Nutritional composition, health benefits and bio-active compounds of chickpea (Cicer arietinum L.).

Chickpea (Cicer arietinum L.), an annual plant of the family Fabaceae is mainly grown in semiarid and temperate regions. Among pulses, cultivated worldwide chickpeas are considered an inexpensive and rich source of protein. Chickpea is a good source of protein and carbohydrate, fiber, and important source of essential minerals and vitamins. The quality of protein is better among other pulses. Consumption of chickpeas is related to beneficial health outcomes. Dietary peptides from the protein of chickpeas gaining more attention. Peptides can be obtained through acid, alkali, and enzymatic hydrolysis. Among all these, enzymatic hydrolysis is considered safe. Various enzymes are used for the production of peptides, i.e., flavorzyme, chymotrypsin, pepsin, alcalase, papain, and trypsin either alone or in combinations. Chickpea hydrolysate and peptides have various bioactivity including angiotensin 1-converting enzyme inhibition, digestive diseases, hypocholesterolemic, CVD, antioxidant activity, type 2 diabetes, anti-inflammatory, antimicrobial, and anticarcinogenic activity. This review summarizes the nutritional composition and bioactivity of hydrolysate and peptides obtained from chickpea protein. The literature shows that chickpea peptides and hydrolysate have various functional activities. But due to the limited research and technology, the sequences of peptides are unknown, due to which it is difficult to conduct the mechanism studies that how these peptides interact. Therefore, emphasis must be given to the optimization of the production of chickpea bioactive peptides, in vivo studies of chickpea bioactivity, and conducting human study trials to check the bioactivity of these peptides and hydrolysate.

Phenylboronic acid-conjugated chitosan nanoparticles for high loading and efficient delivery of curcumin.

In order to achieve high loading and efficient delivery of curcumin, phenylboronic acid-conjugated chitosan nanoparticles were prepared by a simple desolvation method. These nanoparticles exhibited a regular spherical shape with the average size about 200-230 nm and narrow size distribution, which were kinetically stable under physiological condition. Due to boronate ester formation between curcumin and phenylboronic acid groups in the nanoparticles, and the hydrogen bonding interactions between curcumin and nanocarriers, curcumin was successfully loaded into the nanoparticles with high drug loading content. These curcumin-loaded nanoparticles showed pH and reactive oxygen species (ROS)-triggered drug release behavior. In vitro cell experiments revealed that the blank nanoparticles were completely nontoxic to cultured cells, and the curcumin-loaded nanoparticles exhibited efficient antitumor efficiency against cancer cells. Moreover, the drug-loaded nanoparticles performed an enhanced growth inhibition in three-dimensional multicellular tumor spheroids. Thus, these nanocarriers would be a promising candidate for curcumin delivery in tumor treatment.

Functional genomics study of protein inhibitor of activated STAT1 in mouse hippocampal neuronal cells revealed by RNA sequencing.

Protein inhibitor of activated STAT1 (PIAS1), a small ubiquitin-like modifier (SUMO) E3 ligase, was considered to be an inhibitor of STAT1 by inhibiting the DNA-binding activity of STAT1 and blocking STAT1-mediated gene transcription in response to cytokine stimulation. PIAS1 has been determined to be involved in modulating several biological processes such as cell proliferation, DNA damage responses, and inflammatory responses, both in vivo and in vitro. However, the role played by PIAS1 in regulating neurodegenerative diseases, including Alzheimer's disease (AD), has not been determined. In our study, significantly different expression levels of PIAS1 between normal controls and AD patients were detected in four regions of the human brain. Based on a functional analysis of Pias1 in undifferentiated mouse hippocampal neuronal HT-22 cells, we observed that the expression levels of several AD marker genes could be inhibited by Pias1 overexpression. Moreover, the proliferation ability of HT-22 cells could be promoted by the overexpression of Pias1. Furthermore, we performed RNA sequencing (RNA-seq) to evaluate and quantify the gene expression profiles in response to Pias1 overexpression in HT-22 cells. As a result, 285 significantly dysregulated genes, including 79 upregulated genes and 206 downregulated genes, were identified by the comparison of Pias1/+ cells with WT cells. Among these genes, five overlapping genes, including early growth response 1 (Egr1), early growth response 2 (Egr2), early growth response 3 (Egr3), FBJ osteosarcoma oncogene (Fos) and fos-like antigen 1 (Fosl1), were identified by comparison of the transcription factor binding site (TFBS) prediction results for STAT1, whose expression was evaluated by qPCR. Three cell cycle inhibitors, p53, p18 and p21, were significantly downregulated with the overexpression of Pias1. Analysis of functional enrichment and expression levels showed that basic region leucine zipper domain-containing transcription factors including zinc finger C2H2 (zf-C2H2), homeobox and basic/helix-loop-helix (bHLH) in several signaling pathways were significantly involved in PIAS1 regulation in HT-22 cells. A reconstructed regulatory network under PIAS1 overexpression demonstrated that there were 43 related proteins, notably Nr3c2, that directly interacted with PIAS1.

Identification of hub ubiquitin ligase genes affecting Alzheimer's disease by analyzing transcriptome data from multiple brain regions.

The ubiquitin-proteasome system (UPS) plays crucial roles in numerous cellular functions. Dysfunction of the UPS shows certain correlations with the pathological changes in Alzheimer's disease (AD). This study aimed to explore the different impairments of the UPS in multiple brain regions and identify hub ubiquitin ligase (E3) genes in AD. The brain transcriptome, blood transcriptome and proteome data of AD were downloaded from a public database. The UPS genes were collected from the Ubiquitin and Ubiquitin-like Conjugation Database. The hub E3 genes were defined as the differentially expressed E3 genes shared by more than three brain regions. E3Miner and UbiBrowser were used to predict the substrate of hub E3. This study shows varied impairment of the UPS in different brain regions in AD. Furthermore, we identify seven hub E3 genes (CUL1, CUL3, EIF3I, NSMCE1, PAFAH1B1, RNF175, and UCHL1) that are downregulated in more than three brain regions. Three of these genes (CUL1, EIF3I, and NSMCE1) showed consistent low expression in blood. Most of these genes have been reported to promote AD, whereas the impact of RNF175 on AD is not yet reported. Further analysis revealed a potential regulatory mechanism by which hub E3 and its substrate genes may affect transcription functions and then exacerbate AD. This study identified seven hub E3 genes and their substrate genes affect transcription functions and then exacerbate AD. These findings may be helpful for the development of diagnostic biomarkers and therapeutic targets for AD.

Transcriptome integration analysis and specific diagnosis model construction for Hodgkin's lymphoma, diffuse large B-cell lymphoma, and mantle cell lymphoma.

Transcriptome differences between Hodgkin's lymphoma (HL), diffuse large B-cell lymphoma (DLBCL), and mantle cell lymphoma (MCL), which are all derived from B cell, remained unclear. This study aimed to construct lymphoma-specific diagnostic models by screening lymphoma marker genes. Transcriptome data of HL, DLBCL, and MCL were obtained from public databases. Lymphoma marker genes were screened by comparing cases and controls as well as the intergroup differences among lymphomas. A total of 9 HL marker genes, 7 DLBCL marker genes, and 4 MCL marker genes were screened in this study. Most HL marker genes were upregulated, whereas DLBCL and MCL marker genes were downregulated compared to controls. The optimal HL-specific diagnostic model contains one marker gene (MYH2) with an AUC of 0.901. The optimal DLBCL-specific diagnostic model contains 7 marker genes (LIPF, CCDC144B, PRO2964, PHF1, SFTPA2, NTS, and HP) with an AUC of 0.951. The optimal MCL-specific diagnostic model contains 3 marker genes (IGLV3-19, IGKV4-1, and PRB3) with an AUC of 0.843. The present study reveals the transcriptome data-based differences between HL, DLBCL, and MCL, when combined with other clinical markers, may help the clinical diagnosis and prognosis.

ß-catenin regulates myocardial ischemia/reperfusion injury following heterotopic heart transplantation in mice by modulating PTEN pathways.

Ischemia reperfusion (I/R) injury, an inevitable event accompanying heart transplantation, is the primary factor leading to organ failure and graft rejection. In order to prevent I/R injury, we established murine heart transplantation model with I/R and cell culture system to determine whether ß-catenin is a mediate factor in preventing I/R injury in heart transplantation. After successfully established heterotopic heart transplantation mice model, the I/R injury was induced, and two dynamic temporal were studied during different I/R phases. With the increase of ischemia and reperfusion time, heart damage was more severe. In the initial study, we observed that ß-catenin was significantly decreased, while ROCK1 and PTEN increased during the perfusion phase from day 0 to day 1, and remain the same level until 3 days later. The similar pattern that ß-catenin was down-regulated while ROCK1 and PTEN were up-regulated was also observed in the dynamic temporal ischemia study. To further investigate the role of ß-catenin signaling in I/R injury in vitro, ß-catenin over-expressing plasmid was transfected into HL-1 cells, a cardiac cell line. We noted that ß-catenin over-expressing cardiomyocytes showed decreased ROCK1/PTEN expression both at mRNA and protein levels. In addition, cobalt dichloride (CoCl2) -induced oxidative stress model was further established to mimic cardiac I/R injury. We observed that CoCl2-induced activation of ROCK1/PTEN signaling pathway were attenuated by transient transfection of a ß-catenin over-expressing plasmid. Taken together, our results suggest that cardiac transplant induced IR injury is closely associated with the down-regulation of ß-catenin and up-regulation of ROCK1 and PTEN expression.

Combination of cetuximab with met inhibitor in control of cetuximab-resistant oral squamous cell carcinoma.

Objective: To investigate the underlying molecular mechanisms contributing to oral squamous cell carcinoma (OSCC) cell resistance to the epidermal growth factor receptor (EGFR) inhibitor. Materials and methods: OSCC cell lines HSC-2 and HSC-3 were assessed in vitro for drug treatment, cell viability, and gene expression and the online gene expression in OSCC tissues was analyzed for association with OSCC prognosis. Results: HSC-2 and HSC-3 cells expressed high EGFR levels, but hepatocyte growth factor (HGF) treatment induced cetuximab resistance, whereas the Met inhibitor PHA-665752 as well as Met siRNA was able to restore OSCC cell sensitivity to cetuximab. HGF treatment induced tumor cells to express p-Akt and p-ERK1/2. In contrast, the activity of Akt and ERK1/2 was suppressed by treatment with PHA-665752, Met siRNA, or their combination. Furthermore, Met was highly expressed in OSCC tissues and associated with a poor patient survival, while Met/HGF-activated Akt also was associated with a poor patient survival. Conclusions: This study demonstrates that Met/HGF expression results in OSCC resistance to cetuximab and tumor recurrence after cetuximab therapy; thus, inhibition of Met/HGF activity could restore OSCC sensitivity to cetuximab.

Integrated analysis of 10 lymphoma datasets identifies E2F8 as a key regulator in Burkitt's lymphoma and mantle cell lymphoma.

Burkitt's lymphoma (BURK), diffuse large B-cell lymphoma (DLBCL) and mantle cell lymphoma (MCL) are three main types of B-cell lymphomas. This study aimed to compare the differences of affected biological functions and pathways, as well as to explore the possible regulatory mechanisms and the potential therapeutic targets in BURK, DLBCL and MCL. We performed an integrated analysis of 10 lymphoma datasets including 352 BURK patients, 880 DLBCL patients, 216 MCL patients, and 33 controls. Our results showed that signaling pathways, amino acid metabolism and several lipid metabolism pathways varies considerably among these three types of lymphoma. Furthermore, we identified several key transcription factors (TFs) and their target genes that may promote these diseases by influencing multiple carcinogenic pathways. Among these TFs, we reported first that E2F8 displayed the most significant effects in BURK and MCL. Our results demonstrate that over-expression of E2F8 activates target genes that may promote cell cycle, mitosis, immune and other cancer related functions in BURK and MCL. Therefore, we suggest that E2F8 could be used as a biomarker and potential therapeutic target for BURK and MCL. These findings would be helpful in the study of pathogenesis, and drug discovery and also in the prognosis of B cell lymphomas.