Generation of organic stereoisomers with R/S, Z/E, and/or M/P configurations that may contain heteroatoms, multiple bonds, and any kind of cycle (isolated, spiro, condensed, and nested) is described. Inputs for processing are molecular structures in a N_tuple format resident on an automatic (canonical) or manual (non canonical) generated file which are processed by doing internal molecular graph construction, a weighted bipartite tree construction for all atoms and bonds to detect stereocenters, and symmetrical atom groups (SAG) with some specific SAG parameters that constitute a novel way for redundancy elimination of meso structures. Finally, determination of ligand CIP priorities allows for writing the output N_tuples with stereoisomer description. Several examples showing application of this methology to a wide number of structures are also presented.
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http://dx.doi.org/10.1021/ci6002762 | DOI Listing |
BMC Public Health
January 2025
Department of Health Management of Public Health, College of Public Health, Zhengzhou University, 100 Kexue Road, Gaoxin district, Zhengzhou, 450001, Henan, China.
Background: Lifestyle and cardiovascular mortality and all-cause mortality have been exhaustively explored by traditional methods, but the advantages of machine learning (ML) over traditional methods may lead to different or more precise conclusions. The aim of this study was to evaluate the effectiveness of machine learning-based lifestyle factors in predicting cardiovascular and all-cause mortality and compare the results obtained by traditional methods.
Method: A prospective cohort study was conducted using a nationally representative sample of adults aged 40 years or older, drawn from the US National Health and Nutrition Examination Survey from 2007 to 2010.
Images are important information carriers in our lives, and images should be secure when transmitted and stored. Image encryption algorithms based on chaos theory emerge in endlessly. Based on previous various chaotic image fast encryption algorithms, this paper proposes a color image sector fast encryption algorithm based on one-dimensional composite sinusoidal chaotic mapping.
View Article and Find Full Text PDFJ Immunother Cancer
January 2025
Department of Cancer and Functional Genomics, Institute of Genetics and Molecular and Cellular Biology (IGBMC), CNRS/INSERM/UNISTRA, Illkirch-Graffenstaden, France
Background: Endogenous retrovirus (ERV) elements are genomic footprints of ancestral retroviral infections within the human genome. While the dysregulation of ERV transcription has been linked to immune cell infiltration in various cancers, its relationship with immune checkpoint inhibitor (ICI) response in solid tumors, particularly metastatic clear-cell renal cell carcinoma (ccRCC), remains inadequately explored.
Methods: This study analyzed patients with metastatic ccRCC from two prospective clinical trials, encompassing 181 patients receiving nivolumab in the CheckMate trials (-009 to -010 and -025) and 48 patients treated with the ipilimumab-nivolumab combination in the BIONIKK trial.
The field of veterinary medicine, like many others, is expected to undergo a significant transformation due to artificial intelligence (AI), although the full extent remains unclear. Artificial intelligence is already becoming prominent throughout daily life (eg, recommending movies, completing text messages, predicting traffic), yet many people do not realize they interact with it regularly. Despite its prevalence, opinions on AI in veterinary medicine range from skepticism to optimism to indifference.
View Article and Find Full Text PDFInt J Gen Med
January 2025
Department of Pediatrics, College of Medicine, Arab Gulf University, Al Manama, Bahrain.
Introduction: With the incorporation of artificial intelligence (AI), significant advancements have occurred in the field of fetal medicine, holding the potential to transform prenatal care and diagnostics, promising to revolutionize prenatal care and diagnostics. This scoping review aims to explore the recent updates in the prospective application of AI in fetal medicine, evaluating its current uses, potential benefits, and limitations.
Methods: Compiling literature concerning the utilization of AI in fetal medicine does not appear to modify the subject or provide an exhaustive exploration of electronic databases.
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