The optimization of wheat starch esterification (acetylation) with a high degree of substitution was performed through response surface methodology (RSM) via various concentrations of reagents (acetic anhydride), pHs, and temperatures under various ultrasonication frequencies . According to RSM methodology, optimized samples were selected by achieving high degrees of substitution at various frequencies, temperatures, and pHs. Solubility, swelling, X‐ray, RVA, DSC, freeze–thaw stability, texture, and SEM analysis of the optimized samples were performed at three frequencies. X‐ray pattern exhibited a more significant reduction in the crystallinity percentage of esterified starch at frequency 25 + 40 kHz compared with 25 kHz, 40 kHz, and native starch. According to DSC analysis, To, Tp, Tc, and enthalpy of gelatinization (ΔH gel) were lower in AC at frequency 25 + 40 kHz compared with AC at frequency 25 and 40 kHz and N starches. According to morphology analysis, in acetylated starches at 25 and 40 kHz, the surfaces and small granules underwent more damage, whereas in 25 + 40 kHz, large granules were more affected than small granules. Upon acetylation, freeze–thaw stability and textural properties of the starch significantly increased and decreased, respectively. The peak and final viscosity of acetylated starch increased (25 + 40 kHz ˃ 25 kHz ˃ 40 kHz ˃ N starch). The suspensions were completely washed, lyophilized, and milled using a laboratory mill , and manually sieved to obtain particle sizes < 40 μm , and acetic anhydride  was slowly added to the suspension at various pHs. Whole acetylation reaction was performed at 10 min. The suspensions were sonicated at an amplitude of 24%  at 45, 60, and 75°C. The time duration of sonication in each frequency was 5 min . pH was then maintained at 4.5 with HCl solution (1 M) for 5 min. All the experiments were performed in bakers placed at known positions in ultrasonic bath (Pacisa SA) equipped with a temperature controlling system. The ultrasonic bath with internal dimensions of 300 × 150 × 150 mm2.3The titrimetric method of Mbougueng, Tenin, Scher, and Tchiégang  was emplVB and VS are the volumes of the control and modified samples (0.2 M HCl basis), respectively.NHCl is the normality of the consumed acid.W is the weight of the sample.2.4To obtain a relative humidity of 75%, all starch samples were primarily placed, for 5 days, in a relative humidity box containing supersaturated NaCl at room temperature. X‐ray diffraction pattern of the samples was determined by use of an X‐ray diffractometer  , peak temperature (Tp), and conclusion temperature (Tc) for gelatinization were obtained from the exotherm DSC curves.The gelatinization properties of the native and modified wheat starches were analyzed using a DSC instrument  equipped with STAR software making using of Pourmohammadi et al.  method. 2.8The microstructure of the modified starch was specified using SEM (Model Leica Cambridge) by use of the method proposed by Pourmohammadi et al. .2.9Textural properties of starch gels were specified using a Texture Profile Analyzer . To prepare the paste of gelatinized starch, 10 g of starch was added to 100 ml of distilled water, where the slurry remained in water bath (95°C for 30 min). The hot paste was collected and transferred into a cylindrical plastic container of 10 mm diameter and 10 mm height, and kept at 4°C for 24 hr. The gels were then removed from the container and tested for their textural properties. Utilizing a cylindrical aluminum plunger with a diameter of 10 mm, the gels were packed at a test speed of 2 mm/s, pretest and post‐test speed of 5 mm/s, time interval of 10 s, and strain deformation of 24%. The recorded force–time plots were analyzed for the following: hardness (N), springiness (Length 2/ Length 1), cohesiveness, the ratio of the areas of the two resistance peaks (A2/A1), and gumminess according to Abedi, Majzoobi, Farahnaky, Pourmohammadi, and Mahmoudi . Data we2.10With slight modifications in the methods described by Lawal , we dete2.11So as to specify the regression coefficients, the Design‐Expert version 6.0.5) methodology DegreOptimized samples were selected based on minimum reagent consumption (acetic anhydride with achieving to maximum modification). According to response surface methodology (RSM) analysis, the optimized AC wheat starch was acetic anhydride (5%), pH 8.5, and temperature 60°C with 1.22%, 1.37%, and 1.02% acetylation for 25 kHz, 25 + 40 kHz, and 40 kHz, respectively. = O bond of the acetyl group was substituted in all amorphous areas and at the outer lamellae of crystalline sections due to the poor ability of acetic anhydride to penetrate granule structures  of amylose and amylopectin, granular size, presence of lipids, and reaction medium factors, such as pH, temperature, reaction time, mixing uniformity, and reagent content during the modification of the starches  from N (36.89 ± 0.62) to AC at 25 kHz (17.80 ± 0.38), 40 kHz (22.43 ± 0.42), and 25 + 40 kHz (13.57 ± 0.41) frequencies of wheat starches. The X‐ray diffraction showed that with acetylation, the structures of native starch were destroyed, and new structures of esterified starches were formed. Crystalline regions are the main factors preventing the loss of granular structure during reaction with reagents, and preserving the integrity of granular structure  was reduced to 12.68 ± 0.12, 18.93 ± 0.24, and 9.23 ± 0.36 following acetylation at ultrasound frequencies 25, 40, and 25 + 40 kHz, respectively. This means that amorphous regions reacted with acetic anhydride, a finding which is in accordance with Diop, Li, Xie, and Shi  at all measured temperatures. The solubility and water absorption of AC wheat starch at frequencies 25, 40, and 25 + 40 kHz were 7.37–36.77 and 6.30–23.98, 6.57–34.49, and 5.83–20.94, and 8–40.77 and 7.03–27.60, respectively, which is much higher than N wheat starch . Similar increasing trends in solubility and WA due to acetylation have been reported for potato and corn starches  disruption of hydrogen bonds in the starch granules and facilitation of water access to the amorphous region  lower than AC starches at frequencies 25 , 40 , and 25 + 40 kHz . The AC at frequency 25 + 40 kHz (50.9 ± 1.2) had lower pasting temperatures compared with 25 kHz (58.3 ± 1.4), 40 kHz (64.4 ± 1.2), and N (71.6 ± 1.6). These findings are in accordance with the results of Li et al. i et al. . On the i et al. .3.8gel value (11.8 ± 0.8 J/g), followed by AC wheat starches at frequency 25 kHz (6.4 ± 0.8), 40 kHz (9.5 ± 0.4), and 25 + 40 kHz (5.8 ± 0.8). Singh et al. (p < 0.05) decrease in the gelatinization temperature of corn, potato, tapioca, and sweet potato starches following acetylation. The starch gelatinization is controlled by two factors: (a) amylopectin molecular structures such as molar mass, integrity and order of crystallites, polydispersity, and amylopectin chain length with a degree of polymerization (DP) ranging between 5 and 12, and (b) granule structures including granule size, amylose/amylopectin ratio, crystalline zone relationship, and the quality and amount of amorphous crystallites  between N and AC wheat starches as far as cohesiveness is concerned; however, their gumminess was reduced. Adhesiveness is the attraction between the gel and an external surface. Adhesiveness of N wheat starch gel was significantly (p < 0.05) higher than AC wheat starch gels, which is in line with Liu et al.  during storage at 4°C Figure . During 4In order to increase the DS and consumption of minimum reagents, a reaction mixture was carried out under ultrasonic processes. The molar substitution optimizing AC wheat starch was 1.22%, 1.37%, and 1.02% for 25 kHz, 25 + 40 kHz, and 40 kHz, consuming 5% of acetic anhydride. High DS is due to the ultrasonic conditions at dual frequency (25 + 40 kHz) which form fractures, pores, and cracks on the surface of granules, facilitating the penetration of reagents into granule starch. Acetylation ameliorates the solubility, water absorption, resistance to freeze and thaw cycle, and viscosity peak, and reduces the gelatinization temperature.The authors declare that they do not have any conflict of interest.Human and animal testing is unnecessary in this study.


Starch is the main source of energy in commonly used pig diets. Besides effects related to the extent of starch digestion, also several effects related to variation in digestion rate have recently been demonstrated in non-ruminants. Different rates of starch digestion in animals and in in vitro models have been reported, depending on the botanic origin of starch. Starches from different botanic sources differ widely in structural and molecular properties. Predicting the effect of starch properties on in vitro digestion kinetics based on existing literature is hampered by incomplete characterization of the starches, or by a selective choice of starches from a limited number of botanic sources. This research aimed to analyse the relationships between starch properties and in vitro digestion kinetics of pure starches isolated from a broad range of botanic origins, which are used in non-ruminant diets or have a potential to be used in the future. Therefore we studied starch digestion kinetics of potato, pea, corn, rice, barley, and wheat starches, and analysed the granule diameter, number of pores, type and amount of crystalline structure, amylose content and amylopectin side-chain length of all starches.Multivariate analysis revealed strong correlations among starch properties, leading us to conclude that effects of most starch characteristics are strongly interrelated. Across all analysed botanic sources, crystalline type and amylopectin chain length showed the strongest correlation with in vitro digestion kinetics. Increased percentages of A–type crystalline structure and amylopectin side chains of DP 6–24 both increased the rate of digestion. In addition, within, but not across, (clusters of) botanic sources, a decrease in amylose content and increase in number of pores correlated positively with digestion kinetics.The type of crystalline structure and amylopectin chain length distribution of starch correlate significantly with digestion kinetics of starches across botanic sources in an in vitro pig model. Variation in digestion kinetics across botanic sources is not additively explained by other starch properties measured, but appears to be confined within botanical sources.The online version of this article (10.1186/s40104-018-0303-8) contains supplementary material, which is available to authorized users. Starch is the main source of energy in commonly used diets for non-ruminants. Starches in those diets are of various botanic origin, which usually causes variation in digestion rate in the gastro-intestinal tract. Diverse effects related to variation in starch digestion kinetics have been demonstrated in pigs. For example, diets containing resistant starch (RS) or slowly digestible starch (SDS) affect feeding patterns  and ener1 chains participate in one cluster, B2 and B3 chains participate respectively in two or three clusters. A chains are present at the outside of the branched molecule and have only an α(1–6) linkage to B1 chains [1 chains with DP 13–24, B2–4 chains with DP 25–36, and B5-x-and C-chains with DP > 36. Clustered amylopectin side chains and amylose chains are organized in the helix conformation that subsequently forms crystalline structures, which can be divided into three types: A, B and C. In A-type crystalline starch, glucose helixes are packed densely whereas B-type crystalline starch is packed less dense, leaving room for water molecules in between the branches. C-type crystalline starch consists of a combination of A- and B-type crystallinity [Starch is composed of two types of polysaccharides: amylose, a linear α(1–4) linked glucan, and the much larger amylopectin, an α(1–4) linked glucan that contains around 5% α1–6) linkages resulting in a branched molecule  linkages. Side ch1 chains . Based o1 chains  and on t1 chains , A chainallinity , ultimatallinity . Granuleallinity .Research has aimed to describe relationships between structural starch features and (in vitro) digestibility. The outcome of research, however, is influenced by the choice of starting material. For instance, when analysing purified starch samples that originate from the same botanic source, high levels of amylose correlate positively with the proportion of in vitro measured RS –16. ThisEstimating the contribution of each distinct characteristic to starch digestion kinetics is hampered by inherent combinations of these starch characteristics within each botanic source. For example, large granules are usually digested slower than small granules, but often consist of slowly digestible B-type crystals . The samQuantifying the influence of each individual starch characteristic based on literature is extremely difficult . By relaPure starches from different botanic origins were selected to cover maximum relevant variation in amylose content, granular size, proportion and type of crystallinity, and the presence of pores. 15 different starches were used, of which one starch was additionally sieved into 5 fractions, creating a total of 20 samples. Rice starches Remyline AX-DR (waxy rice), Remy B7 (rice A) and Remy B (rice B) were kindly provided by the Beneo group . Nastar yellow pea starch (pea A) was obtained from Cosucra group  and wheat starch (wheat) was obtained from Fluka Biochemika . Corn starches M03401 (corn A) and M04201 (waxy corn) were kindly provided by Cargill B.V. , high amylose corn starch Hylon V (high amylose corn A) was obtained from Ingredion , and barley starch (barley) was kindly provided by Altia Corporation . Native potato starch, Eliane 100 (waxy potato), and experimental Heat Moisture Treated potato starch (HMT potato), based on native potato starch, were kindly provided by Avebe . Regular corn starch (corn B), high amylose Amylomaize (high amylose corn B), and regular pea starch (pea B) were obtained from Roquette . All starch samples were stored at room temperature until analysed. All enzymes and chemicals were purchased from Sigma Aldrich  unless stated otherwise.Granule size distribution was determined as the mean of 5 measurements (maximum standard deviation of the mean diameter was 0.41 μm) with a Mastersizer3000 . Potato starch samples were fractionated using a vibratory sieve shaker  with demineralized water as washing liquid. Size fractions were air-dried overnight at 40 °C. Potato starch was separated into five fractions: smaller than 20 μm, 21–32 μm, 33–53 μm, 54–71 μm, and 72–109 μm, of which the granule size distribution was determined as described above.Starch morphology was determined with a Scanning Electron Microscope (SEM) . Dry starch granules were attached on sample holders using carbon adhesive tabs  and sputter coated with 15 nm tungsten . Granules were analysed with a field emission SEM with SE detection at 2 kV. Starch morphology was studied at 1,000 times magnification and starch surfaces were studied at 25,000 times magnification. All samples were measured at the Wageningen Electron Microscopy Centre and from each sample at least 20 individual granule surfaces were studied. To ensure the analysis of a homogenous sample, individual granules were selected in such a way that granules from each diameter were represented in accordance with their relative abundance as measured with the Mastersizer.X-ray diffraction (XRD) was used to identify the crystalline structure of starch samples. Wide angle X-ray scattering (WAXS) powder diffractograms were recorded on a Bruker Discover D2 diffractometer  in the reflection geometry in the angular range 4–33°(2θ), with a step size of 0.02°(2θ) and an acquisition time of 2.0 s per step. The diffractometer was equipped with an LINEXEYE™ Silicon-strip detector, which had a 4°-5° active area. The Co Kα1 radiation  from the anode, generated at 30 kV and 10 mA, was monochromatized using a Ni filter. The diffractometer was equipped with a 1 mm divergence slit and a 0.5-mm knife edge above the sample stage, which enabled accurate measurements from 4° 2θ upwards. The proportion of crystallinity was determined by subtracting the background from the WAXS pattern of a sample. Intensities are expressed as relative where the intensity of the peak at diffraction angle 20.0°(2θ) is set to 1.0, as this peak showed the highest intensity in both A- as B-type of starch. Samples that contained a mixture of typical A- and B-type crystalline diffraction spectra were modelled (with a least-squares error fit procedure) to deduce the exact proportions of A- and B-type crystallinity.Amylose content of starch samples was determined according to the amylose/amylopectin assay procedure of the supplier , in which amylose was separated from amylopectin by Concanavalin A lectin. Amylose was enzymatically hydrolysed and glucose recovery was determined by a glucose oxidase peroxidase reaction. All samples were analysed in triplicate (maximum standard deviation of 0.8%).Total starch content of each sample was determined according to the total starch assay procedure from Megazyme by subsequently washing the starch with ethanol (part e of the assay procedure supplied by Megazyme), dissolving the starch in KOH (part c of the assay procedure supplied by Megazyme) and finally enzymatically hydrolysing the starch (part a of the assay procedure supplied by Megazyme). Glucose was determined with a glucose oxidase peroxidase reaction. The total starch content was solemnly used as a correction factor in the in vitro digestion assay. All samples were analysed in triplicate (maximum standard deviation of 1.1%).Amylopectin chain length was determined after starch samples were debranched with 0.32 mL isoamylase  per gram starch at pH 4 for 17 h at 50 °C, after starch samples were dissolved in boiling water. Debranched samples were analysed on ICS5000 High Performance Anion Exchange Chromatography system with Pulsed Amperometric detection (HPAEC-PAD)  equipped with a CarboPac PA-1 column (ID 2 mm × 250 mm) and a CarboPac PA guard column (ID 2 mm × 25 mm). The flow rate was set at 0.3 mL/min. The two mobile phases were (A) 0.1 mol/L NaOH and (B) 1 mol/L NaOAc in 0.1 mol/L NaOH and the column temperature was 20 °C. The elution profile was as follows: 0–50 min 5–40% B, 50–65 min 40–100% B, 65–70 min 100% B, 70–70.1 min 100–5% B and finally column re-equilibration by 5% B from 70.1 to 85 min. The injection volume was 10 μL. Glucose was used to quantify concentrations of side-chains with DP up to 5  and maltohexaose was used to quantify side-chains with DP > 5. All samples were analysed in duplicate and the average amylopectin chain length per sample had a maximum standard deviation of 0.7 DP. To facilitate the comparison of starch samples, amylopectin side-chains were clustered into four categories, DP 6–12, DP 13–24, DP 25–36, and DP >  36, in analogy to the cluster model of Robin et al. [n et al. . For Pean et al. , 10.In vitro starch digestion kinetics were determined with a digestion method described by Englyst et al. [t et al.  and Van t et al. . Brieflyt et al. , samplesAlthough multiple equations can be used to model in vitro starch digestion, a relative simple model was chosen to enable further statistical analysis. This resulted in the use of a modified version of the Chapman-Richards model as previously described by van Kempen et al. Eq. 1)::1):starch hydrolysis is expressed as % of starch in sample, plateau is the maximum amount of glucose released during digestion, which is converted to starch (as % of sample weight) by multiplying with factor 0.9. K is the rate of glucose release corrected for plateau effects (as % of starch hydrolysed to glucose per minute). The model was fitted to the data using the average of at least triplicate observations. The K and plateau value of each starch sample were estimated by nonlinear regression procedures . For estimation of the plateau value, a boundary was included forcing the estimation to be ≤100%. The model was also fitted after the plateau value was fixed to 100%, but the fit of this model was less good, as for some starches the estimated plateau value was far below 100%.The Correlation coefficients between measured starch properties were generated using Pearson’s correlation procedure (proc CORR) in SAS. Correlations with P ≤ 0.05 were taken as statistically significant and 0.05 < P ≤ 0.1 as a tendency for significance.Principal Component Analysis (PCA) was conducted using the factor procedure in SAS on the starch characteristics, to examine whether variation in these starch characteristics could be summarized in the estimation of principle components (PC’s) that are uncorrelated. After extraction, PC’s were scaled by their standard deviations  and subjected to orthogonal rotation (varimax) to obtain independent factors. The amount of variation in starch digestion kinetics explained by each independent PC was analysed with Pearson’s correlation procedure.To make a comparison between starches from different botanic sources and their effect on in vitro starch digestion kinetics, 20 starches from different botanic sources  were analysed on several characteristics regarding the molecular and granular structure of the starches.The average granular diameter of the starches used in this study ranged from 6 to 92 μm , illustrating both variation in granular size, size distribution, and shape  to 55% for high amylose corn starch . This indicates that PC1, combining granule diameter, pores, type of crystalline structure, and the side-chain length distribution of amylopectin, is associated with variation in starch digestion rate. This association is less strong for PC2, mainly reflecting the effect of the amylose content. As the proportion of crystalline structure is loaded on both PC1 and PC2 equally, but with loadings below 0.5, this property appears to explain little variation in digestion kinetics.The potential of PC1, PC2 and each of the individual starch properties to explain variation in the rate of starch degradation is presented in Table K  than some of the parameters individually, such as the type of crystalline structure  and the fraction of short (DP 6–12) amylopectin side-chains .Although 4 of 6 parameters have high loadings on PC1, the combination of parameters unexpectedly does not explain more variation in Previous research has focussed on the contribution of starch digestion to dietary energy supply, but currently also the effects of variation in starch digestion kinetics have become more clear –4. PropeMost of the measured starch properties are close to values that were published before , 37–43, t = 24 h) was performed with a selection of those starches, namely high amylose corn A and pea A starch. During this prolonged incubation the extent of starch digestion exceeded the estimated plateau value (towards 84.1% and 100% respectively). This indicates that the estimated plateau value is required for a good fit of data, but does not necessarily reflect the asymptotic maximum glucose release for all starch samples, as stated by van Kempen et al. [The inevitable consequence of a model with only two parameters, is an imperfect fit of data for some starch sources Table , Fig 6. n et al.  and Engln et al. . TherefoAs illustrated with PCA, variation in starch properties could be summarised in two independent factors, but neither factor additively explained variation in digestion kinetics. To understand the contribution of each distinct starch property to the variation observed in starch digestion kinetics, individual properties are further discussed in groups of starches that have similarities in their botanical origin and in groups of starches that have similar properties.r = − 0.72, P = 0.03) between amylose content and starch digestion rate. However, within these cereal starches, interrelationships between amylose content, pores, type of crystalline structure, and the side-chain length distribution of amylopectin were present as well, which were absent in the complete dataset. Those interrelationships between starch characteristics make it impossible to separate effects of the amylose content from other starch characteristics and to draw conclusions on the role of amylose on digestion kinetics.The observation that amylose content, a high loading on PC2, is not associated with starch digestion kinetics, contradicts with previous research –16. HoweP < 0.01) starch hydrolysis of waxy corn (36%) compared with barley (45%) and wheat starch (53%) after 20 min of in vitro digestion. Barley, wheat and waxy corn starch have comparable characteristics, except for the proportion of amylose and the number of pores, as waxy corn starch has a lower amylose content and more pores than barley and wheat starch. This indicates that, across botanic sources, a starch with a low amylose content is not necessarily more rapidly digestible than starches with a normal amylose content.We conclude that an increased amylose content negatively correlates with starch digestion kinetics when comparing starches within botanic sources, but is not the largest factor in explaining variation in starch digestion kinetics across botanic sources. This is clearly illustrated by a lower (P < 0.0001) starch hydrolysis after 20 min of in vitro digestion  than corn A (25%), which has many pores . However, correlations between the number of pores and the amylose content , and number of pores and the percentage of A-type crystals  are also observed within these samples and have additionally been shown for barley starch previously [In general, pores are believed to enable enzymes to digest starch granules from the inside out, which increases the rate of hydrolysis of the granules , 28. Howeviously . TherefoK value was identified , when analysing the complete set of starches. However, it is not clear whether this correlation is the result of collinearity between the granule diameter and another starch parameter, or whether the granular size is affecting the digestion rate. Consequently, additional statistical analysis of sieved fractions of potato starch provides was performed. Those five sieved starch fractions differ primarily in average granule diameters, varying from 18.9 μm to 92.2 μm, whereas the difference among the other properties was negligible , demonstrating that for the potato starch used in this study, granule diameter, and consequently surface area, has no causal relation with digestion kinetics. Previous research on the relation between granule diameter and digestion kinetics showed interrelationships between variables such as granule diameter and amylose content [A correlation between the starch granule diameter and  content , 47 and  content . This imK  but they also have a strong correlation with each other  to long (DP >  36) amylopectin side-chains remain as starch characteristics that affect starch digestion kinetics. Both show strong positive correlations with her Fig. , confirmR2) in digestion kinetics explained by PC1 across all botanic sources did not exceed 45% and was lower than the proportion of variance explained by the type of crystalline structure alone (R2 = 66%). In an attempt to further challenge the concept of additivity, interrelations between the measured starch properties were examined within several clusters of botanic sources and illustrated with PCA. The structural starch properties were correlated with in vitro digestion kinetics within those clusters of botanic sources. When exploring the correlations between starch properties, the lack of additivity proved to be highly affected by the combination of selected botanic sources that were evaluated statistically. For example, multivariate analysis with only corn, pea and potato starches resulted in an PC loading profile that is comparable with the one obtained from the full dataset  exceeds that of the type of crystalline structure (81%), the number of pores (89%), and the ratio of short: long amylopectin side chains (87%) individually  botanical sources variation in digestion kinetics is additively explained by other starch properties measured.Additional file 1:Table S1. In vitro digestion of all analysed starches. (DOCX 36 kb)Additional file 2:Table S2. Rotated factor pattern, eigenvalues and proportion variance explained of principle components in multivariate analysis of subdataset 11. Table S3. Pearson correlation coefficients for starch properties and digestion kinetics, within subdataset 11,2. (DOCX 36 kb)Additional file 3:Table S4. Rotated factor pattern, eigenvalues and proportion variance explained by principle components in multivariate analysis of subdataset 21. Table S5. Pearson correlation coefficients for starch properties and digestion kinetics, within subdataset 21,2. (DOCX 36 kb)


The objective of this study was to investigate the effects of rice variety, water content, and preparation temperature on the textural properties of gels processed from cooked rice grains via high‐speed shear homogenization. Rice gels were prepared from seven high‐amylose rice varieties. The results demonstrated the significant differences in rice gel hardness and hardening rates during storage based on the rice variety used. The proportion of short chains of amylopectin was negatively correlated with the hardness of the rice gel. The sample temperature before shear treatment also influenced the rice gel hardness. Rice gels prepared from cooked rice maintained at 75°C prior to homogenization showed a higher breaking force than those from cooked rice at 25°C. Observation using scanning electron microscopy demonstrated the tendency of the cooked rice sample maintained at 75°C to form a finer gel network after homogenization than those at 25°C from the same rice variety. The rheological properties of rice flour gel contribute to the texture and palatability of rice flour products such as noodles. Starch is the primary component of rice and an important ingredient in processed foods made from rice. When starch granules are heated in excess water, the granules swell and gelatinize, during which process the molecular order of the starch granule is destroyed. When cooling a sufficiently concentrated suspension of gelatinized starch, starch retrogradation occurs, resulting in gel formation. Retrograded starch is common in the human diet, because it is formed by cooking or food processing. The physical properties of starch, such as gelatinization, retrogradation, and gelation, play an important role in determining the quality of rice products. Starches consist of amylose and amylopectin. The short‐term development of retrogradation in starch gels is attributed to the gelation of the solubilized amylose fraction , and HA3 and HA4 were grown at the Western Region Agricultural Research Center, NARO . Yumetoiro (Yume), Momiroman (Momi), and Hoshiyutaka (Hosh) were obtained from farmers.2.2N × 5.95) was determined using the Kjeldahl method.The total starch content of the rice was determined using an assay kit . Apparent amylose content was determined by iodine colorimetry , 3× , or 4×  the mass in distilled water was added to bring the total mass to 80 g . The rice was cooked in a water bath at 98°C for 30 min with an aluminum foil cover, and the cooked rice samples were maintained in a water bath at 25°C or 75°C for 30 min immediately after cooking and then homogenized using an Excel auto homogenizer  at 5000 rpm for 3 min. Stainless steel petri dishes measuring 40 mm in diameter and 15 mm in height were filled with the homogenized rice pastes and sealed in airtight bags, followed by cooling at 5°C for 1 h, 1 day, 3 days, or 5 days.2.4Solubilized starch of rice paste was quantified using a method modified from that described by Han and Hamaker . The hom2.5Cross sections of rice gels were observed using a scanning electron microscopy (SEM) . Freeze‐dried gel samples were fractured and mounted on a specimen holder and then coated with osmium and platinum before SEM observation. The obtained specimens were examined at an accelerating voltage of 5 kV.2.6Texture measurements of cooked rice grains and rice gels were performed using a texture analyzer  equipped with a 5‐kg load cell. For texture measurements on cooked rice grains, a compression test was performed using a cylindrical probe (35 mm diameter). After the cooked rice was maintained at 25°C or 75°C for 30 min, a single cooked rice grain was placed in the center of a base plate and uniaxially compressed by a probe at a constant rate of deformation (0.5 mm/s) to 90% of its original thickness. The forces required for 25% and 90% strains were used to compare surface hardness and overall hardness, respectively  was used to analyze the data. Analysis of variance and Tukey's studentized test were conducted at a 5% significance level.33.1Calculated protein, total starch, and apparent amylose contents, as well as the chain length distribution of amylopectin, are shown in Table 3.2The solubilized starch contents of pastes prepared from the seven cooked rice samples were 0.4%–19.7% 2× water), 0.8%–29.6% (3× water), and 1.0%–32.3% (4× water) . The apparent amylose content was significantly correlated with the compressive force at 25% strain for cooked rice maintained at 75°C . The influences of starch characteristics on textural properties of cooked rice grains have been reported elsewhere. Li, Prakash, Nicholson, Fitzgerald, and Gilbert , but no significant correlation was otherwise observed.The relationship between the hardness of cooked rice grains and rice gel hardness was estimated. The surface hardness of cooked rice grains maintained at 75°C was significantly correlated with the compressive force of rice gels prepared from cooked rice maintained at 75°C on day 0  was found to be negatively correlated with the hardness of rice gels on days 1, 3, and 5 under various preparation conditions. The rice sample temperature before homogenization significantly influenced the compressive force and breaking force of rice gels. The rice gels from cooked rice maintained at 75°C prior to homogenization showed a higher compressive force and breaking force than those from cooked rice maintained at 25°C for almost all of samples. Observations using SEM showed that the cooked rice maintained at 75°C formed a more fibrous and denser structure following homogenization than that maintained at 25°C. The surface of cooked rice grains maintained at 75°C was softer than those maintained at 25°C for almost all. This implies that the softer texture of the cooked rice surface at 75°C may allow the grains to be homogenized more easily, which may contribute to a finer gel network, resulting in the reinforcement and rigidity of the gel structure. These results suggest that the gel network formed in the process of high‐speed shear homogenization had a considerable impact on gel hardness compared to rice flour gel and the optimal combination of rice cultivar, water content, and sample temperature could form rice gels with a wide range of hardness for a variety of applications.The authors declare that they do not have any conflict of interest.This study does not involve any human or animal testing.


Thermoplastic starch (TPS) films are considered one of the most promising alternatives for replacing synthetic polymers in the packaging field due to the starch biodegradability, low cost, and abundant availability. However, starch granule composition, expressed in terms of amylose content and phosphate monoesters, and molecular weight of starch clearly affects some film properties. In this contribution, biodegradable TPS films made from potato, corn, wheat, and rice starch were prepared using the casting technique. The effect of the grain structure of each starch on microstructure, transparency, hydration properties, crystallinity, and mechanical properties of the films, was evaluated. Potato starch films were the most transparent and corn starch films the most opaque. All the films had homogeneous internal structures—highly amorphous and with no pores, both of which point to a good starch gelatinization process. The maximum tensile strength (4.48–8.14 MPa), elongation at break (35.41–100.34%), and Young’s modulus (116.42–294.98 MPa) of the TPS films were clearly influenced by the amylose content, molecular weight, and crystallinity of the film. In this respect, wheat and corn starch films, are the most resistant and least stretchable, while rice starch films are the most extensible but least resistant. These findings show that all the studied starches can be considered suitable for manufacturing resistant and flexible films with similar properties to those of synthetic low-density polyethylene (LDPE), by a simple and environmentally-friendly process.  Hydrogen bonds hold the starch chains together, making it insoluble in cold water. In order to obtain a TPS film, starch granules must be gelatinized with a plasticizer in an excess of water at temperatures lower than 100 °C. Commonly used plasticizers are monosaccharides, disaccharides, oligosaccharides , and polyols . In this way, hydrogen bonds are formed between the plasticizer and the starch in an irreversible gelatinization process. Approximately 40% of food packaging is made of plastic materials . During Starch can be obtained from a great variety of botanical species, which determines the compound’s grain size, size distribution, shape, amylose/amylopectin ratio, molecular weight, and phosphate monoester content. Corn, wheat, potato, and rice starch are the most common starch sources, representing 84%, 7%, 4%, and 1% of world production, respectively . The staThe aim of this work has been to produce biodegradable TPS films from four different starch sources  by the casting technique, using glycerol as plasticizer (33 wt % on starch basis) and to compare their properties. Three sub-objectives are proposed: (i) to characterize the starch grains in terms of their molecular weight, microstructure, size distribution, amylose, phosphate monoester contents, and humidity; (ii) to characterize the TPS films in terms of their hydration properties, migration into food simulants, microstructure, crystallinity, and tensile properties; and (iii) when possible, to establish possible relationships between the starch granule composition and molecular weight of each starch and the subsequent film properties.Corn starch , wheat starch  and rice starch  were purchased from Sigma-Aldrich . Potato starch  was provided by Across Organics , and the plasticizer glycerol was supplied by Fisher Chemical . All chemicals were used without further purification.The morphology and particle size of the four starches were determined by Scanning Electron Microscopy (SEM) and laser diffraction. The shape of the starch grains was observed by SEM  with an accelerating potential of 15 kV. The particle size analysis was carried out by laser diffraction . The Megazyme amylose/amylopectin assay procedure, using the commercial kit, was followed to quantify the amylose content of the starches. Determining phosphorus content was conducted with an inductively coupled plasma mass spectrometer . Gel Permeation Chromatography (GPC) coupled with Multi Angle Light Scattering (MALS) was used to determine the weight-average molecular weight of the starches. A Size-exclusion Chromatographer  with double detection (MALS and refractive index) was employed. The mobile phase was DMSO with 0.1 M LiCl. A certain amount of each sample (≈20 mg) was exactly weighed and added to a defined volume of mobile phase. After that, the samples were dissolved at 80 °C. All solutions were filtered through a 1 µm filter before being injected into the GPC precolumn  and analytical column . The column temperature was controlled at 80 °C and the flow rate was 0.3 mL/min. The weight-average molecular weight of the starch samples was calculated using the WinGPC UniChrom software version 8.3 .The moisture content of the starches was determined by their loss of weight after drying in an oven for 5 h at 110 °C. Crystallinity of the starch grains was studied by X-ray diffraction on a Bruker diffractometer  equipped with a KRISTALLOFLEX K 760-80F X-ray generator  which has an X-ray tube with copper anode (λ = 1.54056 Å). The equipment operated at 40 kV and 40 mA with 2θ varying from 10° to 60° with a step size of 0.05°.2). The plates were dried in an oven with circulating air at 50 °C for 48 h. The dried films were peeled off and stored at room conditions (around 25 °C and 50% relative humidity) for a week before characterization. Starch films were prepared by the casting technique following the procedure described by Medina-Jaramillo et al. . BrieflyFilm thickness was measured in different locations with a Palmer Electronic digital micrometer . The mean value was calculated and used for the rest of the calculations. 2 following procedures described in the literature with some modifications [m0 and m1 are the mass before and after drying, respectively.The water content and solubility in water of the films were determined with samples of 1 × 1 cmications ,11. Firsfm. Water solubility was calculated from the loss of total soluble matter as follows (Equation (2)):After that, the water solubility of the samples was measured by placing the above dried films individually in 10 mL tubes filled with 9 mL of distilled water. The tubes were capped and stored at 25 °C for 24 h, after which the films were taken out and dried again at 110 °C for 5 h in order to determine the final mass of dry matter, The solubility values were taken as the average of at least four repetitions.v/v, simulating hydrophilic foods); simulant B, acetic acid ; and simulant C, isooctane (simulating lipophilic foods with free fats at the surface). Film samples were immersed in 9 mL of the simulants with a contact ratio of 6 dm2 of film per kg of simulant. In accordance with Test number OM1, the films were left in contact with the food simulants for 10 days at 20 °C, after which the samples were withdrawn, dried and weighed. The difference between the initial and final weight corresponds to the mg of the film components released/dm2 of contact surface. The tests were run in quadruplicate.Migration studies were carried out following the current legislation . The simx is the thickness (expressed in mm) of the film and 600Abs is the absorbance measured at 600 nm. Lower values of the opacity parameter, as defined on Equation (1), imply greater transparency.The transparency (in terms of opacity) of the films was determined using a basic VIS V-1200 spectrophotometer  at a wavelength of 600 nm following the procedure used by other researchers [The microstructure of the films was observed from SEM images obtained with a Hitachi Scanning Electron Microscope  using an accelerating voltage of 5 kV. The images were taken on the surface and in cross sections of all the studied films. Dried sheet samples were cryofractured after immersion in liquid nitrogen. Before the analysis, the samples were coated with gold for better observation.Film surfaces were also analyzed by an NT-DMT Atomic Force Microscope  operating in tapping mode. The images were processed using the software Nova Px  and three-dimensional images of the film surfaces (10 µm × 10 µm) were obtained. The mechanical tensile properties of the films were determined with an Instron 3344 Universal Test instrument  equipped with 2000 N load cell and operated at 25 mm/min following ASTM D882-12 (2012)  standardFilm diffractograms were recorded on a Bruker diffractometer  equipped with a KRISTALLOFLEX K 760-80F X-ray generator. The equipment operated at 40 kV and 40 mA, with 2θ varying from 10° to 60° with a step size of 0.05°. The FITYK software  was used for curve fitting. Starch granule size was determined by laser diffraction and the results are shown on The amylose content of the starches was similar for all the starches although with slight differences. These differences could have certain influence on the different properties obtained for the films, as it will be discussed later. In order, the amylose content of the starches was the following: rice 16.9%) < potato (20.5%) < wheat (24.5%) ≈ corn (24.8%). The literature reports considerable discrepancies in the amylose content of starches, mainly due to the exact botanical origin of each starch and the determination method. Nevertheless, the amylose content of the starches we recorded and the values presented in the literature were in good agreement % < potat,18,19.Introduction Section, amylose is a linear polysaccharide with an average molecular mass of 105 g·mol−1 and amylopectin is a branched polysaccharide with an average molecular mass of 106–107 g·mol−1. For this reason, starches with high amylose content could presumably have lower molecular weight and a relatively more linear structure than those with a high content of amylopectin. In contrast to amylose content, the values of weight-average molecular weight of the studied starches have shown significant differences. We found that the molecular weight of rice starch is the highest reaching a value of 83.2 MDa. Potato starch presents an intermediate value (69.5 MDa) and corn and wheat starches have similar and the lowest values (≈51 MDa). The origin of these values could be in the molecular weight of the two macromolecular constituents of starch, amylose, and amylopectin. As stated in the Materials Section. In starch, the phosphorus is present in the form of phosphate monoester [The amount of phosphate monoesters contained in starch is usually very low and depends on plant origin. Generally, potato starch contains a higher phosphate monoester quantity than cereal starches ,21. As eonoester . TherefoWith respect to the moisture content of the starches (determined by a gravimetric method), the most hygroscopic starch was that obtained from potato, which reached values of around 15%, while the other starches showed similar values of around 9–11%. This difference could be related to the fact that potato starch is more phosphorylated and hence has a significant higher hydration capacity . All theThe degree of water solubility of biodegradable films made from water-sensitive biopolymers such as starch is a key parameter, and water solubility is closely related to biodegradability . Water iv/v (simulant A) simulated hydrophilic food, acetic acid 3% w/v (simulant B) acid hydrophilic food (pH under 4.5), and isooctane (simulant C) lipophilic food with free fats at the surface. The three simulants chosen present different polarities, and, in all cases migration. Hence solubility of the components was considerably greater when they were immersed in the hydrophilic simulants (simulants A and B). These results are in good agreement with above mentioned water solubility results since all the films were of a highly hydrophilic nature. Similar results were also obtained in a previous work on corn starch films [ch films . A compaTransparency is a key parameter for films since they are primarily used for food packaging, and a high degree of transparency is usually related to its acceptability as packaging material because of the better visual presentation of the food . HoweverSEM micrographs of the TPS matrix provide interesting information about the microstructure of the obtained films in terms of their homogeneity, layer structure, pores and cracks, and surface smoothness . SEM micz-axis. As expected from the SEM results, all films were very homogeneous without big granule structures. The presence of unplasticized starch in all the starch films was almost missing and the size of the isolated ghost granules observed was much lower than that of the starch grains, indicating the great capacity of glycerol to act as starch plasticizer. Even in the case of potato starch films, which showed a more pronounced presence of starch rests, these granules were less than 2% of the size of the native potato starch grains, pointing to a high degree of plasticization. The small amount of ghost granules observed by AFM could be responsible for the small crystalline diffraction peaks obtained by the XRD analyses, as will be discussed later.AFM helps to understand the surface morphology and homogeneity of films by means of a topographic study based on the atomic interaction between constituents . This teXRD was used to investigate the crystal structure of the films obtained. The crystalline organization of native starch was seen to be strongly influenced by its botanical origin. Cereal starches such as corn, wheat, or rice starch, typically present an A-type crystal structure, while a B-type structure is characteristic of tuber starches such as potato starch ,35,36. FA loss of crystallinity was expected after the plasticization process to obtain starch films due to disruption of the intermolecular hydrogen bonding between starch molecules by the glycerol molecules, which increases the chain mobility of the starch molecules . A compaallinity . Comparing the XRD spectra of corn, wheat, and rice starch films  leads usIn the case of the potato starch film (the only one obtained from a tuber), the films presented an intermediate crystalline structure between rice starch films and those made from corn and wheat starch with undefined broad peaks. This is probably due to potato starch having an intermediate molecular weight and amylose content. In addition, as it was previously mentioned, potato starch contains the highest percent of phosphate monoesters. This could also contribute to the more amorphous nature of potato starch films compared to corn and wheat starch films. Phosphate monoesters are charged groups, which can hinder the starch rearrangement during starch film preparation reducing the ordered or crystal structures of potato starch films. This corroborates the mechanical properties observed for the potato starch films, which are less resistant and more stretchable than corn and wheat starch films, and more resistant and less extensible than rice starch films. Determining the tensile properties of biodegradable films is necessary to confirm their suitability for future applications, for example, in the food packaging field. These properties can be affected by molecular weight and amylose content of starch, film thickness, polymer chain packing, chain interaction, and crystallinity of the film ,47. ValuStarch films from four botanical sources were prepared by the casting technique. The starch granule composition and molecular weight were seen to have a significant influence on several physical and chemical properties of the films developed. The amylose content and molecular weight of the starches strongly affected the mechanical properties of the films, which were more resistant and less extensible when their amylose content and molecular weight were higher and lower, respectively. This is probably due to the fact that the films obtained from starches with a high amylose content usually present a higher quantity of crystalline domains, which are presumably responsible for improving the mechanical behavior of the TPS films. The analysis of the mechanical properties measured reveals that all the films have properties comparable to those of some conventional polymers such as LDPE, underlining the great potential of starch to replace synthetic and non-biodegradable plastics in film manufacturing.


Notably, the midtarsal joint quasi-stiffness during DF was ~2.5 times higher than that of the ankle joint. The increase in midtarsal quasi-stiffness when walking with added mass could not be explained by the windlass mechanism, as the ROM of the metatarsophalangeal joints was not correlated with midtarsal joint quasi-stiffness . The likely source for the quasi-stiffness modulation may be from active foot muscles, however, future research is needed to confirm which anatomical structures (passive or active) contribute to the overall joint quasi-stiffness across locomotor tasks.Examination of how the ankle and midtarsal joints modulate stiffness in response to increased force demand will aid understanding of overall limb function and inform the development of bio-inspired assistive and robotic devices. The purpose of this study is to identify how ankle and midtarsal joint quasi-stiffness are affected by added body mass during over-ground walking. Healthy participants walked barefoot over-ground at 1.25 m/s wearing a weighted vest with 0%, 15% and 30% additional body mass. The effect of added mass was investigated on ankle and midtarsal joint range of motion (ROM), peak moment and quasi-stiffness. Joint quasi-stiffness was broken into two phases, dorsiflexion (DF) and plantarflexion (PF), representing approximately linear regions of their moment-angle curve. Added mass significantly increased ankle joint quasi-stiffness in DF ( Humans dynamically alter the stiffness of their limbs in response to environmental and functional demands. Leg stiffness is modulated during locomotion to control multiple important biomechanical factors including: center of mass excursion when stepping between surfaces of differing compliance , resistaThe ankle/foot complex performs multiple functional roles during gait, including support of body weight , acting Quasi-stiffness of the ankle  is defined as the slope of the joints’ moment-angle relationship . This isSince the ankle accounts for a large proportion of total leg stiffness behavior during hopping , and theThere are a limited number of studies which have investigated the quasi-stiffness of joints within the foot during locomotion, despite its potentially large influence on ankle behavior. During human walking, There are several factors which may modulate midtarsal quasi-stiffness including the windlass mechanism, variations in foot structure (standing arch height) and utilization of intrinsic foot muscles. The windlass mechanism operates when the plantar fascia wraps around the head of the metatarsal bones and is tensioned by extension of the MTP joint . This alThe purpose of this study was to quantify the effect of increased body mass on the quasi-stiffness of the ankle and midtarsal joints during walking. The challenge of increased body mass was selected to directly increase the forces experienced by the foot and ankle , which mA total of 21 participants  were recruited under the oversight of the University of Nebraska Medical Center Institutional Review Board (# 757-16-EP). All subjects gave written consent to participate in this study. All participants were healthy , with no history of impaired mobility. Individuals who were pregnant, had lower extremity pain, injury or surgery within the last year were excluded from this study. Medical history and impairment were assessed through the use of a medical history questionnaire.Subjects walked over-ground while wearing three different levels of added mass: 0%, 15% and 30% of body mass. Subjects walked barefoot at 1.25 m/s in a straight line for ~10 m. Mass was added to subjects using a vest, which was loaded with 2.5 kg metal weights equally distributed medial-laterally and anterior-posteriorly. Targeted walking velocity was ensured using an optical timing system  where only trials which had an average velocity within 1.20 and 1.30 m/s were accepted. Trials with differing levels of body mass were conducted in a randomized order to minimize any potential bias caused by fatigue or acclimatization to the protocol.Foot and ankle kinematics were recorded using an 8-camera motion capture setup  captured at 180 Hz. A set of 53 retro-reflective markers were positioned on the subjects’ lower extremities. The shank, hindfoot, forefoot and hallux segments were identified bi-laterally using a marker set defined previously published multi-segment foot model . 2012b. Following collection, data was processed using Visual3D software  where data was smoothed using a second order dual-pass low-pass Butterworth filter at 6 Hz for kinematic data and 25 Hz for kinetic data.Moments about the midtarsal and ankle joints were quantified by computing the cross product of the ground reaction force with a vector from the joint center to the COP of that limb. This method was chosen over inverse dynamics because as many as three foot segments were simultaneously contacting the force plate. In the midtarsal joint, joint moment was computed only when the COP was anterior to the joint center, and zero moment was assumed when COP was posterior to the midtarsal joint center . MTP joiJoint moment data  and angle data were processed into quasi-stiffness values using a custom script written in MATLAB . This script identifies two functional phases within stance, dorsiflexion (DF) and plantarflexion (PF). DF phase spans from the instant of peak PF to peak DF in the ankle joint. As midtarsal joint moment was assumed to be zero until the joint COP was anterior to the joint center, DF phase in the midtarsal joint began when a non-zero joint moment was present. PF phase spans from peak DF to toe off at both the ankle and midtarsal joints. Quasi-stiffness was quantified by the slope of the moment-angle curve  of both https://jasp-stats.org/). All kinetic variables (quasi-stiffness and moment) were normalized to the body mass of each subject at the 0% added mass condition. All study results were examined for sphericity using a test of Mauchly’s W. If a significant deviation from sphericity was found, a Greenhouse–Geisser correction was performed. If a main effect was found, pairwise comparisons were performed using a Holm–Bonferroni post hoc test.Quasi-stiffness of the ankle and midtarsal joints were computed for each subject using the average moment-angle curve of all trials for each weight condition . There were between four and eight valid trials remaining for each subject and each condition after eliminating trials with errors in marker tracking (large gaps in foot marker positions during stance), walking speed, or force plate contact. A one-way repeated measures ANOVA was utilized to examine the effects of added body mass to changes in quasi-stiffness, range of motion (ROM) and peak moment in the ankle and midtarsal joints using JASP software  = 0.822, p = 0.447) on ankle ROM . However, peak PF moment  significantly increased with added mass  = 279.1, p < 0.001) (p < 0.001). Similarly, it was found that added mass significantly increased joint quasi-stiffness, during both the DF  = 33.27, p < 0.001),  and PF  = 21.48, p < 0.001),  phases (p ≤ 0.013 and p ≤ 0.018) between all weight conditions (The added mass condition displayed no significant effect (< 0.001) . Post ho) phases . During nditions .F = 1.335, p = 0.275) on midtarsal ROM . There was, however, a significant increase  = 256.3, p < 0.001) on peak PF moment  (p < 0.001). Added mass had a significant effect on joint quasi-stiffness in the DF phase  = 5.742, p = 0.006),  as well as PF phase  = 15.24, p < 0.001),  in midtarsal quasi-stiffness (p = 0.040) and 0–30% (p = 0.006) conditions. During the PF phase, post hoc analysis revealed a significant difference only between the 0–15% (p = 0.006) and 0–30% (p < 0.001) conditions (The added mass condition displayed no significant effect (n ± std) . Post hotiffness . During nditions .r = 0.181, p = 0.431) was found between MTP joint ROM and midtarsal joint stiffness at 0% added mass during midtarsal joint DF. Similarly, no correlation was found between change (30–0% added mass) in MTP ROM, and change in midtarsal DF  stiffness  was found between MTP joint ROM and midtarsal joint stiffness at 0% added mass during midtarsal joint PF. No correlation was found between change (30–0% added mass) in MTP ROM, and change in midtarsal PF  stiffness  or PF  phases (No correlation (tiffness . No corrtiffness . No sign) phases .The overall goal of this study was to explore the effect of added body mass on ankle and midtarsal joint quasi-stiffness during walking. Our hypothesis that ankle quasi-stiffness increases with added mass was supported in both DF and PF phases. Our hypothesis that midtarsal quasi-stiffness increases with added mass was also supported in the DF and PF phases. These findings support the mounting evidence that biological limbs can modulate stiffness in response to varying locomotor demands .The moment produced at the ankle and midtarsal joints increased with added mass, but their ROM did not increase correspondingly, which is consistent with the overall trend of a stiffer joint and in agreement with our hypothesis. Overall, there appeared to be little change in either the foot or ankle kinematics with added mass. This is supported by other work which has found little change in ankle kinematics when walking with added mass distributed about the center of mass  and loadMidtarsal quasi-stiffness during the DF (mean quasi-stiffness of 0.23 ± 0.10 Nm/kg° for 0% added body mass) phase was substantially higher than that seen in the ankle or in the midtarsal joint during PF (mean quasi-stiffness of 0.093 ± 0.024 Nm/kg° for 0% added body mass). Although a precise mechanistic understanding for elevated midtarsal quasi-stiffness remains unclear, the values obtained in this study are in agreement with those conducted elsewhere. Midtarsal joint quasi-stiffness during DF had high subject-to-subject and within-subject variability when compared to the ankle joint or to the midtarsal joint during PF. It is possible that the methodology used to compute midtarsal moment (assuming zero joint moment until the COP is anterior to the joint center) underestimated joint moments early in stance and biased results toward higher stiffness values. It seems unlikely however that this result caused a large effect on the overall results of the study, as a recent analysis has shown that only low magnitude joint moments are missed with this assumption . There aOur secondary analysis examined the influence of standing midtarsal joint angle (used as a surrogate measure for standing arch height) on variability of the midtarsal quasi-stiffness. No significant correlation was found between standing midtarsal angle and midtarsal quasi-stiffness in DF or PF. This indicates that standing arch height did not play a major role in the midtarsal quasi-stiffness variability seen in this study. While this disagrees with previous work which has shown a relationship between arch height, leg stiffness  and dynaUtilization of the windlass mechanism was evaluated as an explanatory factor for the variability seen in midtarsal quasi-stiffness during the DF. We found no correlation between MTP joint ROM and midtarsal joint quasi-stiffness at 0% added body mass, and no correlation between change in MTP joint ROM and change in midtarsal joint quasi-stiffness (30–0% added mass). These findings suggest that utilization of the windlass mechanism did not account for between-subject variability, and did not explain increased midtarsal joint quasi-stiffness when walking with added mass. Our findings are in agreement with a recent study involving an isolated arch compression test, which showed that MTP joint DF did not increase overall arch stiffness .A potential explanation for the increased midtarsal joint quasi-stiffness when walking with added mass may be activation of the foot muscles. Although electromyography was not collected in this study, recent studies have provided evidence that midtarsal mechanical behavior is influenced by activation of intrinsic foot muscles   in whichThe range of added body mass that was tested on subjects may have been insufficient to trigger the full spectrum of possible changes seen in the foot and ankle. This study was conducted as a part of a larger study investigating foot mechanics and foot temperature. Therefore, additional trials were conducted either before or after collection of this data based on randomization of that specific subject. It is possible that fatigue or adaptation to the weight vest from that previous walking section may have confounded our results on a subset of subjects. However, given that prior trials were only three 10 min treadmill walking sessions, each separated by 30 min of rest, it seems unlikely that this would be a significant influence in a healthy young population.This study sought to identify how ankle and midtarsal quasi-stiffness is influenced when healthy individuals walk with added mass. In general, it was found that ankle and midtarsal joint quasi-stiffness increases with added mass. Of particular importance was midtarsal joint DF, which has much higher quasi-stiffness than the ankle joint or the midtarsal joint during PF, and displayed large between- and within-subject variability. No significant relationship was found between utilization of the windlass mechanism (MTP joint ROM) and midtarsal joint quasi-stiffness, suggesting that factors outside of those measured  in this study are important to overall joint stiffness. These findings are critical for improving our understanding of how the foot and ankle behaves during walking, running, load carriage and other physiologically realistic conditions, and for uncovering unique mechanical behavior of the foot and ankle. In addition, these data are useful in the design of biologically inspired prosthetic devices, which can replicate function of native joints across a wide variety of tasks of daily living.10.7717/peerj.7487/supp-1Supplemental Information 1Ankle and midtarsal range of motion, peak moment and stiffness and time series of normalized moment and angle.Click here for additional data file.


By adding crosslinkers, we obtained gels that are similar in stiffness to living brain tissue (150–1500 Pa). We further examined the capability of the gels serving as a substrate for stem cell culture and the effect of stiffness on neural lineage differentiation using human iPS cells. Surprisingly, exposure to gels with a stiffness of approximately 1500 Pa during the early period of neural induction promoted the production of dorsal cortical neurons. These findings suggest that brain-stiffness-mimicking gel has the potential to determine the terminal neural subtype. Taken together, the crosslinked tilapia collagen gel is expected to be useful in various reconstitution assays that can be used to explore the role of stiffness in neurogenesis and neural functions. The enhanced production of dorsal cortical neurons may also provide considerable advantages for neural regenerative applications.The mechanical properties of the extracellular microenvironment, including its stiffness, play a crucial role in stem cell fate determination. Although previous studies have demonstrated that the developing brain exhibits spatiotemporal diversity in stiffness, it remains unclear how stiffness regulates stem cell fate towards specific neural lineages. Here, we established a culture substrate that reproduces the stiffness of brain tissue using tilapia collagen for  Among these mechanical properties, the effect of extracellular stiffness on stem cell fate decisions has been intensively analyzed6. A number of studies have determined the range of tissue stiffness in muscle (104 Pa), connective tissue (104 Pa), skin (104 to 105 Pa) and bone (109 to 1010 Pa)9. Notably, brain tissue showed lower stiffness, ranging from 102 to 103 Pa14. Despite these findings, little is known about how tissue stiffness affects the determination of stem cell fate towards specific cellular subtypes either in vitro or in vivo.Determination of the fate of pluripotent stem cells and their development into functional cells is one of the crucial issues in the fields of developmental biology and regenerative medicine. Accumulating evidence demonstrates that biochemical factors, including exogenous gene transfer, regulate the fate determination of stem cells. Recent studies have also revealed the importance of the mechanical properties of the extracellular environment as a trigger of fate determination 13. Brain stiffness changes spatiotemporally throughout the embryonic stages during which neurogenesis from neural stem cells and construction of the brain architecture mostly occur. Accordingly, a fundamental question arises of whether neural lineage choice, including neural induction and differentiation, is influenced by differences in brain tissue stiffness. To address this question, it is essential to reproduce the stiffness conditions of living brain tissue in vitro. Several research groups have utilized polyacrylamide (PAA)-based hydrogels as a culture substrate to provide a wide range of stiffness18. However, it has proven technically demanding to consistently reproduce a substrate with a stiffness close to that of brain due to the relative softness14. Furthermore, acrylamide has been shown to be toxic to neurons19.We previously reported the systematic analysis of living brain tissue stiffness during developmentOreochromis niloticus) skin because the use of fish collagen rather than collagen of mammalian origin is expected to reduce the possibility of the transmission of animal diseases to humans (“zoonosis”)20. Although acid-soluble collagen molecules self-assemble into fibrils under physiological conditions, the stiffness of gels consisting of such fibrils can be controlled by chemical modification. 1-ethyl-3-(3-dimethylaminopropyl)-carbodiimide (EDC) is a commonly used crosslinking reagent for biomaterials, and N-hydroxysuccinimide (NHS) can enhance crosslinking between collagen fibers in the presence of EDC25. Here, we identified an effective combination of EDC and NHS that produces a consistently softer range of collagen gel that mimics brain tissue, the stiffness of which ranges from approximately 150 Pa close to the cortical plate13 to 1500 Pa close to the apical surface14. Notably, the chemically crosslinked collagen gel contained triple-helical structures that may provide a scaffold for integrin signaling. Furthermore, the gel showed high transparency, and its surface appeared almost flattened compared to fibril-formed collagen gels.To overcome these difficulties, here we applied collagen as a material to produce a culture substrate mimicking the stiffness of brain tissue. Collagen is a major component of connective tissue in living tissue and can be easily extracted from various animals by acid solubilization. We selected collagen extracted from tilapia . HiPSCs cultured on gels showed impaired pluripotency and entered the neural lineage in a manner similar to cells cultured on plastic dishes. To our surprise, the neural characteristics acquired after 5 days of neural induction on a gel with a stiffness of 1500 Pa significantly switched to the lineage of dorsal forebrain neurons. These results demonstrate that the tilapia collagen gel established here can be utilized for neural induction from pluripotent cells and that exposure to gels of a particular stiffness during the initial stage of neural induction can determine the direction of differentiation towards a specific neural lineage.28. The molecular weights of the polypeptides present in extracted tilapia skin collagen fell within this range. The band pattern resembled that produced by commercially available type I collagen extracted from tilapia scales and porcine tendon  as shown in Fig. G′ increased up to 496 ± 6 Pa at 100 mM EDC depending on the EDC concentration .The gel stiffness was defined by the storage modulus of the gel  with a linear strain condition. We found that the G″, indicating viscosity of gels, was maintained lower than G′ during measurement in all the conditions with the exception of EDC 10 mM  in an accurately adjustable manner.In further analysis of the characteristics of collagen in gels, we focused on the behavior of collagen molecules during gelation. First, we investigated the interaction between collagen fibers during gelation by monitoring the turbidity of the collagen solution at 310 nm Fig. . In fibr0.1 and [EDC 100 mM]0.1, respectively)  spectrum of the gel material to determine whether a collagen triple helix was present in the gels. We used four representative conditions for CD spectral analysis at 20 °C and 37 °C: 0.3 wt% tilapia collagen solution (pH 3.0), fibril-formed physical collagen gels, and chemically crosslinked collagen gels prepared with 22 and 100 mM EDC ([EDC 22 mM]ly) Fig. . A positly) Fig. . The pature Fig. . The wav16. Here, we addressed whether tilapia collagen gels that mimic brain stiffness have an effect on the differentiation of pluripotent stem cells. HiPSCs were maintained in plastic dishes without feeder cells to avoid the stiffness effect of feeder-derived matrices35. Subsequently, hiPSC-colonies were enzymatically dissociated into single-cell suspensions and seeded at equal densities for passaging either on plastic dishes or on chemically crosslinked gels; the medium was then changed to a neural differentiation medium that has been reported to result in a high rate of production of dorsal cortical neurons36. For hiPS cell-line, we chose RPChiPS771-2 because of the higher production rate of dorsal cortical neurons in our culture condition  and [EDC 100 mM]0.1 (1487 ± 62 Pa); these were defined as “SOFT” and “HARD”, respectively. HiPSCs did not grow on gels, plastic dishes or coverslips without coatings. Therefore, we tested several coating materials and chose Vitronectin XF because it provided sufficient cellular adhesion on all substrates used in this study  assayips Fig. . After tips Fig. . RT-PCR ips Fig. .Figure 6Next, we investigated the expression level of pluripotent markers during neural induction of hiPSCs on gels. Neural induction was initiated 2 days after passaging, which is defined as “Day 0” Fig. . SSEA-4,The effect of stiffness on early neural induction was investigated using PAX6 as a marker of cortical neural stem cells Fig. . Immunoc4 45 were similar in all conditions 49, and an astrocyte marker (GFAP)50, were not significantly different among the tested conditions , as well as different seeding cell densities  of fish collagen, which results in the dissolution of collagen fibrils under human physiological conditions, has been a limitation in its use as a biomaterial56. In contrast, tilapia skin collagen, likely because of its tropical origin, has a higher Td28 that is quite close to the physiological temperature of the human body. Moreover, our CD spectrum analysis  = 0.1 is suitable for producing gels with a stiffness of 150–1500 Pa with high reproducibility. This range of stiffness is similar to the range of stiffness measured in the developing14 and adult brain12. This result suggests that the stiffness of living brain tissue can be reproduced in vitro using tilapia collagen. In contrast, this range of stiffness would not be suitable for the culture of other cell types, which naturally grow under much stiffer conditions such as those found in muscle and bone2. However, we do not exclude the possibility of obtaining gels of greater stiffness by changing the concentrations of collagen and crosslinking reagents.Although collagen gels with a higher stiffness have previously been reported28. These results suggest that tilapia skin collagen can be used for gel formation in a manner similar to mammalian collagen. In general, monomeric collagen extracted from various species forms self-assembling fibrils under physiological conditions. Chemical modification promotes the interaction between monomeric collagen fibers during self-assembly33. Furthermore, the triple helical structure was maintained in crosslinked tilapia collagen gels . Previous studies using PAA gels and poly micropost arrays indicated that the production of PAX6- and TUJ1-positive cells from human pluripotent stem cells was enhanced under softer gel conditions (0.1 to 5 kPa)tex Fig. . Intrigutex Fig. . Remarkatex Fig. . ConsideG′ analysis during crosslinking indicated that tilapia collagen gels exhibit typical properties of elastic gels. Furthermore, SEM analysis indicated that crosslinked tilapia collagen gels have a topographical homogeneity of their surface regardless of the difference in stiffness  for 1 h. Subsequently, acid extraction was performed by soaking the tilapia skin in 3% CH3COOH for 3 days. The collagen solution was gently filtered through gauze and filtered 4 times over a 1-μm-pore filter . Salting-out and acid solubilization of the collagen were performed twice using 0.7 M saturated brine. For this, 0.7 M saturated brine was gently added to the filtered product, and the mixture was incubated for 4 h. After draining the water overnight, the products were cut into small pieces and soaked in 1.2% CH3COOH. The acidic mixture was stirred for 30 min. After salting-out twice, dialysis was performed. The extracted product was dissolved in 0.01% CH3COOH, and the collagen solution was placed in a dialysis membrane . Upon reaching pH 5.0, the inner liquid was replaced with HCl (pH 3.0). The product was sequentially filtered three times using 1-μm , 0.65-μm  and 0.45-μm  membrane filters. The final product was aliquoted and stored at −20 °C. To confirm the protein sequence of extracted collagen, MALDI-TOF/MS was performed. Details are described in Supplementary methods.Tilapia collagen was extracted from the frozen skin of the animals according to a previously reported procedureTilapia skin collagen was diluted into HCl solution (pH 3.0). To compare the components of collagen, similar amounts of porcine tendon (Nitta gelatin) and tilapia scale collagen (Taki Kagaku) were loaded on the same gels. Details are described in Supplementary methods.To obtain gels of various stiffnesses, 1-ethyl-3-(3-dimethylaminopropyl)-carbodiimide (EDC) (Dojindo), N-hydroxysuccinimide (NHS) (Wako) and NaCl solution (Sigma-Aldrich) were diluted into DW at various combinations of final concentrations as shown in Supplementary Tables For fibril formation, all procedures were performed on ice according to the manufacturer’s instructions (Nitta Gelatin). The tilapia collagen solution was mixed well with 10x concentrated DMEM/F12 (Sigma-Aldrich) by pipetting. Reconstruction buffer containing 50 mM sodium hydroxide, 260 mM sodium hydrogen carbonate and 200 mM HEPES was then added, and the components were gently mixed by pipetting. The ratio of components was 8:1:1 . The final concentration of collagen was 0.24 wt%.The bulk stiffness of the materials was measured using a rheometer (Thermo Fisher Scientific). Measurements were conducted using a parallel plate (35 mm diameter) at 37 °C for consistency with the cell culture conditions. The frequency-dependent storage and loss modulus were measured by applying 1 N of force 24 h after crosslinking. The time-dependent storage and loss modulus were measured immediately after mixing the collagen solution and crosslinker for 1 h. The values of the gap from the bottom of the dish at 1 N of force were defined as the “height” of the gel.22. First, the crosslinked collagen gels were freeze-dried. Four milligrams of freeze-dried gel was collected in a glass bottle, and 1 ml of NaHCO3 solution (4% w/v) and 0.5% TNBS solution (Thermo Fisher Scientific) was then added. The glass bottle was incubated in a water bath at 40 °C for 2 h. Then, 3 ml of 6 N HCl was added. The temperature of the water bath was increased to 60 °C, and the glass bottle was incubated for an additional 90 min. After the gel had dissolved completely, the reaction solution was diluted with 5 ml of DW, and 100 μl of the reaction solution was placed in each well of a 96-well plate. The absorbance of the solution at 345 nm was measured at room temperature (25 °C) using a photometer (Tecan). Collagen solution without crosslinking was used as a control.To evaluate the degree of crosslinking of the collagen, the free amine group content was measured following previous proceduresTo quantitate the turbidity of gels during crosslinking, the absorbance of the sample at 310 nm was measured using a photometer (Molecular Devices). Gels were prepared using the crosslinking and fibril-formation methods as described above. One hundred microliters of gel solution was placed in the well of a 96-well plate, and the plate was kept on ice prior to measurement. Measurement of turbidity was performed at room temperature. Turbidity was monitored continuously for 3600 sec at 30-sec intervals.61. The PEG-coated cover glass was then removed in PBS after the crosslinking reaction, and the formed collagen gels were washed thoroughly with PBS to remove the remaining crosslinking reagents. Finally, the collagen gels prepared on the quartz glass were covered with another quartz glass plate using a 30-μm-thick spacer . The collagen gel sample sandwiched between two pieces of quartz glass was placed in the optical path of a CD spectrometer , and the CD spectrum of the sample was measured.To determine whether the native triple helix of collagen was present in the gel samples, the circular dichroism (CD) spectra of fibril-formed physical collagen gels and chemically crosslinked collagen gels were measured. Because the gel samples were generally too concentrated to obtain clear CD spectra due to their strong absorption, the measurement was performed under conditions of reduced optical path length using a 30-μm-thick spacer between two pieces of quartz glass plate. For the physical gel sample, 20 μl of an aqueous solution of collagen  was placed between the two quartz glass plates. For the crosslinked gel sample, the collagen solution, EDC, and NHS were first mixed and placed between a standard cover glass and the quartz glass plates. The cover glass was pre-coated with polyethylene glycol 62, while RPChiPS771-2  were established by the self-replicative RNA reprogramming method63. Expansion and maintenance of hiPSCs were performed according to previously reported feeder-free culture methods for human pluripotent stem cells62 except that Vitronectin XF  was used for coating. Neural differentiation was performed as described previously36 with some modifications. Two days prior to differentiation, the cells were dissociated using 0.5x TrypLE Select ) and seeded at a density of 1× , 3× , or 6 × 104 cells per 35-mm dish on Vitronectin XF-coated gels or on glass coverslips in StemFit Basic02 medium (Ajinomoto). On day 0, the medium was replaced with recombinant human Noggin (R&D systems)-containing neural differentiation medium36. A medium change was performed every 2 days. For replate experiments, the cells were dissociated with 0.25% trypsin-EDTA on day 5 and replated on Vitronectin XF-coated 35-mm plastic dishes at a density of 2 × 105 cells per dish. After replate, the cells were cultured in Noggin-containing differentiation medium for 10 days; the medium was then changed to differentiation medium without Noggin for 4 days. Embryoid body (EB) formation assay37 is described in Supplementary methods.Use of human-derived material in the research is approved by the Research Ethics Committee of Korea Brain Research Institute (KBRI-201603-BR-001-01). Four different hiPSCs lines were tested to characterize the variance in the neural induction. Among them, 1231A3, 1383D2, and 1383D6  were established by the reprogramming method using episomal plasmidsTo measure the neural differentiation of hiPSCs, immunocytochemistry was performed. The fixed cells were incubated with primary antibodies and then with secondary antibodies. The information of antibodies is shown in Supplementary Table −∆∆Ct method. Details are shown in Supplementary methods.To determine the gene expression levels of hiPSCs cultured on gels, qRT-PCR was performed. Triplicate reactions were run for each biological sample using ABI7500fast (Life Technologies). The primer sequences are listed in Supplementary Table t-test was applied to compare two conditions  and one-way ANOVA and Tukey post hoc test was applied to compare three conditions at the same time points. Differences were considered significant for P < 0.05 (*), P < 0.01 (**), P < 0.001 (***). Error bars in graphs were represented as the mean ± SEM.Statistical analysis was performed using Prism version 4.0 (Graphpad Software). Two-tailed paired Supplementary Information