Biology subjects

Korner, A.

Publications and source records attributed to Korner, A..

3 recordsLinked to original sources

bioRxiv2024

Early body weight gain in TALLYHO/JngJ mice predicts adult diabetic phenotype, mimicking childhood obesity

Childhood obesity and type 2 diabetes are two emerging health issues worldwide. To analyze their underlying causes and develop prevention strategies, mouse models are urgently needed. We present novel insights into the polygenic TALLYHO/JngJ mouse model for diabetes. By precisely analyzing our original phenotypic data, we discovered that body weight at weaning age is the main predictor of the adult phenotype in TALLYHO/JngJ mice. The higher the weaning weight of male mice, the more likely they are to develop diabetes later in life. In contrast, a low weaning weight protected against the development of the diabetic phenotype in adults. In females, we found that high weaning body weights led to a constant higher body weight throughout life. We also showed that specifically the suckling period, rather than the in utero period, is crucial for the development of the metabolic phenotype in later life. We observed an earlier onset of diabetes when the mice had higher body weights at weaning, aligning with metabolic histories observed in humans. Therefore, we recommend TALLYHO/JngJ mice as a model to investigate childhood obesity and to develop prevention strategies. HighlightsO_LIThe polygenic TALLYHO/JngJ mouse model is used to investigate type 2 diabetes, but the penetrance of the phenotype is highly variable. C_LIO_LIWe deeply analyzed our phenotype data and find that body weight at the age of weaning (BWW) is the main predictor for the obese and diabetic phenotype in TALLYHO/JngJ male mice later in life. C_LIO_LIWe suggest that TALLYHO/JngJ male mice are an excellent and urgently needed model to study childhood obesity. C_LIO_LIOur data help the relevant scientific community to better control the penetrance of the diabetic phenotype in male TALLYHO/JngJ mice. C_LI

physiology↗

bioRxiv2023

Human subcutaneous and visceral adipocyte atlases uncover classical and specialized adipocytes and depot-specific patterns

Human adipose depots are functionally distinct. Yet, recent single-nucleus RNA-sequencing (snRNA-seq) analyses largely uncovered overlapping/similar cell-type landscapes. We hypothesized that adipocytes subtypes, differentiation trajectories, and/or intercellular communication patterns could illuminate this depot similarity-difference gap. For this, we performed snRNA-seq of human subcutaneous and visceral adipose tissue. Whereas the majority of adipocytes in both depots were classical, namely enriched in lipid metabolism pathways, we also observed specialized adipocyte subtypes that were enriched in immune-related, extracellular matrix deposition (fibrosis), vascularization/angiogenesis, or ribosomal processes. Pseudo-temporal analysis suggested a developmental trajectory from adipose progenitor cells to classical adipocytes via specialized adipocytes, suggesting that the classical state stems from loss, rather than gain, of specialized functions. Lastly, intercellular communication routes were consistent with the different inflammatory tone of the two depots. Jointly, these findings provide a high-resolution view into the contribution of cellular composition, differentiation, and intercellular communication patterns to human fat depot differences.

systems biology↗

bioRxiv2022

Quantum analysis of P3a and P3b from auditory single trial ERPs differentiates borderline personality disorder from schizophrenia

Traditional approaches to EEG modelling use the methods of classical physics to reconstruct scalp potentials in terms of explicit physical models of cortical neuron ensembles. The principal difficulty is that the multiplicity of cellular processes with an intricate array of deterministic and random factors prevents creation of consistent biophysical parameter sets. An original, empirically-testable solution has been recently achieved in our previous studies by a radical departure from the deterministic equations of classical physics to the probabilistic reasoning of quantum mechanics. This crucial step relocates elementary bioelectric sources of EEG signals from the cellular to the molecular level where positively and negatively ions are considered as elementary sources of electricity. The rationale is that despite dramatic differences in cellular machineries, statistical factors governed by the rules of central limit theorem produce EEG waveforms as a statistical aggregate of the synchronized activity of multiple closely-located microscale sources. Using the formalism of nonhomogeneous birth-and-death processes (BDP) the quantum models of microscale events are deduced and linked to the dynamics of macroscale EEG waveforms. This study expands these methods with new features for comprehensive analysis of event related potentials directly from single trials, i.e. the EEG segments which are closely related in timing to cognitive events. We derive a universal model of the components of single trial ERPs both in frequency and time domains. This, for the first time, enables us to quantify all significant cognitive components in single trial ERPs, providing an alternative to the traditional method of averaging. Given P300 as an important objective marker of psychiatric disorders, a methodology which reliably discloses the component compositions of this potential, may have specific diagnostic importance. In this study, reliable identification of the P3a and P3b components from an auditory oddball paradigm provided a means of differentiating borderline personality disorder from schizophrenia.

neuroscience↗