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Background: More than 80% of patients with advanced cancer develop weight loss. Because preclinical data suggest poly (ADP-ribose) polymerase (PARP) inhibitors can treat this weight loss, this study was undertaken to explore the PARP inhibitor veliparib for this indication.
Objective: The current study was undertaken to analyze prospectively gathered data on weight in cancer patients on PARP inhibitors.
Design/setting: The current study relied on a previously published, prospectively conducted phase 1 single institution trial that combined veliparib and topotecan (NCT01012817) as antineoplastic therapy for advanced cancer patients. Serial weight data and, when available and clinically relevant, computerized tomography scans were also examined.
Measurements: The primary endpoint was 10% or greater weight gain from trial enrollment.
Results: Nearly all 60 patients lost weight over time. Only one patient manifested a 10% or greater gain in weight. However, review of computerized tomography L3 images showed this weight gain was a manifestation of ascites. Four other patients gained 5% of their baseline weight. However, findings in two patients with available radiographs showed no evidence of muscle augmentation.
Conclusions: The addition of the PARP inhibitor veliparib to chemotherapy does not appear to result in notable weight gain or in weight maintenance in patients with advanced cancer. Interventions other than PARP inhibitors should be considered for the palliation/treatment of cancer-associated weight loss.
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http://dx.doi.org/10.1089/jpm.2018.0023 | DOI Listing |
Eur J Radiol
September 2025
Department of Radiology, Affiliated Hospital of Hebei University, Baoding 071000, China. Electronic address:
Purpose: The present study aimed to develop a noninvasive predictive framework that integrates clinical data, conventional radiomics, habitat imaging, and deep learning for the preoperative stratification of MGMT gene promoter methylation in glioma.
Materials And Methods: This retrospective study included 410 patients from the University of California, San Francisco, USA, and 102 patients from our hospital. Seven models were constructed using preoperative contrast-enhanced T1-weighted MRI with gadobenate dimeglumine as the contrast agent.
J Trace Elem Med Biol
September 2025
Department of Neurology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, China. Electronic address:
Objective: We previously documented that exposure to a spectrum of elements is associated with autism spectrum disorder (ASD). However, there is a lack of mechanistic understanding as to how elemental mixtures contribute to the ASD development.
Materials And Methods: Serum and urinary concentrations of 26 elements and six biomarkers of ASD-relevant pathophysiologic pathways including serum HIPK 2, serum p53 protein, urine malondialdehyde (MDA), urine 8-OHdG, serum melatonin, and urine carnitine, were measured in 21 ASD cases and 21 age-matched healthy controls of children aged 6-12 years.
Neuro Endocrinol Lett
September 2025
Department of Pediatric Neurology, Cukurova University Faculty of Medicine, Adana, Turkey.
Objective: It is important to raise awareness of the nutritional problems that can be overlooked during the follow-up visits with children who suffer from neuromuscular diseases, as these dietary differences may lead to additional neurological and systemic problems and impair the quality of life of the patient. The aim of this study was to evaluate the nutritional status of children with neuromuscular disorders and to prevent possible complications by recognizing possible nutritional problems in advance.
Methods: Patients who applied to the outpatient clinic at Cukurova University, Faculty of Medicine, Department of Pediatric Neurology beginning in April 2022 with a neuromuscular disorder diagnosis were followed up with and were included in the study.
J Chem Inf Model
September 2025
Department of Chemistry, Delaware State University, Dover, Delaware 19901, United States.
The calculation of the highest occupied molecular orbital-lowest unoccupied molecular orbital (HOMO-LUMO) gap for chemical molecules is computationally intensive using quantum mechanics (QM) methods, while experimental determination is often costly and time-consuming. Machine Learning (ML) offers a cost-effective and rapid alternative, enabling efficient predictions of HOMO-LUMO gap values across large data sets without the need for extensive QM computations or experiments. ML models facilitate the screening of diverse molecules, providing valuable insights into complex chemical spaces and integrating seamlessly into high-throughput workflows to prioritize candidates for experimental validation.
View Article and Find Full Text PDFEur J Gastroenterol Hepatol
September 2025
Department of Gastroenterology, First Affiliated Hospital of Shantou University Medical College, Shantou.
Background: Crohn's disease (CD) and rheumatoid arthritis (RA) are autoimmune diseases. CD is known to be closely associated with RA. However, the mechanisms underlying these relationships remain unclear.
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