The present study was conducted to determine the potential of five cyanobacteria strains isolated from aquatic zones to induce lipid production. The phylogenetic affiliation of the isolates was determined by 16S rRNA gene sequencing. Amongst the isolates, an efficient cyanobacterium, Synechococcus sp. HS01 showing maximal biomass and lipid productivity, was selected for further studies. In order to compare lipid productivity, the HS01 strain was grown in different media to screen potential significant culture ingredients and to evaluate mixotrophic cultivation. Mixotrophic cultivation of the strain using ostrich oil as a carbon source resulted in the best lipid productivity. GC analysis of fatty acid methyl esters of the selected cyanobacterial strain grown in media supplemented with ostrich oil showed a high content of C16 (palmitoleic acid and palmitic acid) and C18 (linoleic acid, oleic acid and linolenic acid) fatty acids of 42.7 and 42.8 %, respectively. Transmission electron micrographs showed that the HS01 cells exhibited an elongated rod-shaped appearance, either isolated, paired, linearly connected or in small clusters. According to initial experiments, ostrich oil, NaNO 3 and NaCl were recognized as potential essential nutrients and selected for optimization of media with the goal of maximizing lipid productivity. A culture optimization technique using the response surface method demonstrated a maximum lipid productivity of 56.5 mg l "1 day "1 . This value was 2.82-fold higher than that for the control, and was achieved in medium containing 1.12 g l "1 NaNO 3 , 1 % (v/v) ostrich oil and 0.09 % (w/v) NaCl.

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Background Multiple sclerosis (MS) is the most common autoimmune disease of the central nervous system (CNS). The main cause of the MS is yet to be revealed, but the most probable theory is based on the molecular mimicry that concludes some infections in the activation of T cells against brain auto-antigens that initiate the disease cascade. Objectives The Purpose of this research is the prediction of the auto-antigen potency of the myelin proteolipid protein (PLP) in multiple sclerosis. Materials and Methods As there wasn’t any tertiary structure of PLP available in the Protein Data Bank (PDB) and in order to characterize the structural properties of the protein, we modeled this protein using prediction servers. Meta prediction method, as a new perspective in silico, was performed to fi nd PLPs epitopes. For this purpose, several T cell epitope prediction web servers were used to predict PLPs epitopes against Human Leukocyte Antigens (HLA). The overlap regions, as were predicted by most web servers were selected as immunogenic epitopes and were subjected to the BLASTP against microorganisms. Results Three common regions, AA58-74, AA161-177, and AA238-254 were detected as immunodominant regions through meta-prediction. Investigating peptides with more than 50% similarity to that of candidate epitope AA58-74 in bacteria showed a similar peptide in bacteria (mainly consistent with that of clostridium and mycobacterium) and spike protein of Alphacoronavirus 1, Canine coronavirus, and Feline coronavirus. These results suggest that cross reaction of the immune system to PLP may have originated from a bacteria or viral infection, and therefore molecular mimicry might have an important role in the progression of MS. Conclusions Through reliable and accurate prediction of the consensus epitopes, it is not necessary to synthesize all PLP fragments and examine their immunogenicity experimentally (in vitro). In this study, the best encephalitogenic antigens were predicted based on bioinformatics tools that may provide reliable results for researches in a shorter time and at a lower cost.

Background: miRNAs are small non-coding RNAs; regulate gene expression using RNA degradation or translation repression. Dysregulation of miRNAs is involved in the initiation and progression of many cancers. We aimed to determine the relationship between miR-5571-5p expression and clinical factors and regulatory mechanisms in breast cancer. Methods: Histopathologic sections approximately with 25 microns thick from FFPE tissues were achievement of Al-Zahra Hospital (Isfahan, Iran) in 2020-2021 years by Pathologist. miR-5571-5p expression, determined using real-time PCR. For miRNA target genes prediction, integrated miRNA target prediction tools, were used. Gene ontology and KEGG pathway analysis were accomplished to identify the biological function. A PPI network was constructed to display key target genes. For hub genes validation, GEPIA databases were used. Results: miR-5571-5p was upregulated in breast tumor tissues, and its increase was significantly related to a poor prognosis in breast cancer (P<0.0001). At first, 324 target genes were predicted, and then 110 genes with a decrease in expression were selected. GO analysis showed that genes were mainly enriched in the regulation of the ERBB2 and EGFR signaling pathway. KEGG pathway analysis suggested that downregulated genes were enriched in glioma, the ErbB signaling pathway, and breast cancer. Finally, the ten hub genes (EGF, PIK3R1, SOS1, PTEN, SHC1, CBLB, LIFR, LEP, PDE1C, and NT5C2) were detected from the PPI network. Conclusion: miR-5571-5p up-regulation is associated with breast cancer progression and worse survival. The current study identified ten genes associated with breast cancer, which might help to provide candidate targets for the treatment.

BACKGROUND: Multiple lines of evidence suggest that single nucleotide polymorphisms (SNPs) in genes encoding components of the microRNA processing machinery may underlie susceptibility to various human diseases, including cancer. OBJECTIVE: The present study aimed to investigate whether rs6877842, rs642321 and rs10719 SNPs of DROSHA, a key component of the miRNA biogenesis pathway, are associated with increased risk of breast cancer. METHODS: A total of 100 patients diagnosed with breast cancer and 100 healthy women were included. Following extraction of DNA, genotyping was performed by tetra primer- amplification refractory mutation system-PCR (T-ARMS-PCR) technique. Under the co-dominant, dominant and recessive inheritance models, the association between DROSHA SNPs and breast cancer risk was determined by logistic regression analysis. The association of DROSHA SNPs with patients’ clinicopathological parameters was assessed. Also, haplotype analysis was performed to evaluate the combined effect of DROSHA SNPs on breast cancer risk. RESULTS: We observed a statistically significant association between DROSHA rs642321 polymorphism and breast cancer susceptibility (P < 0.05). Under the dominant inheritance model, DROSHA rs642321 polymorphism was significantly associated with increased risk of breast cancer (OR: 6.091; 95% CI: 3.291–11.26; P = 0.0001). Our findings demonstrated that DROSHA rs642321 T allele can contribute to the development of breast cancer (OR: 3.125; 95% CI: 1.984–4.923; P = 0.0001). We also found that GTC and GTT haplotypes conferred significant risk for breast cancer (OR: 2.367; 95% CI: 1.453–3.856; P = 0.0001 and OR: 7.944; 95% CI: 2.073–30.43; P = 0.0001, respectively). CONCLUSIONS: These results provide the first evidence that DROSHA rs642321 polymorphism is associated with increased risk of breast cancer. However, further studies are needed to firmly validate these findings.