The immediate neighborhood of virtually every brain neuron contains thin, meandering axons that release serotonin (5-HT). These axons, also referred to as serotonergic fibers, are present in nearly all studied nervous systems (both vertebrate and invertebrate) and appear to be a key component of biological neural networks. In the mammalian brain, they create dense meshworks that are macroscopically described by densities. It is not known how these densities arise from the trajectories of individual fibers, each of which resembles a unique random-walk path. This poses interesting theoretical questions, solving which will advance our understanding of brain plasticity and regeneration. For example, serotonin-associated psychedelics have recently been shown to promote global brain integration in depression [1], and serotonergic fibers are nearly unique in their ability to robustly regenerate in the adult mammalian brain [2].
We have recently introduced a conceptual framework that treats the serotonergic axons as “stochastic axons.” Stochastic axons are different from axons that support point-to-point connectivity (often studied with graph-theoretical methods) and require novel theoretical approaches. We have shown that serotonergic axons can be potentially modeled as paths of fractional Brownian motion (FBM) in the superdiffusive regime (with the Hurst exponent H > 0.5). Our supercomputing simulations demonstrate that particles driven by reflected FBM (rFBM) accumulate at the border enclosing the shape [3]. Likewise, serotonergic fibers tend to accumulate at the border of neural tissue, in addition to their general similarity to simulated FBM paths [4].
This work expands our previous simulations in 2D-brain-like shapes by considering the full 3D-geometry of the brain. This transition is not trivial and cannot be reduced to independent 2D-sections because increments of FBM trajectories exhibit long-range correlation. Supercomputing simulations of rFMB (H > 0.5) were performed in the reconstructed 3D-geometry of a mouse brain at embryonic day 17 (serotonergic fibers are already well developed at this age and begin to invade the cortical plate). The obtained results were compared to the actual distribution of fibers in the mouse brain. In addition, we obtained preliminary results by simulating rFBM with a region-dependent H. This next step in complexity presents challenges (e.g., it can be highly sensitive to mathematical specifications), but it is necessary for the predictive modeling of interior fiber densities in heterogenous brain tissue.
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Data in: Aging power spectrum of membrane protein transport and other subordinated random walks
Datasets generated in the report "Aging power spectrum of membrane protein transport and other subordinated random walks". Included data are:
Numerical simulations
RWdata1.mat: 10,000 realizations, subordinated random walk with Hurst exponent, H=0.3 and \(\alpha\)=0.4.
RWdata3.mat: 10,000 realizations, subordinated random walk with Hurst exponent, H=0.7 and \(\alpha\)=0.4.
RWdata8.mat: 5,000 realizations, subordinated random walk with Hurst exponent, H=0.75 and \(\alpha\)=0.8.
RWdataCTRW.mat: 10,000 realizations, continuous time random walk (CTRW), \(\alpha\)=0.7.
Spectra of simulations
PSDdata1.mat: Power spectral density (PSD) of a subordinated random walk with Hurst exponent, H=0.3 and \(\alpha\)=0.4. Five different realization times are used to compute the PDS: 2^8, 2^10, 2^12, 2^14, and 2^16.
PSDdata3.mat: PSD of a subordinated random walk with Hurst exponent, H=0.7 and \(\alpha\)=0.4. Five different realization times are used to compute the PDS: 2^8, 2^10, 2^12, 2^14, and 2^16.
PSDdata8.mat: PSD of a subordinated random walk with Hurst exponent, H=0.75 and \(\alpha\)=0.8. Four different realization times are used to compute the PDS: 2^15, 2^16, 2^17, and 2^18.
PSDs_CTRW.mat: PSD of a continuous-time random walk (CTRW), \(\alpha\)=0.7. Five different realization times are used to compute the PDS: 2^8, 2^10, 2^12, 2^14, and 2^16.
Experimental data of Nav1.6 channels in the soma of hippocampal neurons
NavMSDtimes.csv: ensemble-averaged (EA) MSD and time-averaged (TA) MSD. The TA-MSD is measured for three observation times, 64, 128, and 256 frames (3.2, 6.4, and 12.8 s).
NavPSD.csv: Power spectral density (PSD) measured for three observation times, 64, 128, and 256 frames.
- Award ID(s):
- 2102832
- NSF-PAR ID:
- 10341514
- Publisher / Repository:
- Zenodo
- Date Published:
- Edition / Version:
- 1
- Subject(s) / Keyword(s):
- ["subordinated random walks, fractional Brownian motion, power soectrum"]
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract. Discerning mechanisms of sulfate formation during fine-particle pollution (referred to as haze hereafter) in Beijing is important for understanding the rapid evolution of haze and for developing cost-effective air pollution mitigation strategies. Here we present observations of the oxygen-17 excess of PM2.5 sulfate (Δ17O(SO42−)) collected in Beijing haze from October 2014 to January 2015 to constrain possible sulfate formation pathways. Throughout the sampling campaign, the 12-hourly averaged PM2.5 concentrations ranged from 16 to 323µg m−3 with a mean of (141 ± 88 (1σ))µg m−3, with SO42− representing 8–25% of PM2.5 mass. The observed Δ17O(SO42−) varied from 0.1 to 1.6‰ with a mean of (0.9 ± 0.3)‰. Δ17O(SO42−) increased with PM2.5 levels in October 2014 while the opposite trend was observed from November 2014 to January 2015. Our estimate suggested that in-cloud reactions dominated sulfate production on polluted days (PDs, PM2.5 ≥ 75µg m−3) of Case II in October 2014 due to the relatively high cloud liquid water content, with a fractional contribution of up to 68%. During PDs of Cases I and III–V, heterogeneous sulfate production (Phet) was estimated to contribute 41–54% to total sulfate formation with a mean of (48 ± 5)%. For the specific mechanisms of heterogeneous oxidation of SO2, chemical reaction kinetics calculations suggested S(IV) ( = SO2 ⚫H2O+HSO3− + SO32−) oxidation by H2O2 in aerosol water accounted for 5–13% of Phet. The relative importance of heterogeneous sulfate production by other mechanisms was constrained by our observed Δ17O(SO42−). Heterogeneous sulfate production via S(IV) oxidation by O3 was estimated to contribute 21–22% of Phet on average. Heterogeneous sulfate production pathways that result in zero-Δ17O(SO42−), such as S(IV) oxidation by NO2 in aerosol water and/or by O2 via a radical chain mechanism, contributed the remaining 66–73% of Phet. The assumption about the thermodynamic state of aerosols (stable or metastable) was found to significantly influence the calculated aerosol pH (7.6 ± 0.1 or 4.7 ± 1.1, respectively), and thus influence the relative importance of heterogeneous sulfate production via S(IV) oxidation by NO2 and by O2. Our local atmospheric conditions-based calculations suggest sulfate formation via NO2 oxidation can be the dominant pathway in aerosols at high-pH conditions calculated assuming stable state while S(IV) oxidation by O2 can be the dominant pathway providing that highly acidic aerosols (pH ≤ 3) exist. Our local atmospheric-conditions-based calculations illustrate the utility of Δ17O(SO42−) for quantifying sulfate formation pathways, but this estimate may be further improved with future regional modeling work.
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Electro-optic quantum coherent interfaces map the amplitude and phase of a quantum signal directly to the phase or intensity of a probe beam. At terahertz frequencies, a fundamental challenge is not only to sense such weak signals (due to a weak coupling with a probe in the near-infrared) but also to resolve them in the time domain. Cavity confinement of both light fields can increase the interaction and achieve strong coupling. Using this approach, current realizations are limited to low microwave frequencies. Alternatively, in bulk crystals, electro-optic sampling was shown to reach quantum-level sensitivity of terahertz waves. Yet, the coupling strength was extremely weak. Here, we propose an on-chip architecture that concomitantly provides subcycle temporal resolution and an extreme sensitivity to sense terahertz intracavity fields below 20 V/m. We use guided femtosecond pulses in the near-infrared and a confinement of the terahertz wave to a volume of
in combination with ultraperformant organic molecules ( ) and accomplish a record-high single-photon electro-optic coupling rate of , 10,000 times higher than in recent reports of sensing vacuum field fluctuations in bulk media. Via homodyne detection implemented directly on chip, the interaction results into an intensity modulation of the femtosecond pulses. The single-photon cooperativity is , and the multiphoton cooperativity is at room temperature. We show dynamic range in intensity at 500 ms integration under irradiation with a weak coherent terahertz field. Similar devices could be employed in future measurements of quantum states in the terahertz at the standard quantum limit, or for entanglement of subsystems on subcycle temporal scales, such as terahertz and near-infrared quantum bits. -
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Terrestrial Parasite Tracker indexed biotic interactions and review summary.
The Terrestrial Parasite Tracker (TPT) project began in 2019 and is funded by the National Science foundation to mobilize data from vector and ectoparasite collections to data aggregators (e.g., iDigBio, GBIF) to help build a comprehensive picture of arthropod host-association evolution, distributions, and the ecological interactions of disease vectors which will assist scientists, educators, land managers, and policy makers. Arthropod parasites often are important to human and wildlife health and safety as vectors of pathogens, and it is critical to digitize these specimens so that they, and their biotic interaction data, will be available to help understand and predict the spread of human and wildlife disease.
This data publication contains versioned TPT associated datasets and related data products that were tracked, reviewed and indexed by Global Biotic Interactions (GloBI) and associated tools. GloBI provides open access to finding species interaction data (e.g., predator-prey, pollinator-plant, pathogen-host, parasite-host) by combining existing open datasets using open source software.
If you have questions or comments about this publication, please open an issue at https://github.com/ParasiteTracker/tpt-reporting or contact the authors by email.
Funding:
The creation of this archive was made possible by the National Science Foundation award "Collaborative Research: Digitization TCN: Digitizing collections to trace parasite-host associations and predict the spread of vector-borne disease," Award numbers DBI:1901932 and DBI:1901926References:
Jorrit H. Poelen, James D. Simons and Chris J. Mungall. (2014). Global Biotic Interactions: An open infrastructure to share and analyze species-interaction datasets. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2014.08.005.GloBI Data Review Report
Datasets under review:
- University of Michigan Museum of Zoology Insect Division. Full Database Export 2020-11-20 provided by Erika Tucker and Barry Oconner. accessed via https://github.com/EMTuckerLabUMMZ/ummzi/archive/6731357a377e9c2748fc931faa2ff3dc0ce3ea7a.zip on 2022-06-24T14:02:48.801Z
- Academy of Natural Sciences Entomology Collection for the Parasite Tracker Project accessed via https://github.com/globalbioticinteractions/ansp-para/archive/5e6592ad09ec89ba7958266ad71ec9d5d21d1a44.zip on 2022-06-24T14:04:22.091Z
- Bernice Pauahi Bishop Museum, J. Linsley Gressitt Center for Research in Entomology accessed via https://github.com/globalbioticinteractions/bpbm-ent/archive/c085398dddd36f8a1169b9cf57de2a572229341b.zip on 2022-06-24T14:04:37.692Z
- Texas A&M University, Biodiversity Teaching and Research Collections accessed via https://github.com/globalbioticinteractions/brtc-para/archive/f0a718145b05ed484c4d88947ff712d5f6395446.zip on 2022-06-24T14:06:40.154Z
- Brigham Young University Arthropod Museum accessed via https://github.com/globalbioticinteractions/byu-byuc/archive/4a609ac6a9a03425e2720b6cdebca6438488f029.zip on 2022-06-24T14:06:51.420Z
- California Academy of Sciences Entomology accessed via https://github.com/globalbioticinteractions/cas-ent/archive/562aea232ec74ab615f771239451e57b057dc7c0.zip on 2022-06-24T14:07:16.371Z
- Clemson University Arthropod Collection accessed via https://github.com/globalbioticinteractions/cu-cuac/archive/6cdcbbaa4f7cec8e1eac705be3a999bc5259e00f.zip on 2022-06-24T14:07:40.925Z
- Denver Museum of Nature and Science (DMNS) Parasite specimens (DMNS:Para) accessed via https://github.com/globalbioticinteractions/dmns-para/archive/a037beb816226eb8196533489ee5f98a6dfda452.zip on 2022-06-24T14:08:00.730Z
- Field Museum of Natural History IPT accessed via https://github.com/globalbioticinteractions/fmnh/archive/6bfc1b7e46140e93f5561c4e837826204adb3c2f.zip on 2022-06-24T14:18:51.995Z
- Illinois Natural History Survey Insect Collection accessed via https://github.com/globalbioticinteractions/inhs-insects/archive/38692496f590577074c7cecf8ea37f85d0594ae1.zip on 2022-06-24T14:19:37.563Z
- UMSP / University of Minnesota / University of Minnesota Insect Collection accessed via https://github.com/globalbioticinteractions/min-umsp/archive/3f1b9d32f947dcb80b9aaab50523e097f0e8776e.zip on 2022-06-24T14:20:27.232Z
- Milwaukee Public Museum Biological Collections Data Portal accessed via https://github.com/globalbioticinteractions/mpm/archive/9f44e99c49ec5aba3f8592cfced07c38d3223dcd.zip on 2022-06-24T14:20:46.185Z
- Museum for Southern Biology (MSB) Parasite Collection accessed via https://github.com/globalbioticinteractions/msb-para/archive/178a0b7aa0a8e14b3fe953e770703fe331eadacc.zip on 2022-06-24T15:16:07.223Z
- The Albert J. Cook Arthropod Research Collection accessed via https://github.com/globalbioticinteractions/msu-msuc/archive/38960906380443bd8108c9e44aeff4590d8d0b50.zip on 2022-06-24T16:09:40.702Z
- Ohio State University Acarology Laboratory accessed via https://github.com/globalbioticinteractions/osal-ar/archive/876269d66a6a94175dbb6b9a604897f8032b93dd.zip on 2022-06-24T16:10:00.281Z
- Frost Entomological Museum, Pennsylvania State University accessed via https://github.com/globalbioticinteractions/psuc-ento/archive/30b1f96619a6e9f10da18b42fb93ff22cc4f72e2.zip on 2022-06-24T16:10:07.741Z
- Purdue Entomological Research Collection accessed via https://github.com/globalbioticinteractions/pu-perc/archive/e0909a7ca0a8df5effccb288ba64b28141e388ba.zip on 2022-06-24T16:10:26.654Z
- Texas A&M University Insect Collection accessed via https://github.com/globalbioticinteractions/tamuic-ent/archive/f261a8c192021408da67c39626a4aac56e3bac41.zip on 2022-06-24T16:10:58.496Z
- University of California Santa Barbara Invertebrate Zoology Collection accessed via https://github.com/globalbioticinteractions/ucsb-izc/archive/825678ad02df93f6d4469f9d8b7cc30151b9aa45.zip on 2022-06-24T16:12:29.854Z
- University of Hawaii Insect Museum accessed via https://github.com/globalbioticinteractions/uhim/archive/53fa790309e48f25685e41ded78ce6a51bafde76.zip on 2022-06-24T16:12:41.408Z
- University of New Hampshire Collection of Insects and other Arthropods UNHC-UNHC accessed via https://github.com/globalbioticinteractions/unhc/archive/f72575a72edda8a4e6126de79b4681b25593d434.zip on 2022-06-24T16:12:59.500Z
- Scott L. Gardner and Gabor R. Racz (2021). University of Nebraska State Museum - Parasitology. Harold W. Manter Laboratory of Parasitology. University of Nebraska State Museum. accessed via https://github.com/globalbioticinteractions/unl-nsm/archive/6bcd8aec22e4309b7f4e8be1afe8191d391e73c6.zip on 2022-06-24T16:13:06.914Z
- Data were obtained from specimens belonging to the United States National Museum of Natural History (USNM), Smithsonian Institution, Washington DC and digitized by the Walter Reed Biosystematics Unit (WRBU). accessed via https://github.com/globalbioticinteractions/usnmentflea/archive/ce5cb1ed2bbc13ee10062b6f75a158fd465ce9bb.zip on 2022-06-24T16:13:38.013Z
- US National Museum of Natural History Ixodes Records accessed via https://github.com/globalbioticinteractions/usnm-ixodes/archive/c5fcd5f34ce412002783544afb628a33db7f47a6.zip on 2022-06-24T16:13:45.666Z
- Price Institute of Parasite Research, School of Biological Sciences, University of Utah accessed via https://github.com/globalbioticinteractions/utah-piper/archive/43da8db550b5776c1e3d17803831c696fe9b8285.zip on 2022-06-24T16:13:54.724Z
- University of Wisconsin Stevens Point, Stephen J. Taft Parasitological Collection accessed via https://github.com/globalbioticinteractions/uwsp-para/archive/f9d0d52cd671731c7f002325e84187979bca4a5b.zip on 2022-06-24T16:14:04.745Z
- Giraldo-Calderón, G. I., Emrich, S. J., MacCallum, R. M., Maslen, G., Dialynas, E., Topalis, P., … Lawson, D. (2015). VectorBase: an updated bioinformatics resource for invertebrate vectors and other organisms related with human diseases. Nucleic acids research, 43(Database issue), D707–D713. doi:10.1093/nar/gku1117. accessed via https://github.com/globalbioticinteractions/vectorbase/archive/00d6285cd4e9f4edd18cb2778624ab31b34b23b8.zip on 2022-06-24T16:14:11.965Z
- WIRC / University of Wisconsin Madison WIS-IH / Wisconsin Insect Research Collection accessed via https://github.com/globalbioticinteractions/wis-ih-wirc/archive/34162b86c0ade4b493471543231ae017cc84816e.zip on 2022-06-24T16:14:29.743Z
- Yale University Peabody Museum Collections Data Portal accessed via https://github.com/globalbioticinteractions/yale-peabody/archive/43be869f17749d71d26fc820c8bd931d6149fe8e.zip on 2022-06-24T16:23:29.289ZGenerated on:
2022-06-24by:
GloBI's Elton 0.12.4
(see https://github.com/globalbioticinteractions/elton).Note that all files ending with .tsv are files formatted
as UTF8 encoded tab-separated values files.https://www.iana.org/assignments/media-types/text/tab-separated-values
Included in this review archive are:README:
This file.review_summary.tsv:
Summary across all reviewed collections of total number of distinct review comments.review_summary_by_collection.tsv:
Summary by reviewed collection of total number of distinct review comments.indexed_interactions_by_collection.tsv:
Summary of number of indexed interaction records by institutionCode and collectionCode.review_comments.tsv.gz:
All review comments by collection.indexed_interactions_full.tsv.gz:
All indexed interactions for all reviewed collections.indexed_interactions_simple.tsv.gz:
All indexed interactions for all reviewed collections selecting only sourceInstitutionCode, sourceCollectionCode, sourceCatalogNumber, sourceTaxonName, interactionTypeName and targetTaxonName.datasets_under_review.tsv:
Details on the datasets under review.elton.jar:
Program used to update datasets and generate the review reports and associated indexed interactions.datasets.zip:
Source datasets used by elton.jar in process of executing the generate_report.sh script.generate_report.sh:
Program used to generate the reportgenerate_report.log:
Log file generated as part of running the generate_report.sh script
-
null (Ed.)Abstract Homeostatic control of neuronal excitability by modulation of synaptic inhibition (I) and excitation (E) of the principal neurons is important during brain maturation. The fundamental features of in-utero brain development, including local synaptic E–I ratio and bioenergetics, can be modeled by cerebral organoids (CO) that have exhibited highly regular nested oscillatory network events. Therefore, we evaluated a 'Phase Zero' clinical study platform combining broadband Vis/near-infrared(NIR) spectroscopy and electrophysiology with studying E–I ratio based on the spectral exponent of local field potentials and bioenergetics based on the activity of mitochondrial Cytochrome-C Oxidase (CCO). We found a significant effect of the age of the healthy controls iPSC CO from 23 days to 3 months on the CCO activity (chi-square (2, N = 10) = 20, p = 4.5400e−05), and spectral exponent between 30–50 Hz (chi-square (2, N = 16) = 13.88, p = 0.001). Also, a significant effect of drugs, choline (CHO), idebenone (IDB), R-alpha-lipoic acid plus acetyl- l -carnitine (LCLA), was found on the CCO activity (chi-square (3, N = 10) = 25.44, p = 1.2492e−05), spectral exponent between 1 and 20 Hz (chi-square (3, N = 16) = 43.5, p = 1.9273e−09) and 30–50 Hz (chi-square (3, N = 16) = 23.47, p = 3.2148e−05) in 34 days old CO from schizophrenia (SCZ) patients iPSC. We present the feasibility of a multimodal approach, combining electrophysiology and broadband Vis–NIR spectroscopy, to monitor neurodevelopment in brain organoid models that can complement traditional drug design approaches to test clinically meaningful hypotheses.more » « less
