Search

BackgroundDepressive symptom, a pervasive mental health disorder, has garnered increasing attention due to its intricate interconnections with various physiological processes. One emerging avenue of investigation delves into the potential association between depressive symptom and Homeostasis Model Assessment of Insulin Resistance (HOMA-IR), a parameter reflecting insulin resistance. The intricate interplay between these two domains holds promising implications for understanding the multifaceted nature of depressive symptom and its impact on metabolic health.MethodsWe used weighted multivariable logistic regression models with subgroup analysis to explore the relationship between depressive symptom and homeostasis model assessment of insulin resistance. Non-linear correlations were explored using fitted smoothing curves. Then, we constructed a two-piece linear regression model and performed a recursive algorithm to calculate the inflection point.ResultsThe study included 20,282 participants in the United States. In the regression model adjusted for all confounding variables, the odds ratio (OR) for the correlation between depressive symptom and the Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) was 1.01 (95% CI: 1.00, 1.01). However, a significant discrepancy between trend tests and regression analyses suggests a potential non-linear relationship between depressive symptom and the assessment of insulin resistance using the Homeostasis Model. Constrained cubic spline analysis confirmed this non-linear relationship, identifying an inflection point at 10.47. Before the inflection point, depressive symptom exhibited a significantly positive correlation with the assessment of insulin resistance using the Homeostasis Model. However, after the inflection point, a negative correlation was observed, though it did not reach statistical significance.ConclusionWe found a curve-like relationship between depressive symptom and homeostasis model assessment of insulin resistance.

IntroductionFatty liver disease is potentially linked to chronic kidney disease (CKD), yet the association between the Framingham Steatosis Index (FSI) and CKD remains uncharted. Our study thoroughly investigated the correlation between FSI and CKD, aiming to elucidate the underlying links between these two conditions.MethodsThe relationship between FSI and CKD was evaluated using a weighted multivariate logistic regression model, and the curvilinear relationship between FSI and CKD was explored through smooth curve fitting. We engaged a recursive partitioning algorithm in conjunction with a two-stage linear regression model to determine the inflection point. By conducting stratified analyses, the heterogeneity within subpopulations was explored.ResultsIn the fully adjusted Model 3, which accounted for all covariates, the odds ratios (ORs) (95% CI) for the association between FSI and CKD were 1.01 (0.97, 1.06), indicating no significant statistical association. Sensitivity analysis confirms the stability of the relationship between FSI and CKD. Smooth curve fitting discloses a non-linear association between FSI and CKD. The two-piecewise linear regression model, applied to explore this non-linearity, identified an inflection point at an FSI value of −3.21. Below this threshold, the OR (95% CI) was 0.25 (0.17, 0.37), signifying an inverse correlation between FSI and CKD. Above the inflection point, the OR (95% CI) was 1.19 (1.13, 1.25), suggesting a positive correlation. In the stratified curve analysis, the results were essentially consistent with the overall findings, except for the subgroups with BMI > 30 and age > 50.ConclusionWe found a curvilinear relationship between FSI and CKD.

Light is one of the most critical stimuli in the majority of living organisms. In the last two decades, blue light (BL) has become a major subject of attention because of developments in light-emitting diodes (LED). The effects of BL on eukaryotic organisms and phototrophic prokaryotes have been well studied, but the knowledge of its effects on non-phototrophic prokaryotes remains unclear. Since BL can penetrate seawater, it is expected that most prokaryotes living in the ocean possess molecular mechanisms which protect against BL. The aim of this study is to assess the molecular mechanisms of Vibrio parahaemolyticus cells against BL as a marine bacterial model compared to other wavelength light exposures. Physiological and transcriptomic analyses of BL-exposed cells compared to other light treated cells revealed the highest ROS fold change, the highest number of differentially expressed genes (DEGs), and up-regulation in the gene responsible to not only compatible solute such as glycine betaine and ectoine but also iron-sulfur biosynthesis related to ROS formation. Furthermore, red light (RL) up-regulated the expression of cryptochrome DASH, a protein known to be excited by BL, and orange light (OL) decreased the expression of thermostable direct hemolysin (TDH), suggesting that OL attenuates the virulence of V. parahaemolyticus. In addition, the expression of VtrA (V. parahaemolyticus type III secretion system 2 (T3SS2) regulator A) but not VtrB (V. parahaemolyticus T3SS2 regulator B) increased under both light treatments, indicating that light exposure is unlikely to be involved in T3SS2-mediated pathogenicity. These results expand our knowledge on unique light responses in non-phototrophic marine prokaryotes.

Vibrionaceae is one of the most diverse bacterial families and is currently classified into over 50 clades, some members of which play an important role in the symbiotic relationships with humans and animals. Halioticoli clade, which currently consists of 10 species: 8 species associated with the gut of abalone (symbiotic), 1 species (V. breoganii) from bivalves, and 1 species (V. ishigakensis) from subtropical seawater (planktonic). To accelerate studies in the evolution, ecogenomics, and biotechnology of Halioticoli clade species, the genomic backbones and pangenome analyses based on complete genome sequences are needed. Genome sizes of Halioticoli clade species ranged from 3.5 Mb to 4.8 Mb, with V. ishigakensis the biggest. The evolutionary relationships using multilocus sequence analysis based on eight housekeeping genes and 125 single-copy core genes revealed a division of five sub-clades in this clade; 1) V. breoganii, V. comitans, V. inusitatus and V. superstes, 2) V. ezurae, V. neonatus, and V. halioticoli, 3) V. rarus, 4) V. gallicus, and 5) V. ishigakensis. The pan-genomic analysis combined with function and metabolism estimations showed that the planktonic group (sub-clade 5) contained the greatest number of specific genes, and more genes responsible for carbohydrate metabolisms, especially the genes encoding D-galactonate degradation. These results demonstrated that the genome expanded by acquiring more abilities for utilizing various carbohydrates during the evolution from symbiotic to a planktonic lifestyle. Moreover, according to Carbohydrate-Active enZYmes (CAZy) profiling, genes encoding alginate degrading enzymes (aly), classified into PL6, PL7, PL15, and PL17 were common in the ten genomes, but sub-clade 1 had the most. Meanwhile, sub-clade 1and 5 also possessed abundant genes related to macroalgae substrates degradation (GHs), which are also responsible for the genome expansion of sub-clade 1 and 5.