Aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor and 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) is a potent ligand for AhR and a known carcinogen. While AhR activation by TCDD leads to significant immunosuppression, how this translates into carcinogenic signal is unclear. Recently, we demonstrated that activation of AhR by TCDD in naïve C57BL6 mice leads to massive induction of myeloid derived-suppressor cells (MDSCs). In the current study, we investigated the role of the gut microbiota in TCDD-mediated MDSC induction. TCDD caused significant alterations in the gut microbiome, such as increases in Prevotella and Lactobacillus, while decreasing Sutterella and Bacteroides. Fecal transplants from TCDD-treated donor mice into antibiotic-treated mice induced MDSCs and increased regulatory T-cells (Tregs). Injecting TCDD directly into antibiotic-treated mice also induced MDSCs, although to a lesser extent. These data suggested that TCDD-induced dysbiosis plays a critical role in MDSC induction. Interestingly, treatment with TCDD led to induction of MDSCs in the colon and undetectable levels of cysteine. MDSCs suppressed T cell proliferation while reconstitution with cysteine restored this response. Lastly, blocking CXC chemokine receptor 2 (CXCR2) impeded TCDD-mediated MDSC induction. Our data demonstrate that AhR activation by TCDD triggers dysbiosis which, in turn, regulates, at least in part, induction of MDSCs.
الوصف Mixed ligand complexes of Cu (II), Co (II) and Zn (II) with 2-((4-(1-(4-chlorophenylimino) ethyl) phenylimino) methyl) phenol (L) and histidine (His) have been prepared and diagnosed by ¹H and13 C NMR, FT-IR and electronic spectral data, thermal gravimetric, molar conductance and metal analysis measurements. The ligand (L) shows a bidentate nature and the coordination occurs through N and O atoms of imine group and phenol group respectively whereas (His) behave as tridentate ligand, coordinating through the-NH2 group and carboxylate oxygen group and N atoms of imidazole ring. The analytical studies for three complexes have shown octahedral structure. The anticancer activity was screened against human cancer cell such Follicular
... Show MoreThis study presents a detailed morphology and taxonomic study of Polysiphonia subtilissima collected from Abdul Rehman Goth, Karachi coast, Pakistan. Polysiphonia is a filamentous heterotrichous red algae, characterized by its branching structures and attachment mechanisms. P. subtilissima is notable for its broad salinity tolerance and wide distribution across marine and freshwater ecosystems. This research provides an in-depth examination of the internal and external structures of P. subtilissima, contributing to its systematic study and documenting its first recorded occurrence in Pakistani coastal areas, bordering the northern Arabian Sea. The findings enhance the understanding of the species taxonomy and its ecological role in
... Show MoreThis work involves synthesis and characterization of some new 1, 3, 4-thiadiazole or pyrazoline derivatives heterocyclic containing indole ring. The new 2-amino-1, 3, 4-thiadiazole derivatives [IV] and [V] a, b were synthesized by cyclization reaction of 2-methyl-1H-indole-carbothiosemicarbazide [III] in H2SO4 acid or by reaction of indole-3-acetic acid or indole-3-butanoic acid with thiosemicarbazide in the presence of phosphorous oxychloride, respectively. Amide derivatives [VI]-[VIII] were synthesized by the reaction equimolar of 2-amino-1, 3, 4-thiadiazoles and (acetyl chloride, benzoyl chloride, anisoyl chloride and heptanoyl chloride) in DMF and pyridine as accepter. The new pyrazolone derivatives [XI] a, b were synthesized from heati
... Show MoreSoftware-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
... Show More