Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
117
datasets available to search
ShareScore release 0.9.0
Dataset results
117 results for “cochlea”
Zellige example dataset: mouse embryonic cochlea stained for F-actin
<p><strong>Mouse embryonic cochlea stained for F-actin at embryonic stage E16.5. </strong></p> <p>The z-stack image encompasses an epithelial surface and a thick mesh of mesenchymal cells. It was acquired with a swept-field confocal microscope (Bruker OpterraII) equipped with a Nikon Plan-Apochromat 60x lens (NA=1.4). Pixel size 0.133 µm, z step <1 µm. This dataset contains both the ground-truth height map and the height map generated with Zellige, along with the parameters used to generate the latter one. The Zellige parameters used are:</p> <p><span class="math-tex">\(T_{A}=1, T_{otsu}=1, S_{min}=5, \sigma_{xy}=4, \sigma_{z}=1, T_{OSE1}=0.1, R_{1}=5, C_{1}=0.7, T_{OSE2}=0.1, R_{2}=10, C_{2}=0.8.\)</span></p> <p>Nota: to compare the ground truth height map with the Zellige height map, one first needs to substrat 1 to all values of the Zellige height map.</p> <p>See the accompanying paper: Extracting multiple surfaces from 3D microscopy images in complex biological tissues with the Zellige software tool. Trébeau <em>et al.</em> 2022: <a href="https://doi.org/10.1101/2022.04.05.485876">https://doi.org/10.1101/2022.04.05.485876</a></p> <p> </p>
Pterostilbene Protects Cochlea from Ototoxicity in Streptozotocin-Induced Diabetic Rats by Inhibiting Apoptosis
<p>Diabetes mellitus (DM) causes ototoxicity by inducing oxidative stress, microangiopathy, and apoptosis in the cochlear sensory hair cells. The natural anti-oxidant pterostilbene (PTS) (trans-3,5-dimethoxy-4-hydroxystylbene) has been reported to relieve oxidative stress and apoptosis in DM, but its role in diabetic-induced ototoxicity is unclear. This study aimed to investigate the effects of dose-dependent PTS on the cochlear cells of streptozotocin (STZ)-induced diabetic rats. The study included 30 albino male Wistar rats that were randomized into five groups: non-diabetic control (Control), diabetic control (DM), and diabetic rats treated with intraperitoneal PTS at 10, 20, or 40 mg/kg/day during the four-week experimental period (DM + PTS10, DM + PTS20, and DM + PTS40). Distortion product otoacoustic emission (DPOAE) tests were performed at the beginning and end of the study. At the end of the experimental period, apoptosis in the rat cochlea was investigated using caspase-8, cytochrome-c, and terminal deoxyribonucleotidyl transferase-mediated dUTP-biotin end labeling (TUNEL). Quantitative real-time polymerase chain reaction was used to assess the mRNA expression levels of the following genes: CASP-3, BCL-associated X protein (BAX), and BCL-2. Body weight, blood glucose, serum insulin, and malondialdehyde (MDA) levels in the rat groups were evaluated. The mean DPOAE amplitude in the DM group was significantly lower than the means of the other groups (0.9–8 kHz; P < 0.001 for all). A dose-dependent increase of the mean DPOAE amplitudes was observed with PTS treatment (P < 0.05 for all). The Caspase-8 and Cytochrome-c protein expressions and the number of TUNEL-positive cells in the hair cells of the Corti organs of the DM rat group were significantly higher than those of the PTS treatment and control groups (DM > DM + PTS10 > DM + PTS20 > DM + PTS40 > Control; P < 0.05 for all). PTS treatment also reduced cell apoptosis in a dose-dependent manner by increasing the mRNA expression of the anti-apoptosis BCL2 gene and by decreasing the mRNA expressions of both the pro-apoptosis BAX gene and its effector CASP-3 and the ratio of BAX/BCL-2 in a dose-dependent manner (P < 0.05 compared to DM for all). PTS treatment significantly improved the metabolic parameters of the diabetic rats, such as body weight, blood glucose, serum insulin, and MDA levels, consistent with our other findings (P < 0.05 compared to DM for all). PTS decreased the cochlear damage caused by diabetes, as confirmed by DPOAE, biochemical, histopathological, immunohistochemical, and molecular findings. This study reports the first in vivo findings to suggest that PTS may be a protective therapeutic agent against diabetes-induced ototoxicity.</p>
Fig. 7 in The origins of the cochlea and impedance matching hearing in synapsids
Fig. 7. Dual function of the auditory and masticatory apparatus of the non-mammalian synapsid Pristerodon mackayi Huxley, 1868 (MB.R.985) from the Late Permian of Biesjespoort, South Africa. A. Auditory region in posteroventral view showing the mechanics of the jaw articulations during mastication. B. Masticatory forces at the quadrate-quadratojugal complex (in posterior view). C. Auditory region in posteroventral view showing the mechanics of sound conduction. D. Mechanics of sound conduction of the quadrate-quadratojugal complex in posterior view. When the jaw muscles were relaxed, the reflected lamina and its putative tympanic membrane would receive the airborne sound, which would cause medio-lateral vibrations of the postdentary bones (although in small amplitude). The sound vibration was transmitted via the jaw hinge and the horizontal stapes to the inner ear. During the vibration, the quadrate is mobile at its ball and socket joint to the cranium, as permitted by a very thin bony connection with the quadratojugal. However, when the jaw musculature contracted during mastication, the quadrate was immobilized, it was strained by masticatory force and oppressed against the quadratojugal and the cleft between the quadrate and the quadratojugal is closed. During the active mastication, hearing was likely suspended, or reduced to a very low sensitivity if feasible at all. Not to scale.
Fig. 3 in The origins of the cochlea and impedance matching hearing in synapsids
Fig. 3. Distribution of cavities in the otic region of the non-mammalian synapsid Pristerodon mackayi Huxley, 1868 (MB.R.985) from the Late Permian of Biesjespoort, South Africa. Note the concentration of a number of large cavities (brown) around the inner ears, which are connected to each other. The neurocranium is shown transparent.
Fig. 6 in The origins of the cochlea and impedance matching hearing in synapsids
Fig. 6. The mandible of the non-mammalian synapsid Pristerodon mackayi Huxley, 1868 (MB.R.985) from the Late Permian of Biesjespoort, South Africa. A. Virtual reconstruction from neutron tomographic data. Note that the dentary is shown in transparent to provide insight into the internal structure. The arrows mark the positions and the number of the tomographic slices shown in B–D. B–D. Tomographic slices (B, 1202; C, 1895; D, 1613) showing the internal structure of the mandible. Note that surangular, prearticular, and angular are not fused with the dentary.
Fig. 9 in The origins of the cochlea and impedance matching hearing in synapsids
Fig. 9. Co-evolution of the cochlea and middle ear in synapsids. Hearing in primitive or burrowing non-mammalian synapsids was predominantly by bone conduction from the ground vibration via the mandible. The tympanic hearing started to assume a more important role as the head became lifted from ground due to a more upright forelimb posture. Adaptations to tympanic hearing and modifications of the middle ear for better sensitivity to airborne sound include: an enhanced acoustical isolation of the postdentary bones from the dentary, an enlarged reflected lamina, a smaller stapes footplates and a more horizontal oriented stapes, an elongate medial trochlear condyle of the quadrate. All these coincided with the origin of a distinctive cochlear cavity. Concurrent with middle ear modifications, the inner ear developed a more laterally facing fenestra vestibule and a ventral cochlear cavity. Later, the detachment of the postdentary bones from the mandible and the elongation of the cochlear canal were further steps towards a refined sensitivity to airborne sound, especially in higher frequencies. Partially redrawn from Luo et al. (2011), Cox (1962), and Luo (2011).
Fig. 2 in The origins of the cochlea and impedance matching hearing in synapsids
Fig. 2. The inner ear labyrinth of the non-mammalian synapsid Pristerodon mackayi Huxley, 1868 (MB.R.985) from the Late Permian of Biesjespoort, South Africa. Virtual cast of the left inner ear labyrinth in posterior (A), lateral (B), and anterior (C) views. Otic region including cochlear cavity of the left (E, tomographic slice 2461) and right (F, tomographic slice 2417) inner ear. D. Inner ear reconstruction of Pristerodon by Barry (1967).
Fig. 8 in The origins of the cochlea and impedance matching hearing in synapsids
Fig. 8. Relative size of the stapes footplate area of the non-mammalian synapsid Pristerodon mackayi (MB.R.985) from the Late Permian of Biesjespoort, South Africa compared with those of other non-mammalian synapsids. The slope of the stapes for each taxon is added in brackets. The regression line is calculated only for non-fossorial species. Note that the stapes footplate area of Pristerodon is smaller than in fossorial taxa. Used data and material see SOM 1: table S2. Abbreviations: hollow symbols, fossorial species; partially filled symbols, semifossorial; filled symbols, non-fossorial or uncertain species; Arc, Arctognathus nasuta; Bra, Brasilitherium riograndensis; Chi, Chiniquodon theotenicus; Cis, Cistecephalus planiceps; Dic hue, Dicynodon huenei; Dic now, Dicynodontoides nowacki; Dii, Diictodon feliceps; Gla, Glanosuchus sp.; Lys, Lystrosaurus declivis; Mas, Massetognathus pascuali; Nia, Niassodon mfumukasi; Not, Nothosollasia lückhoffi; Pri, Pristerodon sp.; Pla, Placerias gigas; Pro, Procynosuchus delaharpeae; Sta, Stahleckeria potens; Sum, Suminia getmanovi; Thri, Thrinaxodon liorhinus; Yun, Yunnanodon. Modified from Laass (2014).
Fig. 1 in The origins of the cochlea and impedance matching hearing in synapsids
Fig. 1. The skull of the non-mammalian synapsid Pristerodon mackayi Huxley, 1868 (MB.R.985) from the Late Permian of Biesjespoort, South Africa. Photograph (A) and virtual 3D model (B) of dorsolateral view.
Fig. 5 in The origins of the cochlea and impedance matching hearing in synapsids
Fig. 5. Virtual reconstruction of the left quadrate-quadratojugal complex of the non-mammalian synapsid Pristerodon mackayi Huxley, 1868 (MB.R.985) from the Late Permian of Biesjespoort, South Africa; in ventral (A), medial (B), and anterior (C) views.
Fig. 4 in The origins of the cochlea and impedance matching hearing in synapsids
Fig. 4. Virtual reconstruction of the left stapes of the non-mammalian synapsid Pristerodon mackayi Huxley, 1868 (MB.R.985) from the Late Permian of Biesjespoort, South Africa; in medial (A), posterior (B), ventral (C), and anterior (D) views.
3D fluorescence dataset of tissue cleared pig cochlea
Open the record for dataset details and reuse information.
MEMS-cochlea: Dataset for publication
<p>This is the dataset to the publication " Neuromorphic acoustic sensing using an adaptive microelectromechanical cochlea with integrated feedback" by Lenk et al. (DOI will follow soon).</p> <p>Explanation of data:</p> <p>1.) 'MEMS cochlea response to natural sound' (dataset for fig 2 in publication): In this dataset, the file "natural sound dateset" was used to drive a loudspeaker. Its given in wav-format. File named timeseries..." give the data of the response of two different sensors as well as a measurement microphone (named "input") to the wav-file. First column time in sec, second column sensor signal in V. Files named "powerspectra..." give the power spectra data of the three time series, first column frequency in Hz, second column power in absolute values not dB.</p> <p>2.) 'Sensor response in dependence of feedback' (dataset for fig 3 in publication): The dataset includes the sensor signal amplitudes in mV (2nd column) as function of sound pressure amplitudes in Pa (1st column) in files with name starting "fig3a..." for different feedback strengths a_f given by the filename. Files, whose names start with "fig3b+c", give the gain (sensor amplitude active, i.e. a_f>0, divided by sensor amplitude passive, i.e. a_f=0) in the 2nd column as a function of the feedback strength a_f (1st column). In files named "fig3e_sensamp...", the sensor signal amplitude in V (2nd column) is given in dependence of the feedback strength a_f (1st column) for different driving voltages of the loudpseaker, given by the number after "loud" in the filename. If the filename says "negafnegDC", the feedback strength a_f is negativ. If it says "posafnegDC", the feedback strength was positive. The DC voltage of the feedback was always -200mV. From the dependence of sensor signal amplitude on the driving signal amplitude (both in mV), the sensitivity is extracted as the slope of the curve in mV/mV. The sensitvity is given in files, named "fig3e_sensitvity..." in the 2nd column as function of feedback strength a_f (first column).</p> <p>3.) 'Comparison experiment vs model' (dataset for fig 4 in publication): These files give the values plotted in the graphs. The files, named "acrit..." contain the values of a_crit (feedback strength at bifurcation, 2nd column of file) as function of bias voltage u_DC in mV (first column of file) obtained either from experiment or from the formula (last equation in methods part). The file, named "sensitivity...", has the feedback strength a_f in the 1st column and the sensitivity in nm/Pa, obtained frome xperiments, in the 2nd column. The files, named "effective_Q_factor...", have the feedback strength a_f in 1st column and the effective Q factor, obtained from simulations, in the 2nd column. </p> <p>4.) 'Two coupled sensors' (dataset for fig 5 in publication): The files contain the frequency response, i.e. power spectral density in dB (2nd column) as function of frequency in kHz (1st column), of two different sensors for different values of the coupling strength, given by the value after "b" in the filename.</p> <p>5.) 'Dynamic_adaptation_with_code' (dataset for fig 6 in publication): This dataset contains files, names starting with "timeseries...", which give the time series (sensor signal in mV vs. time in sec) for two different driving voltages of the loudspeaker (given by the value after "sound" in the filename), which are shown in fig. 6b in the publication. Files, named "envelope...", give the extracted envelope of the modelled sensor signal in V (2nd column) as function of time in sec (1st column) for different modelled sound inputs, as shown in fig 6c. The envelope was extracted with the program "env.m", written in Matlab. The program "spice_sim" is used to start the LTSpice simulations for adaptation with different parameters. The files in the zip-archive "adapt_,8_,5_natelec" incorporates the necessary files for the LTSPice simulation of the adaptation process. </p> <p> </p>
Data for: Early radial positional information in the cochlea is optimized by a precise linear BMP gradient and enhanced by SOX2
<p>Positional information encoded in signaling molecules is essential for early patterning in the prosensory domain of the developing cochlea. The sensory epithelium, the organ of Corti, contains an exquisite repeating pattern of hair cells and supporting cells. This requires precision in the morphogen signals that set the initial radial compartment boundaries, but this has not been investigated. To measure gradient formation and morphogenetic precision in developing cochlea, we developed a quantitative image analysis procedure measuring SOX2 and pSMAD1/5/9 profiles in mouse embryos at embryonic day (E)12.5, E13.5, and E14.5. Intriguingly, we found that the pSMAD1/5/9 profile forms a linear gradient up to the medial ~75% of the PSD from the pSMAD1/5/9 peak in the lateral edge during E12.5 and E13.5. This is a surprising activity readout for a diffusive BMP4 ligand secreted from a tightly constrained lateral region since morphogens typically form exponential or power-law gradient shapes. This is meaningful for gradient interpretation because while linear profiles offer the theoretically highest information content and distributed precision for patterning, a linear morphogen gradient has not yet been observed. Furthermore, this is unique to the cochlear epithelium as the pSMAD1/5/9 gradient is exponential in the surrounding mesenchyme. In addition to the information-optimized linear profile, we found that while pSMAD1/5/9 is stable during this timeframe, an accompanying gradient of SOX2 shifts dynamically. Last, through joint decoding maps of pSMAD1/5/9 and SOX2, we see that there is a high-fidelity mapping between signaling activity and position in the regions that will become Kölliker's organ and the organ of Corti. Mapping is ambiguous in the prosensory domain precursory to the outer sulcus. Altogether, this research provides new insights into the precision of early morphogenetic patterning cues in the radial cochlea prosensory domain.</p>
GABAergic synapses between auditory efferent neurons and type II spiral ganglion afferent neurons in the mouse cochlea
Open the record for dataset details and reuse information.
Data for: Early radial positional information in the cochlea is optimized by a precise linear BMP gradient and enhanced by SOX2
Open the record for dataset details and reuse information.
SCUBA belt transects for abundance data H. cochlea and H. aequicostatus
<p>Marine symbioses are integral to the persistence of ecosystem functioning in coral reefs. Solitary corals of the species <em>Heteropsammia cochlea</em> and <em>Heterocyathus aequicostatus </em>have been observed to live in symbiosis with the sipunculan worm<em> Aspidosiphon muelleri muelleri</em>, which inhabits a cavity within the coral, in Zanzibar (Tanzania). The symbiosis of these photosymbiotic corals enables the coral holobiont to move, in fine to coarse unconsolidated substrata, a process termed as "walking". This allows the coral to escape sediment cover in turbid conditions which is crucial for these light-dependent species. An additional commensalistic symbiosis of this coral-worm holobiont is found between the <em>Aspidosiphon </em>worm and the cryptoendolithic bivalve <em>Jousseaumiella </em>sp., which resides within the cavity of the coral skeleton. To understand the morphological alterations caused by these symbioses, interspecific relationships, with respect to the carbonate structures between these three organisms, are documented using high-resolution imaging techniques (scanning electron microscopy and µCT scanning). Documenting multi-layered symbioses can shed light on how morphological plasticity interacts with environmental conditions to contribute to species persistence.</p>
Figure 8. Hearing and diving can shape the ear structures. A in The shape of water: adaptations of cochlea morphology in seals and oưers
Figure 8. Hearing and diving can shape the ear structures. A, there is a slight correlation (P = 0.021) for terrestrial species of the bandwidth, number of octaves, and the length of the bony meatus. B, linear regression for the ratio of the average cross-section area size of the cochlea and low frequency cut-off in-air are highly significant for all specimens. C, cochlear height is a relevant factor for the high-frequency cut-off in aquatic animals. D, underwater low-frequency cut-off reveals correlation to the area size of the round window. Legend: filled circles = Pinnipedia + Ursidae, unfilled circles = Musteloidea + Canidae; green = terrestrial species, blue = aquatic + semi-aquatic species * = P ≤ 0.05, **** = P ≤ 0.0001.
Figure 2 in The shape of water: adaptations of cochlea morphology in seals and oưers
Figure 2. PCA of cochlea shape in Caniformia. The shape analysis revealed a paưern of clustering along the axes, with highly terrestrial animals (mustelids, dogs, and foxes) primarily on the upper right quadrant and highly aquatic (Pinnipedia) on the leħ one. The two first PCs explain about 82% of the cochlea shape (PC1 = 53%, PC2 = 29%). The four phylogenetic groups of Pinnipedia + Ursidae and Lutrinae + Mustelinae are highlighted by shaded areas. For beưer visualization, thumbnails of animals with audiogram data have been placed at the respective position of the data point. For each investigated sample, data from the right cochlea was used for PC analysis (N = 52). Blue = aquatic and semi-aquatic animals, green = terrestrial animals; full circle = Pinnipedia and Ursidae, empty circle = Musteloidea and Lutrinae.
Figure 1 in The shape of water: adaptations of cochlea morphology in seals and oưers
Figure 1. Phylogenetic tree of the analysed taxa of Caniformia (Mammalia: Carnivora). The circles illustrate how the taxa are grouped for their habitat: green = terrestrial, blue = semi-aquatic, and their phylogenetic affiliation: full circle = Pinnipedia/Ursidae, empty circle = Musteloidea/ Lutrinae + Canidae in this study. The headphone sign indicates the presence of hearing information via audiograms from the literature (see details in the Supporting Information, Table S1). The discussed origin of pinnipeds is marked by question marks and the presumed origin of a secondary return to the habitat of water with water wave symbols.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.