Alcoholic steatohepatitis

Severe alcoholic steatohepatitis has a poor prognosis and is characterized by jaundice and signs of liver failure. Its incidence is unknown, but prevalence is around 20% in cohorts of alcoholics undergoing liver biopsy. Diagnosis is established with elevated liver transaminases, neutrophil counts, serum bilirubin, and impaired coagulation and a history of excessive alcohol consumption, and exclusion of other etiologies. Histology is helpful but not mandatory. Prognostic scores include the Maddrey's discriminant function, the model of end-stage liver disease, and the Glasgow Alcoholic Hepatitis Score. Pathophysiology involves hepatic fat storage, increased hepatic uptake of gut-derived endotoxins triggering Kupffer cell activation and release of proinflammatory triggers, induction of cytochrome P4502E1 producing toxic acetaldehyde and reactive oxygen species, and ethanol-mediated hyperhomocysteinemia causing endoplasmic reticulum stress. Treatment includes abstinence, enteral nutrition, corticosteroids, and possibly pentoxifylline. A debate is ongoing whether certain patients with severe alcoholic steatohepatitis could be eligible for liver transplantation.

Sex determination from os sacrum by postmortem CT

Sex determination in forensic practice is performed mostly on sexually dimorphic bones, including pelvic bones such as the os sacrum. Postmortem CT scan provides an easy and fast method for depicting and measuring bone structures prior to elaborate autopsy preparations. To develop a simple and objective method for sex determination in postmortem CT, metric data were evaluated from CT images of the pelvic-associated os sacrum of 95 corpses (49 men and 46 women) from the Canton of Bern, Switzerland. Discriminant function analysis of the data showed that the best accuracy in determining sex was 76.8% and 78.9% with two different observers. It is concluded that measuring the os sacrumin postmortem CT for sex determination has moderate accuracy and should only be applied in combination with other methods.

Do Zebra Finch Parents Fail to Recognise Their Own Offspring?

Individual recognition systems require the sender to be individually distinctive and the receiver to be able to perceive differences between individuals and react accordingly. Many studies have demonstrated that acoustic signals of almost any species contain individualized information. However, fewer studies have tested experimentally if those signals are used for individual recognition by potential receivers. While laboratory studies using zebra finches have shown that fledglings recognize their parents by their “distance call”, mutual recognition using the same call type has not been demonstrated yet. In a laboratory study with zebra finches, we first quantified between-individual acoustic variation in distance calls of fledglings. In a second step, we tested recognition of fledgling calls by parents using playback experiments. With a discriminant function analysis, we show that individuals are highly distinctive and most measured parameters show very high potential to encode for individuality. The response pattern of zebra finch parents shows that they do react to calls of fledglings, however they do not distinguish between own and unfamiliar offspring, despite individual distinctiveness. This finding is interesting in light of the observation of a high percentage of misdirected feedings in our communal breeding aviaries. Our results demonstrate the importance of adopting a receiver's perspective and suggest that variation in fledgling contact calls might not be used in individual recognition of offspring.

Sampling-Design Effects on Properties of Species-Area Relationships - A Case Study from Estonian Dry Grassland Communities

Despite widespread use of species-area relationships (SARs), dispute remains over the most representative SAR model. Using data of small-scale SARs of Estonian dry grassland communities, we address three questions: (1) Which model describes these SARs best when known artifacts are excluded? (2) How do deviating sampling procedures (marginal instead of central position of the smaller plots in relation to the largest plot; single values instead of average values; randomly located subplots instead of nested subplots) influence the properties of the SARs? (3) Are those effects likely to bias the selection of the best model? Our general dataset consisted of 16 series of nested-plots (1 cm(2)-100 m(2), any-part system), each of which comprised five series of subplots located in the four corners and the centre of the 100-m(2) plot. Data for the three pairs of compared sampling designs were generated from this dataset by subsampling. Five function types (power, quadratic power, logarithmic, Michaelis-Menten, Lomolino) were fitted with non-linear regression. In some of the communities, we found extremely high species densities (including bryophytes and lichens), namely up to eight species in 1 cm(2) and up to 140 species in 100 m(2), which appear to be the highest documented values on these scales. For SARs constructed from nested-plot average-value data, the regular power function generally was the best model, closely followed by the quadratic power function, while the logarithmic and Michaelis-Menten functions performed poorly throughout. However, the relative fit of the latter two models increased significantly relative to the respective best model when the single-value or random-sampling method was applied, however, the power function normally remained far superior. These results confirm the hypothesis that both single-value and random-sampling approaches cause artifacts by increasing stochasticity in the data, which can lead to the selection of inappropriate models.