Diagnostic value of lipopolysaccharide-binding protein and procalcitonin for sepsis diagnosis in forensic pathology.

The aims of this study were twofold. The first was to investigate the diagnostic performance of two biochemical markers, procalcitonin (PCT) and lipopolysaccharide-binding protein (LBP), considering each individually and then combined, for the postmortem diagnosis of sepsis. We also tested the usefulness of pericardial fluid for postmortem LBP determination. Two study groups were formed, a sepsis-related fatalities group of 12 cases and a control group of 30 cases. Postmortem native CT scans, autopsy, histology, neuropathology, and toxicology as well as other postmortem biochemical investigations were performed in all cases. Microbiological investigations were also carried out in the septic group. Postmortem serum PCT and LBP levels differed between the two groups. Both biomarkers, individually considered, allowed septic states to be diagnosed, whereas increases in both postmortem serum PCT and LBP levels were only observed in cases of sepsis. Similarly, normal PCT and LBP values in postmortem serum were identified only in non-septic cases. Pericardial fluid LBP levels do not correlate with the presence of underlying septic states. No relationship was observed between postmortem serum and pericardial fluid LBP levels in either septic or non-septic groups, or between pericardial fluid PCT and LBP levels.

Turnaround across diverse global supply chains using shared metrics and change methodology: The Case of Amer Sports Corporation

Purpose - The purpose of this paper is to document the outcome of a global three-year long supply chain improvement initiative at a multi-national producer of branded sporting goods that is transforming from a holding structure to an integrated company. The case company is comprised of seven internationally well-known sport brands, which form a diverse set of independent sub-cases, on which the same supply chain metrics and change project approach was applied to improve supply chain performance. Design/methodology/approach - By using in-depth case study and statistical analysis the paper analyzes across the brands how supply chain complexity (SKU count), supply chain type (make or buy) and seasonality affect completeness and punctuality of deliveries, and inventory as the change project progresses. Findings - Results show that reduction in supply chain complexity improves delivery performance, but has no impact on inventory. Supply chain type has no impact on service level, but brands with in-house production are better in improving inventory than those with outsourced production. Non-seasonal business units improve service faster than seasonal ones, yet there is no impact on inventory. Research limitations/implications - The longitudinal data used for the analysis is biased with the general business trend, yet the rich data from different cases and three-years of data collection enables generalizations to a certain level. Practical implications - The in-depth case study serves as an example for other companies on how to initiate a supply chain improvement project across business units with tangible results. Originality/value - The seven sub-cases with their different characteristics on which the same improvement initiative was applied sets a unique ground for longitudinal analysis to study supply chain complexity, type and seasonality.

Assessing the value of CAN-gene mutations using MALDI-TOF MS.

PURPOSE: To identify cancer-linked genes, Sjöblom et al. and Wood et al. performed a genome-wide mutation screening in human breast and colorectal cancers. 140 CAN-genes were found in breast cancer, which in turn contained overall 334 mutations. These mutations could prove useful for diagnostic and therapeutic purposes. METHODS: We used a MALDI-TOF MS 40-plex assay for testing 40 loci within 21 high-ranking breast cancer CAN-genes. To confirm mutations, we performed single-plex assays and sequencing. RESULTS: In general, the mutation rate of the analyzed loci in our sample cohort was very low. No mutation from the 40 loci analyzed could be found in the 6 cell lines. In tissue samples, a single breast cancer tissue sample showed heterozygosity at locus c.5834G>A within the ZFYVE26 gene (Zinc finger FYVE domain-containing gene 26). CONCLUSIONS: Sjöblom et al./Wood et al. already showed that the vast majority of CAN-genes are mutated at very low frequency. Due to the fact that we only found one mutation in our cohort, we therefore assume that at the selected loci, mutations might be low-frequency events and therefore, more rarely detectable. However, further evaluation of the CAN-gene mutations in larger cohorts should be the aim of further studies.

Activity in inferior parietal and medial prefrontal cortex signals the accumulation of evidence in a probability learning task.

In an uncertain environment, probabilities are key to predicting future events and making adaptive choices. However, little is known about how humans learn such probabilities and where and how they are encoded in the brain, especially when they concern more than two outcomes. During functional magnetic resonance imaging (fMRI), young adults learned the probabilities of uncertain stimuli through repetitive sampling. Stimuli represented payoffs and participants had to predict their occurrence to maximize their earnings. Choices indicated loss and risk aversion but unbiased estimation of probabilities. BOLD response in medial prefrontal cortex and angular gyri increased linearly with the probability of the currently observed stimulus, untainted by its value. Connectivity analyses during rest and task revealed that these regions belonged to the default mode network. The activation of past outcomes in memory is evoked as a possible mechanism to explain the engagement of the default mode network in probability learning. A BOLD response relating to value was detected only at decision time, mainly in striatum. It is concluded that activity in inferior parietal and medial prefrontal cortex reflects the amount of evidence accumulated in favor of competing and uncertain outcomes.

Assessing multiple sclerosis activity: is the in vitro production of tumor necrosis factor-alpha, interleukins 2, 6, 4, and 10, and immunoglobulin G of value?

Tumor necrosis factor (TNF) alpha, interleukins (IL) 2, 4, 6, and 10, and IgG oligoclonal bands (IgG OB) in vitro production was assessed, after whole-blood stimulation with lipopolysaccharide or concanavalin A, in 61 patients presenting with relapsing-remitting, relapsing-progressive, or chronic progressive multiple sclerosis. Multiple sclerosis patients were receiving no treatment or azathioprine (AZA), cyclosporin, cyclophosphamide, subcutaneous interferon (IFN) beta 1 a, or corticosteroids (CST). Statistical correlations significantly showed that: (a) AZA lowers TNF-alpha (P = 0.002) and increases IL-4 production (P = 0.0024), and IFN-beta 1 a increases TNF-alpha and decreases IL-4 levels; (b) CST has a negative effect on TNF-alpha, IL-6, and IL-4 synthesis; and (c) AZA, IFN-beta 1 a, and CST diminish IgG OB synthesis (P = 0.001). Although our study of the dynamics of TNF-alpha, IL-2, IL-4, IL-6, and IL-10 in vitro production generally found no statistically significant correlations (partly explained by the limited number of values in the various groups), IL-6 was shown to drop during the periods surrounding relapse (P = 0.05) in the absence of treatment, while TNF-alpha (P = 0.04) and IL-6 (P < 0.05) dropped before exacerbation in the presence of AZA. In vitro production of TNF-alpha was closely and positively correlated with that of IL-6, independently of clinical features. The enhanced production of IL-10 detected before or at relapse with AZA and IFN-beta 1 a (trends) may interfere with initiation of the immune reaction and with the development of new CNS lesions. Some discrepancies with previously published results stress the difficulties in studying the state of stimulation of different populations of leukocytes by using a variety of in vitro stimuli and in establishing a correlation between mRNA studies and the amount of final or active protein produced.

Is (1→3)-β-D-glucan the missing link from bedside assessment to pre-emptive therapy of invasive candidiasis?

ABSTRACT: Invasive candidiasis is a frequent life-threatening complication in critically ill patients. Early diagnosis followed by prompt treatment aimed at improving outcome by minimizing unnecessary antifungal use remains a major challenge in the ICU setting. Timely patient selection thus plays a key role for clinically efficient and cost-effective management. Approaches combining clinical risk factors and Candida colonization data have improved our ability to identify such patients early. While the negative predictive value of scores and predicting rules is up to 95 to 99%, the positive predictive value is much lower, ranging between 10 and 60%. Accordingly, if a positive score or rule is used to guide the start of antifungal therapy, many patients may be treated unnecessarily. Candida biomarkers display higher positive predictive values; however, they lack sensitivity and are thus not able to identify all cases of invasive candidiasis. The (1→3)-β-D-glucan (BG) assay, a panfungal antigen test, is recommended as a complementary tool for the diagnosis of invasive mycoses in high-risk hemato-oncological patients. Its role in the more heterogeneous ICU population remains to be defined. More efficient clinical selection strategies combined with performant laboratory tools are needed in order to treat the right patients at the right time by keeping costs of screening and therapy as low as possible. The new approach proposed by Posteraro and colleagues in the previous issue of Critical Care meets these requirements. A single positive BG value in medical patients admitted to the ICU with sepsis and expected to stay for more than 5 days preceded the documentation of candidemia by 1 to 3 days with an unprecedented diagnostic accuracy. Applying this one-point fungal screening on a selected subset of ICU patients with an estimated 15 to 20% risk of developing candidemia is an appealing and potentially cost-effective approach. If confirmed by multicenter investigations, and extended to surgical patients at high risk of invasive candidiasis after abdominal surgery, this Bayesian-based risk stratification approach aimed at maximizing clinical efficiency by minimizing health care resource utilization may substantially simplify the management of critically ill patients at risk of invasive candidiasis.

ARCHITECTING USER-CENTRIC PRIVACY-AS-A-SET-OF-SERVICES: DIGITAL IDENTITY RELATED PRIVACY FRAMEWORK

AbstractDigitalization gives to the Internet the power by allowing several virtual representations of reality, including that of identity. We leave an increasingly digital footprint in cyberspace and this situation puts our identity at high risks. Privacy is a right and fundamental social value that could play a key role as a medium to secure digital identities. Identity functionality is increasingly delivered as sets of services, rather than monolithic applications. So, an identity layer in which identity and privacy management services are loosely coupled, publicly hosted and available to on-demand calls could be more realistic and an acceptable situation. Identity and privacy should be interoperable and distributed through the adoption of service-orientation and implementation based on open standards (technical interoperability). Ihe objective of this project is to provide a way to implement interoperable user-centric digital identity-related privacy to respond to the need of distributed nature of federated identity systems. It is recognized that technical initiatives, emerging standards and protocols are not enough to guarantee resolution for the concerns surrounding a multi-facets and complex issue of identity and privacy. For this reason they should be apprehended within a global perspective through an integrated and a multidisciplinary approach. The approach dictates that privacy law, policies, regulations and technologies are to be crafted together from the start, rather than attaching it to digital identity after the fact. Thus, we draw Digital Identity-Related Privacy (DigldeRP) requirements from global, domestic and business-specific privacy policies. The requirements take shape of business interoperability. We suggest a layered implementation framework (DigldeRP framework) in accordance to model-driven architecture (MDA) approach that would help organizations' security team to turn business interoperability into technical interoperability in the form of a set of services that could accommodate Service-Oriented Architecture (SOA): Privacy-as-a-set-of- services (PaaSS) system. DigldeRP Framework will serve as a basis for vital understanding between business management and technical managers on digital identity related privacy initiatives. The layered DigldeRP framework presents five practical layers as an ordered sequence as a basis of DigldeRP project roadmap, however, in practice, there is an iterative process to assure that each layer supports effectively and enforces requirements of the adjacent ones. Each layer is composed by a set of blocks, which determine a roadmap that security team could follow to successfully implement PaaSS. Several blocks' descriptions are based on OMG SoaML modeling language and BPMN processes description. We identified, designed and implemented seven services that form PaaSS and described their consumption. PaaSS Java QEE project), WSDL, and XSD codes are given and explained.

Missing value imputation in longitudinal measures of alcohol consumption

Attrition in longitudinal studies can lead to biased results. The study is motivated by the unexpected observation that alcohol consumption decreased despite increased availability, which may be due to sample attrition of heavy drinkers. Several imputation methods have been proposed, but rarely compared in longitudinal studies of alcohol consumption. The imputation of consumption level measurements is computationally particularly challenging due to alcohol consumption being a semi-continuous variable (dichotomous drinking status and continuous volume among drinkers), and the non-normality of data in the continuous part. Data come from a longitudinal study in Denmark with four waves (2003-2006) and 1771 individuals at baseline. Five techniques for missing data are compared: Last value carried forward (LVCF) was used as a single, and Hotdeck, Heckman modelling, multivariate imputation by chained equations (MICE), and a Bayesian approach as multiple imputation methods. Predictive mean matching was used to account for non-normality, where instead of imputing regression estimates, "real" observed values from similar cases are imputed. Methods were also compared by means of a simulated dataset. The simulation showed that the Bayesian approach yielded the most unbiased estimates for imputation. The finding of no increase in consumption levels despite a higher availability remained unaltered. Copyright (C) 2011 John Wiley & Sons, Ltd.

Nicotinamide Phosphoribosyltransferase (NAMPT) Inhibitors as Therapeutics: Rationales, Controversies, Clinical Experience.

Nicotinamide adenine dinucleotide (NAD+) biosynthesis from nicotinamide is used by mammalian cells to replenish their NAD+ stores and to avoid unwanted nicotinamide accumulation. Pharmacological inhibition of nicotinamide phosphoribosyltransferase (NAMPT), the key enzyme in this biosynthetic pathway, almost invariably leads to intracellular NAD+ depletion and, when protracted, to ATP shortage and cell demise. Cancer cells and activated immune cells express high levels of NAMPT and are highly susceptible to NAMPT inhibitors, as shown by the activity of these agents in models of malignant and inflammatory disorders. As the spectrum of conditions which could benefit from pharmacological NAMPT inhibition becomes broader, the mechanisms accounting for their activity are also eventually becoming apparent, including the induction of autophagy and the impairment of Ca(2+) - and NF-κB-dependent signaling. Here, we discuss the rationales for exploiting NAMPT inhibitors in cancer and inflammatory diseases and provide an overview of the preclinical and clinical studies in which these agents have been evaluated.

Biochemical analysis of female mice urine with reference to endocrine function: a key tool for estrus detection.

Species-specific chemical signals released through urine, sweat, saliva and feces are involved in communication between animals. Urinary biochemical constituents along with pheromones may contribute to variation across reproductive cycles and facilitate to estrus detection. Hence, the present study was designed to analyze such biochemical profiles, such as proteins, carbohydrates, lipids, fatty acids, in response with steroid hormones such as estradiol and progesterone. The experimental groups were normal, prepubertal, ovariectomized, and ovariectomized with estrogentreated female mice. In normal mice, the protein and lipid concentrations in urine were significantly higher in proestrus and estrus phases and the quantity of fatty acids was also comparatively higher in estrus. Furthermore, certain fatty acids, namely tridecanoic, palmitic and oleic acids, were present during proestrus and estrus phases, but were exclusively absent in ovariectomized mice. However, the carbohydrate level was equally maintained throughout the four phases of estrous cycle. For successful communication, higher concentrations of protein and specific fatty acids in estrus are directly involved. The significant increase in estradiol at estrus and progesterone at metestrus seems to be of greater importance in the expression pattern of biochemical constituents and may play a notable role in estrous cycle regulation. Thus, we conclude that the variations observed in the concentration of the biochemical constituents depend on the phase of the reproductive cycle as well as hormonal status of animals. The appearance of protein and specific fatty acids during estrus phase raises the possibility to use these as a urinary indicators for estrus detection.

Will climate change drive alien invasive plants into areas of high protection value? An improved model-based regional assessment to prioritise the management of invasions.

Species distribution models (SDMs) studies suggest that, without control measures, the distribution of many alien invasive plant species (AIS) will increase under climate and land-use changes. Due to limited resources and large areas colonised by invaders, management and monitoring resources must be prioritised. Choices depend on the conservation value of the invaded areas and can be guided by SDM predictions. Here, we use a hierarchical SDM framework, complemented by connectivity analysis of AIS distributions, to evaluate current and future conflicts between AIS and high conservation value areas. We illustrate the framework with three Australian wattle (Acacia) species and patterns of conservation value in Northern Portugal. Results show that protected areas will likely suffer higher pressure from all three Acacia species under future climatic conditions. Due to this higher predicted conflict in protected areas, management might be prioritised for Acacia dealbata and Acacia melanoxylon. Connectivity of AIS suitable areas inside protected areas is currently lower than across the full study area, but this would change under future environmental conditions. Coupled SDM and connectivity analysis can support resource prioritisation for anticipation and monitoring of AIS impacts. However, further tests of this framework over a wide range of regions and organisms are still required before wide application.