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更新于：2025-05-16
Allopurinol Sodium
别嘌醇钠
更新于：2025-05-16
概要
基本信息
结构/序列
分子式C5H4N4NaO |
InChIKeyAZJYSALMGIGGDH-UHFFFAOYSA-N |
CAS号17795-21-0 |
关联
3
项与 别嘌醇钠 相关的临床试验CTR20181698
注射用别嘌醇钠健康人体药代动力学研究
CTR20132332
注射用别嘌醇人体药代动力学试验
NCT00189007
Does Antenatal Allopurinol Administration Reduce Post-hypoxic-ischemic Reperfusion Damage During Fetal Hypoxia in the Newborn?
100 项与 别嘌醇钠 相关的临床结果
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100 项与 别嘌醇钠 相关的转化医学
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100 项与 别嘌醇钠 相关的专利（医药）
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5,556
项与 别嘌醇钠 相关的文献（医药）2025-06-01JOURNAL OF HAZARDOUS MATERIALS
Neurotoxic effects of per- and polyfluoroalkyl substances (PFAS) mixture exposure in mice: Accumulations in brain and associated changes of behaviors, metabolome, and transcriptome
Article
作者: Zeng, Ni ; Wang, Zhenglu ; He, Qiurong ; Yang, Qingkun ; He, Yuhang ; Wu, Lin
Humans are exposed to complex per- and polyfluoroalkyl substances (PFAS) mixtures, yet their neurotoxicity and mechanisms remains unclear. This study exposed male mice to 17 PFAS mixtures at low levels (0.2-20 µg/L) for 49 days via drinking water. Perfluoropentanoic acid (PFPeA), perfluoroheptanoic acid (PFHpA), 6:2 fluorotelomer sulfonic acid (6:2 FTS), and perfluorooctane Sulfonate (PFOS) accumulated in brain tissues, with brain/plasma ratios of 2.03-5.87, 2.94-12.88, 1.90-3.19, and 0.62-0.93, respectively. Electroencephalogram (EEG) results showed significant alterations, including a reduction in beta spectral edge (21.47-13.85 Hz) and an increase in gamma spectral edge (57.64-79.07 Hz). Histopathological analysis revealed necrosis in the hippocampus, contributing to the observed anxiety-like behaviors and memory impairments in exposed mice. Plasma metabolomics highlighted disrupted osmoprotectants, impaired glutamatergic synapse function, and tryptophan metabolism. Brain metabolomics demonstrated suppression of purine metabolism and activation of arachidonic acid metabolism, suggesting involvement in neurotoxic effects. Transcriptomic profiling further identified dysregulation in neuroactive ligand-receptor interactions, cholinergic and GABAergic synapses, and calcium signaling pathways, with oxytocin signaling highlighted as a critical mechanism. This study, for the first time, links PFAS mixture to neurotoxicity via neurotransmitter-related pathways, underscoring the need for public health policies and preventive strategies to mitigate PFAS exposure risks.
2025-05-04Expert Opinion On Drug Safety
Compartment syndrome associations with drugs: a pharmacovigilance study of the FDA adverse event reporting system (FAERS)
Article
作者: Yang, Xueting ; Shu, Yunfeng ; Tang, Juan ; Wan, Jie ; Kong, Wenqiang
BACKGROUND:
Compartment syndrome is an uncommon but life-threatening condition. No study has comprehensively compared compartment syndrome (CS) association with available drugs. The objective of this study was to estimate the association between CS and drugs using the FDA Adverse Event Report System (FAERS).
RESEARCH DESIGN AND METHODS:
FAERS reports from the first quarter of 2004 to the third quarter of 2023 were analyzed. The Medical Dictionary for Regulatory Activities (MedDRA) was used to identify CS cases. Reporting odds ratio (ROR), corresponding to 95% confidence intervals (95% CI) were calculated to detect a positive signal.
RESULTS:
A total of 2197 reports were considered in the study after the inclusion criteria were applied. Totally 100 drugs were found to be associated with CS. The median time for drug-associated CS was 45 days.
CONCLUSIONS:
By analyzing the FAERS database, the study revealed that certain drugs are significantly associated with compartment syndrome. Further studies are needed to verify whether these drugs are associated with such a risk.
2025-05-01DRUG SAFETY
Network Analysis and Machine Learning for Signal Detection and Prioritization Using Electronic Healthcare Records and Administrative Databases: A Proof of Concept in Drug-Induced Acute Myocardial Infarction
Article
作者: Ágg, Bence ; Ferdinandy, Péter ; Balogh, Olivér M ; Spina, Edoardo ; Sessa, Maurizio ; Battini, Vera ; Casula, Manuela ; Rossi, Andrea ; Barbieri, Maria Antonietta ; Abate, Andrea ; Carnovale, Carla ; Pétervári, Mátyás ; Cocco, Marianna
BACKGROUND:
Safety signals for potential drug-induced adverse events (AEs) typically emerge from multiple data sources, primarily spontaneous reporting systems, despite known limitations. Increasingly, real-world data from sources such as electronic health records (EHRs) and administrative databases are leveraged for signal detection. Although network analysis has shown promise in mapping relationships between clinical attributes for signal detection in spontaneous reporting system databases, its application in real-world data from EHRs and administrative databases remains limited.
OBJECTIVE:
This study aimed to evaluate the performance of network analysis in detecting safety signals within Italian administrative databases, using drug-induced acute myocardial infarction (AMI) as a proof of concept.
METHODS:
We employed a case-crossover design to explore the association between drug exposure and AMI using the Healthcare Administrative Database of Mantova, Italy, from 2014 to 2018. Patients with their first AMI hospitalization were identified after a 365-day washout period to exclude prior hospitalizations. We constructed a network to analyse the relationships between prescribed drugs and diagnoses, represented as nodes, with undirected edges illustrating their interactions. For each patient with AMI, we identified all diagnoses and drugs recorded or redeemed within 365 days of the first AMI episode and generated various drug-diagnosis, drug-drug, and diagnosis-diagnosis pairs. We calculated the frequency of these pairs, and three types of edge weights quantified the strength of connections. We identified outlier drug-AMI pairs using a predictive score (F) based on frequency (C) and full edge weights (WF), with validation for known AMI associations. We prioritized signals using the F score, C of AMI, and WF, analysed through k-means clustering to identify patterns in the data.
RESULTS:
From 2014 to 2018, a total of 3918 patients had an AMI, with 4686 AMI diagnoses. Of those, 2866 had prescriptions in the previous year, totalling 498,591 prescriptions. A network analysis identified 2968 unique nodes, revealing 529,935 diagnosis-diagnosis connections, 235,380 drug-diagnosis connections, and 102,831 drug-drug connections. The median number of connections (C) was 404 (Q1-Q3: 194-671) for drug nodes and 380 (Q1-Q3: 216-664) for diagnosis nodes. The median WF was 11.8 (Q1-Q3: 9-14), and the median F score across pairs was 0.1 (Q1-Q3: 0.1-0.3). A total of 249 potential safety signals were detected, with 63.4% aligning with known AEs. Among the remaining signals, 80 were prioritized, and five emerged as the highest priority: terazosin, tamsulosin, allopurinol, esomeprazole, and omeprazole.
CONCLUSIONS:
Overall, our novel method demonstrates that network analysis is a valuable tool for signal detection and prioritization in drug-induced AEs based on EHRs and administrative databases.
100 项与 别嘌醇钠 相关的药物交易
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研发状态
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| 适应症 | 国家/地区 | 公司 | 日期 |
|---|---|---|---|
| 痛风 | 美国 | 1996-05-17 | |
| 高尿酸血症 | 美国 | 1996-05-17 | |
| 白血病 | 美国 | 1996-05-17 | |
| 淋巴瘤 | 美国 | 1996-05-17 | |
| 实体瘤 | 美国 | 1996-05-17 |
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