PADAPT 1.0 - the Pannonian Dataset of Plant Traits.

The existing plant trait databases' applicability is limited for studies dealing with the flora and vegetation of the eastern and central part of Europe and for large-scale comparisons across regions, mostly because their geographical data coverage is limited and they incorporate records from several different sources, often from regions with markedly different climatic conditions. These problems motivated the compilation of a regional dataset for the flora of the Pannonian region (Eastern Central Europe). PADAPT, the Pannonian Dataset of Plant Traits relies on regional data sources and collates data on 54 traits and attributes of the plant species of the Pannonian region. The current version covers approximately 90% of the species of the region and consists of 126,337 records on 2745 taxa. By including species of the eastern part of Europe not covered by other databases, PADAPT can facilitate studying the flora and vegetation of the eastern part of the continent. Although data coverage is far from complete, PADAPT meets the longstanding need for a regional database of the Pannonian flora.

New thousand-seed weight dataset for plant species of Central Europe.

One of the most important and most easily measurable physical characteristics of plant seeds is their weight, which influences and indicates crucial ecological processes. Seed weight affects spatial and temporal dispersibility, and can also influence seed predation and the germination, growth and survival of seedlings. Providing trait data for species missing from international databases is key to promote studies that advance our understanding of the functioning of plant communities and ecosystems, which is an essential issue in the face of the global climate change and biodiversity loss. Compared to species from Western and Northwestern Europe, those with an Eastern or Central European centre of distribution are underrepresented in most international trait databases. Therefore, the creation of specific trait databases is key to help regional studies. In this respect, it is important not only to collect fresh seeds for weight measurements, but also to measure and process data of seeds preserved in collections and make them available to the broader scientific community. In this data paper we provide seed weight data to fill in missing trait data of plant species of Central and Eastern Europe. Our dataset includes weight measurement for 281 taxa of the Central European flora including also some cultivated and exotic species. The seeds were collected between 1971 and 2021 mostly in Central Europe. One part of the measured seeds was collected in the last decade, the other part is from an older seed collection, but all seeds were measured recently. For each species, we collected a minimum of 3 × 100 intact seeds, if possible. The seeds were air-dried at room temperature (approximately 21 °C and 50% relative humidity) for at least two weeks and measured with an accuracy of 0.001 g using an analytical balance. The thousand-seed weights reported here were calculated based on the measured values. Our goal for the future is to incorporate the seed weight data reported here in a regional database (Pannonian Database of Plant Traits - PADAPT) that gathers plant traits and other plant characteristics for the Pannonian flora. The data presented here will facilitate trait-based analyses of the flora and vegetation of Central Europe.

New data of plant leaf traits from Central Europe.

Trait-based ecology is gaining ground nowadays on species-based ecology: the number of research and publication focusing on the ecological role of taxa instead of the species themselves increased significantly in the last two decades. One great advantage of this approach is that communities with different species composition due to great geographical distances (e.g., different continents) or different environmental conditions (e.g., loess, sand, and alkaline grasslands) become comparable. Obtaining trait values is, however, labour and time consuming even in the case of so-called soft traits. It is therefore reasonable and desirable for scientists to share their data as widely as possible. Demand for such data induced the publication of data papers and the establishment of databases, which support both theoretical ecological research and practical restoration ecological projects. Although several international databases (e.g., TRY, LEDA, CLO-PLA, BiolFLOR) are available nowadays, Central and Eastern European species are either missing or underrepresented in them. Consequently, measurement and publication of the traits of species typical in the above region is necessary. This paper presents leaf trait (leaf fresh and dry weight, leaf area, specific leaf area and leaf dry matter content) data for more than 1100 species of the Central European flora.

Dank or not? Analyzing and predicting the popularity of memes on Reddit.

Internet memes have become an increasingly pervasive form of contemporary social communication that attracted a lot of research interest recently. In this paper, we analyze the data of 129,326 memes collected from Reddit in the middle of March, 2020, when the most serious coronavirus restrictions were being introduced around the world. This article not only provides a looking glass into the thoughts of Internet users during the COVID-19 pandemic but we also perform a content-based predictive analysis of what makes a meme go viral. Using machine learning methods, we also study what incremental predictive power image related attributes have over textual attributes on meme popularity. We find that the success of a meme can be predicted based on its content alone moderately well, our best performing machine learning model predicts viral memes with AUC=0.68. We also find that both image related and textual attributes have significant incremental predictive power over each other.

Unsupervised feature recognition in single-molecule break junction data.

Single-molecule break junction measurements deliver a huge number of conductance vs. electrode separation traces. During such measurements, the target molecules may bind to the electrodes in different geometries, and the evolution and rupture of the single-molecule junction may also follow distinct trajectories. The unraveling of the various typical trace classes is a prerequisite to the proper physical interpretation of the data. Here we exploit the efficient feature recognition properties of neural networks to automatically find the relevant trace classes. To eliminate the need for manually labeled training data we apply a combined method, which automatically selects training traces according to the extreme values of principal component projections or some auxiliary measured quantities. Then the network captures the features of these characteristic traces and generalizes its inference to the entire dataset. The use of a simple neural network structure also enables a direct insight into the decision-making mechanism. We demonstrate that this combined machine learning method is efficient in the unsupervised recognition of unobvious, but highly relevant trace classes within low and room temperature gold-4,4' bipyridine-gold single-molecule break junction data.

The five-items memory screen-extended variant: A tool for assessing memory.

BACKGROUND AND PURPOSE: The detection of memory impairment is an important part of dementia screening. However, the scope of memory measures in current screening batteries is limited. There is a need for a short yet sensitive instrument for early detection of memory impairment that could serve as a complement to existing globally oriented screening tests, for example, Mini-Mental State Examination (MMSE). To that end, the current study investigates the sensitivity and psychometric properties of the memory screening instrument The Five-Items Memory Screen -Extended Variant (FIMS-XV). METHODS: Hundred and forty-five participants included in the Gothenburg Mild Cognitive Impairment Study-27 patients with subjective cognitive impairment (SCI), 73 with mild cognitive impairment (MCI), and 45 with mild dementia-underwent cognitive screening including the MMSE and FIMS-XV. Ninety participants also underwent extensive neuropsychological testing. RESULTS: The FIMS-XV showed high internal consistency and strong correlations with established neuropsychological memory tests. Both the FIMS-XVdelayed recall score and the FIMS-XV total score differentiated mild dementia patients from patients with SCI and MCI. CONCLUSIONS: The FIMS-XV shows promise as a sensitive tool for screening for memory impairment in all putative phases of dementia.

Density-Dependent Plant-Plant Interactions Triggered by Grazing.

Plant species performance in rangelands highly depends on the effect of grazing and also on the occurrence of unpalatable benefactor species that can act as biotic refuges protecting neighboring plants from herbivores. The balance between facilitation and competition may changes with the benefactor density. Despite the high number of studies on the role of biotic refuges, the density dependent effects of unpalatable herbaceous plants on the performance of other species, and on the habitat heterogeneity of rangelands are still unclear. Therefore, we performed a study to test the following hypotheses: (i) Performances of understory species follow a humped-back relationship along the density gradient of the unpalatable benefactor species. (ii) Small-scale heterogeneity of the vegetation decreases with increasing benefactor density. We studied meadow steppes with medium intensity cattle grazing in Hungary. We surveyed understory species' performance (number of flowering shoots and cover scores) along the density gradient of a common, native unpalatable species (Althaea officinalis). Our findings supported both hypotheses. We found unimodal relationship between the benefactor cover and both the flowering success and richness of understory species. Moreover, small-scale heterogeneity declined with increasing benefactor cover. In this study we detected a humped-back pattern of facilitation along the density gradient of an herbaceous benefactor in pastures. Indeed, this pattern was predictable based on such conceptual models like "consumer pressure-abiotic stress model," "humped-back model," "intermediate disturbance hypothesis," and "disturbance heterogeneity model"; but until now the validity of these relationships has not been demonstrated for herbaceous species. By the demonstration of this effect between herbaceous species we can better forecast the responses of grasslands to changes in management.

[Investigation of CNTF, COMT, DDR1, DISC1, DRD2, DRD3, and DTNBP1 candidate genes in schizophrenia: Results from the Hungarian SCHIZOBANK Consortium]. / CNTF, COMT, DDR1, DISC1, DRD2, DRD3 és DTNBP1 kandidáns gének vizsgálata szkizofréniában: eredmények a Magyar SCHIZOBANK Konzorcium vizsgálatából.

Schizophrenia is a chronic, debilitating psychiatric disorder characterized by heterogeneous clinical symptoms. Although the pathogenesis of this disorder is poorly understood, several lines of evidence support the role of both common and rare genetic variants in the etiology of schizophrenia. Common variants, single nucleotide polymorphisms can be investigated by candidate gene association studies or genome-wide association studies, while rare variants, single nucleotide variants are assessable by means of candidate gene resequencing or whole-exome and genome sequencing using next generation sequencing. In this study we investigated polymorphisms of 7 candidate genes in a Hungarian schizophrenia cohort. Candidate genes were chosen on the basis of previous results and biological plausibility. 390 patients were recruited in 5 centers in the framework of the Hungarian SCHIZOBANK Consortium, the schizophrenia sample was contrasted to 1069 healthy control individuals. In this sample SNPs of DDR1 and DRD2 genes demonstrated significant association with schizophrenia. The role of DDR1 and DRD2 genes in the etiology of schizophrenia warrant further investigation, based on their genomic localization and biological functions.

Neurocognitive changes in patients with schizophrenia during relapse and early remission

Background and Objectives: Several studies have demonstrated that patients with schizophrenia have impaired cognitive functioning. In the literature there have been controversial results about the cognitive deficits occurring in the different states of the illness. Furthermore, there have been relatively few studies to investigate the associations between neurocognitive deficits and clinical status over time. In order to follow the changes of neurocognitive subfunctions during relapse and early remission (clinically stable state), in the present study patients with schizophrenia were tested in the acute phase and in clinically stable state, and then the results were correlated with clinical symptoms. Methods: Forty-two patients diagnosed with schizophrenia based on diagnostic interviews by clinicians and 43 normal controls were studied. Neurocognitive skills were evaluated with six subtests of the Cambridge Neuropsychological Test Automated Battery(CANTAB). Among patients with schizophrenia, symptom severity was assessed with the Positive and Negative Syndrome Scale (PANSS). Results: Patients with schizophrenia performed significantly worse in all neurocognitive subtests compared to healthy controls at both relapse and clinically stable state. At follow-up these cognitive changes improved, however still marked dysfunctions were observed. The negative symptoms in the PANSS and CANTAB tests were negatively correlated with both results during relapse and clinically stable state. Conclusions: Cognitive impairment exists among patients with schizophrenia compared to healthy subjects during both relapse and early remission suggesting that these deficits might be permanent (AU)

Investigating the state-like and trait-like characters of social cognition in schizophrenia: a short term follow-up study.

BACKGROUND AND OBJECTIVES: Controversial findings exist in the literature regarding the state- and trait-like characters of social cognition in schizophrenia. In order to explore the relationship of social cognition with symptom severity in the present study, Theory of mind (ToM) and emotion recognition were tested in an acute phase and later in a clinically stable phase in patients. METHODS: ToM and emotion recognition abilities were examined by using the Reading the Mind in the Eyes Test (RMET) and the Ekman 60 Faces Test (FEEST) in 43 patients with schizophrenia and 41 healthy controls. Research diagnoses were based on SCID interviews. Symptom severity in patients was assessed by the Positive and Negative Syndrome Scale (PANSS). RESULTS: ToM and emotion recognition deficits improved in the clinically stable phase compared to relapse, but were still found to be impaired compared to healthy controls. Negative symptom severity showed strong correlation with emotion recognition and ToM at both visits. CONCLUSIONS: Both ToM and emotion recognition fluctuated together with symptom severity, which confirmed the "state-like" component of these abilities. Our results, taken together with the findings of previous investigations show that social cognition deficits in schizophrenia have both state-like and trait-like components.

[SCHIZOBANK - The Hungarian national schizophrenia biobank and its role in schizophrenia research and in personalized medicine]. / Magyar szkizofrénia-biobank a szkizofréniakutatás és a személyre szabott orvoslás szolgálatában.

Delineating the pathogenesis of multifactorial diseases is a major challenge of the postgenomial era. Genetic factors are known to play an important role in the pathogenesis of certain psychiatric disorders as well as in the development of adverse reactions to psychoactive drugs. Containing large numbers of samples and linking them clinical data, biobanks are gaining importance in the studies of chronic multifactorial diseases. Several biobanks are under establishment in Hungary. The first initiative to collect samples in neurological and psychiatric disorders was the NEPSYBANK coordinated by the Hungarian Society of Clinical Neurogenetics. The national biobank network is currently established by the NEKIFUT project of the National Office of Research and Technology. In this article we describe the structure, logistics and informatical background of the national schizophrenia biobank (SCHIZOBANK). The initiative of the SCHIZOBANK originates from a consortium in which academy and health industry partners are collecting biological materials and data in five major psychiatric center under the coordination of the Medical and Health Science Center of the University of Debrecen. We review other international schizophrenia biobanks as well. Major strength of the SCHIZOBANK is the collection of very detailed phenotypic data and of RNA and plasma both in psychotic and non-psychotic state of the patient which permits longitudinal follow-up and the study of both static and dynamically changing transcriptomic, proteomic and metabolomic markers. The collection of the SCHIZOBANK is available not only to consortial partners but to other national and international research groups as well.