Monogenic diabetes secondary to congenital lipodystrophy in a 14-year-old Yemeni girl

A 14-year-old female from Yemen presented with intense abdominal pain and headache. She was born at term to distant cousins, developmentally delayed and significantly dysmorphic. Four years ago, she was diagnosed with diabetes mellitus and undiagnosed hepatic, cardiac, genetic, neurologic, endocrine, musculoskeletal, and gastrointestinal disorders. No therapy was prescribed. Admission laboratory data showed blood glucose = 391 mg/dl, hemoglobin A1c= 12.2%, C-peptide = 3.5 ng/ml, insulin = 6.8 uIU/ml, triglyceride =385 mg/dl, and serum leptin <0.5 ng/ml, (1.1-27.5). Chromosome analysis (46, XX) was normal and serology for Glutamic acid Decarboxylase (GAD), hepatitis and HIV were negative. Clinical examination and laboratory data suggested congenital generalized lipodystrophy (CGL, type BSCL-2). This case illustrates that CGL should be in the differential diagnosis for non-obese patients with diabetes and insulin resistance.     

Comparison of microarray-based RNA expression with ELISA-based protein determination of HER2, uPA and PAI-1 in tumour tissue of patients with breast cancer and relation to outcome

Purpose  

Prognostic and predictive markers in breast cancer are currently determined by single analysis of protein amounts. If RNA-based multi-gene analyses enter clinical practice, simultaneous determination of currently established markers like human epidermal growth factor receptor 2 (HER2), urokinase plasminogen activator (uPA) and its inhibitor (PAI-1) would represent an elegant simplification. To investigate the correlation between RNA and protein levels, we assessed HER2, uPA and PAI-1 in patients with breast cancer. In addition, we evaluated the influence of these factors on patient outcome.     

Posteriores reversibles Enzephalopathiesyndrom (PRES)

Background

Posterior reversible encephalopathy syndrome (PRES) is an acute neurological disease. Although there are some case reports of patients with a poor clinical outcome, studies about PRES and intensive care medicine are rare.

Patients and methods

The medical records of our department were screened for the diagnosis of PRES. Data of 26 patients were analyzed retrospectively.

Results

Of the 26 PRES patients, 65.4% were treated in the intensive care unit (n=13) or stroke unit (n=4) for a mean duration of 3.9 days (range: 1–9 days). During admission, the correct diagnose was suspected for only 1 patient. Generalized seizures occurred in 88.5%. Only 1 patient needed artificial ventilation (>12 h).

Conclusion

Patients with PRES are frequently treated in the intensive care unit/stroke unit because of the clinical occurrence of the syndrome as a severe neurological disease. On the other hand, there are many life-threatening differential diagnoses. Epileptic seizures are the most frequent symptoms. Especially the combination of disturbed vision and epileptic seizures make the diagnosis of PRES more likely.     

An affective computing approach to physiological emotion specificity: toward subject-independent and stimulus-independent classification of film-induced emotions

The hypothesis of physiological emotion specificity has been tested using pattern classification analysis (PCA). To address limitations of prior research using PCA, we studied effects of feature selection (sequential forward selection, sequential backward selection), classifier type (linear and quadratic discriminant analysis, neural networks, k-nearest neighbors method), and cross-validation method (subject- and stimulus-(in)dependence). Analyses were run on a data set of 34 participants watching two sets of three 10-min film clips (fearful, sad, neutral) while autonomic, respiratory, and facial muscle activity were assessed. Results demonstrate that the three states can be classified with high accuracy by most classifiers, with the sparsest model having only five features, even for the most difficult task of identifying the emotion of an unknown subject in an unknown situation (77.5%). Implications for choosing PCA parameters are discussed.