@article{20868,
  abstract     = {Residents of low-latitude megacities face growing vulnerability to humid-heat stress under urbanization and global warming, yet limited research has assessed the morbidity burden of mental and behavioral disorders (MBDs) linked to humid-heat exposures in these cities. Here we quantify the hospital admissions of MBDs in Shanghai, a megacity of over 25 million inhabitants, attributable to humid heat, and project future burdens under various greenhouse gas (GHG)-emission and population scenarios. Humid heat drives a higher morbidity burden than high temperature alone, especially in humid-heat nights. Without population change, the humid-heat-related morbidity burden of MBDs would increase by 68.2% (95% empirical confidence interval 56.7%–81.6%) under the highest-GHG-emission scenario by the 2090s, while 8,465 (95% empirical confidence interval 6,928–10,053) cases would be avoided by reducing emissions to the lowest pathway. With projected population decline, the attributable hospital admissions will decrease toward century’s end. These findings highlight the benefit of GHG mitigation in reducing the growing MBD risks posed by extreme humid heat.},
  author       = {Liang, Chen and Yuan, Jiacan and Zhang, Renhe and Tang, Xu and Schumann, Gunter and Hitchen, Esther and Polemiti, Elli and Serin, Emin and Kebir, Hedi and Lett, Tristram A. and Vaidya, Nilakshi and Roy, Jean-Charles and Walter, Henrik and Heinz, Andreas and Ralser, Markus and Twardziok, Sven and Eils, Roland and Jentsch, Marcel and Taron, Ulrike-Helene and Schütz, Tatjana and Schepanski, Kerstin and Banaschewski, Tobias and Neidhart, Maja and Meyer-Lindenberg, Andreas and Tost, Heike and Holz, Nathalie and Schwarz, Emanuel and Stringaris, Argyris and Christmann, Nina and Janson, Karina and Nees, Frauke and Neidhart, Maja and Seefried, Beke and Aden, Rieke and Andreassen, Ole A. and Westlye, Lars T. and van der Meer, Dennis and Fernández-Cabello, Sara and Kjelkenes, Rikka and Ask, Helga and Rapp, Michael and Tschorn, Mira and Böttger, Sarah Jane and Marquand, Andre and Bernas, Antoine and Novarino, Gaia and Slater, Mel and Gallego, Jaime and Pastor, Álvaro and Feixas, Guillem and Eiroa-Orosa, Francisco José and Nöthen, Markus M. and Forstner, Andreas J. and Claus, Isabelle and Mathey, Carina and Heilmann-Heimbach, Stefanie and Hoffmann, Per and Miller, Abigail and Sommer, Peter and Schmitt, Karen and Wilbertz, Johannes and Patraskaki, Myrto and Jirsa, Viktor and Petkoski, Spase and Athanasiadis, Anastasios-Polykarpos and Spanlang, Bernhard and Pearmund, Charlie and Hese, Sören and Renner, Paul and Jia, Tianye and Chang, Xiao and Dai, Yuxiang and Xia, Yunman and Li, Yuzhu and Zhang, Yanqing and Calhoun, Vince and Thompson, Paul and Clinton, Nicholas and Desrivières, Sylvane and Agunbiade, Kofoworola and Yu, Xinyang and Zhang, Zuo and Chen, Di and Young, Allan H. and Schwalber, Ameli and Köhler, Vanessa and Stahl, Bernd and Ogoh, George and Schikowski, Tamara and Brandlistuen, Ragnhild},
  issn         = {2731-6076},
  journal      = {Nature Mental Health},
  number       = {12},
  pages        = {1532--1544},
  publisher    = {Springer Nature},
  title        = {{Projecting the morbidity burden of mental and behavioral disorders associated with increasing humid heat in Shanghai}},
  doi          = {10.1038/s44220-025-00519-y},
  volume       = {3},
  year         = {2025},
}

@article{15016,
  abstract     = {Amphibians, by virtue of their phylogenetic position, provide invaluable insights on nervous system evolution, development, and remodeling. The genetic toolkit for amphibians, however, remains limited. Recombinant adeno-associated viral vectors (AAVs) are a powerful alternative to transgenesis for labeling and manipulating neurons. Although successful in mammals, AAVs have never been shown to transduce amphibian cells efficiently. We screened AAVs in three amphibian species—the frogs Xenopus laevis and Pelophylax bedriagae and the salamander Pleurodeles waltl—and identified at least two AAV serotypes per species that transduce neurons. In developing amphibians, AAVs labeled groups of neurons generated at the same time during development. In the mature brain, AAVrg retrogradely traced long-range projections. Our study introduces AAVs as a tool for amphibian research, establishes a generalizable workflow for AAV screening in new species, and expands opportunities for cross-species comparisons of nervous system development, function, and evolution.},
  author       = {Jaeger, Eliza C.B. and Vijatovic, David and Deryckere, Astrid and Zorin, Nikol and Nguyen, Akemi L. and Ivanian, Georgiy and Woych, Jamie and Arnold, Rebecca C and Ortega Gurrola, Alonso and Shvartsman, Arik and Barbieri, Francesca and Toma, Florina-Alexandra and Gorbsky, Gary J. and Horb, Marko E. and Cline, Hollis T. and Shay, Timothy F. and Kelley, Darcy B. and Yamaguchi, Ayako and Shein-Idelson, Mark and Tosches, Maria Antonietta and Sweeney, Lora Beatrice Jaeger},
  issn         = {1878-1551},
  journal      = {Developmental Cell},
  number       = {5},
  pages        = {794--812.e6},
  publisher    = {Elsevier},
  title        = {{Adeno-associated viral tools to trace neural development and connectivity across amphibians}},
  doi          = {10.1016/j.devcel.2024.10.025},
  volume       = {60},
  year         = {2025},
}

@article{19444,
  abstract     = {As the field of neural organoids and assembloids expands, there is an emergent need for guidance and advice on designing, conducting and reporting experiments to increase the reproducibility and utility of these models. In this Perspective, we present a framework for the experimental process that encompasses ensuring the quality and integrity of human pluripotent stem cells, characterizing and manipulating neural cells in vitro, transplantation techniques and considerations for modelling human development, evolution and disease. As with all scientific endeavours, we advocate for rigorous experimental designs tailored to explicit scientific questions as well as transparent methodologies and data sharing to provide useful knowledge for current research practices and for developing regulatory standards.},
  author       = {Pașca, Sergiu P. and Arlotta, Paola and Bateup, Helen S. and Camp, J. Gray and Cappello, Silvia and Gage, Fred H. and Knoblich, Jürgen A. and Kriegstein, Arnold R. and Lancaster, Madeline A. and Ming, Guo Li and Novarino, Gaia and Okano, Hideyuki and Parmar, Malin and Park, In Hyun and Reiner, Orly and Song, Hongjun and Studer, Lorenz and Takahashi, Jun and Temple, Sally and Testa, Giuseppe and Treutlein, Barbara and Vaccarino, Flora M. and Vanderhaeghen, Pierre and Young-Pearse, Tracy},
  issn         = {1476-4687},
  journal      = {Nature},
  number       = {8054},
  pages        = {315--320},
  publisher    = {Springer Nature},
  title        = {{A framework for neural organoids, assembloids and transplantation studies}},
  doi          = {10.1038/s41586-024-08487-6},
  volume       = {639},
  year         = {2025},
}

@phdthesis{19557,
  author       = {Schwarz, Lena A},
  issn         = {2663-337X},
  pages        = {124},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Mapping developmental dynamics of autism spectrum disorder mouse models at single-cell resolution}},
  doi          = {10.15479/AT-ISTA-19557},
  year         = {2025},
}

@article{19704,
  abstract     = {The information-processing capability of the brain’s cellular network depends on the physical wiring pattern between neurons and their molecular and functional characteristics. Mapping neurons and resolving their individual synaptic connections can be achieved by volumetric imaging at nanoscale resolution1,2 with dense cellular labelling. Light microscopy is uniquely positioned to visualize specific molecules, but dense, synapse-level circuit reconstruction by light microscopy has been out of reach, owing to limitations in resolution, contrast and volumetric imaging capability. Here we describe light-microscopy-based connectomics (LICONN). We integrated specifically engineered hydrogel embedding and expansion with comprehensive deep-learning-based segmentation and analysis of connectivity, thereby directly incorporating molecular information into synapse-level reconstructions of brain tissue. LICONN will allow synapse-level phenotyping of brain tissue in biological experiments in a readily adoptable manner.},
  author       = {Tavakoli, Mojtaba and Lyudchik, Julia and Januszewski, Michał and Vistunou, Vitali and Agudelo Duenas, Nathalie and Vorlaufer, Jakob and Sommer, Christoph M and Kreuzinger, Caroline and Oliveira, Bárbara and Cenameri, Alban and Novarino, Gaia and Jain, Viren and Danzl, Johann G},
  issn         = {1476-4687},
  journal      = {Nature},
  pages        = {398--410},
  publisher    = {Springer Nature},
  title        = {{Light-microscopy-based connectomic reconstruction of mammalian brain tissue}},
  doi          = {10.1038/s41586-025-08985-1},
  volume       = {642},
  year         = {2025},
}

@article{20662,
  abstract     = {Task-based functional magnetic resonance imaging (fMRI) reveals individual differences in neural correlates of cognition but faces scalability challenges due to cognitive demands, protocol variability, and limited task coverage in large datasets. Here, we propose DeepTaskGen, a deep-learning approach that synthesizes non-acquired task-based contrast maps from resting-state (rs-) fMRI. We validate this approach using the Human Connectome Project lifespan data, then generate 47 contrast maps from 7 different cognitive tasks for over 20,000 individuals from UK Biobank. DeepTaskGen outperforms several benchmarks in generating synthetic task-contrast maps, achieving superior reconstruction performance while retaining inter-individual variation essential for biomarker development. We further show comparable or superior predictive performance of synthetic maps relative to actual maps and rs-connectomes across diverse demographic, cognitive, and clinical variables. This approach facilitates the study of individual differences and the generation of task-related biomarkers by enabling the generation of arbitrary functional cognitive tasks from readily available rs-fMRI data.},
  author       = {Serin, Emin and Ritter, Kerstin and Schumann, Gunter and Banaschewski, Tobias and Marquand, Andre and Walter, Henrik and Ogoh, George and Stahl, Bernd Carsten and Brandlistuen, Ragnhild and Schikowski, Tamara and Young, Allan H. and Xinyang, Yu and Zhang, Zuo and Agunbiade, Kofoworola and Chen, Di and Desrivières, Sylvane and Clinton, Nicholas and Thompson, Paul and Köhler, Venessa and Schwalber, Ameli and Calhoun, Vince D. and Chang, Xiao and Zhang, Yanqing and Li, Yuzhu and Dai, Yuxiang and Yuan, Jiacan and Xia, Yunman and Jia, Tianye and Renner, Paul and Hese, Sören and Spanlang, Bernhard and Pearmund, Charlie and Athanasiadis, Anastasios Polykarpos and Petkoski, Spase and Jirsa, Viktor and Schmitt, Karen and Wilbertz, Johannes H. and Patraskaki, Myrto and Sommer, Peter and Heilmann-Heimbach, Stefanie and Mathey, Carina M. and Miller, Abigail J. and Claus, Isabelle and Nöthen, Markus M. and Hoffmann, Per and Forstner, Andreas J. and Pastor, Alvaro and Gallego, Jaime and Itatani, Reiya and Eiroa-Orosa, Francisco and Feixas, Guillem and Slater, Mel and Novarino, Gaia and Böttger, Sarah Jane and Tschorn, Mira and Rapp, Michael and Ask, Helga and Kjelkenes, Rikka and Fernandez, Sara and Van Der Meer, Dennis and Westlye, Lars T. and Andreassen, Ole A. and Aden, Rieke and Seefried, Beke and Nees, Frauke and Neidhart, Maja and Stringaris, Argyris and Schwarz, Emanuel and Holz, Nathalie and Tost, Heike and Meyer-Lindenberg, Andreas and Christmann, Nina and Janson, Karina and Schepanski, Kerstin and Schütz, Tatjana and Taron, Ulrike Helene and Eils, Roland and Roy, Jean Charles and Lett, Tristram A. and Kebir, Hedi and Polemiti, Elli and Hitchen, Esther and Jentsch, Marcel and Serin, Emin and Bernas, Antoine and Vaidya, Nilakshi and Twardziok, Sven and Ralser, Markus and Heinz, Andreas and Schumann, Gunter},
  issn         = {2399-3642},
  journal      = {Communications Biology},
  publisher    = {Springer Nature},
  title        = {{Generating synthetic task-based brain fingerprints for population neuroscience using deep learning}},
  doi          = {10.1038/s42003-025-09158-6},
  volume       = {8},
  year         = {2025},
}

@article{20731,
  abstract     = {The adult human brain, under resting conditions, consumes approximately 20% of total body glucose, a demand that is even higher during the first decade of life. The brain metabolic landscape is intricately regulated throughout development, and each cell type exhibits distinct metabolic signatures at each specific stage. This picture becomes even more intricate when considering that metabolism is dynamically modulated to sustain critical biological processes, such as cell proliferation and differentiation and synaptic activity–dependent processes. The orchestration between metabolic regulation and the aforementioned physiological processes often relies on metabolism-dependent changes in the epigenetic landscape, which shape gene expression patterns to trigger selected downstream biological responses. Perturbations of brain metabolic pathways are frequently the cause of severe neurodevelopmental disorders. This review explores the latest insights into the regulation of brain metabolism in health and disease.},
  author       = {Marano, Domenico and Mariano, Vittoria and Novarino, Gaia},
  issn         = {1545-2948},
  journal      = {Annual Review of Genetics},
  pages        = {415--434},
  publisher    = {Annual Reviews},
  title        = {{Fueling the mind: Brain metabolism in health and neurodevelopmental disorders}},
  doi          = {10.1146/annurev-genet-111523-102424},
  volume       = {59},
  year         = {2025},
}

@article{14257,
  abstract     = {Mapping the complex and dense arrangement of cells and their connectivity in brain tissue demands nanoscale spatial resolution imaging. Super-resolution optical microscopy excels at visualizing specific molecules and individual cells but fails to provide tissue context. Here we developed Comprehensive Analysis of Tissues across Scales (CATS), a technology to densely map brain tissue architecture from millimeter regional to nanometer synaptic scales in diverse chemically fixed brain preparations, including rodent and human. CATS uses fixation-compatible extracellular labeling and optical imaging, including stimulated emission depletion or expansion microscopy, to comprehensively delineate cellular structures. It enables three-dimensional reconstruction of single synapses and mapping of synaptic connectivity by identification and analysis of putative synaptic cleft regions. Applying CATS to the mouse hippocampal mossy fiber circuitry, we reconstructed and quantified the synaptic input and output structure of identified neurons. We furthermore demonstrate applicability to clinically derived human tissue samples, including formalin-fixed paraffin-embedded routine diagnostic specimens, for visualizing the cellular architecture of brain tissue in health and disease.},
  author       = {Michalska, Julia M and Lyudchik, Julia and Velicky, Philipp and Korinkova, Hana and Watson, Jake and Cenameri, Alban and Sommer, Christoph M and Amberg, Nicole and Venturino, Alessandro and Roessler, Karl and Czech, Thomas and Höftberger, Romana and Siegert, Sandra and Novarino, Gaia and Jonas, Peter M and Danzl, Johann G},
  issn         = {1546-1696},
  journal      = {Nature Biotechnology},
  pages        = {1051--1064},
  publisher    = {Springer Nature},
  title        = {{Imaging brain tissue architecture across millimeter to nanometer scales}},
  doi          = {10.1038/s41587-023-01911-8},
  volume       = {42},
  year         = {2024},
}

@misc{15385,
  abstract     = {Relevant information about the data can be found in the 'Readme_Data.txt' file. 
A previous version of the publication can be found on BioRxiv: https://www.biorxiv.org/content/10.1101/2022.10.11.511691v4
and published in Plos Biology (2024)},
  author       = {Burnett, Laura and Koppensteiner, Peter and Symonova, Olga and Masson, Tomas and Vega Zuniga, Tomas A and Contreras, Ximena and Rülicke, Thomas and Shigemoto, Ryuichi and Novarino, Gaia and Jösch, Maximilian A},
  keywords     = {ASD, periaqueductal gray, perception, behavior, potassium channels},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Shared behavioural impairments in visual perception and place avoidance across different autism models are driven by periaqueductal grey hypoexcitability in Setd5 haploinsufficient mice}},
  doi          = {10.15479/AT:ISTA:15385},
  year         = {2024},
}

@article{17091,
  abstract     = {DNA sequences are connected to genes and functions in the developing and adult brain},
  author       = {Novarino, Gaia and Bock, Christoph},
  issn         = {1095-9203},
  journal      = {Science},
  number       = {6698},
  pages        = {860--861},
  publisher    = {AAAS},
  title        = {{Mapping the brain’s gene-regulatory maze}},
  doi          = {10.1126/science.adp4663},
  volume       = {384},
  year         = {2024},
}

@article{17142,
  abstract     = {Despite the diverse genetic origins of autism spectrum disorders (ASDs), affected individuals share strikingly similar and correlated behavioural traits that include perceptual and sensory processing challenges. Notably, the severity of these sensory symptoms is often predictive of the expression of other autistic traits. However, the origin of these perceptual deficits remains largely elusive. Here, we show a recurrent impairment in visual threat perception that is similarly impaired in 3 independent mouse models of ASD with different molecular aetiologies. Interestingly, this deficit is associated with reduced avoidance of threatening environments—a nonperceptual trait. Focusing on a common cause of ASDs, the Setd5 gene mutation, we define the molecular mechanism. We show that the perceptual impairment is caused by a potassium channel (Kv1)-mediated hypoexcitability in a subcortical node essential for the initiation of escape responses, the dorsal periaqueductal grey (dPAG). Targeted pharmacological Kv1 blockade rescued both perceptual and place avoidance deficits, causally linking seemingly unrelated trait deficits to the dPAG. Furthermore, we show that different molecular mechanisms converge on similar behavioural phenotypes by demonstrating that the autism models Cul3 and Ptchd1, despite having similar behavioural phenotypes, differ in their functional and molecular alteration. Our findings reveal a link between rapid perception controlled by subcortical pathways and appropriate learned interactions with the environment and define a nondevelopmental source of such deficits in ASD.},
  author       = {Burnett, Laura and Koppensteiner, Peter and Symonova, Olga and Masson, Tomas and Vega Zuniga, Tomas A and Contreras, Ximena and Rülicke, Thomas and Shigemoto, Ryuichi and Novarino, Gaia and Jösch, Maximilian A},
  issn         = {1545-7885},
  journal      = {PLoS Biology},
  publisher    = {Public Library of Science},
  title        = {{Shared behavioural impairments in visual perception and place avoidance across different autism models are driven by periaqueductal grey hypoexcitability in Setd5 haploinsufficient mice}},
  doi          = {10.1371/journal.pbio.3002668},
  volume       = {22},
  year         = {2024},
}

@unpublished{18677,
  abstract     = {The information-processing capability of the brain’s cellular network depends on the physical wiring pattern between neurons and their molecular and functional characteristics. Mapping neurons and resolving their individual synaptic connections can be achieved by volumetric imaging at nanoscale resolution with dense cellular labeling. Light microscopy is uniquely positioned to visualize specific molecules but dense, synapse-level circuit reconstruction by light microscopy has been out of reach due to limitations in resolution, contrast, and volumetric imaging capability. Here we developed light-microscopy based connectomics (LICONN). We integrated specifically engineered hydrogel embedding and expansion with comprehensive deep-learning based segmentation and analysis of connectivity, thus directly incorporating molecular information in synapse-level brain tissue reconstructions. LICONN will allow synapse-level brain tissue phenotyping in biological experiments in a readily adoptable manner.},
  author       = {Tavakoli, Mojtaba and Lyudchik, Julia and Januszewski, Michał and Vistunou, Vitali and Agudelo Duenas, Nathalie and Vorlaufer, Jakob and Sommer, Christoph M and Kreuzinger, Caroline and Oliveira, Bárbara and Cenameri, Alban and Novarino, Gaia and Jain, Viren and Danzl, Johann G},
  booktitle    = {bioRxiv},
  title        = {{Light-microscopy based dense connectomic reconstruction of mammalian brain tissue}},
  doi          = {10.1101/2024.03.01.582884},
  year         = {2024},
}

@article{18779,
  abstract     = {Unsupervised segmentation in biological and non-biological images is only partially resolved. Segmentation either requires arbitrary thresholds or large teaching datasets. Here, we propose a spatial autocorrelation method based on Local Moran’s <jats:italic>I</jats:italic> coefficient to differentiate signal, background, and noise in any type of image. The method, originally described for geoinformatics, does not require a predefined intensity threshold or teaching algorithm for image segmentation and allows quantitative comparison of samples obtained in different conditions. It utilizes relative intensity as well as spatial information of neighboring elements to select spatially contiguous groups of pixels. We demonstrate that Moran’s method outperforms threshold-based method in both artificially generated as well as in natural images especially when background noise is substantial. This superior performance can be attributed to the exclusion of false positive pixels resulting from isolated, high intensity pixels in high noise conditions. To test the method’s power in real situation, we used high power confocal images of the somatosensory thalamus immunostained for Kv4.2 and Kv4.3 (A-type) voltage-gated potassium channels in mice. Moran’s method identified high-intensity Kv4.2 and Kv4.3 ion channel clusters in the thalamic neuropil. Spatial distribution of these clusters displayed strong correlation with large sensory axon terminals of subcortical origin. The unique association of the special presynaptic terminals and a postsynaptic voltage-gated ion channel cluster was confirmed with electron microscopy. These data demonstrate that Moran’s method is a rapid, simple image segmentation method optimal for variable and high noise conditions.},
  author       = {Dávid, Csaba and Giber, Kristóf and Szigeti, Margit Katalin and Köllő, Mihály and Nusser, Zoltan and Acsady, Laszlo},
  issn         = {2050-084X},
  journal      = {eLife},
  publisher    = {eLife Sciences Publications},
  title        = {{A novel image segmentation method based on spatial autocorrelation identifies A-type potassium channel clusters in the thalamus}},
  doi          = {10.7554/elife.89361},
  volume       = {12},
  year         = {2024},
}

@article{19446,
  abstract     = {This Comment explores new approaches to enrich large-scale population data, including incorporating macro-environmental and digital health measures.},
  author       = {Nees, Frauke and Renner, Paul and Holz, Nathalie E. and Polemiti, Elli and Siehl, Sebastian and Hese, Sören and Schepanski, Kerstin and Schumann, Gunter and Walter, Henrik and Heinz, Andreas and Ralser, Markus and Twardziok, Sven and Vaidya, Nilakshi and Bernas, Antoine and Serin, Emin and Jentsch, Marcel and Hitchen, Esther and Kebir, Hedi and Lett, Tristram A. and Roy, Jean Charles and Eils, Roland and Taron, Ulrike Helene and Schütz, Tatjana and Banks, Jamie and Banaschewski, Tobias and Jansone, Karina and Christmann, Nina and Meyer-Lindenberg, Andreas and Tost, Heike and Holz, Nathalie and Schwarz, Emanuel and Stringaris, Argyris and Neidhart, Maja and Seefried, Beke and Aden, Rieke and Andreassen, Ole A. and Westlye, Lars T. and Van Der Meer, Dennis and Fernandez, Sara and Kjelkenes, Rikka and Ask, Helga and Rapp, Michael and Tschorn, Mira and Böttger, Sarah Jane and Marquand, Andre and Novarino, Gaia and Marr, Lena and Slater, Mel and Viapiana, Guillem Feixas and Orosa, Francisco Eiroa and Gallego, Jaime and Pastor, Alvaro and Forstner, Andreas J. and Hoffmann, Per and Nöthen, Markus M. and Claus, Isabelle and Miller, Abigail and Mathey, Carina M. and Heilmann-Heimbach, Stefanie and Sommer, Peter and Patraskaki, Myrto and Wilbertz, Johannes and Schmitt, Karen and Jirsa, Viktor and Petkoski, Spase and Pitel, Séverine and Otten, Lisa and Athanasiadis, Anastasios Polykarpos and Pearmund, Charlie and Spanlang, Bernhard and Alvarez, Elena and Sanchez, Mavi and Giner, Arantxa and Jia, Tianye and Gong, Yanting and Xia, Yunman and Chang, Xiao and Calhoun, Vince and Liu, Jingyu and Schwalber, Ameli and Thompson, Paul and Clinton, Nicholas and Desrivières, Sylvane and Young, Allan H. and Stahl, Bernd and Ogoh, George},
  issn         = {2731-6076},
  journal      = {Nature Mental Health},
  number       = {10},
  pages        = {1124--1127},
  publisher    = {Springer Nature},
  title        = {{Large-scale population data enrichment in mental health research}},
  doi          = {10.1038/s44220-024-00316-z},
  volume       = {2},
  year         = {2024},
}

@article{20039,
  abstract     = {This Comment presents a high-level protocol for data harmonization within large cohorts, in which it postulates four main steps including (1) expert review, (2) pre-statistical harmonization, (3) statistical harmonization, and (4) validation.},
  author       = {Neidhart, Maja and Kjelkenes, Rikka and Jansone, Karina and Rehák Bučková, Barbora and Holz, Nathalie and Nees, Frauke and Walter, Henrik and Schumann, Gunter and Rapp, Michael A. and Banaschewski, Tobias and Schwarz, Emanuel and Marquand, Andre and Ogoh, George and Stahl, Bernd and Young, Allan H. and Desrivières, Sylvane and Clinton, Nicholas and Thompson, Paul and Schwalber, Ameli and Liu, Jingyu and Calhoun, Vince and Chang, Xiao and Xia, Yunman and Gong, Yanting and Jia, Tianye and Renner, Paul and Hese, Sören and Giner, Arantxa and Sanchez, Mavi and Alvarez, Elena and Spanlang, Bernhard and Pearmund, Charlie and Athanasiadis, Anastasios Polykarpos and Otten, Lisa and Pitel, Séverine and Petkoski, Spase and Jirsa, Viktor and Schmitt, Karen and Wilbertz, Johannes and Patraskaki, Myrto and Sommer, Peter and Heilmann-Heimbach, Stefanie and Mathey, Carina M. and Miller, Abigail and Claus, Isabelle and Nöthen, Markus M. and Hoffmann, Per and Forstner, Andreas J. and Pastor, Alvaro and Gallego, Jaime and Orosa, Francisco Eiroa and Viapiana, Guillem Feixas and Slater, Mel and Marr, Lena and Novarino, Gaia and Böttger, Sarah Jane and Tschorn, Mira and Rapp, Michael and Ask, Helga and Fernandez, Sara and Van Der Meer, Dennis and Westlye, Lars T. and Andreassen, Ole A. and Aden, Rieke and Seefried, Beke and Siehl, Sebastian and Nees, Frauke and Stringaris, Argyris and Tost, Heike and Meyer-Lindenberg, Andreas and Christmann, Nina and Banks, Jamie and Schepanski, Kerstin and Schütz, Tatjana and Taron, Ulrike Helene and Eils, Roland and Roy, Jean Charles and Lett, Tristram A. and Kebir, Hedi and Polemiti, Elli and Hitchen, Esther and Jentsch, Marcel and Serin, Emin and Bernas, Antoine and Vaidya, Nilakshi and Twardziok, Sven and Ralser, Markus and Heinz, Andreas},
  issn         = {2731-6076},
  journal      = {Nature Mental Health},
  number       = {10},
  pages        = {1134--1137},
  publisher    = {Springer Nature},
  title        = {{A protocol for data harmonization in large cohorts}},
  doi          = {10.1038/s44220-024-00315-0},
  volume       = {2},
  year         = {2024},
}

@article{20156,
  abstract     = {Integrative analyses that incorporate different levels of ‘-omics’ data represent a powerful tool for deciphering the biological mechanisms that underlie environmental influences on mental health and disease. This Comment highlights various aspects of such multi-omics approaches, using the example of the EU-funded environMENTAL project.},
  author       = {Desrivières, Sylvane and Miller, Abigail and Mathey, Carina M. and Yu, Xinyang and Chen, Di and Agunbiade, Kofoworola and Heilmann-Heimbach, Stefanie and Forstner, Andreas J. and Schumann, Gunter and Hoffmann, Per and Nöthen, Markus M. and Ogoh, George and Stahl, Bernd and Young, Allan H. and Clinton, Nicholas and Thompson, Paul and Schwalber, Ameli and Liu, Jingyu and Calhoun, Vince and Chang, Xiao and Xia, Yunman and Gong, Yanting and Jia, Tianye and Renner, Paul and Hese, Sören and Giner, Arantxa and Sanchez, Mavi and Alvarez, Elena and Spanlang, Bernhard and Pearmund, Charlie and Athanasiadis, Anastasios Polykarpos and Otten, Lisa and Pitel, Séverine and Petkoski, Spase and Jirsa, Viktor and Schmitt, Karen and Wilbertz, Johannes and Patraskaki, Myrto and Sommer, Peter and Claus, Isabelle and Pastor, Alvaro and Gallego, Jaime and Orosa, Francisco Eiroa and Viapiana, Guillem Feixas and Slater, Mel and Marr, Lena and Novarino, Gaia and Marquand, Andre and Böttger, Sarah Jane and Tschorn, Mira and Rapp, Michael and Ask, Helga and Kjelkenes, Rikka and Fernandez, Sara and Van Der Meer, Dennis and Westlye, Lars T. and Andreassen, Ole A. and Aden, Rieke and Seefried, Beke and Siehl, Sebastian and Nees, Frauke and Neidhart, Maja and Stringaris, Argyris and Schwarz, Emanuel and Holz, Nathalie and Tost, Heike and Meyer-Lindenberg, Andreas and Christmann, Nina and Jansone, Karina and Banaschewski, Tobias and Banks, Jamie and Schepanski, Kerstin and Schütz, Tatjana and Taron, Ulrike Helene and Eils, Roland and Roy, Jean Charles and Lett, Tristram A. and Kebir, Hedi and Polemiti, Elli and Hitchen, Esther and Jentsch, Marcel and Serin, Emin and Bernas, Antoine and Vaidya, Nilakshi and Twardziok, Sven and Ralser, Markus and Heinz, Andreas and Walter, Henrik},
  issn         = {2731-6076},
  journal      = {Nature Mental Health},
  number       = {10},
  pages        = {1131--1133},
  publisher    = {Springer Nature},
  title        = {{Multi-omics analyses of the environMENTAL project provide insights into mental health and disease}},
  doi          = {10.1038/s44220-024-00317-y},
  volume       = {2},
  year         = {2024},
}

@article{20157,
  abstract     = {The focus of much of contemporary research ethics is on compliance with established protocols. However, large data-driven neuroscience research raises new ethical concerns that have no agreed-upon solution. Here we reflect on these challenges and propose better integration of public and patient involvement in this evolving landscape.},
  author       = {Stahl, Bernd and Ogoh, George and Schumann, Gunter and Walter, Henrik and Stahl, Bernd and Young, Allan H. and Desrivières, Sylvane and Clinton, Nicholas and Thompson, Paul and Schwalber, Ameli and Liu, Jingyu and Calhoun, Vince and Chang, Xiao and Xia, Yunman and Gong, Yanting and Jia, Tianye and Renner, Paul and Hese, Sören and Giner, Arantxa and Sanchez, Mavi and Alvarez, Elena and Spanlang, Bernhard and Pearmund, Charlie and Athanasiadis, Anastasios Polykarpos and Otten, Lisa and Pitel, Séverine and Petkoski, Spase and Jirsa, Viktor and Schmitt, Karen and Wilbertz, Johannes and Patraskaki, Myrto and Sommer, Peter and Heilmann-Heimbach, Stefanie and Mathey, Carina M. and Miller, Abigail and Claus, Isabelle and Nöthen, Markus M. and Hoffmann, Per and Forstner, Andreas J. and Pastor, Alvaro and Gallego, Jaime and Orosa, Francisco Eiroa and Viapiana, Guillem Feixas and Slater, Mel and Marr, Lena and Novarino, Gaia and Marquand, Andre and Böttger, Sarah Jane and Tschorn, Mira and Rapp, Michael and Ask, Helga and Kjelkenes, Rikka and Fernandez, Sara and Van Der Meer, Dennis and Westlye, Lars T. and Andreassen, Ole A. and Aden, Rieke and Seefried, Beke and Siehl, Sebastian and Nees, Frauke and Neidhart, Maja and Stringaris, Argyris and Schwarz, Emanuel and Holz, Nathalie and Tost, Heike and Meyer-Lindenberg, Andreas and Christmann, Nina and Jansone, Karina and Banaschewski, Tobias and Banks, Jamie and Schepanski, Kerstin and Schütz, Tatjana and Taron, Ulrike Helene and Eils, Roland and Roy, Jean Charles and Lett, Tristram A. and Kebir, Hedi and Polemiti, Elli and Hitchen, Esther and Jentsch, Marcel and Serin, Emin and Bernas, Antoine and Vaidya, Nilakshi and Twardziok, Sven and Ralser, Markus and Heinz, Andreas and Walter, Henrik},
  issn         = {2731-6076},
  journal      = {Nature Mental Health},
  number       = {10},
  publisher    = {Springer Nature},
  title        = {{Rethinking ethics in interdisciplinary and big data-driven neuroscience projects}},
  doi          = {10.1038/s44220-024-00320-3},
  volume       = {2},
  year         = {2024},
}

@article{17331,
  abstract     = {Amyloidosis are a group of diseases in which soluble proteins aggregate and deposit in fibrillar conformation extracellularly in tissues. The effectiveness of therapeutic strategies depends on the specific protein involved, being crucial to accurately determine its nature. Moreover, following the diagnosis, the search for the mutation within relatives allows the clinical advice. Here we report the precise diagnosis and explored the possible reasons of the structural pathogenicity for a renal amyloidosis related to a fibrinogen Aα-chain variant. Whole-exome sequencing and GATK calling pipeline were leveraged to characterize the protein variant present in a patient with kidney failure. Bioinformatics strategies were applied to suggest potential explanations of the variants aggregation. Our pipeline allowed the identification of a single-point variant of fibrinogen Aα-chain, which opened the possibility of curative transplantation. In silico structural analysis suggested that the pathogenicity of the variant may be attributed to a heightened susceptibility to yield a peptide prone to deposit as an oligomer with a β-sheet structure. Exploiting the comprehensive coverage of whole-genome sequencing, we managed to fill a vacant stage in the diagnosis of hereditary amyloidosis and to stimulate the advancement in biomedicine.},
  author       = {Cattaneo, Elizabeth R and Gisonno, Romina A and Abba, Martín C and Santana, Marianela and Rosú, Silvana A and Nucifora, Elsa and Aguirre, María A and Giordani, María C and Tricerri, M. Alejandra and Ramella, Nahuel A},
  issn         = {1097-0134},
  journal      = {Proteins: Structure, Function and Bioinformatics},
  number       = {12},
  pages        = {1366--1374},
  publisher    = {Wiley},
  title        = {{Hereditary amyloidosis: Insights into a fibrinogen A variant protein}},
  doi          = {10.1002/prot.26732},
  volume       = {92},
  year         = {2024},
}

@article{12802,
  abstract     = {Little is known about the critical metabolic changes that neural cells have to undergo during development and how temporary shifts in this program can influence brain circuitries and behavior. Inspired by the discovery that mutations in SLC7A5, a transporter of metabolically essential large neutral amino acids (LNAAs), lead to autism, we employed metabolomic profiling to study the metabolic states of the cerebral cortex across different developmental stages. We found that the forebrain undergoes significant metabolic remodeling throughout development, with certain groups of metabolites showing stage-specific changes, but what are the consequences of perturbing this metabolic program? By manipulating Slc7a5 expression in neural cells, we found that the metabolism of LNAAs and lipids are interconnected in the cortex. Deletion of Slc7a5 in neurons affects the postnatal metabolic state, leading to a shift in lipid metabolism. Additionally, it causes stage- and cell-type-specific alterations in neuronal activity patterns, resulting in a long-term circuit dysfunction.},
  author       = {Knaus, Lisa and Basilico, Bernadette and Malzl, Daniel and Gerykova Bujalkova, Maria and Smogavec, Mateja and Schwarz, Lena A. and Gorkiewicz, Sarah and Amberg, Nicole and Pauler, Florian and Knittl-Frank, Christian and Tassinari, Marianna and Maulide, Nuno and Rülicke, Thomas and Menche, Jörg and Hippenmeyer, Simon and Novarino, Gaia},
  issn         = {0092-8674},
  journal      = {Cell},
  keywords     = {General Biochemistry, Genetics and Molecular Biology},
  number       = {9},
  pages        = {1950--1967.e25},
  publisher    = {Elsevier},
  title        = {{Large neutral amino acid levels tune perinatal neuronal excitability and survival}},
  doi          = {10.1016/j.cell.2023.02.037},
  volume       = {186},
  year         = {2023},
}

@phdthesis{13107,
  abstract     = {Within the human body, the brain exhibits the highest rate of energy consumption amongst all organs, with the majority of generated ATP being utilized to sustain neuronal activity. Therefore, the metabolism of the mature cerebral cortex is geared towards preserving metabolic homeostasis whilst generating significant amounts of energy. This requires a precise interplay between diverse metabolic pathways, spanning from a tissue-wide scale to the level of individual neurons. Disturbances to this delicate metabolic equilibrium, such as those resulting from maternal malnutrition
or mutations affecting metabolic enzymes, often result in neuropathological variants of neurodevelopment. For instance, mutations in SLC7A5, a transporter of metabolically essential large neutral amino acids (LNAAs), have been associated with autism and microcephaly. However, despite recent progress in the field, the extent of metabolic restructuring that occurs within the developing brain and the corresponding alterations in nutrient demands during various critical periods remain largely unknown. To investigate this, we performed metabolomic profiling of the murine cerebral cortex to characterize the metabolic state of the forebrain at different developmental stages. We found that the developing cortex undergoes substantial metabolic reprogramming, with specific sets of metabolites displaying stage-specific changes. According to our observations, we determined a distinct temporal period in postnatal development during which the cortex displays heightened reliance on LNAAs. Hence, using a conditional knock-out mouse model, we deleted Slc7a5 in neural cells, allowing us to monitor the impact of a perturbed neuronal metabolic state across multiple developmental stages of corticogenesis. We found that manipulating the levels of essential LNAAs in cortical neurons in vivo affects one particular perinatal developmental period critical for cortical network refinement. Abnormally low intracellular LNAA levels result in cell-autonomous alterations in neuronal lipid metabolism, excitability, and survival during this particular time window. Although most of the effects of Slc7a5 deletion on neuronal physiology are transient, derailment of these processes during this brief but crucial window leads to long-term circuit dysfunction in mice. In conclusion, out data indicate that the cerebral cortex undergoes significant metabolic reorganization during development. This process involves the intricate integration of multiple metabolic pathways to ensure optimal neuronal function throughout different developmental stages. Our findings offer a paradigm for understanding how neurons synchronize the expression of nutrient-related genes with their activity to allow proper brain maturation. Further, our results demonstrate that disruptions in these precisely calibrated metabolic processes during critical periods of brain development may result in neuropathological outcomes in mice and in humans.},
  author       = {Knaus, Lisa},
  issn         = {2663-337X},
  pages        = {147},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{The metabolism of the developing brain : How large neutral amino acids modulate perinatal neuronal excitability and survival}},
  doi          = {10.15479/at:ista:13107},
  year         = {2023},
}