The knöevenagel condensation of 3-phenyl-4-thioxo-2-thiazolidinone (1) with 1-phenyl-3-aryl-1H-pyrazole-4-carbaldehydes 2a-d in refluxing glacial acetic acid or in polyethylene glycol-400 (PEG-400) at room temperature without catalyst, afforded the corresponding 5-hetarylmethylene derivatives 3a-d.[4+2] Cycloaddition reaction of compounds 3 with N-arylmaleimides, acrylonitrile and ethyl acrylate afforded thiopyrano[2,3-d]thiazole derivatives 5a-p. The anticancer activity of some of the newly synthesized compounds was investigated against different human cancer cell lines (MCF7 and HEPG2) and confirmed by molecular docking. Moreover, the structure for one representative example of the new products was confirmed by X-ray crystallography. The structure of all the newly synthesized compounds was established by elemental and spectral data.

Inflammatory breast cancer (IBC) is a rare yet aggressive breast cancer variant, associated with a poor prognosis. The major challenge for IBC is misdiagnosis due to the lack of molecular biomarkers. We profiled dysregulated expression of microRNAs (miRNAs) in primary samples of IBC and non-IBC tumors using human breast cancer miRNA PCR array. We discovered that 28 miRNAs were dysregulated (10 were upregulated, while 18 were underexpressed) in IBC vs. non-IBC tumors. We identified 128 hub genes, which are putative targets of the differentially expressed miRNAs and modulate important cancer biological processes. Furthermore, our qPCR analysis independently verified a significantly upregulated expression of miR-181b-5p, whereas a significant downregulation of miR-200b-3p, miR-200c-3p, and miR-203a-3p was detected in IBC tumors. Receiver operating characteristic (ROC) curves implied that the four miRNAs individually had a diagnostic accuracy in discriminating patients with IBC from non-IBC and that miR-203a-3p had the highest diagnostic value with an AUC of 0.821. Interestingly, a combination of miR-181b-5p, miR-200b-3p, and miR-200c-3p robustly improved the diagnostic accuracy, with an area under the curve (AUC) of 0.897. Intriguingly, qPCR revealed that the expression of zinc finger E box-binding homeobox 2 (ZEB2) mRNA, the putative target of miR-200b-3p, miR-200c-3p, and miR-203a-3p, was upregulated in IBC tumors. Overall, this study identified a set of miRNAs serving as potential biomarkers with diagnostic relevance for IBC.

Inflammatory breast cancer (IBC) is a rare, but aggressive entity of breast carcinoma with rapid dermal lymphatic invasion in young females. It is either poorly or misdiagnosed as mastitis because of the absence of a distinct lump. Small extracellular vesicles (sEVs) circulating in liquid biopsies are a novel class of minimally invasive diagnostic alternative to invasive tissue biopsies. They modulate cancer progression via shuttling their encapsulated cargo including microRNAs (miRNAs) into recipient cells to either trigger signaling or induce malignant transformation of targeted cells. Plasma sEVs < 200 nm were isolated using a modified cost-effective polyethylene glycol (PEG)-based precipitation method and compared to standard methods, namely ultracentrifugation and a commercial kit, where the successful isolation was verified by different approaches. We evaluated the expression levels of selected sEV-derived miR-181b-5p, miR-222-3p and let-7a-5p using quantitative real PCR (qPCR). Relative to non-IBC, our qPCR data showed that sEV-derived miR-181b-5p and miR-222-3p were significantly upregulated, whereas let-7a-5p was downregulated in IBC patients. Interestingly, receiver operating characteristic (ROC) curves analysis revealed that diagnostic accuracy of let-7a-5p alone was the highest for IBC with an area under curve (AUC) value of 0.9188, and when combined with miR-222-3p the AUC was improved to 0.973. Further, 38 hub genes were identified using bioinformatics analysis. Together, circulating sEV-derived miR-181b-5p, miR-222-3p and let-7a-5p serve as promising non-invasive diagnostic biomarkers for IBC.

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E&ptI~qxwtment of Chmiistr)l, 1%-10, llnirlersit?, of Wasbington, Seattle, Wasbington 981 95, USA ABSTRACT Seven comix)iiiids o f a new class o f ionopliores, acyclic nionoxadianiides, were synthesized and tested for the potentiometric selectivity for lithium ion, i n polyvinyl chloride ( WC) membrane electrodes. Four different plasticizers were studied: o-nitroplienyloctyl ether (NPOE), o-nitrophenylphenyl ether (NPI'E), o-nitroplienylbutyl ether (NPHE), and o-nitrophenylbenzyl ether (NI'HnE), as was the addition of trioctylphospliine oxide (TOPO). The ionophore 0-carboxyphenoxyacetic acid dimorpholide (Ig) exhilJited sodiuni-lithium selectivity, IV~',','~.~, o f 0.018 by the matched-potential method in the presence of 1% T01'0 using NI'HE plasticizer. The presence o f TOPO generally causes a substantial increase in the lithium selectivity, but it decreases the slopes o f the calibration curves. Selectivities are reported for sodium, potassium, ammonium, barium, and calcium ions with respect t o tlie lithium ion.

The action of hydrazine on 2‐mercapto and 2‐alkylmercaptoquinazolin‐4‐ones is reinvestigated. The structure of the isolated products have been revised.

PurposeEarly assessment of renal allograft function post‐transplantation is crucial to minimize and control allograft rejection. Biopsy — the gold standard — is used only as a last resort due to its invasiveness, high cost, adverse events (e.g., bleeding, infection, etc.), and the time for reporting. To overcome these limitations, a renal computer‐assisted diagnostic (Renal‐CAD) system was developed to assess kidney transplant function.MethodsThe developed Renal‐CAD system integrates data collected from two image‐based sources and two clinical‐based sources to assess renal transplant function. The imaging sources were the apparent diffusion coefficients (ADCs) extracted from 47 diffusion‐weighted magnetic resonance imaging (DW‐MRI) scans at 11 different b‐values (b0, b50, b100, ..., b1000 s/mm), and the transverse relaxation rate (R2*) extracted from 30 blood oxygen level‐dependent MRI (BOLD‐MRI) scans at 5 different echo times (TEs = 2, 7, 12, 17, and 22 ms). Serum creatinine (SCr) and creatinine clearance (CrCl) were the clinical sources for kidney function evaluation. The Renal‐CAD system initially performed kidney segmentation using the level‐set method, followed by estimation of the ADCs from DW‐MRIs and the R2* from BOLD‐MRIs. ADCs and R2* estimates from 30 subjects that have both types of scans were integrated with their associated SCr and CrCl. The integrated biomarkers were then used as our discriminatory features to train and test a deep learning‐based classifier, namely stacked autoencoders (SAEs) to differentiate non‐rejection (NR) from acute rejection (AR) renal transplants.ResultsUsing a leave‐one‐subject‐out cross‐validation approach along with SAEs, the Renal‐CAD system demonstrated 93.3% accuracy, 90.0% sensitivity, and 95.0% specificity in differentiating AR from NR. Robustness of the Renal‐CAD system was also confirmed by the area under the curve value of 0.92. Using a stratified tenfold cross‐validation approach, the Renal‐CAD system demonstrated its reproducibility and robustness by a diagnostic accuracy of 86.7%, sensitivity of 80.0%, specificity of 90.0%, and AUC of 0.88.ConclusionThe obtained results demonstrate the feasibility and efficacy of accurate, noninvasive identification of AR at an early stage using the Renal‐CAD system.