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Concurrent natural time scales related to relaxation, recombination, trapping, and drifting processes rule the semiconductor heterostructures' response to external drives when charge carrier fluxes are induced. This paper highlights the role of stoichiometry not only for the quantitative tuning of the electron-hole dynamics but also for significant qualitative contrasts of time-resolved optical responses during the operation of resonant tunneling devices. Therefore, similar device architectures and different compositions have been compared to elucidate the correlation among structural parameters, radiative recombination processes, and electron-hole pair and minority carrier relaxation mechanisms. When these ingredients intermix with the electronic structure in Sb-based tunneling devices, it is proven possible to assess various time scales according to the intensity of the current flux, contrary to what has been observed in As-based tunneling devices with similar design and transport characteristics. These time scales are strongly affected not only by the filling process in the $\Gamma$ and L states in Sb-based double-barrier quantum wells but also by the small separation between these states, compared to similar heterostructures based on As., Comment: 11 pages, 6 figures, submitted to the Physical Review Applied journal

Creating single photons in the telecommunication wavelength range from semiconductor quantum dots (QDs) and interfacing them with spins of electrons or holes has been of high interest in recent years, with research mainly focusing on indium based QDs. However, there is not much data on the optical and spin properties of galliumantimonide (GaSb) QDs, despite it being a physically rich system with an indirect to direct bandgap crossover in the telecom wavelength range. Here, we investigate the (quantum-) optical properties of GaSb quantum dots, which are fabricated by filling droplet-etched nanoholes in an aluminum-galliumantimonide (AlGaSb) matrix. We observe photoluminescence (PL) features from isolated and highly symmetric QDs that exhibit narrow linewidth in the telecom S-band and show an excitonic fine structure splitting of $\Delta E=(12.0\pm0.5)\mu eV$. Moreover, we perform time-resolved measurements of the decay characteristics of an exciton and measure the second-order photon autocorrelation function of the charge complex to $g^{(2)}(0)=0.16\pm0.02$, revealing clear antibunching and thus proving the capability of this material platform to generate non-classical light.

The precise pattern and timing of speciation events that gave rise to all living placental mammals remain controversial. We provide a comprehensive phylogenetic analysis of genetic variation across an alignment of 241 placental mammal genome assemblies, addressing prior concerns regarding limited genomic sampling across species. We compared neutral genome-wide phylogenomic signals using concatenation and coalescent-based approaches, interrogated phylogenetic variation across chromosomes, and analyzed extensive catalogs of structural variants. Interordinal relationships exhibit relatively low rates of phylogenomic conflict across diverse datasets and analytical methods. Conversely, X-chromosome versus autosome conflicts characterize multiple independent clades that radiated during the Cenozoic. Genomic time trees reveal an accumulation of cladogenic events before and immediately after the Cretaceous-Paleogene (K-Pg) boundary, implying important roles for Cretaceous continental vicariance and the K-Pg extinction in the placental radiation.

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Optical quantum information science and technologies require the capability to generate, control, and detect single or multiple quanta of light. The need to detect individual photons has motivated the development of a variety of novel and refined single-photon detectors (SPDs) with enhanced detector performance. Superconducting nanowire single-photon detectors (SNSPDs) and single-photon avalanche diodes (SPADs) are the top-performer in this field, but alternative promising and innovative devices are emerging. In this review article, we discuss the current state-of-the-art of one such alternative device capable of single-photon counting: the resonant tunneling diode (RTD) single-photon detector. Due to their peculiar photodetection mechanism and current-voltage characteristic with a region of negative differential conductance, RTD single-photon detectors provide, theoretically, several advantages over conventional SPDs, such as an inherently deadtime-free photon-number resolution at elevated temperatures, while offering low dark counts, a low timing jitter, and multiple photon detection modes. This review article brings together our previous studies and current experimental results. We focus on the current limitations of RTD-SPDs and provide detailed design and parameter variations to be potentially employed in next-generation RTD-SPD to improve the figure of merits of these alternative single-photon counting devices. The single-photon detection capability of RTDs without quantum dots is shown.

Symptoms of neurological diseases emerge through the dysfunction of neural circuits whose diffuse and intertwined architectures pose serious challenges for delivering therapies. Deep brain stimulation (DBS) improves Parkinson���s disease symptoms acutely but does not differentiate between neuronal circuits, and its effects decay rapidly if stimulation is discontinued. Recent findings suggest that optogenetic manipulation of distinct neuronal subpopulations in the external globus pallidus (GPe) provides long-lasting therapeutic effects in dopamine-depleted (DD) mice. We used synaptic differences to excite parvalbumin-expressing GPe neurons and inhibit lim-homeobox-6���expressing GPe neurons simultaneously using brief bursts of electrical stimulation. In DD mice, circuit-inspired DBS provided long-lasting therapeutic benefits that far exceeded those induced by conventional DBS, extending several hours after stimulation. These results establish the feasibility of transforming knowledge of circuit architecture into translatable therapeutic approaches.

Alzheimer's disease (AD) is a severe age-related neurodegenerative disorder characterized by accumulation of amyloid-β plaques and neurofibrillary tangles, synaptic and neuronal loss, and cognitive decline. Several genes have been implicated in AD, but chromatin state alterations during neurodegeneration remain uncharacterized. Here we profile transcriptional and chromatin state dynamics across early and late pathology in the hippocampus of an inducible mouse model of AD-like neurodegeneration. We find a coordinated downregulation of synaptic plasticity genes and regulatory regions, and upregulation of immune response genes and regulatory regions, which are targeted by factors that belong to the ETS family of transcriptional regulators, including PU.1. Human regions orthologous to increasing-level enhancers show immune-cell-specific enhancer signatures as well as immune cell expression quantitative trait loci, while decreasing-level enhancer orthologues show fetal-brain-specific enhancer activity. Notably, AD-associated genetic variants are specifically enriched in increasing-level enhancer orthologues, implicating immune processes in AD predisposition. Indeed, increasing enhancers overlap known AD loci lacking protein-altering variants, and implicate additional loci that do not reach genome-wide significance. Our results reveal new insights into the mechanisms of neurodegeneration and establish the mouse as a useful model for functional studies of AD regulatory regions.

Birds are the most species-rich class of tetrapod vertebrates and have wide relevance across many research fields. We explored bird macroevolution using full genomes from 48 avian species representing all major extant clades. The avian genome is principally characterized by its constrained size, which predominantly arose because of lineage-specific erosion of repetitive elements, large segmental deletions, and gene loss. Avian genomes furthermore show a remarkably high degree of evolutionary stasis at the levels of nucleotide sequence, gene synteny, and chromosomal structure. Despite this pattern of conservation, we detected many non-neutral evolutionary changes in protein-coding genes and noncoding regions. These analyses reveal that pan-avian genomic diversity covaries with adaptations to different lifestyles and convergent evolution of traits.

Vocal learning is the ability modify vocal output based on auditory input and is the basis of human speech acquisition. It is shared by few distantly related bird and mammal orders, and is thus very likely to be an example of convergent evolution, having evolved independently in multiple lineages. This complex behavior is presumed to require networks of regulated genes to develop the necessary neural circuits for learning and maintaining vocalizations. Deciphering these networks has been limited by the lack of high throughput genomic tools in vocal learning avian species and the lack of a solid computational framework to understand the relationship between gene expression and behavior. This dissertation provides new insights into the evolution and mechanisms of vocal learning by taking a top-down, systems biology approach to understanding gene expression regulation across avian and mammalian species. First, I worked with colleagues to develop a zebra finch Agilent oligonucleotide microarray, including developing programs for more accurate annotation of oligonucleotides and genes. I then used these arrays and tools in multiple collaborative, but related projects, to measure transcriptome expression data in vocal learning and non-learning avian species, under a number of behavioral paradigms, with a focus on song production. To make sense of the avian microarray data, I compiled microarray data from other sources, including expression analyses across over 900 human brain regions generated by Allen Brain Institute. To compare these data sets, I developed and performed a variety of computational analyses including clustering, linear models, gene set enrichment analysis, motif discovery, and phylogenetic inference, providing a novel framework to study the gene regulatory networks associated with a complex behavior. Using the developed framework, we are able to better understand vocal learning at different levels: how the brain regions for vocal learning evolved and how those brain regions function during the production of learned vocalizations. At the evolutionary level, we identified genes with unique expression patterns in the brains of vocal learning birds and humans. Interesting candidates include genes related to formation of neural connections, in particular the SLIT/ROBO axon guidance pathway. This algorithm also allowed us to identify the analogous regions that are a part of vocal learning circuit across species, providing the first quantitative evidence relating the human vocal learning circuit to the avian vocal learning circuit. With the avian song system verified as a model for human speech at the molecular level, we conducted an experiment to better understand what is happening in those brain regions during singing by profiling gene expression in a time course as birds are producing song. Surprisingly, an overwhelming majority of the gene expression identified was strongly enriched in a particular region. We also found a tight coupling between the behavioral function of a particular region and the gene expression pattern. To gain insight into the mechanisms of this gene regulation, we conducted a genomic scan of transcription factor binding sites in zebra finch. Many transcription factor binding sites were enriched in the promoters of genes with a particular temporal patterns, several of which had already been hypothesized to play a role in the neural system. Using this data set of gene expression profiles and transcription factor binding sites along with separate experiments conducted in mouse, we were able uncover evidence that the transcription factor CARF plays a role in neuron homeostasis. These results have broadened our understanding of the molecular basis of vocal learning at multiple levels. Overall, this dissertation outlines a novel way of approaching the study of the relationship between genes and behavior.

Promoters initiate RNA synthesis, and enhancers stimulate promoter activity. Whether promoter and enhancer activities are encoded distinctly in DNA sequences is unknown. We measured the enhancer and promoter activities of thousands of DNA fragments transduced into mouse neurons. We focused on genomic loci bound by the neuronal activity-regulated coactivator CREBBP, and we measured enhancer and promoter activities both before and after neuronal activation. We find that the same sequences typically encode both enhancer and promoter activities. However, gene promoters generate more promoter activity than distal enhancers, despite generating similar enhancer activity. Surprisingly, the greater promoter activity of gene promoters is not due to conventional core promoter elements or splicing signals. Instead, we find that particular transcription factor binding motifs are intrinsically biased toward the generation of promoter activity, whereas others are not. Although the specific biases we observe may be dependent on experimental or cellular context, our results suggest that gene promoters are distinguished from distal enhancers by specific complements of transcriptional activators., National Institute of Mental Health (U.S.) (Grant R01 MH101528-01)

Neuronal activity causes the rapid expression of immediate early genes that are crucial for experience-driven changes to synapses, learning, and memory. Here, using both molecular and genome-wide next-generation sequencing methods, we report that neuronal activity stimulation triggers the formation of DNA double strand breaks (DSBs) in the promoters of a subset of early-response genes, including Fos, Npas4, and Egr1. Generation of targeted DNA DSBs within Fos and Npas4 promoters is sufficient to induce their expression even in the absence of an external stimulus. Activity-dependent DSB formation is likely mediated by the type II topoisomerase, Topoisomerase IIβ (Topo IIβ), and knockdown of Topo IIβ attenuates both DSB formation and early-response gene expression following neuronal stimulation. Our results suggest that DSB formation is a physiological event that rapidly resolves topological constraints to early-response gene expression in neurons., National Institutes of Health (U.S.) (R01HG004037-07), National Human Genome Research Institute (U.S.) (R01HG004037-07), National Institutes of Health (U.S.) (RC1HG005334), National Human Genome Research Institute (U.S.) (RC1HG005334), National Institutes of Health (U.S.) (R01AG046174)

Alzheimer’s disease (AD) is a severe age-related neurodegenerative disorder characterized by accumulation of amyloid-β plaques and neurofibrillary tangles, synaptic and neuronal loss, and cognitive decline. Several genes have been implicated in AD, but chromatin state alterations during neurodegeneration remain uncharacterized. Here we profile transcriptional and chromatin state dynamics across early and late pathology in the hippocampus of an inducible mouse model of AD-like neurodegeneration. We find a coordinated downregulation of synaptic plasticity genes and regulatory regions, and upregulation of immune response genes and regulatory regions, which are targeted by factors that belong to the ETS family of transcriptional regulators, including PU.1. Human regions orthologous to increasing-level enhancers show immune-cell-specific enhancer signatures as well as immune cell expression quantitative trait loci, while decreasing-level enhancer orthologues show fetal-brain-specific enhancer activity. Notably, AD-associated genetic variants are specifically enriched in increasing-level enhancer orthologues, implicating immune processes in AD predisposition. Indeed, increasing enhancers overlap known AD loci lacking protein-altering variants, and implicate additional loci that do not reach genome-wide significance. Our results reveal new insights into the mechanisms of neurodegeneration and establish the mouse as a useful model for functional studies of AD regulatory regions., Belfer Neurodegeneration Consortium, National Institutes of Health (U.S.) (National Institute of Neurological Disorders and Stroke (U.S.)/National Institute on Aging RO1NS078839), Swiss National Science Foundation (Early Postdoc Mobility Fellowship P2BSP3_151885), National Institutes of Health (U.S.) (National Human Genome Research Institute (U.S.) R01HG004037-07), National Institutes of Health (U.S.) (National Human Genome Research Institute (U.S.) RC1HG005334)

INTRODUCTION Brain activity drives both behavior and regulated gene expression in neurons. Although past studies have identified activity-induced signaling and gene regulation cascades in cultured neurons, much less is known about how activity- dependent transcriptional networks are affected by the variations in cell-type composition, network interconnections, and firing patterns that comprise behaviorally active brain circuits in vivo. Dual mechanism model for behaviorally regulated gene expression diversity. ( Left ) Song brain circuit and zebra finch song motif (transcribed using https://my.scorecloud.com). ( Middle ) Song nucleus–specific (RA, red; Area X, blue) singing- regulated genes (gene A and gene B) in response to neural f ring (yellow). ( Right ) Region-general EATF and region-specific TF only bind to genomic DNA (lines) with region-specific acetylated histone 3 (H3K27ac peaks) and then transcribe their mRNAs (green arrow). RATIONALE We tested the hypothesis that behaviorally regulated gene expression is anatomically and temporally diverse and that the key determinants of this diversity are networks of transcription factors, their genomic binding sites, and epigenetic chromatin states. We analyzed genome-wide, singing-regulated gene expression across time in the four major forebrain regions of the song control system in songbirds, a model of speech production in humans. We then performed a transcription factor motif analysis to identify gene regulatory networks enriched in each song nucleus and measured acetylation of histone 3 at lysine 27 (H3K27ac) to identify chromatin regions that were transcriptionally active in the genomes of song nuclei before and after singing. RESULTS We found that singing was associated with differential regulation of about 10% of all genes in the avian genome that came in several waves across time. Less than 1% of these genes were comparably regulated in all song nuclei tested, and these comprised a core set dominated by immediate-early gene (IEG) transcription factors. By contrast, the vast majority of singing-regulated genes were regulated in only one or a subset of song nuclei, such that each song nucleus had its own dominant subset of genes regulated with defined temporal profiles, controlling a variety of functions. The promoters of many of the singing-regulated genes contained binding motifs for known early-activated transcription factors (EATFs) that become active in response to neural firing, some of which were expressed differentially between song nuclei at baseline. One EATF, calcium-response factor ( CaRF ), was tested with RNA interference knockdown in cultured neurons and found to regulate the predicted genes in response to neural activity, but was also found to modulate their expression even at baseline. More strikingly, we found with H3K27ac analysis that many song nucleus–specific singing-regulated genes did not show increased chromatin regulatory element activity after singing but rather already had primed region-specific regulatory activity before singing began. CONCLUSIONS We propose a dual mechanism for the diversity of behaviorally regulated genes across different brain regions in vivo (see the figure). First, the neural activity associated with singing activates EATFs, and some TFs differentially expressed in brain regions at baseline, to trigger region-specific expression of their target genes. Second, brain region–specific enhancers near activity- regulated genes are waiting in an epigenetically primed state, ready to modulate transcription of general and song nucleus–specific genes at a moment’s notice when the neurons fire. The combination of these two mechanisms underlies a great diversity of behaviorally regulated gene expression, permitting each nucleus to perform its particular function in this complex behavior.