RESUMO
Copper-Vit B3 MOF was successfully prepared by efficient and eco hydrothermal method. The prepared MOF was characterized as a tetragonal crystal copper-MOF nanoparticles by FTIR, SEM, TEM, EDX and XRD. The prepared nanoparticles were used as an effective, inexpensive and low-toxic catalyst in the one-pot synthesis of some new benzoxanthenone derivatives. As example 4-(9,9-dimethyl-11-oxo-8,10,11,12-tetrahydro-9H-benzo[a]xanthen-12-yl)phenyl benzoate (4h) was synthesized in high yield 92%. The MOF catalyst's role is activating the nucleophilic attack by increasing the carbonyl polarization, and this generally improves the reaction time, which ranges between 20-60 minutes and products' yields ranging between 80-92%. Prepared compounds (4a-4j) undergo molecular docking scanning as Helicobacter pylori type II dehydroquinase inhibitors, and the data obtained showed that there are three promises of the prepared compounds 4d, 4e, 4h and 4j compared with amoxicillin.
RESUMO
Artificial intelligence (AI) has extensive applications in a wide range of disciplines including healthcare and clinical practice. Advances in high-resolution whole-slide brightfield microscopy allow for the digitization of histologically stained tissue sections, producing gigapixel-scale whole-slide images (WSI). The significant improvement in computing and revolution of deep neural network (DNN)-based AI technologies over the last decade allow us to integrate massively parallelized computational power, cutting-edge AI algorithms, and big data storage, management, and processing. Applied to WSIs, AI has created opportunities for improved disease diagnostics and prognostics with the ultimate goal of enhancing precision medicine and resulting patient care. The National Institutes of Health (NIH) has recognized the importance of developing standardized principles for data management and discovery for the advancement of science and proposed the Findable, Accessible, Interoperable, Reusable, (FAIR) Data Principles1 with the goal of building a modernized biomedical data resource ecosystem to establish collaborative research communities. In line with this mission and to democratize AI-based image analysis in digital pathology, we propose ComPRePS: an end-to-end automated Computational Renal Pathology Suite which combines massive scalability, on-demand cloud computing, and an easy-to-use web-based user interface for data upload, storage, management, slide-level visualization, and domain expert interaction. Moreover, our platform is equipped with both in-house and collaborator developed sophisticated AI algorithms in the back-end server for image analysis to identify clinically relevant micro-anatomic functional tissue units (FTU) and to extract image features.
RESUMO
In this innovative research, we aim to reveal pyrazole-based Schiff bases as new multi-target agents. In this context, we re-synthesized three sets of pyrazole-based Schiff bases, 5a-f, 6a-f, and 7a-f, to evaluate their biological applications. The data from in vitro biological assays (including antioxidant and scavenging activities, anti-diabetes, anti-Alzheimer's, and anti-inflammatory properties) of the pyrazole-based Schiff bases 5a-f, 6a-f, and 7a-f showed that the six pyrazole-based Schiff bases 5a, 5d, 5e, 5f, 7a, and 7f possess the highest biological properties among the compounds evaluated. The cytotoxicity against lung (A549) and colon (Caco-2) human cancer types, as well as normal lung (WI-38) cell lines, was evaluated. The data from the cytotoxicity investigation demonstrated that the three Schiff bases 5d, 5e, and 7a are active against lung (A549) cells, while the two Schiff bases 5e and 7a exhibited the highest cytotoxicity towards colon (Caco-2) cells. Additionally, the enzymatic activities against caspase-3 and Bcl-2 of the six pyrazole-based Schiff bases 5a, 5d, 5e, 5f, 7a, and 7f were evaluated. Furthermore, we assessed the in silico absorption, distribution, metabolism, and toxicity (ADMT) properties of the more potent pyrazole-based Schiff bases. After modifying the structures of the six pyrazole-based Schiff bases, we plan to further extend the studies in the future.
RESUMO
Artificial intelligence (AI) has extensive applications in a wide range of disciplines including healthcare and clinical practice. Advances in high-resolution whole-slide brightfield microscopy allow for the digitization of histologically stained tissue sections, producing gigapixel-scale whole-slide images (WSI). The significant improvement in computing and revolution of deep neural network (DNN)-based AI technologies over the last decade allow us to integrate massively parallelized computational power, cutting-edge AI algorithms, and big data storage, management, and processing. Applied to WSIs, AI has created opportunities for improved disease diagnostics and prognostics with the ultimate goal of enhancing precision medicine and resulting patient care. The National Institutes of Health (NIH) has recognized the importance of developing standardized principles for data management and discovery for the advancement of science and proposed the Findable, Accessible, Interoperable, Reusable, (FAIR) Data Principles1 with the goal of building a modernized biomedical data resource ecosystem to establish collaborative research communities. In line with this mission and to democratize AI-based image analysis in digital pathology, we propose ComPRePS: an end-to-end automated Computational Renal Pathology Suite which combines massive scalability, on-demand cloud computing, and an easy-to-use web-based user interface for data upload, storage, management, slide-level visualization, and domain expert interaction. Moreover, our platform is equipped with both in-house and collaborator developed sophisticated AI algorithms in the back-end server for image analysis to identify clinically relevant micro-anatomic functional tissue units (FTU) and to extract image features.
RESUMO
There is a need for new pharmaceutical discoveries from bioactive nitrogenous derivatives due to the emergence of scourges, numerous pandemics, and diverse health problems. In this context, pyrazolo[1,5-a]pyrimidine derivatives 12a and 12b were synthesized and screened to evaluate their biological potentials in vitro as antioxidants, anti-diabetics, anti-Alzheimer's, anti-arthritics, and anti-cancer agents. Additionally, the computational pharmacokinetic and toxicity properties of the two pyrazolo[1,5-a]pyrimidines 12a and 12b were calculated and analyzed. The preliminary studies and results of this work represent the initial steps toward more advanced studies and define the bioactive chemical structure of pyrazolo[1,5-a]pyrimidine derivatives with the goal of exploring new drugs to address numerous health problems.
RESUMO
Based on previous developments of our research programs in trying to find new compounds with multiple biological targets such as antioxidant, anti-diabetic, anti-Alzheimer's, and anti-arthritic agents. In the context, a novel series of sulfonamide derivatives based on the pyrazole or pyridine moieties 3a, b, 7-9, 11-13, 15a, b, and 16 were synthesized from amine compounds with sulfonyl chloride derivatives. The structures of sulfonamide derivatives were elucidated via spectroscopy (1H and 13C NMR). The sulfonamide derivatives were biologically assessed in vitro for their anti-diabetic (α-amylase and α-glucosidase inhibition) and anti-Alzheimer's (acetylcholinesterase inhibition) activities. The biological results revealed that compound 15a is a powerful enzyme inhibitor for α-amylase and α-glucosidase. Also, compound 15b demonstrated inhibitor activity against the acetylcholinesterase enzyme. The structure-activity relationship study of sulfonamide derivatives was accomplished. Furthermore, complementary in silico molecular properties, drug-likeness, ADMET prediction, and surface properties of the two more powerful derivatives 15a and 15b were fulfilled and computed. These studies recommend 15a and 15b as candidates with modifications in their structures before the in vivo assays.
RESUMO
Increasing fertility rates have become one of the factors that concern all people in the world. Therefore, the study aims to use two mutated strains of probiotics enriched with selenium (PSe40/60/1 and BSe50/20/1) to improve fertility. Thirty Swiss albino male mice were divided into three groups; control, LP + S was given Lactobacillus plantarum PSe40/60/1 plus selenium, and BL + S was given Bifidobacterium longum BSe50/20/1 plus selenium. Free testosterone, LH, and FSH were measured in serum by biochemical analysis. Testicular tissues were examined by histopathological analysis. The count and motility of sperm, and sperm abnormalities were determined by microscopic examination. The method of qRT-PCR was used to detect gene expression of Tspyl1, Hsd3b6, and Star genes. The biochemical results showed that serum content of free testosterone (FT) hormone had significantly increase in the BL + S and LP + S groups compared with control. Levels of LH and FSH hormones were the highest in the BL + S group. The treated groups showed all developmental stages of spermatogenesis, including spermatogenesis, spermatocytes, and seminiferous tubule spermatids, as well as intact Sertoli cells and Leydig cells without changes. When compared to the control group, sperm count and motility increased in the BL + S group, while sperm abnormalities decreased. The expression of Tspyl1 gene in testicular tissues decreased in the LP + S and BL + S groups, while the expression of Star and Hsd3b6 genes was higher in the BL + S group and lower in the LP + S group compared with the control group. Therefore, Bifidobacterium longum BSe50/20/1 enriched with selenium could be useful in enhancing male fertility.