The purpose of this study was to examine the feasibility of applying a sample pooling method to the accelerated estimation of the uptake clearance of drugs to the brain in rats. Brain uptake clearances (CL(uptake)) were estimated for five model compounds using the sample pooling method and an integration plot analysis. CL(uptake) was also evaluated for caffeine and theophylline by brain microdialysis. The parameters and throughput of the pooling method were compared with those of typically used standard methods. The correlation for CL(uptake) was statistically significant (P<0.005) between the integration plot and the current method; the throughput of evaluation was 15-fold higher for the sample pooling method. A comparison of CL(uptake) values indicated that the three methods showed comparable results for caffeine while the CL(uptake) of theophylline using the proposed method was significantly different from those of the other methods. A kinetic analysis indicated that a compound with a slower CL(uptake) and longer half-life (e.g., theophylline) is more prone to error and that the lower limit of the CL(uptake) of 0.17 mL min(-1) (g brain)(-1) may be set so as to have an error less than 20% of the estimation. These results suggest that the sample pooling method is applicable for use in the accelerated estimation of the uptake clearance of compounds in the brain for which the value is greater than 0.17 mL min(-1) (g brain)(-1).
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http://dx.doi.org/10.1211/jpp.58.6.0014 | DOI Listing |
BMC Med Inform Decis Mak
January 2025
Department of Nursing, The Affiliated Hospital of Medical College Qingdao University, Qingdao, Shandong, 266003, China.
Background: This systematic review aims to explore the early predictive value of machine learning (ML) models for the progression of gestational diabetes mellitus (GDM) to type 2 diabetes mellitus (T2DM).
Methods: A comprehensive and systematic search was conducted in Pubmed, Cochrane, Embase, and Web of Science up to July 02, 2024. The quality of the studies included was assessed.
World J Surg Oncol
January 2025
Hunan University of Traditional Chinese Medicine, The Second Affiliated Hospital of Hunan University of Traditional Chinese Medicine, No. 233, Cai'e North Road, Kaifu District, Changsha, Hunan, 410005, China.
Background: In recent years, the association between systemic immune-inflammation index (SII) and the prognosis of patients with colorectal cancer (CRC) has remained a topic of considerable debate. To address this, the present study was carried out to investigate the prognostic significance of SII in CRC.
Methods: Databases including PubMed, Embase, the Cochrane Central Register of Controlled Trials (CENTRAL), and Web of Science were scrutinized up to March 27, 2024.
Nutr J
January 2025
Department of Neurology, Affiliated Hospital of Nanjing University of Chinese Medicine, 155 Hanzhong Road, Nanjing, 210029, China.
Background: 25-hydroxyvitamin D [25(OH)D] concentrations and physical activity (PA) are linked and both are associated with changes in mortality. We examined the association of 25(OH)D and PA with all-cause or cause-specific mortality risk in stroke survivors.
Methods: The analysis included 677 stroke survivors from National Health and Nutrition Examination Survey (NHANES) 2007-2008 to 2017-2018.
BMC Nurs
January 2025
Department of Medical Nursing, Teda Health Science College, Gondar, Ethiopia.
Background: The issue of workplace violence (WPV) directed at nurses is a chronic and global public health concern. Numerous studies on workplace violence in Ethiopia have been conducted; however, the results have been inconsistent. The review aims to identify the pooled prevalence and associated factors of workplace violence against nurses.
View Article and Find Full Text PDFBMC Cancer
January 2025
The Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China.
Background And Objectives: Accurate classification of lymphadenopathy is essential for determining the pathological nature of lymph nodes (LNs), which plays a crucial role in treatment selection. The biopsy method is invasive and carries the risk of sampling failure, while the utilization of non-invasive approaches such as ultrasound can minimize the probability of iatrogenic injury and infection. With the advancement of artificial intelligence (AI) and machine learning, the diagnostic efficiency of LNs is further enhanced.
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