Od karcinoida do biološki i prognostički značajne klasifikacije neuroendokrinih tumora probavnog trakta i gušterače

Although well established in the medical terminology, the term carcinoid is no longer adequate to cover the entire morphological and biological spectrum of neoplasms of the disseminated neuroendocrine cell system. Instead of "carcinoid" the WHO classification published in 2000 therefore uses the general terms "neuroendocrine tumor" and "neuroendocrine carcinoma". In this review we describe a classification of gastroenteropancreatic neuroendocrine tumors based on the WHO criteria. We also classify and comment on the most important tumor entities. On the basis of localization and of various morphological and biological criteria we distinguish between benign neuroendocrine tumors, tumors with uncertain malignant potential, and tumors showing low grade and high grade malignancy.Iako je dobro poznat u medicinskoj terminologiji, pojam karcinoid nije više dovoljan da bi pokrio eitav morfološki i biološki spektar neoplazma diseminiranog neuroendokrinog staničnog sustava. Stoga se u klasifikaciji što ju je 2000. godine objavila SZO umjesto "karcinoidi" rabe opći pojmovi "neuroendokrini tumor" i "neuroendokrini karcinom". U ovom preglednom članku opisujemo klasifikaciju gastroenteropankreatičnih neuroendokrinih tumora, koja se temelji na kriterijima SZO. Također dajemo klasifikaciju i primjerene napomene o najvažnijim tumorskim entitetima. Na osnovi lokalizacije i različitih morfoloških i bioloških kriterija razlikujemo benigne neuroendokrine tumore, tumore neodređenog malignog potencijala, te tumore koji pokazuju nizak i visok stupanj malignosti

Robust automated detection of microstructural white matter degeneration in Alzheimer’s disease using machine learning classification of multicenter DTI data

Diffusion tensor imaging (DTI) based assessment of white matter fiber tract integrity can support the diagnosis of Alzheimer’s disease (AD). The use of DTI as a biomarker, however, depends on its applicability in a multicenter setting accounting for effects of different MRI scanners. We applied multivariate machine learning (ML) to a large multicenter sample from the recently created framework of the European DTI study on Dementia (EDSD). We hypothesized that ML approaches may amend effects of multicenter acquisition. We included a sample of 137 patients with clinically probable AD (MMSE 20.6±5.3) and 143 healthy elderly controls, scanned in nine different scanners. For diagnostic classification we used the DTI indices fractional anisotropy (FA) and mean diffusivity (MD) and, for comparison, gray matter and white matter density maps from anatomical MRI. Data were classified using a Support Vector Machine (SVM) and a Naïve Bayes (NB) classifier. We used two cross-validation approaches, (i) test and training samples randomly drawn from the entire data set (pooled cross-validation) and (ii) data from each scanner as test set, and the data from the remaining scanners as training set (scanner-specific cross-validation). In the pooled cross-validation, SVM achieved an accuracy of 80% for FA and 83% for MD. Accuracies for NB were significantly lower, ranging between 68% and 75%. Removing variance components arising from scanners using principal component analysis did not significantly change the classification results for both classifiers. For the scanner-specific cross-validation, the classification accuracy was reduced for both SVM and NB. After mean correction, classification accuracy reached a level comparable to the results obtained from the pooled cross-validation. Our findings support the notion that machine learning classification allows robust classification of DTI data sets arising from multiple scanners, even if a new data set comes from a scanner that was not part of the training sample

Host pathogen interactions in relation to management of light leaf spot disease (caused by Pyrenopeziza brassicae) on Brassica species

Light leaf spot, caused by Pyrenopeziza brassicae, is currently the most damaging disease problem in oilseed rape in the UK. According to recent survey data, the severity of epidemics has increased progressively across the UK, with current yield losses of up to £160M per annum in England and more severe epidemics in Scotland. Light leaf spot is a polycyclic disease with primary inoculum consisting of air-borne ascospores produced on diseased debris from the previous cropping season. Splash-dispersed conidia produced on diseased leaves are the main component of the secondary inoculum. P. brassicae is also able to infect and cause considerable yield losses on vegetable brassicas, especially Brussels sprouts. There may be spread of light leaf spot among different brassica species. Since they have a wide host range, Pyrenopeziza brassicae populations are likely to have considerable genetic diversity and there is evidence suggesting population variations between different regions, which need further study. Available disease-management tools are not sufficient to provide adequate control of the disease. There is a need to identify new sources of resistance, which can be integrated with fungicide applications to achieve sustainable management of light leaf spot. Several major resistance genes and quantitative trait loci have been identified in previous studies, but rapid improvements in the understanding of molecular mechanisms underpinning B. napus – P. brassicae interactions can be expected through exploitation of novel genetic and genomic information for brassicas and extracellular fungal pathogens.Peer reviewe

Harmonizing neuropsychological assessment for mild neurocognitive disorders in Europe

INTRODUCTION Harmonized neuropsychological assessment for neurocognitive disorders, an international priority for valid and reliable diagnostic procedures, has been achieved only in specific countries or research contexts. METHODS To harmonize the assessment of mild cognitive impairment in Europe, a workshop (Geneva, May 2018) convened stakeholders, methodologists, academic, and non-academic clinicians and experts from European, US, and Australian harmonization initiatives. RESULTS With formal presentations and thematic working-groups we defined a standard battery consistent with the U.S. Uniform DataSet, version 3, and homogeneous methodology to obtain consistent normative data across tests and languages. Adaptations consist of including two tests specific to typical Alzheimer's disease and behavioral variant frontotemporal dementia. The methodology for harmonized normative data includes consensus definition of cognitively normal controls, classification of confounding factors (age, sex, and education), and calculation of minimum sample sizes. DISCUSSION This expert consensus allows harmonizing the diagnosis of neurocognitive disorders across European countries and possibly beyond

A survey of the state-of-the-art techniques for cognitive impairment detection in the elderly

With a growing number of elderly people in the UK, more and more of them suffer from various kinds of cognitive impairment. Cognitive impairment can be divided into different stages such as mild cognitive impairment (MCI) and severe cognitive impairment like dementia. Its early detection can be of great importance. However, it is challenging to detect cognitive impairment in the early stage with high accuracy and low cost, when most of the symptoms may not be fully expressed. This survey paper mainly reviews the state of the art techniques for the early detection of cognitive impairment and compares their advantages and weaknesses. In order to build an effective and low-cost automatic system for detecting and monitoring the cognitive impairment for a wide range of elderly people, the applications of computer vision techniques for the early detection of cognitive impairment by monitoring facial expressions, body movements and eye movements are highlighted in this paper. In additional to technique review, the main research challenges for the early detection of cognitive impairment with high accuracy and low cost are analysed in depth. Through carefully comparing and contrasting the currently popular techniques for their advantages and weaknesses, some important research directions are particularly pointed out and highlighted from the viewpoints of the authors alone

Trauma management incorporating focused assessment with computed tomography in trauma (FACTT) - potential effect on survival

Background Immediate recognition of life-threatening conditions and injuries is the key to trauma management. To date, the impact of focused assessment with computed tomography in trauma (FACTT) has not been formally assessed. We aimed to find out whether the concept of using FACTT during primary trauma survey has a negative or positive effect on survival. Methods In a retrospective, multicentre study, we compared our time management and probability of survival (Ps) in major trauma patients who received FACTT during trauma resuscitation with the trauma registry of the German Trauma Society (DGU). FACTT is defined as whole-body computed tomography (WBCT) during primary trauma survey. We determined the probability of survival according to the Trauma and Injury Severity Score (TRISS), the Revised Injury Severity Classification score (RISC) and the standardized mortality ratio (SMR). Results We analysed 4.817 patients from the DGU database from 2002 until 2004, 160 (3.3%) were from our trauma centre at the Ludwig-Maximilians-University (LMU) and 4.657 (96.7%) from the DGU group. 73.2% were male with a mean age of 42.5 years, a mean ISS of 29.8. 96.2% had suffered from blunt trauma. Time from admission to FAST (focused assessment with sonography for trauma)(4.3 vs. 8.7 min), chest x-ray (8.1 vs. 16.0 min) and whole-body CT (20.7 vs. 36.6 min) was shorter at the LMU compared to the other trauma centres (p < 0.001). SMR calculated by TRISS was 0.74 (CI95% 0.40-1.08) for the LMU (p = 0.24) and 0.92 (CI95% 0.84-1.01) for the DGU group (p = 0.10). RISC methodology revealed a SMR of 0.69 (95%CI 0.47-0.92) for the LMU (p = 0.043) and 1.00 (95%CI 0.94-1.06) for the DGU group (p = 0.88). Conclusion Trauma management incorporating FACTT enhances a rapid response to life-threatening problems and enables a comprehensive assessment of the severity of each relevant injury. Due to its speed and accuracy, FACTT during primary trauma survey supports rapid decision-making and may increase survival

Amyloid in the islets of Langerhans: Thoughts and some historical aspects

Deposition of amyloid, derived from the polypeptide hormone islet amyloid polypeptide (IAPP; ‘amylin’) is the single most typical islet alteration in type 2 diabetes. Islet amyloid was described as hyalinization already in 1901, but not until 1986 was it understood that it is a polymerization product of a novel β-cell regulatory product. The subject of this focused review deals with the pathogenesis and importance of the islet amyloid itself, not with the biological effect of the polypeptide. Similar to the situation in Alzheimer's disease, it has been argued that the amyloid may not be of importance since there is no strict correlation between the degree of islet amyloid infiltration and the disease. However, it is hardly discussable that the amyloid is important in subjects where islets have been destroyed by pronounced islet amyloid deposits. Even when there is less islet amyloid the deposits are widely spread, and β-cells show ultrastructural signs of cell membrane destruction. It is suggested that type 2 diabetes is heterogeneous and that in one major subtype aggregation of IAPP into amyloid fibrils is determining the progressive loss of β-cells. Interestingly, development of islet amyloid may be an important event in the loss of β-cell function after islet transplantation into type 1 diabetic subjects