Automated Organization ProfileMedical University of Bialystok
Medical University of Bialystok
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets in this organization
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the organization's datasets
Total Mentions
Total mentions of the organization's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 9.3 (sum of 6 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
The repository contained analytical results of samples from 20 patients diagnosed with HGSOC. A file detailing the range of analyses performed using panel testing to identify somatic variants, as well as a list of genes selected for WES testing to identify germline variants, was also included. Subsequent files contained a list of variants detected.
Authors
- Bukłaho, Patrycja Aleksandra ;
- Kiśluk, Joanna ;
- Bauer, Witold ;
- Nikliński, Jacek
The repository contained analytical results of samples from 20 patients diagnosed with HGSOC. A file detailing the range of analyses performed using panel testing to identify somatic variants, as well as a list of genes selected for WES testing to identify germline variants, was also included. Subsequent files contained a list of variants detected.
Authors
- Bukłaho, Patrycja Aleksandra ;
- Kiśluk, Joanna ;
- Bauer, Witold ;
- Nikliński, Jacek
The database includes data of patients derived from the population-based Bialystok PLUS Study. Randomized individuals were stratified into two groups, those with age-related macular degeneration (AMD-1 group) or without age-related macular degeneration (AMD-0 group). Using a cutoff value of −1.0 to identify low bone mass, participants with femoral bone mineral density T-scores above −1.0 were assigned to the normal reference, and those with T-scores below −1.0 were assigned to the osteopenia category.
Authors
- Kamiński, Karol
The prupose of the single scientific activity was gain knowledge about the influence of cannabigerol on the extracellular matrix (ECM) composition in primary rat hepatocytes with the fibrotic changes induced by palmitate and fructose. This dataset contains the results of determination of concentration-dependent effects of cannabigerol on the ECM composition. The specific goals of this scientific activity included the role of this phytocannabinoids as a potential therapeutic compound in the treatment of liver structure and function disorders related to the fibrosis process.This research was funded by the National Science Center (Poland) (NCN), project entitled "The influence of cannabigerol on the content of hepatocytes’ extracellular matrix proteins in the fibrosis process induced by palmitate and fructose", MINIATURA-6, no. 2022/06/X/NZ3/00542.Data deposited in the repository was saved in .csv format.The files named "ELISA_determinations", "Western_blot_determinations" and "PCR_determinations" contain data related to the publication by Sztolsztener K, Konstantynowicz-Nowicka K, Pędzińska-Betiuk A, Chabowski A. "Concentration-Dependent Attenuation of Pro-Fibrotic Responses after Cannabigerol Exposure in Primary Rat Hepatocytes Cultured in Palmitate and Fructose Media", Cells. 2023 Sep 9;12(18):2243. doi: 10.3390/cells12182243, which is the result of the implementation of the MINIATURA-6 scientific activity.See README.txt file for details on data.
Authors
- Sztolsztener, Klaudia
Background: Infection with human immunodeficiency virus type 1 (HIV) typically results from transmission of a small and genetically uniform viral population. Following transmission, the virus population becomes more diverse because of recombination and acquired mutations through genetic drift and selection. Viral intrahost genetic diversity remains a major obstacle to the cure of HIV; however, there is a disagreement whether intrahost viral genetic diversification associates positively or negatively with disease progression and progression markers. Viral load is a key progression marker and understanding its relationship to viral intrahost genetic diversity could help design future strategies for HIV monitoring and treatment. Methods: We analyzed deep-sequenced viral genomes from 2,650 treatment-naive HIV-infected persons to measure the intrahost genetic diversity of 2,447 genomic codon positions as calculated by Shannon entropy. We tested for associations between viral load (VL) and amino acid (AA) entropy accounting for sex, age, race, duration of infection, and HIV population structure. Results: We confirmed that the intrahost genetic diversity is highest in the env gene. Furthermore, we showed that mean Shannon entropy is significantly associated with VL, especially in infections of >24 months duration. We identified 16 significant associations between VL (p-value<2.0x10-5) and Shannon entropy at AA positions which in our association analysis explained 13% of the variance in VL. Conclusions: Our results elucidate that viral intrahost genetic diversity is associated with VL and could be used as a better disease progression marker than HIV consensus sequence variants, especially in infections of longer duration. We emphasize that viral intrahost diversity should be considered when studying viral genomes and infection outcomes.
Authors
- Gabrielaite, Migle ;
- Bennedbæk, Marc ;
- Rasmussen, Malthe Sebro ;
- Kan, Virginia ;
- Furrer, Hansjakob ;
- Flisiak, Robert ;
- Losso, Marcelo ;
- Lundgren, Jens D. ;
- Marvig, Rasmus L.
Data used in the paper submitted to BMC Geriatrics, Wojszel ZB & Kasiukiewicz A, 2019, "A retrospective cross-sectional study of type 2 diabetes overtreatment in patients admitted to the geriatric ward" Abstract Background: Glycemic control targets in older patients should be individualized according to functional status and comorbidities. The aim of the study was to identify high-risk patients who had evidence of tight glycemic control and thus at risk of serious hypoglycemia. Methods: Retrospective cross-sectional study of type 2 diabetes patients admitted to the geriatric ward receiving diabetes medications. Patients’ hospital records were analyzed. The high risk of hypoglycemia group constituted patients who were aged 80+ years, diagnosed with dementia, with end- stage renal disease, or with a history of macrovascular complications. The primary outcome measure was hemoglobin A1C (HbA1C)≤7.0% [53mmol/mol]. Results: 213 patients were included (77.5% women; 49.3% 80+ year-old). 65.3% received sulfonylurea, 39,4%- metformin, 32.9% insulin, and 4.2%- acarbose (in 61.5% as monotherapy, and in 38.5% combination therapy). We identified 130 patients (60%) as the denominator for the primary outcome measure; 73.1% had a HbA1C value ≤7.0% [53.3mmol/mol], but 55.4% ≤6,5% [48.8mmol/mol], and 40.8% ≤6.0% [42mmol/mol]. Conclusions: The results show a very high rate of tight glycemic control in older patients admitted to the geriatric ward, for whom higher HbA1C targets are recommended. This indicates the high probability of diabetes overtreatment in this group, associated with a high risk of recurrent hypoglycemia. This is all the more likely because most of them received medications known to cause hypoglycemia. This points to the need of paying more attention to specific difficulties in diabetes treatment in older people, especially those suffering from various geriatric syndromes and diseases worsening their prognosis.
Authors
- Wojszel, Zyta ;
- Kasiukiewicz, Agnieszka