Biology subjects

Ziegler, D.

Publications and source records attributed to Ziegler, D..

10 recordsLinked to original sources

bioRxiv2026

Individualized brain-body signatures of positive emotions revealed by large-scale multimodal neurophysiological recording

Using one of the most comprehensive multimodal biosensing datasets in affective research, densely sampled within individuals, we asked how emotions are instantiated in each person's brain and body. Four participants viewed 168 emotion-evoking videos during 128-channel EEG and 28 autonomic, ocular and facial recordings. Cross-validated elastic-net classifiers distinguished each of 15 positive and neutral emotions from baseline in every participant (mean accuracy 87-97%). We found that no emotion was predicted by a single marker and each reflected a multimodal ensemble of cortical and autonomic activity whose composition was largely person-specific. Yet physiology-derived groupings converged selectively with self-report; Interest-Awe-Amusement-Satisfaction and Entrancement-Aesthetic Appreciation recurred across individuals based on physiology. Across emotion groups, frontal and posterior delta, posterior alpha and electrodermal activity formed a shared backbone, plausibly reflecting affective and sensory engagement, whereas cardiovascular and facial signals varied between people. This framework yields individualized, objective neurophysiological indicators of emotion, potentially aiding personalized diagnosis.

neuroscience↗

bioRxiv2025

High extraversion enhances attentional control through dynamic network reorganization

The extraversion-introversion dimension of personality is hypothesized to differ based on low or high cortical arousal, respectively. Notably, high cortical arousal in introverts is thought to underlie increased distractibility. Here, we assess fMRI while participants meditate (focused attention to their breath) under three levels of auditory distraction: no, low and high. Whereas introverts exhibited worsening attentional focus on their breath with increasing distraction, extraverts retained their ability to focus attention despite distraction. Dynamic functional connectivity analysis indicated that extraverts exhibited less globally efficient and less modular networks, which may prevent distracting stimuli from creating interference. Furthermore, connectivity strengths amongst the default mode, central executive, and salience networks were increased for extraverts and decreased in introverts during high focused attention; potentially indicating distinct cognitive processes that support attentional control. These findings support the hypothesis regarding differing levels of cortical arousal in extraverts and introverts and extend personality theory by linking the extraversion dimension to attentional control and functional connectivity dynamics.

neuroscience↗

bioRxiv2025

"Awe-scillations": EEG spectral and complexity representations of awe

Awe is a positive emotion often accompanied by sensations of vastness and unity, with known benefits for well-being and social behavior. However, its neural underpinnings remain poorly understood. We recorded electroencephalography (EEG) and autonomic physiology in 23 healthy older participants while they watched a nature-based audiovisual film and subjectively rated awe events. Awe was the predominant emotion reported - though other positive emotions (e.g., joy) were also highly rated. Awe events were associated with decreased skin conductance level (SCL), and decreased EEG alpha and theta spectral power - physiological changes associated with low arousal and positively valenced emotional states. Interestingly, awe events exhibited increased Lempel Ziv Complexity (LZC) - indicating heightened neural signal entropy and increased richness of the conscious experience. LZC was also positively associated with the intensity of the awe ratings and negatively associated with SCL. Three additional datasets with separate independent induction methods (video clips and pharmacological induction via N,N-dimethyltryptamine) also showed positive occipital LZC associations with awe - suggesting some generalizability of LZC as a neurophysiological marker of awe. These results suggest that awe evokes neurophysiological states linked to the subjective affective experience. Impact StatementAwe, an emotion of increasing interest, has been studied with fMRI and peripheral physiology - but few studies have used electroencephalography (EEG). In this EEG study, we utilize a movie-watching paradigm to explore potential physiological correlates of awe. The results present EEG-based complexity increases as a potential correlate of awe, though showing limited generalization to independent datasets and limited uniqueness compared to joy, another positive emotion.

neuroscience↗

bioRxiv2024

MYC shapes ER-mitochondria calcium transfer by directly targeting ITPR1: implications for MYC-induced safeguard mechanisms and cancer

The MYC and NMYC transcription factors (TFs) play a key role in cell proliferation and are overexpressed in most cancer cells. However, in normal cells their overexpression triggers safeguard mechanisms promoting cell death and cellular senescence, which are bypassed in cancer cells. The mechanisms of action of this TF family are only partially understood. Here, we reveal that in normal cells MYC binds to the Inositol 1,4,5-Trisphosphate Receptor type 1 (ITPR1) gene and upregulates its expression, triggering an ER-mitochondria calcium (Ca2+) transfer, which is involved in MYC-induced cell death and senescence. Supporting a tumor suppressive role of MYC/ITPR1 axis, ITPR1 expression is generally decreased in cancer and reactivation of this pathway induces cancer cell death. Nevertheless, some cancer cells, generally expressing high levels of MYCN and/or MYC, also express high level of ITPR1, which correlates with high expression of BCL2, encoding an inhibitor of ITPR1. Strikingly, in high-risk MYCN-amplified neuroblastoma, ITPR1 expression is controlled by NMYC and its level correlates with worse patient survival. In these cells, blocking the interaction between BCL2 and ITPR1 induces mitochondrial Ca2+ accumulation and cell death, and decreases tumor size. Collectively these data highlight a new function of MYC factors by controlling Ca2+ signaling, which could constitute an unsuspected vulnerability for some cancer cells, including high-risk MYCN-amplified neuroblastoma cells.

cancer biology↗

bioRxiv2024

The Interpretable Multimodal Machine Learning (IMML) framework reveals pathological signatures of distal sensorimotor polyneuropathy

Distal sensorimotor polyneuropathy (DSPN) is a common neurological disorder in elderly adults and people with obesity, prediabetes and diabetes and is associated with high morbidity and premature mortality. DSPN is a multifactorial disease and not fully understood yet. Here, we developed the Interpretable Multimodal Machine Learning (IMML) framework for predicting DSPN prevalence and incidence based on sparse multimodal data. Exploiting IMMLs interpretability further empowered biomarker identification. We leveraged the population-based KORA F4/FF4 cohort including 1,091 participants and their deep multimodal characterisation, i.e. clinical data, genomics, methylomics, transcriptomics, proteomics, inflammatory proteins and metabolomics. Clinical data alone is sufficient to stratify individuals with and without DSPN (AUROC = 0.752), whilst predicting DSPN incidence 6.5{+/-}0.2 years later strongly benefits from clinical data complemented with two or more molecular modalities (improved {Delta}AUROC >0.1, achieved AUROC of 0.714). Important and interpretable features of incident DSPN prediction include up-regulation of proinflammatory cytokines, down-regulation of SUMOylation pathway and essential fatty acids, thus yielding novel insights in the disease pathophysiology. These may become biomarkers for incident DSPN, guide prevention strategies and serve as proof of concept for the utility of IMML in studying complex diseases.

bioinformatics↗

bioRxiv2022

Copper chelation inhibits TGF-β pathways and suppresses epithelial-mesenchymal transition in cancer

Copper is a trace element essential to cellular function with elevated levels implicated in cancer progression. Clinical trials using copper chelators are associated with improved patient survival, however, the molecular mechanisms by which copper depletion inhibits tumor progression are poorly understood. This remains a major hurdle to the clinical translation of copper chelators. Epithelial-mesenchymal transition (EMT) is often exploited by malignant cells to promote growth and metastasis. Transforming growth factor (TGF)-{beta} is a master regulator of EMT and facilitates cancer progression through changes in the tumor and its microenvironment. Herein, we report that a reduction of copper with the chelating agent tetraethylenepentamine (TEPA) inhibited EMT in vitro in three diverse cancer cell types; human triple-negative breast cancer (TNBC), neuroblastoma (NB), and diffuse intrinsic pontine glioma (DIPG) cell lines. Single-molecule imaging demonstrated EMT markers including Vimentin, {beta}-catenin, ZEB1, and p-SMAD2 had increased expression with copper treatment and this pro-mesenchymal shift was rescued by the addition of TEPA. Moreover, SNAI1, ZEB1, and p-SMAD2 demonstrated increased accumulation in the cytoplasm after treating with TEPA. Transcriptomic analyses revealed a significant downregulation of the EMT pathway, including canonical (TGF-{beta}/SMAD2&3) and non-canonical (TGF-{beta}/PI3K/AKT and TGF-{beta}/RAS/RAF/MEK/ERK) TGF signaling pathways. Matrix metalloproteinases MMP-9 and MMP-14 proteins which activate latent TGF-{beta} complexes were also downregulated by TEPA treatment. These molecular changes are consistent with reduced plasma levels of TGF-{beta} we observed in cancer models treated with TEPA. Importantly, copper chelation reduced metastasis to the lung in a TNBC orthotopic syngeneic mouse model. Our studies suggest copper chelation therapy can be used to inhibit EMT-induced metastasis by targeting TGF-{beta} signalling. Because on-target anti-TGF-{beta} therapies are failing in the clinic, copper chelation presents itself as a potential therapy for targeting TGF-{beta} in cancer.

cancer biology↗

bioRxiv2022

CDK4 deletion in mice prevents fat accumulation and increases endurance capacity through activation of estrogen related receptor (ERR)driven oxidative metabolism in skeletal muscle

Cyclin-dependent kinase 4 (CDK4) canonical role is to control cell cycle progression from G1 to S phases. However, recent studies reported that CDK4 regulates energy metabolism in non-proliferating cells such as hepatocytes or adipocytes. The objective of our work is to study CDK4 function in skeletal muscle using a model of mice lacking CDK4 (cdk4-/-). By coupling treadmill running to indirect calorimetry, we show that cdk4-/- mice display improved endurance and higher capacity to use fat as fuel during exercise. Isolated muscles lacking CDK4 are more resistant to fatigue in response to repeated contractions and have increased oxidative capacity and mitochondrial content compared to cdk4+/+ muscles. Transcriptomic analysis reveals upregulation of genes controlled by the nuclear receptors estrogen-related receptors (ERRs) in cdk4-/- skeletal muscle, associated with elevated levels of the ERR co-activator PGC1a. Supporting in vivo results, C2C12 myotubes treated with a CDK4 inhibitor have increased mitochondrial oxygen consumption, PGC1 expression and ERR transcriptional activity measured by a luciferase reporter. In normal housing conditions, cdk4-/- mice show an increased basal metabolic rate and are resistant to weight gain and fat accumulation. In conclusion, our study uncovers a role for CDK4 in the control of skeletal muscle metabolism. Moreover, CDK4 inhibition may be an alternative strategy against obesity-associated metabolic disorders.

physiology↗

bioRxiv2020

Genomic asymmetry of the Brassica napus seed: Epigenetic contributions of DNA methylation and small RNAs to subgenome bias

Polyploidy has predominated the genetic history of the angiosperms, and allopolyploidy is known to have contributed to the vast speciation of flowering plants. Brassica napus, one of the worlds most important oilseeds, is one such polyploid species originating from the interspecific hybridization of Brassica rapa (An) and Brassica oleracea (Cn). Nascent amphidiploids must balance progenitor genomes during reproduction, though the role of epigenetic regulation in subgenome maintenance is unknown. The seed is the pivotal developmental transition into the new sporophytic generation and as such undergoes substantial epigenetic modifications. We investigated subgenome bias between the An and Cn subgenomes as well as across syntenic regions by profiling DNA methylation and siRNAs characteristic of B. napus seed development. DNA methylation and siRNA accumulation were prevalent in the Cn subgenome and most pronounced early during seed morphogenesis. Hypermethylation during seed maturation was most pronounced on non-coding elements, including promoters, repetitive elements, and siRNAs. Methylation on siRNA clusters was more prevalent in syntenic regions of the Cn subgenome and implies selective silencing of genomic loci of the seed. Together, we find compelling evidence for the asymmetrical epigenetic regulation of the An and Cn subgenomes of Brassica napus across seed development.

plant biology↗

bioRxiv2020

Gene expression profiling reveals subgenome dominance during Brassica napus seed development

We profiled the gene regulatory landscape of Brassica napus reproductive development using RNA sequencing. Comparative analysis of this nascent amphidiploid across the plant lifecycle revealed the contribution of each subgenome to plant reproduction. Global mRNA profiling revealed lower accumulation of Cn subgenome transcripts relative to the An subgenome. Subgenome-specific transcriptional networks identified distinct transcription factor families enriched in each of the An and Cn subgenome early in seed development. Global gene expression profiling of laser-microdissected seed subregions further reveal subgenome expression dynamics in the embryo, endosperm, and seed coat of early stage seeds. Transcription factors predicted to be regulators encoded by the An subgenome are expressed primarily in the seed coat whereas regulators encoded by the Cn subgenome were expressed primarily in the embryo. Data suggest subgenome bias are characteristic features of the B. napus seed throughout development, and that such bias might not be universal across the embryo, endosperm, and seed coat of the developing seed. Whole genome transcription factor networks identified BZIP11 as a transcriptional regulator of early B. napus seed development. Knockdown of BZIP11 using RNA interference resulted in a similar reduction in gene activity of predicted gene targets, and a reproductive-lethal phenotype. Taken together, transcriptional networks spanning both the An and Cn genomes of the B. napus seed can identify valuable targets for seed development research and that-omics level approaches to studying gene regulation in B. napus can benefit from both broad and high-resolution analyses. One Sentence SummaryGlobal RNA sequencing coupled with laser microdissection provides a critical resource to study subgenome bias in whole seeds and specific tissues of polyploid plants.

plant biology↗

bioRxiv2018

Focus on the breath: Brain decoding reveals internal states of attention during meditation

Meditation practices are used to cultivate internally-oriented attention to bodily sensations, which may improve health via cognitive and emotion regulation of bodily signals. However, it remains unclear how meditation impacts internal attention states due to lack of measurement tools that can objectively assess mental states during meditation practice itself, and produce time estimates of internal focus at individual or group levels. To address these measurement gaps, we tested the feasibility of applying multi-voxel pattern analysis (MVPA) to single-subject fMRI data to (1) learn and recognize internal attentional (IA) states relevant for meditation during a directed IA task, and (2) decode or estimate the presence of those IA states during an independent meditation session. Within a mixed sample of experienced meditators and novice controls (N=16), we first used MVPA to develop single-subject brain classifiers for 5 modes of attention during an IA task in which subjects were specifically instructed to engage in one of five states (i.e., meditation-related states: breath attention, mind wandering, and self-referential processing, and control states: attention to feet and sounds). Using standard cross-validation procedures, MVPA classifiers were trained in five of six IA blocks for each subject, and predictive accuracy was tested on the independent sixth block (iterated until all block volumes were tested, N=2160). Across participants, all five IA states were significantly recognized well above chance (>41% vs. 20% chance). At the individual level, IA states were recognized in most participants (87.5%), suggesting that recognition of IA neural patterns may be generalizable for most participants, particularly experienced meditators. Next, for those who showed accurate IA neural patterns, the originally trained classifiers were then applied to a separate meditation run (10-min) to make an inference about the percentage time engaged in each IA state (breath attention, mind wandering, or self-referential processing). Preliminary group-level analyses demonstrated that during meditation practice, participants spent more time attending to breath compared to mind wandering or self-referential processing. This paradigm established the feasibility of using MVPA classifiers to objectively assess mental states during meditation at the participant level, which holds promise for improved measurement of internal attention states cultivated by meditation.

neuroscience↗