Growth Performance,Hemato-Immunological Responses,and Digestive Enzyme Activities in Silvery-Black Porgy (<Emphasis Type="Italic">Sparidentex hasta</Emphasis>) Fed Dietary Bovine Lactoferrin

An 8-week study was conducted to evaluate three different diets supplemented with bovine lactoferrin (LF) at 0 (control), 800, and 1200 mg LF kg^?1 diet on somatic growth, hemato-immunological parameters, antioxidant status, and digestive enzyme activities in silvery-black porgy (Sparidentex hasta) juveniles. Fish fed the 800 mg LF kg^?1 diet had higher growth performance and feed utilization parameters than the other groups. Hematological and liver antioxidant parameters were not affected by dietary LF supplementation. Fish fed the 800 mg LF kg^?1 diet had higher plasma lysozyme activity values than the other groups. Total protease activity was higher in fish fed LF-supplemented diets than the control group. Results indicated that diet supplemented with 800 mg kg^?1 for 8 weeks enhanced somatic growth performance, lysozyme activity, and proteolytic digestive enzyme activities in S. hasta, as well as improving feed efficiency parameters like the protein efficiency and feed conversion ratios.     

Protein Interaction Network of Arabidopsis thaliana Female Gametophyte Development Identifies Novel Proteins and Relations

Although the female gametophyte in angiosperms consists of just seven cells, it has a complex biological network. In this study, female gametophyte microarray data from Arabidopsis thaliana were integrated into the Arabidopsis interactome database to generate a putative interaction map of the female gametophyte development including proteome map based on biological processes and molecular functions of proteins. Biological and functional groups as well as topological characteristics of the network were investigated by analyzing phytohormones, plant defense, cell death, transporters, regulatory factors, and hydrolases. This approach led to the prediction of critical members and bottlenecks of the network. Seventy-four and 24 upregulated genes as well as 171 and 3 downregulated genes were identified in subtracted networks based on biological processes and molecular function respectively, including novel genes such as the pathogenesis-related protein 4, ER type Ca²⁺ ATPase 3, dihydroflavonol reductase, and ATP disulfate isomerase. Biologically important relationships between genes, critical nodes, and new essential proteins such as AT1G26830, AT5G20850, CYP74A, AT1G42396, PR4 and MEA were found in the interactome''s network. The positions of novel genes, both upregulated and downregulated, and their relationships with biological pathways, in particular phytohormones, were highlighted in this study.     

Design of tissue culture media for efficient Prunus rootstock micropropagation using artificial intelligence models

Establishing optimized protocols for micropropagation of some economical plants, such as Prunus sp., is still one of the most important challenges for in vitro plant culture researchers. As an example, micropropagation of GF677 hybrid rootstocks (peach × almond) are extremely dependent on the medium ingredients and a large undesirable proportion of GF677 shoots need to be discarded as a result of hyperhydricity and chlorosis. In this study, an artificial intelligence technique—specifically neurofuzzy logic—has been employed, as a modeling tool, to increase knowledge on the effect of 8 ion macronutrients (NH₄ ⁺, NO₃ ^?, Ca²⁺, K⁺, Mg²⁺, SO₄ ^2?, PO₄ ^2? and Na⁺; as inputs) on three growth parameters (outputs): total number of shoots per explant, healthy number of shoots per explant, and their bud number. The model delivered new insights, by three sets of IF–THEN rules, pinpointing the key role of NO₃ ^? and their interactions (NO₃ ^? × Ca²⁺ and NO₃ ^? × Ca²⁺ × K⁺) on all growth parameters measured. All growth parameters showed a high correlation ratio between experimental and predicted values being 77.48, 91.78 and 90.78 for total shoots, healthy number and bud number, respectively. Regression coefficients higher than 77 % together with statistical significant ANOVA (p < 0.01) indicated good performance of neurofuzzy logic models. Moreover, The model also can be used for inferring the best combination of ion concentrations to obtain high quality GF677 micropropagated shoots. In conclusion, we assess the utility of neurofuzzy logic technology in modeling complex databases, identifying new complex interactions among macronutrients, and inferring new results and valuable knowledge, which can be applied to design new plant tissue culture media and improve plant micropropagation.     

Cellular uptake and apoptotic properties of gemini curcumin in gastric cancer cells

Molecular Biology Reports - Curcumin is a polyphenolic natural compound, which has demonstrated to possess antioxidant, anti-inflammatory, and anticancer effects in vitro &amp; in vivo....     

Design,synthesis, and evaluation of imidazo[4,5-c]pyridin-4-one derivatives with dual activity at angiotensin II type 1 receptor and peroxisome proliferator-activated receptor-γ

Identification of a series of imidazo[4,5-c]pyridin-4-one derivatives that act as dual angiotensin II type 1 (AT1) receptor antagonists and peroxisome proliferator-activated receptor-γ (PPARγ) partial agonists is described. Starting from a known AT1 antagonist template, conformational restriction was introduced by incorporation of an indane ring that when combined with appropriate substitution at the imidazo[4,5-c]pyridin-4-one provided novel series 5 possessing the desired dual activity. The mode of interaction of this series with PPARγ was corroborated through the X-ray crystal structure of 12b bound to the human PPARγ ligand binding domain. Modulation of activity at both receptors through substitution at the pyridone nitrogen led to the identification of potent dual AT1 antagonists/PPARγ partial agonists. Among them, 21b was identified possessing potent dual pharmacology (AT1 IC₅₀ = 7 nM; PPARγ EC₅₀ = 295 nM, 27% max) and good ADME properties.     

Combined gene expression and proteomic analysis of EGF induced apoptosis in A431 cells suggests multiple pathways trigger apoptosis

A431 cells, derived from epidermoid carcinoma, overexpress the epidermal growth factor receptor (EGFR) and when treated with a high dose of EGF will undergo apoptosis. We exploited microarray and proteomics techniques and network prediction to study the regulatory mechanisms of EGF-induced apoptosis in A431 cells. We observed significant changes in gene expression in 162 genes, approximately evenly split between pro-apoptotic and anti-apoptotic genes and identified 30 proteins from the proteomic data that had either pro or anti-apoptotic annotation. Our correlation analysis of gene expression and proteome modeled a number of distinct sub-networks that are associated with the onset of apoptosis, allowing us to identify specific pathways and components. These include components of the interferon signalling pathway, and down stream components, including cytokines and suppressors of cytokine signalling. A central component of almost all gene expression sub-networks identified was TP53, which is mutated in A431 cells, and was down regulated. This down regulation of TP53 appeared to be correlated with proteomic sub-networks of cytoskeletal or cell adhesion components that might induce apoptosis by triggering cytochrome C release. Of the only three genes also differentially expressed as proteins, only serpinb1 had a known association with apoptosis. We confirmed that up regulation and cleavage of serpinb1 into L-DNAaseII was correlated with the induction of apoptosis. It is unlikely that a single pathway, but more likely a combination of pathways is needed to trigger EGF induced apoptosis in A431cells.     

Discovery of EST-SSRs in lung cancer: tagged ESTs with SSRs lead to differential amino acid and protein expression patterns in cancerous tissues

Tandem repeats are found in both coding and non-coding sequences of higher organisms. These sequences can be used in cancer genetics and diagnosis to unravel the genetic basis of tumor formation and progression. In this study, a possible relationship between SSR distributions and lung cancer was studied by comparative analysis of EST-SSRs in normal and lung cancerous tissues. While the EST-SSR distribution was similar between tumorous tissues, this distribution was different between normal and tumorous tissues. Trinucleotides tandem repeats were highly different; the number of trinucleotides in ESTs of lung cancer was 3 times higher than normal tissue. Significant negative correlation between normal and cancerous tissue showed that cancerous tissue generates different types of trinucleotides. GGC and CGC were the more frequent expressed trinucleotides in cancerous tissue, but these SSRs were not expressed in normal tissue. Similar to the EST level, the expression pattern of EST-SSRs-derived amino acids was significantly different between normal and cancerous tissues. Arg, Pro, Ser, Gly, and Lys were the most abundant amino acids in cancerous tissues, and Leu, Cys, Phe, and His were significantly more abundant in normal tissues than in cancerous tissues. Next, the putative functions of triplet SSR-containing genes were analyzed. In cancerous tissue, EST-SSRs produce different types of proteins. Chromodomain helicase DNA binding proteins were one of the major protein products of EST-SSRs in the cancerous library, while these proteins were not produced from EST-SSRs in normal tissue. For the first time, the findings of this study confirmed that EST-SSRs in normal lung tissues are different than in unhealthy tissues, and tagged ESTs with SSRs cause remarkable differences in amino acid and protein expression patterns in cancerous tissue. We suggest that EST-SSRs and EST-SSRs differentially expressed in cancerous tissue may be suitable candidate markers for lung cancer diagnosis and prediction.     

Protein attributes contribute to halo-stability, bioinformatics approach

Halophile proteins can tolerate high salt concentrations. Understanding halophilicity features is the first step toward engineering halostable crops. To this end, we examined protein features contributing to the halo-toleration of halophilic organisms. We compared more than 850 features for halophilic and non-halophilic proteins with various screening, clustering, decision tree, and generalized rule induction models to search for patterns that code for halo-toleration. Up to 251 protein attributes selected by various attribute weighting algorithms as important features contribute to halo-stability; from them 14 attributes selected by 90% of models and the count of hydrogen gained the highest value (1.0) in 70% of attribute weighting models, showing the importance of this attribute in feature selection modeling. The other attributes mostly were the frequencies of di-peptides. No changes were found in the numbers of groups when K-Means and TwoStep clustering modeling were performed on datasets with or without feature selection filtering. Although the depths of induced trees were not high, the accuracies of trees were higher than 94% and the frequency of hydrophobic residues pointed as the most important feature to build trees. The performance evaluation of decision tree models had the same values and the best correctness percentage recorded with the Exhaustive CHAID and CHAID models. We did not find any significant difference in the percent of correctness, performance evaluation, and mean correctness of various decision tree models with or without feature selection. For the first time, we analyzed the performance of different screening, clustering, and decision tree algorithms for discriminating halophilic and non-halophilic proteins and the results showed that amino acid composition can be used to discriminate between halo-tolerant and halo-sensitive proteins.     

Potential drugs used in the antibody–drug conjugate (ADC) architecture for cancer therapy

Cytotoxic small-molecule drugs have a major influence on the fate of antibody–drug conjugates (ADCs). An ideal cytotoxic agent should be highly potent, remain stable while linked to ADCs, kill the targeted tumor cell upon internalization and release from the ADCs, and maintain its activity in multidrug-resistant tumor cells. Lessons learned from successful and failed experiences in ADC development resulted in remarkable progress in the discovery and development of novel highly potent small molecules. A better understanding of such small-molecule drugs is important for development of effective ADCs. The present review discusses requirements making a payload appropriate for antitumor ADCs and focuses on the main characteristics of commonly-used cytotoxic payloads that showed acceptable results in clinical trials. In addition, the present study represents emerging trends and recent advances of payloads used in ADCs currently under clinical trials.