Using transcranial magnetic stimulation (TMS) to delineate upper motor neuron (UMN) signs of two neurodegenerative disorders: amyotrophic lateral sclerosis (ALS) and multiple system atrophy (MSA).Medical records including clinical signs for UMN damage and TMS results were reviewed retrospectively. The UMN signs were classified into none, mild, and severe based on neurological examination of various reflexes. Then TMS-elicited motor evoked potentials (MEPs) were recorded from a hand and a leg muscle to calculate the central motor conduction time (CMCT), which represents fast, mono-synaptic conduction along the corticospinal tract. Relations between the UMN signs and CMCT were analysed for the two diseases.Prevalence and severity of the UMN signs for ALS and MSA were comparable for both upper and lower limbs. However, abnormality in CMCT was found more frequently in ALS: CMCT abnormalities were found in upper limbs for 44% in ALS patients but only for 7% in MSA patients; CMCT abnormalities in lower limbs were 55% in ALS and 20% in MSA. Some ALS patients showed abnormal CMCT in limbs without UMN signs, which was not true for most MSA patients.The abnormalities of CMCT were different in ALS and MSA, even for those who clinically had similar UMN signs. Sometimes, CMCT can reveal UMN damage in the absence of clinical UMN signs. Differences presumably derive from selective degeneration of different fibres in the motor descending pathways. Longitudinal studies must be conducted to accumulate neuroimaging and pathological findings.CMCT can be useful to differentiate ALS and MSA. The UMN signs include Babinski sign, exaggerated tendon reflex, and spasticity, primarily caused by lesions in the primary motor area (M1) and its descending pathways. Although the signs are quite familiar to many neurologists, no precise pathophysiology underlying them is known .Transcranial magnetic stimulation (TMS) facilitates investigation of motor descending pathways in a non-invasive manner. A TMS coil placed over the skull produces electric fields in the brain through electromagnetic induction. When the fields activate neurons in the M1 sufficiently, action potentials travel down the descending motor pathways, eventually giving rise to muscle twitch. Electromyography (EMG) corresponding to the twitch is termed motor evoked potential (MEP). Because MEP is believed to represent fast, monosynaptic conductions from the M1 to the spinal cord, central motor conduction time (CMCT) estimated from the MEP latency can be used as an index for conduction along the motor descending pathways. For example, a lesion such as a plaque of multiple sclerosis in the spinal cord would prolong CMCT, indicative of demyelinating characteristics of the lesion . NeverthTo elucidate relations between TMS measures including CMCT and UMN signs in different neurodegenerative diseases, we specifically examined data of patients with amyotrophic lateral sclerosis (ALS) and multiple system atrophy (MSA). First, ALS and MSA present with the UMN signs in a large proportion of patients. Reports of the literature describe that 40–70% of ALS patients  and 7–73This retrospective study is aimed at exploring potential association between the UMN signs and CMCT testing in ALS and MSA. In addition to comparison of CMCT, we assessed correlation between CMCT and UMN signs for both diseases.22.1This study is a retrospective, observational study. The study protocol was approved by the ethics committee of the Faculty of Medicine of the University of Tokyo. Medical records were inspected from 2015 to 2019 for ALS patients, and from 2009 to 2019 for MSA patients to obtain similar numbers of records for both. Inclusion criteria were possible, probable or definite ALS according to the revised El Escorial criteria , and pos2.2Clinical information was collected with some emphasis on the UMN signs. Age, height, and duration from onset to CMCT testing were extracted from the records. As a measure of activity of daily living, the Barthel Index was extracted whenever possible.The UMN signs were represented as the UMN score based on an earlier report . For the2.3To measure CMCT, TMS had been conducted using a standard protocol . In brie2.4Clinical and physiological data were aggregated on the disease and limb basis. The UMN signs and CMCT testing for right and left sides were analyzed together, where the right and left limbs were both counted as one limb each, i.e., each patient provided data on two upper limbs and two lower limbs for physiological parameters.t-test or χ2 test. Differences in the UMN signs and CMCT abnormality between ALS and MSA were compared using the χ2 test. Relations between the CMCT value and UMN signs were explored using two-way analysis of variance (ANOVA) separately for the upper and lower limbs, where DISEASE (two levels: ALS and MSA) and UMN sign  were between-subjects factors. Given we had no within-subject factor, repeated-measures ANOVA was not used. Height was included as a covariate. Post-hoc tests were conducted using the Bonferroni method as a correction for multiple comparisons. To assess influence of more general clinical status on CMCT, correlation between the Barthel Index and CMCT was tested.Demographic findings were compared between ALS and MSA using independent To explore the influence of the disease subtype, CMCT abnormality was classified as normal or abnormal. Prolonged and inexcitable CMCT were considered abnormal; the others were normal.Information on the LMN function could be inferred in 58 ALS patients by amplitude of compound muscle action potential (CMAP) and latency of F-wave recorded from abductor pollicis brevis (APB) of the hand and abductor hallucis (AH) of the foot. Correlations were investigated between FDI-CMCT and APB CMAP/F-latency, and TA-CMCT and AH CMAP/F-latency.p ≤ 0.05. All statistical analyses were conducted using software .Significance was inferred for 3In total, medical records from 61 ALS patients (35 men and 26 women) and 61 MSA patients (40 men and 21 women) were reviewed. Their characteristics are presented in 3.1p = 0.276 and 0.424, χ2-test). More specifically, 59 upper limbs of ALS (48%) did not show UMN signs, 23 (19%) showed mild and 40 (33%) showed severe signs, whereas 47 (39%), 30 (25%), and 45 (37%) upper limbs of MSA presented, respectively with no, mild, and severe UMN signs. Similarly, 44 (36%), 31 (25%), and 47 (39%) lower limbs of ALS presented respectively with no, mild, and severe UMN signs, and 36 (30%), 39 (32%), and 47 (39) lower limbs of MSA respectively showed no, mild, and severe UMN signs.Severity of the UMN sign was not significantly different between ALS and MSA. 3.2p < 0.001, χ2-test). Neither FDI-CMCT nor TA-CMCT were correlated with the Barthel Index significantly .In contrast with the clinical UMN signs, CMCT was more abnormal in ALS patients than in MSA patients . Specifi3.31,217 = 22.78, p < 0.001; UMN sign: F2,217 = 6.52, p = 0.002) and TA-CMCT . Interaction between them was significant for TA-CMCT , but not for FDI-CMCT . The covariate (height) was significant for TA , but not for FDI . Post-hoc analyses were conducted for each disease. With FDI-CMCT of ALS, a one-way ANOVA revealed a significant main effect of UMN sign , and patients with severe UMN sign had longer CMCT than those without UMN sign . Similarly, TA-CMCT of ALS was affected significantly by the UMN sign , but the difference among degrees of UMN sign were only marginal . With FDI-CMCT of MSA, the ANOVA revealed a significant main effect of UMN sign . Findings indicate that MSA patients with severe UMN sign had longer CMCT than those without UMN sign . TA-CMCT did not differ across different degrees of the UMN sign in MSA .3.4p = 0.001 (FDI) and < 0.001 (TA), χ2-test). Differences in the MSA subtype had no influence on CMCT test results (p = 0.776 (FDI) and 0.879 (TA), χ2-test, In the ALS patients, onset body-part affected the CMCT results. For the bulbar-onset ALS patients, abnormal CMCT was less likely for both FDI and TA . Also, p3.5p-values were 0.879 (FDI-CMCT and APB-CMAP), 0.955 (FDI-CMCT and APB F-latency), 0.574 (TA-CMCT and AH-CMAP), and 0.644 (TA-CMCT and AH F-latency).Correlation analysis between CMAP or F-latency and CMCT turned out to be insignificant. The 4We explored relations between clinical UMN signs and CMCT in ALS and MSA. The main findings were that (1) ALS and MSA patients showed clinical UMN signs with similar frequency and severity, and that (2) CMCT was more abnormal in ALS than in MSA. The onset body part was associated with CMCT abnormality in ALS, but MSA subtype was not.4.1Results show that profiles of the UMN signs were similar in ALS and MSA, as indexed by the UMN score. Evidence shows that the UMN signs are observed in around 40–70% of ALS patients , and tha4.2In stark contrast to the clinical signs, the CMCT testing results were different between the two diseases. Indeed, earlier studies failed to document degeneration of the UMN in MSA using physiological or neuroimaging measures . Sobue eWhy are the UMN signs and results of the CMCT testing incongruent between ALS and MSA? One might consider involvement of the LMN dysfunction. With foraminal stimulation, the calculated CMCT includes conduction between the motoneuron and the foramen, and it is possible that pathology here contributes to the longer CMCT in ALS. Alternatively the difference in CMCT could reflect different pathologies of the pyramidal tract in ALS and MSA. Large myelinated fibres comprising the direct cortico-motoneuron system are considered the main target of degeneration in ALS , whereas4.3Interestingly, CMCT was prolonged or inexcitable in ALS patients even without UMN signs, especially in the upper limb. Such discrepancy can be resolved by incorporating at least two factors. The first is the fact that very severe lower motor neuron (LMN) signs sometimes conceal co-existing UMN signs. The most conspicuous example would be the primary progressive atrophy, a subtype of ALS, for which autopsy often reveals degeneration in the corticospinal tract in spite of absent UMN signs throughout the clinical course . Such maIn comparison with FDI-CMCT, TA-CMCT was not found to be significantly different across the severity of the UMN signs. One possible explanation for this finding is that CMCT estimated by the peripheral motor conduction time with the foraminal stimulation overestimates the central component. Prolonged TA-CMCT might be explained by the LMN signs of the leg. Another consideration would be the composition of the corticospinal tract. Evolutionally speaking, the descending pathway in the hand contains more direct corticospinal fibres than the leg . Such diResults show that ALS patients with different body parts as the onset site presented with different CMCT findings. It is quite straightforward that bulbar-onset ALS patients showed CMCT abnormality less frequently because the test was performed with the upper and lower limb. Objective tests must be developed to elucidate UMN degeneration in the cortico-bulbar tract.Because CMCT measurements with the foraminal stimulation are contaminated by conduction from the motoneuron to the foramen, we looked for a correlation between the nerve conduction findings and CMCT in the ALS patients. There was none, but unfortunately the nerve conduction studies were not performed on the same muscles as CMCT. This issue requires further confirmation in future studies.4.4CMCT can increase the chance of detecting degeneration of the corticospinal tract in the absence of clinical UMN signs. A neuroimaging study partially confirmed this notion by showing correlation between CMCT and parameters of diffusion tensor imaging associated with white matter degeneration . Abnorma4.5This study has several limitations mainly originating from the retrospective nature. Some demographic factors are different between ALS and MSA: The ALS patients were older than the MSA patients; the MSA patients were taller and had longer disease duration. We have no relevant neuroimaging or neuropathological results to confirm fibre-type difference in degeneration of the corticospinal tract. Other TMS parameters including motor thresholds and MEP amplitude could not be extracted in a comprehensive manner. Also, CMCT calculation using the F-wave latency was not available in the present study. These issues must be addressed in future prospective studies.5In conclusion, CMCT testing revealed differential abnormality between ALS and MSA with similar profiles of the clinical UMN signs. Pathological differences might underlie the physiological distinction. Future research including investigations of autopsy findings and longitudinal observations is warranted.10.13039/100016163Kanae Foundation for the Promotion of Medical Science to YS. Part of this paper was submitted as a thesis by JO to the 10.13039/100005688Graduate School of Medicine, the University of Tokyo.This work was supported by JSPS KAKENHI Grant No JP 21K07454 (YS) and 22K07534 (MH), and by a grant from the 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.


Stiffness) based on the estimated joint torque and the estimated elbow angle. Finally, novel Stiffness scales  for upper limb functional assessment in the two performed test scenarios were proposed. The stiffness scales showed an exponentially increasing trend with increasing movement tempo, as well as with increasing weights. The obtained general Stiffness patterns from the group of participants without sensorimotor disorders could significantly contribute to the further monitoring of motor recovery in patients with sensorimotor disorders.The ultimate goal of rehabilitation engineering is to provide objective assessment tools for the level of injury and/or the degree of neurorehabilitation recovery based on a combination of different sensing technologies that enable the monitoring of relevant measurable variables, as well as the assessment of non-measurable variables . This paper aims to present a feasibility study for a general assessment methodology for subject-specific non-measurable elbow model parameter prediction and elbow joint stiffness estimation. Ten participants without sensorimotor disorders performed a modified “Reach and retrieve” task of the Wolf Motor Function Test while electromyography (EMG) data of an antagonistic muscle pair (the triceps brachii long head and biceps brachii long head muscle) and elbow angle were simultaneously acquired. A complete list of the Hill’s muscle model and passive joint structure model parameters was generated using a genetic algorithm (GA) on the acquired training dataset with a maximum deviation of 6.1% of the full elbow angle range values during the modified task 8 of the Wolf Motor Function Test, and it was also verified using two experimental test scenarios (a task tempo variation scenario and a load variation scenario with a maximum deviation of 8.1%). The recursive least square (RLS) algorithm was used to estimate elbow joint stiffness ( Functional assessment is a basic and indispensable component of neurorehabilitation that identifies sensorimotor deficits in patients, determines priorities, and plans therapeutic protocols, i.e., it monitors the effects of therapy. Clinical scales such as the Fugl-Meyer Assessment (FMA) and the Wolf Motor Function Test (WMFT) are frequently used to assess motor functionality in patients after stroke ,2. HowevAmong non-measurable variables, the human ability to adequately generate an interaction force is recognized as one of the basic parameters for the analysis of human movement dynamics and its application in neurorehabilitation. Pathological conditions, such as post-stroke, lead to a reduction in joint stiffness and force due to the improper activation of antagonist muscle pairs. While several studies have investigated how to detect the rotational stiffness of lower-limb joints during locomotion, exploiting the cyclicity of gait or implementing musculoskeletal models driven by muscle activity, less attention has been given to the real-time estimation of upper limb stiffness modulation during non-cyclic movements .Basic approaches have been proposed to estimate joint stiffness and force during human arm movement . StiffneA common method for estimating joint stiffness during small movements of the human arm using a linear model was proposed by Perreault ,11. ThisNonlinear models of the human arm require modeling of the musculoskeletal system, which is predominantly based on Hill’s muscle model and the passive joint structure model ,19. ThisThe research performed in this paper takes into account the nonlinearity of human muscles and considers a stiffness estimation method based on Hill’s muscle model and the passive joint structure model, resulting in a complete list of verified model parameters during the elbow flexion/extension task, as well as elbow stiffness curves  for different task tempos and loads. It is worth noting that our approach provides continuous estimation of stiffness in time, which is highly beneficial for human–robot interaction tasks ,29 and fTen healthy volunteers without sensorimotor disorders participated in the study: 5 males (age 33.6 ± 4.27) and 5 females (age 28 ± 9.35). The participants verbally confirmed that they had no previous injuries to the elbow joint, nor did they currently feel any discomfort. Before the experiment, the selected body segment parameters (BSP) of each participant were measured using the Hanavan model of the human body  Table 1Table 1.cm), and the moment of inertia (M) of the forearm-hand segment. The estimated parameters were used as input parameters for Hill’s muscle model and the passive joint structure model  of the forearm–hand segment, the distance from the elbow joint axis to the center of the forearm mass  . In the All participants were subjected to the same experimental conditions. Each participant was instructed to move their hand while holding the weight from the starting position to a position that corresponded to the maximum flexion of the user’s elbow (the range of elbow motion was approximately from 0° to 150°), i.e., touching the chest with the hand. The far-right position of the “moving dot” on the feedback monitor corresponded to an outstretched human arm , while the far-left position corresponded to maximum flexion at the elbow. The participants were instructed to avoid pushing the weight against the table and lifting the weight. Friction between the weights and the table was ignored due to the rigid, smooth finish and different materials. The weight was made of stainless steel and the table had a veneer top.m), included: (1) attempting to push the weight across the table by flexing the elbow and (2) attempting to push the weight across the table by extending the elbow.The overall performed task, the modified task 8 of WMFT  system was used for the data acquisition of: (1) surface EMG activity of two antagonistic muscle pairs of the upper arm (triceps brachii long head and biceps brachii long head muscle) and (2) the angle in the elbow. Trigno Avanti Duo EMG units  were used for EMG recordings and a goniometer  with Trigno Avanti Goniometer Adapter Sensor  was used for angle measurement. The positions of all sensors are shown in During the task activity, the TrignoMaximum voluntary contraction (MVC) data acquisition for the triceps brachii long head and biceps brachii long head muscle against static resistance ,34,35,36m rotation (while pulling the 0.5 kg weight) of the elbow joint following the tempo of the “moving dot” shown on the feedback display. The tempo of the “moving dot” was set to 15 beats per minute (bpm), 30 bpm, 45 bpm, and 60 bpm and it was changed for each 10 WMFT8m movement, respectively. This phase was used for estimating the parameters of Hill’s model  of the elbow joint following the tempo of the “moving dot” shown on the feedback display. The tempo of the “moving dot” was set to 15 bpm, 30 bmp, 45 bmp, and 60 bmp. The participant repeated the WMFT8m movement for each tempo 10 times in three series. The resting pause between series was 1 min. The resting pause between different tempos was 5 min.Task frequency variation experiment (E1). In the beginning, the participant’s arm was in the initial position A. The pam rotation of the elbow joint following the tempo of the “moving dot” shown on the feedback display. The tempo of the “moving dot” was set to 30 bmp. The participant repeated the same WMFT8m movement with different “pulling” weights: 0.25, 0.5, 0.75, and 1 kg. The participant repeated the WMFT8m movement for each weight 10 times in three series. The resting pause between series was 1 min. The resting pause between different weights was 5 min.Load variation experiment (E2). In the beginning, the participant’s arm was in the initial position A. The paThe overall experimental scenario included the following phases:The experimental design was approved by the ethical review board of the University of Belgrade—School of Electrical Engineering. Participants were well-informed about the noninvasive protocol, and they signed informed consent forms.The acquired EMG and MVC signals from antagonistic pairs were processed to achieve muscle activation. First, the EMG and MVC signals were filtered using the Butterworth bandpass filter  and the Butterworth Notch filter . The filtered EMG and MVC signals were rectified, giving the Processed EMG signal , left anu(t) . Muscle ion time , as suggion time , given iAn example of the specific measurement of the Processed EMG signal and its envelope data for E1 and E2 belonging to participant 9 is presented in p), damping torque (τd), and gravity torque (τg) based on the estimated joint angle (q) and velocity (J) is defined as the sum of torques coming from the antagonistic muscle pair  and passive joint structures . GA adjusts the parameters of Hill’s muscle model for the muscle pair and passive joint structures by taking into account the difference between the measured joint angle  and the estimated joint angle (q). The RLS algorithm was used to estimate the joint stiffness (Stiffness) based on the estimated joint torque τJ and the estimated joint angle q. The following sections will provide more details on all assessment modules.m), while the coupling force F will increase the length of the muscle.A typical and widely used representation of the muscle is Hill’s muscle model  Figure . The modCE) is given in Equations (2)–(4):The force generated by CE (Fp) and damping (Fd) force (Equation (5)).The total force p, given in Equations (6) and (7):d is given in Equation (8):The muscle can act as a spring and has a nonlinear characteristic. The spring nature of the muscle is modeled as stiffness with its force FSE is given in Equations (9) and (10):The tendon connects muscle and bone and is modeled as SE. The force in the muscle tendon FHaving in mind muscle representation given in Equations (2)–(10), the actual muscle fiber length The joint torque Passive joint structure implies stability in the musculoskeletal model ,40. The The total joint torque According to Newton’s Second Law for rotation, Equation (16), the joint angular velocity goni) and the estimated joint angle (q). Thus, one combination of coefficients in GA notation is one individual. Each individual consists of chromosomes and represents a unique solution within the solution space. For GA, in this paper, each chromosome represents one parameter. Accordingly, the initial values of these parameters and their ranges are defined and encoded into GA using the actual value of the chromosome representation. The population of the designed GA is represented by a set of 20 individuals. By testing GA with different numbers of individuals in one population, it was concluded that 20 individuals are a good compromise between the complexity of GA, its execution time, and optimization quality. To cover the complete solution space, a uniform distribution of individuals was used to generate the initial population. The fitness function defined by Equation (22) was evaluated for each individual per generation:goni is the joint angle measured using a goniometer, q is the estimated joint angle according to Equation (21), GA is defined as a multi-objective optimization approach that aims to calculate the optimal combination of Hill’s and the passive joint structure model parameters  individuals were created using the crossover operator. Other children were defined using the mutation operator or were elite individuals. Two individuals with the lowest values of the fitness function in the current generation  were selected and directly included in the next generation to accelerate the convergence of the GA to the optimal solution. To create new combinations of parameters  that differed from the existing ones, the mutation operator was used. Mutation provides genetic diversity, allows the GA to search a wider space, and can take individuals out of a local minimum and move them towards a global one. The mutation operator added a Gaussian distributed random value to a chromosome gene. If it fell outside the lower and upper limits for the gene, the new value of the gene was truncated. The imposed condition for stopping the GA was heuristically obtained since the change in the best value of the fitness function F was not greater than ga within the Matlab Global Optimization toolbox. The ga function contained: an objective (fitness) function that is given in Equation (22); the number of variables set to 24 (the number of Hill’s and passive joint structure model parameters); ‘PopulationSize’ set to 20 individuals; ‘SelectionFcn’ set to ‘selectionroulette’; ‘EliteCount’ set to 2; and ‘CrossoverFraction’ set to 0.7. The values of the Hill’s and passive joint structure model parameters given in papers [A PC platform with an Intel(R) Core(TM) i7-9700F CPU at 3.00 GHz and 64.0 GB RAM was used for the optimization procedure. The software used for the Hill’s and passive joint structure models was the Matlab2022 (license: Matlab Campus-Wide 2022) package Simulink. The Hill’s and passive joint structure model parameters were estimated using genetic algorithm functions n papers ,26,27,28n papers ,26,27,28goni) in the Training phase (described in goni) from the Training phase and the estimated joint angle (q) were compared using Dynamic Time Wrapping (DTW) [goni). The Training GA output verification is represented by the obtained DTW value divided by the number of samples.The measured joint angle (qng (DTW) . DTW givStiffness) in each time sample Analogously to the approach presented in ,43, the posed in  and givegoni) and the estimated joint angle (q) to quantify the estimation error. Finally, fitting curves  for different task frequencies (Stiffness (tempo) in E1) and different weights (Stiffness (weight) in E2) were defined.The data acquired in E1 and E2 were used for designing novel functional scales. First, the parameters of the Hill’s and passive joint structure models estimated in the Training phase were applied to the acquired data in E1 and E2. Second, Dynamic Time Wrapping (DTW)  was perfAG(t)) triceps brachii long head (aANT(t)) and the measured elbow joint angle (qgoni) from the Training phase were used as inputs in the Hill’s and passive joint structure models. The range values  of the Hill’s and passive joint structure models’ parameters for the elbow joint for each parameter were calculated as the boundary values (minimum and maximum) of all values estimated for all participants for each parameter.goni) and estimated (q) angles in the elbow joint (DTW divided by the number of samples) for 10 participants.Verification of the accuracy of the Hill’s model and passive joint structure parameter estimation was performed using the DTW algorithm  and standard deviation (shaded area) of these signals were obtained by overlapping all WMFT8m movements and their normalization with the time: (A) measured (qgoni) and estimated (q) elbow joint angles; (B) estimated stiffness value (Stiffness); and (C) estimated total joint torque value   see , while fm movements and their normalization with the time. Using the boxplots, the stiffness behavior for each tempo for all 10 participants is shown in The comparative analysis of the stiffness value through different tempos in task E1 is presented in A stiffness fitting curve  for different task tempos m movements and their normalization with the time. Using the boxplots, the stiffness behavior for each load for all 10 participants is shown The comparative analysis of the stiffness value through different loads in task E2 is presented in Stiffness fitting curves  for different “pulling” weights Stiffness functional scale  that is useful for the further neurorehabilitation follow-up of patients.This paper presents a novel methodology for elbow joint stiffness estimation in people without sensorimotor disorders during different movement scenarios regarding movement tempo and the upper limb load. The overall research goal of the paper is to define a mopt, lts, lms) are presented in [max values are given in [mopt, lts, lms, Fmax, Considering that the musculoskeletal system of the upper limb is a nonlinear model, Hill’s muscle model and the passive joint structure model are convenient for use in such research ,19. One ented in ,26,27,28given in ,24,27,28given in ,27, af vented in , and vmagiven in ,28. In tCavallaro et al.  and ZhaoDue to the variability in biological mechanisms and experimental conditions, we qualitatively compared the stiffness evolution in our work with results from the relevant literature in cases where the human arm is moving with different velocities and where it is acting against different forces. Humans perform interaction tasks with ease and precision by modulating their mechanical stiffness. It is intuitively expected and proven in the literature that the co-contraction of antagonistic muscle groups  depends on velocity  or load The stiffness estimation in tasks E1 and E2 is presented in This paper introduced a general assessment methodology for elbow joint stiffness estimation based on Hill’s muscle model and the passive joint structure model, and a genetic optimization procedure during the “Reach and retrieve” task that is conventionally used within neurorehabilitation testing. The model parameters were estimated using the short-term tempo ramp scenario, and then, verified in two independent scenarios, resulting in 6.1% and 8.1% errors for the training and test datasets, respectively. The estimated joint stiffness in the two long-term test scenarios (the first one with tempo variation and the second one with load variation) was used for creating elbow stiffness curves to represent the general pattern of motor behavior in the population without sensorimotor disorders. The proposed objectification criteria of motor behavior in the form of stiffness patterns could significantly contribute to the monitoring of motor recovery in patients with sensorimotor disorders. A comparison to the results obtained using the proposed model with existing clinical scales  would be of interest for future work, as would further automatization of the overall system using collaborative robot-based approaches. Understanding human stiffness patterns and stiffness monitoring is a prerequisite for the development of rehabilitation devices based on collaborative robots capable of imposing recommended stiffness patterns, on the one hand, and monitoring Cartesian stiffness in contact tasks, on the other hand. Future research will exploit the presented methodology in clinical studies for assessment of the rehabilitation process with a larger number of participants.


This work aimed to explore the influence of four different cooking methods  on the sensory characteristics of scallop muscles. Headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) and electronic nose (e-nose) were combined to analyze the aroma of scallops. Combined with the results of free amino acids and electronic tongue (e-tongue), the taste changes of different samples were analyzed. Furthermore, texture profile and microstructure analysis jointly showed the influence of cooking methods on texture. The results showed that frying was the most suitable cooking method for scallop muscle because it resulted the best tasted products, boiled scallops retain the highest similarity to fresh scallops. Besides, a higher level of lipid oxidation and Maillard reaction resulted in significant increase in aldehydes, ketones, furans, umami, and sweet amino acid. For the boiled sample, the loss of water-soluble compounds and less fat oxidation resulted in fewer flavor substances and free amino acids, along with looser organizational structure and poorer sensory quality. The research showed that besides the texture of scallop muscle, volatile organic compounds and free amino acids as well as their mutual roles in taste and smell were also important to sensory receptivity. Argopecten irradians, Patinopecten yessoensis, and Chlamys farreri are the three major scallops produced in the coastal areas of China  and corn oil were purchased from a local supermarket in Baoding, Hebei, China. Chemicals, such as sulfosalicylic acid, sodium citrate and ninhydrin were obtained from Sinopharm Chemical Reagent Co., Ltd. . The mixed amino acid standard solution  was purchased from Sigma-Aldrich Chemical Co. .Fresh scallops . For boiling cooking, the sample was heated in boiling water for 10 min (BS). The roasted scallops (RS) were prepared by dry roasting inside a preheated oven (200°C) for 10 min; the samples were turned over at the fifth min. Scallops were fried in a pan containing preheated corn oil (150°C) for 6 min (FS). Microwaved scallops (MS) were obtained by heating them in a microwave oven at 400 W for 2 min. After cooling, all the samples were packed in zip-lock aluminum bags and kept in a fridge until further analysis.®, G.A.S., Dortmund, Germany) was used to analyze the volatile compounds of scallop muscle following the method of Li et al. (Headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS)  was used as reference to identify the retention index (RI) of the substance. Then, RI and drift time (DT) were compared with GC × IMS Library.The method of Zhang et al.  was usedThe PEN-3 electronic nose  was used to differentiate the flavor of raw scallop muscle from that of the scallop muscles cooked in four different ways. The e-nose had 10 metal receptors in total. Each receptor was sensitive to a specific type of substances. Sample (2.0 g) was cut into 2 mm × 2 mm pieces and put into a 20 mL glass bottle; after incubation at 60°C for 10 min, testing was done for 120 s. The e-nose was cleaned before each testing.The SA-4028 electronic tongue  was used to differentiate the taste of raw scallop muscle from cooked samples. Accurately weighed (10 g) cut sample was mixed with deionized water at 1:8 ratio and homogenized  for 2 min at 32,000 r/min until well mixed. Supernatant was collected after centrifugation at 10,000 × g for 10 min, which was used for e-tongue analysis. The electronic tongue used sensors to detect soluble substances in the liquid sample to generate a signal response value of each sensor for analysis .Ten trained tasters  were selected to assess sensory characteristics. Each taster had an independent space and was not disturbed by another taster. The scallop muscle sample was presented in a clean and transparent cup with a random 3-digit code. After each tasting, the panelist was normalized their mouth by a bite of biscuit and then cleaned with water. Scores were given for odor, taste, texture, and appearance; the average score from all the panelists was considered for the data analysis.Using TMS-Pro texture profile analyzer  with a cylindrical probe (50 mm dia.), texture parameters were analyzed . The meaP < 0.05 as the significant difference. Origin 2021 was used to conduct radar map-based visual analysis of the samples. Advanced Heatmap Plots was performed using the OmicStudio tools from https://www.omicstudio.cn. Main component analysis was performed using https://www.chiplot.online/. Correlation analysis and graphic presentations were generated using the R “corrplot” package . The significance of the differences was conducted with Duncan multiple comparison method, considering  package . For corHeadspace-gas chromatography-ion mobility spectrometry was used to identify the volatile organic compounds in scallop muscle and analyze the change in flavor components among different samples. By testing and analyzing through HS-GC-IMS , the volAldehydes were mainly generated from lipid oxidation and protein degradation, with the lower odor thresholds and having bigger influence on scallop flavor . AldehydKetones are mainly from lipid oxidation . The conThe main flavor substances in scallop muscles at the cooking stage were aldehydes and alcohols . HoweverEsters provide sweet and fruit flavors; for example, ethyl hexanoate, ethyl acetate, and ethyl butyrate . Esters The principal component analysis method was used to develop the spatial distribution map, as shown in The principal component analysis method was used to develop the spatial distribution map  of diffeThe radar map for the sensory assessment of scallop muscle cooked by different ways is shown in The TPA method was used to simulate the secondary chewing process in human oral cavity and analyze the influence of different cooking methods on the taste of scallop muscle. The roasted sample was much harder and chewier than the other three samples; also, it was much more elastic than the boiled sample .We used the scanning electron microscopy to observe the microstructure of the section of scallop muscle cooked in different ways. The muscle fibers in the control sample were arranged most loosely, while the seams among muscle bundles notably shrank after heating during cooking by different methods, probably caused by the loss of water during heating . The musTaste, volatile, and texture are important factors affecting the sensory assessment of foods. One physicochemical indicator cannot reflect the cross-effect of these factors on sensory . So, we P < 0.05) showed the correlation between the e-nose metal receptor signals and the concentration of flavor substances. Significant correlation appeared in W1W and W2W metal receptors; W1W metal receptor (Sensitive to many terpene and organic sulfur compounds) showed a significant positive correlation with octanal, 3-methylthiopropanal, 2-butanone, 4-methyl-2-pentanone, 5-methyl-2-furanmethanol, 2-methyl-1-pentanol, 3-methyl-3-buten-1-ol, 2-octanol, ethyl hexanoate, ethyl butyrate, isopropyl acetate, propanoic acid, 2-butoxyethanol, 3-butenenitrile, and 2-pentyl furan, while W2W metal receptor (Sensitive to aromatic compounds and organic sulfide) was significant positively correlated with octanal, 3-methylthiopropanal, 2-butanone, 4-methyl-2-pentanone, 5-methyl-2-furanmethanol, 2-octanol, isopropyl acetate, propanoic acid, and 2-butoxyethanol. Such compounds affected the e-nose results to a larger degree.The results of the e-nose and the correlation heat map for volatile organic compounds identified through HS-GC-IMS (P < 0.05), the contents of Asp, Thr, Ser, Glu, Gly, Ala, Cys, and Arg had significant positive correlation with the umami signal and convergence signal of e-tongue, and was negatively correlated to the sweet signal of e-tongue. The acid signal of e-tongue was negatively correlated with Asp, Thr, Ser, and Arg, while positively correlated with Met, Phe, Lys, and Pro. The aftertaste signal of e-tongue was negatively correlated with Gly, Ala, Met, Ile, His, Lys, and Pro, while positively correlated with Arg. Besides, Phe and Lys were negatively correlated with the umami signal; Arg was positively correlated with the umami signal; His and Arg were negatively correlated with the sweet signal; Phe was positively correlated with the sweet signal; all the 17 free amino acids had no significant correlation with the bitter and salty signals of e-tongue.Many researches showed that free amino acids (FAAs) were positively correlated to taste . AccordiP < 0.001) with the umami signal of e-tongue. Glu was positively correlated with the sensory score of taste and overall sensory score . Besides, as shown in P < 0.01)  , 31.r| ≥ 0.7, P < 0.05). Among the 48 volatile flavor compounds separated through HS-GC-IMS, 30 compounds were correlated with sensory scores. Among them, 23 flavor compounds, including benzaldehyde, heptanal, and 2-pentyl furan, were positively correlated with the sensory score of odor; pentanal was negatively correlated with the sensory score of odor; 23 flavor compounds, including octanal, and heptanal were positively correlated with the sensory score of taste; 23 flavor compounds, including octanal, and benzaldehyde were positively correlated with overall sensory scores. Eight of the 17 free amino acids were significantly correlated with the sensory scores. The contents of Ala, Glu, Arg, Ser, Gly, and Cys were positively correlated with taste, odor and overall sensory scores. Besides, the content of Pro and Asp were positively correlated with the sensory score of odor, while the content of Pro was positively correlated with the overall sensory score. E-nose sensor W1W was positively correlated with the overall sensory score. Only the aftertaste-B signal of e-tongue was negatively correlated with the sensory score of taste. As the sensory score of structure had no significant correlation with other indicators, it was not indicated in the figure.r| ≥ 0.7, P < 0.05). However, sweet free amino acids, including Gly, Thr, Ser, and Ala were negatively correlated with the sweet results of e-tongue (P < 0.001), probably related to the limitations of e-tongue. Shen et al.  (| n et al.  pointed n et al. .Interestingly, some researches showed 3-methylthiopropanal was able to positively activate human T1R1/T1R3, the taste receptor of umami . In thisThis research provided a comprehensive method that uses HS-GC-IMS, e-nose, e-tongue, sensory analysis, and free amino acid tests to identify the sensory characteristics of scallop muscle cooked in different ways. It also explained the differences of taste among samples through texture profile and microstructure analysis. Overall results showed that fried scallop had the best sensory score, probably because of the significant increase in aldehydes and ketones, caused by a higher degree of lipid oxidation and Maillard reaction as well as the increase in furans, umami, and sweet free amino acids. Boiled scallop had the lowest sensory score, probably related to the decrease in sweet and umami amino acids, caused by the loss of water-soluble compounds and fewer contents of volatile organic compounds. The interactions between senses of smell and taste resulted from volatile organic compounds and free amino acids were crucial to the formation of the sensory quality of scallop.The original contributions presented in this study are included in the article/YW and JG conceived and designed the study. YW performed the experiments, analyzed the data, and wrote the manuscript. ZW and KM performed the statistical analysis. GT, JG, BC, and XB contributed to revisions of the manuscript. YS, JG, XB, and JL projected administration. All authors have read and approved the manuscript.


Dietary phenolic compounds must be released from the food matrix in the gastrointestinal tract to play a bioactive role, the release of which is interfered with by food structure. The release of phenolics (unbound and bound) of cold and hot extruded noodles enriched with phenolics (2.0%) during simulated in vitro gastrointestinal digestion was investigated. Bound phenolic content and X-ray diffraction (XRD) analysis were utilized to characterize the intensity and manner of starch-phenolic complexation during the preparation of extruded noodles. Hot extrusion induced the formation of more complexes, especially the V-type inclusion complexes, with a higher proportion of bound phenolics than cold extrusion, contributing to a more controlled release of phenolics along with slower starch digestion. For instance, during simulated small intestinal digestion, less unbound phenolics (59.4%) were released from hot extruded phenolic-enhanced noodles than from the corresponding cold extruded noodles (68.2%). This is similar to the release behavior of bound phenolics, that cold extruded noodles released more bound phenolics (56.5%) than hot extruded noodles (41.9%). For noodles extruded with rutin, the release of unbound rutin from hot extruded noodles and cold extruded noodles was 63.6% and 79.0%, respectively, in the small intestine phase, and bound rutin was released at a much lower amount from the hot extruded noodles (55.8%) than from the cold extruded noodles (89.7%). Hot extrusion may allow more potential bioaccessible phenolics (such as rutin), further improving the development of starchy foods enriched with controlled phenolics. Dietary phenolic compounds have attracted increasing attention in modulating the blood glucose, cholesterol, and radical scavenging activity, against certain chronic diseases such as type-II diabetes, cardiovascular disease, obesity, and cancer ,2,3. HowAs for phenolic-enhanced starchy foods, starch digestion is accompanied by the release of phenolic compounds. A slow digestion rate and a low digestibility of the starch matrix were related to a controlled release of phenolics ,6. BasedDifferent from a model system with mixed starch and phenolics in a gel , specialIn this study, noodles supplemented with starch and phenolic extract (2%) with different forms of phenolics were prepared using cold and hot extrusion. Extruded noodles were in vitro digested, and the release of total phenolics, including predominant profiles, from the extruded noodles was monitored during digestion. A possible mechanism of phenolic release was introduced to assist the understanding of how the bound phenolics can be controlled during release, further improving their bioaccessibility.Dehulled buckwheat flour was purchased locally . Buckwheat hull was purchased from Farmers Mill Ltd. . Pepsin , pancreatin , amyloglucosidase (AMG)  were from Sigma, New York, NY, USA. Folin-Ciocalteu reagent (2 N) was obtained from Sigma, St Louis, MO, USA. All chemicals used were of analytical grades.w/v), and the starch was sedimented within 2 h. The excess water was dumped, followed by centrifugation at 3500× g for 10 min in a centrifuge . The brown layer on top of the pellet was scraped off. This process was repeated 5 times. The remaining pellet was lyophilized  and ground using a grinder with a 500 µm sieve. The AACC Methods of 46-10 [Starch was extracted from the buckwheat flour using the method described by Cho, et al. . Since dof 46-10 , 30-10 [of 46-10 , and 08-of 46-10  were usew/v) was subjected to ultrasound-assisted extraction (ultrasonic frequency of 59 KHz and power of 500 W) for 30 min and then centrifuged at 2500× g for 10 min. The supernatant was collected and evaporated to remove ethanol. Samples were freeze-dried and stored at −20 °C.Phenolic compounds were extracted from the buckwheat hull (with a higher content of phenolics than bran and flour ). ComparThe phenolic extract  was pre-dissolved in distilled water, and then the buckwheat starch was blended with the solution to adjust the moisture content to 35%, followed by equilibration at 4 °C overnight. The blend was extruded into starch-phenolic noodles using a twin-screw extruder  with the ratio of screw length to diameter (L/D) of 20:1 and the diameter of the die nozzle was 3 mm. Cold (CE) and hot extrusion (HE) were carried out under the temperature of 40-40-40-40-40 °C (I–V zones) and the temperature of 40-65-90-90-90 °C (I–V zones), respectively. The screw speed was 100 rpm, and the feed rate was 20 g/min. Control samples were prepared using starch only. The buckwheat starch was blended with distilled water , followed by equilibration at 4 °C overnight. The extrusion conditions of control samples were the same as those of phenolic-enriched noodles. The noodles were stored at −20 °C before analysis, considering the possible retrogradation of starch at room temperature or 4 °C  on cold −1 with a scanning step of 0.01° [RC) and that of V-type crystallites (RCv) were calculated using the OriginPro 9.0.0 Software  according to Equations (1) and (2). The proportion of V-type crystallinity (Pv) was calculated according to Equation (3):c, Aa, and Avc are the integrated areas of all the crystalline peaks, amorphous region, and V-type crystalline peaks on the XRD pattern.The crystalline structure of non-extruded starch and extruded noodle powders were monitored using an X-ray diffractometer  using Cu-Kα radiation at 40 kV and 40 mA. The diffractograms were obtained over a scattering range (2θ) range of 5–40° at a scanning speed of 20° minof 0.01° . All meaExtruded noodles were in vitro digested as described previously . ExtrudeRDS), slowly digestible starch (SDS), and resistant starch (RS) [20 and G120 represent the glucose contents of hydrolysis within 20 and 120 min, respectively; F refers to the content of free glucose; T is the total weight of starch.Rapidly digestible starch (rch (RS)  were calt (%) is the percentage of starch in the noodles digested at time t (min), and C∞ (%) is the predicted digestibility at the end of the reaction; k (min−1) represents the rate coefficient of the enzyme hydrolysis. A logarithm of slope (LOS) plot (Equation (8)) was obtained by expressing the first derivative of the first-order equation in logarithmic form Equation (7).k and C∞ were used to construct model-fit starch digestion curves according to Equation (7).The hydrolysis kinetics of extruded noodles with unbound and bound phenolics, bound phenolics only were fitted to the first-order kinetic model  as shownThe morphologies of uncooked, cooked, and digested  noodles were characterized following the method of Wang, Li, Chen, Hui, Tang and Wei . The noow/v), followed by centrifugation at 2000× g for 10 min. The supernatants were collected and concentrated for the analysis of the unbound phenolic content (UPC), while the remaining precipitates were used to extract the bound phenolics. The precipitates were hydrolyzed in 4 mol/L sodium hydroxide solution  for 2 h . Then, the hydrolysates were centrifugated at 15,000× g for 30 min. The supernatants were concentrated for the analysis of bound phenolic content (BPC). The phenolic content was determined according to the description of Singleton and Rossi [−1)’. Total phenolic content (TPC) was calculated by unbound phenolic content plus bound phenolic content.Uncooked, cooked noodles and digestion residues  were extracted three times with 80% methanol  of the rutin, vitexin, and hyperin from phenolic-enhanced noodles represent the number of phenolic profiles released after simulated gastrointestinal digestion that could become available for absorption into the systemic circulation [Cr is the total phenol content (mg/100 g) in digestion liquids after in vitro digestion, and C0 is the total phenol content (mg/100 g) before in vitro digestion.The bioaccessibility index (culation . This in3) at a ratio of 10:1:1 (v/v/v). Then, 0.25 mL of the sample extract was mixed well with 2.5 mL of FRAP reagent. Then, the mixture was in incubation at 37 °C for 2 h, followed by the monitoring of absorbance at 593 nm using a spectrophotometer . The iron (II) sulfate (FeSO4) (0 to 1000 μM) was prepared as the standard solution and assayed under similar conditions. FRAP results were expressed as ‘μmol of Fe2+ per gram dry weight (μmol Fe2+/g DW)’.Ferric reducing antioxidant power (FRAP) analysis was measured based on the method  to characterize the antioxidant activity of extruded noodles and residues during in vitro gastrointestinal digestion. FRAP reagent was prepared with a mixture of 300 μM Acetate buffer pH 3.6, 10 mM 2, 4, 6-Tris (2-pyridyl)-s-triazine (TPTZ) in 40 Mm HCl and 20 mM Ferric chloride .All analysis was conducted in triplicate unless stated otherwise. ANOVA and Duncan’s multiple range test were used at a significance level of −1 of UPC, 0.160 mg GAE·g DW−1 of BPC, and 0.623 mg GAE·g DW−1 of TPC. The phenolic extract had a UPC of 284 mg GAE·g DW−1 without bound phenolics (The extracted starch contained 0.463 mg GAE·g DWhenolics . The thrhenolics  and quanhenolics . The staRC significantly decreased from 5.41% to 4.39% (p < 0.05). This suggests that phenolic compounds interfered with the crystalline structure of extruded starch. It is noted that the phenolic molecules caused a slight increase in the relative crystallinity of V-type crystallites (RCv), ranging from 1.14% to 1.24%. On the other hand, hot extrusion almost destroyed native A-type crystallites and induced the generation of new V-type crystallites. XRD patterns of hot extruded noodles with or without 2.0% of phenolics (HE-S and HE-S-P2) lost most peaks representing A-type crystallites, but sharp peaks at 12.8° and 19.6° of 2θ  appeared. Similar to CE noodles, the incorporation of phenolic compounds caused a decrease in RC from 3.25% to 3.05% and an increase in RCv from 2.05% to 2.19%. Meanwhile, the proportion of V-type crystallites increased up to 72.1%. Hot extrusion caused lower RC but higher RCv than cold extrusion. Tao, Zhu, Nan, Jiang and Wang [XRD is an effective technique to characterize the formation of complexes between starch and phenolics, including non-inclusion complexes ,38,39 orand Wang  reportedExtruded phenolic-enhanced noodles showed a relatively low digestion rate and digestibility owing to the inhibitory effects of phenolics on the digestion enzymes (such as α-amylase)  or the pk) (0.0401 min−1) and digestibility (C∞) (98.34%). The main reason is attributed to the faster digestion of the powder samples (UE-S) than extruded noodle samples. Phenolic-enhanced noodles prepared through cold extrusion displayed a significantly lower proportion of RDS (24.12%) and SDS (39.60%) but a higher proportion of RS (36.28%) compared to noodles in the absence of phenolics  (p < 0.05)  decreased significantly when compared with the noodles with starch only , indicating that phenolics caused the lower hydrolysis rate of starch after both cold and hot extrusion. Additionally, HE noodles had a lower hydrolysis rate of starch than CE noodles with corresponding formulas. With the incorporation of phenolics, decreased C∞ values were observed for CE and HE noodles . In other words, the decreased digestibility was caused by phenolics.Compared with cold and hot extruded noodles, cooked unextruded starch showed a higher proportion of RDS (58.77%), a lower proportion of SDS (20.95%) and RS (20.28%), and a higher digestion rate ( < 0.05) . HE nood < 0.05)  showed t2 and B3 chains). However, the leached amylose during extrusion may be responsible for the increase in RS [Compared to cold extrusion, hot extrusion may cause a higher degree of gelatinization  and morese in RS . The gelse in RS . A hypotse in RS  reportedse in RS ,50,51. Tse in RS  and the se in RS . The eff−1 of UPC, respectively, significantly higher than uncooked CE-S (0.163 mg GAE·g DW−1) and HE-S (0.099 mg GAE·g DW−1)   A. The coctively) B. The toctively) C. CookedAlong with gradual starch digestion, the phenolics on the surface, physically embedded and bound in the starch matrix after extrusion, can be released gradually. In turn, the released phenolics can inhibit starch digestion by interacting with digestion enzymes to inhibit enzyme activity, further interfering with the release of phenolics . The rel−1 respectively. At the early stage of small intestinal digestion (within 20 min), 0.625 (48.5%) and 0.301 (43.2%) mg GAE·g DW−1 of UPC were released from CE-S-P2 and HE-S-P2 residues, respectively; with gastrointestinal digestion from 20 min to 120 min (within 100 min), CE-S-P2 and HE-S-P2 residues released 0.254 (19.7%) and 0.113 (16.2%) mg GAE·g DW−1 of UPC respectively. Any remaining unbound phenolics (17.2% in CE-S-P2 and 16.6% in HE-S-P2) may be released completely as gastrointestinal digestion is prolonged. CE-S and HE-S noodles released 0.093 and 0.037 mg GAE·g DW−1 of UPC during the whole gastrointestinal digestion. The phenolic-enhanced noodles released the highest proportion of unbound phenolics within the first 20 min of small intestinal digestion, consistent with the result of Chi, Li, Zhang, Chen, Xie, Li and Bai [There was a sustained drop in the UPC of noodles to a different extent at various stages of starch digestion A. The re−1 of BPC during the whole gastrointestinal digestion. Different from the release of unbound phenolics, both the cold and hot extruded phenolic-enhanced noodles released the highest proportion of bound phenolics within the later 100 min of small intestinal digestion during whole gastrointestinal digestion. Hot extruded phenolic-enhanced noodles displayed a more controlled release of bound phenolics in the gastric and small intestinal phase than cold extrusion. Hot extruded phenolic-enhanced noodles released more bound phenolics in the gastric phase, whereas cold extruded noodles released more in the small intestinal phase. After 120 min of gastrointestinal digestion, a larger proportion of bound phenolics (slower release) remained in residues than unbound phenolics may be attributed to the protection of starch-phenolic complexes [The bound phenolics content (BPC) experienced a gradual release during starch digestion B, which omplexes .In terms of the changes in total phenolics content (TPC) during digestion C, CE-S-PThe changes of rutin, vitexin, and hyperin in the unbound, bound, and total phenolic fractions of extruded noodles and their residues during in vitro gastrointestinal were monitored D–F. AmonBefore digestion, in the unbound phenolic fraction D, the ruIn general, in the unbound fraction, rutin contents experienced a significant decrease for both CE-S-P2% and HE-S-P2% during gastrointestinal digestion, indicating the increased release of rutin D. FollowThe release of rutin in the bound fraction behaved differently from that in the unbound fractions E. In theCE-S-P2 and HE-S-P2, after gastrointestinal digestion for 120 min, had a cumulative release of total rutin of 94.88% and 77.93%, respectively F. As a rApart from the rutin, the vitexin and hyperin in unbound, bound, and total phenolic fractions of CE-S-P2 and HE-S-P2 showed a similar sustained release to rutin during in vitro gastrointestinal digestion. Differently, vitexin and hyperin can be released completely earlier than rutin; for instance, these profiles in the bound fraction could not be detected after gastrointestinal digestion for 20 min to CE-S-P2 and 120 min to HE-S-P2. This may be attributed to the complexation between rutin, vitexin, or hyperin and extruded starch. Owing to different structures and conformation among three phenolic profiles , they maThe bioaccessibility of three major phenolic profiles  from phenolic-enhanced noodles was evaluated based on the bioaccessible content of profiles in the digestion liquids after in vitro gastrointestinal digestion . The biop < 0.05). As phenolics were lost during cooking and released during digestion, phenolic contents of extruded noodles and residues gradually decreased, resulting in decreased FRAP  compared to the corresponding cooked samples (16.609 and 7.882 μmol Fe2+·g DW−1). As digested continuously, CE-S-P2 witnessed a significant decrease in FRAP (16.609-13.708-5.474-2.884 μmol Fe2+·g DW−1), and similar tendency but lower values were observed for HE-S-P2 (7.882-7.413-2.405-1.070 μmol Fe2+·g DW−1). On the other hand, the bound phenolic fractions of uncooked CE-S-P2 and HE-S-P2 were reported with 6.665 and 8.222 μmol Fe2+·g DW−1 of FRAP, respectively. This was significantly higher than that of cooked CE-S-P2 (5.775 μmol Fe2+·g DW−1) and HE-S-P2 (7.452 μmol Fe2+·g DW−1). The FRAP of bound phenolic fractions of digested CE-S-P2 and HE-S-P2 significantly decreased to 1.335 and 3.002 μmol Fe2+·g DW−1, respectively. Hot extruded phenolic-enhanced noodles consisted of a higher content of bound phenolics than cold extruded noodles  and physically embedded inner starch matrix (Form II), as well as bound phenolics forming non-inclusion complexes with amylopectin (form III) or amylose (Form IV) or inclusion complexes with amylose (Form V) . The strExtrusion can disrupt the multi-level structure of starch  , with stThe unbound phenolics embedded on the surfaces of the starch matrix (form I) and physically embedded inner starch matrix (Form II) are preferentially released compared to bound phenolics  , as repoMore unbound phenolics (>80%) and less bound ones (~60%) were released after simulated in vitro gastrointestinal digestion, respectively. A rational design of starch-phenolic complexes can control the release of phenolics and further improve their bioavailability during gastrointestinal digestion. Compared with cold extrusion, hot extrusion induced the formation of more starch-phenolic complexes, especially the V-type inclusion complexes, with a higher proportion of bound phenolics, contributing to slower starch digestion and, thus, a more controlled release of phenolics. A lower proportion of BPC (41.9%) was released from hot extruded noodles than from cold extruded noodles (56.5%). Particularly, a lower proportion of complexed rutin was released from CE-S-P2 into the simulated small intestinal phase than that from HE-S-P2 (89.7% vs. 55.8%). Hot extrusion may allow more potential bioaccessible phenolics (such as rutin) than cold extrusion. Further studies must focus on the relationship between the dynamic structural changes of starch-phenolic complexes and phenolic release in vitro and in vivo gastrointestinal tracts.


Journal of Cross-Cultural Psychology, Best . Another study re-evaluated Hofstede's Values Survey Module (VSM). Using a large dataset across 57 countries, Gerlach and Eriksson observed that the country scores of VSM based on this sample were weakly correlated with those scores obtained in previous studies. Also, the reliability of the VSM was poor in general. These studies echo the question we raised in this Research Topic: how can we enhance the prediction precision of cultural models? There is a clear need to update measures or develop new constructs of cultural dimensions. Meanwhile, the other research groups highlighted new observations on international business, such as cross-cultural leadership , advertising (Liu and Liu), and impulsive buying . Findings from the studies featured in this collection shed light on the effects of culture on consumer behaviors, business communications, transnational marketing, etc. Collectively, the featured research represents key areas as well as identifies problems embedded in the current cultural models. However, much less is known about what kind of new constructs can incrementally unpack cultural differences. How do new constructs affect international business systematically? What is the nomological network of the new constructs? This collection is only one attempt to enrich cross-cultural theorizing. We hope it can spur future studies in deepening our understanding of the evolving dynamics of cultural constructs, and their antecedents and consequences across a variety of domains such as international business and cross-cultural communication.The editorial call for a special issue on revisiting cross-cultural comparison on international business resulted in a number of impressive submissions from researchers in relevant fields. This collection contributes to cross-cultural literature with data from more than 60 countries. In addition, it involves varied and sophisticated methodological approaches including both quantitative and qualitative analyses. Two research groups focused on validating instruments of cultural values. Specifically, one study investigating intercultural adaptation revisited three established scales, the Multicultural Personality Questionnaire, Cultural Intelligence Scale, and the Intercultural Adjustment Potential Scale, and uncovered a new latent structure underlying the combined tests, consisting of five dimensions, namely assertiveness, attentiveness to others, emotional robustness, caution, and self-awareness .The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Donor–recipient diameter discrepancy can be problematic when using an autologous great saphenous vein graft for internal jugular vein reconstruction. A triple-paneled method of saphenous vein grafting is one solution.A 54-year-old man with a thyroid papillary carcinoma underwent total thyroidectomy and bilateral neck dissection. An 8-cm segment of the right internal jugular vein was resected. For reconstruction, a 30-cm segment of the great saphenous vein was harvested and divided into three pieces of equal length. After opening each piece longitudinally, they were sutured together in a side-by-side fashion to create a cylinder that was used to reconstruct the internal jugular vein defect. The graft was patent 10 months after the surgery.The triple-paneled method is feasible for autologous great saphenous vein graft reconstruction of the internal jugular vein.The online version contains supplementary material available at 10.1186/s12957-023-02902-4. Simultaneous resection of both internal jugular veins (IJVs) can cause acute reduction in cerebral venous drainage and result in blindness, inappropriate anti-diuretic hormone hypersecretion, cerebral edema, cerebral vessel complications, and even death. Potential non-cerebral complications include facial and laryngeal edema . TherefoAlthough various methods have been reported for IJV reconstruction, autologous vein grafting is ideal. The most common graft used is the great saphenous vein (GSV). However, matching its diameter with that of the IJV can be problematic –4. We deA 54-year-old man with a thyroid papillary carcinoma underwent total thyroidectomy and bilateral neck dissection. Both IJVs were invaded by metastatic cervical lymph nodes. The right IJV was completely resected while the left one only required partial resection. The resulting right IJV defect spanned approximately 8 cm Fig. .Fig. 1InThe defect was immediately reconstructed using a 30-cm section of the right GSV, which was harvested through three small incisions in the medial thigh. The graft was then divided into three pieces of equal length. After opening each piece longitudinally, they were sutured together in a side-by-side fashion using continuous 6-0 polypropylene suture to create a single cylinder, finally wrapping it around a surgical marker pen Figs.  and 3. TThe patient’s postoperative course was uneventful. IJV patency was monitored using color Doppler ultrasonography Video . Ten monThe GSV is the most frequently used donor vein for IJV reconstruction. Although such a reconstruction can be performed with an intact GSV , 6, thisThe most frequently used technique for reconstructing large veins using small vein grafts is the spiral method , 7, whicThe paneled method is another commonly used technique , 8. WithIn our patient, the right IJV was reconstructed using a triple-paneled method, which perfectly fit the required diameter. Pantoja et al. reported the use of triple-paneled saphenous vein grafts to reconstruct the portomesenteric venous system after pancreaticoduodenectomy . To the The main drawback of the triple-paneled method is that the graft needs to be at least three times as long as the defect. A GSV graft approximately 35 cm in length can be harvested using three or four small incisions between the inguinal area and the knee. If additional incisions are made in the lower leg, a 70-cm graft can be harvested, which should be adequate for most IJV defects.Triple-paneled GSV grafts are simple to construct and feasible for use in IJV reconstruction. Furthermore, they have potential to expand the use of autologous vein grafts in the reconstruction of other large vessels. Future studies are warranted to examine their long-term patency rate.Additional file 1: Video 1. IJV patency was confirmed by color Doppler ultrasonography at 10 months postoperatively.


Fragile X-associated tremor/ataxia syndrome (FXTAS) and fragile X syndrome (FXS) are primary examples of fragile X-related disorders (FXDs) caused by abnormal expansion of CGG repeats above a certain threshold in the 5′-untranslated region of the fragile X mental retardation (FMR1) gene. Both diseases have distinct clinical manifestations and molecular pathogenesis. FXTAS is a late-adult-onset neurodegenerative disorder caused by a premutation (PM) allele (CGG expansion of 55–200 repeats), resulting in FMR1 gene hyperexpression. On the other hand, FXS is a neurodevelopmental disorder that results from a full mutation (FM) allele (CGG expansions of ≥200 repeats) leading to heterochromatization and transcriptional silencing of the FMR1 gene. The main challenge is to determine how CGG repeat expansion affects the fundamentally distinct nature of FMR1 expression in FM and PM ranges. Abnormal CGG repeat expansions form a variety of non-canonical DNA and RNA structures that can disrupt various cellular processes and cause distinct effects in PM and FM alleles. Here, we review these structures and how they are related to underlying mutations and disease pathology in FXS and FXTAS. Finally, as new CGG expansions within the genome have been identified, it will be interesting to determine their implications in disease pathology and treatment. CGG repeats are a type of microsatellite or short tandem repeat (STR) found in the human genome, with the majority located in the 5′-untranslated regions (5′-UTRs), suggesting that they may play a role in transcriptional regulation or translation initiation . Abnormain vitro and in vivo using Watson-Crick G:C and Hoogsteen G:G base pairs (As shown in se pairs  (Chen etse pairs . Howeverse pairs  (Kettanise pairs . The forse pairs . The strse pairs  (Abu Diase pairs . A hairpse pairs . Interesse pairs  suggestiin vitro and in vivo studies (FMR1 is flanked by two origins of replication (ORIs): One 45 kb upstream and one 45 kb downstream . Inactiv studies , resulti studies . In cont studies . ReplicaRepeat expansion can also occur during the repair of secondary structures through redundant repair events that are not protective but are harmful either by leading to repeat expansion or contraction . Genome-in vitro and in vivo studies have linked PM alleles, as well as long tracts of CGG/CCG repeats, to a transcriptionally active euchromatic configuration of the FMR1 locus , prevents neurodegeneration in transgenic flies expressing riboCGG repeats within the PM range  in an FXTAS model system. In addition, FMRpolyG interacts with lamina-associated polypeptide 2 beta (LAP2β), a nuclear membrane protein, and rescues neuronal cell death in a mouse FXTAS model  establish cytosine methylation across the entire promoter, including the fragile X related element 1 (FREE1), CpG island, CGG repeat, and fragile X related element 2 (FREE2) regions of FMR1 gene   . Pathogee (NIID) , Parkinse (NIID) , and mule (NIID) . In addie (NIID) , GIPC1 (e (NIID) , NOTCH2Ne (NIID) , and RILe (NIID) , respecte (NIID) . Interese (NIID) . In patie (NIID) . In addie (NIID) . While te (NIID) , howevere (NIID) . Therefoe (NIID) .FXTAS and FXS are two primary diseases caused by dynamic mutations in FMR1, and have distinct clinical manifestations and molecular pathogenesis. FXTAS is a late-onset neurodegenerative disorder that typically affects men >50 years of age. On the other hand, FXS is a neurodevelopmental disease and the most common type of inherited intellectual disability. Both are caused by the abnormal expansion of CGG repeats beyond the normal range in the 5′-UTR of the FMR1 gene. PM alleles (CGG expansions of 55–200 repeats) were associated with elevated FMR1 mRNA levels and relatively normal FMRP levels. In contrast, FM alleles (CGG expansion of ≥200 repeats) typically result in transcriptional silencing and, consequently, the loss of FMR1 protein (FMRP). Abnormal CGG expansions form a variety of secondary structures that are linked to the pathology and transmission risk in both diseases. As CGG/CCG/GGC repeats with characteristics similar to those of CGG repeat expansions associated with FXS or FXTAS are abundant in the human genome, these studies suggest that CGG repeats are broadly involved in neurological diseases. Although several rare folate-sensitive fragile sites associated with neurodevelopmental diseases have been cloned as expanded CGG repeats, the number of studies of CGG/GGC repeat-related disorders has increased in recent years. A recent study using whole-genome STR analysis discovered hundreds of unique-CGG repeats with highly variable repeat lengths and intergenerational instability, most of which are linked to known neurodevelopmental disease genes or strong candidate genes . Further


Musa acuminata Colla acuminata and double balbisiana (MA), Musa double acuminata cv. Pisang Mas (MAM), Musa acuminata cv. Pisang Awak (MAA), and Musa Basjoo Siebold (MBS), and Musa double acuminata and balbisiana-Prata (MAP) were investigated. Results exhibited that all starches exhibited high content of amylose (34.04–42.59%). According to the particle size, they were divided into medium  (14.54–17.71 μm) and large  (23.01–23.82 μm) group. The medium group with A-type crystallization showed higher peak viscosity (PV), final viscosity, gel fracturability and gel hardness. For large group with B-type crystallization, the compact particle morphology, higher degree of crystallinity, short range order, gelatinization enthalpy, pasting temperature, lower porosity, water absorption capacity (WAC) and oil absorption capacity were found. In addition, the medium group with higher PV and gel hardness could be used as food thickening or gelling agents. The large group with higher Rc, short-range order, lower porosity and WAC could be potential to become raw material for resistant starch. All results showed the amylose content, had significant effect on the microstructure and physicochemical properties of starch samples. Outcomes in this investigation might provide a basis of theoretical application for industrial food production.Investigation on staple crop starch of new species has been becoming the research focus of scholars at present. Based on this, the physicochemical properties and microstructural characteristics of starches isolated from Chinese mutant  Musa spp.) is a subtropical and tropical giant perennial herb belonging to the Musaceae botanical family originating from Southeast Asia, Malaysia, and China. China is the second largest Musa producer after India  banana pulps into starch would provide a more stable storage form (1–2 years) and increase its generality and practicality , Musa double acuminata cv. Pisang Mas (MAM), Musa acuminata cv. Pisang Awak (MAA), Musa Basjoo Siebold (MBS), and Musa double acuminata and balbisiana-Prata (MAP). The proximate composition, physicochemical properties, and crystal characteristics were measured. Principal component analysis (PCA) was used to determine the correlation between each characteristic parameter. The results obtained from this analysis will contribute to food and non-food applications in the future.Therefore, this study aimed to characterize the crystal structure and physicochemical properties of high-amylose starch from five mutant banana species grown in China: Unripe fruits of all banana species were collected from the agricultural land of the South Subtropical Crops Research Institute, Chinese Academy of Tropical Agricultural Sciences . The banana species were obtained in three batches-−29 August 2021, 25 September 2021, and 30 October 2021—and each batch included 20 kg of each banana species.Musa flour (100 g) was mixed with 1 L of distilled water, and the mixed liquor was sieved through a 100-mesh filter cloth. The filtrate was centrifuged , the precipitate was dissolved in 1 L of NaOH (0.2% w/v), and the solution was stirred (10 min) to remove soluble fibers. The mixed liquor was centrifuged at 4,000 × g for 10 min, and the supernatant was discarded. Then, the brown skin (exogenous impurities) was removed, and the starch sediment was repeatedly washed with distilled water until neutrality was achieved. The remaining samples were dried at 50°C for 24 h until the moisture content was <13 g/100 g and was then filtered through a 100-mesh sieve (The unripe mutant banana pulp was dried in a vacuum freeze dryer (50°C for 48 h) and ground into banana flour. The sh sieve .X-ray diffraction (XRD) patterns were analyzed using an X-ray diffractometer . A copper tube was used to measure starch samples . The diffraction pattern was measured by a step length of 0.02°, a scattering slit width of 1°, a slit width of 0.02 mm, and scanning from 4 to 40° (2°) at a speed of 4°/min. Each sample was evaluated in triplicate. The relative crystallinity of different starch samples was calculated as described by Barros et al. .The amylose content was quantified as mentioned by Li et al. . A measuFor studying the pasting properties, 3 g of the starch sample was added to 25 ml of deionized water in an RVA container. The solution was stirred at 960 rpm/min for 10 s, followed by 160 rpm/min, and then was analyzed using a Rapid Visco Analyzer . The corresponding viscosity characteristics was calculated by a Stander 1 program in this instrument . The samThe granule morphology of the starch samples was examined using a scanning electron microscope (SEM) . The starch samples were applied to a silver plate coated with a thin film of gold (10 nm) and then kept at an accelerating voltage of 15 kV. Then, the samples were examined using a polarized light microscope linked to a CCD camera, using which we observed Maltese crosses .The size distributions corresponding to granules of the starch were measured using a Malvern Mastersizer 3,000 laser diffraction size analyzer following the method of Barros et al.  and Ren A measure of 1 gram of the starch sample was taken in a centrifuge tube and then 10 ml of distilled water or first-grade peanut oil was added to it, and the mixture was pre-weighed. The solution was mixed for 1 h in a vortex oscillator. The mixture was centrifuged , the supernatant was discarded, and the tube containing the pellet was weighed. The oil and water absorption capacities were expressed as percentages of water or oil absorbed by the starch samples .d) was measured using the liquid displacement method and calculated as follows:Bulk densities were measured by using the method of Zhang et al. , except where W is the weight of the sample, S is the specific gravity of xylene, X is the weight of the bottle and xylene, and Y is the weight of the bottle, xylene, and the sample.f) of the starch sample was calculated using the following formula:The porosity  equipped with a thermal analysis data station  was used to study the gelatinization parameters of thermal properties following the method of Zhang et al. . A total−1, respectively. The ratio of 1,047/1,022 cm−1 was recorded  linked to a smart ITR attachment. The scanning times and resolution were 64 and 4 cmrecorded .Plus, Texture Technologies Corp., United Kingdom) equipped with a weight sensor (max 50 kg) was used to conduct a texture profile analysis (TPA) of starch gels prepared by the RVA. The Texture Expert Exceed version 1.0 program (Stable Micro Systems software) was used to record and analyze the texture properties of the gel. A P/36R cylinder probe was used to carry out the TPA pattern, and a P/0.5R cylinder probe was used to determine the gel 0.5 pattern according to the methods in the program with 40% strain, a pre-test speed of 1.0 mm/s, a test speed of 2 mm/s, and a post-test speed of 2 mm/s. The hardness, fracturability, adhesiveness, springiness, cohesiveness, gumminess, chewiness, resilience, gel strength, gel rupture strength, gel rupture distance, and gel hardness of the sample were determined . Significant differences between the means were determined by using Duncan's multiple range test at a significance level of 0.05. The significant differences, mean values, and standard deviation between values were identified by Duncan's multiple range tests at a significance level of 0.05 . IBM SPSS 20.0 was used to analyze the principal component analysis (PCA), neural network analysis, and cluster analysis.c) followed the order: MAP (37.06%) > MBS (33.75%) > MAA (32.01%) > MAM (30.95%) > MA (27.36%)   is consistent with longer single helices of amylose and greater disruption of double helix crystals.The characteristics of crystalline structures and long-range order in the starch granules were analyzed by XRD . The dif(27.36%) . A signi(27.36%) , this di MBS 33.7% > MAA ((27.36%) . The Rc (28–30%) . Accordi(28–30%) , a more g et al.  also repThe moisture and protein contents of starch from all banana species were below 13 and 1.0%, respectively, in accordance with the food industry of China and Food Chemicals Codex , which rAccording to Jiang et al. , the totp < 0.05).The particle morphologies of MA, MAM, MAA, MBS, and MAP starch samples showed two major shapes: elongated and spherical  left. MAp < 0.05), the starch samples could be divided into two groups: medium  and large  (p < 0.05) than the other starch samples. Meanwhile, MA showed the lowest Dx  . MAP hadBS, MAP) , Dx 50)owest Dx , Dx (50)0owest Dxowest Dx  and Espiowest Dx , the higowest Dx , indicatowest Dx . Accordiowest Dx , the surColocasia starch samples (69.7–73.28%)  had a significantly higher bulk density and true density than the medium-sized group (MA and MAM), and significant differences in bulk density were also found between samples in the medium-sized group . The tru–73.28%) . The dif–73.28%) , 27.p < 0.05). MA and MAP showed the highest and the lowest ability to bind water and oil, respectively. This differs from the WAC and OAC values of various rice starch samples  (The water absorption capacity (WAC) and oil absorption capacity (OAC) of the five different samples were ranked as MA (88.45 and 67.66%) > MAM (83.20 and 65.49%) > MAA (80.92 and 62.19%) > MBS (77.84 and 60.39%) > MAP (74.53 and 58.85%) , indicatctively) . The difctively) . Accordictively) , the lowp < 0.05). Specifically, the onset temperatures  and conclusion temperatures  of MA, MAM, MAA, MBS, and MAP in this study  and gelatinization enthalpies  were consistent with those of Brazilian banana starch  . The peak viscosity  and breakdown viscosity  of banana starch in our study were comparable with those reported in previous studies on cassava, corn, potato, maize, wheat, and rice   . Similarty BDV, 2–2,383 cP,717 cP) .The setback viscosity (SBV) and final viscosity (FV) of MA, MAM, MAA, MBS, and MAP were 2,661–5,414 cP and 4,623–8,161 cP, respectively , Table 2Musa starch samples varied significantly among samples (The peak time (4.93–5.07 min) and pasting temperature  of the  samples , Table 2−1  of the five banana samples ranging from 0.68 to 0.87 (p < 0.05). These results are comparable with those obtained for Amaranthus starch (0.644)  . Starch  (0.644) , 30. Mor (0.644) , which c reports , 28, the7 p < 0.0. These r reports , 2, whicin vitro via double occlusion. The apparent texture property parameter of gelatinous foods was measured by an A P/36R TPA pattern. In general, the internal texture property parameter is determined by using a P/0.5R cylinder probe. TPA using T/36 R and T/0.5 R probes showed consistent results, with the MA and MAP gels being the hardest (434.60 g for T/36R and 210.96 g for T/0.5R) and softest (122.90 g for T/36R and 169.16 g for T/0.5R), respectively, from the five samples . This differs from the hardness reported for wheat starch (68.0–131.1 g) in vitro c since the Rc of jackfruit seed starch increases from 13.29 to 15.87% when the gel adhesiveness increases from 134.38 to 121.31 g.s , followed by MBS (−0.63 g.s), MA −4.16 g.s), MAA (−4.47 g.s), and MAM (−13.40 g.s). This was lower than the values obtained for potato starch gel (−26.257 g.s to −81.315 g.s) , indicat g.s, MAAe et al. .a, b)]. Higher fracturability, springiness, cohesiveness, gumminess, and chewiness but lower resilience of MA, MAM, MAA, MBS, and MAP were determined in this study compared with the earlier reports of wheat, potato, and rice starch  could be conjectured when the inclined angle between two components was remarkably smaller than 90°. Furthermore, there might be a positive correlation when the angle between the two components was remarkably higher than 90° (p < 0.05), whereas no correlation could be conjectured when the angle between the two components was nearly 90° (p > 0.05). The first principal component (PC1) mainly included PV, BDV, porosity, WAC and OAC, hardness, gel rupture strength, and FV. The second principal component (PC2) mainly included amylose content, Rc, Tp, Pt, ΔHg, R, D, and 1,047/1,022. A significantly positive correlation was observed between gel adhesiveness, Rc, Tp, Pt, ΔHg, R, D, 1,047/1,022, and amylose content (p < 0.05), and among PV, porosity, WAC and OAC, hardness, gel rupture strength, and FV. The PV, BDV, porosity, WAC, and OAC also showed a positive correlation. These findings broadly correlate with the results reported in a study by Utrilla-Coello et al. . A similar result using cocoyam starch found that when the FV increased from 189.79 to 252.17 RVU, Pt decreased from 88.75 to 84.83°C (p > 0.05). A proportion of BDV showed a weak correlation with the gel rupture strength, hardness, and FV (p > 0.05).The interactions among the physicochemical characteristics using PCA showed that the starch samples were widely scattered, indicating that the type of starch markable affected the physicochemical and functional characteristics . Accordio et al. , who fou 84.83°C . The amyp < 0.5), while lines of other colors represented a less correlation between physicochemical characteristic parameters. In this part, a remarkably positive correlation was shown for Rc, Tp, Pt, ΔHg, R, D, and 1,047/1,022. Porosity showed a significantly positive correlation with WAC and OAC. FV was positively correlated with hardness, gel rupture strength, and PV and BDV. The amylose content showed a positive correlation with BDV. Rc displayed a negative correlation with WAC and OAC, FV, hardness, gel rupture strength, and PV. Porosity showed a significantly negative correlation with Rc, Tp, 1,047/1,022, and D. Tp and 1,047/1,022 showed a negative correlation with WAC and OAC, FV, gel rupture strength, and PV. ΔHg showed a negative correlation with WAC and OAC, and D displayed a significantly negative correlation with WAC and OAC, hardness, and gel rupture strength. The results of neural network analysis slightly differed from the results of principal component analysis. Based on Li et al.  in MAP than the other banana starch samples, while the opposite particle properties were observed among the other samples. However, Zhang et al. , amylose content, and particle size significantly influenced the physicochemical characteristics of A-type crystal green banana starch. Strong hydrogen bonds between the double helix of amylose and amylopectin form a higher long-/short-range order, double helix arrangement order, double helix structure content, and larger and smoother particle morphology , which rg et al.  reportedoperties , 32, 33,operties , 18, 24,p < 0.05). Based on diverse starch properties, the starch samples were divided into the medium-size group (MA and MAM) and the large-size group . The higher amylose content, Rc, short-range molecular order, Pt, Tp, and lower viscous characteristics and gel hardness were shown by the large-size group, and a contrary result was shown by the medium-size group. The A-type structure of banana starch was found in the medium-sized group, and the B-type structure was shown in the other group. Neural network and cluster analyses further showed that gel adhesiveness, Rc, Tp, Pt, ΔH, R, D, and 1,047/1,022 were significantly positively correlated (p < 0.05). A significant positive correlation was also exhibited among PV, porosity, WAC, and OAC; hardness, gel rupture strength, and FV; PV, BDV, porosity, WAC, and OAC. Meanwhile, gel adhesiveness, amylose, Rc, Tp, Pt, ΔHg, R, D, and 1,047/1,022 were significantly negatively correlated with PV, porosity, WAC and OAC, gel hardness, gel rupture strength, and FV (p < 0.05). These results demonstrated that a higher amylose content, short-range order, double helix arrangement order, double helix structure content, and larger and smoother particle morphology of MAP lead to its higher Pt, Tp, and ΔHg, and lower porosity, WAC, FV, PV, and gel hardness than those of MA, MAM, MAA, and MBS. These findings may be used as a reference to prompt a wider investigation of green banana starch for utilization in the food and non-food industries.The characteristics of starch from Chinese mutant banana species were investigated, which showed a high-amylose starch content. The crystal structure and physicochemical properties varied among the starch species  and the Chinese Central Public-Interest Scientific Institution Basal Research Fund (1630142022007). This study was financially supported by the College of Light Industry and Food Engineering of Guangxi University and Spice and Beverage Research Institute, the Chinese Academy of Tropical Agricultural Sciences, and the Key Laboratory of Processing Suitability and Quality Control of the Special Tropical Crops of Hainan Province.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.