited differential expression (DEGs) when comparing normal conditions to those of the treatment. Subsequent analysis, encompassing gene ontology, KEGG, TF, and motifs, revealed that these DEGs were actively engaged in multiple biological processes, particularly in responding to various stresses and stimuli. Additionally, these genes were notably enriched in diverse biosynthetic pathways, including those related to TIAs, housing valuable medicinal compounds found in this plant. Furthermore, by conducting co-expression network analysis, we identified hub genes within modules associated with stress response and the production of TIAs. Most genes linked to the biosynthesis pathway of TIAs clustered within three specific modules. Noteworthy hub genes, including Helicase ATP-binding domain, hbdA, and ALP1 genes within the blue, turquoise, and green module networks, are presumed to play a role in the TIAs pathway. These identified candidate genes hold potential for forthcoming genetic and metabolic engineering initiatives aimed at augmenting the production of secondary metabolites and medicinal compounds within C. roseus.

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. METHODS: Cachectic mouse muscle transcriptomic datasets of ten different studies were combined and mined by seven attribute weighting models, which analysed both categorical variables and numerical variables. The transcriptomic signature of cancer cachexia was identified by attribute weighting algorithms and was used to evaluate the performance of eleven pattern discovery models. The signature was employed to find the best combination of drugs (drug repurposing) for developing cancer cachexia treatment strategies, as well as to evaluate currently used cachexia drugs by literature mining. RESULTS: Attribute weighting algorithms ranked 26 genes as the transcriptomic signature of muscle from mice with cancer cachexia. Deep Learning and Random Forest models performed better in differentiating cancer cachexia cases based on muscle transcriptomic data. Literature mining revealed that a combination of melatonin and infliximab has negative interactions with 2 key genes (Rorc and Fbxo32) upregulated in the transcriptomic signature of cancer cachexia in muscle. CONCLUSIONS: The integration of machine learning, meta-analysis and literature mining was found to be an efficient approach to identifying a robust transcriptomic signature for cancer cachexia, with implications for improving clinical diagnosis and management of this condition.

A Panel of miRNA Biomarkers Common to Serum and Brain-Derived Extracellular Vesicles Identified in Mouse Model of Amyotrophic Lateral Sclerosis.

Amyotrophic lateral sclerosis (ALS) is a progressive motor neuron disease characterised by the deposition of aggregated proteins including TAR DNA-binding protein 43 (TDP-43) in vulnerable motor neurons and the brain. Extracellular vesicles (EVs) facilitate the spread of neurodegenerative diseases and can be easily accessed in the bloodstream. This study aimed to identify a panel of EV miRNAs that can capture the pathology occurring in the brain and peripheral circulation. EVs were isolated from the cortex (BDEVs) and serum (serum EVs) of 3 month-old and 6-month-old TDP-43*Q331K and TDP-43*WT mice. Following characterisation and miRNA isolation, the EVs underwent next-generation sequencing where 24 differentially packaged miRNAs were identified in the TDP-43*Q331K BDEVs and 7 in the TDP-43*Q331K serum EVs. Several miRNAs, including miR-183-5p, were linked to ALS. Additionally, miR-122-5p and miR-486b-5p were identified in both panels, demonstrating the ability of the serum EVs to capture the dysregulation occurring in the brain. This is the first study to identify miRNAs common to both the serum EVs and BDEVs in a mouse model of ALS.

Bunium persicum Seeds Extract in Combination with Vincristine Mediates Apoptosis in MCF-7 Cells through Regulation of Involved Genes and Proteins Expression.

BACKGROUND: Bunium persicum seeds, a member of the Apiaceae family, have historically been consumed as part of the Iranian diet. OBJECTIVE: While many of this herb's biological properties have been fully investigated, there is currently no reliable information about its anticancer/cytotoxic properties. METHODS: Herein, we first determined the major bioactive compounds of B. persicum seed extract (BPSE) via GC-Mass analysis. We evaluated the cytotoxicity of the extract alone as well as in combination with vincristine (VCR), a commonly used chemotherapy drug, using MTT assays on two breast cancer cell lines, MCF-7 and MDA-MB-231, as well as a normal breast cancer cell line, MCF-10A. Moreover, these compounds were evaluated in vitro for their anticancer activity using ROS assays, Real-Time PCR, Western blots, flow cytometry, and cell cycle assays. RESULTS: As a result of our investigation, it was determined that the extract significantly reduced the viability of cancerous cells while remaining harmless to normal cells. The combination of BPSE and VCR also resulted in synergistic effects. BPSE and/or BPSE-VCR treatment increased the intracellular ROS of MCF-7 cells by over twofold. Moreover, the IC30 of BPSE (100 µg/ml) significantly increased the BAX/BCL-2 and P53 gene expression while reducing the expression of the MYC gene. Moreover, treated cells were arrested in the G2 phase of the cell cycle. The BPSE-VCR combination synergistically reduced the NF-κB and increased the Caspase-7 proteins' expression. The percent of apoptosis in the cells treated with the extract, VCR, and their combination was 27, 11, and 50, respectively. CONCLUSIONS: The present study demonstrated the anticancer activity of the BPSE and its potential for application in combination therapy with VCR.

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. Despite this, short- and long-term CR regulated different sets of genes, leading to distinct transcriptomic signatures. The employed models were able to simultaneously analyze categorical and numerical variables, evaluating the effect of tissue type along with expression data. In all tissues, transcription factors, zinc finger protein 45-like and zinc finger BTB domain-containing two, were the top selected genes by the models in short and long-term CR treatments, respectively. Text mining identified associations between genes of the short-term CR signature and neurodegeneration, stress, and obesity and between genes of the long-term signature and the nervous system. Literature mining-based drug repurposing showed that alongside known CR mimetics such as resveratrol and rapamycin, candidates not typically associated with CR mimetics may be repurposed based on their interaction with transcriptomic signatures of CR. This study goes some way to unravelling the global effects of CR and opens new avenues for treatment for emotional disorders, neurodegeneration, and obesity.

Meta-analysis of integrated ChIP-seq and transcriptome data revealed genomic regions affected by estrogen receptor alpha in breast cancer.

BACKGROUND: The largest group of patients with breast cancer are estrogen receptor-positive (ER+) type. The estrogen receptor acts as a transcription factor and triggers cell proliferation and differentiation. Hence, investigating ER-DNA interaction genomic regions can help identify genes directly regulated by ER and understand the mechanism of ER action in cancer progression. METHODS: In the present study, we employed a workflow to do a meta-analysis of ChIP-seq data of ER+ cell lines stimulated with 10 nM and 100 nM of E2. All publicly available data sets were re-analyzed with the same platform. Then, the known and unknown batch effects were removed. Finally, the meta-analysis was performed to obtain meta-differentially bound sites in estrogen-treated MCF7 cell lines compared to vehicles (as control). Also, the meta-analysis results were compared with the results of T47D cell lines for more precision. Enrichment analyses were also employed to find the functional importance of common meta-differentially bound sites and associated genes among both cell lines. RESULTS: Remarkably, POU5F1B, ZNF662, ZNF442, KIN, ZNF410, and SGSM2 transcription factors were recognized in the meta-analysis but not in individual studies. Enrichment of the meta-differentially bound sites resulted in the candidacy of pathways not previously reported in breast cancer. PCGF2, HNF1B, and ZBED6 transcription factors were also predicted through the enrichment analysis of associated genes. In addition, comparing the meta-analysis results of both ChIP-seq and RNA-seq data showed that many transcription factors affected by ER were up-regulated. CONCLUSION: The meta-analysis of ChIP-seq data of estrogen-treated MCF7 cell line leads to the identification of new binding sites of ER that have not been previously reported. Also, enrichment of the meta-differentially bound sites and their associated genes revealed new terms and pathways involved in the development of breast cancer which should be examined in future in vitro and in vivo studies.

Apoptotic effects of human amniotic fluid mesenchymal stem cells conditioned medium on human MCF-7 breast cancer cell line.

Introduction: Breast cancer, as the most common malignancy among women, is shown to have a high mortality rate and resistance to chemotherapy. Research has shown the possible inhibitory role of Mesenchymal stem cells in curing cancer. Thus, the present work used human amniotic fluid mesenchymal stem cell-conditioned medium (hAFMSCs-CM) as an apoptotic reagent on the human MCF-7 breast cancer cell line. Methods: Conditioned medium (CM) was prepared from hAFMSCs. After treating MCF-7 cells with CM, a number of analytical procedures (MTT, real-time PCR, western blot, and flow cytometry) were recruited to evaluate the cell viability, Bax and Bcl-2 gene expression, P53 protein expression, and apoptosis, respectively. Human fibroblast cells (Hu02) were used as the negative control. In addition, an integrated approach to meta-analysis was performed. Results: The MCF-7 cells' viability was decreased significantly after 24 hours (P < 0.0001) and 72 hours (P < 0.05) of treatment. Compared with the control cells, Bax gene's mRNA expression increased and Bcl-2's mRNA expression decreased considerably after treating for 24 hours with 80% hAFMSCs-CM (P = 0.0012, P < 0.0001, respectively); an increasing pattern in P53 protein expression could also be observed. The flow cytometry analysis indicated apoptosis. Results from literature mining and the integrated meta-analysis showed that hAFMSCs-CM is able to activate a molecular network where Bcl2 downregulation stands in harmony with the upregulation of P53, EIF5A, DDB2, and Bax, leading to the activation of apoptosis. Conclusion: Our finding demonstrated that hAFMSCs-CM presents apoptotic effect on MCF-7 cells; therefore, the application of hAFMSCs-CM, as a therapeutic reagent, can suppress breast cancer cells' viabilities and induce apoptosis.

Gut Microbiota and Behavioural Issues in Production, Performance, and Companion Animals: A Systematic Review.

The literature has identified poor nutrition as the leading factor in the manifestation of many behavioural issues in animals, including aggression, hyperalertness, and stereotypies. Literature focused on all species of interest consistently reported that although there were no significant differences in the richness of specific bacterial taxa in the microbiota of individual subjects with abnormal behaviour (termed alpha diversity), there was variability in species diversity between these subjects compared to controls (termed beta diversity). As seen in humans with mental disorders, animals exhibiting abnormal behaviour often have an enrichment of pro-inflammatory and lactic acid-producing bacteria and a reduction in butyrate-producing bacteria. It is evident from the literature that an association exists between gut microbiota diversity (and by extension, the concurrent production of microbial metabolites) and abnormal behavioural phenotypes across various species, including pigs, dogs, and horses. Similar microbiota population changes are also evident in human mental health patients. However, there are insufficient data to identify this association as a cause or effect. This review provides testable hypotheses for future research to establish causal relationships between gut microbiota and behavioural issues in animals, offering promising potential for the development of novel therapeutic and/or preventative interventions aimed at restoring a healthy gut-brain-immune axis to mitigate behavioural issues and, in turn, improve health, performance, and production in animals.

Integration of transcriptomic and metabolomic analyses provides insights into response mechanisms to nitrogen and phosphorus deficiencies in soybean.

Nitrogen (N) and phosphorus (P) are two essential plant macronutrients that can limit plant growth by different mechanisms. We aimed to shed light on how soybean respond to low nitrogen (LN), low phosphorus (LP) and their combined deficiency (LNP). Generally, these conditions triggered changes in gene expression of the same processes, including cell wall organization, defense response, response to oxidative stress, and photosynthesis, however, response was different in each condition. A typical primary response to LN and LP was detected also in soybean, i.e., the enhanced uptake of N and P, respectively, by upregulation of genes for the corresponding transporters. The regulation of genes involved in cell wall organization showed that in LP roots tended to produce more casparian strip, in LN more secondary wall biosynthesis occurred, and in LNP reduction in expression of genes involved in secondary wall production accompanied by cell wall loosening was observed. Flavonoid biosynthesis also showed distinct pattern of regulation in different conditions: more anthocyanin production in LP, and more isoflavonoid production in LN and LNP, which we confirmed also on the metabolite level. Interestingly, in soybean the nutrient deficiencies reduced defense response by lowering expression of genes involved in defense response, suggesting a role of N and P nutrition in plant disease resistance. In conclusion, we provide detailed information on how LN, LP, and LNP affect different processes in soybean roots on the molecular and physiological levels.

Machine learning models effectively distinguish attention-deficit/hyperactivity disorder using event-related potentials.

Accurate diagnosis of Attention-Deficit/Hyperactivity Disorder (ADHD) is a significant challenge. Misdiagnosis has significant negative medical side effects. Due to the complex nature of this disorder, there is no computational expert system for diagnosis. Recently, automatic diagnosis of ADHD by machine learning analysis of brain signals has received an increased attention. This paper aimed to achieve an accurate model to discriminate between ADHD patients and healthy controls by pattern discovery. Event-Related Potentials (ERP) data were collected from ADHD patients and healthy controls. After pre-processing, ERP signals were decomposed and features were calculated for different frequency bands. The classification was carried out based on each feature using seven machine learning algorithms. Important features were then selected and combined. To find specific patterns for each model, the classification was repeated using the proposed patterns. Results indicated that the combination of complementary features can significantly improve the performance of the predictive models. The newly developed features, defined based on band power, were able to provide the best classification using the Generalized Linear Model, Logistic Regression, and Deep Learning with the average accuracy and Receiver operating characteristic curve > %99.85 and > 0.999, respectively. High and low frequencies (Beta, Delta) performed better than the mid, frequencies in the discrimination of ADHD from control. Altogether, this study developed a machine learning expert system that minimises misdiagnosis of ADHD and is beneficial for the evaluation of treatment efficacy.

Long-Term Calorie Restriction Alters Anxiety-like Behaviour and the Brain and Adrenal Gland Transcriptomes of the Ageing Male Rat.

Further examination of the molecular regulators of long-term calorie restriction (CR), reported to have an anxiolytic effect, may highlight novel therapeutic targets for anxiety disorders. Here, adult male Hooded Wistar rats were exposed to a 25% CR whilst anxiety-like behaviour was assessed at 6-, 12-, and 18-months of age via the elevated plus maze, open field, and acoustic startle tests. Next-generation sequencing was then used to measure transcriptome-wide gene expression in the hypothalamus, amygdala, pituitary, and adrenal glands. Results showed an anxiolytic behavioural profile across early, middle, and late adulthood by CR, with the strongest effects noted at 6-months. Transcriptomic analysis by seven attribute weighting algorithms, including Info Gain Ratio, Rule, Chi Squared, Gini Index, Uncertainty, Relief, and Info Gain, led to the development of a signature of long-term CR, independent of region. Complement C1q A chain (C1qa), an extracellular protein, expression was significantly decreased by CR in most regions examined. Furthermore, text mining highlighted the positive involvement of C1qa in anxiety, depression, neurodegeneration, stress, and ageing, collectively identifying a suitable biomarker candidate for CR. Overall, the current study identified anxiety-related phenotypic changes and a novel transcriptome signature of long-term CR, indicating potential therapeutic targets for anxiety, depression, and neurodegeneration.

Meta-analysis highlights the key drought responsive genes in genes: PEPC and TaSAG7 are hubs response networks.

BACKGROUND: Wheat is the most important cereal. One of the environmental stresses is drought that harm the production of many cereals and every year due to low rainfall and frequent droughts, the need to produce plants resistant to this stress is felt. Therefore, identification and evaluation of the genes involved in the production of this resistance in plants are of great importance. By identifying these genes and changing their expression, it is possible to produce resistant plants that can tolerate dehydration and drought, with at least a qualitative and quantitative reduction in yield. RESULTS: Based on the meta-analysis results obtained in this study, in resistant cultivars ~ 4% (2394/61290) of the probe IDs decreased and ~ 4.5% (2670/61290) increased expression, furthermore in susceptible cultivars ~ 7% (4183/61290) of probe IDs decreased and ~ 6% (3591/61290) increased expression (P value ≤ 0.05). List of up- and downregulated genes was revealed, among the expressed genes of transcription factors Myb3, ethylene-responsive 5a, MIKC-type MADS-box WM24B, and salinity inducible ERF4 in resistant cultivars and transcription factors WRKY15, MADS-box TaAGL8, WRKY39, and Myb in susceptible cultivars, they showed a significant increase in expression, these transcription factors are of great importance in drought stress. Among them, ethylene responsive 5a in resistant cultivars by 3 times and Myb in susceptible cultivars by 2.6 times have shown the highest expression change. Using Cytoscape Hub software, the Phosphoenolpyruvate carboxylase (PEPC) and lyase isocitrate (TaSAG7) genes, which have significantly different expressions in resistant and susceptible wheat cultivars. PEPC and TaSAG7 genes were upregulated in resistant wheat cultivars as well as down regulated in susceptible cultivars. Also, the qPCR results of selected genes were consistent with the outcomes of the meta-analysis. CONCLUSIONS: All microarray data were collected from the NCBI Gene Expression Omnibus site. Libraries with drought-tolerant and susceptible cultivars for wheat were considered under the stress and control conditions from whole leaf tissue. By meta-analysis combined the purposeful results of multiple experiments, and found list of genes expressed in reverse between the two cultivars. These genes can distinguish between different susceptible and resistant wheat cultivars.

Transcriptome Analysis of Breast Muscle Reveals Pathways Related to Protein Deposition in High Feed Efficiency of Native Turkeys.

Feed efficiency is important due to the high cost of food, which accounts for about 70% of the total cost of a turkey breeding system. Native poultry are an important genetic resource in poultry breeding programs. This study aimed to conduct a global transcriptome analysis of native male turkeys which have been phenotyped for high and low feed efficiency. Feed efficiency traits were recorded during the experimental period. After slaughter, the three most efficient and three least efficient male turkeys were selected for RNA-Seq analysis. A total of 365 genes with different expressions in muscle tissue were identified between turkeys with a high feed efficiency compared to turkeys with a low feed efficiency. In the pathway analysis of up-regulated genes, major pathways included the "metabolism of glycine, serine, and threonine"; the "adipocytokine signaling pathway" and the "biosynthesis of amino acids". In the pathway analysis of down-regulated genes, the major pathways included "dorso-ventral axis formation" and "actin cytoskeleton regulation". In addition, gene set enrichment analyses were performed, which showed that high feed efficiency birds exhibit an increased expression of genes related to the biosynthesis of amino acids and low feed efficiency birds an increased expression of genes related to the immune response. Furthermore, functional analysis and protein network interaction analysis revealed that genes including GATM, PSAT1, PSPH, PHGDH, VCAM1, CD44, KRAS, SRC, CAV3, NEDD9, and PTPRQ were key genes for feed efficiency. These key genes may be good potential candidates for biomarkers of feed efficiency in genetic selection in turkeys.

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. A particular attention was paid to genomic locations of splice-disrupt variants on target genes. HLA-A in prostate cancer, MSR1 in familial prostate cancer, and EGFR in both castration-resistant prostate cancer and metastatic castration-resistant had the highest allele frequencies of splice-disrupt variations. Some splice-disrupt variants, located on coding sequences of NCOR2, PTPRC, and CRP, were solely present in the advanced metastatic castration-resistant prostate cancer. High-risk splice-disrupt variants were identified based on computationally calculated Polymorphism Phenotyping (PolyPhen), Sorting Intolerant From Tolerant (SIFT), and Genomic Evolutionary Rate Profiling (GERP) + + scores as well as the recorded clinical significance in dbSNP database of NCBI. Functional annotation of damaging splice-disrupt variants highlighted important cancer-associated functions, including endocrine resistance, lipid metabolic process, steroid metabolic process, regulation of mitotic cell cycle, and regulation of metabolic process. This is the first study that profiles the splice-disrupt genomic variants and their target genes in prostate cancer. Literature mining based variant analysis highlighted the importance of rs1800716 variant, located on the CYP2D6 gene, involved in a range of important functions, such as RNA spicing, drug interaction, death, and urotoxicity. CONCLUSIONS: This is the first study that profiles the splice-disrupt genomic variants and their target genes in different types of prostate cancer. Unravelling alternative splicing opens a new avenue towards the establishment of new diagnostic and prognostic markers for prostate cancer progression and metastasis.

Comparative transcriptome analysis of two contrasting resistant and susceptible Aegilops tauschii accessions to wheat leaf rust (Puccinia triticina) using RNA-sequencing.

Leaf rust, caused by Puccinia triticina Eriks., is the most common rust disease of wheat (Triticum aestivum L.) worldwide. Owing to the rapid evolution of virulent pathotypes, new and effective leaf rust resistance sources must be found. Aegilops tauschii, an excellent source of resistance genes to a wide range of diseases and pests, may provide novel routes for resistance to this disease. In this study, we aimed to elucidate the transcriptome of leaf rust resistance in two contrasting resistant and susceptible Ae. tauschii accessions using RNA-sequencing. Gene ontology, analysis of pathway enrichment and transcription factors provided an apprehensible review of differentially expressed genes and highlighted biological mechanisms behind the Aegilops-P. triticina interaction. The results showed the resistant accession could uniquely recognize pathogen invasion and respond precisely via reducing galactosyltransferase and overexpressing chromatin remodeling, signaling pathways, cellular homeostasis regulation, alkaloid biosynthesis pathway and alpha-linolenic acid metabolism. However, the suppression of photosynthetic pathway and external stimulus responses were observed upon rust infection in the susceptible genotype. In particular, this first report of comparative transcriptome analysis offers an insight into the strength and weakness of Aegilops against leaf rust and exhibits a pipeline for future wheat breeding programs.

Transcriptome signature of two lactation stages in Ghezel sheep identifies using RNA-Sequencing.

The expression of genes and their regulation during lactation in Ghezel sheep breed remains less understood. To explore the underlying molecular mechanism of the lactation process in the mammary gland, transcriptome profiles of Iranian fat-tailed Ghezel sheep breed milk at two stages, before (BF) and after peak (AF) stages of lactation were investigated. Functional impacts of differentially expressed genes (DEGs) between BF and AF stages were surveyed using Gene Ontology (GO) and Protein-Protein Interaction (PPI) network analysis. Totally, 75 DEGs were identified between BF and AF stages of lactation. The RNA-Seq results were validated by Q-RT-PCR. Gene ontology of DEGs mainly enriched in metabolic process and oxidative phosphorylation. PPI network analysis also highlighted the contribution of peroxisome proliferator-activated receptors (PPAR) signaling, oxidative phosphorylation and metabolic pathways in the lactation process. Intriguingly, the genes involved in fat metabolism dominantly down-regulated at AF stage. Our results provide new insight into transcriptional changes and add to growing body of knowledge on the lactation process in fat-tailed sheep breeds.

AFExNet: An Adversarial Autoencoder for Differentiating Breast Cancer Sub-Types and Extracting Biologically Relevant Genes.

Technological advancements in high-throughput genomics enable the generation of complex and large data sets that can be used for classification, clustering, and bio-marker identification. Modern deep learning algorithms provide us with the opportunity of finding most significant features in such huge dataset to characterize diseases (e.g., cancer) and their sub-types. Thus, developing such deep learning method, which can successfully extract meaningful features from various breast cancer sub-types, is of current research interest. In this paper, we develop dual stage (unsupervised pre-training and supervised fine-tuning) neural network architecture termed AFExNet based on adversarial auto-encoder (AAE) to extract features from high dimensional genetic data. We evaluated the performance of our model through twelve different supervised classifiers to verify the usefulness of the new features using public RNA-Seq dataset of breast cancer. AFExNet provides consistent results in all performance metrics across twelve different classifiers which makes our model classifier independent. We also develop a method named 'TopGene' to find highly weighted genes from the latent space which could be useful for finding cancer bio-markers. Put together, AFExNet has great potential for biological data to accurately and effectively extract features. Our work is fully reproducible and source code can be downloaded from Github: https://github.com/NeuroSyd/breast-cancer-sub-types.

Pharmacokinetic profile and effect on the faecal microbiome of a single dose of pradofloxacin oral suspension in the rabbit (Oryctolagus cuniculus).

Fluoroquinolones are often administered to pet rabbits given their perceived safety and limited effects on anaerobic gut microbiota. However, the pharmacokinetics and relative safety of pradofloxacin, a third-generation veterinary fluoroquinolone with a much broader spectrum of activity, have not been reported in this species. Here, we determined the pharmacokinetic profile of a single dose of oral pradofloxacin in rabbits and evaluated effects on the faecal microbiome. Four mature female rabbits were administered pradofloxacin (25 mg/ml oral suspension), at a dose of 7.5 mg/kg. The pradofloxacin median (range) Tmax was 4.50 (2.00-5.00) h, Cmax 600.66 (395.85-886.72) ng/ml and t½ was 1.27 (0.12-1.39) h. These results indicated that oral absorption of pradofloxacin was slower, and elimination faster compared with other fluoroquinolones in healthy rabbits, as well as relative to cats and dogs. Following treatment with pradofloxacin, faecal microbiota profiling showed some compositional differences between treated and control animals. This was the result of a significant decrease in the abundance of Proteobacteria, in particular bacteria belonging to the Pseudomonas, Atopostipes and Parabacteroides genera. The pharmacokinetic profile of pradofloxacin in rabbits should be further studied by increasing the sample size and using multiple-dose protocols (i.e. 7 days) to confirm safety. Further information on the effects of protein binding, higher dosages and disease on pradofloxacin pharmacokinetics in rabbits are needed before an accurate dosing regimen can be recommended.

The Essential Oil from Oliveria decumbens Vent. (Apiaceae) as Inhibitor of Breast Cancer Cell (MCF-7) Growth.

Oliveria decumbens Vent. is an aromatic and medicinal plant traditionally used in Iran for the treatment of infections, gastrointestinal diseases, cancer, and inflammation. This research was aimed at investigating the pharmacological potential of O. decumbens essential oil (OEO) and its main compounds, focusing on OEO's cytotoxic effects on MCF-7 breast cancer cells. OEO was obtained by hydro-distillation, and the chemical constituents were identified using GC-MS. Thymol, carvacrol, γ-terpinene, and p-cymene were the main OEO constituents. When MCF-7 cells were treated with OEO, the expressions of genes related to apoptosis (BIM and Bcl-2), tumor suppression (PTEN), and cell growth inhibition (AURKA), were evaluated using real-time PCR. Moreover, molecular docking was used for studying in silico the interaction of OEO principal compounds with PTEN and AURKA. The expression of AURKA was significantly reduced since the OEO treatment enhanced the expression of PTEN. Through in silico molecular docking, it was revealed that thymol, carvacrol, p-cymene, and γ-terpinene can activate PTEN and thus inhibit AURKA. Additionally, the DNA fragmentation assay, acridine orange/ethidium bromide (AO/EB) double-staining assay, and real-time PCR highlighted the fact that the OEO treatment could activate apoptosis and inhibit cell proliferation. Therefore, OEO is a viable candidate to be employed in the pharmaceutical industry, specifically as a possible agent for cancer therapy.

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. A worldwide population-based observational study has been conducted and a range of attributes were weighted using 10 attribute weighting models against the normalized number of infected cases or death in the form of numeric, binominal and polynomial labels. Statistical analysis was performed for the most weighted and the most common attributes of all types of labels. By the end of March 2021, the school closure data of 198 countries with at least one COVID-19 case were available. The days before the first school closure were one of the most weighted factors in relation to the normalized number of infected cases and deaths in numeric, binomial, and quartile forms. The average of days before the first school closure in the lowest quartile to highest quartile of infected cases (Q1, Q2, Q3 and Q4) was -6.10 [95% CI, -26.5 to 14.2], 9.35 [95% CI, 2.16 to 16.53], 17.55 [95% CI, 5.95 to 29.15], and 16.00 [95% CI, 11.69 to 20.31], respectively. In addition, 188 countries reported at least one death from COVID-19. The average of the days before the first school closure in the lowest quartile of death to highest quartile (Q1, Q2, Q3 and Q4) was -49.4 [95% CI, -76.5 to -22.3], -10.34 [95% CI, -30.12 to 9.44], -18.74 [95% CI, -32.72 to -4.77], and -12.89 [95% CI, -27.84 to 2.06], respectively. Countries that closed schools faster, especially before the detection of any confirmed case or death, had fewer COVID-19 cases or deaths per million of the population on total days of involvement. It can be concluded that rapid prevention policies are the main determinants of the countries' success.