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custom-developed algorithms  (MathWorks Inc)


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    MathWorks Inc custom-developed algorithms
    Custom Developed Algorithms, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/custom-developed+algorithm/pmc12163178-107-12-13
    Average 90 stars, based on 1 article reviews
    custom-developed algorithms - by Bioz Stars, 2026-09
    90/100 stars

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    Article Title: Competing Effects between Condensation and Self-Removal of Water Droplets Determine Antifrosting Performance of Superhydrophobic Surfaces.
    Article Snippet: Preventing condensation frosting is crucial for air conditioning units, refrigeration systems, and other cryogenic equipment.. Coalescence-induced self-propelled jumping of condensed microdroplets on superhydrophobic surfaces serves as a favorable strategy against condensation frosting.. In previous reports, efforts were dedicated to enhance the efficiency of self-propelled jumping by constructing appropriate surface structures on superhydrophobic surfaces.

    Article Title: Near-infrared angiography for critical limb ischemia in a diabetic murine model
    Article Snippet: Similar to previous assessments, an investigator blind to the murine diabetic status evaluated the perfusion variables using a custom-developed algorithm in MATLAB and C++.

    Article Title: Improvement of inverse change-point modeling of electricity consumption in residential buildings across multiple climate zones
    Article Snippet: Inverse modeling is a common method to predict electricity consumption in buildings.. Residential building electricity consumption patterns can vary significantly due to occupants and their sporadic energy-consuming behaviors, as well as due to variations in HVAC system types and characteristics across climate zones.. However most data-driven methods in this area have been developed and evaluated using limited datasets.

    Article Title: Pectoralis major tendon repair: a biomechanical study of suture button versus transosseous suture techniques.
    Article Snippet: Data were analysed using a custom-developed algorithm written with Matlab R2011b (Mathworks, MA, USA).

    Article Title: Can Binocular Alignment Distinguish Hypertropia in Sagging Eye Syndrome From Superior Oblique Palsy?
    Article Snippet: Hess screen charts were digitally scanned, and the horizontal and vertical deviations at each target position were quantified by a custom-developed algorithm written in MATLAB (MathWorks, Natick, MA).

    Article Title: Different contractility modes control cell escape from multicellular spheroids and tumor explants
    Article Snippet: The resultant cell outlines are further analyzed with MATLAB using a custom-developed algorithm.

    Article Title: Wavelet Analysis of the Temporal Dynamics of the Laser Speckle Contrast in Human Skin
    Article Snippet: The images obtained were processed with a customdeveloped algorithm using Matlab R2018b.



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    EC-Confetti mice treated with d-flow and hypercholesterolemia at 4 weeks post-PCL (N=6 male and 15 female) were imaged macroscopically ( A ) and LCAs/RCAs were longitudinally sectioned, stained, imaged by fluorescence microscopy ( B-R ), and quantified ( S-V ). A shows representative gross image of LCA, RCA, and aortic arch. B-R . LCAs and RCAs were immunostained with markers of endothelial inflammation (Vcam1 and Icam1, B-D ); EndMT (Acta2, Snai1, and Cnn1, E-H ); EndIT (Cd68, C1qa, C1qb, and Lyz2, I-M ); and EndFT (Spp1, Lgals3, Trem2, and BODIPY, N-R ). B, E, I, and N show merged images of confetti and FIRE markers at low magnification (10X), while the rest show 40X images. Confetti signals show eGFP (green), YFP (green), and RFP (red). All FIRE markers are shown in white except for green BODIPY ( R ). White arrows indicate confetti + ECs co-expressing the FIRE markers. S-V. Percent confetti + ECs co-expressing each FIRE marker was quantified by a combined <t>Matlab</t> and ImageJ analysis. Confetti + ECs expressing markers of inflammation (Icam1 and Vcam1, S ); EndMT (Acta2, Cnn1, and Snai1, T ); EndIT (C1qa, C1qb, Lyz2, and Cd68, U ); and EndFT (Lgals3, Trem2, and Spp1, V ). Shown are mean ± SEM, each dot represents % of confetti + ECs coexpressing FIRE markers in each longitudinal section used for quantification (N=4 to 10 longitudinal sections for RCA; N=6 to 31 longitudinal sections for LCA). P values were calculated by 2-tailed unpaired Student t test with or without Welch’s correction for normal data and 2-tailed unpaired Mann-Whitney U test for non-normal data.
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    EC-Confetti mice treated with d-flow and hypercholesterolemia at 4 weeks post-PCL (N=6 male and 15 female) were imaged macroscopically ( A ) and LCAs/RCAs were longitudinally sectioned, stained, imaged by fluorescence microscopy ( B-R ), and quantified ( S-V ). A shows representative gross image of LCA, RCA, and aortic arch. B-R . LCAs and RCAs were immunostained with markers of endothelial inflammation (Vcam1 and Icam1, B-D ); EndMT (Acta2, Snai1, and Cnn1, E-H ); EndIT (Cd68, C1qa, C1qb, and Lyz2, I-M ); and EndFT (Spp1, Lgals3, Trem2, and BODIPY, N-R ). B, E, I, and N show merged images of confetti and FIRE markers at low magnification (10X), while the rest show 40X images. Confetti signals show eGFP (green), YFP (green), and RFP (red). All FIRE markers are shown in white except for green BODIPY ( R ). White arrows indicate confetti + ECs co-expressing the FIRE markers. S-V. Percent confetti + ECs co-expressing each FIRE marker was quantified by a combined <t>Matlab</t> and ImageJ analysis. Confetti + ECs expressing markers of inflammation (Icam1 and Vcam1, S ); EndMT (Acta2, Cnn1, and Snai1, T ); EndIT (C1qa, C1qb, Lyz2, and Cd68, U ); and EndFT (Lgals3, Trem2, and Spp1, V ). Shown are mean ± SEM, each dot represents % of confetti + ECs coexpressing FIRE markers in each longitudinal section used for quantification (N=4 to 10 longitudinal sections for RCA; N=6 to 31 longitudinal sections for LCA). P values were calculated by 2-tailed unpaired Student t test with or without Welch’s correction for normal data and 2-tailed unpaired Mann-Whitney U test for non-normal data.
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    EC-Confetti mice treated with d-flow and hypercholesterolemia at 4 weeks post-PCL (N=6 male and 15 female) were imaged macroscopically ( A ) and LCAs/RCAs were longitudinally sectioned, stained, imaged by fluorescence microscopy ( B-R ), and quantified ( S-V ). A shows representative gross image of LCA, RCA, and aortic arch. B-R . LCAs and RCAs were immunostained with markers of endothelial inflammation (Vcam1 and Icam1, B-D ); EndMT (Acta2, Snai1, and Cnn1, E-H ); EndIT (Cd68, C1qa, C1qb, and Lyz2, I-M ); and EndFT (Spp1, Lgals3, Trem2, and BODIPY, N-R ). B, E, I, and N show merged images of confetti and FIRE markers at low magnification (10X), while the rest show 40X images. Confetti signals show eGFP (green), YFP (green), and RFP (red). All FIRE markers are shown in white except for green BODIPY ( R ). White arrows indicate confetti + ECs co-expressing the FIRE markers. S-V. Percent confetti + ECs co-expressing each FIRE marker was quantified by a combined Matlab and ImageJ analysis. Confetti + ECs expressing markers of inflammation (Icam1 and Vcam1, S ); EndMT (Acta2, Cnn1, and Snai1, T ); EndIT (C1qa, C1qb, Lyz2, and Cd68, U ); and EndFT (Lgals3, Trem2, and Spp1, V ). Shown are mean ± SEM, each dot represents % of confetti + ECs coexpressing FIRE markers in each longitudinal section used for quantification (N=4 to 10 longitudinal sections for RCA; N=6 to 31 longitudinal sections for LCA). P values were calculated by 2-tailed unpaired Student t test with or without Welch’s correction for normal data and 2-tailed unpaired Mann-Whitney U test for non-normal data.

    Journal: bioRxiv

    Article Title: Disturbed Flow Induces Reprogramming of Endothelial Cells to Immune-like and Foam Cells under Hypercholesterolemia during Atherogenesis

    doi: 10.1101/2025.03.06.641843

    Figure Lengend Snippet: EC-Confetti mice treated with d-flow and hypercholesterolemia at 4 weeks post-PCL (N=6 male and 15 female) were imaged macroscopically ( A ) and LCAs/RCAs were longitudinally sectioned, stained, imaged by fluorescence microscopy ( B-R ), and quantified ( S-V ). A shows representative gross image of LCA, RCA, and aortic arch. B-R . LCAs and RCAs were immunostained with markers of endothelial inflammation (Vcam1 and Icam1, B-D ); EndMT (Acta2, Snai1, and Cnn1, E-H ); EndIT (Cd68, C1qa, C1qb, and Lyz2, I-M ); and EndFT (Spp1, Lgals3, Trem2, and BODIPY, N-R ). B, E, I, and N show merged images of confetti and FIRE markers at low magnification (10X), while the rest show 40X images. Confetti signals show eGFP (green), YFP (green), and RFP (red). All FIRE markers are shown in white except for green BODIPY ( R ). White arrows indicate confetti + ECs co-expressing the FIRE markers. S-V. Percent confetti + ECs co-expressing each FIRE marker was quantified by a combined Matlab and ImageJ analysis. Confetti + ECs expressing markers of inflammation (Icam1 and Vcam1, S ); EndMT (Acta2, Cnn1, and Snai1, T ); EndIT (C1qa, C1qb, Lyz2, and Cd68, U ); and EndFT (Lgals3, Trem2, and Spp1, V ). Shown are mean ± SEM, each dot represents % of confetti + ECs coexpressing FIRE markers in each longitudinal section used for quantification (N=4 to 10 longitudinal sections for RCA; N=6 to 31 longitudinal sections for LCA). P values were calculated by 2-tailed unpaired Student t test with or without Welch’s correction for normal data and 2-tailed unpaired Mann-Whitney U test for non-normal data.

    Article Snippet: To determine the proportion of confetti + ECs undergoing FIRE, multi-level image thresholding was performed via combined use of custom-developed MATLAB algorithms and ImageJ .

    Techniques: Staining, Fluorescence, Microscopy, Expressing, Marker, MANN-WHITNEY