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Coconuts are one of nature’s toughest lignocellulosic materials, possessing a fracture toughness on par with dentin and a compressive strength ten times that of bamboo. The coconut’s hierarchical structure has been characterized before, except prior studies left out one key aspect, the smallest length scales, approaching the molecular level. Here we exfoliate the hard shell of Cocos nucifera, revealing the true cellular organization and the dimensions of the crystalline cellulose nanofibrils found in the cell walls. After chemical pretreatments, we found entanglement between elongated sclereid cells that was not visible in the untreated coconut shell. This may contribute to the mechanical performance of the endocarp; it also utilizes elongated, high-aspect ratio structural elements at the cellular level, in addition to the nanofibrillar level previously known. Compared to other wood-like materials, the cellulose nanofibrils were shorter and represented a smaller weight fraction. This reduced length and the lower filler-to-matrix ratio could be the optimal lignocellulosic nanostructure for tough biomaterials. These newly discovered unique features explain how the endocarp of Cocos nucifera mechanically outperforms materials consisting of the same molecular components. 

Raw data of optical microscopy (OM), field-emission scanning electron microscopy (FE-SEM), atomic force microscopy (AFM), X-ray diffraction (XRD), and data analysis. The data is organized by the figure numbers used in the manuscript, in the order of appearance. This organization is best seen if viewed in the "Tree" mode. File Formats * AFM raw data is provided in NT-MDT's proprietary format (MDT) as well as Gwyddion format (GWY), which can both be viewed using the Gwyddion AFM viewer, which has been released under the GNU public software license GPLv3 and can be downloaded for free at http://gwyddion.net/. * AFM line profile raw data is provided in plain text ASCII (TXT) format. * XRD raw data is provided in plain text ASCII (TXT) format. * FE-SEM raw data always has the SEM image data, provided in TIF format, along with a parameter file produced by the SEM instrument in plain text ASCII (TXT). * Optical microscopy raw data is provided in PNG format. * Data analysis results of nanofibril dimensions are provided in an Excel sheet (XLSX). Data (Folder Structure) Figure 1 * FE-SEM raw data and PNG file from optical microscopy of the coconut. Figure 2 * FE-SEM raw data of all images of the coconut. Figure 3 * MDT and GWY files of all AFM scans of the exfoliated coconut cellulose. Lengths of crystalline nanofibrils were determined manually by running a line profile longitudinally across each nanofibril and determining its end-to-end length, ignoring any bends or kinks. The results of this procedure are shown in an XLSX file (column A). Other columns of this spread sheet contain the number average (B), its standard deviation (C), the sum of lengths (D), and the length weights (E) used to calculate the length-weighted average (G). Figure 4 * MDT and GWY file of the exfoliated coconut cellulose AFM scans. TXT files from XRD and line profile of AFM image. 

While spider silk threads mainly consist of a core of partially crystalline silk proteins, it has been found that they also exhibit a very thin skin layer of distinct structure and a coating rich in lipids and glycoproteins. These outer layers are poorly researched, but can be assumed to be a major player governing the interaction of cells with spider silk threads, as observed in cell culture. Here we propose SAXS/WAXS mapping with ultra-high spatial resolution to examine the surface layer of thin cryo-cut sections of different spider silks that have shown different cell guiding behavior in cell culture. This approach allows studying surface layers from two orientations (along and normal to fiber axis) and the cryo-approach minimizes morphological changes. In a recent nano-SAXS/WAXS beamtime at ID13, we obtained very promising data, however with whole threads and with lower resolution. This follow-up work aims to characterize the surface layer systematically. 

Raw data of optical microscopy, field emission scanning electron microscopy (FE-SEM), transmission electron microscopy (TEM), atomic force microscopy (AFM), force spectroscopy, and data analysis. File Formats * AFM and force spectroscopy raw data, is provided in NT-MDT's proprietary format (MDT) as well as Gwyddion format (GWY), which can both be viewed using the Gwyddion AFM viewer, which has been released under the GNU public software license GPLv3 and can be downloaded for free at http://gwyddion.net/ * FE-SEM and TEM raw data is provided in TIF format * Optical microscopy is provided in PNG format * Data analysis is provided in an excel sheet (XLSX) Data (Folder Structure) Figure 1 * All TIF files (with accompanying TXT files) from FE-SEM and PNG files from optical microscopy of the cribellate silk structure from the K. hibernalis. Figure 2 * All TIF files from TEM, TIF files (with accompanying TXT files) from FE-SEM, MDT and GWY files from AFM of the cribellate silk nanofibrils. Figure 3 + S3 * MDT and GWY files from AFM and force spectroscopy of the cribellate silk nanofibrils as well as the hard substrate and holes within the substrate. XLSX file containing data analysis process with descriptive boxes of what each row does. Figure S4 * MDT and GWY files from AFM and force spectroscopy of the cribellate silk nanofibrils. 

Spider silk (SPSI) is a promising candidate for use as a filler material in nerve guidance conduits (NGCs), facilitating peripheral nerve regeneration by providing a scaffold for Schwann cells (SCs) and axonal growth. However, the specific properties of SPSI that contribute to its regenerative success remain unclear. In this study, the egg sac silk of Trichonephila (T.) inaurata is investigated, which contains two distinct fiber types: tubuliform (TU) and major ampullate (MA) silk. These fibers serve as models to derive material parameters governing SC migration on natural silk substrates, since they are produced by the same spider, yet exhibiting distinct composition and morphology. In this paper, detailed characterization of the fibers’ material properties and in vitro evaluation of their SC-guiding performance were conducted. Live cell imaging revealed significantly enhanced SC mobility and directionality on TU silk compared to MA silk, which is remarkable, given the lack of studies on TU silk for nerve regeneration. Our results suggest that the distinct morphological and material properties of these fibers are critical to their nerve-guiding potential. These insights contribute to the optimization of NGC filler materials by identifying key parameters essential for effective nerve regeneration. 

Atomic force microscopy (AFM) image raw data, force spectroscopy raw data, data analysis/data plotting, and force modeling. File Formats The raw files of the AFM imaging scans of the colloidal probe surface are provided in NT-MDTs proprietary .mdt file format, which can be opened using the Gwyddion software package. Gwyddion has been released under the GNU public software license GPLv3 and can be downloaded free of charge at http://gwyddion.net/. The processed image files are included in Gwyddions .gwy file format. Force spectroscopy raw files are also provided in .mdt file format, which can be opened using NT-MDTs NOVA Px software (we used 3.2.5 rev. 10881). All the force data were converted to ASCII files (*.txt) using the NOVA Px software to also provide them in human readable form with this data set. The MATLAB codes used for force curve processing and data analysis are given as *.m files and can be opened by MATLAB (https://www.mathworks.com/products/matlab) or by a text editor. The raw and processed force curve data and other values used for data processing are stored in binary form in *.mat MATLAB data files, which can be opened by MATLAB. Organized by figure, all the raw and processed force curve data are given in Excel worksheets (*.xlsx), one per probe/substrate combination. Data (Folder Structure) The data in the dataverse is best viewed in Tree mode. Codes for Force Curve Processing The three MATLAB codes used for force curve processing are contained in this folder. The text file Read me.txt provides all the instructions to process raw force data using these three MATLAB codes. Figure 3B, 3C – AFM images The raw (.mdt) and processed (.gwy) AFM images of the colloidal probe before and after coating with graphene oxide (GO) are contained in this folder. Figure 4 – Force Curve GO The raw data of the force curve shown in Figure 4 and the substrate force curve data (used to find inverse optical lever sensitivity) are given as .mdt files and were exported as ASCII files given in the same folder. The raw and processed force curve data are also given in the variables_GO_Tip 18.mat and GO_Tip 18.xlsx files. The force curve processing codes and instructions can be found in the Codes for Force Curve Processing folder, as mentioned above. Figure 5A – Force–Displacement Curves GO, rGO1, rGO10 All the raw data of the force curves (GO, rGO1, rGO10) shown in Figure 5A and the corresponding substrate force curve data (used to find inverse optical lever sensitivity) are given as .mdt files and were exported as ASCII files given in the same folder. The raw and processed force curve data are also given in *.mat and *.xlsx files. Figure 5B, 5C – Averages of Force and Displacement for Snap-On and Pull-Off Events All the raw data of the force curves (GO, rGO1, rGO10) for all the probes and corresponding substrate force curve data are given as .mdt files and were exported as ASCII files given in this folder. The raw and processed force curve data are also provided in *.mat and *.xlsx files. The snap-on force, snap-on displacement, and pull-off displacement values were obtained from each force curve and averaged as in Code_Figure5B_5C.m. The same code was used for plotting the average values. Figure 6A – Force–Distance Curves GO, rGO1, rGO10 The raw data provided in Figure 5A – Force Displacement Curves GO, rGO1, rGO10 folder were processed into force-vs-distance curves. The raw and processed force curve data are also given in *.mat and *.xlsx files. Figure 6B – Average Snap-On and Pull-Off Distances The same raw data provided in Figure 5B, 5C – Average Snap on Force, Displacement, Pull off Displacement folder were processed into force-vs-distance curves. The raw and processed force curve data of GO, rGO1, rGO10 of all the probes are also given in *.mat and *.xlsx files. The snap-on distance and pull-off distance values were obtained from each force curve and averaged as in Code_Figure6B.m. The code used for plotting is also given in the same text file. Figure 6C – Contact Angles Advancing and receding contact angles were calculated using each processed force-vs-distance curve and averaged according to the reduction time. The obtained values and the code used to plot is given in Code_Figure6C.m. Figure 9A – Force Curve Repetition The raw data of all five force curves and the substrate force curve data are given as .mdt files and were exported as ASCII files given in the same folder. The raw and processed force curve data are also given in *.mat and *.xlsx files. Figure 9B – Repulsive Force Comparison The data of the zoomed-in region of Figure 9A was plotted as Experimental curve. Initial baseline correction was done using the MATLAB code bc.m, and the procedure is given in the Read Me.txt text file. All the raw and processed data are given in rGO10_Tip19_Trial1.xlsx and variables_rGO10_Tip 19.mat files. The MATLAB code used to model other forces and plot all the curves in Figure 9B is given in Exp_vdW_EDL.m. 

Spider silk is biocompatible, biodegradable, and rivals some of the best synthetic materials in terms of strength and toughness. Despite extensive research, comprehensive experimental evidence of the formation and morphology of its internal structure is still limited and controversially discussed. Here, we report the complete mechanical decomposition of natural silk fibers from the golden silk orb-weaver Trichonephila clavipes into ≈10 nm-diameter nanofibrils, the material's apparent fundamental building blocks. Furthermore, we produced nanofibrils of virtually identical morphology by triggering an intrinsic self-assembly mechanism of the silk proteins. Independent physico-chemical fibrillation triggers were revealed, enabling fiber assembly from stored precursors “at-will”. This knowledge furthers the understanding of this exceptional material's fundamentals, and ultimately, leads toward the realization of silk-based high-performance materials. 

Peripheral nerve reconstruction through the employment of nerve guidance conduits with Trichonephila dragline silk as a luminal filling has emerged as an outstanding preclinical alternative to avoid nerve autografts. Yet, it remains unknown whether the outcome is similar for silk fibers harvested from other spider species. This study compares the regenerative potential of dragline silk from two orb‐weaving spiders, Trichonephila naurata and Nuctenea umbratica, as well as the silk of the jumping spider Phidippus regius. Proliferation, migration, and transcriptomic state of Schwann cells seeded on these silks are investigated. In addition, fiber morphology, primary protein structure, and mechanical properties are studied. The results demonstrate that the increased velocity of Schwann cells on Phidippus regius fibers can be primarily attributed to the interplay between the silk's primary protein structure and its mechanical properties. Furthermore, the capacity of silk fibers to trigger cells toward a gene expression profile of a myelinating Schwann cell phenotype is shown. The findings for the first time allow an in‐depth comparison of the specific cellular response to various native spider silks and a correlation with the fibers’ material properties. This knowledge is essential to open up possibilities for targeted manufacturing of synthetic nervous tissue replacement. 

Adhesive tapes are versatile and widely used yet lack adhesion strength due to their tendency to fail via peeling, a weak failure mode. A tape with surprising adhesive properties is the recluse spider's 50 nm-thin silk ribbon with a 1 : 150 aspect ratio. Junctions of these microscopic sticky tapes can withstand the material's tensile failure stress of ≈1 GPa. We modeled these natural tape–tape junctions and revealed a bi-modal failure behavior, critically dependent on the two tapes’ intersection angle. One mode leads to regular, low-strength peeling failure, while the other causes the junction to self-strengthen, eliminating the inherent weakness in peeling. This self-strengthening mechanism locks the two tapes together, increasing the junction strength by 550% and allowing some junctions to remain intact after tensile failure. This impressive adhesive strength of tapes has never before been observed or predicted. We found that recluse spiders make tape junctions with pre-stress to force the locked, high-strength failure mode. We used this approach to make junctions with synthetic adhesive tapes that overcame the weak peeling failure. 

Raw data of scanning electron microscopy (SEM), atomic force microscopy (AFM), force spectroscopy, data analysis and plotting, optical microscopy, and finite element simulations (FEA) for our manuscript. File Formats AFM raw data is provided in Gwyddion format, which can be viewed using the Gwyddion AFM viewer, which has been released under the GNU public software licence GPLv3 and can be downloaded free of charge at http://gwyddion.net/ Optical microscopy data is provided in JPEG format SEM raw data is provided in TIFF format Data analysis codes were written in MATLAB (https://www.mathworks.com/products/matlab) and stored as *.m files Imported raw data to MATLAB and saved MATLAB data were stored as MATLAB multidimensional arrays (MATLAB “struct” data format, *.mat files) FEA results were saved as text files, .txt files) Data (Folder Structure) The data in the dataverse is best viewed in Tree mode. Read me file.docx More Explanations of analysis in docx format. Figure 1 Figure 1 - panel b.jpg (5.5 MB) Optical micrograph (JPEG format) Figure 1 - panel c - AFM Raw Data.gwy (8.0 MB) AFM raw data (Gwyddion format) Figure 1 - panel e - P0_Force-curve_raw_data.txt (3 KB) Raw force-displacement data at P0 (text format) Figure 1 - panel e - Px_Force-curve_raw_data.txt (3 KB) Raw force-displacement data at Px (text format) Figure 1 - panel e - Py_Force-curve_raw_data.txt (3 KB) Raw force-displacement data at Py (text format) Figure 1 - panel e - P0_simulation_raw_data.txt (12 KB) FEA simulated force-distance data at P0 (text format) Figure 1 - panel e - Px_simulation_raw_data.txt (12 KB) FEA simulated force-distance data at Px (text format) Figure 1 - panel e - Py_simulation_raw_data.txt (12 KB) FEA simulated force-distance data at Py (text format) Figure 1 - panel e - FCfindc.m (2 KB) MATLAB code to calculate inverse optical lever sensitivity (InverseOLS) of AFM cantelever (matlab .m format) Figure 1 - panel e - FreqFindANoise_new.m (2 KB) MATLAB code to calculate white noise constant, A (Explained in the Read me file) (matlab .m format) Figure 1 - panel e - FreqFindQ_new.m (4 KB) MATLAB code to calculate Q factor of the AFM cantelever (matlab .m format) Figure 1 - panel e - FCkeff.m (2 KB) MATLAB code to calculate the effective spring constant k of the AFM cantelever (matlab .m format) Figure 1 - panel e - FCimport.m (7 KB) MATLAB code to import raw force-displacement data into MATLAB (matlab .m format) Figure 1 - panel e - FCForceDist.m (2 KB) MATLAB code to convert raw force-displacement data into force-distance data (matlab .m format) Figure 1 - panel e - Figure 1- Panel e - data.mat (6 KB) MATALB struct data file for calibrated force-distance data at all indentation points (matlab .mat format) Figure 1 - panel e - Panel_e_MatlabCode.m (6 KB) MATALB code for plotting experimental and simulated force curves in panel e (matlab .m format) Figure 1 - panel e - Read me file - force curve calibration.docx (14 KB) Explains force curve calibration (.docx format) Figure 1 - panel e - Read me file - lever spring constant calibration.docx (14 KB) Explains AFM lever spring constant calibration (.docx format) Figure 2 Figure 2 - panel a - MATLAB data.mat (2.6 KB) MATALB data file for simulated data (matlab .mat format) Figure 2 - panel b - MATLAB data.mat (2.4 KB) MATALB data file for simulated data (matlab .mat format) Figure 2 - panel a - simulation raw data.txt (5.0 KB) Raw simulation data: xyz coordinates of the nodes of deformed FEA mesh (text format) Figure 2 - panel b - simulation raw data.txt (5.0 KB) Raw simulation data: xyz coordinates of the nodes of deformed FEA mesh (text format) Figure 2 - panel ab - MATLABcode.m (1.0 KB) MATALB code for plotting panel a b figures (matlab .m format) Figure 2 - panel c - Degree of Anisotropy datacode.m (1.0 KB) MATALB code for plotting panel c graph (matlab .m format) Figure 3 Figure 3 - panel a - App_curve_1_raw_data.txt (35 KB) Raw force-displacement data approach curve 1 (text format) Figure 3 - panel a - App_curve_2_raw_data.txt (34 KB) Raw force-displacement data approach curve 2 (text format) Figure 3 - panel a - App_curve_3_raw_data.txt (34 KB) Raw force-displacement data approach curve 3 (text format) Figure 3 - panel a - App_curve_4_raw_data.txt (34 KB) Raw force-displacement data approach curve 4 (text format) Figure 3 - panel a - Ret_curve_1_raw_data.txt (35 KB) Raw force-displacement data of retract curve 1 (text format) Figure 3 - panel a - Ret_curve_2_raw_data.txt (35 KB) Raw force-displacement data of retract curve 2 (text format) Figure 3 - panel a - Ret_curve_3_raw_data.txt (35 KB) Raw force-displacement data of retract curve 3 (text format) Figure 3 - panel a - Simulation_raw_data-part 1.txt (43 KB) simulated force-displacement data of -part 1 (text format) Figure 3 - panel a - Simulation_raw_data-part 2.txt (43 KB) simulated force-displacement data of -part 2 (text format) Figure 3 - panel a - FCfindc.m (2 KB) MATLAB code to calculate inverse optical lever sensitivity (InverseOLS) of AFM cantelever (matlab .m format) Figure 3 - panel a - FreqFindANoise_new.m (2 KB) MATLAB code to calculate white noise constant, A (Explained in the Read me file) (matlab .m format) Figure 3 - panel a - FreqFindQ_new.m (4 KB) MATLAB code to calculate Q factor of the AFM cantelever (matlab .m format) Figure 3 - panel a - FCkeff.m (2 KB) MATLAB code to calculate the effective spring constant k of the AFM cantelever (matlab .m format) Figure 3 - panel a - FCimport.m (7 KB) MATLAB code to import raw force-displacement data into MATLAB (matlab .m format) Figure 3 - panel a - FCForceDist.m (2 KB) MATLAB code to convert raw force-displacement data into force-distance data (matlab .m format) Figure 1 - panel e - Read me file - force curve calibration.docx (14 KB) Explains force curve calibration (.docx format) Figure 1 - panel e - Read me file - lever spring constant calibration.docx (14 KB) Explains AFM lever spring constant calibration (.docx format) Figure 3 - panel b - SEM Raw Data.tiff (9 KB) SEM raw image of broken silk membrane due to extreme indentation (.tiff format)