Synthesis of thiazolyltriazole substituted azetidinones as antimicrobial agents

321-325The reaction of ethyl 2-amino-4-methylthiazole-5-carboxylate 1 with acetic anhydride followed by reaction with hydrazine hydrate yields the ethyl 2-acetamido-4-methylthiazole-5-carboxylate 2 and N-[5-(hydrazinecarbonyl)-4-methylthiazol-2-yl]acetamide 3, respectively. The compound 3 on further reaction with alcoholic potassium hydroxide-carbon disulphide followed by cyclization with hydrazine hydrate gives N-[5-(4-amino-5-mercapto-4H-1,2,4-triazol-3-yl)-4-methylthiazol-2-yl]acetamide 5. The compound 5 is then condensed with different aromatic aldehydes to offer Schiff bases 6a-h. The Schiff bases on cyclization with chloroacetyl chloride in presence of triethylamine as catalyst furnish the azetidin-2-one 7a-h. The compounds are synthesized in good yield and the chemical structures of the compounds are elucidated from their IR, 1H NMR, and elemental analysis. All the synthesized compounds have been screened for their antimicrobial activity

Synthesis and Antimicrobial Activity of SomeNovel Benzimidazolyl Chalcones

Some novel benzimidazolyl chalcones were synthesized by condensation of N-(4-(1H-benzo[d]imidazol-2-yl)phenyl)acetamide with aromatic aldehydes in presence of aqueous potassium hydroxide solution at room temperature. All the synthesized compounds were characterized on the basis of their IR, 1H NMR spectroscopic data and elemental analysis. All the compounds have been screened for antimicrobial activity by the cup-plate method

Computer extracted gland features from H&E predicts prostate cancer recurrence comparably to a genomic companion diagnostic test: a large multi-site study.

Existing tools for post-radical prostatectomy (RP) prostate cancer biochemical recurrence (BCR) prognosis rely on human pathologist-derived parameters such as tumor grade, with the resulting inter-reviewer variability. Genomic companion diagnostic tests such as Decipher tend to be tissue destructive, expensive, and not routinely available in most centers. We present a tissue non-destructive method for automated BCR prognosis, termed "Histotyping", that employs computational image analysis of morphologic patterns of prostate tissue from a single, routinely acquired hematoxylin and eosin slide. Patients from two institutions (n = 214) were used to train Histotyping for identifying high-risk patients based on six features of glandular morphology extracted from RP specimens. Histotyping was validated for post-RP BCR prognosis on a separate set of n = 675 patients from five institutions and compared against Decipher on n = 167 patients. Histotyping was prognostic of BCR in the validation set (p < 0.001, univariable hazard ratio [HR] = 2.83, 95% confidence interval [CI]: 2.03-3.93, concordance index [c-index] = 0.68, median years-to-BCR: 1.7). Histotyping was also prognostic in clinically stratified subsets, such as patients with Gleason grade group 3 (HR = 4.09) and negative surgical margins (HR = 3.26). Histotyping was prognostic independent of grade group, margin status, pathological stage, and preoperative prostate-specific antigen (PSA) (multivariable p < 0.001, HR = 2.09, 95% CI: 1.40-3.10, n = 648). The combination of Histotyping, grade group, and preoperative PSA outperformed Decipher (c-index = 0.75 vs. 0.70, n = 167). These results suggest that a prognostic classifier for prostate cancer based on digital images could serve as an alternative or complement to molecular-based companion diagnostic tests