ORCID Profile
0000-0003-0460-4584
Current Organisations
ECMWF
,
David Geffen School of Medicine at UCLA
,
Hong Kong University of Science and Technology
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Publisher: American Geophysical Union (AGU)
Date: 08-2021
DOI: 10.1029/2021MS002493
Abstract: Global wave hindcasts are developed using the third generation spectral wave model WAVEWATCH III with the observation‐based source terms (ST6) and a hybrid rectilinear‐curvilinear, irregular‐regular‐irregular grid system (approximately at ). Three distinct global hindcasts are produced: (a) a long‐term hindcast (1979–2019) forced by the ERA5 conventional winds and (b) two short‐term hindcasts (2011–2019) driven by the NCEP climate forecast system (CFS)v2 and the ERA5 neutral winds , respectively. The input field for ice is sourced from the Ocean and Sea Ice Satellite Application Facility (OSI SAF) sea‐ice concentration climate data records. These wave simulations, together with the driving wind forcing, are validated against extensive in‐situ observations and satellite altimeter records. The performance of the ST6 wave hindcasts shows promising results across multiple wave parameters, including the conventional wave characteristics (e.g., wave height and wave period) and high‐order spectral moments (e.g., the surface Stokes drift and mean square slope). The ERA5‐based simulations generally present lower random errors, but the CFS‐based run represents extreme sea states (e.g., m) considerably better. Novel wave parameters available in our hindcasts, namely the dominant wave breaking probability, wave‐induced mixed layer depth, freak wave indexes and wave‐spreading factor, are further described and briefly discussed. Inter‐comparisons of from the long‐term (41 years) wave hindcast, buoy measurements and two different calibrated altimeter data sets highlight the inconsistency in these altimeter records arising from different calibration methodology. Significant errors in the low‐frequency bins (period s) for both wave energy and directionality call for further model development.
Publisher: Bentham Science Publishers Ltd.
Date: 10-2008
DOI: 10.2174/138920008786049302
Abstract: The current 'fixed-dosage strategy' approach to medicine, means there is much inter-in idual variation in drug response. Pharmacogenetics is the study of how inter-in idual variations in the DNA sequence of specific genes affect drug responses. This article will highlight current pharmacogenetic knowledge on important drug metabolizing enzymes, drug transporters and drug targets to understand interin idual variability in drug clearance and responses in clinical practice and potential use in personalized medicine. Polymorphisms in the cytochrome P450 (CYP) family may have had the most impact on the fate of pharmaceutical drugs. CYP2D6, CYP2C19 and CYP2C9 gene polymorphisms and gene duplications account for the most frequent variations in phase I metabolism of drugs since nearly 80% of drugs in use today are metabolised by these enzymes. Approximately 5% of Europeans and 1% of Asians lack CYP2D6 activity, and these in iduals are known as poor metabolizers. CYP2C9 is another clinically significant drug metabolising enzyme that demonstrates genetic variants. Studies into CYP2C9 polymorphism have highlighted the importance of the CYP2C9*2 and CYP2C9*3 alleles. Extensive polymorphism also occurs in a majority of Phase II drug metabolizing enzymes. One of the most important polymorphisms is thiopurine S-methyl transferases (TPMT) that catalyzes the S-methylation of thiopurine drugs. With respect to drug transport polymorphism, the most extensively studied drug transporter is P-glycoprotein (P-gp/MDR1), but the current data on the clinical impact is limited. Polymorphisms in drug transporters may change drug's distribution, excretion and response. Recent advances in molecular research have revealed many of the genes that encode drug targets demonstrate genetic polymorphism. These variations, in many cases, have altered the targets sensitivity to the specific drug molecule and thus have a profound effect on drug efficacy and toxicity. For ex le, the beta (2)-adrenoreceptor, which is encoded by the ADRB2 gene, illustrates a clinically significant genetic variation in drug targets. The variable number tandem repeat polymorphisms in serotonin transporter (SERT/SLC6A4) gene are associated with response to antidepressants. The distribution of the common variant alleles of genes that encode drug metabolizing enzymes, drug transporters and drug targets has been found to vary among different populations. The promise of pharmacogenetics lies in its potential to identify the right drug at the right dose for the right in idual. Drugs with a narrow therapeutic index are thought to benefit more from pharmacogenetic studies. For ex le, warfarin serves as a good practical ex le of how pharmacogenetics can be utilized prior to commencement of therapy in order to achieve maximum efficacy and minimum toxicity. As such, pharmacogenetics has the potential to achieve optimal quality use of medicines, and to improve the efficacy and safety of both prospective and licensed drugs.
Location: United States of America
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