Ethnomedicine in healthcare systems of the world: a Semester at Sea pilot survey in 11 countries

An understanding and appreciation for the varied healthcare systems in use throughout the world are increasingly vital for medical personnel as patient populations are now composed of ethnically diverse people with wide-ranging belief systems. While not a statistically valid survey, this pilot study gives a global overview of healthcare differences around the world. A pilot study of 459 individuals from 11 different countries around the world was administered by 33 students in the upper division course, People, Pathology, and World Medicine from Semester at Sea, Fall 2007, to ascertain trends in healthcare therapies. Open-ended surveys were conducted in English, through an interpreter, or in the native language. Western hospital use ranked highly for all countries, while ethnomedical therapies were utilized to a lesser degree. Among the findings, mainland China exhibited the greatest overall percentage of ethnomedical therapies, while the island of Hong Kong, the largest use of Western hospitals. The figures and trends from the surveys suggest the importance of understanding diverse cultural healthcare beliefs when treating individuals of different ethnic backgrounds. The study also revealed the increasingly complex and multisystem-based medical treatments being used internationally

Psychiatric Disorder Criteria and their Application to Research in Different Racial Groups

BACKGROUND: The advent of standardized classification and assessment of psychiatric disorders, and considerable joint efforts among many countries has led to the reporting of international rates of psychiatric disorders, and inevitably, their comparison between different racial groups. RESULTS: In neurologic diseases with defined genetic etiologies, the same genetic cause has different phenotypes in different racial groups. CONCLUSION: We suggest that genetic differences between races mean that diagnostic criteria refined in one racial group, may not be directly and simply applicable to other racial groups and thus more effort needs to be expended on defining diseases in other groups. Cross-racial confounds (in addition to cultural confounds) make the interpretation of rates in different groups even more hazardous than seems to have been appreciated

PCR Primers for Metazoan Mitochondrial 12S Ribosomal DNA Sequences

Background: Assessment of the biodiversity of communities of small organisms is most readily done using PCR-based analysis of environmental samples consisting of mixtures of individuals. Known as metagenetics, this approach has transformed understanding of microbial communities and is beginning to be applied to metazoans as well. Unlike microbial studies, where analysis of the 16S ribosomal DNA sequence is standard, the best gene for metazoan metagenetics is less clear. In this study we designed a set of PCR primers for the mitochondrial 12S ribosomal DNA sequence based on 64 complete mitochondrial genomes and then tested their efficacy. Methodology/Principal Findings: A total of the 64 complete mitochondrial genome sequences representing all metazoan classes available in GenBank were downloaded using the NCBI Taxonomy Browser. Alignment of sequences was performed for the excised mitochondrial 12S ribosomal DNA sequences, and conserved regions were identified for all 64 mitochondrial genomes. These regions were used to design a primer pair that flanks a more variable region in the gene. Then all of the complete metazoan mitochondrial genomes available in NCBI’s Organelle Genome Resources database were used to determine the percentage of taxa that would likely be amplified using these primers. Results suggest that these primers will amplify target sequences for many metazoans. Conclusions/Significance: Newly designed 12S ribosomal DNA primers have considerable potential for metazoa

Collaborative meta-analysis finds no evidence of a strong interaction between stress and 5-HTTLPR genotype contributing to the development of depression

The hypothesis that the S allele of the 5-HTTLPR serotonin transporter promoter region is associated with increased risk of depression, but only in individuals exposed to stressful situations, has generated much interest, research and controversy since first proposed in 2003. Multiple meta-analyses combining results from heterogeneous analyses have not settled the issue. To determine the magnitude of the interaction and the conditions under which it might be observed, we performed new analyses on 31 data sets containing 38 802 European ancestry subjects genotyped for 5-HTTLPR and assessed for depression and childhood maltreatment or other stressful life events, and meta-analysed the results. Analyses targeted two stressors (narrow, broad) and two depression outcomes (current, lifetime). All groups that published on this topic prior to the initiation of our study and met the assessment and sample size criteria were invited to participate. Additional groups, identified by consortium members or self-identified in response to our protocol (published prior to the start of analysis) with qualifying unpublished data, were also invited to participate. A uniform data analysis script implementing the protocol was executed by each of the consortium members. Our findings do not support the interaction hypothesis. We found no subgroups or variable definitions for which an interaction between stress and 5-HTTLPR genotype was statistically significant. In contrast, our findings for the main effects of life stressors (strong risk factor) and 5-HTTLPR genotype (no impact on risk) are strikingly consistent across our contributing studies, the original study reporting the interaction and subsequent meta-analyses. Our conclusion is that if an interaction exists in which the S allele of 5-HTTLPR increases risk of depression only in stressed individuals, then it is not broadly generalisable, but must be of modest effect size and only observable in limited situations.Molecular Psychiatry advance online publication, 4 April 2017; doi:10.1038/mp.2017.44.ALSPAC: Grant 102215/2/13/2 from The Wellcome Trust and grant MC_UU_12013- /6 from the UK Medical Research Council. The University of Bristol also provides core support for ALSPAC. LB receives funding as an Early Career Research Fellow from the Leverhulme Trust. MRM is a member of the UK Centre for Tobacco and Alcohol Studies, a UK Clinical Research Council Public Health Research: Centre of Excellence. Funding from British Heart Foundation, Cancer Research UK, Economic and Social Research Council, Medical Research Council, and the National Institute for Health Research, under the auspices of the UK Clinical Research Collaboration, is gratefully acknowledged. ASPIS: EKBAN 97 from the General Secretariat of Research and Technology, Greek Ministry of Development. ATP: Grants DP130101459, DP160103160 and APP1082406 from the Australian Research Council and The National Health and Medical Research Council of Australia. CHDS: Grant HRC 11/792 from the Health Research Council of New Zealand. CoFaMS: Grant APP1060524 to BTB from the National Health and Medical Research Council of Australia. We acknowledge the University of Adelaide for the provision of seed funding in support of this project. COGA: Grant U10AA008401 from the National Institutes of Health, NIAAA and NIDA. COGEND: National Institutes of Health grants P01CA089392 from NCI and R01DA036583 from NIDA. DeCC: Grant G0701420 from the UK Medical Research Council, and a UK MRC Population Health Scientist fellowship (G1002366) and an MQ Fellows Award (MQ14F40) to Helen L Fisher. EPIC-Norfolk: Grants G9502233, G0300128, C865/A2883 from the UK Medical Research Council and Cancer Research UK. ESPRIT Montpellier: An unconditional grant from Novartis and from the National Research Agency (ANR Project 07 LVIE004). G1219: A project grant from the WT Grant Foundation and G120/635, a Career Development Award from the UK Medical Research Council to Thalia Eley. The GENESiS project was supported by Grant G9901258 from the UK Medical Research Council. This study presents independent research part- funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. GAN12-France: Research Protocol C0829 from INSERM; Research Protocol GAN12 from Assistance Publique des Hôpitaux de Paris; ANR-11-IDEX- 0004 from Investissements d’Avenir program managed by the ANR, and RTRS Sante Mentale from Fondation FondaMental. GENESIS: Grant PHRC UF 7653 & ANR NEURO 2007 ‘GENESIS’ from CHU Montpellier & Agence Nationale de la Recherche. Heart and Soul: Epidemiology Merit Review Program from the Department of Veterans Affairs; National Institutes of Health grant R01HL-079235 from NHLBI; Generalist Physician Faculty Scholars Program from the Robert Woods Johnson foundation; Paul Beeson Faculty Scholars Program from the American Federation for Aging Research; and a Young Investigator Award from the Bran and Behavior Research Foundation. MARS: Grant LA 733/2-1 from German Research Foundation (DFG) and the Federal Ministry for Education and Research as part of the 'National Genome Research Network'. MLS: National Institutes of Health grants R01 AA07065 and R37 AA07065 from NIAAA. MoodInFlame: Grant EU-FP7- HEALTH-F2-2008-222963 from the European Union. Muenster Neuroimaging Study: Grant FOR2107, DA1151/5-1 from the German Research Foundation (DFG). NEWMOOD: Grants LSHM-CT-2004-503474 from Sixth Framework Program of the European Union; KTIA_NAP_13-1-2013-0001, KTIA_13_NAP-A-II/14 from National Development Agency Hungarian Brain Research Program; KTIA_NAP_13-2-2015-0001 from MTA-SE-NAP B Genetic Brain Imaging Migraine Research Group, Hungarian Academy of Sciences, Semmelweis University; support from Hungarian Academy of Sciences, MTA-SE Neuropsychopharmacology and Neurochemistry Research Group; and support from the National Institute for Health Research Manchester Biomedical Research Centre. NESDA/NTR: The Netherlands Organization for Scientific Research (NWO) and MagW/ZonMW grants Middelgroot-911-09-032, Spinozapremie 56-464- 14192, Geestkracht program of the Netherlands Organization for Health Research and Development (ZonMW 10-000-1002), Center for Medical Systems Biology (CSMB, NWO Genomics), Genetic influences on stability and change in psychopathology from childhood to young adulthood (ZonMW 912-10-020), NBIC/BioAssist/RK (2008.024), Biobanking and Biomolecular Resources Research Infrastructure (BBMRI -NL, 184.021.007), VU University's Institute for Health and Care Research (EMGO+) and Neuroscience Campus Amsterdam (NCA); the European Science Council (ERC Advanced, 230374). Part of the genotyping and analyses were funded by the Genetic Association Information Network (GAIN) of the Foundation for the National Institutes of Health, Rutgers University Cell and DNA Repository (NIMH U24 MH068457-06), the Avera Institute, Sioux Falls, South Dakota (USA) and the National Institutes of Health (NIH R01 HD042157-01A1, MH081802, Grand Opportunity grants 1RC2 MH089951 and 1RC2 MH089995). PATH: Program Grant Number 179805 from the National Health and Medical Research Council of Australia. POUCH: Grants 20FY01-38 and 20-FY04-37 of the Perinatal Epidemiologic Research Initiative Program Grant from the March of Dimes Foundation; National Institutes of Health grant R01 HD34543 from NICHD and NINR; grant 02816-7 from the Thrasher Research Foundation; and grant U01 DP000143-01 from the Centers for Disease Control and Prevention. QIMRtwin: Grants 941177, 971232, 339450, 443011 from the National Health and Medical Research Council of Australia; AA07535, AA07728, AA10249 from US Public Health Service; National Institutes of Health grant K99DA023549-01A2 from NIDA. Additional support was provided by Beyond Blue. SALVe 2001 and SALVe 2006: Grants FO2012-0326, FO2013-0023, FO2014-0243 from The Brain Foundation (Hjärnfonden); SLS-559921 from Söderström-Königska Foundation; 2015-00897 from Swedish Council for Working Life and Social Research; and M15-0239 from Åke Wiberg's Foundation. Additional funding was provided by Systembolagets Råd för Alkoholforskning, SRA and Svenska Spel Research Council. SEBAS: National Institutes of Health grants R01 AG16790, R01 AG16661 and R56 AG01661 from NIA and grant P2CHD047879 from NICHD; and additional financial support from the Graduate School of Arts and Sciences at Georgetown University. SHIP/TREND: This work was supported by the German Federal Ministry of Education and Research within the framework of the e:Med research and funding concept (Integrament) Grant No. 01ZX1314E. Study of Health in Pomerania is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research Grant Nos. 01ZZ9603, 01ZZ0103 and 01ZZ0403; the Ministry of Cultural Affairs; and the Social Ministry of the Federal State of Mecklenburg-West Pomerania. Genome-wide data were supported by the Federal Ministry of Education and Research Grant No. 03ZIK012 and a joint grant from Siemens Healthcare, Erlangen, Germany and the Federal State of Mecklenburg-West Pomerania. The Greifswald Approach to Individualised Medicine (GANI_MED) was funded by the Federal Ministry of Education and Research Grant No. 03IS2061A and the German Research Foundation Grant No. GR 1912/5-1. TRAILS: Grants GB-MW 940- 38-011, ZonMW Brainpower 100-001-004, Investment grant 175.010.2003.005, GBMaGW 480-07-001 and Longitudinal Survey and Panel Funding 481-08-013 from the Netherlands Organization for Scientific Research (NWO). Additional funding was provided by the Dutch Ministry of Justice, the European Science Foundation, BBMRINL and the participating centres (UMCG, RUG, Erasmus MC, UU, Radboud MC, Parnassia Bavo group): VAHCS: Grants APP1063091, 1008271 and 1019887 from Australia’s National Health and Medical Research Council of Australia (NHMRC)

Hepatic Abnormalities Associated with Aluminum Loading in Piglets

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141476/1/jpen0293.pd

The Trypanosoma cruzi Sylvio X10 strain maxicircle sequence: the third musketeer

<p>Abstract</p> <p>Background</p> <p>Chagas disease has a diverse pathology caused by the parasite <it>Trypanosoma cruzi</it>, and is indigenous to Central and South America. A pronounced feature of the trypanosomes is the kinetoplast, which is comprised of catenated maxicircles and minicircles that provide the transcripts involved in uridine insertion/deletion RNA editing. <it>T. cruzi </it>exchange genetic material through a hybridization event. Extant strains are grouped into six discrete typing units by nuclear markers, and three clades, A, B, and C, based on maxicircle gene analysis. Clades A and B are the more closely related. Representative clade B and C maxicircles are known in their entirety, and portions of A, B, and C clades from multiple strains show intra-strain heterogeneity with the potential for maxicircle taxonomic markers that may correlate with clinical presentation.</p> <p>Results</p> <p>To perform a genome-wide analysis of the three maxicircle clades, the coding region of clade A representative strain Sylvio X10 (a.k.a. Silvio X10) was sequenced by PCR amplification of specific fragments followed by assembly and comparison with the known CL Brener and Esmeraldo maxicircle sequences. The clade A rRNA and protein coding region maintained synteny with clades B and C. Amino acid analysis of non-edited and 5'-edited genes for Sylvio X10 showed the anticipated gene sequences, with notable frameshifts in the non-edited regions of Cyb and ND4. Comparisons of genes that undergo extensive uridine insertion and deletion display a high number of insertion/deletion mutations that are likely permissible due to the post-transcriptional activity of RNA editing.</p> <p>Conclusion</p> <p>Phylogenetic analysis of the entire maxicircle coding region supports the closer evolutionary relationship of clade B to A, consistent with uniparental mitochondrial inheritance from a discrete typing unit TcI parental strain and studies on smaller fragments of the mitochondrial genome. Gene variance that can be corrected by RNA editing hints at an unusual depth for maxicircle taxonomic markers, which will aid in the ability to distinguish strains, their corresponding symptoms, and further our understanding of the <it>T. cruzi </it>population structure. The prevalence of apparently compromised coding regions outside of normally edited regions hints at undescribed but active mechanisms of genetic exchange.</p