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$Figure 4. <t>FRAP</t> rates of GFP-gephyrin clusters are slowed during inhibitory synapse maturation in vitro. (A) Series of FRAP images taken from single GFP-gephyrin clusters in the CA1 stratum radiatum after bleaching at the 0-min time point; images are from 1- and 4-weeks-old slice cultures prepared from Thy1-EGFPgephyrin mice. Control, unbleached GFP-gephyrin cluster. (B) Quantitative evaluation of experiments as shown in (A). Fast FRAP was seen in 1-week-old cultures, with 30% of the averaged prebleach GFP-gephyrin ﬂuorescence recovering within the ﬁrst 5 min after photobleaching. In contrast, in 4-weeks-old cultures, 30% recovery was reached only 30 min after bleaching (n = 5 cultures per stage; 5–12 clusters bleached per culture; signiﬁcance indicated for averaged 65–80 min values). (C) Group parameters obtained by bi-exponential ﬁtting of the <t>FRAP</t> <t>data</t> shown in (B). While the τ values of the slow and the fast FRAP components were not signiﬁcantly different (n.s.) between 1- and 4-weeks-old cultures, the relative fraction of the fast component was lower, and of the slow component larger, at 4 weeks when compared with 1 week. In addition, a signiﬁcant increase in the stationary fraction of gephyrin clusters was observed in$
Frap Data, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 2341 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/frap+data/Database+Toolbox/pm22918984-96-0-10
Average 96 stars, based on 2341 article reviews

frap data - by Bioz Stars, 2026-10

96/100 stars

Images

1) Product Images from "Homeostatic regulation of gephyrin scaffolds and synaptic strength at mature hippocampal GABAergic postsynapses."

Article Title: Homeostatic regulation of gephyrin scaffolds and synaptic strength at mature hippocampal GABAergic postsynapses.

Journal: Cerebral cortex (New York, N.Y. : 1991)

doi: 10.1093/cercor/bhs260

$Figure 4. FRAP rates of GFP-gephyrin clusters are slowed during inhibitory synapse maturation in vitro. (A) Series of FRAP images taken from single GFP-gephyrin clusters in the CA1 stratum radiatum after bleaching at the 0-min time point; images are from 1- and 4-weeks-old slice cultures prepared from Thy1-EGFPgephyrin mice. Control, unbleached GFP-gephyrin cluster. (B) Quantitative evaluation of experiments as shown in (A). Fast FRAP was seen in 1-week-old cultures, with 30% of the averaged prebleach GFP-gephyrin ﬂuorescence recovering within the ﬁrst 5 min after photobleaching. In contrast, in 4-weeks-old cultures, 30% recovery was reached only 30 min after bleaching (n = 5 cultures per stage; 5–12 clusters bleached per culture; signiﬁcance indicated for averaged 65–80 min values). (C) Group parameters obtained by bi-exponential ﬁtting of the FRAP data shown in (B). While the τ values of the slow and the fast FRAP components were not signiﬁcantly different (n.s.) between 1- and 4-weeks-old cultures, the relative fraction of the fast component was lower, and of the slow component larger, at 4 weeks when compared with 1 week. In addition, a signiﬁcant increase in the stationary fraction of gephyrin clusters was observed in$
Figure Legend Snippet: Figure 4. FRAP rates of GFP-gephyrin clusters are slowed during inhibitory synapse maturation in vitro. (A) Series of FRAP images taken from single GFP-gephyrin clusters in the CA1 stratum radiatum after bleaching at the 0-min time point; images are from 1- and 4-weeks-old slice cultures prepared from Thy1-EGFPgephyrin mice. Control, unbleached GFP-gephyrin cluster. (B) Quantitative evaluation of experiments as shown in (A). Fast FRAP was seen in 1-week-old cultures, with 30% of the averaged prebleach GFP-gephyrin ﬂuorescence recovering within the ﬁrst 5 min after photobleaching. In contrast, in 4-weeks-old cultures, 30% recovery was reached only 30 min after bleaching (n = 5 cultures per stage; 5–12 clusters bleached per culture; signiﬁcance indicated for averaged 65–80 min values). (C) Group parameters obtained by bi-exponential ﬁtting of the FRAP data shown in (B). While the τ values of the slow and the fast FRAP components were not signiﬁcantly different (n.s.) between 1- and 4-weeks-old cultures, the relative fraction of the fast component was lower, and of the slow component larger, at 4 weeks when compared with 1 week. In addition, a signiﬁcant increase in the stationary fraction of gephyrin clusters was observed in

Techniques Used: In Vitro, Control

other:

Article Title: During natural vision, semantic novelty modulates fixation-related processing in primate cortex
Article Snippet: In the human intracranial dataset, the electrode arrays each contained multiple contacts, which were identified using the iELVis MATLAB toolbox ( ).

Article Title: From statistics to deep learning in single-molecule fluorescence resonance energy transfer analysis.
Article Snippet: MASH-FRET [9,26], a MATLAB-based toolbox, uses the BOBA-FRET’s analysis and simulation framework, while adding workflows for molecule localisation and dynamic characterisation. iSMS [27] and SMART [28] offer graphical interfaces for data analysis and visualisation, and enhance standard HMM by incorporating VB and the Bayesian Information Criterion (BIC) while estimating the number of states.

Software:

Article Title: Alpha‐adrenergic mediated changes in blood pressure variability after hypoxia‐ischaemia in preterm fetal sheep
Article Snippet: .. For beat-to-beat BPV analysis, systolic arterial blood pressure peak amplitudes were extracted using LabVIEW software and imported into a customised physiological data analysis toolbox using MATLAB (MATLAB 2023A; The MathWorks, Inc., Natick, MA, USA) to calculate features of beat-to-beat variability. ..

Clinical Proteomics:

Article Title: Parvalbumin-positive neurons in the medial septum participate in the formation of hippocampal-dependent spatial memory.
Article Snippet: .. The EDF files were exported to MATLAB and then analysis sleep state using an open source MATLAB toolbox (https://data.mendeley.com/datasets/c872f83pdz/4)58 Plasma corticosterone measures Plasma samples were collected approximately 12-15 hours after SD, including from the gentle handling SD group. ..

Article Title: Parvalbumin-positive neurons in the medial septum participate in the formation of hippocampal-dependent spatial memory.
Article Snippet: .. The EDF files were exported to MATLAB and then analysis sleep state using an open source MATLAB toolbox (https://data.mendeley.com/datasets/c872f83pdz/4) Plasma corticosterone measures Plasma samples were collected approximately 12-15 hours after SD, including from the gentle handling SD group. ..

Gentle:

Article Title: Parvalbumin-positive neurons in the medial septum participate in the formation of hippocampal-dependent spatial memory.
Article Snippet: .. The EDF files were exported to MATLAB and then analysis sleep state using an open source MATLAB toolbox (https://data.mendeley.com/datasets/c872f83pdz/4) Plasma corticosterone measures Plasma samples were collected approximately 12-15 hours after SD, including from the gentle handling SD group. ..

Generated:

Article Title: Opposing cortical forces: Alpha slowing and sensorimotor mu acceleration during motor-related BCI training.
Article Snippet: .. Topoplots were generated using the MATLAB toolbox from Víctor Martínez-Cagigal (2025): Topographic EEG/MEG plot (https://www.mathworks.com/matlabcentral/fileexchange/72729-topographic-eeg-meg-plot). https://doi.org/10.1371/journal.pcbi.1014112.g003 PLOS Computational Biology | https://doi.org/10.1371/journal.pcbi.1014112 April 1, 2026 8 / 22 showing a positive association with posterior alpha frequency acceleration with effects ranging from negligible to moderate depending on dataset. ..

Functional Assay:

Article Title: Fronto-Cerebellar Connectivity Disruptions and Functional Reorganization in Friedreich's Ataxia: A Structural and Resting-State fMRI Study.
Article Snippet: .. For functional data, grouplevel analyses were performed using the CONN toolbox in MATLAB (v.R2022a) (Nieto-Castanon and Whitfield-Gabrieli, 2022). ..

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Image Search Results

$Live-cell single-molecule microscopy reveals fraction of stably bound PARP1 and PARP2 in undamaged cells (A) (i) Schematic describing the covalent binding of JF646 dye to the HaloTag. (ii) Sample cropped frames from a representative 97 Hz SPT movie depicting the trajectory of a single PARP1 molecule. The 640 nm excitation laser was used continuously for imaging while the camera exposure time was 10.3 ms. (B and C) Single-particle trajectories (length of >2) over 30 s for Halo-PARP1 (in B) or Halo-PARP2 (in C) in a single representative nucleus. (D) Fraction bound ( F bound ) of Halo-PARP1 and Halo-PARP2 in undamaged cells inferred from Spot-On’s three-state model fitting to 97 Hz SPT data. Bar graphs show the mean F bound ± SEM obtained from ≥42,000 trajectories (>3 detections) from ≥52 cells from ≥5 independent replicates (represented by dots), each of which were fitted separately. Statistical difference between the two groups was determined using unpaired t-test. (E) Cumulative distribution function (CDF) of displacements for Halo-PARP1 and Halo-PARP2 (representative Δ τ = 30 ms) in undamaged cells. Individual curves depict data merged from ≥42,000 trajectories (>3 detections) from ≥52 cells from ≥5 independent replicates. (F) A log-log plot showing the uncorrected survival probability (1-CDF) of individual Halo-PARP1 and Halo-PARP2 molecules and their respective two-phase exponential model fits (solid curves) to 2 Hz SPT data in undamaged cells. Each curve represents data merged from ≥870 trajectories from ≥13 cells from ≥3 independent replicates. Data acquired for H2B-Halo (11,737 trajectories from ≥40 cells from 10 independent replicates) was used for photobleaching correction and thereby deriving values for τ transient and τ stable (See <xref ref-type=$ Table S3 ). (G) Scheme showing 97 Hz and 2 Hz SPT workflow. Three-state model fits to 97 Hz SPT data using Spot-On was used to derive fractions and diffusion coefficients of fast diffusing ( F fast , D fast ), slow diffusing ( F slow , D slow ), and bound PARP ( F bound , D bound ) molecules. Further, 2 Hz SPT data were fit using a two-phase exponential model to derive fractions and duration of transient (Fraction transient, τ transient ) and stable (Fraction stable, τ stable ) PARP binding events. (H and I) Pie chart illustrations summarizing the derivation of overall fractions of Halo-PARP1 (in H) and Halo-PARP2 (in I) engaging in transient and stable binding, slow diffusion, and fast diffusion from 97 to 2 Hz SPT experiments. The bound, slow, and fast-diffusing fractions (in i) were determined using Spot-On’s three-state model fitting to 97 Hz SPT data. The bound fraction (in ii) in Halo-PARP1 and Halo-PARP2 cells was analyzed by 2 Hz SPT and fit to a two-phase exponential model. Data acquired for H2B-Halo were used for photobleaching correction, and a correction factor (see ) was applied to obtain the true fraction of transiently and stably binding Halo-PARP molecules (in iii). These data were compiled together to obtain the overall fractions of endogenous Halo-PARP1 and Halo-PARP2 molecules (in iv). (J) Normalized and photobleaching corrected recovery curves from FRAP experiments performed on Halo-PARP1 (blue circles) and Halo-PARP2 (red circles). H2B-Halo (green circles) was used for photobleaching correction. A two-phase exponential model (solid line) was fit to the FRAP data. Error bars represent SD from 11 to 18 cells from ≥3 independent replicates. " width="100%" height="100%">

Journal: iScience

Article Title: Dynamics of endogenous PARP1 and PARP2 during DNA damage revealed by live-cell single-molecule imaging

doi: 10.1016/j.isci.2022.105779

Figure Lengend Snippet: Live-cell single-molecule microscopy reveals fraction of stably bound PARP1 and PARP2 in undamaged cells (A) (i) Schematic describing the covalent binding of JF646 dye to the HaloTag. (ii) Sample cropped frames from a representative 97 Hz SPT movie depicting the trajectory of a single PARP1 molecule. The 640 nm excitation laser was used continuously for imaging while the camera exposure time was 10.3 ms. (B and C) Single-particle trajectories (length of >2) over 30 s for Halo-PARP1 (in B) or Halo-PARP2 (in C) in a single representative nucleus. (D) Fraction bound ( F bound ) of Halo-PARP1 and Halo-PARP2 in undamaged cells inferred from Spot-On’s three-state model fitting to 97 Hz SPT data. Bar graphs show the mean F bound ± SEM obtained from ≥42,000 trajectories (>3 detections) from ≥52 cells from ≥5 independent replicates (represented by dots), each of which were fitted separately. Statistical difference between the two groups was determined using unpaired t-test. (E) Cumulative distribution function (CDF) of displacements for Halo-PARP1 and Halo-PARP2 (representative Δ τ = 30 ms) in undamaged cells. Individual curves depict data merged from ≥42,000 trajectories (>3 detections) from ≥52 cells from ≥5 independent replicates. (F) A log-log plot showing the uncorrected survival probability (1-CDF) of individual Halo-PARP1 and Halo-PARP2 molecules and their respective two-phase exponential model fits (solid curves) to 2 Hz SPT data in undamaged cells. Each curve represents data merged from ≥870 trajectories from ≥13 cells from ≥3 independent replicates. Data acquired for H2B-Halo (11,737 trajectories from ≥40 cells from 10 independent replicates) was used for photobleaching correction and thereby deriving values for τ transient and τ stable (See Table S3 ). (G) Scheme showing 97 Hz and 2 Hz SPT workflow. Three-state model fits to 97 Hz SPT data using Spot-On was used to derive fractions and diffusion coefficients of fast diffusing ( F fast , D fast ), slow diffusing ( F slow , D slow ), and bound PARP ( F bound , D bound ) molecules. Further, 2 Hz SPT data were fit using a two-phase exponential model to derive fractions and duration of transient (Fraction transient, τ transient ) and stable (Fraction stable, τ stable ) PARP binding events. (H and I) Pie chart illustrations summarizing the derivation of overall fractions of Halo-PARP1 (in H) and Halo-PARP2 (in I) engaging in transient and stable binding, slow diffusion, and fast diffusion from 97 to 2 Hz SPT experiments. The bound, slow, and fast-diffusing fractions (in i) were determined using Spot-On’s three-state model fitting to 97 Hz SPT data. The bound fraction (in ii) in Halo-PARP1 and Halo-PARP2 cells was analyzed by 2 Hz SPT and fit to a two-phase exponential model. Data acquired for H2B-Halo were used for photobleaching correction, and a correction factor (see ) was applied to obtain the true fraction of transiently and stably binding Halo-PARP molecules (in iii). These data were compiled together to obtain the overall fractions of endogenous Halo-PARP1 and Halo-PARP2 molecules (in iv). (J) Normalized and photobleaching corrected recovery curves from FRAP experiments performed on Halo-PARP1 (blue circles) and Halo-PARP2 (red circles). H2B-Halo (green circles) was used for photobleaching correction. A two-phase exponential model (solid line) was fit to the FRAP data. Error bars represent SD from 11 to 18 cells from ≥3 independent replicates.

Article Snippet: FRAP data analysis (MatLab script) , Hansen et al. and Sprague et al. , , https://gitlab.com/anders.sejr.hansen/Mahadevan_2022.

Techniques: Microscopy, Stable Transfection, Binding Assay, Imaging, Single Particle, Diffusion-based Assay