CLIWOC multilingual meteorological dictionary

This dictionary is the first attempt to express the wealth of archaic logbook wind force terms in a form that is comprehensible to the modern-day reader. Oliver and Kington (1970) and Lamb (1982) have drawn attention to the importance of logbooks in climatic studies, and Lamb (1991) offered a conversion scale for early eighteenth century English wind force terms, but no studies have thus far pursued the matter to any greater depth. This text attempts to make good this deficiency, and is derived from the research undertaken by the CLIWOC project1 in which British, Dutch, French and Spanish naval and merchant logbooks from the period 1750 to 1850 were used to derive a global database of climatic information. At an early stage in the project it was apparent that many of the logbook weather terms, whilst conforming to a conventional vocabulary, possessed meanings that were unclear to twenty-first century readers or had changed over time. This was particularly the case for the important element of wind force; but no special plea is entered for the evolution in nautical vocabulary, which often reflected more wide-ranging changes in the respective native languages.The key objective was to translate the archaic vocabulary of the late eighteenth and early nineteenth century mariner into expressions directly comparable with the Beaufort Scale (see Appendix I). Only then could the projects scientific programme be embarked upon. This dictionary is the result of the largest undertaking into logbook studies that has yet been carried out. Several thousand logbooks from British, Dutch, French and Spanish archives were examined, and the exercise offered a unique opportunity to explore the vocabulary of the one hundred year period beginning in 1750. The logbooks from which the raw data have been abstracted range widely across the North and South Atlantic and the Indian Oceans. Only the Pacific, largely in consequence of the paucity of regular naval activity in that area, is not well represented. The range of climates encountered in this otherwise wide geographic domain gives ample opportunity for the full range of the mariners nautical weather vocabulary to be assessed, from the calms of the Equatorial regions, through the gales of the mid-latitude systems to the fearsome storms of the tropical latitudes. The Trade Winds belts, the Doldrums, the unsettled mid-latitudes, even the icy wastes of the high latitudes, are all embraced in this study. It is not here intended to pass any judgements on the climatological record of the logbooks, and this text seeks only to provide a means of understanding archaic wind force terms and, other than to indicate those items that were not commonly used, no information is given on the frequency with which different terms appeared in the logbooks. Attention is, furthermore, confined to Dutch, English, French and Spanish because these once great imperial powers were the only nations able to support wide-ranging ocean-going fleets with their attendant collections of logbooks and documents over this long period of time. The work is offered to the wider academic community in the hope that they will prove to be of as much value as it has been to the CLIWOC team

Semi-automated non-target processing in GC × GC–MS metabolomics analysis: applicability for biomedical studies

Due to the complexity of typical metabolomics samples and the many steps required to obtain quantitative data in GC × GC–MS consisting of deconvolution, peak picking, peak merging, and integration, the unbiased non-target quantification of GC × GC–MS data still poses a major challenge in metabolomics analysis. The feasibility of using commercially available software for non-target processing of GC × GC–MS data was assessed. For this purpose a set of mouse liver samples (24 study samples and five quality control (QC) samples prepared from the study samples) were measured with GC × GC–MS and GC–MS to study the development and progression of insulin resistance, a primary characteristic of diabetes type 2. A total of 170 and 691 peaks were quantified in, respectively, the GC–MS and GC × GC–MS data for all study and QC samples. The quantitative results for the QC samples were compared to assess the quality of semi-automated GC × GC–MS processing compared to targeted GC–MS processing which involved time-consuming manual correction of all wrongly integrated metabolites and was considered as golden standard. The relative standard deviations (RSDs) obtained with GC × GC–MS were somewhat higher than with GC–MS, due to less accurate processing. Still, the biological information in the study samples was preserved and the added value of GC × GC–MS was demonstrated; many additional candidate biomarkers were found with GC × GC–MS compared to GC–MS

Fluorescence analysis of the Hansenula polymorpha peroxisomal targeting signal-1 receptor, Pex5p

Correct sorting of newly synthesized peroxisomal matrix proteins is dependent on a peroxisomal targeting signal (PTS). So far two PTSs are known. PTS1 consists of a tripeptide that is located at the extreme C terminus of matrix proteins and is specifically recognized by the PTS1-receptor Pex5p. We studied Hansenula polymorpha Pex5p (HpPex5p) using fluorescence spectroscopy. The intensity of Trp fluorescence of purified HpPex5p increased by 25% upon shifting the pH from pH 6.0 to pH 7.2. Together with the results of fluorescence quenching by acrylamide, these data suggest that the conformation of HpPex5p differs at these two pH values. Fluorescence anisotropy decay measurements revealed that the pH affected the oligomeric state of HpPex5p, possibly from monomers/dimers at pH 6.0 to larger oligomeric forms at pH 7.2. Addition of dansylated peptides containing a PTS1, caused some shortening of the average fluorescence lifetime of the Trp residues, which was most pronounced at pH 7.2. Our data are discussed in relation to a molecular model of HpPex5p based on the three-dimensional structure of human Pex5p

Chemical fingerprints of emotional body odor

Chemical communication is common among animals. In humans, the chemical basis of social communication has remained a black box, despite psychological and neural research showing distinctive physiological, behavioral, and neural consequences of body odors emitted during emotional states like fear and happiness. We used a multidisciplinary approach to examine whether molecular cues could be associated with an emotional state in the emitter. Our research revealed that the volatile molecules transmitting different emotions to perceivers also have objectively different chemical properties. Chemical analysis of underarm sweat collected from the same donors in fearful, happy, and emotionally neutral states was conducted using untargeted two-dimensional (GC×GC) coupled with time of flight (ToF) MS-based profiling. Based on the multivariate statistical analyses, we find that the pattern of chemical volatiles (N = 1655 peaks) associated with fearful state is clearly different from that associated with (pleasant) neutral state. Happy sweat is also significantly different from the other states, chemically, but shows a bipolar pattern of overlap with fearful as well as neutral state. Candidate chemical classes associated with emotional and neutral sweat have been identified, specifically, linear aldehydes, ketones, esters, and cyclic molecules (5 rings). This research constitutes a first step toward identifying the chemical fingerprints of emotion.info:eu-repo/semantics/publishedVersio

Phencyclidine-induced catalepsy in pigeons: Specificity and stereoselectivity

A procedure is described for the rapid assessment of cataleptic activity (loss of righting, without head-drop and without eye closure) of phencyclidine-type drugs. Single- and cumulative-dosing procedures with phencyclidine and ketamine produced similar results. Pentobarbital produced loss of righting at doses which also induced head-drop and eye closure. Catalepsy was induced exclusively by the d-isomers of ketamine, 1-(1-phenylcyclohexyl)-3-methylpiperidine and [alpha]-dioxadrol. The procedure is suitable for studying compounds which may interact with phencyclidine receptors.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/24637/1/0000048.pd

Decynium-22 enhances SSRI-induced antidepressant-like effects in mice: uncovering novel targets to treat depression

Mood disorders cause much suffering and lost productivity worldwide, compounded by the fact that many patients are not effectively treated by currently available medications. The most commonly prescribed antidepressant drugs are the selective serotonin (5-HT) reuptake inhibitors (SSRIs), which act by blocking the high-affinity 5-HT transporter (SERT). The increase in extracellular 5-HT produced by SSRIs is thought to be critical to initiate downstream events needed for therapeutic effects. A potential explanation for their limited therapeutic efficacy is the recently characterized presence of low-affinity, high-capacity transporters for 5-HT in brain [i.e., organic cation transporters (OCTs) and plasma membrane monoamine transporter], which may limit the ability of SSRIs to increase extracellular 5-HT. Decynium-22 (D-22) is a blocker of these transporters, and using this compound we uncovered a significant role for OCTs in 5-HT uptake in mice genetically modified to have reduced or no SERT expression (Baganz et al., 2008). This raised the possibility that pharmacological inactivation of D-22-sensitive transporters might enhance the neurochemical and behavioral effects of SSRIs. Here we show that in wild-type mice D-22 enhances the effects of the SSRI fluvoxamine to inhibit 5-HT clearance and to produce antidepressant-like activity. This antidepressant-like activity of D-22 was attenuated in OCT3 KO mice, whereas the effect of D-22 to inhibit 5-HT clearance in the CA3 region of hippocampus persisted. Our findings point to OCT3, as well as other D-22-sensitive transporters, as novel targets for new antidepressant drugs with improved therapeutic potential.Rebecca E. Horton, Deana M. Apple, W. Anthony Owens, Nicole L. Baganz, Sonia Cano, Nathan C. Mitchell, Melissa Vitela, Georgianna G. Gould, Wouter Koek and Lynette C. Daw

Discovery of early-stage biomarkers for diabetic kidney disease using ms-based metabolomics (FinnDiane study)

Diabetic kidney disease (DKD) is a devastating complication that affects an estimated third of patients with type 1 diabetes mellitus (DM). There is no cure once the disease is diagnosed, but early treatment at a sub-clinical stage can prevent or at least halt the progression. DKD is clinically diagnosed as abnormally high urinary albumin excretion rate (AER). We hypothesize that subtle changes in the urine metabolome precede the clinically significant rise in AER. To test this, 52 type 1 diabetic patients were recruited by the FinnDiane study that had normal AER (normoalbuminuric). After an average of 5.5 years of follow-up half of the subjects (26) progressed from normal AER to microalbuminuria or DKD (macroalbuminuria), the other half remained normoalbuminuric. The objective of this study is to discover urinary biomarkers that differentiate the progressive form of albuminuria from non-progressive form of albuminuria in humans. Metabolite profiles of baseline 24 h urine samples were obtained by gas chromatography–mass spectrometry (GC–MS) and liquid chromatography–mass spectrometry (LC–MS) to detect potential early indicators of pathological changes. Multivariate logistic regression modeling of the metabolomics data resulted in a profile of metabolites that separated those patients that progressed from normoalbuminuric AER to microalbuminuric AER from those patients that maintained normoalbuminuric AER with an accuracy of 75% and a precision of 73%. As this data and samples are from an actual patient population and as such, gathered within a less controlled environment it is striking to see that within this profile a number of metabolites (identified as early indicators) have been associated with DKD already in literature, but also that new candidate biomarkers were found. The discriminating metabolites included acyl-carnitines, acyl-glycines and metabolites related to tryptophan metabolism. We found candidate biomarkers that were univariately significant different. This study demonstrates the potential of multivariate data analysis and metabolomics in the field of diabetic complications, and suggests several metabolic pathways relevant for further biological studies