@phdthesis{12364,
abstract = {Autism spectrum disorders (ASDs) are a group of neurodevelopmental disorders characterized by behavioral symptoms such as problems in social communication and interaction, as
well as repetitive, restricted behaviors and interests. These disorders show a high degree
of heritability and hundreds of risk genes have been identifed using high throughput
sequencing technologies. This genetic heterogeneity has hampered eforts in understanding
the pathogenesis of ASD but at the same time given rise to the concept of convergent
mechanisms. Previous studies have identifed that risk genes for ASD broadly converge
onto specifc functional categories with transcriptional regulation being one of the biggest
groups. In this thesis, I focus on this subgroup of genes and investigate the gene regulatory
consequences of some of them in the context of neurodevelopment.
First, we showed that mutations in the ASD and intellectual disability risk gene Setd5 lead
to perturbations of gene regulatory programs in early cell fate specifcation. In addition,
adult animals display abnormal learning behavior which is mirrored at the transcriptional
level by altered activity dependent regulation of postsynaptic gene expression. Lastly,
we link the regulatory function of Setd5 to its interaction with the Paf1 and the NCoR
complex.
Second, by modeling the heterozygous loss of the top ASD gene CHD8 in human cerebral
organoids we demonstrate profound changes in the developmental trajectories of both
inhibitory and excitatory neurons using single cell RNA-sequencing. While the former
were generated earlier in CHD8+/- organoids, the generation of the latter was shifted to
later times in favor of a prolonged progenitor expansion phase and ultimately increased
organoid size.
Finally, by modeling heterozygous mutations for four ASD associated chromatin modifers,
ASH1L, KDM6B, KMT5B, and SETD5 in human cortical spheroids we show evidence of
regulatory convergence across three of those genes. We observe a shift from dorsal cortical
excitatory neuron fates towards partially ventralized cell types resembling cells from the
lateral ganglionic eminence. As this project is still ongoing at the time of writing, future
experiments will aim at elucidating the regulatory mechanisms underlying this shift with
the aim of linking these three ASD risk genes through biological convergence.},
author = {Dotter, Christoph},
issn = {2663-337X},
pages = {152},
publisher = {Institute of Science and Technology Austria},
title = {{Transcriptional consequences of mutations in genes associated with Autism Spectrum Disorder}},
doi = {10.15479/at:ista:12094},
year = {2022},
}
@phdthesis{11393,
abstract = {AMPA receptors (AMPARs) mediate fast excitatory neurotransmission and their role is
implicated in complex processes such as learning and memory and various neurological
diseases. These receptors are composed of different subunits and the subunit composition can
affect channel properties, receptor trafficking and interaction with other associated proteins.
Using the high sensitivity SDS-digested freeze-fracture replica labeling (SDS-FRL) for
electron microscopy I investigated the number, density, and localization of AMPAR subunits,
GluA1, GluA2, GluA3, and GluA1-3 (panAMPA) in pyramidal cells in the CA1 area of mouse
hippocampus. I have found that the immunogold labeling for all of these subunits in the
postsynaptic sites was highest in stratum radiatum and lowest in stratum lacunosummoleculare. The labeling density for the all subunits in the extrasynaptic sites showed a gradual
increase from the pyramidal cell soma towards the distal part of stratum radiatum. The densities
of extrasynaptic GluA1, GluA2 and panAMPA labeling reached 10-15% of synaptic densities,
while the ratio of extrasynaptic labeling for GluA3 was significantly lower compared than those
for other subunits. The labeling patterns for GluA1, GluA2 and GluA1-3 are similar and their
densities were higher in the periphery than center of synapses. In contrast, the GluA3-
containing receptors were more centrally localized compared to the GluA1- and GluA2-
containing receptors.
The hippocampus plays a central role in learning and memory. Contextual learning has been
shown to require the delivery of AMPA receptors to CA1 synapses in the dorsal hippocampus.
However, proximodistal heterogeneity of this plasticity and particular contribution of different
AMPA receptor subunits are not fully understood. By combining inhibitory avoidance task, a
hippocampus-dependent contextual fear-learning paradigm, with SDS-FRL, I have revealed an
increase in synaptic density specific to GluA1-containing AMPA receptors in the CA1 area.
The intrasynaptic distribution of GluA1 also changed from the periphery to center-preferred
pattern. Furthermore, this synaptic plasticity was evident selectively in stratum radiatum but
not stratum oriens, and in the CA1 subregion proximal but not distal to CA2. These findings
further contribute to our understanding of how specific hippocampal subregions and AMPA
receptor subunits are involved in physiological learning.
Although the immunolabeling results above shed light on subunit-specific plasticity in
AMPAR distribution, no tools to visualize and study the subunit composition at the single
channel level in situ have been available. Electron microscopy with conventional immunogold
labeling approaches has limitations in the single channel analysis because of the large size of
antibodies and steric hindrance hampering multiple subunit labeling of single channels. I
managed to develop a new chemical labeling system using a short peptide tag and small
synthetic probes, which form specific covalent bond with a cysteine residue in the tag fused to
proteins of interest (reactive tag system). I additionally made substantial progress into adapting
this system for AMPA receptor subunits.},
author = {Jevtic, Marijo},
issn = {2663-337X},
pages = {108},
publisher = {Institute of Science and Technology Austria},
title = {{Contextual fear learning induced changes in AMPA receptor subtypes along the proximodistal axis in dorsal hippocampus}},
doi = {10.15479/at:ista:11393},
year = {2022},
}
@phdthesis{12366,
abstract = {Recent substantial advances in the feld of superconducting circuits have shown its
potential as a leading platform for future quantum computing. In contrast to classical
computers based on bits that are represented by a single binary value, 0 or 1, quantum
bits (or qubits) can be in a superposition of both. Thus, quantum computers can store
and handle more information at the same time and a quantum advantage has already
been demonstrated for two types of computational tasks. Rapid progress in academic
and industry labs accelerates the development of superconducting processors which may
soon fnd applications in complex computations, chemical simulations, cryptography, and
optimization. Now that these machines are scaled up to tackle such problems the questions
of qubit interconnects and networks becomes very relevant. How to route signals on-chip
between diferent processor components? What is the most efcient way to entangle
qubits? And how to then send and process entangled signals between distant cryostats
hosting superconducting processors?
In this thesis, we are looking for solutions to these problems by studying the collective
behavior of superconducting qubit ensembles. We frst demonstrate on-demand tunable
directional scattering of microwave photons from a pair of qubits in a waveguide. Such a
device can route microwave photons on-chip with a high diode efciency. Then we focus
on studying ultra-strong coupling regimes between light (microwave photons) and matter
(superconducting qubits), a regime that could be promising for extremely fast multi-qubit
entanglement generation. Finally, we show coherent pulse storage and periodic revivals
in a fve qubit ensemble strongly coupled to a resonator. Such a reconfgurable storage
device could be used as part of a quantum repeater that is needed for longer-distance
quantum communication.
The achieved high degree of control over multi-qubit ensembles highlights not only the
beautiful physics of circuit quantum electrodynamics, it also represents the frst step
toward new quantum simulation and communication methods, and certain techniques
may also fnd applications in future superconducting quantum computing hardware.
},
author = {Redchenko, Elena},
isbn = {978-3-99078-024-4},
issn = {2663-337X},
pages = {168},
publisher = {Institute of Science and Technology Austria},
title = {{Controllable states of superconducting Qubit ensembles}},
doi = {10.15479/at:ista:12132},
year = {2022},
}
@unpublished{11943,
abstract = {Complex wiring between neurons underlies the information-processing network enabling all brain functions, including cognition and memory. For understanding how the network is structured, processes information, and changes over time, comprehensive visualization of the architecture of living brain tissue with its cellular and molecular components would open up major opportunities. However, electron microscopy (EM) provides nanometre-scale resolution required for full in-silico reconstruction1–5, yet is limited to fixed specimens and static representations. Light microscopy allows live observation, with super-resolution approaches6–12 facilitating nanoscale visualization, but comprehensive 3D-reconstruction of living brain tissue has been hindered by tissue photo-burden, photobleaching, insufficient 3D-resolution, and inadequate signal-to-noise ratio (SNR). Here we demonstrate saturated reconstruction of living brain tissue. We developed an integrated imaging and analysis technology, adapting stimulated emission depletion (STED) microscopy6,13 in extracellularly labelled tissue14 for high SNR and near-isotropic resolution. Centrally, a two-stage deep-learning approach leveraged previously obtained information on sample structure to drastically reduce photo-burden and enable automated volumetric reconstruction down to single synapse level. Live reconstruction provides unbiased analysis of tissue architecture across time in relation to functional activity and targeted activation, and contextual understanding of molecular labelling. This adoptable technology will facilitate novel insights into the dynamic functional architecture of living brain tissue.},
author = {Velicky, Philipp and Miguel Villalba, Eder and Michalska, Julia M and Wei, Donglai and Lin, Zudi and Watson, Jake and Troidl, Jakob and Beyer, Johanna and Ben Simon, Yoav and Sommer, Christoph M and Jahr, Wiebke and Cenameri, Alban and Broichhagen, Johannes and Grant, Seth G. N. and Jonas, Peter M and Novarino, Gaia and Pfister, Hanspeter and Bickel, Bernd and Danzl, Johann G},
booktitle = {bioRxiv},
publisher = {Cold Spring Harbor Laboratory},
title = {{Saturated reconstruction of living brain tissue}},
doi = {10.1101/2022.03.16.484431},
year = {2022},
}
@unpublished{11950,
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 nanoscopic synaptic scales in diverse chemically fixed brain preparations, including rodent and human. CATS leverages fixation-compatible extracellular labeling and advanced optical readout, in particular stimulated-emission depletion and expansion microscopy, to comprehensively delineate cellular structures. It enables 3D-reconstructing single synapses and mapping synaptic connectivity by identification and tailored analysis of putative synaptic cleft regions. Applying CATS to the hippocampal mossy fiber circuitry, we demonstrate its power to reveal the system’s molecularly informed ultrastructure across spatial scales and assess local connectivity by reconstructing and quantifying the synaptic input and output structure of identified neurons.},
author = {Michalska, Julia M and Lyudchik, Julia and Velicky, Philipp and Korinkova, Hana and Watson, Jake and Cenameri, Alban and Sommer, Christoph M and Venturino, Alessandro and Roessler, Karl and Czech, Thomas and Siegert, Sandra and Novarino, Gaia and Jonas, Peter M and Danzl, Johann G},
booktitle = {bioRxiv},
publisher = {Cold Spring Harbor Laboratory},
title = {{Uncovering brain tissue architecture across scales with super-resolution light microscopy}},
doi = {10.1101/2022.08.17.504272},
year = {2022},
}
@article{10614,
abstract = {The infiltration of immune cells into tissues underlies the establishment of tissue-resident macrophages and responses to infections and tumors. Yet the mechanisms immune cells utilize to negotiate tissue barriers in living organisms are not well understood, and a role for cortical actin has not been examined. Here, we find that the tissue invasion of Drosophila macrophages, also known as plasmatocytes or hemocytes, utilizes enhanced cortical F-actin levels stimulated by the Drosophila member of the fos proto oncogene transcription factor family (Dfos, Kayak). RNA sequencing analysis and live imaging show that Dfos enhances F-actin levels around the entire macrophage surface by increasing mRNA levels of the membrane spanning molecular scaffold tetraspanin TM4SF, and the actin cross-linking filamin Cheerio, which are themselves required for invasion. Both the filamin and the tetraspanin enhance the cortical activity of Rho1 and the formin Diaphanous and thus the assembly of cortical actin, which is a critical function since expressing a dominant active form of Diaphanous can rescue the Dfos macrophage invasion defect. In vivo imaging shows that Dfos enhances the efficiency of the initial phases of macrophage tissue entry. Genetic evidence argues that this Dfos-induced program in macrophages counteracts the constraint produced by the tension of surrounding tissues and buffers the properties of the macrophage nucleus from affecting tissue entry. We thus identify strengthening the cortical actin cytoskeleton through Dfos as a key process allowing efficient forward movement of an immune cell into surrounding tissues. },
author = {Belyaeva, Vera and Wachner, Stephanie and György, Attila and Emtenani, Shamsi and Gridchyn, Igor and Akhmanova, Maria and Linder, M and Roblek, Marko and Sibilia, M and Siekhaus, Daria E},
issn = {1545-7885},
journal = {PLoS Biology},
number = {1},
pages = {e3001494},
publisher = {Public Library of Science},
title = {{Fos regulates macrophage infiltration against surrounding tissue resistance by a cortical actin-based mechanism in Drosophila}},
doi = {10.1371/journal.pbio.3001494},
volume = {20},
year = {2022},
}
@phdthesis{11193,
abstract = {The infiltration of immune cells into tissues underlies the establishment of tissue-resident
macrophages and responses to infections and tumors. However, the mechanisms immune
cells utilize to collectively migrate through tissue barriers in vivo are not yet well understood.
In this thesis, I describe two mechanisms that Drosophila immune cells (hemocytes) use to
overcome the tissue barrier of the germband in the embryo. One strategy is the strengthening
of the actin cortex through developmentally controlled transcriptional regulation induced by
the Drosophila proto-oncogene family member Dfos, which I show in Chapter 2. Dfos induces
expression of the tetraspanin TM4SF and the filamin Cher leading to higher levels of the
activated formin Dia at the cortex and increased cortical F-actin. This enhanced cortical
strength allows hemocytes to overcome the physical resistance of the surrounding tissue and
translocate their nucleus to move forward. This mechanism affects the speed of migration
when hemocytes face a confined environment in vivo.
Another aspect of the invasion process is the initial step of the leading hemocytes entering
the tissue, which potentially guides the follower cells. In Chapter 3, I describe a novel
subpopulation of hemocytes activated by BMP signaling prior to tissue invasion that leads
penetration into the germband. Hemocytes that are deficient in BMP signaling activation
show impaired persistence at the tissue entry, while their migration speed remains
unaffected.
This suggests that there might be different mechanisms controlling immune cell migration
within the confined environment in vivo, one of these being the general ability to overcome
the resistance of the surrounding tissue and another affecting the order of hemocytes that
collectively invade the tissue in a stream of individual cells.
Together, my findings provide deeper insights into transcriptional changes in immune
cells that enable efficient tissue invasion and pave the way for future studies investigating the
early colonization of tissues by macrophages in higher organisms. Moreover, they extend the
current view of Drosophila immune cell heterogeneity and point toward a potentially
conserved role for canonical BMP signaling in specifying immune cells that lead the migration
of tissue resident macrophages during embryogenesis.},
author = {Wachner, Stephanie},
issn = {2663-337X},
pages = {170},
publisher = {Institute of Science and Technology Austria},
title = {{Transcriptional regulation by Dfos and BMP-signaling support tissue invasion of Drosophila immune cells}},
doi = {10.15479/at:ista:11193},
year = {2022},
}
@phdthesis{11932,
abstract = {The ability to form and retrieve memories is central to survival. In mammals, the hippocampus
is a brain region essential to the acquisition and consolidation of new memories. It is also
involved in keeping track of one’s position in space and aids navigation. Although this
space-memory has been a source of contradiction, evidence supports the view that the role of
the hippocampus in navigation is memory, thanks to the formation of cognitive maps. First
introduced by Tolman in 1948, cognitive maps are generally used to organize experiences in
memory; however, the detailed mechanisms by which these maps are formed and stored are not
yet agreed upon. Some influential theories describe this process as involving three fundamental
steps: initial encoding by the hippocampus, interactions between the hippocampus and other
cortical areas, and long-term extra-hippocampal consolidation. In this thesis, I will show how
the investigation of cognitive maps of space helped to shed light on each of these three memory
processes.
The first study included in this thesis deals with the initial encoding of spatial memories in
the hippocampus. Much is known about encoding at the level of single cells, but less about
their co-activity or joint contribution to the encoding of novel spatial information. I will
describe the structure of an interaction network that allows for efficient encoding of noisy
spatial information during the first exploration of a novel environment.
The second study describes the interactions between the hippocampus and the prefrontal
cortex (PFC), two areas directly and indirectly connected. It is known that the PFC, in concert
with the hippocampus, is involved in various processes, including memory storage and spatial
navigation. Nonetheless, the detailed mechanisms by which PFC receives information from the
hippocampus are not clear. I will show how a transient improvement in theta phase locking of
PFC cells enables interactions of cell pairs across the two regions.
The third study describes the learning of behaviorally-relevant spatial locations in the hippocampus and the medial entorhinal cortex. I will show how the accumulation of firing around
goal locations, a correlate of learning, can shed light on the transition from short- to long-term
spatial memories and the speed of consolidation in different brain areas.
The studies included in this thesis represent the main scientific contributions of my Ph.D. They
involve statistical analyses and models of neural responses of cells in different brain areas of
rats executing spatial tasks. I will conclude the thesis by discussing the impact of the findings
on principles of memory formation and retention, including the mechanisms, the speed, and
the duration of these processes.},
author = {Nardin, Michele},
issn = {2663-337X},
pages = {136},
publisher = {Institute of Science and Technology Austria},
title = {{On the encoding, transfer, and consolidation of spatial memories}},
doi = {10.15479/at:ista:11932},
year = {2022},
}
@article{12244,
abstract = {Environmental cues influence the highly dynamic morphology of microglia. Strategies to characterize these changes usually involve user-selected morphometric features, which preclude the identification of a spectrum of context-dependent morphological phenotypes. Here we develop MorphOMICs, a topological data analysis approach, which enables semiautomatic mapping of microglial morphology into an atlas of cue-dependent phenotypes and overcomes feature-selection biases and biological variability. We extract spatially heterogeneous and sexually dimorphic morphological phenotypes for seven adult mouse brain regions. This sex-specific phenotype declines with maturation but increases over the disease trajectories in two neurodegeneration mouse models, with females showing a faster morphological shift in affected brain regions. Remarkably, microglia morphologies reflect an adaptation upon repeated exposure to ketamine anesthesia and do not recover to control morphologies. Finally, we demonstrate that both long primary processes and short terminal processes provide distinct insights to morphological phenotypes. MorphOMICs opens a new perspective to characterize microglial morphology.},
author = {Colombo, Gloria and Cubero, Ryan J and Kanari, Lida and Venturino, Alessandro and Schulz, Rouven and Scolamiero, Martina and Agerberg, Jens and Mathys, Hansruedi and Tsai, Li-Huei and Chachólski, Wojciech and Hess, Kathryn and Siegert, Sandra},
issn = {1546-1726},
journal = {Nature Neuroscience},
keywords = {General Neuroscience},
number = {10},
pages = {1379--1393},
publisher = {Springer Nature},
title = {{A tool for mapping microglial morphology, morphOMICs, reveals brain-region and sex-dependent phenotypes}},
doi = {10.1038/s41593-022-01167-6},
volume = {25},
year = {2022},
}
@phdthesis{12378,
abstract = {Environmental cues influence the highly dynamic morphology of microglia. Strategies to
characterize these changes usually involve user-selected morphometric features, which
preclude the identification of a spectrum of context-dependent morphological phenotypes.
Here, we develop MorphOMICs, a topological data analysis approach, which enables semiautomatic mapping of microglial morphology into an atlas of cue-dependent phenotypes,
overcomes feature-selection bias and minimizes biological variability.
First, with MorphOMICs we derive the morphological spectrum of microglia across seven
brain regions during postnatal development and in two distinct Alzheimer’s disease
degeneration mouse models. We uncover region-specific and sexually dimorphic
morphological trajectories, with females showing an earlier morphological shift than males in
the degenerating brain. Overall, we demonstrate that both long primary- and short terminal
processes provide distinct insights to morphological phenotypes. Moreover, using machine
learning to map novel condition on the spectrum, we observe that microglia morphologies
reflect a dose-dependent adaptation upon ketamine anesthesia and do not recover to control
morphologies.
Next, we took advantage of MorphOMICs to build a high-resolution and layer-specific map of
microglial morphological spectrum in the retina, covering postnatal development and rd10
degeneration. Here, following photoreceptor death, microglia assume an early developmentlike morphology. Finally, we map microglial morphology following optic nerve crush on the
retinal spectrum and observe a layer- and sex-dependent response.
Overall, MorphOMICs opens a new perspective to analyze microglial morphology across
multiple conditions, and provides a novel tool to characterize microglial morphology beyond
the traditionally dichotomized view of microglia.},
author = {Colombo, Gloria},
issn = {2663-337X},
pages = {142},
publisher = {Institute of Science and Technology Austria},
title = {{MorphOMICs, a tool for mapping microglial morphology, reveals brain region- and sex-dependent phenotypes}},
doi = {10.15479/at:ista:12378},
year = {2022},
}
@phdthesis{11388,
abstract = {In evolve and resequence experiments, a population is sequenced, subjected to selection and
then sequenced again, so that genetic changes before and after selection can be observed at
the genetic level. Here, I use these studies to better understand the genetic basis of complex
traits - traits which depend on more than a few genes.
In the first chapter, I discuss the first evolve and resequence experiment, in which a population
of mice, the so-called "Longshanks" mice, were selected for tibia length while their body mass
was kept constant. The full pedigree is known. We observed a selection response on all
chromosomes and used the infinitesimal model with linkage, a model which assumes an infinite
number of genes with infinitesimally small effect sizes, as a null model. Results implied a very
polygenic basis with a few loci of major effect standing out and changing in parallel. There
was large variability between the different chromosomes in this study, probably due to LD.
In chapter two, I go on to discuss the impact of LD, on the variability in an allele-frequency
based summary statistic, giving an equation based on the initial allele frequencies, average
pairwise LD, and the first four moments of the haplotype block copy number distribution. I
describe this distribution by referring back to the founder generation. I then demonstrate
how to infer selection via a maximum likelihood scheme on the example of a single locus and
discuss how to extend this to more realistic scenarios.
In chapter three, I discuss the second evolve and resequence experiment, in which a small
population of Drosophila melanogaster was selected for increased pupal case size over 6
generations. The experiment was highly replicated with 27 lines selected within family and a
known pedigree. We observed a phenotypic selection response of over one standard deviation.
I describe the patterns in allele frequency data, including allele frequency changes and patterns
of heterozygosity, and give ideas for future work.},
author = {Belohlavy, Stefanie},
isbn = {978-3-99078-018-3},
pages = {98},
publisher = {Institute of Science and Technology Austria},
title = {{The genetic basis of complex traits studied via analysis of evolve and resequence experiments}},
doi = {10.15479/at:ista:11388},
year = {2022},
}
@article{10703,
abstract = {When crawling through the body, leukocytes often traverse tissues that are densely packed with extracellular matrix and other cells, and this raises the question: How do leukocytes overcome compressive mechanical loads? Here, we show that the actin cortex of leukocytes is mechanoresponsive and that this responsiveness requires neither force sensing via the nucleus nor adhesive interactions with a substrate. Upon global compression of the cell body as well as local indentation of the plasma membrane, Wiskott-Aldrich syndrome protein (WASp) assembles into dot-like structures, providing activation platforms for Arp2/3 nucleated actin patches. These patches locally push against the external load, which can be obstructing collagen fibers or other cells, and thereby create space to facilitate forward locomotion. We show in vitro and in vivo that this WASp function is rate limiting for ameboid leukocyte migration in dense but not in loose environments and is required for trafficking through diverse tissues such as skin and lymph nodes.},
author = {Gaertner, Florian and Dos Reis Rodrigues, Patricia and De Vries, Ingrid and Hons, Miroslav and Aguilera, Juan and Riedl, Michael and Leithner, Alexander F and Tasciyan, Saren and Kopf, Aglaja and Merrin, Jack and Zheden, Vanessa and Kaufmann, Walter and Hauschild, Robert and Sixt, Michael K},
issn = {1878-1551},
journal = {Developmental Cell},
number = {1},
pages = {47--62.e9},
publisher = {Cell Press},
title = {{WASp triggers mechanosensitive actin patches to facilitate immune cell migration in dense tissues}},
doi = {10.1016/j.devcel.2021.11.024},
volume = {57},
year = {2022},
}
@phdthesis{12401,
abstract = {Detachment of the cancer cells from the bulk of the tumor is the first step of metastasis, which
is the primary cause of cancer related deaths. It is unclear, which factors contribute to this step.
Recent studies indicate a crucial role of the tumor microenvironment in malignant
transformation and metastasis. Studying cancer cell invasion and detachments quantitatively in
the context of its physiological microenvironment is technically challenging. Especially, precise
control of microenvironmental properties in vivo is currently not possible. Here, I studied the
role of microenvironment geometry in the invasion and detachment of cancer cells from the
bulk with a simplistic and reductionist approach. In this approach, I engineered microfluidic
devices to mimic a pseudo 3D extracellular matrix environment, where I was able to
quantitatively tune the geometrical configuration of the microenvironment and follow tumor
cells with fluorescence live imaging. To aid quantitative analysis I developed a widely applicable
software application to automatically analyze and visualize particle tracking data.
Quantitative analysis of tumor cell invasion in isotropic and anisotropic microenvironments
showed that heterogeneity in the microenvironment promotes faster invasion and more
frequent detachment of cells. These observations correlated with overall higher speed of cells at
the edge of the bulk of the cells. In heterogeneous microenvironments cells preferentially
passed through larger pores, thus invading areas of least resistance and generating finger-like
invasive structures. The detachments occurred mostly at the tips of these structures.
To investigate the potential mechanism, we established a two dimensional model to simulate
active Brownian particles representing the cell nuclei dynamics. These simulations backed our in
vitro observations without the need of precise fitting the simulation parameters. Our model
suggests the importance of the pore heterogeneity in the direction perpendicular to the
orientation of bias field (lateral heterogeneity), which causes the interface roughening.},
author = {Tasciyan, Saren},
issn = {2663-337X},
pages = {105},
publisher = {Institute of Science and Technology Austria},
title = {{Role of microenvironment heterogeneity in cancer cell invasion}},
doi = {10.15479/at:ista:12401},
year = {2022},
}
@article{12248,
abstract = {Eurasian brine shrimp (genus Artemia) have closely related sexual and asexual lineages of parthenogenetic females, which produce rare males at low frequencies. Although they are known to have ZW chromosomes, these are not well characterized, and it is unclear whether they are shared across the clade. Furthermore, the underlying genetic architecture of the transmission of asexuality, which can occur when rare males mate with closely related sexual females, is not well understood. We produced a chromosome-level assembly for the sexual Eurasian species Artemia sinica and characterized in detail the pair of sex chromosomes of this species. We combined this new assembly with short-read genomic data for the sexual species Artemia sp. Kazakhstan and several asexual lineages of Artemia parthenogenetica, allowing us to perform an in-depth characterization of sex-chromosome evolution across the genus. We identified a small differentiated region of the ZW pair that is shared by all sexual and asexual lineages, supporting the shared ancestry of the sex chromosomes. We also inferred that recombination suppression has spread to larger sections of the chromosome independently in the American and Eurasian lineages. Finally, we took advantage of a rare male, which we backcrossed to sexual females, to explore the genetic basis of asexuality. Our results suggest that parthenogenesis is likely partly controlled by a locus on the Z chromosome, highlighting the interplay between sex determination and asexuality.},
author = {Elkrewi, Marwan N and Khauratovich, Uladzislava and Toups, Melissa A and Bett, Vincent K and Mrnjavac, Andrea and Macon, Ariana and Fraisse, Christelle and Sax, Luca and Huylmans, Ann K and Hontoria, Francisco and Vicoso, Beatriz},
issn = {1943-2631},
journal = {Genetics},
keywords = {Genetics},
number = {2},
publisher = {Oxford University Press},
title = {{ZW sex-chromosome evolution and contagious parthenogenesis in Artemia brine shrimp}},
doi = {10.1093/genetics/iyac123},
volume = {222},
year = {2022},
}
@article{10767,
abstract = {The t-haplotype of mice is a classical model for autosomal transmission distortion. A largely non-recombining variant of the proximal region of chromosome 17, it is transmitted to more than 90% of the progeny of heterozygous males through the disabling of sperm carrying a standard chromosome. While extensive genetic and functional work has shed light on individual genes involved in drive, much less is known about the evolution and function of the rest of its hundreds of genes. Here, we characterize the sequence and expression of dozens of t-specific transcripts and of their chromosome 17 homologues. Many genes showed reduced expression of the t-allele, but an equal number of genes showed increased expression of their t-copy, consistent with increased activity or a newly evolved function. Genes on the t-haplotype had a significantly higher non-synonymous substitution rate than their homologues on the standard chromosome, with several genes harbouring dN/dS ratios above 1. Finally, the t-haplotype has acquired at least two genes from other chromosomes, which show high and tissue-specific expression. These results provide a first overview of the gene content of this selfish element, and support a more dynamic evolutionary scenario than expected of a large genomic region with almost no recombination.},
author = {Kelemen, Réka K and Elkrewi, Marwan N and Lindholm, Anna K. and Vicoso, Beatriz},
issn = {1471-2954},
journal = {Proceedings of the Royal Society B: Biological Sciences},
number = {1968},
pages = {20211985},
publisher = {The Royal Society},
title = {{Novel patterns of expression and recruitment of new genes on the t-haplotype, a mouse selfish chromosome}},
doi = {10.1098/rspb.2021.1985},
volume = {289},
year = {2022},
}
@article{10924,
abstract = {Solid-state microwave systems offer strong interactions for fast quantum logic and sensing but photons at telecom wavelength are the ideal choice for high-density low-loss quantum interconnects. A general-purpose interface that can make use of single photon effects requires < 1 input noise quanta, which has remained elusive due to either low efficiency or pump induced heating. Here we demonstrate coherent electro-optic modulation on nanosecond-timescales with only 0.16+0.02−0.01 microwave input noise photons with a total bidirectional transduction efficiency of 8.7% (or up to 15% with 0.41+0.02−0.02), as required for near-term heralded quantum network protocols. The use of short and high-power optical pump pulses also enables near-unity cooperativity of the electro-optic interaction leading to an internal pure conversion efficiency of up to 99.5%. Together with the low mode occupancy this provides evidence for electro-optic laser cooling and vacuum amplification as predicted a decade ago.},
author = {Sahu, Rishabh and Hease, William J and Rueda Sanchez, Alfredo R and Arnold, Georg M and Qiu, Liu and Fink, Johannes M},
issn = {2041-1723},
journal = {Nature Communications},
publisher = {Springer Nature},
title = {{Quantum-enabled operation of a microwave-optical interface}},
doi = {10.1038/s41467-022-28924-2},
volume = {13},
year = {2022},
}
@inproceedings{11452,
abstract = {We study efficient distributed algorithms for the fundamental problem of principal component analysis and leading eigenvector computation on the sphere, when the data are randomly distributed among a set of computational nodes. We propose a new quantized variant of Riemannian gradient descent to solve this problem, and prove that the algorithm converges with high probability under a set of necessary spherical-convexity properties. We give bounds on the number of bits transmitted by the algorithm under common initialization schemes, and investigate the dependency on the problem dimension in each case.},
author = {Alimisis, Foivos and Davies, Peter and Vandereycken, Bart and Alistarh, Dan-Adrian},
booktitle = {Advances in Neural Information Processing Systems - 35th Conference on Neural Information Processing Systems},
isbn = {9781713845393},
issn = {1049-5258},
location = {Virtual, Online},
pages = {2823--2834},
publisher = {Neural Information Processing Systems Foundation},
title = {{Distributed principal component analysis with limited communication}},
volume = {4},
year = {2021},
}
@inproceedings{11453,
abstract = {Neuronal computations depend on synaptic connectivity and intrinsic electrophysiological properties. Synaptic connectivity determines which inputs from presynaptic neurons are integrated, while cellular properties determine how inputs are filtered over time. Unlike their biological counterparts, most computational approaches to learning in simulated neural networks are limited to changes in synaptic connectivity. However, if intrinsic parameters change, neural computations are altered drastically. Here, we include the parameters that determine the intrinsic properties,
e.g., time constants and reset potential, into the learning paradigm. Using sparse feedback signals that indicate target spike times, and gradient-based parameter updates, we show that the intrinsic parameters can be learned along with the synaptic weights to produce specific input-output functions. Specifically, we use a teacher-student paradigm in which a randomly initialised leaky integrate-and-fire or resonate-and-fire neuron must recover the parameters of a teacher neuron. We show that complex temporal functions can be learned online and without backpropagation through time, relying on event-based updates only. Our results are a step towards online learning of neural computations from ungraded and unsigned sparse feedback signals with a biologically inspired learning mechanism.},
author = {Braun, Lukas and Vogels, Tim P},
booktitle = {Advances in Neural Information Processing Systems - 35th Conference on Neural Information Processing Systems},
isbn = {9781713845393},
issn = {1049-5258},
location = {Virtual, Online},
pages = {16437--16450},
publisher = {Neural Information Processing Systems Foundation},
title = {{Online learning of neural computations from sparse temporal feedback}},
volume = {20},
year = {2021},
}
@inproceedings{11463,
abstract = {Efficiently approximating local curvature information of the loss function is a key tool for optimization and compression of deep neural networks. Yet, most existing methods to approximate second-order information have high computational
or storage costs, which limits their practicality. In this work, we investigate matrix-free, linear-time approaches for estimating Inverse-Hessian Vector Products (IHVPs) for the case when the Hessian can be approximated as a sum of rank-one matrices, as in the classic approximation of the Hessian by the empirical Fisher matrix. We propose two new algorithms: the first is tailored towards network compression and can compute the IHVP for dimension d, if the Hessian is given as a sum of m rank-one matrices, using O(dm2) precomputation, O(dm) cost for computing the IHVP, and query cost O(m) for any single element of the inverse Hessian. The second algorithm targets an optimization setting, where we wish to compute the product between the inverse Hessian, estimated over a sliding window of optimization steps, and a given gradient direction, as required for preconditioned SGD. We give an algorithm with cost O(dm + m2) for computing the IHVP and O(dm + m3) for adding or removing any gradient from the sliding window. These
two algorithms yield state-of-the-art results for network pruning and optimization with lower computational overhead relative to existing second-order methods. Implementations are available at [9] and [17].},
author = {Frantar, Elias and Kurtic, Eldar and Alistarh, Dan-Adrian},
booktitle = {35th Conference on Neural Information Processing Systems},
isbn = {9781713845393},
issn = {1049-5258},
location = {Virtual, Online},
pages = {14873--14886},
publisher = {Neural Information Processing Systems Foundation},
title = {{M-FAC: Efficient matrix-free approximations of second-order information}},
volume = {34},
year = {2021},
}
@inproceedings{11464,
abstract = {We consider a standard distributed optimisation setting where N machines, each holding a d-dimensional function
fi, aim to jointly minimise the sum of the functions ∑Ni=1fi(x). This problem arises naturally in large-scale distributed optimisation, where a standard solution is to apply variants of (stochastic) gradient descent. We focus on the communication complexity of this problem: our main result provides the first fully unconditional bounds on total number of bits which need to be sent and received by the N machines to solve this problem under point-to-point communication, within a given error-tolerance. Specifically, we show that Ω(Ndlogd/Nε) total bits need to be communicated between the machines to find an additive ϵ-approximation to the minimum of ∑Ni=1fi(x). The result holds for both deterministic and randomised algorithms, and, importantly, requires no assumptions on the algorithm structure. The lower bound is tight under certain restrictions on parameter values, and is matched within constant factors for quadratic objectives by a new variant of quantised gradient descent, which we describe and analyse. Our results bring over tools from communication complexity to distributed optimisation, which has potential for further applications.},
author = {Alistarh, Dan-Adrian and Korhonen, Janne},
booktitle = {35th Conference on Neural Information Processing Systems},
isbn = {9781713845393},
issn = {1049-5258},
location = {Virtual, Online},
pages = {7254--7266},
publisher = {Neural Information Processing Systems Foundation},
title = {{Towards tight communication lower bounds for distributed optimisation}},
volume = {34},
year = {2021},
}