25 resultados para Abington, Mrs. (Frances Barton), 1737-1815.

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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Standard methods for the estimation of the postmortem interval (PMI, time since death), based on the cooling of the corpse, are limited to about 48 h after death. As an alternative, noninvasive postmortem observation of alterations of brain metabolites by means of (1)H MRS has been suggested for an estimation of the PMI at room temperature, so far without including the effect of other ambient temperatures. In order to study the temperature effect, localized (1)H MRS was used to follow brain decomposition in a sheep brain model at four different temperatures between 4 and 26°C with repeated measurements up to 2100 h postmortem. The simultaneous determination of 25 different biochemical compounds at each measurement allowed the time courses of concentration changes to be followed. A sudden and almost simultaneous change of the concentrations of seven compounds was observed after a time span that decreased exponentially from 700 h at 4°C to 30 h at 26°C ambient temperature. As this represents, most probably, the onset of highly variable bacterial decomposition, and thus defines the upper limit for a reliable PMI estimation, data were analyzed only up to this start of bacterial decomposition. As 13 compounds showed unequivocal, reproducible concentration changes during this period while eight showed a linear increase with a slope that was unambiguously related to ambient temperature. Therefore, a single analytical function with PMI and temperature as variables can describe the time courses of metabolite concentrations. Using the inverse of this function, metabolite concentrations determined from a single MR spectrum can be used, together with known ambient temperatures, to calculate the PMI of a corpse. It is concluded that the effect of ambient temperature can be reliably included in the PMI determination by (1)H MRS.

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This article contributes to the research on demographics and public health of urban populations of preindustrial Europe. The key source is a burial register that contains information on the deceased, such as age and sex, residence and cause of death. This register is one of the earliest compilations of data sets of individuals with this high degree of completeness and consistency. Critical assessment of the register's origin, formation and upkeep promises high validity and reliability. Between 1805 and 1815, 4,390 deceased inhabitants were registered. Information concerning these individuals provides the basis for this study. Life tables of Bern's population were created using different models. The causes of death were classified and their frequency calculated. Furthermore, the susceptibility of age groups to certain causes of death was established. Special attention was given to causes of death and mortality of newborns, infants and birth-giving women. In comparison to other cities and regions in Central Europe, Bern's mortality structure shows low rates for infants (q0=0.144) and children (q1-4=0.068). This could have simply indicated better living conditions. Life expectancy at birth was 43 years. Mortality was high in winter and spring, and decreased in summer to a low level with a short rise in August. The study of the causes of death was inhibited by difficulties in translating early 19th century nomenclature into the modern medical system. Nonetheless, death from metabolic disorders, illnesses of the respiratory system, and debilitation were the most prominent causes in Bern. Apparently, the worst killer of infants up to 12 months was the "gichteren", an obsolete German term for lethal spasmodic convulsions. The exact modern identification of this disease remains unclear. Possibilities such as infant tetanus or infant epilepsy are discussed. The maternal death rate of 0.72% is comparable with values calculated from contemporaneous sources. Relevance of childbed fever in the early 1800s was low. Bern's data indicate that the extent of deaths related to childbirth in this period is overrated. This research has an explicit interdisciplinary value for various fields including both the humanities and natural sciences, since information reported here represents the complete age and sex structure of a deceased population. Physical anthropologists can use these data as a true reference group for their palaeodemographic studies of preindustrial Central Europe of the late 18th and early 19th century. It is a call to both historians and anthropologists to use our resources to a better effect through combination of methods and exchange of knowledge.

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Knowledge of the time interval from death (post-mortem interval, PMI) has an enormous legal, criminological and psychological impact. Aiming to find an objective method for the determination of PMIs in forensic medicine, 1H-MR spectroscopy (1H-MRS) was used in a sheep head model to follow changes in brain metabolite concentrations after death. Following the characterization of newly observed metabolites (Ith et al., Magn. Reson. Med. 2002; 5: 915-920), the full set of acquired spectra was analyzed statistically to provide a quantitative estimation of PMIs with their respective confidence limits. In a first step, analytical mathematical functions are proposed to describe the time courses of 10 metabolites in the decomposing brain up to 3 weeks post-mortem. Subsequently, the inverted functions are used to predict PMIs based on the measured metabolite concentrations. Individual PMIs calculated from five different metabolites are then pooled, being weighted by their inverse variances. The predicted PMIs from all individual examinations in the sheep model are compared with known true times. In addition, four human cases with forensically estimated PMIs are compared with predictions based on single in situ MRS measurements. Interpretation of the individual sheep examinations gave a good correlation up to 250 h post-mortem, demonstrating that the predicted PMIs are consistent with the data used to generate the model. Comparison of the estimated PMIs with the forensically determined PMIs in the four human cases shows an adequate correlation. Current PMI estimations based on forensic methods typically suffer from uncertainties in the order of days to weeks without mathematically defined confidence information. In turn, a single 1H-MRS measurement of brain tissue in situ results in PMIs with defined and favorable confidence intervals in the range of hours, thus offering a quantitative and objective method for the determination of PMIs.