An Explainable Deep Learning Classifier of Bovine Mastitis Based on Whole-Genome Sequence Data-Circumventing the p >> n Problem.

The serious drawback underlying the biological annotation of whole-genome sequence data is the p >> n problem, which means that the number of polymorphic variants (p) is much larger than the number of available phenotypic records (n). We propose a way to circumvent the problem by combining a LASSO logistic regression with deep learning to classify cows as susceptible or resistant to mastitis, based on single nucleotide polymorphism (SNP) genotypes. Among several architectures, the one with 204,642 SNPs was selected as the best. This architecture was composed of two layers with, respectively, 7 and 46 units per layer implementing respective drop-out rates of 0.210 and 0.358. The classification of the test data resulted in AUC = 0.750, accuracy = 0.650, sensitivity = 0.600, and specificity = 0.700. Significant SNPs were selected based on the SHapley Additive exPlanation (SHAP). As a final result, one GO term related to the biological process and thirteen GO terms related to molecular function were significantly enriched in the gene set that corresponded to the significant SNPs. Our findings revealed that the optimal approach can correctly predict susceptibility or resistance status for approximately 65% of cows. Genes marked by the most significant SNPs are related to the immune response and protein synthesis.

The cancer-risk variant frequency among Polish population reported by the first national whole-genome sequencing study.

Introduction: Population-based cancer screening has raised many controversies in recent years, not only regarding the costs but also regarding the ethical nature and issues related to variant interpretation. Nowadays, genetic cancer screening standards are different in every country and usually encompass only individuals with a personal or family history of relevant cancer. Methods: Here we performed a broad genetic screening for cancer-related rare germline variants on population data from the Thousand Polish Genomes database based on 1076 Polish unrelated individuals that underwent whole genome sequencing (WGS). Results: We identified 19 551 rare variants in 806 genes related to oncological diseases, among them 89% have been located in non-coding regions. The combined BRCA1/BRCA2 pathogenic/likely pathogenic according to ClinVar allele frequency in the unselected population of 1076 Poles was 0.42%, corresponding to nine carriers. Discussion: Altogether, on the population level, we found especially problematic the assessment of the pathogenicity of variants and the relation of ACMG guidelines to the population frequency. Some of the variants may be overinterpreted as disease-causing due to their rarity or lack of annotation in the databases. On the other hand, some relevant variants may have been overseen given that there is little pooled population whole genome data on oncology. Before population WGS screening will become a standard, further studies are needed to assess the frequency of the variants suspected to be pathogenic on the population level and with reporting of likely benign variants.

Better safe than sorry-Whole-genome sequencing indicates that missense variants are significant in susceptibility to COVID-19.

Undoubtedly, genetic factors play an important role in susceptibility and resistance to COVID-19. In this study, we conducted the GWAS analysis. Out of 15,489,173 SNPs, we identified 18,191 significant SNPs for severe and 11,799 SNPs for resistant phenotype, showing that a great number of loci were significant in different COVID-19 representations. The majority of variants were synonymous (60.56% for severe, 58.46% for resistant phenotype) or located in introns (55.77% for severe, 59.83% for resistant phenotype). We identified the most significant SNPs for a severe outcome (in AJAP1 intron) and for COVID resistance (in FIG4 intron). We found no missense variants with a potential causal function on resistance to COVID-19; however, two missense variants were determined as significant a severe phenotype (in PM20D1 and LRP4 exons). None of the aforementioned SNPs and missense variants found in this study have been previously associated with COVID-19.

Bioinformatic modelling of SARS-CoV-2 pandemic with a focus on country-specific dynamics.

BACKGROUND: One of the seminal events since 2019 has been the outbreak of the SARS-CoV-2 pandemic. Countries have adopted various policies to deal with it, but they also differ in their socio-geographical characteristics and public health care facilities. Our study aimed to investigate differences between epidemiological parameters across countries. METHOD: The analysed data represents SARS-CoV-2 repository provided by the Johns Hopkins University. Separately for each country, we estimated recovery and mortality rates using the SIRD model applied to the first 30, 60, 150, and 300 days of the pandemic. Moreover, a mixture of normal distributions was fitted to the number of confirmed cases and deaths during the first 300 days. The estimates of peaks' means and variances were used to identify countries with outlying parameters. RESULTS: For 300 days Belgium, Cyprus, France, the Netherlands, Serbia, and the UK were classified as outliers by all three outlier detection methods. Yemen was classified as an outlier for each of the four considered timeframes, due to high mortality rates. During the first 300 days of the pandemic, the majority of countries underwent three peaks in the number of confirmed cases, except Australia and Kazakhstan with two peaks. CONCLUSIONS: Considering recovery and mortality rates we observed heterogeneity between countries. Liechtenstein was the "positive" outlier with low mortality rates and high recovery rates, at the opposite, Yemen represented a "negative" outlier with high mortality for all four considered periods and low recovery for 30 and 60 days.

Gene Variants Related to Cardiovascular and Pulmonary Diseases May Correlate with Severe Outcome of COVID-19.

Background: Severe outcomes of COVID-19 account for up to 15% of all cases. The study aims to check if any gene variants related to cardiovascular (CVD) and pulmonary diseases (PD) are correlated with a severe outcome of COVID-19 in a Polish cohort of COVID-19 patients. Methods: In this study, a subset of 747 samples from unrelated individuals collected across Poland in 2020 and 2021 was used and whole-genome sequencing was performed. Results: The GWAS analysis of SNPs and short indels located in genes related to CVD identified one variant significant in COVID-19 severe outcome in the HADHA gene, while for the PD gene panel, we found two significant variants in the DRC1 gene. In this study, both potentially protective and risk variants were identified, of which variants in the HADHA gene deserve the most attention. Conclusions: This is the first study reporting the association between the HADHA and DRC1 genetic variants and COVID-19 severe outcome based on the cohort WGS analysis. Although all the identified variants are localised in introns, they may be correlated and therefore inherited along with other risk variants, potentially causative to severe outcome of COVID-19 but not discovered yet.

Beyond GWAS-Could Genetic Differentiation within the Allograft Rejection Pathway Shape Natural Immunity to COVID-19?

COVID-19 infections pose a serious global health concern so it is crucial to identify the biomarkers for the susceptibility to and resistance against this disease that could help in a rapid risk assessment and reliable decisions being made on patients' treatment and their potential hospitalisation. Several studies investigated the factors associated with severe COVID-19 outcomes that can be either environmental, population based, or genetic. It was demonstrated that the genetics of the host plays an important role in the various immune responses and, therefore, there are different clinical presentations of COVID-19 infection. In this study, we aimed to use variant descriptive statistics from GWAS (Genome-Wide Association Study) and variant genomic annotations to identify metabolic pathways that are associated with a severe COVID-19 infection as well as pathways related to resistance to COVID-19. For this purpose, we applied a custom-designed mixed linear model implemented into custom-written software. Our analysis of more than 12.5 million SNPs did not indicate any pathway that was significant for a severe COVID-19 infection. However, the Allograft rejection pathway (hsa05330) was significant (p = 0.01087) for resistance to the infection. The majority of the 27 SNP marking genes constituting the Allograft rejection pathway were located on chromosome 6 (19 SNPs) and the remainder were mapped to chromosomes 2, 3, 10, 12, 20, and X. This pathway comprises several immune system components crucial for the self versus non-self recognition, but also the components of antiviral immunity. Our study demonstrated that not only single variants are important for resistance to COVID-19, but also the cumulative impact of several SNPs within the same pathway matters.

Genome-Wide Genomic and Functional Association Study for Workability and Calving Traits in Holstein Cattle.

The goal of our study was to identify the SNPs, metabolic pathways (KEGG), and gene ontology (GO) terms significantly associated with calving and workability traits in dairy cattle. We analysed direct (DCE) and maternal (MCE) calving ease, direct (DSB) and maternal (MSB) stillbirth, milking speed (MSP), and temperament (TEM) based on a Holstein-Friesian dairy cattle population consisting of 35,203 individuals. The number of animals, depending on the trait, ranged from 22,301 bulls for TEM to 30,603 for DCE. We estimated the SNP effects (based on 46,216 polymorphisms from Illumina BovineSNP50 BeadChip Version 2) using a multi-SNP mixed model. The SNP positions were mapped to genes and the GO terms/KEGG pathways of the corresponding genes were assigned. The estimation of the GO term/KEGG pathway effects was based on a mixed model using the SNP effects as dependent variables. The number of significant SNPs comprised 59 for DCE, 25 for DSB and MSP, 17 for MCE and MSB, and 7 for TEM. Significant KEGG pathways were found for MSB (2), TEM (2), and MSP (1) and 11 GO terms were significant for MSP, 10 for DCE, 8 for DSB and TEM, 5 for MCE, and 3 for MSB. From the perspective of a better understanding of the genomic background of the phenotypes, traits with low heritabilities suggest that the focus should be moved from single genes to the metabolic pathways or gene ontologies significant for the phenotype.

The Thousand Polish Genomes-A Database of Polish Variant Allele Frequencies.

Although Slavic populations account for over 4.5% of world inhabitants, no centralised, open-source reference database of genetic variation of any Slavic population exists to date. Such data are crucial for clinical genetics, biomedical research, as well as archeological and historical studies. The Polish population, which is homogenous and sedentary in its nature but influenced by many migrations of the past, is unique and could serve as a genetic reference for the Slavic nations. In this study, we analysed whole genomes of 1222 Poles to identify and genotype a wide spectrum of genomic variation, such as small and structural variants, runs of homozygosity, mitochondrial haplogroups, and de novo variants. Common variant analyses showed that the Polish cohort is highly homogenous and shares ancestry with other European populations. In rare variant analyses, we identified 32 autosomal-recessive genes with significantly different frequencies of pathogenic alleles in the Polish population as compared to the non-Finish Europeans, including C2, TGM5, NUP93, C19orf12, and PROP1. The allele frequencies for small and structural variants, calculated for 1076 unrelated individuals, are released publicly as The Thousand Polish Genomes database, and will contribute to the worldwide genomic resources available to researchers and clinicians.

Identification of functional features underlying heat stress response in Sprague-Dawley rats using mixed linear models.

Since global temperature is expected to rise by 2 °C in 2050 heat stress may become the most severe environmental factor. In the study, we illustrate the application of mixed linear models for the analysis of whole transcriptome expression in livers and adrenal tissues of Sprague-Dawley rats obtained by a heat stress experiment. By applying those models, we considered four sources of variation in transcript expression, comprising transcripts (1), genes (2), Gene Ontology terms (3), and Reactome pathways (4) and focussed on accounting for the similarity within each source, which was expressed as a covariance matrix. Models based on transcripts or genes levels explained a larger proportion of log2 fold change than models fitting the functional components of Gene Ontology terms or Reactome pathways. In the liver, among the most significant genes were PNKD and TRIP12. In the adrenal tissue, one transcript of the SUCO gene was expressed more strongly in the control group than in the heat-stress group. PLEC had two transcripts, which were significantly overexpressed in the heat-stress group. PER3 was significant only on gene level. Moving to the functional scale, five Gene Ontologies and one Reactome pathway were significant in the liver. They can be grouped into ontologies related to DNA repair, histone ubiquitination, the regulation of embryonic development and cytoplasmic translation. Linear mixed models are valuable tools for the analysis of high-throughput biological data. Their main advantages are the possibility to incorporate information on covariance between observations and circumventing the problem of multiple testing.

The Course and the Effects of Agricultural Biomass Pyrolysis in the Production of High-Calorific Biochar.

The thermal pyrolysis of agriculture biomass has been studied in a fixed-bed reactor, where the pyrolysis was conducted at a steady temperature of 800 °C. This work analyses the pyrolysis products of six agricultural wastes: pistachio husks, walnut husks, sunflower hulls, buckwheat husks, corncobs and coconut shells. The conducted research compared examples of large waste biomass streams from different parts of the world as a potential source of renewable energy. Additionally, the kinetics of the reaction with the activation energy were analyzed and calculated for all raw materials in pyrolysis process. Biochars are characterised by higher combustion heat in comparison to the raw material samples. The average value of the heat of combustion increased due to pyrolysis process from 10 MJ/kg, with minimal value of 2.7 MJ/kg (corncob) and maximum of 13.0 MJ/kg for coconut, which is also characterised by the maximal absolute combustion heating value (32.3 MJ/kg). The increase in calorific values varied from 15% to 172% (with 54% reference for wood chips), which indicates that charring is an effective method for increasing the energy concentration. The obtained biochar were compared with wood chips, which are widely used solid fuel of organic origin. The studied biomass-derived fuels are characterised by lower ash contribution than wood. An analogous observation was made for the obtained biochars, whose ash contribution was lower than for the chips in terms of both unit-mass and unit-combustion-heat. The main advantage of this method is the production of solid fuel from biomass, which increases the calorific value and bulk density of biochar in comparison to raw material.

History of Heart Failure in Patients Hospitalized Due to COVID-19: Relevant Factor of In-Hospital Complications and All-Cause Mortality up to Six Months.

BACKGROUND: Patients with heart failure (HF) are at high risk of unfavorable courses of COVID-19. The aim of this study was to evaluate characteristics and outcomes of COVID-19 patients with HF. METHODS: Data of patients hospitalized in a tertiary hospital in Poland between March 2020 and May 2021 with laboratory-confirmed COVID-19 were analyzed. The study population was divided into a HF group (patients with a history of HF) and a non-HF group. RESULTS: Out of 2184 patients (65 ± 13 years old, 50% male), 12% had a history of HF. Patients from the HF group were older, more often males, had more comorbidities, more often dyspnea, pulmonary and peripheral congestion, inflammation, and end-organ damage biomarkers. HF patients had longer and more complicated hospital stay, with more frequent acute HF development as compared with non-HF. They had significantly higher mortality assessed in hospital (35% vs. 12%) at three (53% vs. 22%) and six months (72% vs. 47%). Of 76 (4%) patients who developed acute HF, 71% died during hospitalization, 79% at three, and 87% at six months. CONCLUSIONS: The history of HF identifies patients with COVID-19 who are at high risk of in-hospital complications and mortality up to six months of follow-up.

Burden of multimorbidity in a Polish cohort of ambulatory and hospitalized heart failure patients from 2 large European registry programs: prognostic implications.

Introduction: Individual comorbidities have been shown to adversely affect prognosis in heart failure (HF). However, our knowledge of multimorbidity in HF and understanding of its prognostic implications still remain incomplete. Objectives: We aimed to analyze the prevalence of multimorbidity in Polish HF patients and to investigate the quantitative and qualitative impact of comorbidity burden on 12-month outcomes in that population. Patients and methods: We retrospectively analyzed data of 1765 Polish patients with ambulatory or acute (requiring hospitalization) HF from 2 multicenter observational European Society of Cardiology registries: the ESC-HF Pilot Survey (2009­2010) and ESC-HF-LT Registry (2011­2013). Results: Arterial hypertension and coronary artery disease were the most prevalent comorbidities, similarly to the entire European cohort. The great majority of HF patients had more than 1 predefined comorbidity and the most frequent number of comorbidities was 3. Importantly, in almost half of the patients, 4 or more comorbidities were reported. The best accuracy for predicting the adjusted 12-month rate of all-cause death was ensured by the model including only anemia and kidney dysfunction. The model including 4 comorbidities­anemia, kidney dysfunction, diabetes, and coronary artery disease­provided best accuracy for predicting 12-month rate of composite all-cause death or HF hospitalization. Conclusions: Multimorbidity is highly prevalent in a real-world cohort of Polish HF patients and the quantitative burden of comorbidities is related to increased mortality. In such patients, the clinical profile characterized by pathophysiological continuum of diabetes, kidney dysfunction, and anemia is particularly associated with unfavorable outcomes.

SNP prioritization in targeted sequencing data associated with humoral immune responses in chicken.

Our study aimed to identify single nucleotide polymorphisms (SNPs) with a significant impact on the innate immunity represented by antibody response against lipopolysaccharide (LPS) and lipoteichoid acid (LTA) and the adaptive immune response represented toward keyhole limpet hemocyanin (KLH) using the SNP prioritization method. Data set consisted of 288 F2 experimental individuals, created by crossing Green-legged Partridgelike and White Leghorn. The analyzed SNPs were located within 24 short genomic regions of GGA1, GGA2, GGA3, GGA4, GGA9, GGA10, GGA14, GGA18, and GGZ, pre-targeted based on literature references and database information. For the specific antibody response toward KLH at d 0 the most highly prioritized SNP for additive and dominance effects were located on GGA2 in the 3'UTR of MYD88. For the response at d 7, the most highly prioritized SNP pointed at the 3'UTR of MYD88, but potential causal additive variants were located within ADIPOQ and one in PROCR. The highest priority for additive and dominance effects in the antibody response toward lipoteichoic acid at d 0 was attributed to the same SNP, located on GGA2 in the 3'UTR region of MYD88. Two SNPs among the top-10 for additive effect were located in the exon of NOCT. SNPs selected for their additive effect on antibody response toward lipopolysaccharide at d 0 marked 3 genes - NOCT, MYD88, and SNX8, while SNPs selected for their dominance effect marked - NOCT, ADIPOQ, and MYD88. The top-10 variants identified in our study were located in different functional parts of the genome. In the context of causality three groups can be distinguished: variants located in exons of protein coding genes (ADIPOQ, NOCT, PROCR, SNX8), variants within exons of non-coding transcripts, and variants located in genes' UTR regions. Variants from the first group influence protein structure and variants from both latter groups' exhibit regulatory roles on DNA (UTR) or RNA (lncRNA).

Pyrolysis of Pruning Residues from Various Types of Orchards and Pretreatment for Energetic Use of Biochar.

The routine pruning and cutting of fruit trees provides a considerable amount of biowaste each year. This lignocellulosic biomass, mainly in the form of branches, trunks, rootstocks, and leaves, is a potential high-quality fuel, yet often is treated as waste. The results of a feasibility study on biochar production by pyrolysis of residues from orchard pruning were presented. Three types of biomass waste were selected as raw materials and were obtained from the most common fruit trees in Poland: apple (AP), pear (PR), and plum (PL) tree prunings. Two heating rates and three final pyrolysis temperatures were applied. For the slow (SP) and fast pyrolysis (FP) processes, the heating rates were 15 °C/min and 100 °C/min, respectively. The samples were heated from 25 °C up to 400, 500, and 600 °C. Chemical analyses of the raw materials were conducted, and the pyrolysis product yields were determined. A significant rise of higher heating value (HHV) was observed for the solid pyrolysis products, from approximately 23.45 MJ/kg for raw materials up to approximately 29.52 MJ/kg for pyrolysis products at 400 °C, and 30.53 MJ/kg for pyrolysis products at 600 °C. Higher carbon content was observed for materials obtained by fast pyrolysis conducted at higher temperatures.

Iron deficiency contributes to resistance to endogenous erythropoietin in anaemic heart failure patients.

AIMS: Abnormal endogenous erythropoietin (EPO) constitutes an important cause of anaemia in chronic diseases. We analysed the relationships between iron deficiency (ID) and the adequacy of endogenous EPO in anaemic heart failure (HF) patients, and the impact of abnormal EPO on 12-month mortality. METHODS AND RESULTS: We investigated 435 anaemic HF patients (age: 74 ± 10 years; males: 60%; New York Heart Association class I or II: 39%; left ventricular ejection fraction: 43 ± 17%). Patients with EPO higher than expected for a given haemoglobin were considered EPO-resistant whereas those with EPO lower than expected - EPO-deficient. ID was defined as serum ferritin <100 µg/L or 100-299 µg/L with transferrin saturation <20%. EPO-resistant patients (22%) had more advanced HF whereas those with EPO deficiency (57%) were more frequently females and had worse renal function. Lower serum ferritin (indicating depleted body iron stores) was related to higher EPO observed/predicted ratio when adjusted for significant clinical confounders, including C-reactive protein. One year all-cause mortality was 28% in patients with EPO resistance compared to 17% in patients with EPO deficiency and 10% in patients with adequate EPO (log-rank test for the comparison EPO resistance vs. adequate EPO: P = 0.02). When adjusted for other prognosticators, there was still a trend towards increased 12-month mortality in patients with higher EPO level. CONCLUSION: Anaemic HF patients with endogenous EPO deficiency vs. resistance have different clinical and laboratory characteristics. In such patients, ID contributes to EPO resistance independently of inflammation.

High soluble transferrin receptor in patients with heart failure: a measure of iron deficiency and a strong predictor of mortality.

AIMS: Iron deficiency (ID) is frequent in heart failure (HF), linked with exercise intolerance and poor prognosis. Intravenous iron repletion improves clinical status in HF patients with left ventricular ejection fraction (LVEF) ≤45%. However, uncertainty exists about the accuracy of serum biomarkers in diagnosing ID. The aims of this study were (i) to identify the iron biomarker with the greatest accuracy for the diagnosis of ID in bone marrow in patients with ischaemic HF, and (ii) to establish the prevalence of ID using this biomarker and its prognostic value in HF patients. METHODS AND RESULTS: Bone marrow was stained for iron in 30 patients with ischaemic HF with LVEF ≤45% and 10 healthy controls, and ID was diagnosed for 0-1 grades (Gale scale). A total of 791 patients with HF with LVEF ≤45% were prospectively followed up for 3 years. Serum ferritin, transferrin saturation, soluble transferrin receptor (sTfR) were assessed as iron biomarkers. Most patients with HF (n = 25, 83%) had ID in bone marrow, but none of the controls (P < 0.001). Serum sTfR had the best accuracy in predicting ID in bone marrow (area under the curve 0.920, 95% confidence interval 0.761-0.987, for cut-off 1.25 mg/L sensitivity 84%, specificity 100%). Serum sTfR was ≥1.25 mg/L in 47% of HF patients, in 56% and 46% of anaemics and non-anaemics, respectively (P < 0.05). The reclassification methods revealed that serum sTfR significantly added the prognostic value to the baseline prognostic model, and to the greater extent than plasma N-terminal pro B-type natriuretic peptide. Based on internal derivation and validation procedures, serum sTfR ≥1.41 mg/L was the optimal threshold for predicting 3-year mortality, independent of other established variables. CONCLUSIONS: High serum sTfR accurately reflects depleted iron stores in bone marrow in patients with HF, and identifies those with a high 3-year mortality.

Exploring the Potential Genetic Heterogeneity in the Incidence of Hoof Disorders in Austrian Fleckvieh and Braunvieh Cattle.

Genetic heterogeneity denotes the situation when different genetic architectures underlying diverse populations result in the same phenotype. In this study, we explore the genetic background underlying differences in the incidence of hoof disorders between Braunvieh and Fleckvieh cattle in the context of genetic heterogeneity between the breeds. Despite potentially higher power of testing due to twice as large sample size, none of the SNPs was significantly associated with the total number of hoof disorders in Fleckvieh, while 15 SNPs were significant in Braunvieh. The most promising candidate genes in Braunvieh were as follows: CBLB on BTA1, which causes arthritis in rats; CAV2 on BTA4, which affects skeletal muscles in mice; PTHLH on BTA5, which causes disease phenotypes related to the skeleton in humans, mice, and zebrafish; and SORCS2 on BTA6, which causes decreased susceptibility to injury in mice. Some of the significant SNPs (BTA1, BTA4, BTA5, BTA13, and BTA16) revealed allelic heterogeneity-i.e., different allele frequencies between Fleckvieh and Braunvieh. Some of the significant regions (BTA1, BTA5, BTA13, and BTA16) correlated to inter-breed differences in linkage disequilibrium (LD) structure and may thus represent false-positive heterogeneity. However, positions on BTA6 (SORCS2), BTA14, and BTA24 mark Braunvieh-specific regions. We hypothesize that the observed genetic heterogeneity of hoof disorders is a by-product of different selection goals defined for the analyzed breeds-toward dairy production in Braunvieh and toward beef production in Fleckvieh. Based on the current dataset, it is not possible to unequivocally confirm or exclude the hypothesis of genetic heterogeneity in the susceptibility to hoof disorders between Fleckvieh and Braunvieh. The main reason for the problem is that the potential heterogeneity was explored through SNP-phenotype associations and not through causal mutations, due to a limited SNP density offered by the SNP-chip. The rationale against genetic heterogeneity comprises a limited power of detection of true associations as well as differences in the length of LD blocks and in linkage phase between breeds. On the other hand, different selection goals defined for the analyzed breeds accompanied by no systematic, genome-wide differences in LD structure between the breeds favor the heterogeneity hypothesis at some smaller genomic regions.

Waste Rubber Pyrolysis: Product Yields and Limonene Concentration.

Tires, conveyor belts, floor mats, and shoe soles form a main-stream of rubber waste. The amount of these used materials continuously increases due to development of the rubber market. Therefore, pro-ecological utilization (i.e., energy recycling instead of burning) and recovering valuable and recyclable materials becomes an urgent necessity. In this regard, this work was devoted to the chemical recycling of selected used rubber products, and it especially explores the possibility of limonene production. Different types of waste rubber were characterized and pyrolyzed at microgram and laboratory scales, and the results were compared. Additionally, the pyrolysis of tires, the most significant stream of rubber waste, was also conducted in a semi-technical scale reactor. The effectiveness of limonene formation in the liquid fractions obtained from different types of waste rubber was compared.

10 year trends in hospitalization rates due to heart failure and related in-hospital mortality in Poland (2010-2019).

AIMS: Heart failure (HF) remains a major public health challenge worldwide. Contemporary epidemiological data on HF hospitalization rates and related in-hospital mortality are scarce also in Poland. The aim of the study was to determine the trends in hospitalization rates due to HF and related in-hospital mortality in Poland in the recent decade. METHODS AND RESULTS: Data on HF hospitalizations and in-hospital mortality in patients aged >17 years in Poland between 2010 and 2019 were obtained from the central database of the Polish National Health Fund. Hospitalizations with either primary or secondary diagnosis of HF were identified using the 10th revision of the International Statistical Classification of Diseases and Related Health Problems codes (I50, I42, J81 with extensions, and R57.0). There were 4 259 698 HF hospitalizations and 608 577 in-hospital deaths (14% in-hospital mortality) reported during 2010-2019 in Poland. During this period, there was a steady increase in the number of HF hospitalizations per 1000 inhabitants in subsequent years, being more pronounced in men than in women (in 2019: 16 and 13 HF hospitalizations per 1000 inhabitants in men and women, respectively). The relative risk of HF hospitalization was higher in men than in women, and this gender-related difference steadily increased from 9% in 2010 to 25% in 2019. During 2010-2019, there was an increase in the number of HF hospitalizations per 1000 inhabitants in subsequent age groups, with a trend being more pronounced in men than in women (129 and 99 HF hospitalizations per 1000 inhabitants in men and women aged ≥80 years, respectively). During this period, there was a slight increase in in-hospital mortality during HF hospitalization in subsequent years, being more pronounced in women than in men (in 2019: 16% and 14% of in-hospital mortality in women and men, respectively). The relative risk of in-hospital mortality during HF hospitalization was higher in women than in men, and this gender-related difference steadily increased from 8% in 2010 to 18% in 2019. During this period, in-hospital mortality during HF hospitalization was ~12% for women and men aged 18-29 years, whereas the highest values of in-hospital mortality reached ~19% for patients aged ≥80 years. CONCLUSIONS: We have observed steady growing trends in HF hospitalization rates and related in-hospital mortality in Poland over the last decade. Both age and gender have differentiated the reported epidemiological patterns.

Correction to: The application of deep learning for the classification of correct and incorrect SNP genotypes from whole-genome DNA sequencing pipelines.

The original version on this paper contained an error. Figure 5 was published with the same image of Fig. 4.