New approach for hair keratin characterization: Use of the confocal Raman spectroscopy to assess the effect of thermal stress on human hair fibre

Abstract Objective The objective of our research was to investigate the heat‐protecting effect of a product ex vivo and in vivo on human hair fibres. Methods A preparatory study was carried out in order to determine an optimal threshold of thermal stress. For this, the structure of cross‐sections of the hair fibre was observed by optical microscopy. Then, Scanning Electron Microscopy (SEM) and Confocal Raman Spectroscopy (CRS) were applied to analyse ex vivo and in vivo morphological and molecular damage in hair structure after heat stress. Finally, in vivo tests were used to collect consumer perception. Results The preparatory study enabled us to determine an optimal stress threshold of 10 heating cycle for SEM and 5 heating cycle for CRS. Based on spectral hierarchical classification using Ward's clustering algorithm, the ex vivo Raman results show that the spectral signature of the hair treated and heated is very close to the negative control. This shows that the product preserves the keratin structure after thermal stress. These results were also confirmed by an in vivo Raman analysis performed on hair samples from 5 donors. In concordance with Raman results, SEM shows that treated hair presents lesser “bubbles” and “crackling” on the hair surface. Finally, the in vivo studies proved that hair was more protected from heat. Conclusion The authors concluded that the product shows protective properties with respect to morphological and molecular heat damage. We also demonstrate that the product promotes the α‐helix keratin conformation and preserves the S‐S disulfide bands.

INTRODUCTION
The hair, like the skin, undergoes various internal and external aggressions. Among the external aggressions, we have the environmental factors but also the accumulation of numerous chemical or physical treatments [1] that attack and weaken the hair fibre. The use of heat styling appliances such as straighteners, curling irons and hair dryers is becoming more and more common. However, the temperature of these appliances can reach extremely high levels of heat and this heat stress causes long-term damage to unprotected hair, and this damage is cumulative. Moreover, this damage is not limited to the surface of the hair (depletion of the protective lipidic film, cracks in the cuticle and detachment of the scales) [2], it also damages the fibre in depth (evaporation of water and appearance of heat bubbles and degradation of keratin, a heat-sensitive protein) [3]. The hair then becomes rough, dry, dull and brittle with split ends.
The hair fibre is the visible part of the hair, it is made up of keratinized cells arranged in three layers: the cuticle, the cortex and the marrow. Human hair is mainly constituted of keratin: a hard and fibrous protein substance that gives the hair its strength and elasticity. It is made up of long chains of amino acids, including cysteine, rich in sulfur, which plays an important role in the cohesion of the hair. In fact, the keratin chains are sealed to each other by: 1. Disulfide bridges: stretched between two neighbouring cysteines, these bonds are very strong and are truly characteristic of the keratin structure. However, they are also the weak point of the hair structure because they are sensitive to attack. Cela montre que le produit préserve la structure de la kératine après un stress thermique. Ces résultats ont également été confirmés par une analyse Raman « in vivo » réalisée sur des échantillons de cheveux de 5 donneurs. En concordance avec les résultats Raman, la MEB montre que les cheveux traités présentent moins de « bulles » et de « craquelures » à la surface des cheveux. Enfin, l'étude in vivo a prouvé que les cheveux sont mieux protégés de la chaleur.
2. Weak bonds (salt bridges and hydrogen bonds): The keratin chains are organized into protofibrils, then into microfibrils which are themselves the constituents of the macrofibrils.
Several physical techniques have demonstrated the importance of hair analysis in different fields such as medical, environmental, cosmetic and forensic sciences. Some studies report the use of trichoscopy, x-ray diffraction, solid state nuclear magnetic resonance, circular dichroism, scanning electron microscopy and high-pressure liquid chromatography-mass spectrometry for human hair fibres analysis [4][5][6][7][8][9]. Although widely accepted, these methods lack accuracy and spatial resolution and they give only surface or structural information without any accurate molecular information. In addition, these techniques present some technical limitations related to protocol complexities, prior sample preparation, the need for extraction and reagent costs. These techniques are therefore not suitable for routine application in cosmetic laboratories [10].
Other spectroscopic techniques are finding their way into the cosmetic field and have been proposed for the investigation of human hair fibres. Both Fourier transform infrared (FTIR) and Raman spectroscopy have been extensively used to probe hair chemical composition and keratin structural changes under different treatments [11][12][13][14]. These powerful approaches represent analytical, nondestructive and dynamic methods to investigate changes in whole hair fibre with only little biomass and without any labeling or sample preparation or extraction. The FTIR and Raman spectra constitute very specific spectroscopic fingerprints which reflect the chemical composition and the structure of the hair fibres. This makes it possible to investigate the influence of chemical and physical treatments (active ingredient, reduction, heating, UV exposition and oxidation) on the structure of keratin in human hair fibres [12,13,15]. Previous research suggests that FTIR spectroscopy can be proposed, for example, for distinguishing hair follicle tissue layers based on their molecular structure, for discriminating untreated from treated hair, or also for monitoring the chemical changes related to the aging effect of human hair fibre [11,16]. In parallel, Raman spectroscopy has been used successfully to study L-Phenylalanine and hydrolyzed egg white protein penetration into keratin fibres, to detect the structural change in keratin after chemical treatments or more recently by our team to analyse conformation changes in human hair keratin after active ingredient application [10,14,16].
In the present study, the aim is to evaluate a thermoactive hair care product that protects the hair from heat, acting as a heat shield to preserve the fibre of heating devices. The use of hair irons at high temperatures in addition to hair dryers causes hair damage. The cuticles which make up the surfaces of hair are known to have "lift-ups" and to form "blisters" that are porous flares in hair caused by the heat treatment [2]. For this, we analyse the morphological and molecular changes incurred in the structure of hair samples after thermal treatments with a straightening iron at 235°C. Different methods have been investigated in order to assess the hair damage after the heat stress: (i) for morphological analysis, Scanning Electron Microscopy (SEM) has been used in order to examine the surface of hair fibres. (ii) Raman microspectroscopy to investigate, ex vivo and in vivo, the molecular thermal damages of keratin in human hair fibres by a direct confocal measurement and (iii) finally an in vivo test to collect the consumer perception combined with a hairdresser assessment about the efficiency. By comparing the information provided from those techniques, it will be possible to correlate keratin molecular changes with the morphological information and the structural integrity of the hair fibres as well as the consumer perception of their hair.

Human hair samples collection and treatment
Standardized hair tresses were provided by Kerling International (KERLING INTERNATIONAL HAARFABRIK GMBH; D-71522 Backnang -Waldrems Postfach 1330). These standardized tresses mean that the hair fibres were obtained from several donors and standardized according to the origin, colour, treatment and length. For the present study, the work was done with standardized stresses of European origin (several donors), 13 cm long and 2 mm large and shade 9/0 (blond) (reference Glued Hair Weft). In order to limit fluorescence interference during Raman measurements, we used natural light blond hair. The care product was applied at 10% of the tresses weight for 5 min (mean weight of tresses: 336 ± 13 mg; mean quantity of test product applied: 34 ± 2 mg). The tresses received the application of heat directly from the straightening iron at 235°C over the entire length of the hair shaft. Five or 10 cycles of the heating process were done (one cycle is equivalent to 5 s of heating at 235°C followed by 15 s of cooling at room temperature). In this work, a flat iron model Babyliss i-pro 235 ionic XL Wet&Dry was used.

Preparatory study
A study of a wide range of deterioration with heat was initially studied. Different heating cycles (0, 5 and 10) were applied to hair fibres in order to reveal the conditions allowing visualization of molecular changes without harmful effects on hair fibre morphology.
In the first step, the cross sections of the hair fibres were carried out after applying different heating cycles. In order to evaluate the degree of deterioration of the hair fibre after heat stress and to choose an optimal stress threshold to conduct the study, a comparison of the hair sections was carried out by an optical microscope with a 100× objective. For this, Optimal Cutting Temperature (OCT) compound was used to embed hair samples prior to frozen sectioning on a cryostat (−20°C). After the heating cycles, the hair samples become brittle and break easily. For this, they must be handled and included gently in the OCT to avoid morphological deformations and curvatures. After rapid freezing at −80°C, 10 μmthick transverse sections were cut by cryostat, and three sections per sample were placed onto CaF2 slides for optical microscope analysis. These observations were also correlated with the images observed with SEM in order to choose the degree of heat stress to be applied in the study. For this purpose, hair fibres after (0, 5, and 10) heating cycles were observed with SEM for evaluation of morphological changes after heat stress.

Scanning electron microscopy observation
Hair tresses were shampooed (with a classic lauryl sulfate based shampoo) in order to eliminate residues on hair before SEM observations as following procedure: Tresses were wet with tap water. Excess water was removed with gloved fingers. The shampoo was then deposed onto the hair tresses and 20 rotations over the entire length of the tresses were done until foaming. Finally, hair tresses were rinsed before ambient air drying. Several hair fibres per case were observed (at least 4 per case). The morphology of hair samples after thermal treatment was examined by a scanning electron microscope (MEB-FEG ZEISS GeminiSEM 300). The samples were placed on specimen mounts using double-sided adhesive tape and were made electrically conductive by coating them with a thin layer (2 nm) of gold (Agar manual Sputter Coater). The pictures were taken at a working distance (WD) between 6.2 and 6.5 mm and EHT (Electron High Tension) between 2 and 8 kV.

Raman spectrometer
Raman spectral acquisitions of hair samples were recorded using a Labram microspectrometer (Horiba Jobin Yvon). The set-up included a microscope (Olympus, BX41) equipped with a computer-controlled motorized x-y stage, which enabled automatic scanning of the sample with a spatial resolution of 1 μm. Raman measurements were recorded by using a dispersive Raman spectrograph (Labram, Horiba Jobin Yvon) via a 100× (0.8 N.A) long working distance objective (Olympus) operating in air. The objective was mounted on a highprecision piezoelectric device (Physics instrument, Germany) which allowed focusing the laser light on each measuring point of the hair sample. This objective collected light that was scattered by the sample, which was then detected by a charge-coupled device (CCD) detector of 1024 × 256 elements cooled by Peltier effect at −65°C. The spectrometer comprises also a grating of 950 grooves/mm permitted to collect data with a spectral resolution of 4 cm −1 . The confocal hole was set at 150 μm, assuring an axial resolution of approximately 2 μm.
The excitation source was provided by titaniumsapphire laser (Model 3900S, Spectra-Physics, France) generating a laser beam with a 785 nm wavelength and operating at 50 mW under the microscope objective, which is non-destructive for hair samples and does not cause any thermal or photochemical degradation. The laser wavelength excitation was chosen as the optimal compromise to ensure the reduction of parasitic fluorescence generation, good penetration of the light deep into the hair samples and sensitivity of the CCD detector over the spectral range.

Confocal measurements (Z) on hair fibres
The axial Z profiles were recorded directly on a hair fibre for each sample and without any particular preparation.
For the choice of the mapping (Z) profile, we visualized the hair fibre with 3 objectives (10×, 50× and 100×) of the camera microscope ( Figure 1).
The mapping (Z) profiles consist of an in-depth scanning through the hair fibre. Raman spectra were collected at different focus points, from the surface Z = 0 μm to 30 μm with a 3 μm step. The spectral acquisitions were recorded on the 400-4000 cm −1 spectral range at different focus points, taking into consideration the cortex and the cuticle of the fibres in each measurement. Figure 2 shows the spectra corresponding to each depth of the hair fibre up to 30 μm and with a step of 3 μm. The areas under the curve (AUC) of the full spectrum for each depth are displayed in this figure.
For each spectrum, one accumulation of 50 s of laser exposure was taken. Data acquisition was performed using LabSpec 5 software (Horiba Jobin Yvon). Prior to data acquisition, the instrument was calibrated to the 520.7 cm −1 Raman line of silicon and the laser power at the sample level was regularly controlled.

Data pre-processing and profiles analysis
The spectral data processing methods used in this study were previously described in our work based on the analysis of human hair fibre by Raman spectroscopy [10].
Briefly, in the current study the spectral acquisitions were recorded on the 400-4000 cm −1 spectral range. Prior to data processing on all Raman spectra, the 400-3600 cm −1 spectral range was extracted. Beyond 3600 cm −1 Raman spectra do not present any molecular information. The preprocessing of spectral data was performed using LabSpec 5 software (Horiba Jobin Yvon). First, cosmic radiation was removed and all aberrant profiles were excluded from the database. Each remaining profile was subjected to corrections to clean up the Raman signal for the hair fibres. These corrections applied to the raw spectral data included the correction of spectral shifts, noise reduction using a 5-point average Savitzky-Golay smoothing filter, and baseline correction using a polynomial function of degree 5 to remove the fluorescence background. Finally, for spectral data processing, the set of spectra were vector normalized across the entire spectral range (400-3600 cm −1 ). Three axial Z profiles were recorded for each hair sample, and mean Raman spectra were calculated to ensure that the Raman measurements were reproducible. Due to the irregularity of the flatness of the hair surface, the surface point can slightly vary and no longer corresponds to the zero position (Z = 0) of the objective lens shift operated by the piezoelectric device. The surface point is estimated at the half-maximal intensity of CH vibration (2800-3000 cm −1 ) when the lower half of the laser beam is in the hair fibre and the upper half is in the air. In this case, the maximum focal point is located exactly at the hair surface. The offset calculated at the surface position was also used to correct the depth of all spectra of the same profile. For further data processing, the average spectra from surface point (Z = 0) to 30 μm of depth (Z = 30 μm) were calculated for each profile. These average spectra from 30 μm have been used in the analysis, taking into account the molecular information of hair in the cortex and the cuticle.
After the pre-processing steps were completed, the corrected average spectra from 30 μm were processed using self-coded software based on a hierarchical classification algorithm and Amide I band curve-fitting methods operating in the Matlab environment (The Math Works Inc.). The average spectra from axial (Z) profiles of hair fibres were classified using Ward's clustering algorithm. This function calculates Euclidean distances between the spectra and groups them into clusters according to their similarities. This method of cluster analysis allows for the classification of hair fibres with a similar keratin structure. The results are shown as a dendrogram. Curve fitting may be used when the resolved features of overlapping Raman bands are difficult to observe. In our analysis, curve-fitting analysis was used to extract unresolved αhelix and βsheet keratin conformations from the hair fibres' spectra in the Amide I spectral band. This procedure was based on the least-squares method using Gaussian and Lorentzian functions. After the curve fitting, we have integrated αhelix and βsheets keratin marker, respectively, at (1640-1660 cm −1 ) and (1660-1685 cm −1 ) spectral regions. For S-S cysteine keratin cross-links bands, we have integrated the peak at 510 cm −1 [10].

In-vivo tests
Two studies were conducted in accordance with the International Council for Harmonization (ICH), the Guidelines for Good Clinical Practice and the Declaration of Helsinki. All participants provided written informed consent prior to study beginning.
Both in use tests, of a 1-month duration, were performed on either 23 Caucasian subjects or 23 Asian subjects. They used the heat protective hair treatment on hair lengths and ends, under the normal condition of use, 3 times a week before using their own straightening iron or hair dryer.
Among the Caucasian subjects using a straightening iron, 5 of them with natural blond or light brown hair (in order to limit fluorescence interference during Raman measurements) were selected for the Raman spectroscopy analysis. A sampling of their hair (about 15-20 hair and 5-6 cm of length) was collected for analysis before hair treatment and after 1 month of use (with the last application 2 days before). The subjects answered a satisfaction questionnaire about hair care effect after 1 month of use, the percentage was calculated taking into account the positive answers.
An evaluation by a hairdresser, on the whole hair, was performed on the Caucasian panel based on a sensory analysis of 4 descriptors (brittle aspect, split aspect, repaired aspect of the hair and hair shininess) before and after 1 month. This evaluation was carried out using structured scales defined by the references "no intensity" (limit 0) and "maximum intensity" (limit 10). The hairdresser evaluates the intensity of each descriptor by attributed a mark on the scale displayed on a computer screen on a specific software developed.
The improvement percentage was calculated and validated by statistical analysis. The results of both the satisfaction questionnaire and hairdresser assessment could be a support to claim that the product can beautify the hair despite having been heated.

Statistical analysis
The results that followed a parametric distribution were subjected to statistical analysis using Student's t-test, while those that did not follow a parametric distribution were subjected to statistical analysis using the Mann-Whitney test. p values from significance scores are presented in figures as follows: *p value <0.05; **p value <0.01; ***p value <0.001.

Preparatory study
In order to determine a heat stress threshold suitable for our study without causing significant damage on the hair fibre, different heat stress cycles (0, 5 and 10) were applied to hair fibres followed by morphological analysis by conventional microscopy on cross sections and by SEM on intact fibres. The heat stress cycles were applied using a hair iron straightener at 235°C.
Compared to untreated hair fibre, the results (Figure 3) of the conventional microscopy and the SEM show a significant degradation of the fibre structure at 10 stress cycles by the formation of bubbles and cracks.
These results show that 10 heat stress cycles are too aggressive on the hair structure and cause significant F I G U R E 2 Raman mapping (Z) profile showing the depth scanning through the hair fibre from the surface Z = 0-30 μm of depth morphological alteration of the fibres by the appearance of bubbles and cracks. Based on these results, we chose to conduct our study with two different heat stress thresholds. For the SEM technique, a 10 heat cycle threshold was chosen because this threshold allows observing morphological modifications on the hair structure fibre. For the CRS technique, a lower heat stress threshold at 5 cycles was chosen to preserve the morphological integrity of the hair fibres in order to focus the study on molecular changes after heat stress.

Evaluation of thermal stress on the hair by SEM method
This technique was used to evaluate the effect of exposing the surface of the hair fibre to excess heat (235°C). Figure 4 shows the SEM images of hair fibres that were subjected to 10 cycles of thermal treatment using a hair iron straightener at 235°C. The SEM pictures below are representative of the obtained effect of heat on untreated and treated hair with the hair care product.
The pictures show substantial damage of heat on untreated hair fibres by the appearance of bubbles and cracks. These phenomena were as expected: the inner part of hair contains about 10% of "bound water" (water bound to keratin chains). This water contained in hair fibres gives the hair its elasticity and suppleness. Heat stress induces the "boiling" of this water and tiny vapour bubbles (also called heat bubbles) are formed inside the hair fibres. These water vapour bubbles deform the hair from the inside by exerting pressure on the constituent parts of the fibre and hair loses its flexibility and becomes very brittle [3]. Heating devices induce crackles on hair fibres by altering the natural lipidic film that protects the hair fibre surface.
The tested hair care product clearly shows protective properties with respect to heat damage. Hair treatment with the test product before heat damage systematically showed lesser "bubbles" and "crackling" on the hair surface.

Evaluation of thermal stress on the hair by Raman spectroscopy
Assignments of keratin markers in Raman spectra of human hair fibre The first step of this work was to determine the reference Raman spectra of all hair samples and to compare them with reference human keratin Raman signal. The corresponding Raman spectrum is shown in Figure 5. The comparison between Raman spectra of human hair fibres and F I G U R E 3 Light microscopy images (100×) of cross section of hair fibres subjected to (0, 5 and 10) heat stress cycles (a) and SEM images (×1000) of hair fibres subjected to (0, 5 and 10) heat stress cycles (b) (formation bubbles and cracks indicated by white arrows) pure keratin molecules allowed us to evaluate the contribution of the keratin molecule to the hair fibre spectrum and the assignment of specific keratin bands in the global spectrum of human hair. The results show very close spectral signatures between hair samples and reference keratin Raman signal. In the spectra, several peaks specific to keratin molecules can be distinguished (highlighted bands in Figure 5) and the major bands are found in two spectral windows: 400-1700 cm −1 and 2700-3000 cm −1 [10].

Raman ex-vivo analysis
To investigate the influence of treatments with hair product and thermal stress with straightening process on hair fibres; the keratin structure of 4 samples [S1: untreated and unheated (Control), S2: treated and unheated (T UH), S3: untreated and heated (5×) (UT H) and S4: treated and heated (5×) hair sample (T H)] of natural human hair was directly analysed by using confocal Raman spectroscopy. We recorded 3 Raman (Z) profiles directly on the human hair fibre resulting from each treatment. Before the data analysis, the Raman signal of the product has been checked and does not show any interference with the hair keratin signal in the spectral region of interest (Amide I and S-S disulfide bands). The spectral comparison of the hair samples with the product is shown in Figure 6.
To estimate the spectral difference, the mean Raman spectra of the 4 hair samples were compared and the corresponding spectra were classified by using a hierarchical cluster analysis algorithm. The function used calculates Euclidean distances between the spectra and the group according to their similarities in a cluster. The results are shown in Figure 7.
The results of this spectral classification based on the mean spectra, allowed to distinguish four spectral groups corresponding, respectively, to the S1, S2 S3 and S4 samples. These results show that the Raman spectral signature of the treated and heated hair fibre (S4 sample) is very close to the negative control (untreated and unheated S1 sample) (framed samples) compared to the S2 and S3 samples. The S3 hair sample (untreated and heated) shows the maximum spectral heterogeneity threshold (5) compared to the other hair samples (S1, S2 and S4). This classification suggests that the keratin spectral signature is preserved by hair product after thermal stress with the straightening process.
To investigate which molecular component of keratin the product has a significant effect, the Raman spectra of the 4 hair samples are submitted to a statistical analysis to determine whether there are significant differences between them. The comparison between mean spectra of negative control (S1) and the means spectra of each hair sample (S2, S3 or S4) by using the Mann-Whitney statistical test (p = 0.05) allowed possible to determine the most pertinent spectral markers for detecting the molecular changes in the keratin. The spectral comparisons show a specific and non-specific spectral variability, the amide I and disulfide S-S cysteine keratin bands are identified as a discriminant between the samples after hair treatment with the product and after thermal stress; these results suggest that the hair product has a molecular effect on these molecular bands. For this, the spectral analysis was particularly focused on the amide I and disulfide S-S cysteine bands. The more keratin hair fibres are constructed almost exclusively of αhelices and are rich in cysteine which provides covalent disulfide (S-S at 510 cm −1 ) crosslinks between adjacent polypeptide chains.
The amide I region allows detecting the change in αhelix and βsheet keratin conformation. To evaluate the influence of treatment and thermal stress on hair fibres two molecular spectral markers were calculated: the ratio of αhelix (1640-1660 cm −1 ) to βsheets (1660-1685 cm −1 ) on amide I region and disulfide S-S cysteine keratin crosslinks bands (510 cm −1 ).
The results are shown in Figure 8. These results show that the thermal stress has a tendency to decrease the αhelix keratin conformation (for S3 and S4 samples) ( Figure 8, graph a). In parallel, significant increase in βsheets keratin conformation is observed for S3 sample (untreated and heated) (Figure 8, graph b), and this increase is not significant for treated hair samples (S2 and S4). These variations in αhelix and βsheets keratin conformation cause a significant decrease in the ratio of αhelix to βhelix sheets keratin band for S3 sample (untreated and heated) (Figure 8, graph c). This result can be explained by the fact that the product provides thermal protection of the hair fibres by promoting the αhelix keratin conformation and inhibits the transition to the βsheets keratin conformation.
Disulfide bonds are important for the stabilization of folding structure of keratin. The stability of S-S disulfide bonds in keratin can be assessed by calculating the conformational order of disulfide S-S cysteine bonds in the 474-578 cm −1 spectral range. The results are shown in graph ( Figure 9).
These results show that the thermal stress decreases the intensity of covalent cross-links bands of cysteine for S3 sample (untreated and heated). This can be explained by a fragility in the keratin structure caused by thermal stress. In parallel, for S4 sample (treated and heated), we observe stability in the S-S disulfide keratin bands, suggesting that the product preserves the (S-S) disulfide keratin bands from thermal damage and stabilize the tertiary structure of keratin hair fibre.

Raman in-vivo analysis
In order to confirm the results obtained from ex vivo analysis, a complementary in vivo study was carried out on volunteers. For this, 5 volunteers with light blond hair were included in this analysis and two hair samples per subject were taken. The first hair sample on D0 before product application and the second hair sample at 28 days (D28) after product applications and thermal stress. As for ex vivo analysis, the molecular analysis was particularly focused on the disulfide S-S and amide I keratin bands. The results are shown in graphs ( Figure 10). As observed for ex vivo analysis, the ratio of αhelix to βsheets keratin conformation increases significantly at D28 after hair treatment and a tendency (limit to significance) to decrease in the S-S disulfide keratin bands was observed. These results confirm our hypothesis, suggesting that the hair product promotes the αhelix keratin conformation and contributes to the stability of its tertiary structure.
Evaluation of the hair care effect during the clinical study Furthermore, these results were also completed with another analysis and enable to validate the efficiency of the hair care from a consumer and a hairdresser point of view.
The hairdresser assessed an immediate decrease of 37% of the brittle aspect of the hair and of 30% of split hair as well as an increase, after 1 month of use, of 17% of the hair shininess and of 26% of a repaired hair aspect. After 1 month of use, the satisfaction questionnaire revealed the following results ( Figure 11).

DISCUSSION
In this study, the evaluation of a thermal protection of a cosmetic finished product with several methods provided interesting information on the effect of the thermal stress on hair fibres. This hair care product acts through thermoactive technology formed by two ionic polymers. Activated by heat, this product forms an adhesive microgel that helps the appearance of hair by closing scales and filling in breaks. Thus, the fibre should be protected from the heat, the hair is shinier, softer and more supple with less split ends and less brittle hair.
The SEM method enabled the evaluation of the effect of excess heat on hair fibres. The obtained images showed changes in the hair surface after a thermal stress. Two main deformation patterns were observed: cracks on hair cuticles and bubble formation in the hair fibres. The treatment of the hair fibres with the hair care product decreased the heat associated damage.
At the molecular level, the results of Raman spectroscopy showed, on the one hand, that the product provides thermal protection of the hair fibres by promoting the αhelix keratin conformation and inhibits the transition to the βsheets keratin conformation. On the other hand, for treated and heated hair samples, we observed stability in the S-S disulfide keratin bands and this suggests that the product preserves the (S-S) disulfide keratin bands from thermal damage. F I G U R E 8 Evolution of αhelix (a), βsheets (b) and ratio αhelix/β-sheets (c) keratin conformation of 4 hair samples. Data are shown as the mean ± standard error (**p < 0.01, *p < 0.05, NS: not significant p > 0.05). S1: untreated and unheated (Control), S2: treated and unheated (T UH), S3: untreated and heated (5×) (UT H) and S4: treated and heated (5×) (T H) According to our results, we can suppose that the product provides thermal protection of the hair fibres by acting at two levels of keratin molecular structure: (i) at secondary structure by promoting the αhelix keratin conformation and (ii) at tertiary structure by protecting hydrogen keratin bonds and stabilization of disulfide bridges. These results are consistent with the thermal protective claims of the product and with the morphological observations made in SEM.
However, we have confirmed the Raman and SEM results with other techniques, such as the repairing effect on the split ends of the hair fibres, the evaluation of the protection of hair's lipid envelope by fluorescence microscopy on hair fibres cross-sections and Differential Scanning Calorimetry (DSC) (Supplementary Data: S1).
Furthermore, these results were also confirmed by the Asian and Caucasian consumers and a hairdresser. After 1 month of use, most of the consumers found that their hair was protected from the heat of styling appliances by protecting hair against split ends and brittle hair. The hair was shinier, softer, more supple and thus more beautiful; those improvements were also found by the hairdresser. However, these results need to be confirmed on more donors by combining other factors affecting heat-protecting effect of product such as (origin, colour, age and sex …).

CONCLUSIONS
Through the results obtained in this work, we have demonstrated by the Raman spectroscopy technique that the hair care product has thermal protective activity by acting on the conformation and disulfide bridges of keratin. However, by SEM analysis, we established a link between the molecular action of the product and the preservation of hair fibre morphology against thermal damage, such as F I G U R E 9 Evolution of disulfide (S-S) cross-links band of 4 hair samples. Data are shown as the mean ± standard error of the disulfide (S-S) cross-links band (**p < 0.01, *p < 0.05, NS: not significant p > 0.05). S1: untreated and unheated (Control), S2: treated and unheated (T UH), S3: untreated and heated (5×) (UT H) and S4: treated and heated (5×) (T H) F I G U R E 1 0 Evolution of αhelix/β-sheets keratin conformation (a) and disulfide (S-S) cross-links band (b) of in-vivo hair samples (**p < 0.01, *p < 0.05, NS: not significant p > 0.05). D0 before product application, D28 after product application and thermal stress bubbles and cracks. Moreover, a complementary clinical study confirms the results obtained with the SEM and the Raman spectroscopy by showing a good perception by the subjects of the thermo-protective effect provided by the hair care treatment as well as the overall beautifying effect on the hair.
According to our results, Raman spectroscopy is a technique with a great molecular potential that offers the opportunity to evaluate other important aspects related to the effectiveness of cosmetics on human hair such as hydration, active penetration, oxidative and UV stress and this without performing any labeling or sample extraction.


Aggregation of konjac glucomannan by ethanol under low-alkali treatment

Highlights • Microstructure of KGM alcogels is distinct from that of normal KGM gels.• Gel network of EAKgel is more heterogeneous than that of EKgel.• Ethanol arranges the aggregation of deacetylated KGM chains.• Both structure and function of KGM aggregates are altered by ethanol and alkali.• Solvent quality deterioration drives the formation of low-alkali KGM alcogels.

Introduction
Konjac glucomannan (KGM) known for the remarkable gel-forming capacity is a food hydrocolloid extracted from tubes of Amorphophallus konjac C. Koch, which has increasing worldwide popularity recently due to its physiological activities and health benefits (Devaraj, Reddy, & Xu, 2019). Chemically, KGM is composed of β-1,4-linked D-mannosyl and Dglucosyl residues at a molar ratio of (1.5 -1.7): 1.0 with a small degree of β-1,3-branching linked at the C-3 position of mannose. Acetyl groups are essentially randomly distributed along the chain backbone with the degree of substitution around 0.05 -0.11 (BeMiller, 2019). Heating KGM dispersions in the presence of alkalis or basic salts can form thermally irreversible heat-set gels. The understanding of KGM gelation has been evolving over the last decade and recently overviewed by Liu et al. (2021). Fundamentally, its gelation includes the deacetylation of KGM chain by alkali addition, the stretching and physically association of macromolecules upon heat-treatment, and the three-dimensional gel network established on the agglomeration of random network. In the structure of KGM there is a segregation into polar (OH groups) and nonpolar (CH groups) patches, and thus a clear amphiphilicity. For this reason, both hydrophobic interactions and hydrogen bonds are driving the aggregation of KGM and the resultant gel formation.
Despite a few experimental studies on gelation of concentrated KGM dispersions with no alkali addition (Jiang, Reddy, Huang, Chen, & Xu, 2019), it has been acknowledged that the strong alkaline environment is critical for gel-forming which only occurs at pH in the range of 11.3 -12.6 (Huang et al., 2002). Depending on the alkali concentration, various important aspects of KGM gelation are expected to differ, such as the deacetylation and aggregation (Liu et al., 2021). It is a common practice to regulate the gelling rate and the mechanical strength of resultant gels by varying the alkali concentration (Solo-de-Zaldívar, Tovar, Borderías, & Herranz, 2014). Nevertheless, preparing KGM gels in the presence of such a considerable amount of alkaline also presents challenges associated with undesired product defects including significant syneresis, brown color and strong alkaline taste (Herranz et al, 2013), as well as a huge amount of alkaline wastewater produced subject to further treatment before its discharge. Developing alternative low-alkali or non-alkali KGM gelation is of practical importance and this is an active area of investigation currently. In essence, the phenomenon of polysaccharide gelation arises from polymer chains being aggregated and entangled which can trap solvent via surface tension. It is clear that we can promote the gelation of polysaccharides, either by enhancing the aggregation or entanglement. Despite the noteworthy role of salt bridges, the tendency of the macromolecular chains to hydrate or aggregate is normally controlled and impacted by the balance between hydrogen bonds and hydrophobic forces in aqueous environments (Ozbas, Kretsinger, Rajagopal, Schneider, & Pochan, 2004). Essentially, water molecules need to break some of their hydrogen bonds to accommodate macromolecules. This loss of hydrogen bonds between water and water will induce fluctuations and depletion of water density near large solutes. Therefore, hydrophobic interactions are originated from the collective motions of water hydrogen bond networks surrounding solutes (Jiang, Cao, Cheung, Zheng, Leung, Peng, & Huang, 2017). With regard to certain substances, sugars (i.e., glucose, fructose and sucrose) and alcohols (i.e., methanol, ethanol and glycerin) have manifested themselves as gelation promoters in various studies with underlying mechanism being explained by either the excluded volume effect which render those gelling polymers shrinking at low hydration levels or affecting the structural interactions: water molecules tend to be more restrained around those small molecules, promoting polymer-polymer interactions rather than polymer-solvent interactions. The gel of which the dispersing medium consists predominantly of an alcohol or a combination of alcohols and other solvent molecules is known as alcogel (Zhang, Song, Tian, Zhao, Zhou, 2022).
In an effort to reduce the alkali usage in KGM gel food processing, we have incorporated ethanol to facilitate the formation of KGM gels (Zhou et al., 2020). These scenarios addressed the extreme case of adding up to 40 vol% ethanol to the KGM dispersions with varying concentrations of alkali and provided convincing evidence for the discrepancies in the gel properties between those low-alkali or non-alkali KGM alcogels. It must be noted that the observed dissimilar nature of those KGM alcogels has not been elucidated yet in the absence of understanding of synergistic effect between the ethanol and alkali, which is fascinating not only out of scientific curiosity, but also for reducing alkali in konjac food processing.
In light of this, the present work was intended to address the specific role of ethanol on the given low-alkali KGM systems with regard to the structural interactions within KGM aggregation and the resultant KGM gelation. Rheological studies were performed to identify the macroscopic temperature-and time-dependent relaxation behaviors of each KGM system treated by either ethanol/alkali or both. The nanoscale gel structure was probed with some advanced in situ characterization techniques such as cryo-Scanning Electron Microscopy (cryo-SEM) and synchrotron-radiation Small-angle X-ray Scattering (SAXS) in conjunction with chemical structure study by Fourier Transform Infrared spectroscopy (FTIR). Before proceeding, it is worthwhile to know this study was not designed with a continuous change in ethanol and alkali concentrations, considering there had been research activity investigating the dose-effect relationship in KGM alcogels (Tong et al., 2022), while insight of structural features nevertheless was not satisfactorily explained in these studies.

Materials
The purified konjac glucomannan (KGM) (>95.1 wt%, dry basis) was purchased from the Hubei Yizhi Konjac Biotechnology Co., ltd. (China). The contents of moisture and crude protein were 8.2 wt% and 0.76 wt%, respectively. The weight-average molecular weight of KGM was 2.59 × 10 3 ± 57.56 kDa determined by gel permeation chromatography (GPC) using a dilute aqueous solution of KGM. All chemicals used were analytical grade and supplied by the Beijing Chemical Reagent Co., ltd. (China).

Sample preparation
The purified KGM was slowly dispersed in deionized water under magnetic stirring and swelled overnight at room temperature to obtain the 0.8 wt% KGM dispersion (denoted as K). The 0.04 wt% Na 2 CO 3 and/ or 20 % (v/w) ethanol were then added to KGM dispersions to prepare the dispersions of Na 2 CO 3 /KGM, ethanol/KGM and Na 2 CO 3 /ethanol/ KGM abbreviated as AK, EK, and EAK, respectively. It should be noted that ethanol was added very slowly to the KGM dispersions upon agitating in order to prevent the pre-gel formation associated with localized rapid aggregation.
Structure characterizations, except the temperature sweep test, were employed on heat-treated K, AK, EK, and EAK. To clearly distinguish different states between samples, gels formed upon heating EK or EAK at 75 • C were denoted as EK gel or EAK gel , while K or AK with no gelling process observed even at 85 • C were denoted as K sol or AK sol .

Rheological measurements
The rheological behaviors of samples were measured with a DHR2 rheometer (TA Instruments, USA) with a Peltier plate temperature control system.

Temperature sweep test
The K, AK, EK, or EAK in their liquid state were loaded onto the bottom plate of the rheometer at 25 • C with a gap of 2 mm. The cycled temperature sweep at 0.5 % strain and 1 Hz were conducted by heating from 25 to 75 • C immediately followed by cooling down to 25 • C at a temperature scanning rate of 5 • C/min for three times. In this scenario, EK gel and EAK gel could be obtained in situ to make sure the EK and EAK in their gel state were intact before starting the temperature cycle. All the samples were over filling to minimize the impacts of evaporation due to continuous heating. Considering the huge difference in viscoelasticity between gels and sols, this setup was performed either under a 40 mm parallel plate (for EK and EAK) or 60 mm parallel plate (for K and AK). To prevent the slippery between wet gels and the geometry, axial force of 5 N was adopted with a sensitivity at 5 N.

Amplitude sweep test
The strain amplitude sweep measurements were conducted at a fixed frequency of 1 Hz with strains in the range from 0.1 % to 1000 %. The storage modulus G ′ and loss modulus G ′′ were recorded during measurements.

Creep-recovery test
The creep-recovery test was programmed in three intervals at constant 1 Hz with varying shearing stress: rest for 100 s at low shear stress of 10 Pa (the first interval) followed by structural deformation for 50 s at high stress of 50, 100, 150, 200, or 250 Pa (the second interval) and structural recovery for 100 s at low stress of 10 Pa (the third interval). A quantitative analysis of the structural deformation and recovery was made to represent the degree of structural deformation (D def ) and the degree of recovery (D rec ) of the hydrogels, which are expressed as below: where G 1 ′ and G 2 ′ are the last G ′ values of the first and the second interval, G 3 ′ is the first G ′ value of the third interval.

Cryo-scanning electron microscopy (Cryo-SEM)
A small amount of sample (1 -2 g) was placed into a slot on a stub with rivets and cryo-vitrified with liquid nitrogen rapidly to prevent the formation of large ice crystals. After being transferred onto a cryo-stage (at − 160 • C) of the PP3010T Cryo-SEM Preparation System (Quorum Technologies, UK), samples were fractured and subsequently the frozen water was sublimated at − 90 • C under controlled vacuum conditions. After 15 min, samples were sputtered with platinum using argon gas to prevent charging during electron beam targeting before being transferred on to the JSM 7100F SEM stage (JEOL ltd., Japan) at − 160 • C and scanned at a magnification of 1 × 10 4 (Patel et al., 2015).
All cryo-SEM images are segmented using Otsu thresholding by the open-source ImageJ software (National Institutes of Health, USA) in order to extract the network information. Removal of outliers was performed to remove noise and unwanted small objects from the structure. We segmented images using watershed by pixel flooding for pore partitioning and labelled those segmented meshes and watershed ridges for fibril diameter and mesh size calculation. Three images were used for each sample and ten different segments on each image were randomly measured.

Small-Angle X-ray scattering (SAXS) characterization
Synchrotron-radiation SAXS characterization was conducted at Synchrotron X-ray Beamline 1W2A in the Beijing Synchrotron Radiation Facility (BSRF, wavelength 0.154 Å). The wavelength was λ = 1.54 Å. The sample-to-detector distance was 2000 mm. EAK gel and EK gel were formed in situ in cuvettes by heating before measurements at room temperature. The background was determined by measuring the empty sample holder with solvents.
The FIT2D software (https://www.esrf.eu/computing/scientific/ FIT2D/) was employed to transfer 2D scattering pattern to 1D scattering curve. The scattering vector was q = 4π/λ⋅sin(θ/2) and the θ is the scattering angle. Scattering curves can be used to differentiate between fractal dimensions which obey the power law: I(q) ~ q -α , where α is the slope of the straight line on a log-log plot scattering curves (Singhal, Toth, Beaucage, Lin, & Peterson, 1997). For mass fractals, one obtains α = D f with 1 < D f < 3, and for surface fractals,

Fourier transform infrared (FTIR) spectroscopy
FTIR spectra of freeze-dried K sol , AK sol , EK gel and EAK gel were assessed using an iS10 FTIR spectrometer (Nicolet, Germany) with a single reflection attenuated total reflectance (ATR) accessory equipped with a diamond crystal. The spectral range was 4000 -400 cm − 1 with a resolution of 4 cm − 1 . All the spectra are an average of 200 scans with background and ATR correction.

Statistical analysis
The results are represented as mean ± standard deviation. Significant differences among the samples were determined by analysis of variance (ANOVA) and Duncan's test (p < 0.05), using the SPSS Statistics software (version 23.0, IBM Crop., USA).

Temperature-dependence
The storage modulus (G ′ ) and loss modulus (G ′′ ) variation of K, AK, EK EAK with respect to a temperature cycle was plotted in Fig. 1. AK and K exhibited comparable mechanical response in terms of both heating and cooling (Fig. 1A). Albeit with a slightly higher G ′ than corresponding G ′′ upon cooling to 25 • C, AK and K were still in a sol state, which illustrate the role of the strong alkaline environment in gelforming (Zhou et al., 2020). Even though the plotted data of EK exhibited some scatter when heating to beyond 55 • C, in part due to the gel syneresis and the ongoing ethanol evaporation as temperature raises. Opposite trends of moduli at elevated temperatures were observed in EAK and EK (Fig. 1A). A closer examination of the temperaturedependence of G ′ revealed that EAK tended to be more elastic after heating, while EK experienced a G ′ slump before the recovery of elasticity during the latter heating processing, similar to what happened in the induction of KGM gelation in the presence of alkali (Williams, Foster, Martin, Norton, Yoshimura, & Nishinari, 2000). The representative gelation of KGM upon alkali-treatment has been illustrated by Liu et al. (2021), which could at least give some clues on the structural changes behind this trend of G ′ . However, it is still interesting to know the impacts of ethanol on KGM gelation can be altered at such a low alkali concentration.
Despite the post-gelation behavior of KGM gel being long ignored for simplicity and discussed only in limited studies, usually in conjunction with the significant syneresis effect (Herranz et al, 2013), the G ′ and G ′′ of EAK did not vary during the cooling and no hysteresis in the moduli between the heating and cooling curves was observed in both the second and the third temperature cycles. However, hysteresis always existed for EK in several temperature scans ( Fig. 1B and 1C). From purely a thermodynamics perspective, the hysteresis could be driven by the changes in the role of the entropic term of water and macromolecule-solvent interactions, which could be reflected on the changes in hydrogen bonding (Wang, Liu, Ru, Bai, & Feng, 2016). Regardless of the thermodynamics, the resistance of gel to temperature changes could be ascribed to a structural explanation as well. In essence, time and temperature are equivalent in terms of relaxation and the physical associations are expected to be transient which will relax on a timescale comparable to the lifetime of the given physical associations (Dooling, Buck, Zhang, & Tirrell, 2016). When the given heating condition was applied, there was sufficient time for EK to relax, while it was not enough for EAK to do so. Thus, we presumed there were some interactions or structural components which would stabilize the network even when the physical associations were largely weakened upon heating.

Deformation-recovery behaviors
We investigated the solid-liquid transition of EAK gel and EK gel by measuring the dynamic moduli under strain amplitude increment. Both gels could sustain finite deformations, which could quickly recover by releasing external forces on the timescale of the experiment before approaching the linear viscoelastic strain limits (i.e., 49.8 Pa for EAK gel and 2.3 Pa for EK gel ), if strain was converted to stress ( Fig. 2A). Such a stress value probably reflected the elastic strength of the interactions between neighboring structural elements. The primary breakup of the soft semi-solid structure is actually a small-scale phenomenon which normally occurs at the scale of an individual structural element such as the stiffness of the elastic bonds, and is insensitive to the coupling between neighboring structural units, i.e., interconnection by fairly weak hydrogen bonds (Andreas, PutzTeodor, & Burghelea, 2009). However, the subsequent loss of solidity corresponds to the interactions between structural units in a larger spatial scale and obviously, such a structural unit of EAK gel , albeit not well-defined yet, was supposed to be superior in rigidity in comparison with EK gel , given much higher values of G ′ for EAK gel .
When local deformations exceeded such certain linear strain limits, elastic-solid nature of the gel began to change and stepped into the solid-fluid phase co-existence regime (Hamada, Gakhar, & Longo, 2021). There was a competition between the destruction and reformation of the gel. The break-up of the gel network is commonly accepted to be the microscopic scale origin of the macroscopic yielding. Applied external forces could definitely cause a damage to the structural units, but such a force was not large enough to allow entire recombination in a different configuration and part of them could have enough time to recover subject to slow deformation (Ju, Ha, Song, & Lee, 2021). Thus, this preyielding process could be attributed to the heterogeneity of the gel network. A broader spectrum of phase co-existence might result from a higher level of spatial heterogeneity (Andreas, PutzTeodor, & Burghelea, 2009).
More spectacular differences, however, were observed when comparing the nonlinear response of EK gel to that of EAK gel . The coexistence regimes ended at 8.869 Pa and 173.014 Pa for EK gel and EAK gel , depicted by red arrows in Fig. 2A. This critical stress, which is typically obtained from the intersection of two asymptotic lines drawn through the initial and post-breakdown modulus data, can be considered to be an approximate measure of the yield stress of the material (Rafe, & Razavi, 2013). EK gel and EAK gel were subject to viscous flow at the macroscopic level in the nonlinear region, where entire interactions between neighboring structural units were broken and the probability of their rebinding was negligibly small. As a consequence, the destruction of the gel network prevailed in the viscous flow regime. However, there was a visible peak on their G ′′ curves in this purely viscous regime revealing strain amplitude where energy dissipation was maximized, which was assigned to the weak strain overshoot archetype. The underlying origins of overshoot were thought to be a variation of microstructure, either compacting of clusters that pushed the gel system towards phase separation or restructuring of clusters which would ultimately rupture in individual pieces. Compared to EK gel , the overshoot was largely magnified in EAK gel , probably because larger and betterdefined clusters was formed in the sheared EAK gel network at different shear stress (Wagner, & Mewis, 2021).
To further identify the difference of stress response and recovery behaviors between EAK gel and EK gel , we implemented several stressvarying interval thixotropic tests that includes both deformation and recovery processes. Considering EAK gel and EK gel did not share the same viscous flow regimes, we selected 250 Pa and 50 Pa for EAK gel and EK gel as the corresponding applied stress for breaking the structural unites and hence we can observe their deformation and recovery behaviors (Fig. 2B). As already pointed out, due to the strong heterogeneity of the gel network, the break-up and reconstruction of these structural unites should, in principle, occur over a whole interval of applied stresses (Andreas, PutzTeodor, & Burghelea, 2009).
The observed decrease of G ′ shown in Fig. 2B was accompanying with the implementation of the second interval and G ′ was found to be very close or even much smaller to G ′′ during deformation, indicating that EK gel and EAK gel were already in a fluid state due to a structural break-up (Shitrit, & Bianco-Peled, 2021). However, they presented quite different flow behaviors. In terms of EK gel , G ′ is nearly negligible (≈ 1 Pa), once again confirming its purely viscous nature. In contrast, the comparable G ′′ to G ′ of EAK gel implied an anomaly with the assumption that microscopic environment of broken network is not primarily viscous. It is more plausible to consider it is a viscous environment consist of concentrated centers of strongly associated macromolecules surrounded by regions of dilute macromolecular solution. The underlying origins of the difference were thought to be either structural or conditional. Therefore, we conducted a quantitative analysis of the structural deformation and recovery by applying several stresses over a broad spectrum and results were represented in Fig. 2C and 2D.
Both the degree of deformation (D def ) and the degree of recovery (D rec ) of EAK gel were much less than the EK gel (P < 0.05) in operating stress conditions < 100 Pa, thus revealing the structural origin of the phenomenon. We also noted anywhere from 150 to 250 Pa to applied shear stress beyond 250 Pa, the deformation-recovery behaviors of each gel were rather not significantly different. Namely, gel structure did not make a difference in the deformation-recovery behaviors and instead the external force dominated the structural transition given very high applied stress. Significant deviations in the D def and D rec of EAK gel occurring compared to EK gel , which is especially apparent at higher shear stress, could be explained by the restructured gel morphology with more anisotropy and a less well-defined structural patterns (Ju, Ha, Song, & Lee, 2021).

Gel microstructure
We employed direct imaging to provide some insights into the microstructure patterns with cryo-SEM, which could overcome the shortcoming of dehydration which might cause the severe collapse and flattening. Typical cryo-SEM images for EK gel and EAK gel were shown in Fig. 3A.
Overall, both gels were essentially composed of highly interconnected network structures where the water was embedded in both the large pores and small meshes. We could see those networks were inserted with some locally flat walls probably caused by the artificial reorganization such as frozen fracture and drying orientation (Wu, Gaharwar, Chan, & Schmidt, 2011). The cryo-SEM images of K sol and AK sol could be also found in Fig. S1, presenting morphological pictures of KGM dispersion in polar solvent due to the strong role of KGM/solvent interactions. On macroscopic level, the freeze-drying process allows for the achievement of monoliths that preserve the size and shape of the container submitted to freezing. In colloid dispersions, spaces originally resided by ice crystals are transformed to empty areas enclosed by "walls" of matter, leading to ordered porous structures rather than interconnected networks, while such an oriented honeycomb-like structure may be formed in the sublimation of icy crystals (Tripathi, Parsons, Khan, & Rojas, 2018). As a result, KGM chains were mostly aggregated and sequestered into unfrozen water regions, thus being contained in the dense wall-like structures.
A visual inspection of Fig. 3A revealed that EAK gel were relatively disordered in network configuration, while the network of EK gel displayed a lower degree of anisotropy. This result was consistent with aforementioned a broader spectrum of solid-fluid co-existence for EAK gel . The structure of fibril, as one of the integral components of morphological investigations on gel network, was illustrated by presenting its diameter distribution in Fig. 3B. When the fibril diameter data were plotted together, there is a significant deviation between the mean, median (i.e., D50) and mode diameters (Table S1), existing in a non-symmetric distribution, reflecting the dimensional anisotropy of fibrils as a natural consequence of the complex multiscale aggregation of KGM chains in the whole scanned regime.
EAK gel appeared to be not significantly different with EK gel in terms of mode and D50 values, but the average diameters of those rod-like elongated aggregated fibril, determined to be 193.8 ± 34.1 nm and 262.3 ± 22.3 nm for EK gel and EAK gel , were significantly increased with alkali. The distinction in diameter of fibril was in accord with the visual inspection of gel network in Fig. 3A and revealed the tendency of agglomeration of fibrils in EAK gel . In principle, the size of the fibril is determined by the elastic energy required to form the rod-like structure aggregated from macromolecules, and the interfacial energy associated with the macromolecule-solvent interactions that tends to decrease by minimizing the surface area. The aggregated supramolecular nanodomains of EAK gel which could agglomerate into larger and stronger rod-like aggregates and further hierarchical network structures could probably be the individual structural element contributing to the elastic strength discussed above. The resultant thicker fibrils were much stronger, and hence provided stiffness to the network. In light of recent evidence providing that both EAK gel and EK gel are composed of a semicrystalline KGM matrix (Fig. S2), although the crystalline structure is not definitively known, those nanodomains were illustrated to be a certain low degree of crystallinity, but packed differently under different conditions.
The network of EAK gel seemed to be denser than that of EK gel shown in Fig. 3A. However, the highly anisotropic characteristics of gel network made representation of morphology with an accurately quantification of domains, shape, distribution, and connectivity, especially across meshes really challenging. Thus, we tried segmenting cryo-SEM images using Otsu thresholding, whereby we were able to recognize the differences in the network displayed in Fig. 3A. As shown in Fig. 3C, a shift of mesh size distribution and size toward smaller range was seen in EAK gel (see also Table S2). While the small hydrophobic mesh enabled a continuous transport pathway of external force through the network, its mechanical stability could be improved as illustrated in Fig. 2C. Moreover, smaller mesh could also be interpreted as there is the smaller spacing between the physically associated zone. By combining with the rheological study results, we could expect the physically associated zone was much stronger for EAK gel , and hence provided stiffness to the network. Albeit with systematic artificial reorganization, the smaller spacing between association zones implied the existence of the synergistic effect of ethanol and alkali (Tong et al., 2022), even at very low concentration. Introducing ethanol can prolong the interaction time between two colliding aggregates, which fluctuated by thermal motion. If the interaction time is much longer than the time required for macromolecular aggregates to diffuse, penetrate and merge, the probability of fusing into large associated zone can be largely increased. Herein, it is more conducive to the formation of smaller spacing between association in the case of alkali treatment which can induce deacetylation and eliminate such internal constraints against fusing (unpublished data). Thus, it is important to gain insights into the characteristic structure of those association zone.

Characterization of KGM aggregates
Fig. S3 displays the SAXS spectra with the corresponding length scale. The q is proportional to the inverse of the apparent periodic length d, as d = 2π/q (Wang et al., 2018). The scale of length was determined to be ~ 6 nm, confirming the extracted SAXS data was scattering of KGM aggregates or the interior substructures of aggregates. Typically, there are two commonly studied q-regimes: the small-q upturn Guinier regime providing information about larger-scale structural features of scatterer and the large-q Porod regime providing information about the interface of scatterer (Gutsche, Guo, Dingenouts, & Nirschl, 2015).
In Fig. S3, SAXS profiles manifest themselves in the asymptotic regime of Porod as there was a strong continuous decrease in scattering intensity with a characteristic slope. As we can see from the logarithmic plots, which were no longer straight lines, the assemblage should contain a distribution of aggregate size. The average physical quantity related to the spatial distribution of the mass, i.e., radius of gyration (R g ) was measured for aggregate size interpretation. To determine the R g of each aggregate fraction of each sample, graphical reduction was employed with results being showed in Table 1 (see Fig. S4 and Table S3 for the complete calculation by the method of graphical reduction).
We found the R g of K sol was significantly smaller than others in Table 1 and both the large and middle-sized aggregates were negligible in volume fraction for K sol . Giving the nearly monodisperse nature of KGM aggregates of K sol at nanoscale, K sol formed a colloid system with very small aggregates of KGM since the macromolecule backbones tend to be stretching without any treatments. In terms of the alkali or ethanol treated sample, the KGM aggregates were as expected to differ in size (Table 1). Deacetylated KGM molecules did not stretch but rater exhibited dispersion-like behavior with spherical aggregates (Zhou et al., 2018). It has been well accepted that the deacetylation significantly reduces the steric hindrance (Qiao et al., 2022), which will favor intermolecular aggregation. And it was observed such a low concentration of alkali could remove almost all the acetyl groups along the KGM chain (~95 % degree of deacetylation for EAK gel and AK sol ).
Surprisingly, despite the gel nature of EK gel , its KGM aggregates were even smaller than AK sol in the spatial distribution of the mass. It is seemingly difficult to imagine that such a collapsed aggregate structure could overcome the rotation agitated by thermal energy, making the chains confined within entanglements, unless the surrounding solvent deteriorated in quality and inhibited the slippery because of the more negative excluded volume effect. KGM aggregates of EAK gel were relatively the largest, suggesting only with both alkali and ethanol did these aggregating effects coming come into play. The size of the aggregates is determined by the elastic energy required to form the rod-like structure, the interfacial energy that tends to decrease by minimizing the surface area, and most importantly, the spatial confinement effect associated with the KGM − solvent interactions. The small-sized KGM aggregates of AK sol and EAK gel was very similar in weight fraction (99.36 % vs 99.63 %). Suppose the deacetylation was completed much faster than the intermolecular aggregation, we could propose the associated zones of EAK gel were not distributed in the polymer network, but only located at the original junction zones of alkali gels essentially composed of acetylfree portions. In addition to the (main) correlation region, there is two sharp peaks (see Fig. S3) in the EAK gel spectra indicated by arrows, clearly revealing KGM molecules could assembled into some small-scale ordered structures (Wang et al., 2018), i.e., the nanodomains aforementioned. Nevertheless, there is no peak exhibiting in curves other than EAK gel , suggesting that the KGM aggregates are mostly homogenous and amorphous on the length scale of this experiment.
As the interior structure of aggregates is expected to consist of a complex "fractal-like" micropores, the values of D f (see Table 1) were also extracted by scaling I(q) in the asymptotic regime of Fig. S3, those were 1.78, 2.18, 2.278 and 2.874 for K sol , AK sol , EK gel and EAK gel . We obtained mass fractal with 1 < D f < 3, which has been positively related to the compactness of the scatterer (Shilova, 2020) and thus the free volume in the scatterer can be interpreted, i.e., larger mass fractal indicates smaller volume of the micropore. The closely spaced hydroxyls in the hydrogen-bonded form would endow aggregates substructures with more continuous and better-connected domains. Otherwise, KGM aggregates could be loosened due to the larger volume of such micropores which can accommodate water clusters. Key to that assumption is the local environment of hydrogen bonds and their property, which has been probed by FTIR.

Hydrogen bonding
We attended to interpret the aggregation of the KGM backbone via the with a focus on the analysis of the IR information related to hydrogen bonding induced changes in hydroxyl-water local environment (see Fig. 4). The characteristic IR fingerprints of KGM are associated with the macromolecular chains (the stretching bands for -CH 2 and C-O at 2884 cm − 1 and 1247 cm − 1 ), acetyl groups (asymmetric v as (C--O) at 1725 cm − 1 ) and interacting with free water (H-O-H bending at 1620 -1740 cm − 1 , ν(O -H) stretching at 3000 -3450 cm − 1 , and 1638 cm − 1 for hydroxyl groups associated of C-O (Ye, Kennedy, Li, & Xie, 2006). The peak at 1725 cm − 1 for both AK sol and EAK gel disappeared in the spectra, indicating that all the acetyl groups had been removed as a result of alkali treatment.
The absorption bands at 1638 cm − 1 and 3000 -3500 cm − 1 being assigned to ν(O -H) stretching could be used to identify the in-plane deformation of the water molecule and local hydrogen bonding environment (Wu et al., 2012). As noted, the latter characteristic absorption band was wide and strong in each IR spectra, demonstrating the existence of hydrogen bonded hydroxyls and thus the shifts in this band are ascribed to alternations in the extent of the formation of intra-or intermolecular hydrogen bonding (Wang et al., 2020). Despite the ν(O -H) band at 3000 -3500 cm -1 of EAK gel being down-shifted to 3313.49 cm − 1 , the band at 1638 cm − 1 up-shifted to 1649 cm − 1 , suggesting the hydrogen bonding stack size has been changed (Panja, Dietrich, Trabold, Zydel, Qadir, & Adams, 2021), which probably lead to different molecular packing in the EAK gel . What occurred in EAK gel IR spectra could be interpreted as the existence of the chains with largely restricted motion in confined spaces. Albeit with the tendency for such a stretched macromolecular chain in EAK gel to contract to increase its conformational entropy, as thermodynamics reveals an isolated system always spontaneously moves towards the direction of increasing entropy (Fang, 2021), it is critical to understand why this happens only in EAK gel and that is, only segments of deacetylated KGM chain with ethanoltreatment randomly move inside a 'smaller box' indicated by the SAXS analysis and can still approach the neighbor chains for hydrogen bonding.
In principle, the chain motion has opposite dependence on excluded volume and entropy elasticity effects and their competition allows each macromolecular chain to approach or repel each other (Kreer, 2016). It is reasonable to understand ethanol can change the balance of this competition by increasing the translational entropy and excluded volume will limit the motion of chain. The hydrophobic interaction thus plays a pivotal role in controlling the molecular packing in the gelation of EAK gel , instead of hydrogen bonding. However, the extent of contributions from hydrophobicity to this process still remains unclear because quantitative measurements of hydrophobic interactions are very challenging.
When it comes to the impact of alkali, the distinct conformations of deacetylated KGM chain in a comparison with the native one, which were evident from the study of Zhou et al (2018), could explain the intrinsic factors controlling the entropy elasticity effects, if we treated the KGM chain as a spring with similar length even after the removal of acetyl. Unequivocally, impact of ions on excluded volume of neutral KGM chains is expected to be negligible in a comparison with that of ethanol. Besides the apparent R g of KGM aggregates, the differences in properties of the EKgel and EAKgel can be also ascribed to the change in underlying molecular packing due to the existence of different noncovalent interactions.

Aggregation of KGM by ethanol under low-alkali treatment
Combining, several features of ethanol and low-alkali treated KGM aggregation could be outlined from the provided data on EAK gel as shown in Fig. 5: a) intermolecular aggregation of KGM chains was intensified; b) patterns exhibited stronger anisotropy in gel network; c) KGM fibrils were possibly formed with some random small-scale ordered nanodomains inserted in; d) there might be preferential hydrophobic interaction than hydrogen bonding constraining the associative domain.
Similar to the gelation of pectin, alginate, xanthan and guar gum, there was an increase of solvent hydrophobicity due to addition of ethanol (Tkalec, Knez, & Novak, 2015). Consistent with observations reported in the literature, the formation of some nanodomains could lead to spatial segregation of KGM aggregates, which would concentrate in the diminishing water domains as the alcohol content increases and the extent of the aggregation would be tied to the ability of the alcohol to create these nanodomains (da Silva, Calabrese, Schmitt, Celebi, Scott, & Edler, 2018). The self-association of cellulose in alcoholic aqueous binary mixtures which leads to the occurrence of inhomogeneous clustering at short length scales has been reported (From, Larsson, Andreasson, Medronho, Svanedal, Edlund, & Norgren, 2020). Studies of cellulose derivatives also pointed to the strong effect of short-lived hydrophobic interactions in aqueous solution, but there is no indication of hydrogen bonding driving association between the cellulose derivatives molecules in water or playing a role in association phenomena in general (Lindman, Medronho, Alves, Costa, Edlund, & Norgren, 2017). Notably, this indicates that low-alkali treatment will affect the KGM aggregation and ethanol cannot be considered as the only influencing factor.

Conclusion
Recent developments on KGM alcogels has provided significant improvements on reducing the alkali usage in konjac food processing. A related issue that is garnering much more attention is why KGM can gel under a low-alkali condition in an ethanol-containing solvent system. In view of the discrepancy in multiscale structure between K sol , AK sol , EK gel and EAK gel , ethanol could intensify the intermolecular aggregation of KGM chains and created stronger anisotropy in gel network with some random nanodomains of deacetylated KGM aggregates. The existence of different molecular packing patterns between the EKgel and EAKgel could be interpreted as a result of different non-covalent interactions holding KGM chain in a spatial confined configuration. Inspired by these observations, we propose the arranged structural reorganization in EAK gel could be attributed to the aggregation of deacetylated KGM chains as the solvent quality deteriorates. Such systems serve as proxies for complex intermolecular association in the gelation of carbohydrate polymers under ethanol and exhibit phenomena associated with excluded volume effect and related hydrophobic interaction.

Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.