Statistical deviations in the analysis of asphalt mix properties

Glavni je cilj ovog istraživanja pronaći metodu kojom se određuju statistička odstupanja u analizama svojstava asfaltnih mješavina AC 22, koja ne nastaju slučajno, već su uzrokovana vanjskim faktorima poput promjene normi, laboratorijske opreme ili osoblja. Proveden je proračun kako bi se odredila odstupanja koeficijenata korelacije u svojstvima asfaltnih mješavina raspoređenih u dvije skupine. Skupine se odnose na dva vremenska razmaka, a proračun je ponovljen nasumičnim odabirom podataka unutar dviju skupina, kako bi se odredila odstupanja unutar skupina.The main purpose of this research is to establish a method for identifying statistical deviations in the analysis of properties of the asphalt mix AC 22, which are not accidental, but are caused by external factors, such as the change of standards, laboratory equipment, or staff. The analysis was made to determine deviation of correlation coefficients for properties of asphalt mixes divided into two groups. The groups are related to two time intervals, and the computation was repeated by random selection of data within the two groups, so as to determine deviations within the groups

Discovering rare pathological changes in candidate genes for multiple sclerosis

Multipla skleroza (MS) je nevrodegenerativna bolezen z okoljskimi in genetskimi dejavniki tveganja, vendar je njena etiologija slabo razumljena. Izvedene so bile že številne študije s pristopom GWAS (angl. genome-wide association study), vendar potrebujemo zanesljivejše označevalce na podlagi redkih genetskih različic. Z namenom boljšega razumevanja genetskih dejavnikov MS je bilo predhodno izvedeno eksomsko sekvenciranje pri treh skupinah preiskovancev: bolnikih z družinsko obliko MS, bolnikih s sporadično obliko in kontrolni skupini. V analizo smo zajeli različice nukleotidnega zaporedja v 938 genih, ki so bili z MS predhodno povezani s pristopom GWAS. Kriteriji za izbor genskih različic so bili naslednji: 1. frekvenca manj pogostega alela (angl. minor allele frequencyMAF) < 0,05, 2. ocena orodja CADD (angl. Combined annotation dependent depletion) ⡥ 20 ter 3. odsotnost različice v kontrolni skupini in prisotnost pri vsaj eni skupini bolnikov. Tem pogojem je ustrezalo 25 različic nukleotidnega zaporedja v 19 genih. Med njimi je pet genov vsebovalo več kot eno redko različicogen SORBS2 je vseboval tri različice, medtem ko so AGAP2, CLEC16A, ELMO1 in RREB1 vsebovali dve različici. Z orodjema STRING in Enrichr smo ugotovili, da je teh 19 genov obogatenih v bioloških poteh, ki so povezane z MS, imunskim sistemom in avtoimunskimi boleznimi. Pet od 19 genov je povezanih z biološko potjo Wnt, in sicer: AHI1, AGAP2, KCNMA1, TCF7 in TNKS. Z odkrivanjem redkih patoloških različic smo v tej raziskavi izpostavili zanesljivejše kandidatne gene za razvoj MS in s tem prispevali k razvoju diagnostičnih tehnik v prihodnosti. Vlogo kandidatnih genov pri razvoju MS bo potrebno preveriti z dodatnimi funkcionalnimi analizami.Multiple sclerosis (MS) is a neurodegenerative disease of unclear etiology with both environmental and genetic risk factors. Multiple genome wide association studies (GWAS) have been conducted, however it is necessary to identify more reliable disease markers based on rare genetic variants. For the purpose of better understanding its genetic risk factors exome sequencing was conducted beforehand - probands were divided into three groups: patients with familial MS, sporadic MS and the control group. The analysis included nucleotide variants of 938 genes previously associated with MS using GWAS. These genes were analyzed for rare gene variants based on the following criteria: minor allele frequency (MAF) < 0.05, CADD (combined annotation dependent depletion) score ⡥ 20 and absence from the control group with simultaneous presence in at least one group with MS. We determined 25 variants located in 19 genes that fit the criteria. Among them five genes contained more than one rare gene variant – SORBS2 contained three rare variants while AGAP2, CLEC16A, ELMO1 and RREB1 contained two variants each. Using the STRING and Enrichr tools we found that these 19 genes were enriched in biological pathways associated with MS, the immune system and autoimmune diseases. Five of the 19 genes were connected to the Wnt biological pathway: AHI1, AGAP2, KCNMA1, TCF7 and TNKS. With the discovery of rare pathological variants we have contributed to the understanding of MS\u27 genetic components and with it to the development of potential future diagnostic methods. The role of candidate genes in the development of MS requires further research via functional analyses

Shared genetic risk factors between cancer and cardiovascular diseases

Cancer and cardiovascular diseases (CVD) account for approximately 27.5 million deaths every year. While they share some common environmental risk factors, their shared genetic risk factors are not yet fully understood. The aim of the present study was to aggregate genetic risk factors associated with the comorbidity of cancer and CVDs. For this purpose, we: (1) created a catalog of genes associated with cancer and CVDs, (2) visualized retrieved data as a gene-disease network, and (3) performed a pathway enrichment analysis. We performed screening of PubMed database for literature reporting genetic risk factors in patients with both cancer and CVD. The gene-disease network was visualized using Cytoscape and the enrichment analysis was conducted using Enrichr software. We manually reviewed the 181 articles fitting the search criteria and included 13 articles in the study. Data visualization revealed a highly interconnected network containing a single subnetwork with 56 nodes and 146 edges. Genes in the network with the highest number of disease interactions were JAK2, TTN, TET2, and ATM. The pathway enrichment analysis revealed that genes included in the study were significantly enriched in DNA damage repair (DDR) pathways, such as homologous recombination. The role of DDR mechanisms in the development of CVDs has been studied in previously published research; however, additional functional studies are required to elucidate their contribution to the pathophysiology to CVDs

MicroRNA-target interaction regulatory network in Alzheimer’s disease

Alzheimer’s Disease (AD) is a progressive neurodegenerative disorder and the most common cause of dementiahowever, early diagnosis of the disease is challenging. Research suggests that biomarkers found in blood, such as microRNAs (miRNA), may be promising for AD diagnostics. Experimental data on miRNA–target interactions (MTI) associated with AD are scattered across databases and publications, thus making the identification of promising miRNA biomarkers for AD difficult. In response to this, a list of experimentally validated AD-associated MTIs was obtained from miRTarBase. Cytoscape was used to create a visual MTI network. STRING software was used for protein–protein interaction analysis and mirPath was used for pathway enrichment analysis. Several targets regulated by multiple miRNAs were identified, including: BACE1, APP, NCSTN, SP1, SIRT1, and PTEN. The miRNA with the highest numbers of interactions in the network were: miR-9, miR-16, miR-34a, miR-106a, miR-107, miR-125b, miR-146, and miR-181c. The analysis revealed seven subnetworks, representing disease modules which have a potential for further biomarker development. The obtained MTI network is not yet complete, and additional studies are needed for the comprehensive understanding of the AD-associated miRNA targetome

MicroRNAs in leukemias

Leukemias are a group of malignancies of the blood and bone marrow. Multiple types of leukemia are known, however reliable treatments have not been developed for most leukemia types. Furthermore, even relatively reliable treatments can result in relapses. MicroRNAs (miRNAs) are a class of short, noncoding RNAs responsible for epigenetic regulation of gene expression and have been proposed as a source of potential novel therapeutic targets for leukemias. In order to identify central miRNAs for leukemia, we conducted data synthesis using two databases: miRTarBase and DISNOR. A total of 137 unique miRNAs associated with 16 types of leukemia were retrieved from miRTarBase and 86 protein-coding genes associated with leukemia were retrieved from the DISNOR database. Based on these data, we formed a visual network of 248 miRNA-target interactions (MTI) between leukemia-associated genes and miRNAs associated with ≥4 leukemia types. We then manually reviewed the literature describing these 248 MTIs for interactions identified in leukemia studies. This manually curated data was then used to visualize a network of 64 MTIs identified in leukemia patients, cell lines and animal models. We also formed a visual network of miRNA-leukemia associations. Finally, we compiled leukemia clinical trials from the ClinicalTrials database. miRNAs with the highest number of MTIs were miR-125b-5p, miR-155-5p, miR-181a-5p and miR-19a-3p, while target genes with the highest number of MTIs were TP53, BCL2, KIT, ATM, RUNX1 and ABL1. The analysis of 248 MTIs revealed a large, highly interconnected network. Additionally, a large MTI subnetwork was present in the network visualized from manually reviewed data. The interconnectedness of the MTI subnetwork suggests that certain miRNAs represent central disease molecules for multiple leukemia types. Additional studies on miRNAs, their target genes and associated biological pathways are required to elucidate the therapeutic potential of miRNAs in leukemia

Towards a Multi-Omics of Male Infertility

Infertility is a common problem affecting one in six couples and in 30% of infertile couples, the male factor is a major cause. A large number of genes are involved in spermatogenesis and a significant proportion of male infertility phenotypes are of genetic origin. Studies on infertility have so far primarily focused on chromosomal abnormalities and sequence variants in protein-coding genes and have identified a large number of disease-associated genes. However, it has been shown that a multitude of factors across various omics levels also contribute to infertility phenotypes. The complexity of male infertility has led to the understanding that an integrated, multi-omics analysis may be optimal for unravelling this disease. While there is a vast array of different factors across omics levels associated with infertility, the present review focuses on known factors from the genomics, epigenomics, transcriptomics, proteomics, metabolomics, glycomics, lipidomics, miRNomics, and integrated omics levels. These include: repeat expansions in AR, POLG, ATXN1, DMPK, and SHBG, multiple SNPs, copy number variants in the AZF region, disregulated miRNAs, altered H3K9 methylation, differential MTHFR, MEG3, PEG1, and LIT1 methylation, altered protamine ratios and protein hypo/hyperphosphorylation. This integrative review presents a step towards a multi-omics approach to understanding the complex etiology of male infertility. Currently only a few genetic factors, namely chromosomal abnormalities and Y chromosome microdeletions, are routinely tested in infertile men undergoing intracytoplasmic sperm injection. A multi-omics approach to understanding infertility phenotypes may yield a more holistic view of the disease and contribute to the development of improved screening methods and treatment options. Therefore, beside discovering as of yet unknown genetic causes of infertility, integrating multiple fields of study could yield valuable contributions to the understanding of disease development. Future multi-omics studies will enable to synthesise fragmented information and facilitate biomarker discovery and treatments in male infertility

Cystatin C deficiency suppresses tumor growth in a breast cancer model through decreased proliferation of tumor cells

Cysteine cathepsins are proteases that, in addition to their important physiological functions, have been associated with multiple pathologies, including cancer. Cystatin C (CstC) is a major endogenous inhibitor that regulates the extracellular activity of cysteine cathepsins. We investigated the role of cystatin C in mammary cancer using CstC knockout mice and a mouse model of breast cancer induced by expression of the polyoma middle T oncoprotein (PyMT) in the mammary epithelium. We showed that the ablation of CstC reduced the rate of mammary tumor growth. Notably, a decrease in the proliferation of CstC knockout PyMT tumor cells was demonstrated ex vivo and in vitro, indicating a role for this protease inhibitor in signaling pathways that control cell proliferation. An increase in phosphorylated p-38 was observed in CstC knockout tumors, suggesting a novel function for cystatin C in cancer development, independent of the TGF-β pathway. Moreover, proteomic analysis of the CstC wild-type and knockout PyMT primary cell secretomes revealed a decrease in the levels of 14-3-3 proteins in the secretome of knock-out cells, suggesting a novel link between cysteine cathepsins, cystatin C and 14-3-3 proteins in tumorigenesis, calling for further investigations

Association of impaired renal function with changes in urinary mineral excretion and stone composition

Objective: To investigate the effect of kidney function on stone composition and urinary mineral excretion in patients undergoing surgical intervention for nephrolithiasis. Methods: Using our institutional kidney stone database, we performed a retrospective review of stone patients who underwent surgical intervention between 2004 and 2015. Patients\u27 demographic information, 24-hour urinary mineral excretion, and stone characteristics were reported. The patients\u27 estimated glomerular filtration rates (eGFR) were compared with their stone compositions and 24-hour urine mineral excretions. Results: A statistically significant difference was noted between the groups, with uric acid stones being associated with lower eGFR and calcium phosphate stones associated with higher eGFR. No relationship could be demonstrated between eGFR and calcium oxalate or struvite stones. Patients with lower eGFR also demonstrated a statistically significant association with lower urinary pH as well as lower urinary excretion of calcium and citrate. Conclusion: While various factors have been found to play significant roles in kidney stone formation and composition, our findings demonstrate a definite relationship between these and renal function. This paper highlights the fact that renal function evaluation should be considered an important component in the evaluation, counseling, and management of patients with nephrolithiasis