Investigation of the effects of different substrates on the promotion of the soil microbial consortium, encompassing bacteria and fungi, in the bioremediation of decabromodiphenyl ether (BDE-209).

Decabromodiphenyl ether (BDE-209) is recognized as an emerging and hazardous pollutant in numerous ecosystems. Despite this, only a few studies have concurrently investigated the biodegradation of BDE-209 by a microbial consortium comprising both bacteria and fungi. Consequently, the interactions between bacterial and fungal populations and their mutual effects on BDE-209 degradation remain unclear. Our main objective was to concurrently assess the changes and activity of bacterial and fungal communities during the biodegradation of BDE-209 in a real soil matrix. In the present study, various organic substrates were employed to promote soil biomass for the biodegradation of BDE-209. Soil respiration and molecular analysis were utilized to monitor biological activity and biomass community structure, respectively. The findings revealed that the use of wheat straw in the soil matrix resulted in the highest soil respiration and microbial activity among the treatments. This approach obviously provided suitable habitats for the soil microflora, which led to a significant increase in the biodegradability of BDE-209 (49%). Biomass survival efforts and the metabolic pathway of lignin degradation through co-metabolism contributed to the biodegradation of BDE-209. Microbial community analysis identified Proteobacteria (Alphaproteobacteria-Betaproteobacteria), Firmicutes, Bacteroides (bacterial phyla), as well as Ascomycota and Basidiomycota (fungal phyla) as the key microorganisms in the biological community involved in the biodegradation of BDE-209. This study demonstrated that applying wheat straw can improve both the biological activity and the biodegradation of BDE-209 in the soil of polluted sites.

Association of MGLL Intronic C>T Single Nucleotide Polymorphism (rs782440) with Borderline Personality Disorder: A Case-Control Study.

OBJECTIVE: From the perspective of etiology, borderline personality disorder (BPD) is a multifactorial and complex disorder, hence our understanding about the molecular basis and signaling of this disorder is extremely limited. The purpose of this study was evaluating the relationship between BPD and the Monoacylglycerol lipase (MGLL) polymorphism rs782440 in the population of Hamadan, Iran. MATERIALS AND METHODS: In this case-control study, 106 participants including 53 patients with BPD and 53 healthy control subjects were selected by psychiatrists in the Department of Psychiatry at Farshchian Sina Hospital in Hamadan. The BPD patients were selected based on the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) form for diagnosing BPD patients. For genotyping, polymerase chain reaction (PCR) was used to amplify the desired region including the (MGLL) intronic C>T single nucleotide polymorphism (SNP) (rs782440) and afterward the amplicon was sequenced using the Sanger sequencing method. To determine the genotype of these patients, their sequences were aligned with the reference sequence of MGLL through the CLC genomic workbench software. RESULTS: The results indicated that the frequency of TT in comparison to the CC genotype was significantly different (P=0.003) and the risk of BPD in change from the TT genotype to CC genotype was increased by 6.679%. Regarding the frequency of allele in this group, no significant difference was observed. CONCLUSION: This paper, has studied and reports for the first time, the association between MGLL SNP (rs782440) with BPD. The findings of the current research revealed that the TT genotype increases the risk of BPD compared to the CC genotype. Considering the lack of a suitable diagnostic biomarker for BPD, using this potential biomarker in the near future can be promising.

Using machine learning approach for screening metastatic biomarkers in colorectal cancer and predictive modeling with experimental validation.

Colorectal cancer (CRC) liver metastasis accounts for the majority of fatalities associated with CRC. Early detection of metastasis is crucial for improving patient outcomes but can be delayed due to a lack of symptoms. In this research, we aimed to investigate CRC metastasis-related biomarkers by employing a machine learning (ML) approach and experimental validation. The gene expression profile of CRC patients with liver metastasis was obtained using the GSE41568 dataset, and the differentially expressed genes between primary and metastatic samples were screened. Subsequently, we carried out feature selection to identify the most relevant DEGs using LASSO and Penalized-SVM methods. DEGs commonly selected by these methods were selected for further analysis. Finally, the experimental validation was done through qRT-PCR. 11 genes were commonly selected by LASSO and P-SVM algorithms, among which seven had prognostic value in colorectal cancer. It was found that the expression of the MMP3 gene decreases in stage IV of colorectal cancer compared to other stages (P value < 0.01). Also, the expression level of the WNT11 gene was observed to increase significantly in this stage (P value < 0.001). It was also found that the expression of WNT5a, TNFSF11, and MMP3 is significantly lower, and the expression level of WNT11 is significantly higher in liver metastasis samples compared to primary tumors. In summary, this study has identified a set of potential biomarkers for CRC metastasis using ML algorithms. The findings of this research may provide new insights into identifying biomarkers for CRC metastasis and may potentially lay the groundwork for innovative therapeutic strategies for treatment of this disease.

Lansoprazole as a potent HDAC2 inhibitor for treatment of colorectal cancer: An in-silico analysis and experimental validation.

BACKGROUND: Histone deacetylase 2 (HDAC2), belonging to the class I HDAC family, holds significant therapeutic potential as a crucial target for diverse cancer types. As key players in the realm of epigenetic regulatory enzymes, histone deacetylases (HDACs) are intricately involved in the onset and progression of cancer. Consequently, pursuing isoform-specific inhibitors targeting histone deacetylases (HDACs) has garnered substantial interest in both biological and medical circles. The objective of the present investigation was to employ a drug repurposing approach to discover novel and potent HDAC2 inhibitors. MATERIALS AND METHODS: In this study, our protocol is presented on virtual screening to identify novel potential HDAC2 inhibitors through 3D-QSAR, molecular docking, pharmacophore modeling, and molecular dynamics (MD) simulation. Afterward, In-vitro assays were employed to evaluate the cytotoxicity, apoptosis, and migration of HCT-116 cell lines under treatment of hit compound and valproic acid as a control inhibitor. The expression levels of HDAC2, TP53, BCL2, and BAX were evaluated by QRT-PCR. RESULTS: RMSD, RMSF, H-bond, and DSSP analysis results confirmed that among bioinformatically selected compounds, lansoprazole exhibited the highest HDAC2 inhibitory potential. Experimental validation revealed that lansoprazole displayed significant antiproliferative activity. The determined IC50 value was 400 ± 2.36 µM. Furthermore, the apoptotic cells ratio concentration-dependently increased under Lansoprazole treatment. Results of the Scratch assay indicated that lansoprazole led to decreasing the migration of CRC cells. Finally, under Lansoprazole treatment the expression level of BCL2 and HDAC2 decreased and BAX and TP53 increased. CONCLUSION: Taking together the results of the current study indicated that Lansoprazole as a novel HDAC2 inhibitor, could be used as a potential therapeutic agent for the treatment of CRC. Although, further experimental studies should be performed before using this compound in the clinic.

In vitro co-delivery of 5-fluorouracil and all-trans retinoic acid by PEGylated liposomes for colorectal cancer treatment.

BACKGROUND: Single-target inhibitors have not been successful in cancer treatment due to the development of drug resistance. Nevertheless, therapeutic agents capable of simultaneously inhibiting multiple targets have revealed encouraging results in inducing apoptosis and overcoming drug resistance in cancerous cells. Here, we designed a composite liposomal nano-carrier co-loading 5-Fluorouracil (5-FU) with all-trans retinoic acid (ATRA) to assess anticancer efficacy of the combined drugs in colorectal cancer (CRC). METHODS: A PEGylated liposomal nano-carrier with phospholipid/cholesterol/DSPE-PEG (2000) was synthesized by the thin film hydration technique for co-delivery of ATRA and 5-FU. After characterizing, the role of 5-FU and ATRA co-loaded liposomal nano-carrier in proliferation, epithelial-mesenchymal transition (EMT), apoptosis, and cancer stem cells (CSCs) were investigated by using colony forming and MTT assay, RT-qPCR and Annexin V/PI kit. RESULTS: The average size of liposomes (LPs) was < 150 nm with uniform size distribution. Drug release analyses indicated that both ATRA and 5-FU could simultaneously release from LPs in a sustained release manner. The synergistic inhibitory effects of ATRA and 5-FU loaded in LPs were verified with a combination index of 0.43. Dual drug LPs showed the highest cytotoxicity, enhanced inhibition of cell proliferation, increased apoptotic potential, decreased CSCs, and attenuated EMT-associated biomarkers. Also, dual drug LPs decreased ß-catenin gene expression more than other liposomal formulations. CONCLUSION: These findings suggest that using LPs to achieve a synergistic effect of ATRA and 5-FU is an effectual approach to increase the therapeutic effect of 5-FU toward CRC cells.

Expression patterns of T cells-specific long noncoding RNAs in systemic lupus erythematosus patients carrying HLA risk/nonrisk alleles.

BACKGROUND: Long noncoding RNAs (LncRNAs) play key roles in the regulation of gene expression and subsequently in the pathogenesis of several autoimmune diseases. This study aimed to explore the peripheral expression levels of T-cells-specific LncRNAs and transcription factors in systemic lupus erythematosus (SLE) patients carrying either human leukocyte antigens (HLA) risk or non-risk alleles. METHODS: Genotypes of HLA-DRB1 and HLA-DQB1 loci for 106 SLE patients were determined by PCR-SSP. In the next step, patients were stratified based on the presence of HLA-DRB1*03 and/or DRB1*16 allele groups (HLA risk alleles positive or HLA-RPos) or carrying other DRB1 allele groups (HLA-RNeg). Then, transcript levels of LncRNAs (IFNG-AS1, RMRP, Th2LCR, and DQ786243) and mRNAs for transcription factors (Foxp3, Gata3, and Tbx21) were measured using qRT-PCR and compared between two subgroups of patients. RESULTS: Totally, 47 cases were classified as HLA-RPos and 59 cases as HLA-RNeg patients. The HLA-RPos patients showed decreased transcript levels of DQ786243 (p = .001) and elevated expression of IFNG-AS1 (p = .06) and T-bet mRNA (p = .03) compared to the HLA-RNeg group. We observed significantly lower expression of Th2LCR (p < .0001) and DQ786243 (p = .001) and higher expression of Tbx21 (p = .009) and Foxp3 (p = .02) in DR3-positive versus DR3-negative patients. Likewise, decreased transcript levels of DQ786243 (p = .02) and RMRP (p = .003) were observed in DR16-positive versus DR16-negative patients. ROC curve analysis revealed the potential of DQ786243 and RMRP as biomarkers in SLE disease based on the carriage of HLA risk alleles. CONCLUSIONS: Our results indicate that the contribution of multiple T cell subsets in SLE disease progression as judged by expression analysis of LncRNAs and transcription factors can be inspired by the inheritance of HLA risk/nonrisk alleles is SLE patients.

Introducing novel key genes and transcription factors associated with rectal cancer response to chemoradiation through co-expression network analysis.

Preoperative radiochemotherapy is a promising therapeutic method for locally advanced rectal cancer patients. However, the response of colorectal cancer (CRC) patients to preoperative radiotherapy varies widely. In this study, we aimed to identify novel biomarkers that could predict the response of colorectal tumors to treatment using a systems biology approach. We applied the Weighted Gene Co-Expression Network Analysis to construct co-expression networks and evaluated the correlation of these networks with radiation using the module-trait relationship. We then identified hub genes and related transcription factors in the selected co-expression module. Our analysis of seven constructed modules revealed that one module, which contained 113 nodes and 6066 edges, had the strongest correlation with radiation effects on CRC (correlation = 0.85; p-value = 6e-7). By analyzing the selected module with the CytoHubba plugin, we identified four hub genes, including ZEB2, JAM2, NDN, and PPAP2A. We also identified seven important transcription factors, including KLF4, SUZ12, TCF4, NANOG, POU5F1, SOX2, and SMARCA4, which may play essential roles in regulating the four hub genes. In summary, our findings suggest that ZEB2, JAM2, NDN, and PPAP2A, along with the seven transcription factors related to these hub genes, may be associated with the response of colorectal tumors to chemoradiotherapy.

Psoriasis Associated Hub Genes Revealed by Weighted Gene Co-Expression Network Analysis.

OBJECTIVE: Psoriasis, an immune-mediated disorder, is a multifactorial disease with unidentified cause(s). This study aimed to discover possible biomarkers of this papulosquamous skin disease. MATERIALS AND METHODS: The gene chip GSE55201, resulted from an experimental study, including 44 Psoriasis patients and 30 healthy controls was downloaded from GEO and weighted gene co-expression network analysis was utilized to identify hub genes. Key modules were determined using the module eigenvalues. We used biological functions (BFs), cellular components, and molecular functions in the Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes enrichment analysis in the gene metabolic pathway were used for enrichment analysis. RESULTS: Adjacency matrix was built by using power adjacency function and the power to turn the correlation to adjacency matrix was four with a topology fit index of 0.92. Using the weighted gene co-expression network analysis, 11 modules were identified. The green-yellow module eigenvalues were significantly associated with Psoriasis (Pearson correlation=0.53, P<0.001). Candidate hub genes were determined by their higher connectivity and relationship with module eigenvalue. The genes including SIGLEC8, IL5RA, CCR3, RNASE2, CPA3, GATA2, c-KIT, and PRSS33 were recorded as the hub genes. CONCLUSION: We can conclude that SIGLEC8, IL5RA, CCR3, RNASE2, CPA3, GATA2, c-KIT, and PRSS33 have an important role in the immune response regulation and they could be considered as a potential diagnostic biomarker and therapeutic target for Psoriasis.

Highlighting functions of apoptosis and circular RNAs in colorectal cancer.

Colorectal cancer (CRC) is known as one of the global problems that endangers the lives of thousands of people every year. Various treatments have been used to deal with this disease, but in some cases, they are not effective. Circular RNAs, as a novel class of noncoding RNAs, have different expression levels and various functions in cancer cells, such as gene regulation through microRNA sponging. They play an important role in various cellular processes, including differentiation, proliferation, invasion, and apoptosis. Changes in the process of apoptosis are closely related to the progression or inhibition of various malignancies. Induction of apoptosis in cancer cells is a promising target for tumor therapy. In this study, circRNAs were investigated as being central to the induction or inhibition of apoptosis in CRC. It is hoped that through targeted changes in the function of these biomolecules, better outcomes will be achieved in cancer treatment. Perhaps better outcomes for cancer treatment can be achieved by using new methods and modifying the expression of these nucleic acids. However, using this method may come with challenges and limitations.

A Systems Biology Approach to Identify Novel Biomarkers in Progression from Crohn's Disease to Colorectal Cancer.

OBJECTIVE: This study aimed to find the key genes and miRNAs as potential biomarkers related to the progression of colorectal cancer (CRC) from Crohn's disease (CD). BACKGROUND: CD is widely accepted as one of the main risk factors leading to CRC. So, Identifying the novel molecular pathways involved in the development of CRC from CD can provide potential solutions for therapeutic interventions. METHODS: By implementing a systematic approach, we have analyzed mRNA and miRNA datasets containing CRC and CD samples to determine differentially expressed genes (DEGs) and miRNAs (DEmiRNA). Then by selecting common genes involved in the progression from CD to CRC, different downstream analyses including mRNA-miRNA network, functional enrichment analysis, gene set enrichment analysis, and survival analysis were performed. Finally, quantitative real-time PCR (RT-PCR) analysis of tissue samples obtained from Normal/CRC samples was used to confirm the differential expression of selected genes and miRNA. RESULTS: There were 10 DE miRNA and 181 genes DEGs common between progression from CD to CRC. The genes obtained for each of the 10 miRNAs were considered as the final target for downstream analyzes. In addition, analysis of RT-PCR indicated that miR-195-5p, PHLPP2, and LITAF   were downregulated in the cancer group compared to the control group. CONCLUSION: This study showed that PHLPP2, LITAF, and miR-195-5p may have key roles in the tumorigenesis of CRC and they can be used as therapeutic targets and diagnostic biomarkers after further in-vitro and in-vivo evaluation.

Identification of Prognostic Biomarkers for Breast Cancer Metastasis Using Penalized Additive Hazards Regression Model.

Background: Breast cancer (BC) has been reported as one of the most common cancers diagnosed in females throughout the world. Survival rate of BC patients is affected by metastasis. So, exploring its underlying mechanisms and identifying related biomarkers to monitor BC relapse/recurrence using new statistical methods is essential. This study investigated the high-dimensional gene-expression profiles of BC patients using penalized additive hazards regression models. Methods: A publicly available dataset related to the time to metastasis in BC patients (GSE2034) was used. There was information of 22 283 genes expression profiles related to 286 BC patients. Penalized additive hazards regression models with different penalties, including LASSO, SCAD, SICA, MCP and Elastic net were used to identify metastasis related genes. Results: Five regression models with penalties were applied in the additive hazards model and jointly found 9 genes including SNU13, CLINT1, MAPK9, ABCC5, NKX3-1, NCOR2, COL2A1, and ZNF219. According the median of the prognostic index calculated using the regression coefficients of the penalized additive hazards model, the patients were labeled as high/low risk groups. A significant difference was detected in the survival curves of the identified groups. The selected genes were examined using validation data and were significantly associated with the hazard of metastasis. Conclusion: This study showed that MAPK9, NKX3-1, NCOR1, ABCC5, and CD44 are the potential recurrence and metastatic predictors in breast cancer and can be taken into account as candidates for further research in tumorigenesis, invasion, metastasis, and epithelial-mesenchymal transition of breast cancer.

Identification of key genes in colorectal cancer diagnosis by co-expression analysis weighted gene co-expression network analysis.

BACKGROUND: The purpose of this study was using bioinformatics tools to identify biomarkers and molecular factors involved in the diagnosis of colorectal cancer, which are effective for the diagnosis and treatment of the disease. METHODS: We determined differentially expressed genes (DEGs) related to colorectal cancer (CRC) using the data series retrieved from GEO database. Then the weighted gene co-expression network analysis (WGCNA) was conducted to explore co-expression modules related to CRC diagnosis. Next, the relationship between the integrated modules with clinical features such as the stage of CRC was evaluated. Other downstream analyses were performed on selected module genes. RESULTS: In this study, after performing the WGCNA method, a module named blue module which was more significantly associated with the CRC stage was selected for further evaluation. Afterward, the Protein-protein interaction network through sting software for 154 genes of the blue module was constructed and eight hub genes were identified through the evaluation of constructed network with Cytoscape. Among these eight hub genes, upregulation of MMP9, SERPINH1, COL1A2, COL5A2, COL1A1, SPARC, and COL5A1 in CRC was validated in other microarray and TCGA data. Based on the results of the mRNA-miRNA interaction network, SERPINH1 was found as a target gene of miR-940. Finally, results of the DGIDB database indicated that Andecaliximab, Carboxylated glucosamine, Marimastat, Tozuleristide, S-3304, Incyclinide, Curcumin, Prinomastat, Demethylwedelolactone, and Bevacizumab, could be used as a therapeutic agent for targeting the MMP9. Furthermore, Ocriplasmin and Collagenase clostridium histolyticum could target COL1A1, COL1A2, COL5A1, and COL5A2. CONCLUSION: Taken together, the results of the current study indicated that seven hub genes including COL1A2, COL5A1, COL5A2, SERPINH1, MMP9, SPARC, and COL1A1 which were upregulated in CRC could be used as a diagnostic and progression biomarker of CRC. On the other hand, miR-940 which targets SERPINH1 could be used as a potential biomarker of CRC. More ever, Andecaliximab, Carboxylated glucosamine, Marimastat, Tozuleristide, S-3304, Incyclinide, Curcumin, Prinomastat, Demethylwedelolactone, Bevacizumab, Ocriplasmin , and Collagenase clostridium histolyticum were introduced as therapeutic agents for CRC which their therapeutic potential should be evaluated experimentally.

Identification of gene profiles related to the development of oral cancer using a deep learning technique.

BACKGROUND: Oral cancer (OC) is a debilitating disease that can affect the quality of life of these patients adversely. Oral premalignant lesion patients have a high risk of developing OC. Therefore, identifying robust survival subgroups among them may significantly improve patient therapy and care. This study aimed to identify prognostic biomarkers that predict the time-to-development of OC and survival stratification for patients using state-of-the-art machine learning and deep learning. METHODS: Gene expression profiles (29,096 probes) related to 86 patients from the GSE26549 dataset from the GEO repository were used. An autoencoder deep learning neural network model was used to extract features. We also used a univariate Cox regression model to select significant features obtained from the deep learning method (P < 0.05). High-risk and low-risk groups were then identified using a hierarchical clustering technique based on 100 encoded features (the number of units of the encoding layer, i.e., bottleneck of the network) from autoencoder and selected by Cox proportional hazards model and a supervised random forest (RF) classifier was used to identify gene profiles related to subtypes of OC from the original 29,096 probes. RESULTS: Among 100 encoded features extracted by autoencoder, seventy features were significantly related to time-to-OC-development, based on the univariate Cox model, which was used as the inputs for the clustering of patients. Two survival risk groups were identified (P value of log-rank test = 0.003) and were used as the labels for supervised classification. The overall accuracy of the RF classifier was 0.916 over the test set, yielded 21 top genes (FUT8-DDR2-ATM-CD247-ETS1-ZEB2-COL5A2-GMAP7-CDH1-COL11A2-COL3A1-AHR-COL2A1-CHORDC1-PTP4A3-COL1A2-CCR2-PDGFRB-COL1A1-FERMT2-PIK3CB) associated with time to developing OC, selected among the original 29,096 probes. CONCLUSIONS: Using deep learning, our study identified prominent transcriptional biomarkers in determining high-risk patients for developing oral cancer, which may be prognostic as significant targets for OC therapy. The identified genes may serve as potential targets for oral cancer chemoprevention. Additional validation of these biomarkers in experimental prospective and retrospective studies will launch them in OC clinics.

Novel biomarkers for neoplastic progression from ulcerative colitis to colorectal cancer: a systems biology approach.

In recent studies, the void of evaluation and in-depth understanding of unknown clinically relevant potential molecular biomarkers involved in colorectal cancer (CRC) from the inflammatory stage of ulcerative colitis (UC) to CRC metastasis, which can be suitable therapeutic targets, is deeply felt. The regulation and interaction among different cancer-promoting molecules, including messenger RNAs (mRNAs) and micro RNAs (miRNAs) in CRC and its progression, were the aim we pursued in this study. Using microarray data, we investigated the differential expression for five datasets, including mRNA and microRNA samples related to UC, tumor/normal. Then, using robust data analysis, separate lists of differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRNAs) were identified, which were used for robust rank aggregation (RRA) and co-expression network analysis. Then, comprehensive computational systems biology analyses, including gene ontology and Kyoto encyclopedia of genes and genomic pathway enrichment analyses, mRNA-miRNA regulatory network, and survival analysis, were employed to achieve the aim of this study. Finally, we used clinical samples to validate this potential and new target. According to this systems biology approach, a total of 98 DEGs and 8 DEmiRNAs with common differential expression were identified. By combining the distinct results of RRA and network, several potential therapeutic targets, and predictive and prognostic biomarkers for UC and CRC were identified. These targets include six common hub genes, CXCL1, CXCL8, MMP7, SLCA16A9, PLAU, and TIMP1, which are upregulated. Among these, the important and new biomarker SLC16A9 is negatively regulated by hsa-mir-194-5p, and hsa-miR-378a-5p take. The findings of the present study provide new insight into the pathogenesis of CRC in UC. Our study suggests future evaluation of the functional role of SLC16A9 and hsa-mir-194-5p and hsa-miR-378a-5p in CRC development.

Identification of Novel Biomarkers for Response to Preoperative Chemoradiation in Locally Advanced Rectal Cancer with Genetic Algorithm-Based Gene Selection.

BACKGROUND: The conventional treatment for patients with locally advanced colorectal tumors is preoperative chemo-radiotherapy (PCRT) preceding surgery. This treatment strategy has some long-term side effects, and some patients do not respond to it. Therefore, an evaluation of biomarkers that may help predict patients' response to PCRT is essential. METHODS: We took advantage of genetic algorithm to search the space of possible combinations of features to choose subsets of genes that would yield convenient performance in differentiating PCRT responders from non-responders using a logistic regression model as our classifier. RESULTS: We developed two gene signatures; first, to achieve the maximum prediction accuracy, the algorithm yielded 39 genes, and then, aiming to reduce the feature numbers as much as possible (while maintaining acceptable performance), a 5-gene signature was chosen. The performance of the two gene signatures was (accuracy = 0.97 and 0.81, sensitivity = 0.96 and 0.83, and specificity = 86 and 0.77) using a logistic regression classifier. Through analyzing bias and variance decomposition of the model error, we further investigated the involved genes by discovering and validating another 28-gene signature which possibly points towards two different sub-systems involved in the response of the patients to treatment. CONCLUSIONS: Using genetic algorithm as our gene selection method, we have identified two groups of genes that can differentiate PCRT responders from non-responders in patients of the studied dataset with considerable performance. IMPACT: After passing standard requirements, our gene signatures may be applicable as a robust and effective PCRT response prediction tool for colorectal cancer patients in clinical settings and may also help future studies aiming to further investigate involved pathways gain a clearer picture for the course of their research.

Comparison of Pulsed and Continuous Wave Diode Laser at 940 nm on the Viability and Migration of Gingival Fibroblasts.

Gingival fibroblasts have critical roles in oral wound healing. Photobiomodulation (PBM) has been shown to promote mucosal healing and is now recommended for managing oncotherapy-associated oral mucositis. This study examined the effects of the emission mode of a 940 nm diode laser on the viability and migration of human gingival fibroblasts. Cells were cultured in a routine growth media and treated with PBM (average power 0.1 W cm-2 , average fluence 3 J cm-2 , every 12 h for six sessions) in one continuous wave and two pulsing settings with 20% and 50% duty cycles. Cell viability was assessed using MTT, and digital imaging quantified cell migration. After 48 and 72 h, all treatment groups had significantly higher viability (n = 6, P < 0.05) compared with the control. The highest viability was seen in the pulsed (20% duty cycle) group at the 72-h time point. PBM improved fibroblast migration in all PBM-treated groups, but differences were not statistically significant (n = 2, P > 0.05). PBM treatments can promote cell viability in both continuous and pulsed modes. Further studies are needed to elucidate the optimal setting for PBM-evoked responses for its rationalized use in promoting specific phases of oral wound healing.

NIR irradiation of human buccal fat pad adipose stem cells and its effect on TRP ion channels.

The effect of near infrared (NIR) laser irradiation on proliferation and osteogenic differentiation of buccal fat pad-derived stem cells and the role of transient receptor potential (TRP) channels was investigated in the current research. After stem cell isolation, a 940 nm laser with 0.1 W, 3 J/cm2 was used in pulsed and continuous mode for irradiation in 3 sessions once every 48 h. The cells were cultured in the following groups: non-osteogenic differentiation medium/primary medium (PM) and osteogenic medium (OM) groups with laser-irradiated (L +), without irradiation (L -), laser treated + Capsazepine inhibitor (L + Cap), and laser treated + Skf96365 inhibitor (L + Skf). Alizarin Red staining and RT-PCR were used to assess osteogenic differentiation and evaluate RUNX2, Osterix, and ALP gene expression levels. The pulsed setting showed the best viability results (P < 0.05) and was used for osteogenic differentiation evaluations. The results of Alizarin red staining were not statistically different between the four groups. Osterix and ALP expression increased in the (L +) group. This upregulation abrogated in the presence of Capsazepine, TRPV1 inhibitor (L + Cap); however, no significant effect was observed with Skf96365 (L + Skf).

Deciphering the role of miR-71 and let-7 in the fertility of cystic echinococcosis cysts: a preliminary assessment.

Cystic echinococcosis (CE) is a neglected helminthic zoonosis in many parts of the world. Some CE cysts in the intermediate host are non-fertile. Considering the function of microRNAs in many biological processes such as embryonic development, cell proliferation, and apoptosis, this study investigated the function and comparison of miR-71 and let-7 in fertile and non-fertile CE cysts. Here, we determined the expression level of the miRNAs for 33 animal cysts and 16 human cysts (Echinococcus granulosus sensu stricto (G1). The quantitative real-time PCR method was conducted for the expression evaluation of miR-71 and let-7. The expression of both miRNAs in all samples was determined using the following formula: [ΔCT = CT (target) - CT (internal control)]. A comparison of Δct of miR-71 and let-7 in fertile and non-fertile cysts did not show a significant difference (P = 0.911 and 0.354). In cattle, sheep, and humans, Δct of miR-71, and let-7 were higher, respectively. Therefore, the mean expression of miR-71 and let-7 indicates an increase in humans compared to other intermediate hosts. Also, statistical results show a significant difference in the expression of these miRNAs in sheep, cattle, and human cysts (P = 0.025 and 0.01). The lower expression of these miRNAs in cattle cysts and their common infertility might be associated with the hypothesis and function of miRNAs in the fertility of CE cysts. So we should not ignore the function and role of miRNAs in this subject due to the importance of infertility in E. granulosus epidemiology.

Role of EFNA1 SNP (rs12904) in Tumorigenesis and Metastasis of Colorectal Cancer: A Bioinformatic Analysis and HRM SNP Genotyping Verification.

OBJECTIVE: Colorectal cancer is a prevalent disease with a poor prognosis and is known as a heterogeneous disease with many differences in clinical Symptoms and molecular profiles. The present study aimed to systematically evaluate the association of SNPs in miRNA binding sites of target genes that are involved in CRC angiogenesis, epithelial to mesenchymal transition, and cytoskeleton organization with tumorigenesis and metastasis of CRC. METHODS: A case-control study was performed on 146 samples of CRC patients and 132 healthy samples. After that, the DNA of all samples was isolated by the salting-out method. Finally, the genotypes for EFNA1 SNP (rs12904) were identified by HRM (High-resolution melting analysis) method. In order to evaluate the results of genotyping, two samples from each genotype were sequenced using the sanger sequencing method. RESULT: The frequency of AA genotype and the frequency of GG for rs12904 in satge4 and other stages are different from each other (P-value <0.0001) (P-value = 0.008). Also, the frequency of AA genotype in patients with different grades is different from each other (P-value = 0.035), while the frequency of AG   genotype and the frequency of GG   genotype is not significantly different in patients with different grades (P-value = 0.377) (P-value = 0.284). CONCLUSION: Results of this study indicated that patients carrying the GA and GG genotypes reduced the risk of disease progression compared to the AA genotype. As a result, this polymorphism plays a key role in CRC pathogenesis and metastasis and could be used as a biomarker in molecular diagnosis and metastatic state prediction in the near future after further study of its signaling pathways and molecular mechanism.

Identification of Novel Noninvasive Diagnostics Biomarkers in the Parkinson's Diseases and Improving the Disease Classification Using Support Vector Machine.

Background: Parkinson's disease (PD) is a neurological disorder that is marked by the deficit of neurons in the midbrain that changes motor and cognitive function. In the substantia nigra, the selective demise of dopamine-producing neurons was the main cause of this disease. The purpose of this research was to discover genes involved in PD development. Methods: In this study, the microarray dataset (GSE22491) provided by GEO was used for further analysis. The Limma package under R software was used to examine and assess gene expression and identify DEGs. The DAVID online tool was used to accomplish GO enrichment analysis and KEGG pathway for DEGs. Furthermore, the PPI network of these DEGs was depicted using the STRING database and analyzed through the Cytoscape to identify hub genes. Support vector machine (SVM) classifier was subsequently employed to predict the accuracy of genes. Result: PPI network consisted of 264 nodes as well as 502 edges was generated using the DEGs recognized from the Limma package under the R software. Moreover, three genes were identified as hubs: GNB5, GNG11, and ELANE. By using 3-gene combination, SVM found that prediction accuracy of 88% can be achieved. Conclusion: According to the findings of the study, the 3 hub genes GNB5, GNG11, and ELANE may be used as PD detection biomarkers. Moreover, the results obtained from SVM with high accuracy can be considered as PD biomarkers in further investigations.