Publications by authors named "K Podsiadlo"

Background: Functional gastrointestinal disorders (FGIDs), now known as disorders of gut-brain interaction (DGBIs), such as Irritable Bowel Syndrome (IBS) and Functional Dyspepsia (FD), significantly impact global health, reducing quality of life and burdening healthcare systems. This study addresses the epidemiological gap in Poland, focusing on the West Pomeranian Voivodeship.

Methods: We conducted a cross-sectional study of 2070 Caucasian patients (58.

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The aim of this study was to investigate the relationship between gut microbiota and major depressive disorder (MDD) and schizophrenia (SCZ) by comparing 36 inpatients with these conditions to 29 healthy controls (HC) matched for age, sex, and body mass index (BMI). Individuals with SCZ exhibited greater microbiota richness compared to HC (FDR P(Q)=0.028).

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There is now substantial evidence that zinc-finger proteins are implicated in adiposity. Aims were to datamine for high-frequency (near-neutral selection) pretermination-codon (PTC) single-nucleotide polymorphisms (SNPs; n = 141) from a database with > 550,000 variants and analyze possible association with body mass index in a large Polish sample (n = 5757). BMI was regressed (males/females together or separately) against genetic models.

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Objectives: Probiotics are known to regulate host metabolism. The aim of this study was to assess whether interventions with a multi-strain probiotic formula affect fecal short-chain fatty acids (SCFAs).

Methods: The analysis was carried out in 56 obese, postmenopausal women randomized to three groups: probiotic dose 2.

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Bernstein fits implemented into R allow another route for Kruskal-Wallis power-study tool development. Monte-Carlo Kruskal-Wallis power studies were compared with measured power, a Monte-Carlo ANOVA equivalent and with an analytical method, with or without normalization, using four simulated runs, each with 60-100 populations (each population with N = 30,000 from a set of Pearson-type ranges): random selection gave 6300 samples analyzed for predictive power. Three medical-study datasets (Dialysis/systolic blood pressure; Diabetes/sleep-hours; Marital-status/high-density-lipoprotein cholesterol) were also analyzed.

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