Evaluation of Retinal Blood Flow in Patients with Monoclonal Gammopathy Using OCT Angiography

Background: Monoclonal gammopathy (MG) is characterized by monoclonal protein overproduction, potentially leading to the development of hyperviscosity syndrome. Objective: To assess retinal circulation using optical coherence tomography angiography (OCTA) parameters in patients with monoclonal gammopathy. Methods: OCTA measurements were performed using the Optovue AngioVue system by examining 44 eyes of 27 patients with MG and 62 eyes of 36 control subjects. Superficial and deep retinal capillary vessel density (VD SVP and DVP) in the whole 3 × 3 mm macular and parafoveal area, foveal avascular zone (FAZ) area, and central retinal thickness (CRT) were measured using the AngioAnalytics software. The OCTA parameters were evaluated in both groups using a multivariate regression model, after controlling for the effect of imaging quality (SQ). Results: There was no significant difference in age between the subjects with monoclonal gammopathy and the controls (63.59 ± 9.33 vs. 58.01 ± 11.46 years; p > 0.05). Taking into account the effect of image quality, the VD SVP was significantly lower in the MG group compared to the control group (44.54 ± 3.22% vs. 46.62 ± 2.84%; p < 0.05). No significant differences were found between the two groups regarding the other OCTA parameters (p > 0.05). Conclusions: A decreased superficial retinal capillary vessel density measured using OCTA in patients with MG suggests a slow blood flow, reduced capillary circulation, and consequent tissue hypoperfusion. An evaluation of retinal circulation using OCTA in cases of monoclonal gammopathy may be a sensitive method for the non-invasive detection and follow-up of early microcirculatory dysfunction caused by increased viscosity

Effect of dietary supplementation of spirulina (arthrospira platensis) and thyme (thymus vulgaris) on serum biochemistry, immune response and antioxidant status of rabbits

Growing rabbits’ (42 rabbits/group, 3 rabbits/cage, 14 cages/treatment) diet was supplemented with 5% Spirulina (Arthrospira platensis) and 3% thyme (Thymus vulgaris L.) powder single (S or T) and in combination (ST) between 35 and 77 days of age. On day 0 (weaning at 35 days of age) 14 rabbits were vaccinated with 100 µg/animal ovalbumin to provoke immune response. Blood samples were taken on days 0, 14, 28 and 42 of the experimental period. Sampling dates significantly influenced total protein, albumin, glucose, cholesterol, urea, creatinine concentration and enzyme (AST, ALT, GGT) activities, with a significant age × diet interaction in the case of TP and CREA. There was a significant increase in ALT (+45 and 74%) and GGT (+87 and 102%) activity after immunisation. While Spirulina and thyme significantly ameliorated the rise in AST activity, their effect was inefficient in the case of GGT. Spirulina, both single and in combination showed a tendency in higher IgG level as compared to control (P<0.05). No significant effect of sampling date or treatment on phagocytic activity or secretory IgA was demonstrable (P>0.05). Higher MDA concentration was measured in the red blood cells of S, T and ST animals, while no other significant diet effect on the antioxidant parameters was detected, however, significant sampling date × diet interaction was found in the case of GPx activity. Plasma GGT (increase by 19–66%) was inversely associated with GSH (decrease by 66–113%) between days 0 to 42 of the experimental period (r=–0.57, P<0.05). It can be concluded that Spirulina supplementation alone resulted in higher IgG production, but none of the phytobiotics, at the dose used, affected significantly the antioxidant status of bloo

Challenges of machine learning model validation using correlated behaviour data: Evaluation of cross-validation strategies and accuracy measures.

Automated monitoring of the movements and behaviour of animals is a valuable research tool. Recently, machine learning tools were applied to many species to classify units of behaviour. For the monitoring of wild species, collecting enough data for training models might be problematic, thus we examine how machine learning models trained on one species can be applied to another closely related species with similar behavioural conformation. We contrast two ways to calculate accuracies, termed here as overall and threshold accuracy, because the field has yet to define solid standards for reporting and measuring classification performances. We measure 21 dogs and 7 wolves, and find that overall accuracies are between 51 and 60% for classifying 8 behaviours (lay, sit, stand, walk, trot, run, eat, drink) when training and testing data are from the same species and between 41 and 51% when training and testing is cross-species. We show that using data from dogs to predict the behaviour of wolves is feasible. We also show that optimising the model for overall accuracy leads to similar overall and threshold accuracies, while optimizing for threshold accuracy leads to threshold accuracies well above 80%, but yielding very low overall accuracies, often below the chance level. Moreover, we show that the most common method for dividing the data between training and testing data (random selection of test data) overestimates the accuracy of models when applied to data of new specimens. Consequently, we argue that for the most common goals of animal behaviour recognition overall accuracy should be the preferred metric. Considering, that often the goal is to collect movement data without other methods of observation, we argue that training data and testing data should be divided by individual and not randomly

A fenntartható bioüzemanyag-termelés lehetőségei Magyarországon a BIKE projekt eredményei alapján

Az Európai Unió stratégiai célként kezeli a megújuló energiatermelés növelését, amelynek jelentőségét a klímapolitikai célkitűzések mellett az orosz–ukrán háború kirobbanása miatt kialakuló energiapiaci válság is tovább erősíti. A növényi alapú bioüzemanyagok esetében az EU felismerte, hogy az energetikai célú növényi biomassza termelésének fokozódása veszélyeztetheti az élelmezésbiztonságot és növelheti az üvegházhatású gázok kibocsátását. E kockázatok mérséklése érdekében az Unió törekszik a megfelelő szabályozási környezet kialakítására, és támogatja a gyakorlati megoldásokat kereső kutatási projekteket. A bioüzemanyag alapanyag iránti többletigény kielégítésének egyik módja az alacsony közvetett földhasználat-változás kockázattal járó biomassza-alapanyag termelés lehet. A BIKE projektben elvégzett kutatások középpontjában egyrészt az energetikai célú növénytermesztés potenciális célterületeinek lehatárolása (beleértve a feldolgozó kapacitás vizsgálatát), másrészt a termesztésbe vonható növények köre és a hozamnövelés lehetőségei álltak. Az EU a RED II irányelvben és annak végrehajtási rendeletében a fejlett bioüzemanyagok növekvő arányú felhasználását írja elő a közlekedésben, illetve a hagyományos bioüzemanyagok esetén a közvetett földhasználat-változás szempontjából alacsony kockázatúnak minősített alapanyagok felhasználását részesíti előnyben. Továbbá a termelők számára meghatározza azokat a termelési és egyéb gazdaságossági feltételeket, amelyek biztosítják az alacsony kockázatú és fenntartható alapanyag-termelést. Az Unió piaci beavatkozási logikája szerint e szabályozások révén a piaci szereplők hajlandóak lesznek „piaci prémiumot” fizetni a gazdálkodóknak azért, hogy az előírásoknak megfelelő mennyiségű és minőségű bioüzemanyag-alapanyagot fenntartható módon állítsák elő. Az EU stratégiai céljainak elérése alapvetően azon múlik majd, hogy miként lehet a most kialakuló szabályozási környezetet a gazdálkodói gyakorlatba hatékonyan átültetni