Estimation of the postmortem interval by means of ¹H MRS of decomposing brain tissue: influence of ambient temperature

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.

Stability of coagulation assays performed in plasma from citrated whole blood transported at ambient temperature

Many preanalytical variables affect the results of coagulation assays. A possible way to control some of them would be to accept blood specimens shipped in the original collection tube. The aim of our study was to investigate the stability of coagulation assays in citrated whole blood transported at ambient temperature for up to two days after specimen collection. Blood samples from 59 patients who attended our haematology outpatient ward for thrombophilia screening were transported at ambient temperature (outdoor during the day, indoor overnight) for following periods of time: <1 hour, 4-6, 8-12, 24-28 and 48-52 hours prior to centrifugation and plasma-freezing. The following coagulation tests were performed: PT, aPTT, fibrinogen, FII:C, FV:C, FVII:C, FVIII:C, FIX:C, FX:C, FXI:C, VWF:RCo, VWF:Ag, AT, PC activity, total and free PS antigen, modified APC-sensitivity-ratio, thrombin-antithrombin-complex and D-dimer. Clinically significant changes, defined as a percentage change of more than 10% from the initial value, were observed for FV:C, FVIII:C and total PS antigen starting at 24-28 hours, and for PT, aPTT and FVII:C at 48-52 hours. No statistically significant differences were seen for fibrinogen, antithrombin, or thrombin-antithrombin complexes (Friedman repeated measures analysis of variance). The present data suggest that the use of whole blood samples transported at ambient temperature may be an acceptable means of delivering specimens for coagulation analysis. With the exception of factor V and VIII coagulant activity, and total PS antigen all investigated parameters can be measured 24-28 hours after specimen collection without observing clinically relevant changes.

Color and Scent: How Single Genes Influence Pollinator Attraction

A major function of angiosperm flowers is the recruitment of animal pollinators that serve to transfer pollen among conspecific plants. Distinct sets of floral characteristics, called pollination syndromes, are correlated with visitation by specific groups of pollinators. Switches among pollination syndromes have occurred in many plant families. Such switches must have involved coordinated changes in multiple traits and multiple genes. Two well-studied floral traits affecting pollinator attraction are petal color and scent production. We review current knowledge about the biosynthetic pathways for floral color and scent production and their interaction at the genetic and biochemical levels. A key question in the field concerns the genes that underlie natural variation in color and scent and how such genes affect pollinator preference, reproductive isolation, and ultimately speciation.

Net CO 2 surface emissions at Bern, Switzerland inferred from ambient observations of CO 2 , δ(O 2 /N 2 ), and 222 Rn using a customized radon tracer inversion

The 222Radon tracer method is a powerful tool to estimate local and regional surface emissions of, e.g., greenhouse gases. In this paper we demonstrate that in practice, the method as it is commonly used, produces inaccurate results in case of nonhomogeneously spread emission sources, and we propose a different approach to account for this. We have applied the new methodology to ambient observations of CO2 and 222Radon to estimate CO2 surface emissions for the city of Bern, Switzerland. Furthermore, by utilizing combined measurements of CO2 and δ(O2/N2) we obtain valuable information about the spatial and temporal variability of the main emission sources. Mean net CO2 emissions based on 2 years of observations are estimated at (11.2 ± 2.9) kt km−2 a−1. Oxidative ratios indicate a significant influence from the regional biosphere in summer/spring and fossil fuel combustion processes in winter/autumn. Our data indicate that the emissions from fossil fuels are, to a large degree, related to the combustion of natural gas which is used for heating purposes.

A web-based non-intrusive ambient system to measure and classify activities of daily living.

BACKGROUND The number of older adults in the global population is increasing. This demographic shift leads to an increasing prevalence of age-associated disorders, such as Alzheimer's disease and other types of dementia. With the progression of the disease, the risk for institutional care increases, which contrasts with the desire of most patients to stay in their home environment. Despite doctors' and caregivers' awareness of the patient's cognitive status, they are often uncertain about its consequences on activities of daily living (ADL). To provide effective care, they need to know how patients cope with ADL, in particular, the estimation of risks associated with the cognitive decline. The occurrence, performance, and duration of different ADL are important indicators of functional ability. The patient's ability to cope with these activities is traditionally assessed with questionnaires, which has disadvantages (eg, lack of reliability and sensitivity). Several groups have proposed sensor-based systems to recognize and quantify these activities in the patient's home. Combined with Web technology, these systems can inform caregivers about their patients in real-time (e.g., via smartphone). OBJECTIVE We hypothesize that a non-intrusive system, which does not use body-mounted sensors, video-based imaging, and microphone recordings would be better suited for use in dementia patients. Since it does not require patient's attention and compliance, such a system might be well accepted by patients. We present a passive, Web-based, non-intrusive, assistive technology system that recognizes and classifies ADL. METHODS The components of this novel assistive technology system were wireless sensors distributed in every room of the participant's home and a central computer unit (CCU). The environmental data were acquired for 20 days (per participant) and then stored and processed on the CCU. In consultation with medical experts, eight ADL were classified. RESULTS In this study, 10 healthy participants (6 women, 4 men; mean age 48.8 years; SD 20.0 years; age range 28-79 years) were included. For explorative purposes, one female Alzheimer patient (Montreal Cognitive Assessment score=23, Timed Up and Go=19.8 seconds, Trail Making Test A=84.3 seconds, Trail Making Test B=146 seconds) was measured in parallel with the healthy subjects. In total, 1317 ADL were performed by the participants, 1211 ADL were classified correctly, and 106 ADL were missed. This led to an overall sensitivity of 91.27% and a specificity of 92.52%. Each subject performed an average of 134.8 ADL (SD 75). CONCLUSIONS The non-intrusive wireless sensor system can acquire environmental data essential for the classification of activities of daily living. By analyzing retrieved data, it is possible to distinguish and assign data patterns to subjects' specific activities and to identify eight different activities in daily living. The Web-based technology allows the system to improve care and provides valuable information about the patient in real-time.

Ambient cosmology and spacetime singularities

We present a new approach to the issues of spacetime singularities and cosmic censorship in general relativity. This is based on the idea that standard 4-dimensional spacetime is the conformal infinity of an ambient metric for the 5-dimensional Einstein equations with fluid sources. We then find that the existence of spacetime singularities in four dimensions is constrained by asymptotic properties of the ambient 5-metric, while the non-degeneracy of the latter crucially depends on cosmic censorship holding on the boundary.

Scent-marking behaviour and social dynamics in a wild population of Eurasian lynx Lynx lynx.

Scent-marking is widespread among mammals and has been observed in many felid species. Although the behaviour is well-described, little is known about its function in wild felid populations. We investigated patterns of scent-marking and its role in intra- and intersexual communication among resident and non-resident Eurasian lynx Lynx lynx by observing interactions among wild lynx at natural marking sites by means of infrared camera traps. Marking activity of resident animals showed a peak during the mating season and was lowest during the time when females gave birth and lactated. Both sexes scent-marked, but male lynx visited marking sites much more often than females and marked relatively more often when visiting a site. Most visits to marking sites were by residents but we also observed scent-marking by non-residents. Juveniles were never observed marking. We found no evidence of lynx regularly renewing scent-marks after a certain 'expiry date' but the presence of a strange scent-mark triggered over-marking. Males responded similarly to the presence of another individual's scent-mark, irrespective of whether it was the top- or the underlying scent-mark in a mixture of scent-marks they encountered. Our results suggest that marking sites could serve as 'chemical bulletin boards', where male lynx advertise their presence and gain information on ownership relationships in a given area. Females placed their urine marks on top of the ones left by resident males, but further studies are needed to explain the functions of over-marking in females.

Evaluation of Three State-of-the-Art Classifiers for Recognition of Activities of Daily Living from Smart Home Ambient Data

Smart homes for the aging population have recently started attracting the attention of the research community. The "health state" of smart homes is comprised of many different levels; starting with the physical health of citizens, it also includes longer-term health norms and outcomes, as well as the arena of positive behavior changes. One of the problems of interest is to monitor the activities of daily living (ADL) of the elderly, aiming at their protection and well-being. For this purpose, we installed passive infrared (PIR) sensors to detect motion in a specific area inside a smart apartment and used them to collect a set of ADL. In a novel approach, we describe a technology that allows the ground truth collected in one smart home to train activity recognition systems for other smart homes. We asked the users to label all instances of all ADL only once and subsequently applied data mining techniques to cluster in-home sensor firings. Each cluster would therefore represent the instances of the same activity. Once the clusters were associated to their corresponding activities, our system was able to recognize future activities. To improve the activity recognition accuracy, our system preprocessed raw sensor data by identifying overlapping activities. To evaluate the recognition performance from a 200-day dataset, we implemented three different active learning classification algorithms and compared their performance: naive Bayesian (NB), support vector machine (SVM) and random forest (RF). Based on our results, the RF classifier recognized activities with an average specificity of 96.53%, a sensitivity of 68.49%, a precision of 74.41% and an F-measure of 71.33%, outperforming both the NB and SVM classifiers. Further clustering markedly improved the results of the RF classifier. An activity recognition system based on PIR sensors in conjunction with a clustering classification approach was able to detect ADL from datasets collected from different homes. Thus, our PIR-based smart home technology could improve care and provide valuable information to better understand the functioning of our societies, as well as to inform both individual and collective action in a smart city scenario.

Topology of the ambient boundary and the convergence of causal curves

We discuss the topological nature of the boundary spacetime, the conformal infinity of the ambient cosmological metric. Due to the existence of a homothetic group, the bounding spacetime must be equipped not with the usual Euclidean metric topology but with the Zeeman fine topology. This then places severe constraints to the convergence of a sequence of causal curves and the extraction of a limit curve, and also to our ability to formulate conditions for singularity formation.