"Brienzi" - The blue Vivianite man of Switzerland: Time since death estimation of an adipocere body

In 1996, a cadaver in adipocere condition was discovered in a bay of the Brienzer See in Switzerland. The torso was named "Brienzi" following the "Iceman" Ötzi. Several outer parts of the body were incrusted; the incrustation was in blue color. Further investigations showed that the bluish covering of parts of the adipocere torso were a mineral known as Vivianite. Vivianite (Fe(3)(PO(4))(2-)(H(2)O)(8)) is an iron phosphate mineral with needle lengths between 100 and 150μm. It is normally associated in a context with organic archaeological and geological materials (some hundreds to millions of years old). Hitherto, it is only described in three cases of human remains. We were able to reconstruct the following facts about 'Brienzi': The man drowned in Lake Brienz or in one of its tributaries during the 1700s. The body was subsequently covered with sedimentation and thus buried under water. An earthquake produced an underwater landslide which eventually exposed the corpse.

Statistical evaluation of time-dependent metabolite concentrations: estimation of post-mortem intervals based on in situ 1H-MRS of the brain

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.

Parametric estimation of pulse arrival time: a robust approach to pulse wave velocity

Pulse wave velocity (PWV) is a surrogate of arterial stiffness and represents a non-invasive marker of cardiovascular risk. The non-invasive measurement of PWV requires tracking the arrival time of pressure pulses recorded in vivo, commonly referred to as pulse arrival time (PAT). In the state of the art, PAT is estimated by identifying a characteristic point of the pressure pulse waveform. This paper demonstrates that for ambulatory scenarios, where signal-to-noise ratios are below 10 dB, the performance in terms of repeatability of PAT measurements through characteristic points identification degrades drastically. Hence, we introduce a novel family of PAT estimators based on the parametric modeling of the anacrotic phase of a pressure pulse. In particular, we propose a parametric PAT estimator (TANH) that depicts high correlation with the Complior(R) characteristic point D1 (CC = 0.99), increases noise robustness and reduces by a five-fold factor the number of heartbeats required to obtain reliable PAT measurements.

A shift from oral to intravenous iron supplementation therapy is observed over time in a large swiss cohort of patients with inflammatory bowel disease

BACKGROUND In 2007, leading international experts in the field of inflammatory bowel disease (IBD) recommended intravenous (IV) iron supplements over oral (PO) ones because of superior effectiveness and better tolerance. We aimed to determine the percentage of patients with IBD undergoing iron therapy and to assess the dynamics of iron prescription habits (IV versus PO). METHODS We analyzed anonymized data on patients with Crohn's disease and ulcerative colitis extracted from the Helsana database. Helsana is a Swiss health insurance company providing coverage for 18% of the Swiss population (1.2 million individuals). RESULTS In total, 629 patients with Crohn's disease (61% female) and 398 patients with ulcerative colitis (57% female) were identified; mean observation time was 31.8 months for Crohn's disease and 31.0 months for ulcerative colitis patients. Of all patients with IBD, 27.1% were prescribed iron (21.1% in males; 31.1% in females). Patients treated with steroids, immunomodulators, and/or anti-tumor necrosis factor drugs were more frequently treated with iron supplements when compared with those not treated with any medications (35.0% versus 20.9%, odds ratio, 1.94; P < 0.001). The frequency of IV iron prescriptions increased significantly from 2006 to 2009 for both genders (males: from 2.6% to 10.1%, odds ratio = 3.84, P < 0.001; females: from 5.3% to 12.1%, odds ratio = 2.26, P = 0.002), whereas the percentage of PO iron prescriptions did not change. CONCLUSIONS Twenty-seven percent of patients with IBD were treated with iron supplements. Iron supplements administered IV were prescribed more frequently over time. These prescription habits are consistent with the implementation of guidelines on the management of iron deficiency in IBD.

Surgical Treatment of Recurrent Endometrial Cancer: Time for a Paradigm Shift.

BACKGROUND Although surgery represents the cornerstone treatment of endometrial cancer at initial diagnosis, scarce data are available in recurrent setting. The purpose of this study was to review the outcome of surgery in these patients. METHODS Medical records of all patients undergoing surgery for recurrent endometrial cancer at NCI Milano between January 2003 and January 2014 were reviewed. Survival was determined from the time of surgery for recurrence to last follow-up. Survival was estimated using Kaplan-Meier methods. Differences in survival were analyzed using the log-rank test. The Fisher's exact test was used to compare optimal versus suboptimal cytoreduction against possible predictive factors. RESULTS Sixty-four patients were identified. Median age was 66 years. Recurrences were multiple in 38 % of the cases. Optimal cytoreduction was achieved in 65.6 %. Median OR time was 165 min, median postoperative hemoglobin drop was 2.4 g/dl, and median length hospital stay was 5.5 days. Eleven patients developed postoperative complications, but only four required surgical management. Estimated 5-year progression-free survival (PFS) was 42 and 19 % in optimally and suboptimally cytoreduced patients, respectively. At multivariate analysis, only residual disease was associated with PFS. Estimated 5-year overall survival (OS) was 60 and 30 % in optimally and suboptimally cytoreduced patients, respectively. At multivariate analysis, residual disease and histotype were associated with OS. At multivariate analysis, only performance status was associated with optimal cytoreduction. CONCLUSIONS Secondary cytoreduction in endometrial cancer is associated with long PFS and OS. The only factors associated with improved long-term outcome are the absence of residual disease at the end of surgical resection and histotype.

Sample size estimation: an overview with applications to orthodontic clinical trial designs

Proper sample size estimation is an important part of clinical trial methodology and closely related to the precision and power of the trial's results. Trials with sufficient sample sizes are scientifically and ethically justified and more credible compared with trials with insufficient sizes. Planning clinical trials with inadequate sample sizes might be considered as a waste of time and resources, as well as unethical, since patients might be enrolled in a study in which the expected results will not be trusted and are unlikely to have an impact on clinical practice. Because of the low emphasis of sample size calculation in clinical trials in orthodontics, it is the objective of this article to introduce the orthodontic clinician to the importance and the general principles of sample size calculations for randomized controlled trials to serve as guidance for study designs and as a tool for quality assessment when reviewing published clinical trials in our specialty. Examples of calculations are shown for 2-arm parallel trials applicable to orthodontics. The working examples are analyzed, and the implications of design or inherent complexities in each category are discussed.

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.

A real time simulation model of glucose-insulin metabolism for type 1 diabetes patients

In this paper, a simulation model of glucose-insulin metabolism for Type 1 diabetes patients is presented. The proposed system is based on the combination of Compartmental Models (CMs) and artificial Neural Networks (NNs). This model aims at the development of an accurate system, in order to assist Type 1 diabetes patients to handle their blood glucose profile and recognize dangerous metabolic states. Data from a Type 1 diabetes patient, stored in a database, have been used as input to the hybrid system. The data contain information about measured blood glucose levels, insulin intake, and description of food intake, along with the corresponding time. The data are passed to three separate CMs, which produce estimations about (i) the effect of Short Acting (SA) insulin intake on blood insulin concentration, (ii) the effect of Intermediate Acting (IA) insulin intake on blood insulin concentration, and (iii) the effect of carbohydrate intake on blood glucose absorption from the gut. The outputs of the three CMs are passed to a Recurrent NN (RNN) in order to predict subsequent blood glucose levels. The RNN is trained with the Real Time Recurrent Learning (RTRL) algorithm. The resulted blood glucose predictions are promising for the use of the proposed model for blood glucose level estimation for Type 1 diabetes patients.

Non-invasive quantitative estimation of bone density in rats throughout the life cycle and in arthritic osteopenia: preliminary results

A longitudinal bone survey was conducted in 86 female Wistar rats in order to assess mineral density kinetics from young age (5 weeks: 115 g) till late adulthood (64 weeks: 586 g). In vivo quantitative radiographic scanning was performed on the caudal vertebrae, taking trabecular mass as the parameter. Measurements were expressed as Relative Optical Density (ROD) units by means of a high resolution densitometric device. Results showed a progressive increase in mineral density throughout the life cycle, with a tendency to level in the higher weight range, indicating that progressive mineral aposition occurs in rats in dependency of age. This phenomenon, however, should be always considered within the context of continuous skeletal growth and related changes typical of this species. Twelve different animals were also examined following induction of articular inflammation with Freund's adjuvant in six of them. Bone survey conducted 12 to 18 days after inoculation revealed a significant (P less than 0.01) reduction in trabecular bone mass of scanned vertebrae in comparison with the weight-matched untreated controls. It is concluded that the in vivo quantitative assessment of bone density illustrated in this report represents a sensitive and useful tool for the long-term survey of naturally occurring or experimentally induced bone changes. Scanning of the same part of the skeleton can be repeated, thereby avoiding sacrifice of the animal and time-consuming preparation of post-mortem material.

Climate spectrum estimation in the presence of timescale errors

We introduce an algorithm (called REDFITmc2) for spectrum estimation in the presence of timescale errors. It is based on the Lomb-Scargle periodogram for unevenly spaced time series, in combination with the Welch's Overlapped Segment Averaging procedure, bootstrap bias correction and persistence estimation. The timescale errors are modelled parametrically and included in the simulations for determining (1) the upper levels of the spectrum of the red-noise AR(1) alternative and (2) the uncertainty of the frequency of a spectral peak. Application of REDFITmc2 to ice core and stalagmite records of palaeoclimate allowed a more realistic evaluation of spectral peaks than when ignoring this source of uncertainty. The results support qualitatively the intuition that stronger effects on the spectrum estimate (decreased detectability and increased frequency uncertainty) occur for higher frequencies. The surplus information brought by algorithm REDFITmc2 is that those effects are quantified. Regarding timescale construction, not only the fixpoints, dating errors and the functional form of the age-depth model play a role. Also the joint distribution of all time points (serial correlation, stratigraphic order) determines spectrum estimation.