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Abstract Background Empirical evidence on the epidemiology of hypertension, diabetes and hypercholesterolemia is limited in many countries in Central and Eastern Europe. We aimed to estimate the prevalence, awareness, treatment and control of hypertension, diabetes and hypercholesterolemia in the Czech Republic, Russia, Poland and Lithuania, and to identify the risk factors for the three chronic conditions. Methods We analysed cross-sectional data from the HAPIEE study, including adults aged 45–69 years in the Czech Republic, Russia, Poland and Lithuania, collected between 2002 and 2008 (total sample N = 30,882). Among prevalent cases, we estimated awareness, treatment, and control of hypertension, diabetes and hypercholesterolemia by gender and country. Multivariate logistic regression was applied to identify associated risk factors. Results In each country among both men and women, we found high prevalence but low control of hypertension, diabetes, and hypercholesterolemia. Awareness rates of hypertension were the lowest in both men (61.40%) and women (69.21%) in the Czech Republic, while awareness rates of hypercholesterolemia were the highest in both men (46.51%) and women (51.20%) in Poland. Polish participants also had the highest rates of awareness (77.37% in men and 79.53% in women), treatment (71.99% in men and 74.87% in women) and control (30.98% in men and 38.08% in women) of diabetes. The common risk factors for the three chronic conditions were age, gender, education, obesity and alcohol consumption. Conclusions Patterns of awareness, treatment and control rates of hypertension, diabetes and hypercholesterolemia differed by country. Efforts should be made in all four countries to control these conditions, including implementation of international guidelines in everyday practice to improve detection and effective management of these conditions.

Data in ASCII format related to the figures in the publication. Each figure has a description file (TXT) which contains the list of spreadsheet names and the data file (DAT, containing all the data relevant to the listed spreadsheets). Fig1.dat.txt (description file) Fig1.dat (data file) Fig8-9.dat.txt Fig.8-9.dat Each spreadsheet in the data file contains a header where all the parameters of the experiment are listed.

Genome sequencing, assembly, and microsatellite development For whole-genome sequencing DNA from G. obscura isolate 6BE2, which originally was cultured from body wash samples from a X. crassiusculus beetle live-trapped in eastern Tennessee (Chahal et al. 2019), was extracted using Qiagen Blood and Cell Culture DNA Kit Maxi (Qiagen, Germantown, MD, USA), according to the protocol (Gazis et al., 2016). Libraries were prepared at the Michigan State University Genomics Core lab (https://rtsf.natsci.msu.edu/genomics/) using the Illumina TruSeq Nano DNA Library Preparation kit on a Perkin Elmer Sciclone G3 robot following the manufacturer’s recommendation. Completed libraries were checked for quality (QC) and quantified using a combination of Qubit dsDNA HS and Caliper LabChipGX HS DNA assays. All libraries were pooled in equimolar amounts based on QC and quantified using the Kapa Biosystems Illumina Library Quantification qPCR kit. Library sequencing was performed with Illumina HiSeq 4000 flow cell using a 2x150bp paired end format and a HiSeq 4000 SBS reagent kit. Base calling was completed using Illumina Real Time Analysis (RTA) v2.7.6 and output of RTA was demultiplexed and converted to FastQ format with Illumina Bcl2fastq v2.19.0. The transcript quality of these reads was assessed using FastQC (Andrews, 2010) and error correction performed using default values with Bloom Filter Correction (BFC) (Li, 2015). Using the trimming program Skewer (Jiang et al., 2014) adapter sequences were removed and reads were filtered by requiring a minimal quality score of 20 in at least 70% of the bases. With the exception of minimal read length after trimming set to 30, all default parameters were used. Next, the transcripts were assembled using Assembly By Short Sequences (ABySS), specifically its paired-end option, abyss-pe, using a k-mer size of 81 and default settings for all other options (Simpson et al., 2009). Finally, sequences were masked for low complexity regions with Dustmasker (level of 1) (Morgulis et al., 2006). Microsatellite markers were identified with a custom perl script (Staton and Ficklin, 2018) (Table 1). This script utilizes Primer3 (Rozen and Skaletsky, 2000) to search for di, tri, and tetra-repeating motifs, with primer product size range between 100-250 base pairs long (Untergasser et al., 2012). This script also produced text files containing the IDs and forward and reverse primers for the identified markers; these would be used to identify common regions between the different species’ genome scaffolds. Fungal strain selection, DNA extraction, amplification and molecular confirmation Following Gazis et al. (2018) protocol, axenic cultures from seven G. obscura isolates and 18 additional isolates of Geosmithia species (Table 2) were placed onto Difco™ Potato Dextrose Broth (PDB) (Becton, Dickinson and company, Sparks, MD, USA) at 22⁰C for up to two weeks, after which mycelium was harvested for DNA extraction. For species confirmation, GeneJet Genomic DNA Purification Kit (Thermo Fisher Scientific, Pittsburgh, PA, USA) was used, following manufacturer’s protocols with slight modifications. These modifications included increased proteinase K to 40 µL/sample and an extended overnight incubation period at 56°C. Samples were quantified using a nanodrop 1000 spectrophotometer (Thermo Fisher Scientific, Pittsburgh, PA, USA) and stored at -20⁰C until used. To confirm the identity of the Geosmithia isolates, the RNA operon was amplified and sequenced using the ITS primers ITS1F (Gardes and Bruns, 1993) and ITS4R (White et al., 1990), following Gazis et al. (2018) protocol. PCR product was visualized on a 2% agarose gel and sent to MCLAB (www.mclab.com) for cleaning and sequencing. Sequenced strands were assembled into contigs using Sequencher 5.0 (Gene Codes Corporation, Ann Arbor, MI, USA). Sequences were compared to the NCBI nucleotide database using BLAST search optimized to exclude uncultured/environmental sample sequences and to search sequences from type material. If species identity of 99-100% was not obtained, an unrestricted BLAST search was performed (Table 2). Additional Geosmithia spp. (G. obscura CBS121749, G. lavendula CBS344.49, G. pallida CBS260.33,) and other species (Penicillium [formerly Geosmithia] namyslowskii CBS686.85 and Talaromyces [formerly Geosmithia] viridulus CBS252.07) were acquired as DNA samples from The Dutch Centraalbureau voor Schimmelcultures (CBS) Fungal Biodiversity Centre collection or from previously verified DNA samples from our collection [G. obscura 14MCE1, G. sp. 23 4MN3, G. morbida GM182, G. morbida GM249, G. morbida GM250, and Rasamsonia argillacea (Stolk, H.C. Evans & T. Nilsson) Houbraken & Frisvad (formerly G. argillacea)]. Microsatellite characterization and cross-amplification A total of 2815 microsatellite markers were identified with flanking primer sequences. Of those, 75 microsatellite markers (consisting of 25 di-, 25 tri-, and 25 tetra-nucleotide sequences) were randomly selected and screened to identify polymorphic markers. For the initial characterization, all primer pairs were tested using three G. obscura and one G. morbida isolates. PCR reactions were conducted using 4 µL GoTaq G2 Hot Start Colorless Master Mix (Promega Corporation, Madison, WI, USA), 1 µL each forward and reverse primers, 0.5 µL DMSO, 5 µL sterile water, and 1 µL genomic DNA providing a 12.5 µL sample volume. Samples were placed in a SimpliAmp ThermalCycler (Thermo Fisher Scientific) with the following protocol: 94°C for 3 min followed by 35 cycles of denaturation at 94°C for 40 sec, annealing at 55°C for 40 sec, and primer extension at 72°C for 30 sec, followed by 72°C for 4 min. PCR products were separated using a QIAxcel Capillary Electrophoresis System (Qiagen, Germantown, MD, USA) with a 25-500 bp size standard. Products with a relative fluorescence unit (RFU) of 100 or greater were scored as positive amplification. Only a subset of microsatellite markers (n=28) that were identified as polymorphic were further screened in the cross-amplification study. To accomplish this step, six G. obscura isolates along with 24 isolates from nine different Geosmithia species and three additional isolates outside Geosmithia were screened. Isolates were amplified using the PCR protocol described above and separated using QIAxcel Capillary Electrophoresis System with an RFU value of 100 or greater scored as positive. Number of alleles and haploid genetic diversity was obtained using the program GenAlEx 6.5 (Peakall and Smouse, 2012). Background. Symbioses between Geosmithia fungi and wood-boring and bark beetles seldom result in disease induction within the plant host. Yet exceptions exist such as Geosmithia morbida, the causal agent of Thousand Cankers Disease (TCD) of walnuts and wingnuts and Geosmithia sp. 41, the causal agent of Foamy Bark Canker disease of oaks. Isolates of G. obscura were recovered from black walnut trees in eastern Tennessee and at least one isolate induced cankers following artificial inoculation. Due to the putative pathogenicity and lack of recovery of G. obscura from natural lesions, a molecular diagnostic screening tool was developed using microsatellite markers mined from the G. obscura genome. Results. A total of 3,256 candidate microsatellite markers were identified (2236, 789, 137 di-, tri-, and tetra- motifs were identified, respectively), with 2011, 703, 101 di-, tri-, and tetra- motifs containing markers with primers. From these, 75 microsatellite markers were randomly selected, screened, and optimized, resulting in 28 polymorphic markers that yielded single, consistently recovered bands which were used in downstream analyses. Five of these microsatellite markers were found to be specific to G. obscura and did not cross-amplify into other, closely related species. Although the remaining tested markers could be useful, they cross-amplified within different Geosmithia species, making them not reliable for G. obscura detection. Conclusion. Five novel microsatellite markers (GOBS9, GOBS10, GOBS41, GOBS43, GOBS50) were developed based on G. obscura genome. These species-specific microsatellite markers are available as a tool for use in molecular diagnostics and can assist future surveillance studies. Abyss assembly of 9.1 million paired sequencing reads from DNA of G. obscura resulted in 5,752 unitigs spanning 28.9 Mb with an N50 of 24,134 and 47.4x coverage. The assembled sequences were screened for microsatellite development, from which 1,653 unitigs yielded at least one microsatellite marker, resulting in 3,256 candidate microsatellite markers. From this group, we identified 94 compound microsatellites, which were either located next to each other, or separated by less than 15 base pairs (bp), and 2,815 microsatellite markers with flanking primer sequences. Parameters for minimum number of replicates for each motif were established at 8 for dinucleotides, 7 for trinucleotides, and 6 for tetranucleotides. Using these baseline parameters, a total of 2236, 789, 137 di-, tri-, and tetra- motifs were identified respectively, with 2011, 703, 101 di-, tri-, and tetra- motifs containing markers with primers. We tested 75 markers for amplification and the presence of polymorphic bands. All tested markers resulted in amplification, and a total of 36 markers were polymorphic (11 di-, 13 tri-, 12 tetra-nucleotides). Further optimization of the microsatellite markers yielded 28 markers with single, consistently recovered bands (Table 3), which were used to test cross-amplification of G. obscura markers into other Geosmithia species.

In this study, we present data related to optimizing Si-PVdF slurry mixing and electrode fabrication techniques to enhance the performance of lithium-ion batteries. Three critical experimental conditions are documented in Tables 1, 2, and 3, corresponding to different stages of the research. Table 1 records data from an initial unsuccessful attempt, while Table 2 captures data from a subsequent trial that did not yield successful results. Figure 1(a) clearly depicts an unsuccessful endeavor in the slurry mixing process of Si-PVdF, utilizing a volume of 0.9 ml of NMP. The image presented exhibits notable visual characteristics that illustrate the difficulties encountered in attaining a uniform slurry, as evidenced by noticeable irregularities and accumulation within the mixture [3]. The proposed visual representation emphasizes the crucial significance of accurate quantity control of NMP (N-Methyl-2-pyrrolidone) and sheds light on the challenges encountered during the electrode fabrication process in this research phase [4]. Fig. 1(b) depicts an additional instance of an unsuccessful endeavor in the slurry mixing process of Si-PVdF, wherein 1.0 ml of NMP was employed. The sharp and detailed image captures the persistence of issues observed in Fig. 1(a), emphasizing the importance of optimizing the NMP concentration. This striking visual evidence accentuates the necessity for fine-tuning the formulation to overcome challenges and attain a consistent slurry mixture. Table 3, on the other hand, represents the outcome of a successful experiment. Each table provides information on the materials used, including Silicon (Si), Polyvinylidene fluoride (PVdF), Graphite (G), and N-methyl-2-pyrrolidone (NMP), along with their respective weights and proportions. Figure 1(c) represents a significant achievement in the research, illustrating the successful fabrication of Si-PVdF slurry following a crucial aging procedure [5]. The visual representation conveys a perception of achievement through its consistent and seamless surface quality, effectively demonstrating enhanced bonding between the slurry material and the copper foil. Additionally, the tables include electrode and copper foil weight measurements and active Si weight percentage values. The data in these tables highlight the critical role of NMP quantity and aging time in achieving a homogenous slurry and successful electrode fabrication. Notably, the successful experiment in Table 3 is marked by improved adhesion of the slurry material to the copper foil, preventing delamination. This dataset provides valuable insights into the optimization process for Si-PVdF electrode fabrication in lithium-ion batteries. It can serve as a reference for future research in battery materials science [9].

Nálezy z archeologického výzkumu v Březnici (okr. Tábor) v letech 2005-2009 a 2019. Výzkum provedl O. Chvojka (Archeologický ústav FF JU v Českých Budějovicích). Data zahrnují údaje o keramice a dalších nálezech použitých k depoziční analýze sídlištních objektů mladší doby bronzové, zejména tzv. žlabů. Výsledky analýzy jsou publikovány v Chvojka et al. 2021. Popis databáze je obsažen v přiloženém PDF souboru. Podpořeno Grantovou agenturou ČR (18-10747S). Finds from the archaeological excavations in Březnice (Tábor district, South Bohemia, Czech Republic) in 2005-2009 and 2019. The fieldwork was directed by O. Chvojka (Institute of Archaeology, South Bohemian University in České Budějovice). Data concern the pottery fragments and other finds (daub, loom weights) used for the analysis of deposition processes in the Late Bronze Age settlement features. Based on this material, a model of house biography and the concept of closing rituals were formulated (see Chvojka et al. 2021). These models suggest an interpretation for the so-called trenches, specific sunken features filled with an unusually rich content of secondary-burnt pottery and other finds. Details of the database are given in the attached PDF file. Supported by the Czech Sceince Foundation (18-10747S). Chvojka, O. – Kuna, M. – Menšík, P. et al. 2021: Rituály ukončení a obnovy. Sídliště mladší doby bronzové v Březnici u Bechyně – Rituals of termination and renewal. The Late Bronze Age settlement in Březnice near Bechyně. České Budějovice – Praha – Plzeň. ISBN 978-80-7394-899-3; ISBN 978-80-7581-039-7; ISBN 978-80-261-1083-5.

Rapid and reliable identification of insects is important in many contexts, from the detection of disease vectors and invasive species to the sorting of material from biodiversity inventories. Because of the shortage of adequate expertise, there has long been an interest in developing automated systems for this task. Previous attempts have been based on laborious and complex handcrafted extraction of image features, but in recent years it has been shown that sophisticated convolutional neural networks (CNNs) can learn to extract relevant features automatically, without human intervention. Unfortunately, reaching expert-level accuracy in CNN identifications requires substantial computational power and huge training datasets, which are often not available for taxonomic tasks. This can be addressed using feature transfer: a CNN that has been pretrained on a generic image classification task is exposed to the taxonomic images of interest, and information about its perception of those images is used in training a simpler, dedicated identification system. Here, we develop an effective method of CNN feature transfer, which achieves expert-level accuracy in taxonomic identification of insects with training sets of 100 images or less per category. Specifically, we extract rich representations of intermediate to high-level image features from the CNN architecture VGG16 pretrained on the ImageNet dataset. This information is fed into a linear support vector machine classifier, which is trained on the target problem. We tested the performance of our approach on two types of challenging taxonomic tasks: (1) identifying insects to higher groups when they are likely to belong to subgroups that have not been seen previously; and (2) identifying visually similar species that are difficult to separate even for experts. For the first task, our approach reaches > 92 % accuracy on one dataset (884 face images of 11 families of Diptera, all specimens representing unique species), and > 96 % accuracy on another (2936 dorsal habitus images of 14 families of Coleoptera, over 90 % of specimens belonging to unique species). For the second task, our approach outperforms a leading taxonomic expert on one dataset (339 images of three species of the Coleoptera genus Oxythyrea; 97 % accuracy), and both humans and traditional automated identification systems on another dataset (3845 images of nine species of Plecoptera larvae; 98.6 % accuracy). Reanalyzing several biological image identification tasks studied in the recent literature, we show that our approach is broadly applicable and provides significant improvements over previous methods, whether based on dedicated CNNs, CNN feature transfer, or more traditional techniques. Thus, our method, which is easy to apply, can be highly successful in developing automated taxonomic identification systems even when training datasets are small and computational budgets limited. valan2018_SUPPLEMENT.tarThis directory contains: * metadata to obtain images from the three novel datasets we designed for our study * notebooks with thorough evaluation of off-the-shelf approach for image classification based on a feature extraction with a single feed forward pass trough pretrained VGG16 * script to run on your own dataset with what we found to be optimal settings. You can also access it here https://github.com/valanm/off-the-shelf-insect-identificationSupplementary_Figure1Impact of concatenating globally max pooled (MAX) and globally average pooled (AVG) features on identification accuracy for datasets D1, D2, D3 and D4. We used input images of size 416x416 and features are extracted after 4th convolutional block (c4). Concatenation of MAX and AVG features resulted in accuracy somewhere between the global average pooling (performed the best in all cases) and global max pooling (performed the worst in all cases).valan2018_latex

Abstract Numerous hypotheses try to explain the unusual appearance of the human eye with its bright sclera and transparent conjunctiva and how it could have evolved from a dark-eyed phenotype, as is present in many non-human primates. Recently, it has been argued that pigmentation defects induced by self-domestication may have led to bright-eyed ocular phenotypes in humans and some other primate lineages, such as marmosets. However, it has never been systematically studied whether actual domesticated mammals consistently deviate from wild mammals in regard to their conjunctival pigmentation and if this trait might therefore be part of a domestication syndrome. Here, we test this idea by drawing phylogenetically informed comparisons from a photographic dataset spanning 13 domesticated mammal species and their closest living wild relatives (n ≥ 15 photos per taxon). We did not recover significant differences in scleral appearance or irido-scleral contrast between domesticated and wild forms, suggesting that conjunctival depigmentation, unlike cutaneous pigmentation disorders, is not a general correlate of domestication. Regardless of their domestication status, macroscopically depigmented conjunctivae were observed in carnivorans and lagomorphs, whereas ungulates generally displayed darker eyes. For some taxa, we observed pronounced intraspecific variation, which should be addressed in more exhaustive future studies. Based on our dataset, we also present preliminary evidence for a general increase of conjunctival pigmentation with eye size in mammals. Our findings suggest that conjunctival depigmentation in humans is not a byproduct of self-domestication, even if we assume that our species has undergone such a process in its recent evolutionary history.

The genome annotation files for M. exilis genome, based on nanopore sequencing. The annotation was further polished using long-read transcriptomic data.