144444 research outputs found
Sort by
Ancient landscape evolution tracked through cosmogenic krypton in detrital zircon
No full textCosmogenic nuclides have revolutionized our quantitative understanding of landscape evolution via measurements of near-surface erosion, exposure, and burial. Here, we integrate stable cosmogenic krypton in detrital zircon with U–Pb geochronology to extend the temporal limits of cosmogenic nuclide applications and reconstruct Eocene landscape evolution from drill cores of placer deposits in southern Australia. Zircon U–Pb crystallization ages are interpreted to reflect paleodrainage from a deeply weathered ~800,000 km 2 hinterland and transport via a ~1,000 km littoral drift system. The measured cosmogenic 78 Kr concentration of detrital zircon samples ranges from ~6.4 × 10 5 to 1.8 × 10 7 atoms per gram, suggesting low paleodenudation rates of 0.3 to 0.7 m per My [interquartile range (IQR)]. Such low denudation rates are below those expected by comparison to modern analogs and point to underestimation due to re-exposure during sediment transport and shallow storage. Expressing the concentrations as apparent exposure times, which approximate the near-surface integrated residence time, yields estimates of 0.9 to 2.1 My (IQR). In the stratigraphic and mineralogical context, the dataset records a shift from compositionally mature placers with uniformly high residence times (~1.6 My) to less mature placers with stratigraphically variable residence times (~0.7 to 2.7 My). We infer a shift from prolonged sediment storage, during which the mineral assemblage was modified, to a more dynamic transport regime with higher net transfer rates. The timing suggests eustatic and tectonic forcing, and cosmogenic krypton captures this transition, aiding reconstruction of how ancient landscapes and the sedimentary record coevolve.Minerals Research Institute of Western Australia http://dx.doi.org/10.13039/501100009108Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/50110000165
Static and dynamic rough energy landscapes can lead to identical diffusivity
No full textMolecules in dense environments, such as biological cells, are subjected to forces that fluctuate both in time and in space. While spatial fluctuations are captured by Lifson-Jackson-Zwanzig’s model of “diffusion in a rough potential,” and temporal fluctuations are often viewed as leading to additional friction effects, a unified view where the environment fluctuates both in time and in space is currently lacking. Here, we introduce a discrete-state model of a landscape fluctuating both in time and in space. Importantly, the model accounts for the reciprocal interaction of the diffusing particle with the landscape, which alters the landscape dynamics. As a result we find, surprisingly, that many features of the observable dynamics do not depend on the temporal fluctuation timescales and are already captured by the model of diffusion in a rough potential, even though this assumes a static energy landscape. Using this model, we reevaluate results of several experimental studies of protein dynamics and propose more accurate bounds on the inferred energetic roughness scales, which account for landscape dynamics.National Science Foundation 100000001Welch Foundation 100000928Alexander von Humboldt-Stiftung 10000515
Minimum important slowing of disease progression as determined by the ALS functional rating scale – a survey of patient expectations toward disease-modifying drugs in ALS
No full textBoris Canessa ALS StiftungHannover Medical School and DFGBoris Canessa ALS Stiftun
Medial temporal ageing-related tau astrogliopathy below 66 years is associated with neurodegeneration
No full textAbstract Aging-related tau astrogliopathy (ARTAG) refers to aggregates of pathological tau protein in astroglial cells in the brain. Thorny astrocytes at the level of the glia limitans and/or white matter, and granular/fuzzy astrocytes in the grey matter are characteristic for ARTAG, which correlates with aging. However, also rare cases with ARTAG below the age of 66 have been reported. We studied a cohort of 157 brains from donors deceased between 48 and 65 years of age received from the Leuven neuropathological research group and Netherlands Brain Bank in order to gain insight into ARTAG in the medial temporal lobe at younger age, and to find underlying correlates that might be obscured by age-related co-pathologies in older cohorts. Analyses were also performed on two comparison cohorts (Leuven: 268 cases and Netherlands: 397 cases), with ages ranging from 66 to 99 years. Twenty-six out of 157 cases (16.6 %) between 48-65 years had ARTAG, mostly restricted to the medial temporal lobe. Only 6 cases exhibited ARTAG in lobar regions. ARTAG was found in all 5 previously described morphologies and locations: subpial, subependymal, perivascular, white matter and grey matter. In our young cohort, a significant correlation was found between ARTAG and the presence of neurodegenerative conditions of any kind and between ARTAG and age. When correcting for age and sex, the association between ARTAG and the presence of neurodegenerative conditions was upheld. There were no significant associations between ARTAG and specific proteinopathies, though trends were observed for α-synucleinopathy, Tauopathy and TDP-43 proteinopathy diagnoses. The presence of lobar ARTAG was related to ARTAG severity in the young cohort. In the older cohorts, only age was significantly associated with ARTAG. These results suggest a link between ARTAG in the medial temporal lobe of young individuals and pathological protein aggregation of any kind in the brain independent of age and might raise the question whether ARTAG points to astrocytes as important players for selective vulnerability for the aggregation of pathological proteins in distinct brain regions in this patient population
Intracranial haemorrhage without early clinical deterioration after mechanical thrombectomy: rethinking the “asymptomatic” label
No full textAbstract Introduction ICH is a common complication following endovascular therapy (EVT) for ischaemic stroke. While sICH is known to worsen outcomes, the impact of ICH without early neurological deterioration (END), commonly referred to as “asymptomatic” (aICH), remains controversial. This study aimed to assess imaging patterns of aICH and its effect on clinical outcomes. Patients and methods This study used data from the prospective, multicentre German Stroke Registry-Endovascular Treatment. Bleedings were assessed on follow-up imaging at 24 hours applying the Heidelberg Bleeding Classification. European Cooperative Acute Stroke Study III (ECASS)-III criteria were used to stratify patients into (1) no ICH, (2) aICH and (3) sICH. The primary outcome was functional independence (mRS ≤ 2) at 3 months. Secondary outcomes included mRS shift and 3-month mortality. Results Among 4834 patients with EVT (median age 76, 51% female, median NIHSS 14), ICH occurred in 13.2% (aICH: 9.7%, sICH: 3.5%). Haemorrhage patterns differed, with sICH being more often parenchymal (48.2% vs 34.6%), multicompartmental (34.1% vs 20.2%) and involving the ventricular system (18.8% vs 7.6%), while aICH were predominantly haemorrhagic transformation (34.6% vs 21.8%). Functional independence at 90 days was reached by 40.0% (no ICH), 25.4% (aICH; adjusted odds ratio [aOR] 0.43 [0.32–0.58]) and 6.5% (sICH; aOR 0.06 [0.03–0.14]), respectively. aICH was associated with worse overall recovery (mRS shift adjusted common OR 0.51 [0.41–0.63]) and higher 90-day mortality (35.5% vs 24.9%; aOR 1.90 [1.44–2.51]), when compared to no ICH. Conclusion ICH after EVT was associated with worse functional recovery and higher mortality, even in the absence of END. Given these results, the term “asymptomatic ICH” warrants reconsideration
Setaphyte VERY-LONG-CHAIN FATTY ACYL DESATURASES impact glycerolipid and sphingolipid metabolism
No full textAbstract Desaturases in plants are diverse. They vary in localization, source of reducing power, and substrate preference, accepting glycerolipids, long-chain bases, acyl-CoAs, and acyl-ACPs, in varying states of (un)saturation and chain length. Their products are incorporated into membrane glycerolipids, sphingolipids, or storage lipids. We previously characterized a desaturase from Physcomitrium patens that predominantly affects the monounsaturation of very-long-chain fatty acyl (VLCFA) moieties of sphingolipids, naming this desaturase SPHINGOLIPID FATTY ACYL DESATURASE (SFD). Among embryophytes, candidate SFDs were only identified in setaphytes, including one paralog in P. patens and an ortholog in Marchantia polymorpha. Here, we characterize the P. patens paralog, and clarify via mutant analysis that SFDs affect not only sphingolipid metabolism, but also glycerolipid metabolism. We express both paralogs, as well as the candidate gene from M. polymorpha, in Saccharomyces cerevisiae, and show they desaturate VLCFAs incorporated into sphingolipids, triacylglycerols, and acyl-CoAs. The simplest explanation is that “SFDs” likely accept an acyl-CoA, rather than a sphingolipid substrate as initially proposed. We suggest renaming these desaturases VERY-LONG-CHAIN FATTY ACYL DESATURASES (VFADs). The physiological functions of VFADs and functionally similar enzymes from other plant systems are discussed, as are the challenges with classifying desaturases
Multiple Key Hosts and Network Structure Shape Viral Prevalence Across Multispecies Communities of Bees
No full textABSTRACT Emerging infectious diseases (EIDs) threaten biodiversity, yet identifying key host species in complex ecological communities remains a major challenge. Here, we develop a quantitative framework combining field data, epidemiological modelling, simulations, and Bayesian inference to pinpoint key viral hosts in multispecies bee communities. Using flower–visitor interaction data and molecular virus screening, we estimate species‐specific basic reproduction numbers ( R 0 ) and assess the role of both key hosts and community metrics in virus transmission and persistence. We show that, while honeybees often act as primary reservoirs for deformed wing virus and black queen cell virus, others, such as the bumblebee Bombus lapidarius , can drive the spread of acute bee paralysis virus. Viral dynamics are primarily explained by exposure to key hosts, while community effects are not as pronounced. Identification of non‐honeybee key hosts challenges existing assumptions and highlights drivers of transmission and pathogen persistence in complex host–pathogen networks.Bundesanstalt für Landwirtschaft und Ernährung https://doi.org/10.13039/501100010771Deutsche Forschungsgemeinschaft https://doi.org/10.13039/50110000165
Acute Rejection With DSA ‐Negative Severe Microvascular Inflammation in a Kidney Transplant Recipient With an Isolated DPB1*04 ‐Mismatch Successfully Stabilised With Daratumumab
No full textABSTRACT Microvascular inflammation (MVI) in kidney allografts in the absence of detectable donor‐specific anti‐HLA antibodies (DSA) is increasingly recognised as a cause of premature graft failure following kidney transplantation. Potential mechanisms include NK cell alloreactivity mediated by recognition of mismatched HLA class I molecules (missing‐self) via killer‐immunoglobulin‐like receptors. Here, we report the case of an early kidney allograft rejection with severe MVI on biopsy in a patient that was fully HLA‐matched except for a HLA‐DPB1*04 mismatch in the donor. There were no detectable DSA at any time. MVI was successfully reversed and clinically stabilised with a 9‐month course of daratumumab (anti‐CD38 mAb). This case suggests alternative mechanisms of alloreactivity, such as NK cell‐mediated effects, and highlights the existence of MVI in the absence of detectable B cell alloreactivity. Moreover, this case exemplifies the potential of anti‐CD38 treatment in these patients
The evolution of gene regulation in mammalian cerebellum development
No full textGene regulatory changes are considered major drivers of evolutionary innovations, including the cerebellum’s expansion during human evolution, yet they remain largely unexplored. In this study, we combined single-nucleus measurements of gene expression and chromatin accessibility from six mammals (human, bonobo, macaque, marmoset, mouse, and opossum) to uncover conserved and diverged regulatory networks in cerebellum development. We identified core regulators of cell identity and developed sequence-based models that revealed conserved regulatory codes. By predicting chromatin accessibility across 240 mammalian species, we reconstructed the evolutionary histories of human cis-regulatory elements, identifying sets associated with positive selection and gene expression changes, including the recent gain of THRB expression in cerebellar progenitor cells. Collectively, our work reveals the shared and mammalian lineage-specific regulatory programs governing cerebellum development.Editor’s summary The mechanisms underlying brain development during evolution remain to be fully elucidated. Sarropulos et al . focused on the cerebellum and used previous single-nucleus multiome (RNA expression and DNA accessibility) and newly generated datasets across six mammalian species (human, bonobo, macaque, marmoset, mouse, and opossum) to develop a deep-learning model able to predict gene regulatory networks and cis-regulatory elements conserved or diverged during evolution for cerebellum development. By combining the cross-species multiomic resource with state-of-the-art machine learning and deep learning modeling of gene regulatory networks and enhancer grammar, this work provides valuable insights into brain development and evolution. —Mattia MarosoINTRODUCTION The mammalian cerebellum has experienced many evolutionary innovations, but their molecular basis remains elusive. Most phenotypic changes are thought to be driven by mutations in cis-regulatory elements (CREs) such as enhancers and promoters, which control gene expression in a cell type–specific manner. However, the fast CRE evolution and our limited understanding of how DNA sequences encode regulatory activity have hindered our ability to study regulatory innovations. RATIONALE Single-cell multiomics enable the mapping of CRE cell type specificity, whereas recent advances in machine learning facilitate predicting CRE accessibility from DNA sequence. We reasoned that if CRE sequence codes of cerebellar cell types are conserved across mammals, then we could use sequence-based deep learning models to reconstruct CRE evolutionary histories from genomic sequences and identify sequence changes underlying gene regulatory innovation. RESULTS We built comprehensive single-cell gene expression and chromatin accessibility atlases of cerebellum development across six mammalian species, human, bonobo, macaque, marmoset, mouse, and opossum, spanning 780,000 single-cell profiles. We aligned developmental timelines between species, found common cell types, and dated our previously reported expansion of fetal Purkinje cells in the human lineage within the past 40 million years, highlighting a recent evolutionary innovation in the cerebellum. By inferring gene regulatory networks, we identified major transcription factor regulators of cerebellar cell identities and showed that their activity is largely conserved across species. Grouping CREs on the basis of their spatiotemporal accessibility revealed shared transcription factor motif signatures between human and mouse CREs, suggesting that their regulatory codes, i.e., motif combinations, are conserved despite extensive turnover of individual CREs. Next, we developed deep learning models that successfully predicted cerebellar cell type–specific CRE accessibilities from DNA sequence across species. Using a model trained on human and mouse data, DeepCeREvo (deep learning of cerebellar regulatory evolution), we demonstrated that the logic linking DNA sequence to CRE function, the regulatory grammar, of cerebellar cell types remained markedly stable over 160 million years of mammalian evolution. Building on this, we expanded our predictions to 240 mammalian genomes and reconstructed the evolutionary histories of human CREs. We identified clade-specific CREs that, after their emergence, were preserved, and detected signs of positive selection in human-specific elements, suggesting potential links to evolutionary innovations. We validated these predictions using nonhuman primate datasets not included in model training and enhancer reporter assays. Finally, we linked primate-specific CREs to genes with expression gains in the same cell type in the primate lineage. Notably, we traced an expression gain of THRB in human early progenitor cells to single-nucleotide substitutions that potentially created a new CRE ~3 kilobases upstream of the transcription start site ~25 to 40 million years ago. CONCLUSION Our study provides a comprehensive framework for understanding gene regulatory evolution by combining comparative single-cell genomics with machine learning approaches. We demonstrate that despite rapid turnover of individual regulatory elements, conserved regulatory grammar governs cell type–specific gene expression in cerebellum development across mammals. By linking specific sequence changes to expression evolution, we identified regulatory innovations that likely contributed to human cerebellar evolution. This approach is broadly applicable to understanding regulatory evolution across tissues and species. Single-cell multiomics analysis of cerebellar regulatory evolution across mammals. Single-cell multiomics atlases delineate gene regulation of cerebellar cell types across species (left). Sequence-based deep learning models revealed that the regulatory grammar, the sequence logic underlying CRE accessibility, of cerebellar cell types has been conserved over 160 million years of mammalian evolution, enabling inference of evolutionary histories of human CREs using orthologous regions across 240 mammals (top right). Recent innovations in human CREs are linked to changes in gene expression between species (bottom right).Gene regulatory changes are considered major drivers of evolutionary innovations, including the cerebellum’s expansion during human evolution, yet they remain largely unexplored. In this study, we combined single-nucleus measurements of gene expression and chromatin accessibility from six mammals (human, bonobo, macaque, marmoset, mouse, and opossum) to uncover conserved and diverged regulatory networks in cerebellum development. We identified core regulators of cell identity and developed sequence-based models that revealed conserved regulatory codes. By predicting chromatin accessibility across 240 mammalian species, we reconstructed the evolutionary histories of human cis-regulatory elements, identifying sets associated with positive selection and gene expression changes, including the recent gain of THRB expression in cerebellar progenitor cells. Collectively, our work reveals the shared and mammalian lineage-specific regulatory programs governing cerebellum development.Editor’s summary The mechanisms underlying brain development during evolution remain to be fully elucidated. Sarropulos et al . focused on the cerebellum and used previous single-nucleus multiome (RNA expression and DNA accessibility) and newly generated datasets across six mammalian species (human, bonobo, macaque, marmoset, mouse, and opossum) to develop a deep-learning model able to predict gene regulatory networks and cis-regulatory elements conserved or diverged during evolution for cerebellum development. By combining the cross-species multiomic resource with state-of-the-art machine learning and deep learning modeling of gene regulatory networks and enhancer grammar, this work provides valuable insights into brain development and evolution. —Mattia MarosoINTRODUCTION The mammalian cerebellum has experienced many evolutionary innovations, but their molecular basis remains elusive. Most phenotypic changes are thought to be driven by mutations in cis-regulatory elements (CREs) such as enhancers and promoters, which control gene expression in a cell type–specific manner. However, the fast CRE evolution and our limited understanding of how DNA sequences encode regulatory activity have hindered our ability to study regulatory innovations. RATIONALE Single-cell multiomics enable the mapping of CRE cell type specificity, whereas recent advances in machine learning facilitate predicting CRE accessibility from DNA sequence. We reasoned that if CRE sequence codes of cerebellar cell types are conserved across mammals, then we could use sequence-based deep learning models to reconstruct CRE evolutionary histories from genomic sequences and identify sequence changes underlying gene regulatory innovation. RESULTS We built comprehensive single-cell gene expression and chromatin accessibility atlases of cerebellum development across six mammalian species, human, bonobo, macaque, marmoset, mouse, and opossum, spanning 780,000 single-cell profiles. We aligned developmental timelines between species, found common cell types, and dated our previously reported expansion of fetal Purkinje cells in the human lineage within the past 40 million years, highlighting a recent evolutionary innovation in the cerebellum. By inferring gene regulatory networks, we identified major transcription factor regulators of cerebellar cell identities and showed that their activity is largely conserved across species. Grouping CREs on the basis of their spatiotemporal accessibility revealed shared transcription factor motif signatures between human and mouse CREs, suggesting that their regulatory codes, i.e., motif combinations, are conserved despite extensive turnover of individual CREs. Next, we developed deep learning models that successfully predicted cerebellar cell type–specific CRE accessibilities from DNA sequence across species. Using a model trained on human and mouse data, DeepCeREvo (deep learning of cerebellar regulatory evolution), we demonstrated that the logic linking DNA sequence to CRE function, the regulatory grammar, of cerebellar cell types remained markedly stable over 160 million years of mammalian evolution. Building on this, we expanded our predictions to 240 mammalian genomes and reconstructed the evolutionary histories of human CREs. We identified clade-specific CREs that, after their emergence, were preserved, and detected signs of positive selection in human-specific elements, suggesting potential links to evolutionary innovations. We validated these predictions using nonhuman primate datasets not included in model training and enhancer reporter assays. Finally, we linked primate-specific CREs to genes with expression gains in the same cell type in the primate lineage. Notably, we traced an expression gain of THRB in human early progenitor cells to single-nucleotide substitutions that potentially created a new CRE ~3 kilobases upstream of the transcription start site ~25 to 40 million years ago. CONCLUSION Our study provides a comprehensive framework for understanding gene regulatory evolution by combining comparative single-cell genomics with machine learning approaches. We demonstrate that despite rapid turnover of individual regulatory elements, conserved regulatory grammar governs cell type–specific gene expression in cerebellum development across mammals. By linking specific sequence changes to expression evolution, we identified regulatory innovations that likely contributed to human cerebellar evolution. This approach is broadly applicable to understanding regulatory evolution across tissues and species. Single-cell multiomics analysis of cerebellar regulatory evolution across mammals. Single-cell multiomics atlases delineate gene regulation of cerebellar cell types across species (left). Sequence-based deep learning models revealed that the regulatory grammar, the sequence logic underlying CRE accessibility, of cerebellar cell types has been conserved over 160 million years of mammalian evolution, enabling inference of evolutionary histories of human CREs using orthologous regions across 240 mammals (top right). Recent innovations in human CREs are linked to changes in gene expression between species (bottom right).Gene regulatory changes are considered major drivers of evolutionary innovations, including the cerebellum’s expansion during human evolution, yet they remain largely unexplored. In this study, we combined single-nucleus measurements of gene expression and chromatin accessibility from six mammals (human, bonobo, macaque, marmoset, mouse, and opossum) to uncover conserved and diverged regulatory networks in cerebellum development. We identified core regulators of cell identity and developed sequence-based models that revealed conserved regulatory codes. By predicting chromatin accessibility across 240 mammalian species, we reconstructed the evolutionary histories of human cis-regulatory elements, identifying sets associated with positive selection and gene expression changes, including the recent gain of THRB expression in cerebellar progenitor cells. Collectively, our work reveals the shared and mammalian lineage-specific regulatory programs governing cerebellum development.Editor’s summary The mechanisms underlying brain development during evolution remain to be fully elucidated. Sarropulos et al . focused on the cerebellum and used previous single-nucleus multiome (RNA expression and DNA accessibility) and newly generated datasets across six mammalian species (human, bonobo, macaque, marmoset, mouse, and opossum) to develop a deep-learning model able to predict gene regulatory networks and cis-regulatory elements conserved or diverged during evolution for cerebellum development. By combining the cross-species multiomic resource with state-of-the-art machine learning and deep learning modeling of gene regulatory networks and enhancer grammar, this work provides valuable insights into brain development and evolution. —Mattia MarosoINTRODUCTION The mammalian cerebellum has experienced many evolutionary innovations, but their molecular basis remains elusive. Most phenotypic changes are thought to be driven by mutations in cis-regulatory elements (CREs) such as enhancers and promoters, which control gene expression in a cell type–specific manner. However, the fast CRE evolution and our limited understanding of how DNA sequences encode regulatory activity have hindered our ability to study regulatory innovations. RATIONALE Single-cell multiomics enable the mapping of CRE cell type specificity, whereas recent advances in machine learning facilitate predicting CRE accessibility from DNA sequence. We reasoned that if CRE sequence codes of cerebellar cell types are conserved across mammals, then we could use sequence-based deep learning models to reconstruct CRE evolutionary histories from genomic sequences and identify sequence changes underlying gene regulatory innovation. RESULTS We built comprehensive single-cell gene expression and chromatin accessibility atlases of cerebellum development across six mammalian species, human, bonobo, macaque, marmoset, mouse, and opossum, spanning 780,000 single-cell profiles. We aligned developmental timelines between species, found common cell types, and dated our previously reported expansion of fetal Purkinje cells in the human lineage within the past 40 million years, highlighting a recent evolutionary innovation in the cerebellum. By inferring gene regulatory networks, we identified major transcription factor regulators of cerebellar cell identities and showed that their activity is largely conserved across species. Grouping CREs on the basis of their spatiotemporal accessibility revealed shared transcription factor motif signatures between human and mouse CREs, suggesting that their regulatory codes, i.e., motif combinations, are conserved despite extensive turnover of individual CREs. Next, we developed deep learning models that successfully predicted cerebellar cell type–specific CRE accessibilities from DNA sequence across species. Using a model trained on human and mouse data, DeepCeREvo (deep learning of cerebellar regulatory evolution), we demonstrated that the logic linking DNA sequence to CRE function, the regulatory grammar, of cerebellar cell types remained markedly stable over 160 million years of mammalian evolution. Building on this, we expanded our predictions to 240 mammalian genomes and reconstructed the evolutionary histories of human CREs. We identified clade-specific CREs that, after their emergence, were preserved, and detected signs of positive selection in human-specific elements, suggesting potential links to evolutionary innovations. We validated these predictions using nonhuman primate datasets not included in model training and enhancer reporter assays. Finally, we linked primate-specific CREs to genes with expression gains in the same cell type in the primate lineage. Notably, we traced an expression gain of THRB in human early progenitor cells to single-nucleotide substitutions that potentially created a new CRE ~3 kilobases upstream of the transcription start site ~25 to 40 million years ago. CONCLUSION Our study provides a comprehensive framework for understanding gene regulatory evolution by combining comparative single-cell genomics with machine learning approaches. We demonstrate that despite rapid turnover of individual regulatory elements, conserved regulatory grammar governs cell type–specific gene expression in cerebellum development across mammals. By linking specific sequence changes to expression evolution, we identified regulatory innovations that likely contributed to human cerebellar evolution. This approach is broadly applicable to understanding regulatory evolution across tissues and species. Single-cell multiomics analysis of cerebellar regulatory evolution across mammals. Single-cell multiomics atlases delineate gene regulation of cerebellar cell types across species (left). Sequence-based deep learning models revealed that the regulatory grammar, the sequence logic underlying CRE accessibility, of cerebellar cell types has been conserved over 160 million years of mammalian evolution, enabling inference of evolutionary histories of human CREs using orthologous regions across 240 mammals (top right). Recent innovations in human CREs are linked to changes in gene expression between species (bottom right)
UNIversity students’ LIFEstyle behaviours and Mental health cohort (UNILIFE-M): study protocol of a multicentre, prospective cohort study
No full textIntroduction Students enrolling in higher education often adopt lifestyles linked to worse mental health, potentially contributing to the peak age onset of mental health problems in early adulthood. However, extensive research is limited by focusing on single lifestyle behaviours, including single time points, within limited cultural contexts, and focusing on a limited set of mental health symptoms. Methods and analysis The UNIversity students’ LIFEstyle behaviours and Mental health cohort (UNILIFE-M) is a prospective worldwide cohort study aiming to investigate the associations between students’ lifestyle behaviours and mental health symptoms during their college years. The UNILIFE-M will gather self-reported data through an online survey on mental health symptoms (ie, depression, anxiety, mania, sleep problems, substance abuse, inattention/hyperactivity and obsessive/compulsive thoughts/behaviours) and lifestyle behaviours (ie, diet, physical activity, substance use, stress management, social support, restorative sleep, environment and sedentary behaviour) over 3.5 years. Participants of 69 universities from 28 countries (300 per site) will be assessed at university admission in the 2023 and/or the 2024 academic year and followed up for 1, 2 and 3.5 years. Ethics and dissemination The study was first approved at a national level in Brazil (CAE:63025822.8.1001.5346). Study sites outside Brazil obtained additional ethics approval from their institutions using the main approval. Results from the UNILIFE-M cohort will be disseminated through scientific publications, presentations at scientific meetings, press releases, the general media and social media.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior CAPEShttp://dx.doi.org/10.13039/501100004263 Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sulhttp://dx.doi.org/10.13039/501100003593 Conselho Nacional de Desenvolvimento Científico e Tecnológic