Research ArticleAPPLIED SCIENCES AND ENGINEERING

Diving beetle–like miniaturized plungers with reversible, rapid biofluid capturing for machine learning–based care of skin disease

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Science Advances  16 Jun 2021:
Vol. 7, no. 25, eabf5695
DOI: 10.1126/sciadv.abf5695
  • Fig. 1 The diving beetle–like reversible microplungers with biofluid-capturing hydrogel.

    (A) Photographic image of the forelegs of H. pacificus. SEM images magnify the spatula setae with suction cup–like structures and circular cavities. Photo credit: C. Pang, Sungkyunkwan University. (B) Schematic illustration of the spatula setae for suction effect and selective binding onto chemical signals to deliver as chemosensory neurons. (C) Schematic illustration of the adhesive patch with diving beetle–inspired suction chambers against rough and wet human skin. (D) Photographic and SEM images of the adhesive patch arrayed with diving beetle–inspired suction chambers. Here, the microcavities are embedded with biofluid-capturing hydrogels for rapid liquid capture. Photo credit: S. Baik, Sungkyunkwan University. (E) Schematic mechanism of suction chambers with embedded hydrogel for absorption of liquid and formation of vacuum chamber upon hydration for reversible attachment. (F) Practical applications of the adhesive patch arrayed with diving beetle–inspired suction chambers for untethered skin pH analysis for facile skincare monitoring.

  • Fig. 2 Adhesion of the DIAs via structural deformation in dry and wet conditions.

    (A) Profiles of normal adhesion for different adhesive samples against silicon wafers in dry and underwater conditions. A preload of 2 N/cm2 is applied for each measurement. (B) Measurements of normal adhesion in dry and underwater conditions with varied material properties of the DIA tip. wt %, weight %. (C) Measurements of normal adhesion in dry and underwater conditions for s-DIAs of different diameters. (D) (i) FEM simulation analysis of stress distribution during the application of a 2 N/cm2 preload. (ii) Volume expansion of the inner chamber during detachment to yield the suction effect. (E) Comparison of stress distribution via FEM simulation for the bottom surface of (i) DIA and (ii) MCP. (F) Predicted (green) and experimental results of normal adhesive strength in dry and underwater conditions corresponding to preload for different adhesive samples.

  • Fig. 3 Adhesive mechanism and performance of the DIAs embedded with biofluid-capturing hydrogels (H-s-DIAs) in dry and wet conditions.

    (A) Schematic illustration of the s-DIA embedded with hydrogel for instantaneous capture of liquids. (B) Measurements of normal adhesion for H-s-DIA in dry (red) and underwater (blue) conditions, s-DIA in dry (violet) and underwater (sky blue) conditions, and bare hydrogel in dry (orange) and underwater (green) conditions with respect to contact time. (C) Schematic illustration of the interfacial fluid transport on the hydrogel-substrate interface for the (i) bare hydrogel before and after liquid absorption and the (ii) H-s-DIA before and after hydrogel swelling within its inner chamber for the optimized state. (D) Confocal fluorescence microscopy images of the embedded hydrogel (i) before and (ii) after the hydrogel is swelled for 2 hours. (E) Adhesive performances of the H-s-DIA adhesives in different states with varying preloads applied in (i) dry and (ii) underwater conditions. Here, the different states of the H-s-DIAs consist of H-s-DIA before contact (orange), H-s-DIA after contact for 2 hours (red), H-s-DIA (blue), and flat samples (gray). (F) Cyclic measurements of normal adhesion for H-s-DIA after 2 hours of contact time in dry and underwater conditions. (G) FEM simulation analysis of the stress distribution and structural deformation of an H-s-DIA during the application of a 2 N/cm2 preload. After the application of a weak preload, the volume of the suction chamber is effortlessly minimized by swelled hydrogel, inducing a vacuum-like state within the chamber.

  • Fig. 4 Applications of the H-s-DIA patch on human skin for pH diagnosis and machine learning–based quantification.

    (A) Profiles of normal, shear, and peeling adhesion of H-s-DIA against dry and sweaty pigskin. (B) Confocal fluorescence microscopy of liquid capture into the embedded hydrogel chamber of H-s-DIA [red, mixture of fluorescent dye (rhodamine 6G), water, and silicon oil]. (C) Schematic illustration of the adhesive patch with skin-attachable, biofluid-capturing suction chambers. The inset shows a representative photographic image of H-s-DIAs of 3-mm tip diameters attached to wet human skin. Photo credit: S. Baik, Sungkyunkwan University. (D) Photographic image of the diving beetle–inspired adhesive embedded with colorimetric hydrogel for reversible skincare monitoring. Time-dependent profiles of red, green, and blue color percentages and cyclic measurements of red, green, and blue color percentages for different pH values of 3 and 9 on skin. (E) Software program for quantifying pH values via supervised machine learning. The software automatically provides pH value by converting RGB values of the captured hydrogel image into x and y values. Photo credit: S. Baik, Sungkyunkwan University. (F) Scatter plot of colors (i.e., x and y values) and pH values. An example image is shown with its color and pH values. (G) Correlation between actual and predicted pH values.

  • Fig. 5 Evaluating the feasibility of the H-s-DIA patch as a smart skincare system.

    (A) Schematic illustration of a mouse study. (B) Scatter plot showing actual and predicted pH values of all data. (C to F) Effect of conditional drug administration in a mouse acne model. All groups except the no treatment (NT) group were treated with patch: the NT group received no drug treatment after acne induction (gray); the pathology score feedback (pathology) group received drug treatment if the pathology score was 4 or higher (blue); the pH monitoring feedback (pH) group received drug treatment if the skin pH value was 7 or higher (red); and the normal skin group did not induce acne (black). The pH value analyses in individual mice (C) and groups (D). (E) Skin pathology score analysis (i) and representative images of acne lesions in each group (ii). (F) Histological analyses of skin tissues using H&E, TB, Gram, and immunohistochemical staining. Scale bars, 250 μm or 100 μm. Black arrows indicate TB-positive cells. Quantification of epidermal thickness using H&E-stained specimens. One-way or two-way analysis of variance (ANOVA) was used to determine statistical significance. *P < 0.05, **P < 0.01, and ***P < 0.001 versus NT. #P < 0.05, ##P < 0.01, and ###P < 0.001 versus pathology score feedback. n.s., not significant.

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