Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0036572 (seizures)
 80,221 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Optimization of the sampling schedule can be used in pharmacokinetic (PK) experiments to increase the accuracy and the precision of parameter estimation or to reduce the number of samples required. Several optimization criteria that formally incorporate prior parameter uncertainty have been proposed earlier. These criteria consist in finding the sampling schedule that maximizes the expectation (over a given parameter distribution) of det F (ED-optimality) or Log(det F) (API-optimality), or minimizes the expectation of 1/det F (EID-optimality), where F is the Fisher information matrix. The precision and the accuracy of parameter estimation after having fitted a PK model to a small number of optimal data points (determined according to D, ED, EID, and API criteria) or to a naive sampling schedule were compared in a Monte Carlo simulation study. A one-compartment model with first-order absorption rate (3 parameters) and a two-compartment model with zero-order infusion rate (4 parameters) were considered. Data were simulated for 300 subjects with both structural models, combined with several residual error models (homoscedastic, heteroscedastic with constant or variable coefficient of variation). Interindividual variabilities in PK parameters ranged from 25-66%. ED-, EID-, and API-optimal sampling times were calculated using the software OSP-Fit. Three or five samples were allowed for parameter estimation by extended least-squares. Performances of each design criterion were evaluated in terms of mean prediction error, root mean squared error, and number of acceptable estimates (i.e., with a SE less than 30%). Compared to the D-optimal design, the EID and API designs reduced the bias and the imprecision of the estimation of the parameters having a large interindividual variability. Moreover, the API design resulted in some cases in a higher number of acceptable estimates.
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PMID:Comparison of ED, EID, and API criteria for the robust optimization of sampling times in pharmacokinetics. 956 92

Understanding the reaction mechanism of co-catalytic metallopeptidases provides a starting point for the design and synthesis of new molecules that can be screened as potential pharmaceuticals. Many of the enzymes that contain co-catalytic metallo-active sites play important roles in cellular processes such as tissue repair, protein maturation, hormone level regulation, cell-cycle control and protein degradation. Therefore, these enzymes play central roles in several disease states including cancer, HIV, stroke, diabetes, bacterial infections, neurological processes, schizophrenia, seizure disorders, and amyotrophic lateral sclerosis. The mechanism of AAP, an aminopeptidase from Aeromonas proteolytica, is one of the best-characterized examples of a metallopeptidase containing a co-catalytic metallo-active site, although this enzyme is not a specific pharmaceutical target at this time. As a large majority of co-catalytic metallopeptidases contain active sites that are nearly identical to the one observed in AAP, the major steps of their catalytic mechanisms are likely to be very similar. With this in mind, it is possible to propose a general catalytic mechanism for the hydrolysis of amino acid substrates.
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PMID:Co-catalytic metallopeptidases as pharmaceutical targets. 1271 52

Lead poisoning affects an estimated 890,000 young children in the United States annually (American Academy of Pediatrics [AAP], 1998). Extremely high levels in the child can cause mental retardation, coma, seizures, and death. Chronic low level exposure is more commonly seen with multiple effects, including learning disabilities, impaired growth, and hearing loss. Lead poisoning prevention efforts have significantly reduced the number of children affected by this serious health hazard. Health care providers need to continue their vigilant efforts to educate families living in older homes about the risks, screening, and treatment.
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PMID:Lead poisoning: a summary of treatment and prevention. 1296 48

Counterfeit (or falsified) and substandard medicines pose a major public health risk. We describe the findings of Operation Storm I and II conducted in 2008-2009 to combat counterfeit medicines through partnership between national customs, Drug Regulatory Agencies (DRAs), and police in Cambodia, Indonesia, Laos, Myanmar, Singapore, Thailand, and Vietnam. Samples were obtained from seizures and market surveillance by national DRAs. Laboratory analysis using spectroscopic and chromatographic techniques and examination of packaging were performed. Ninety-three suspect antibiotics and 95 antimalarial samples were collected. Of the 93 antibiotics, 29 (31%) had % active pharmaceutical ingredient content (%API) < 85% or > 115% (including one counterfeit). Of the 95 antimalarials, 30 (32%) had %API < 85 > 115% API (including one counterfeit). A significant minority of samples, antimalarials (13%) and antibiotics (15%), were collected in plastic bags with minimal or no labeling. Of 20 ampicillin samples, 13 (65%) contained < 85% API (with one counterfeit containing additional amoxicillin). Of 34 oral artesunate samples, 7 (21%) contained %API out of the 85-115% range. Coordinated and synergistic partnership adopted by the participating countries, International Criminal Police Organization (INTERPOL), World Health Organization (WHO), and laboratories facilitated a platform for discussions and intelligence sharing, helping to improve each participating country's capacity to combat poor-quality medicines.
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PMID:Collaborative health and enforcement operations on the quality of antimalarials and antibiotics in southeast Asia. 2644 19

In this paper we present a new, versatile workflow for a synthesis impurity profiling concept, using the combination of flash chromatography (F-LC), liquid chromatography coupled to mass spectrometry (LC-MS), and multivariate data analysis. For three highly pure, structurally different synthetic cannabinoids, we demonstrate that via F-LC more than 99% of the main component (API) can be removed from a sample to enrich present impurities and yield combined fractions of targeted synthesis impurities with reproducible chromatographic signatures via LC-MS. The maximum overall relative standard deviation (RSD) of the complete experimental procedure for isolation and measurement of the impurity profiles (FL-C + LC-MS) was found to be 13.8% on average. The impurity signatures of 40 1 kg samples of MDMB-CHMICA (methyl ( S)-2-(1-(cyclohexylmethyl)-1 H-indole-3-carboxamido)-3,3-dimethylbutanoate) from one large seizure by Luxembourg customs were assessed via UHPLC-MS and compared via principle component analysis (PCA) to possibly discriminate between individual synthesis pathways or production batches and to deduce batch sizes. Three of these 40 samples could be identified as outliers, i. a., as a result of a highly abundant impurity with m/ z 498, isolated via F-LC and identified as methyl 2-(2-(1-(cyclohexylmethyl)-1 H-indole-3-carboxamido)-3,3-dimethylbutanamido)-3,3-dimethylbutanoate, most probably manufactured with a varying synthesis pathway. The remaining 37 samples were subdivided via PCA and hierarchical cluster analysis into five clusters between five and ten samples, representing a maximum possible batch size of 10 kg of pure MDMB-CHMICA. Furthermore, the profiling concept was successfully applied to self-produced and seized "spice-products" to extract impurity profiles of MDMB-CHMICA without any ion suppression or chemical interference.
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PMID:A Novel Impurity-Profiling Workflow with the Combination of Flash-Chromatography, UHPLC-MS, and Multivariate Data Analysis for Highly Pure Drugs: A Study on the Synthetic Cannabinoid MDMB-CHMICA. 3007 31

The trend of using wearables for healthcare is steeply increasing nowadays, and, consequently, in the market, there are several gadgets that measure several body features. In addition, the mixed use between smartphones and wearables has motivated research like the current one. The main goal of this work is to reduce the amount of times that a certain smartband (SB) measures the heart rate (HR) in order to save energy in communications without significantly reducing the utility of the application. This work has used an SB Sony 2 for measuring heart rate, Fit API for storing data and Android for managing data. The current approach has been assessed with data from HR sensors collected for more than three months. Once all HR measures were collected, then the current approach detected hourly ranges whose heart rate were higher than normal. The hourly ranges allowed for estimating the time periods of weeks that the user could be at potential risk for measuring frequently in these (60 times per hour) ranges. Out of these ranges, the measurement frequency was lower (six times per hour). If SB measures an unusual heart rate, the app warns the user so they are aware of the risk and can act accordingly. We analyzed two cases and we conclude that energy consumption was reduced in 83.57% in communications when using training of several weeks. In addition, a prediction per day was made using data of 20 users. On average, tests obtained 63.04% of accuracy in this experimentation using the training over the data of one day for each user.
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PMID:Green Communication for Tracking Heart Rate with Smartbands. 3010 99

It is well-established that both volume conduction and the choice of recording reference (montage) affect the correlation measures obtained from scalp EEG, both in the time and frequency domains. As a result, a number of correlation measures have been proposed aiming to reduce these effects. In our previous work, we have showed that scalp-EEG based functional brain networks in patients with epilepsy exhibit clear periodic patterns at different time scales and that these patterns are strongly correlated to seizure onset, particularly at shorter time scales (around 3 and 5 h), which has important clinical implications. In the present work, we use the same long-duration clinical scalp EEG data (multiple days) to investigate the extent to which the aforementioned results are affected by the choice of reference choice and correlation measure, by considering several widely used montages as well as correlation metrics that are differentially sensitive to the effects of volume conduction. Specifically, we compare two standard and commonly used linear correlation measures, cross-correlation in the time domain, and coherence in the frequency domain, with measures that account for zero-lag correlations: corrected cross-correlation, imaginary coherence, phase lag index, and weighted phase lag index. We show that the graphs constructed with corrected cross-correlation and WPLI are more stable across different choices of reference. Also, we demonstrate that all the examined correlation measures revealed similar periodic patterns in the obtained graph measures when the bipolar and common reference (Cz) montage were used. This includes circadian-related periodicities (e.g., a clear increase in connectivity during sleep periods as compared to awake periods), as well as periodicities at shorter time scales (around 3 and 5 h). On the other hand, these results were affected to a large degree when the average reference montage was used in combination with standard cross-correlation, coherence, imaginary coherence, and PLI, which is likely due to the low number of electrodes and inadequate electrode coverage of the scalp. Finally, we demonstrate that the correlation between seizure onset and the brain network periodicities is preserved when corrected cross-correlation and WPLI were used for all the examined montages. This suggests that, even in the standard clinical setting of EEG recording in epilepsy where only a limited number of scalp EEG measurements are available, graph-theoretic quantification of periodic patterns using appropriate montage, and correlation measures corrected for volume conduction provides useful insights into seizure onset.
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PMID:Graph Theoretical Characteristics of EEG-Based Functional Brain Networks in Patients With Epilepsy: The Effect of Reference Choice and Volume Conduction. 3094 21