Incidence trends in childhood onset IDDM in four countries around the Baltic sea during 1983-1992

Funding Information: Acknowledgements. This study was partly supported by theWe present secular trends of childhood onset insulin-dependent diabetes mellitus (IDDM) in Finland, Estonia, Latvia and Lithuania during the period of 1983-1992. Incidence data were obtained from the national IDDM registries. The average age-standardized incidence per 100,000/year was 35.0 in Finland, followed by 10.2 in Estonia, 7.1 in Lithuania and 6.5 in Latvia. A male excess in incidence was recorded in Finland (1.15) and Latvia (1.01). In all countries, the highest age-specific risk of IDDM was observed in the 11-13 year age range. The large difference in incidence between Finland and other Baltic countries was seen even in 1-2-year-old children. During the 10-year study period overall changes in incidence of IDDM were relatively small in these four countries. The incidence increased in Finland and Lithuania on average by 1% and 1.4% per year, respectively. A statistically significant increase was recorded only in 0-4 year old children in Finland, at 5.6% per year. In Estonia, an 8.3% increase in this age group, however, was not statistically significant The different trends in the age-group specific incidence rates were confirmed in Finland. In conclusion, from 1983 to 1992 the incidence of childhood onset IDDM was increasing in Finland and Lithuania, while in Latvia and Estonia it was stable. There are still great differences in IDDM incidence between the countries around the Baltic Sea.Peer reviewe

The impact of maternal high-fat diet on offspring neurodevelopment

A maternal high-fat diet affects offspring neurodevelopment with long-term consequences on their brain health and behavior. During the past three decades, obesity has rapidly increased in the whole human population worldwide, including women of reproductive age. It is known that maternal obesity caused by a high-fat diet may lead to neurodevelopmental disorders in their offspring, such as autism spectrum disorder, attention deficit hyperactivity disorder, anxiety, depression, and schizophrenia. A maternal high-fat diet can affect offspring neurodevelopment due to inflammatory activation of the maternal gut, adipose tissue, and placenta, mirrored by increased levels of pro-inflammatory cytokines in both maternal and fetal circulation. Furthermore, a maternal high fat diet causes gut microbial dysbiosis further contributing to increased inflammatory milieu during pregnancy and lactation, thus disturbing both prenatal and postnatal neurodevelopment of the offspring. In addition, global molecular and cellular changes in the offspring’s brain may occur due to epigenetic modifications including the downregulation of brain-derived neurotrophic factor (BDNF) expression and the activation of the endocannabinoid system. These neurodevelopmental aberrations are reflected in behavioral deficits observed in animals, corresponding to behavioral phenotypes of certain neurodevelopmental disorders in humans. Here we reviewed recent findings from rodent models and from human studies to reveal potential mechanisms by which a maternal high-fat diet interferes with the neurodevelopment of the offspring

Effect of nanoscale curvature sign and bundle structure on supercritical H2 and CH4 adsorptivity of single wall carbon nanotube

The adsorptivities of supercritical CH(4) and H(2) of the external and internal tube walls of single wall carbon nanotube (SWCNT) were determined. The internal tube wall of the negative curvature showed the higher adsorptivities for supercritical CH(4) and H(2) than the external tube wall of the positive curvature due to their interaction potential difference. Fine SWCNT bundles were prepared by the capillary force-aided drying treatment using toluene or methanol in order to produce the interstitial pore spaces having the strongest interaction potential for CH(4) or H(2); the bundled SWCNT showed the highest adsorptivity for supercritical CH(4) and H(2). It was clearly shown that these nanostructures of SWCNTs are crucial for supercritical gas adsorptivity.ArticleADSORPTION-JOURNAL OF THE INTERNATIONAL ADSORPTION SOCIETY. 17(3):643-651 (2011)journal articl

Neringa Urbonaite's Quick Files

The Quick Files feature was discontinued and it’s files were migrated into this Project on March 11, 2022. The file URL’s will still resolve properly, and the Quick Files logs are available in the Project’s Recent Activity

Tracking Single Cell Lineages in Saccharomyces Cerevisiae

The ability to measure the number of gene-specific mRNA molecules in individual mammalian cells has transformed the transcriptomics field. Among the key technologies enabling single-cell mRNA sequencing has been Droplet Sequencing (Drop-Seq). While this method works efficiently for mammalian cells, its direct application to yeast cells has been problematic due to cell-type specific differences such as size, doublet formation rate, and cell wall. Here we introduce yeast DropSeq, a single-cell RNA sequencing method for the study of transcriptomics in yeast. I modified and optimized the original Drop-Seq method to address the issues that emerged from smaller cell sizes and the presence of the cell wall. I also quantified the rate of doublet formation through a species-mixing experiment. As proof-of-principle application of yeast DropSeq, I investigated the transcriptomic effects of mycophenolic acid (MPA), a lifespan-extending compound that decreases de novo GMP synthesis. I compared transcript levels between cells treated with MPA and cells treated with DMSO and/or guanine, MPA’s epistatic agent. I discovered that isogenic populations of yeast cells contain transcriptionally distinct subpopulations in all treatment conditions excluding MPA-treated cells. I found that cells treated with MPA experience an upregulation of genes coding for proteins involved in antioxidation, pre-RNA processing, translation initiation, tRNA synthetase and tRNA methyltransferase, histone and nucleosome assembly, and ribosome component transport. Conversely, a downregulation of mRNA expression was observed for genes encoding the 40S and 60S ribosomal subunits, and for genes involved in mitochondrial function. Yeast DropSeq will accelerate biological discovery by facilitating droplet-based transcriptomics of yeast cells.Additionally, I present the development of a lineage tracking cell barcoding mechanism. This tracking mechanism, termed the dynamic barcode, relies on a CRISPR-based system that targets itself to introduce changes. The components of the system include a Cas9 protein tagged with an estrogen-binding domain to control localization and a self-excising and self-targeting gRNA cassette that can be placed under an mRNA promoter. The self-excising (RGR) system allows the gRNA to be expressed under an mRNA, RNA polII promoter, and the self-targeting (stg) system allows the gRNA to target itself and produce progressive changes in its sequence. The goal of this system is to make progressive cuts in its target sequence (itself) over time to mark changes in cells that would allow for the tracking of their ages. I induce cutting in the system and show all the possible changes, both insertions and deletions, that are made using traditional sequencing of single colonies. With further modifications, such as extending the length of the self-targeting region, this system will allow for the tracking of multiple generations over a period of time. Ultimately, this system will be combined with a daughter-specific promoter, such that the self-targeting and self-excising gRNA will target and cut itself only in daughter cells. This will allow only daughter cells to accumulate changes in the dynamic barcode, with the youngest cells accruing the most changes. This dynamic barcode could therefore be used to determine ages of cells within a culture

Evaluation of non-pharmaceutical intervention effectiveness in Covid-19 pandemic by using excess mortality metric

INTRODUCTION: The study focuses on finding a methodology for evaluating the effectiveness of the nonpharmaceutical intervention in the face of a new pathogen entering the population. Different interventions can have different effectiveness levels in different populations; thus, studying possible correlations and effectiveness among different groups is essential. With better knowledge of the topic, the outbreak management could be done more cost-effectively, reducing the need for antibiotics, vaccines, and possible reduction of infectious diseases caused burden in developing regions. Furthermore, the study aims to determine the ways of using excess mortality as an evaluation technique for nonpharmaceutical interventions used in the Covid-19 pandemic.  METHOD: The variables in time-series format were used to calculate a cross-correlation score alongside other correlation coefficient tests. With the cross-correlation, the lag will be established to estimate how the variables correlate in the timeline. In addition, the study will attempt to establish the connections between different nonpharmaceutical interventions and their strengths and different age groups. RESULTS: The most frequent lag scores identified were 1 with 16 observations and 2 with 9 observations. The highest lag score was 4, which was observed once for the dataset of Hungary. The correlation between excess mortality and different harshness of NPI's was calculated. The correlation coefficient ranges from -0.3 to -0.39, indicating an overall low to medium correlation. The highest correlation was detected with stay-at-home requirements (-0.36), workplace closing (-0.37), and gathering restrictions (-0.39). In the final step, age-based correlations were established. The correlation ranged from 0.26 – 0.36, indicating an overall medium correlation. The lowest correlation can be seen in the youngest age group, 15-64 (correlation coefficient of 0.26), while the highest correlation of 0.36 can be seen in the 75-84 age group. Surprisingly the age group 85+ had a little lower correlation than the 75-84 age group. DISCUSSION AND CONCLUSIONS: A stronger correlation between excess mortality and stringency index was detected in the countries with a higher death per capita. The two groups of intervention effectiveness were established: more effective (school closing, workplace closing, public event limitation, gathering restriction, and stay at home requirement) and less effective (public transport limitation, restriction on internal movement, international travel control, public information campaigns, protection of elderly campaigns). This suggests that NPI effectiveness depends on population size. In the age-group-based analysis, the correlation became stronger with the age increase, indicating nonpharmaceutical intervention effectiveness against high mortality in older adults.