[structure: see text] The configuration of the alpha-substituted alpha-hydroxy-beta-aminoester moiety in a series of 2'-substituted taxanes was analyzed according to the recently proposed Universal NMR Database (UDB) approach. A critical analysis of the results showed that modifications regarding chemical shift adjustment (so as to render the shifts virtually connectivity independent) were necessary to get consistent stereoassignments in this set of compounds. On this basis, a modified UDB-based strategy, especially tailored to the configurational assignment of densely substituted diastereomeric fragments, is proposed.
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http://dx.doi.org/10.1021/ol047600d | DOI Listing |
J Clin Med
January 2025
Medical Oncology Department, Hospital Universitario Miguel Servet, 50012 Zaragoza, Spain.
: Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy with a five-year survival rate of approximately 13% for advanced stages. While the majority of PDAC cases are sporadic, a significant subset is attributable to hereditary and familial predispositions, accounting for approximately 25% of cases. This article synthesizes recent advancements in the understanding, detection, and management of hereditary pancreatic cancer (PC).
View Article and Find Full Text PDFNPJ Vaccines
January 2025
Division of Molecular Microbiology, School of Life Sciences, Dundee, United Kingdom.
Group A Streptococcus (Strep A) is a human-exclusive bacterial pathogen killing annually more than 500,000 patients, and no current licensed vaccine exists. Strep A bacteria are highly diverse, but all produce an essential, abundant, and conserved surface carbohydrate, the Group A Carbohydrate, which contains a rhamnose polysaccharide (RhaPS) backbone. RhaPS is a validated universal vaccine candidate in a glycoconjugate prepared by chemical conjugation of the native carbohydrate to a carrier protein.
View Article and Find Full Text PDFQuant Imaging Med Surg
January 2025
Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China.
Background: Magnetic resonance (MR) diffusion-derived 'vessel density' (DDVD) is calculated according to: DDVD = Sb0/ROI - S/ROI, where S and S refer to the tissue signal when -value is 0 or 2 s/mm. S and ROI can also be approximated by other low -values diffusion-weighted imaging (DWI). This study investigates the influence of the second motion probing gradient -value and T2 on DDVD calculations of the liver, spleen, and liver simple cyst.
View Article and Find Full Text PDFPlast Reconstr Surg Glob Open
January 2025
From the Department of Surgical Sciences, School of Medicine and Surgery, Tor Vergata University of Rome, Rome, Italy.
Background: The deep inferior epigastric perforator (DIEP) flap is universally considered the gold standard technique for breast reconstruction (BR), though it cannot always be proposed to patients with insufficient donor-site volume. We explore the efficacy of autologous fat transfer (AFT) of the Holm abdomen zone IV in the retropectoral plane during DIEP flap reconstruction (lipo-DIEP flap), to enhance the volume provided by the abdominal donor site in patients with low body mass index (BMI).
Methods: We prospectively enrolled patients with BMI less than 25 kg/m and candidates for lipo-DIEP flap BR (group A) comparing them with a control group (group B) undergoing traditional DIEP flap BR with the same characteristics of the first group (BMI < 25 kg/m).
Insights Imaging
January 2025
Department of Radiology, the Second Affiliated Hospital of Dalian Medical University, Dalian, 116023, China.
Objective: To evaluate the feasibility of utilizing artificial intelligence (AI)-predicted biparametric MRI (bpMRI) image features for predicting the aggressiveness of prostate cancer (PCa).
Materials And Methods: A total of 878 PCa patients from 4 hospitals were retrospectively collected, all of whom had pathological results after radical prostatectomy (RP). A pre-trained AI algorithm was used to select suspected PCa lesions and extract lesion features for model development.
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