Tie strength has been examined as an antecedent of creativity. Although it has been discovered that international collaboration affects scientific performance, the effect of tie strength in the international collaboration network has been largely neglected. Based on international publications of 72 countries/regions published from 1993 to 2013, we combine descriptive and panel regression methods to examine how the bonding of strong collaboration ties contributes to countries’ international scientific performance. Strong ties occur at an average rate of 1 in 4 collaborators, whereas countries/regions share on average 84% of articles with their strong-tie collaborators. Our quantitative results provide an explanation for this phenomenon in international collaboration: the establishment of a strong tie relationship contributes to above-average productivity and citation frequency for countries/regions. To further explore which types of strong ties tend to have stronger citation impact, we analyse the relationship between persistent and stable collaboration and publication citation impact. Experimental results show that international collaborations with greater persistence and moderate stability tend to produce high impact publications. It is noteworthy that when the collaboration period is divided into different time intervals, similar findings can be found after the same analysis procedure is carried out. This indicates that our conclusions are robust. Overall, this study provides quantitative insights into the added value of long-term commitment and social trust associated with strong collaborative partnerships in international collaboration. With the development of globalization, research activities have become increasingly internationalized, and scientific collaboration among countries has become an inexorable trend , 2. CollIt is important to place a productive country or region within a network of collaborative relationships to better understand its participation in international collaboration . ScholarThe characteristics of collaboration ties shape collaboration networks, which, in turn, affect the impact or usefulness of the publications created by the network . PreviouAgainst this background, this paper uses quantitative methods to enhance our understanding of the relationship between collaboration ties and scientific performance from the perspective of international collaboration. Specifically, we analyse the collaboration ties among 72 countries/regions from an egocentric perspective and focus on the effect of tie strength on citation impact and productivity at the national level. Moreover, from the perspective of international collaboration, the stability and persistence of strong ties are explored, as they can offer insights into which types of international collaborations are “optimal” and which types tend to have the strongest citation impact . By combWhat kinds of ties exist across different countries/regions in terms of international research collaboration? Are they weak, strong or super ties?How do strong ties in international scientific collaborations affect productivity and the number of citations of articles?How do stability and persistence interact to influence the success (measured by citation impact) of international papers produced through strong-tie collaborations?The remainder of this study is structured as follows. Section 2 presents an overview of the literature on the features of international collaboration. Section 3 introduces the data gathered for this study and the methods for quantifying and distinguishing international collaborative ties. Subsequently, the results are thoroughly analysed and discussed. Finally, conclusions are drawn from the analysis of the results, and policy suggestions are outlined.In the era of globalization, scientific collaboration among different countries has become a general trend . Gazni eBy analysing international paper collaboration networks from the Science Citation Index (SCI) database, Leydesdorff and Wagner  highlighBy exposing collaborators to various knowledge and perspectives, collaboration can increase the chances of novel ideas being generated , 34. IntTie strength can be defined as “a combination of the amount of time, the emotional intensity, the intimacy , and the reciprocal services which characterize the tie” . In scieCompared to short-distance collaboration, long-distance collaboration is costlier to practitioners in terms of time and resources. As Barjak and Robinson  pointed Most of the extant literature has argued that international collaborations and partnerships can provide rich opportunities to enhance research , 43. WagOverall, the existing literature has focused on the characteristics of macroscopic international collaboration networks and the impact of international collaboration on countries’ academic performance. Previous studies focused on the social capital that can be derived by a country from its position in the international network, whereas the effect of tie strength in the egocentric international collaboration network has been largely neglected. Tie strength involves only two collaborators. Therefore, tie strength can be more easily managed by individual countries, which allows for the drawing of more direct management recommendations and policies. From the perspective of egocentric collaboration networks at the national level, this study focuses on heterogeneity in collaborative tie strength and quantifies the added value of strong ties for countries’ scientific performance.The dataset used in this study comes from the ArnetMiner academic social networking platform , which cNote that 1993 is taken as the analysis’s starting year in this study. In this way, data from countries like the Union of Soviet Socialist Republics, Yugoslavia, and Czechoslovakia are excluded from further analysis, since their names or composition have been changed since 1970. In addition, Germany was reunified in 1990, so using data from Germany after 1993 in our analysis also eliminates the ambiguity over the information of the country, which means that the data from the German Democratic Republic (1949–1990) is excluded from our analysis. The ArnetMiner dataset ends in 2014, and we pick 2013 as the ending year for analysis so that the papers published before 2013 can have a long-time window to accumulate citations. International collaborations are represented using coauthored papers with two or more countries/regions. In the end, we obtain a dataset of 153,545 international collaborative articles, which involves 114 countries/regions.We employ the following counting procedures to calculate the number of international papers of each country/region. Regardless of the order of authorship, if collaborating authors’ institutions recorded in a paper are located in different countries/regions, each country/region is considered to have produced one paper. For example, if a paper has authors from two different countries/regions, those two countries/regions each receive one paper count. Using the thresholds of a minimum of 100 international collaboration papers, in In order to conduct a comparative analysis, we divide the 72 countries and regions into two groups  according to the cumulative distribution of the total number of published international publications .We take the point in The international scientific collaborative network offers a unique perspective on the ranks and positions of countries/regions. We use VOSviewer to visualize the collaboration network of the 72 countries/regions . Each noThe average path length of the network in As shown in Kij as the cumulative number of publications coauthored by two countries, i and j, during the time period between their first and last publications. We calculate the average tie strength of each country i as follows, and refer to country i as the focused country:In this paper, we define collaborative tie strength Si of focused country i. We use average collaborative tie strength 〈Ki〉 to distinguish strong ties (Kij ≥ 〈Ki〉) from weak ties (Kij < 〈Ki〉). Super ties in the collaboration of each country are identified according to a tie strength threshold:Average tie strength is calculated across the number of distinct collaborative countries j with Kij > i [Si represents the number of collaborative countries of a certain country, Si is greater than or equal to 3 in our research. As this approach is centred around i, three types of tie definitions are not symmetrical; for example, if country j is a strong tie of i, then i is not necessarily a strong tie of j. According to [P(Kij), the super tie threshold P(Kij) of the international collaborative tie strength also follows the exponential distribution by exploring the distribution of normalized collaboration strength x = Kij/〈Ki〉 using the Anderson-Darling test. Thus, the super tie threshold Each collaborative country ountry i . It shourding to , using aIn this paper, among the three types of ties, strong ties are the main focus. Because almost all of the countries/regions analysed have more than one strong tie, we are able to quantify the added value of strong ties by using descriptive measures.N, suppose that two countries, i and j, have a certain number of publications each year: y = 1, 2, …, N). The stability of collaboration between countries i and j, Si,j, is thus represented using the equation below, where max(cij) refers to the maximum number of coauthored publications in a year.This paper adopts indicators of the stability and persistence of collaborative pairs of countries with strong ties. We use an explicit mathematical definition of international collaborative stability : the conDi,j between countries i and j [In addition, we apply the following formula to calculate the persistence of collaboration  i and j . CompareN, sij is the number of skip years without collaboration, which refers to the number of years in which countries i and j have zero coauthored articles within those N years; vi,j is the number of intervals without collaboration between countries i and j within N years, defined as the number of contiguous time periods in which the two countries have no joint publication; and λ (0 < λ < 1) is a parameter to fit the model, which presents the importance of vi,j in the model. In this article, we refer to Bu’s article and set λ = 0.5. Note that a country pair can have only one persistence value.Given a consecutive year The scientific success of a collaborative pair is measured by the average scientific success of all publications coauthored by that pair. Thus, we calculate the yearly average number of citations (YANC) received per article, which indicates the impact of coauthored articles. The YANC minimizes the bias towards older papers, which tend to accumulate more citations. We also calculate the proportion of coauthored articles that have received at least 10 citations (CAP10C), which is actually the number of coauthored articles that have received at least 10 citations divided by the number of coauthored articles written by two countries.Ki〉 indicates the average tie strength of country i with all collaborative countries. Due to space restrictions, we only display the collaboration of five high-productivity countries, and only the top five countries with the most collaborative papers are included in the collaborative country’s column. The close collaboration ties of all high-productivity countries are documented in S1 Table in We summarize the collaborative relationships of each country/region according to our definitions of weak, strong and super ties. Scientific research collaboration occurs between any two high-productivity countries. For these countries, most of the coauthored papers are written in collaboration with other high-productivity countries. The US is a strong tie of every other high-productivity country, indicating that collaboration with the US plays an important role in international collaboration for these countries. The US has an enormous number of publications and collaborative relations, and thus, it has advantages and power in international scientific research collaboration. Mainland China and France have the largest number of super ties, with 4 each. The UK has the largest number of strong ties, with 18.Similarly, P(≤ 〈Ki〉) of the mean tie strength 〈Ki〉 of high- and low-productivity countries, which can vary over a wide range depending on a country/region’s involvement in international science activities. This measure captures the variability in collaboration strength. In Ki〉 values. Vertical lines indicate the mean values. The figure shows that the average collaborative tie strength of high-productivity countries  is generally higher than that of low-productivity countries .Here, we focus on the cross-sectional distribution of tie strength within the ego network. SR,i. The strong tie coauthor fraction fR,i = SR,i/Si measures the strong tie frequency on a per-collaborator basis, with a mean value of 〈fR〉 ≈ 0.236, which indicates that strong ties occur at an average rate of 1 in 4 coauthor countries/regions. Furthermore, P(≤fR) of two groups of countries. The mean value of the strong-tie coauthor fraction of high-productivity countries  is generally smaller than that of low-productivity countries . High-productivity countries have greater scientific capacity to attract more countries/regions as collaborators, so the proportion of strong ties in these countries is relatively small.How common are strong ties in international collaboration? We denote the number of co-author countries/regions that are strong ties as fN,i , with a mean of 0.866 for high-productivity countries and 0.842 for low-productivity countries. The establishment of close partnerships can reduce the risk of inefficient collaboration for countries/regions. Overall, the mean value of fN,i for low-productivity countries is lower than that of high-productivity countries, indicating that high-productivity countries have higher levels of strong tie dependency than do their low-productivity counterparts.In this subsection, we find that on average, a country/region’s publications coauthored with at least one strong tie account for more than 80% of all collaborative papers. Does collaboration with strong ties bring about benefits to countries/regions in terms of scientific research performance? In next subsection, we investigate the role of strong ties at the micro-level by analysing annual productivity and the citation impact of international publications.t-year periods. Panel data for 72 countries/regions from 1993 to 2013 as well as two time periods, each lasting around 10 years, from 1993 to 2003 and 2004 to 2013, are used to build the regression model.We analyse the profile of collaborative research from 1993 to 2013, separating the data into nonoverlapping Δi, we label each strong-tie j with the indicator variable ni,t/〈ni〉, which is productivity aggregated over Δt-year periods, normalized by the baseline average calculated over the period of analysis. To better understand the factors contributing to productivity growth, in our regression model, we use four explanatory variables that are specific to country/region (i).For country/region Ni,t, the total number of publications up to year t, which is a measure of the focused country/region’s activeness and research profile. Finally, for each period t, we calculate the contribution of strong-tie collaborators ρi,t, normalized by the contribution of all other collaborators to account for the possibility that the relative contribution of strong ties may affect productivity.First, we calculate the average number of countries per publication ρi,t is nonzero. To deal with the nonstationarity of the data, we use the logarithmic forms of three variables. Variance inflation factors (VIF) are used in this study to test for multicollinearity. We adopt the criterion that the presence of multicollinearity is indicated by VIF values larger than 10. The results show that the VIF values of the independent variables are less than 3, indicating that there is no threat of multicollinearity problem [p < 0.01). Thus, the analysis is mainly based on fixed effects regression.We include countries/regions in this analysis only if there are data of 5 years or more of international collaboration for which the denominator of  problem . The fix problem . We emplβi,0) with robust standard errors (SEs) to account for autocorrelation within each i. t = 1 year. In addition to individual regressions for high- and low-productivity country groups, we run the regression for the full dataset (“All”).We implement the fixed effects model as follows:βρ = 0.005 , meaning that larger contributions from strong ties are associated with above-average productivity and that strong ties play an important role in sustaining productivity growth. For example, let us consider the scenario where the average ρi,t value observed is 7.378. Then, let us consider a second scenario with ρi,t = 1, corresponding to equal input from strong ties and their counterparts. If all other parameters contribute a baseline productivity value of 1, then the additional contribution from βρ corresponds to a 7.378 βρ/(1+7.378βρ) = 4.2% productivity increase. We also find that above-average productivity is associated with a higher total number of publications of the focused country/region . The coefficient of βρ coefficient of high-productivity countries is 0.003, while that of low-productivity countries is 0.006. Moreover, strong ties contribute a 2.2% increase in scientific research productivity for high-productivity countries and a 4.5% increase for low-productivity countries. By observing the coefficient βρ, we find that in international collaboration, collaboration with strong ties increases productivity more for low-productivity countries than for high-productivity ones.We observe a positive coefficient, Throughout different time intervals, strong ties also contribute to productivity advantages for countries/regions. A 2.8% increase in the productivity of a country/region’s publications is related to the effects of strong ties between 1993 and 2003, as shown in S3 Table in ci,t, which is the average YANC aggregated over Δt-year periods.It is very difficult to measure the impact of strong ties on the number of citations of a country/region’s publications, because old publications have more time to accrue citations than do new papers, so a direct comparison of raw citation counts for publications from different years is technically flawed. Therefore, we calculate the YANC, which indicates the impact of coauthored articles and minimizes the bias towards older papers. Then, we model the dependent variable Ni,t up to year t, and the normalized contribution of strong-tie collaborators ρi,t. For the panel data regression method, we also use the Hausmann test to identify the appropriate regression model. The p-value shows that the fixed effects model is more suitable than is the random effects model for quantifying the impact of strong ties on the number of citations of publications. Thus, we implement fixed effects regression to estimate the parameters of the citation impact model.Following the previous step, we use the same explanatory variables as in t = 1 year.βρ = 0.029 (p≤0.05 in the “All” dataset), indicating that a 18.8% increase in the number of citations of a country/region’s publications is related to the effects of strong ties. We argue that the reason for this may be that strong ties contribute to publication visibility. We also observe a positive coefficient, p<0.05 in the “All” dataset), of the number of collaborative countries parameter, meaning that average annual number of citations is also associated with the average number of collaborative countries of the focused country/region. Strong ties also result in citation gains for countries/regions for various time periods, as demonstrated in S5 and S6 Tables in We estimate βρ = 0.053) have a βρ parameter that is higher than that of low-productivity countries (βρ = 0.030). In other words, the influence of strong ties on the number of citations of high-productivity countries increases by 28.8%, while that on the number of citations of low-productivity countries increases by 19.2%. This indicates that academic collaboration with strong ties provides more visibility and influence to high-productivity countries than to low-productivity countries.For the regression results for high- and low-productivity countries, we can see that high-productivity countries  as low-stability pairs, those with [0.75, 0.80) as low-to-medium-stability pairs, those with [0.80, 0.85) as medium-stability pairs, those with [0.85, 0.90) as medium-to-high-stability pairs and those with [0.90, 1.00) as high-stability pairs. Generally, groups with a high stability value can have more chances to increase their YANC and CAP10C values. However, as shown in We also explore the relationship between stability of collaboration and scientific performance between countries/regions in different time intervals. The same trend as that during the entire era of collaboration is observed in 2004–2013, as shown in S9 Fig in Stability represents the degree of the long-term and consistent investment into a collaborative relationship. Country pairs with a higher degree of stability have better research performance than those with lower stability. Stability may be important for fostering knowledge exchange among participating countries and producing achievements of a high calibre , 54. AccTo better understand international scientific collaboration, we need a host of perspectives. Both persistence and stability measure the characteristics of collaboration counts of a given country pair. To understand how persistence may interact with stability to affect the citation impact of international publications is therefore of interest. Thus, here, we use collaborative persistence and stability to better understand the structure of successful international scientific collaboration. In The correlations between persistence, stability, and the YANC from 1993 to 2003 are depicted in S10a Fig in According to S11a Fig in Most of the abovementioned research on international collaborative relations has focused on strong ties between countries/regions. In previous sections, we find that strong ties contribute to above-average productivity and a higher number of citations per publication for countries/regions. In this subsection, for the minority of international collaborations characterized by super ties, we quantify the impact of these ties on countries/regions’ research performance to draw new insights.ni,t/〈ni〉 and three independent variables  in the model are the same as those in φi,t. For country/region i, we label each super tie j with indicator variable We implement a fixed effects regression model to determine the sign and strength of the contribution of super ties to countries/regions’ productivity. The dependent variable The fixed effects regression model is as follows:φi,t is nonzero. In t = 1 year.In the regressions, we only include countries/regions with data of 5 years or more of international collaboration, where βφ = 0.033 , meaning that larger contributions by super ties are associated with above-average productivity. Our calculations show that the contribution of super ties leads to a 4.5% increase in scientific research productivity for countries/regions, which is greater than the increase in productivity brought about by strong ties. As shown in S7 Table in We observe a positive coefficient, βφ coefficient of high-productivity countries is 0.003, while that of low-productivity countries is 0.033. Thus, super ties are found to contribute a 4.0% increase in scientific research productivity for high-productivity countries and a 4.5% increase for low-productivity countries.In the model results, the t, Ni,t, and the normalized contribution of super tie collaborators φi,t.Referencing t = 1 year.βφ is 0.182. In other words, a 21.4% increase in the number of citations of a country/region’s publications can be traced to the effects of super ties, which is much higher than the increase in the number of citations brought about by strong ties. Super ties, according to S9 Table in As seen from In addition, the influence of super ties increases the number of citations of high-productivity countries by 43.3% and those of low-productivity countries by 21.5%. Similar to strong ties, super ties lead to more influence gains for the high-productivity countries and more productivity gains for the low-productivity countries.International collaboration plays an important role in the production and dissemination of new scientific knowledge. An increasing share of scientific papers is co-authored by scientists from two or more countries/regions, which results in the emergence of international collaboration network . PreviouTo explore the collaborative relationships between countries/regions, we quantify tie strength using an egocentric perspective of the collaboration network. Our analysis indicates that more than 3/4  of the international collaboration ties analysed are weak. However, the remaining strong ties represent collaboration investments that can indeed have significant long-term effects for countries/regions. Although a country/region’s strong ties account for a lower proportion  of collaborative relationships, countries/regions share on average 84% of articles with their strong-tie collaborators. Many scholars have proposed various explanations for why such extremely strong international collaboration exists . The greContinuous and close scientific collaboration may contribute to the production of international papers, to investigate how these strong ties are sustained, the persistence and stability characteristics of international collaboration are analysed. Collaborators with a high degree of persistence tend to receive more citations, persistent collaboration and less interference help build strong trust between countries/regions and bring long-term academic success. This result is similar to previous research revealing that persistence is closely related to scientific success . For staOur quantitative results are in accordance with literature suggesting the general trend of international collaborative work on the national level . Our meaThe findings of our study provide several implications for practicing managers concerning the question on how to configure international alliance relationships to promote scientific research performance. Global teamwork has evident consequences for the efficiency of scientific activities , the choThe main purpose of this study is to explore how the bonding of collaboration ties contributes to countries/regions’ international scientific performances. It enriches the study of collaboration ties between countries/regions from the view of egocentric international collaboration networks. In an international collaboration network, two countries/regions are connected if they have coauthored a paper, and all collaborations are divided into dyadic relationships, which is the most central part of the collaboration network . Second,This paper provides an exploratory study of the effect of strong ties in the international collaboration, but there are still some limitations. First, ArnetMiner is an effective dataset to explore the contribution of strong relationships in international collaboration, but it also had limits. For example, the data solely contains articles in the field of computer science; citations from journals in other fields are not taken into account. We will expand the dataset of papers in more disciplines to precisely elucidate countries’ international collaboration. Second, the strong collaborative relationship between two subjects can be extended to the larger group to further expand the scope of the study. Last, in future studies, we will further explore the characteristics and effects of super ties, thus enriching and extending the existing findings.S1 Appendix(DOCX)Click here for additional data file.


Random forest (RFT) was conducted to classify the samples and to determine the importance levels of the analysis parameters. According to the results, AE and mixograph MID line peak values were the most discriminant parameters to distinguish the samples into groups. High-level HS alone caused undesirable effects on the dough quality, yet the addition of modified starches could be used to compensate for the undesirable effects. When used together, the interaction between hazelnut skin and modified starches should be considered. Glutopeak provides a means for assessing the impacts of additives such as hazelnut skin or modified starches on flour functionality.Hazelnut skin is a by-product produced from hazelnut processing. It can be used as a nutritional supplement due to its high nutrient values. The purpose of this study was to evaluate the dough properties of refined flour (RF) with the addition of hazelnut skin (HS), cross-linked starch (CS), and oxidized starch (OS). Principal component analysis showed a positive correlation between maximum torque, torque after maximum, and aggregation energy. Usage of 10% HS significantly ( In addition to the products with technological advantages, products with increased nutritional value and the recycling of waste and by-products are of great interest. Hazelnut skin is a by-product obtained after roasting during the processing of hazelnut and is very rich in phenolic, antioxidant, and dietary fiber content . Due to With the modification of the starch, some technological expansions are achieved by increasing the functionality of native starch. Bonds between hydroxyl groups are responsible for the production of cross-linked starch in the starch structure. Since the cross-linked starch has low digestibility, it is also considered a dietary fiber and is used because of its effects, such as increased viscosity and stability in foods . For exaThe purpose of this study was to investigate the individual and combined effects of hazelnut skin, cross-linked starch, and oxidized starch on dough quality. It was also aimed to compare the glutopeak test and mixograph parameters and to reveal the relative relevance of the parameters with principal component analysis (PCA) and random forest (RFT).Corylus avellana L.) was obtained from a hazelnut processing plant in Ordu, Turkey. Hazelnut skin was ground in a laboratory grinder and sifted through sieves with a mesh size range of 0.50 to 0.85 mm. Both modified corn flour oxidized starch  and modified corn flour cross-linked starch  were obtained from Pendik Nisasta . Hazelnut skin at 5% and 10% flour replacement was used along with 3% and 5% of modified starches on a flour basis. Each sample was prepared in triplicate.The North Dakota State Mill supplied commercial hard red spring wheat flour free of oxidizing agents and other ingredients . Hazelnut skin , according to Chandi and Seetharaman . To mainThe Glutopeak and mixograph results of samples were analyzed through PCA to establish the linear relationships between the samples and between the results. The data were standardized and decomposed into principal components (PCs), and the biplot was drawn using the first two PCs .RFT is an ensemble machine-learning model that can be applied to both classification and regression operations. It contains multiple decision tree models. Each tree is built using a unique “bag” of bootstrap samples from the training set. When separating the nodes, the best predictor variable from a group of predictors randomly chosen for each node is taken into consideration. The remaining data are utilized as a test set for this particular tree because it is regarded as being “out of the bag.” It offers information on the variable importance rate . A machiThe analysis of variance (ANOVA) was carried out using statistical analysis software (SAS v.9.4). For mean separation, the least significant difference (LSD) was applied.p < 0.05) affect the PMT, but oxidized starch did cause an increase in PMT (p < 0.05) with the use of 10% hazelnut skin (p < 0.05) decrease in the TAM of dough containing hazelnut skin. It was observed that AE showed some variation between samples with hazelnut skin  increased with the addition of wheat bran, PMT and AE significantly (p < 0.05) decreased. On the other hand, another study reported that the addition of bran to flour increased MT, while PMT and AE significantly decreased [p < 0.05) decreased with the addition of modified starches, which was more pronounced in oxidized starch. On the other hand, a PMT value of 70.5 s was observed when 10% hazelnut skin was used alone. When 5% cross-linked starch and 5% oxidized starch were added, PMT was 106.0 and 108.5, respectively. It was observed that MT, TAM, and AE values obtained with 10% hazelnut skin decreased statistically significantly (p < 0.05) with the addition of 5% modified starches. Overall, the findings of the Glutopeak test were generally worsened by the addition of 10% hazelnut skin, and cross-linked starch performed better than oxidized starch. Accordingly, it is clear that there is an interaction between hazelnut skin and modified starches. The high dietary fiber content of the hazelnut skin causes its water binding capacity to be high. This causes the starch granules to swell less due to a lack of water [The Glutopeak test has the potential to be utilized as a quick tool for testing the quality of flour, but comparing the findings is challenging due to varying testing parameters such as mixing speed and flour to water ratio used in the literature . Marti eecreased . Althougecreased . Wang etecreased  used whoecreased . Rakita ecreased  stated tecreased . High vaof water . The fatof water . Emulsifof water . The oilof water ,26. Phenof water ,26. Accoof water , starch–The PCA biplot provides an overview of the similarities and differences among the flour samples and the interrelationships among the measured properties . The disThe relationships between the Glutopeak and mixograph features were revealed using the biplot of the principal component analysis (PCA) . A positRandom forest (RFT) is an ensemble tree-building technique in which data are divided into several consecutive class subsets, depending on whether the variable is significantly related to the response variable. In RFT models, many classification and regression trees (CARTs) are built and ensembled to obtain more robust and reliable results. Multiple CARTs are generated with RFT, and these are used by combining them to get a more accurate and stable prediction. RFT algorithm is a machine learning method capable of feature selection . In thisMixograph results for the different flour blends are summarized in p > 0.05) affect the mixograph properties, MMLPW was significantly (p < 0.05) reduced by increasing the oxidized starch level to 5% (p > 0.05) with the addition of hazelnut skin and modified starches. This partially corroborates the finding of Al-Foudari et al. [It was determined that hazelnut skin remarkably extended the required time for mixing. These results indicate that MMLPT for optimum dough development increased as the cross-linked starch content increased. This may be due to the slow hydration of the cross-linked starch. The same amount of water was used for each mixograph test; therefore, water absorption capacity impacts mixograph parameters. According to mixograph properties, dough with a larger peak width, longer mixing time, and lower breakdown indicates a stable and strong dough. The MMLPV and MMLPW tended to decrease at the higher levels of modified starch, indicating a weaker dough. While adding 3% oxidized starch to flour did not significantly  is shown in The RFT for modified starch addition is shown in This research demonstrated that 10% hazelnut skin had significant effects on Glutopeak test properties and mixograph characteristics in wheat flour blends. As hazelnut skin concentration increased, MT and TAM values gradually decreased. The addition of 5% hazelnut skin had almost no effect on glutopeak test results. However, the fact that the addition of 5% hazelnut skin caused significant changes in the samples containing modified starch indicates the existence of an interaction between hazelnut skin and modified starches. Glutopeak test results were negatively affected by the addition of 10% hazelnut skin. It was observed that cross-linked starch had better results than oxidized starch, and 3% was appropriate to compensate for the unfavorable effects of hazelnut skin. PCA showed that there were highly positive correlations among TAM, AE, and MT, between MELS and MMLPV, and between PMT and MMLPT results of the Glutopeak test and mixograph. Similar results were obtained between the use of oxidized starch at 3% and 5% and the use of cross-linked starch in the same proportions in terms of effects on dough strength. The mixograph findings revealed that oxidized starch was favorable compared to cross-linked starch, while 3% utilization yielded better results for both starches. The use of 5% hazelnut skin provided appropriate results; however, 10% hazelnut skin led to a decline in dough quality. According to RFT results, in order to observe the effects of modified starch addition on flour, the most important parameters were determined as AE, PMT, MT, and MMLPW, whereas TAM, MMLPV, and MMLPW parameters were decisive for the addition of hazelnut skin. Overall, the use of hazelnut skin in flour formulation at certain levels is appropriate in terms of dough quality, and the interaction capability between hazelnut skin and modified starches should be taken into consideration when used together.


In view of the significant differences among genotypes in the appearance of soft rice, it is necessary to conduct research on the differences in the appearance quality of soft rice and their mechanisms. It can provide a theoretical basis for the selection and breeding of superior appearance varieties at a later stage. In order to clarify the differences in appearance phenotypes between different soft rice genotypes and structural basis of endosperm structures behind the differences, four soft rice varieties were selected in this study, including two varieties with good-appearance and two varieties with cloudy appearance. The differences in appearance phenotypes and endosperm structure in mature grains of soft rice with different appearance phenotypes were scientifically analyzed. The development process of their endosperm differences at the filling stage was investigated. The results show that the difference in the rice appearance of soft rice varieties mainly lay in the chalk-free seed transparency and chalkiness. These differences were caused by two completely different types of endosperm structure. Fewer and smaller starch grain cavities were responsible for higher chalk-free transparency of soft rice grains, denser starch granules arrangement caused lower chalkiness of soft rice grains. Ten days after flowering, the starch granules in the back and heart of good-appearance soft rice were already significantly fuller and more closely packed than those of cloudy soft rice. At the same time, the number and area of starch granule holes were significantly smaller than those of cloudy soft rice. This difference gradually increased until maturity. Therefore, based on appearance evaluation, soft rice with good-appearance should have higher transparency and lower chalkiness. The endosperm starch granules should be full and tightly arranged. The number of starch grain cavities and the area should be smaller. These differences develop in the early stages of grouting and gradually increase. Compare in 2020 . In term in 2020 .Rice appearance quality is the specific appearance characteristics developed after the involvement of rice grain endosperm in light reflection and transmission. Starch, the most important storage material in rice endosperm, accounts for over 80% of the dry weight of endosperm. Endosperm structure  is an important factor affecting the appearance quality of rice . It has 22.1The tests were conducted in 2021 at the test site in Shatou, Yangzhou, with wheat being the previous crop in that area. The good-appearance soft rice varieties (Yangnongxiang 28 and Nanjing 5718), and the cloudy soft rice varieties (Wuxiangjing 113 and Yangjing 5118), used in 2020, were selected as test materials. For notations, Y28 represents Yangnongxiang 28; N5718 represents Nanjing 5718; W113 represents Wuxiangjing 113; Y5118 represents Yangjing 5118.2.2The test site was selected from plots with medium to good ground strength and balance (basic ground strength), yields above 400 kg and easy access to irrigation. A normalized group design was used.The cultivation method was machine inserting blanket seedlings, in rows 30cm × 11.7cm apart, and with 4-5 plants per hole.2, based on base fertilizer: tiller fertilizer: spike fertilizer = 3.5:3.5:3. Tiller fertilizer was applied seven days after transplanting, and spike fertilizer was applied at the inverted four-leaf stage. The ratio of N: P: K was 2:1:2, with phosphate as a one-time base fertilizer and potash applied in equal amounts before plowing and at the nodulation stage respectively. Water management, pest and weed control and other related cultivation measures were implemented following high yield cultivation requirements.Nitrogen fertilizer level was 270kg /hm2.3Spikes with uniform growth and flowering on the same day were tagged at the beginning of flowering for each variety. Seed samples were taken 5, 10, 15 and 20 days after flowering (DAY) and at maturity.2.4The chalkiness of the seeds at maturity was determined according to GB/T 17891-2017. The chalkiness, chalk area and chalky rate were calculated .2.5When the rice sample was placed in a 1 cm thick cuvette, the transparency of the rice can be expressed by its transmission using a colorimeter with a D65 light source (CM-5 Japan). The transparency of normal seeds at maturity and non-chalky seeds. were measured.2.6Representative rice was arranged neatly in a dark room. The appearance of the white rice was photographed with a stereo microscope .2.7The seed samples were fixed in pre-chilled 2.5% glutaraldehyde solution immediately after leaving the spike at the filling stage, and washed three times with 0.1 mol/L (pH 7.2) phosphate buffer after three hours. Then ethanol gradient dehydration, isoamyl acetate replacement, and CO2 critical point drying were conducted. The final sample was prepared using ion beam sputtering coating and then observed using a scanning electron microscope .Mature seeds were frozen in liquid nitrogen for 3~5 min. Then the external force was applied to the rice grains with forceps to make them brittle. The sample was pasted, sputter-coated and observed in the same way as described above.2.8The particle size distribution of starch was investigated using a laser diffraction particle size analyzer . About 0.2 g starch samples were immersed in 500 mL absolute ethyl alcohol and stirred at 2000 rpm. The instrument was calibrated to measure starch particle sizes ranging from 0.1 to 2000 µm.2.9T2 (transverse relaxation time) values of cooked rice were measured using a nuclear magnetic resonance analyzer  with the Carr-PurcellMeiboom-Gill (CPMG) sequence. A subsample of each rice sample used to determine taste was weighed to 5 g in glass vials and placed in a nuclear magnetic tube with a diameter of 25 mm. The center frequency was first calibrated with a free induction (FID) decay pulse train using the NMR spectrum analysis software. The parameters of the CPMG pulse train for each rice sample were set as follows: main frequency SF1=20MHz; sampling frequency SW=200 kHz; 90° hard pulse RF pulse width P1=6 μs; 180° hard pulse RF pulse width P2=13.04 μs; signal sampling points TD=600010; waiting time for repeat sampling, TW=2500 ms; the number of replicates, NS=4; echo number NECH=15000. This technique was studied and explained in depth by Klitsadee et al. .2.10After obtaining the images by scanning electron microscopy, 200 starch grains were selected for each sample according to the magnification-corrected scale, and the number of starch grain cavities was calculated. The area of the cavities was measured using the PS software, and their mean and standard deviation were obtained using Excel.2.11Each experiment was repeated at least three times independently. All of the reported date were calculated into averages and analyzed using one-way analysis of variance (ANOVA) and Tukey’s test in SPSS (version 16.0).33.1The appearance of Y28 and N5718 differed significantly from that of W113 and Y5118 Figure 1Rice transparency is measured as the overall transparency of sampled fine rice grains in previous studies, which refers to light transmission performance of sampled fine rice under transmitted light. It can be affected by both chalky and non-chalky parts of rice grains. In order to further investigate the causes of the differences in soft rice transparency, the non-chalky grain transparency of four soft rice varieties was also measured in this study. This transparency can represent original chalk-free transparency of rice grains without the interference of chalkiness Table 1.3.2The above analysis shows that the appearance of these four varieties was significantly different regarding chalk-free seed transparency and chalkiness. Normal and non-chalky grains of these four varieties were selected to further investigate the endosperm structure that caused differences in these two types of appearance.3.2.1The endosperm of normal grains of Y28 and N5718 had relatively dense structures, and there was no clearly visibly structure at low magnification . This suggests that the denseness of endosperm structure is the direct cause of the differences in chalky phenotypes of different soft rice varieties. The number and size of cavities in the endosperm of the good-appearance soft rice varieties were significantly smaller than those of the cloudy soft rice varieties Table 2.3.2.3The overall starch grain surface area and volume of Y28 and N5718 were larger than those of W113 and Y5118 Table 3.3.2.4The transverse relaxation time is divided into short transverse relaxation time  and long transverse relaxation time . T21 and T22 represent the bound water and free water distribution inside the specimen, respectively. A2 represents a significant linear relationship between the signal amplitude of the magnetic resonance transverse relaxation spectrum and the moisture content of the grains. C2 represents the proportion of water in each state to the total moisture content of the grains. Compared with the cloudy varieties, the good-appearance varieties had significantly higher A22 and C22 but significantly lower C21 Table 4.3.3The differential endosperm structure of different soft rice varieties is closely related to the grain-filling process. What characteristics does endosperm exhibit during this process? Therefore, the endosperm structure of different soft rice varieties at different stages after flowering was systematically investigated.3.3.1At DAF 5, the grains started to accumulate starch and amyloplasts of the endosperm cells began to produce small starch grains. The starch grains were ovoid or spherical and less angular Figure 73.3.2A large number of compound starch grains and a small number of single starch grains were observed in the endosperm back and core parts of Y28 and N5718. The compound starch grains were closely arranged and compressed. Spherical protein bodies can be observed between the starch grains (3.3.3Since DAF 15, the endosperm starch grains of each variety expanded and the gap was significantly reduced. The endosperm cells had been filled with amyloplasts, with deformed protein bodies remaining in the amyloplast gap Figure 93.3.4At DAF 20, the core and belly parts of the endosperm of all soft rice varieties showed clear cavities. The back and core parts of the endosperm of all soft rice varieties were further filled compared to at 15 days. However, the gap between starch grains on the back was slightly larger than that on the core. This is possibly due to more protein bodies between the starch grains of the endosperm back, thus inhibiting the denser arrangement of the starch grains (3.3.5At DAF 10, the starch grains in the endosperm of all soft rice varieties showed clear cavities. At each stage after DAF 10, cavities in the starch grains were also observed (44.1Better appearance quality has always been an effective means for rice resources to enhance their market competitiveness. However, there is no industry-accepted standard for determining good-appearance soft rice varieties. In China, the appearance quality of ordinary rice is mainly measured by chalkiness . It indi4.2The endosperm structure is a direct cause of the rice appearance quality. In many previous studies, the endosperm structure of highly chalky rice was compared with that of low chalky rice. It was found that chalkiness was mainly caused by the insufficient filling of endosperm, insufficient fullness of starch grains and loose arrangement . In someIV gene, the presence of starch granule cavities in the endosperm of low transparency was found (The endosperm structure of soft rice was also compared with that of ordinary rice in previous studies . Zhang eas found . Howeveras found . There aas found . This st4.3Many scholars have concluded that the development of rice chalkiness was closely related to the dynamic variation of dry matter accumulation, filling rate and moisture content of rice grains during rice filling . The preYang et al. reported that the formation of starch grain cavities may be due to gradual water loss in the transition to the yellow ripeness stage after the number and shape of starch grains are set and filled with endosperm cells in the milky ripeness stage . Hao et 5This study concluded that the difference in the appearance of different soft rice varieties was mainly in chalk-free seed transparency and chalkiness. The soft rice varieties with good-appearance had higher chalk-free seed transparency and lower chalkiness. The analysis of endosperm structure indicates that the appearance difference was attributed to two completely different types of endosperm structure: fewer and smaller starch grain cavities were responsible for higher chalk-free seed transparency of soft rice, the denser starch grain arrangement caused lower chalkiness of soft rice. The analysis of endosperm development shows that the differences in endosperm structure of different soft rice varieties started to develop at DAF 10 until maturity. Then, the endosperm structure showed a continuous trend of development and enlargement process.All relevant data is contained within the article: The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.Writing—original draft preparation: PF. Consulting references: JX, ZW, JT, GL, ZZ. Funding acquisition: HW and HZ. All authors contributed to the article and approved the submitted version.


Sir,We read with great interest the recent publication by Karlsson et al.Hysterectomy may be (i) electively planned after live birth at cesarean section or later; or (ii) due to multiple failed pregnancy attempts, (iii) graft failures from insufficient blood flow or irreversible rejection, (iv) adverse events such as nephrotoxicity, infection or malignancies caused by immunosuppressants, or and (v) psychological burden. Moreover, a second pregnancy after raising a healthy child requires a thorough decision‐making process because of the limited recipient‐graft time.A major concern in UTx is the need for the removal of a failed uterine graft, as UTx is not a life‐supporting organ transplant and differs from conventional life‐supporting transplants in which graft removal generally results in a fatal outcome. In our experiments using cynomolgus macaques, the general conditions, including biochemical parameters, remained good in all animals when graft failures occurred because of ischemia and irreversible rejection.Another concern with hysterectomy secondary to UTx is that the uterus adheres to the surrounding tissues, leading to more time‐consuming and operative complications than in a regular hysterectomy. Furthermore, this operation may involve multiple laparotomies, and the burden  on the recipient is expected to be relatively high. Therefore, maximum consideration should be given to measures that avoid complications, such as placement of ureteric stents as well as multi‐faceted psychological care.Although there is no consensus on the indications and decision‐making for hysterectomy after UTx, when performed following thorough consideration by each team, we hope that the criteria for these exit strategies will be established based on future clinical experience data.


Anthocyanins obtained from jambolan have been used as active agents in different carboxymethyl starch-based tablet formulations and their release profiles evaluated in simulated gastric fluids (SGF) and simulated intestinal (SIF) fluids. Structural analysis highlighted a strong interaction between anthocyanins and carboxymethyl starch, evidenced by scanning electron microscopy and infrared analysis. Tablet dissolution behavior varied according to the pH of the media, being controlled by the swelling and/or erosion of the polymeric matrix. Various formulations for immediate, fast, and sustained release of anthocyanins for 30 min, 2 h and 12 h of dissolution have been developed. It was found that monolithic carboxymethyl starch tablets loaded with powdered jambolan extract efficiently afforded the complete delivery (100% of anthocyanins) to different sites of the simulated gastrointestinal tract and ensured the stability of these pigments, which maintained their antioxidant activity. Syzygium cumini L.), a tropical and underexploited fruit, was used as a source for the extraction of ACNs.Anthocyanins (ACNs) are water-soluble pigments, widely distributed in plants, and responsible for the blue, purple, red, and pink shades of flowers, fruits, and leaves. These molecules present interesting biological properties and are particularly known known as powerful natural antioxidants ,2. In faJambolan is a fruit widely distributed in Latin America that presents an attractive purple colour and an exotic flavour, both provided by the combination of organic acids, sugar, and phenolic compounds . Some stThe effectiveness of ACNs depends on their bioavailability, which corresponds to the amount of ACNs that will reach the systemic circulation, usually referring to the absorption and metabolism of these compounds by the organism ,13,14,15In humans, the complete mechanism of ACN absorption and metabolism are still unclear. Experimental evidence suggested that ACNs are mainly absorbed in the upper gastrointestinal tract  ,17. The To guarantee the bioactivity of ACNs, a practical strategy would be to increase their retention time in sites of the GIT where they are actively absorbed . In thisDifferent polysaccharides have been studied with the aim of protecting and boosting ACNs’ functionality ,27. ACNsThe notable potential that ACNs represent for human health demands the development of strategies to enhance their stability and bioavailability, including preliminary studies that may offer basic information about the behaviour of ACN delivery systems. In this research, ACNs and CMS were associated to produce monolithic tablets for delivery of ACNs into gastrointestinal simulated media. The release of ACNs was evaluated and formulations were developed for their controlled release at different sites of the gastrointestinal tract. To the best of our knowledge, this is the first study to evaluate the use of CMS as an excipient for the delivery of ACNs.The electron micrographs of native starch, CMS and the ACNs:CMS complex are presented in The morphologies obtained from the ACNs and CMS association are shown in −1) and asymmetrical (1600 cm−1) stretching vibration of carboxylate groups (-COO−), are proofs of carboxymethylation of the native starch  vibration and to the stretching vibration (C=C) of the aromatic ring. The band at 1230 cm−1 was assigned to the pyran rings stretching, a flavonoid compounds signature, while the signal at 1340 cm−1 was assigned to C-O angular deformations of phenols  radical cation was evaluated for the ACNs released from C4 tablets. The ABTS•+ radical was prepared according to Konan et al. [•+ and the absorbances were recorded after 1 min of reaction at 734 nm. The results were expressed in µM of Trolox equivalence per mL of solution. The decrease of the initial absorbance of the radical (0.700) was evaluated and plotted against the percentage of ACNs released in the referred medium.The ability to reduce the ABTSn et al. . AliquotThe data generated in the experiments were analyzed in Software OriginPro version 8. The experiments were carried out in triplicate and error bars represent the standard error for three measurements.(n) revealed variations for the anthocyanin release mechanism mainly due to the pH of the dissolution medium, except when ACNs:CMS was pre-stabilized by protonation in gastric acidity. It was possible to develop dosage-forms able to release 100% of their anthocyanin content from 30 min (immediate-release) to 12 h (sustained release), suggesting that the delivery of anthocyanins in different sites of the gastrointestinal tract could be obtained. The carboxymethyl starch was shown to be an excipient suitable for delivery of ACNs, which may increase their structural stabilization and provide enhanced benefits for human health. This paper presents important information for further studies related to the development of delivery systems for ACNs using carboxymethyl starch as carrier.The jambolan anthocyanin extract was associated with carboxymethyl starch to obtain optimized formulations for the gastric and intestinal delivery of ACNs. The release of ACNs was controlled by the CMS matrix which is pH sensitive. The dissolution data were well fitted with the Korsmeyer–Peppas model: the release exponent


Glochidion wallichianum Muell Arg) (MP) extract—was conducted using a variety of developed methods which modified the techno-functionality and digestibility of the end product. With and without the aid of ultrasonication (US), phenolic compounds were complexed with hydrothermally pre-gelatinized rice starch prepared using distilled water or plasma-activated water (PAW). The in vitro digestibility, structural features, rheological and thermal properties, and in vitro antioxidant activity of starch–phenolic complexes were evaluated. The US-assisted starch–MP complex in water had the highest complexing index (CI) value (77.11%) and resistant starch (RS) content (88.35%), resulting in a more compact and stable ordered structure. In all complexes, XRD revealed a new minor crystalline region of V-type, which was stabilized by hydrogen bonding as defined by FTIR and H1-NMR. Polyphenols caused a looser gel structure of starch, as imaged by a scanning electron microscope (SEM). Starch–phenolic complexes outperformed other complexes in terms of in vitro antioxidant activity. Gallic acid addition to starch molecules boosted DPPH scavenging activity, notably when synthesized in PAW regardless of US assistance, although having lower CI and RS values than the MP complex. Therefore, this research lays the groundwork for the efficient production of functional food ingredients based on rice starch and polyphenols.A thorough investigation of the viability of rice starch conjugation with three different phenolic compounds—gallic acid, sinapic acid, and crude Mon-pu ( A high-carbohydrate diet is linked to an increased risk of obesity, diabetes, and cardiovascular disease in both developed and developing countries. Carbohydrates, particularly starch, are the primary source of metabolic energy in foods, accounting for approximately 52% of the calories consumed in the US and up to 80% in developing countries. There is a need for strategies to reduce the caloric impact of starchy foods without compromising their sensory properties . Starch Starch can form inclusion complexes with a variety of small molecules, including alcohols, phenolics, fatty acids, and flavor compounds . AmyloseTo date, several methods for producing starch polyphenol complexes have been developed, which can be classified as traditional preparation methods and thermo-mechanical approaches . High hyGlochidion wallichianum Muell Arg) leaf extract, MP) on the extent of complexation, physicochemical properties, and in vitro antioxidant activity of resulting starch–phenolic conjugates were studied using a variety of analytical techniques. This study’s choice of MP was made due to its strong antioxidant effects and high phenolic content [The current study focused on developing a novel strategy for improving starch–phenolic complexes by employing novel techniques, including plasma-activated water (PAW), ultrasonication (US), and their combination, with hydrothermal treatment and then determining the physicochemical and biological properties of the modified starches. Due to the assumption of greater diffusibility in the starch granule, PAW was used in this experiment instead of cold plasma . In orde content ,25. OverOryza sativa L.), an indigenous underutilized hard rice of Southern Thailand. To obtain flour, NK brown rice (10 kg) was ground in a double-disk stone mill after being soaked in water at a 1:4 (w/v) ratio for 6 h at 4 °C. After that, the slurry was put in a large fabric bag and compressed using a hydraulic press for 10 min. The moisture level of the wet-milled flour was then brought down to about 11% by drying it in a hot-air oven at 60 °C. Using an MK 5087M Panasonic food processor , the dried sample was crushed into a powder form and sieved through a 100-mesh sieve. Rice flour was stored at −20 °C in ethylene–vinyl alcohol copolymer (EVOH) bags until used. The storage period was limited to one month.Wet milling was used to prepare rice flour from Noui Khuea (NK) brown rice (w/v) ratio with 0.3% sodium hydroxide, stirred for 30 min, and allowed to settle overnight at room temperature (27–29 °C). The precipitate was rinsed with distilled water after the cloudy supernatant was carefully drained. Three repeats of this washing process were conducted in order to make the supernatant clear. The precipitate was resuspended in distilled water and passed through a steel sieve with a mesh size of 100. The resulting filtrate (starch) was air-dried for 12 h at 40 °C [In order to extract rice starch, rice powder was mixed in a 1:10  was obtained for 60 min of discharge with pH of 3.0. The freshly prepared PAW was used in the following experiment.The PAW was prepared using air as the working gas, as described by Chaijan et al. . PAW wit2 of the standard curve was 0.9993. The phenolic content was expressed as milligrams of gallic acid equivalents (GAEs) per 100 g of MP.Dried Mon-pu leaf powder  was added with 50 mL of distilled water. The mixture was continuously stirred at 50 °C for 15 h. The mixture was filtered using Whatman No.4 filter paper . The filtrate was freeze-dried, and the powder, referred to as MP, was vacuum packed and stored at −80 °C until used. The total extractable phenolic content in the MP was determined following the Folin–Ciocalteu colorimetric method, using a standard curve of gallic acid (0–100 ppm) . The R2 w/v) gallic acid , sinapic acid , or MP solution in the pre-gelatinized starch solution was performed over a 10 min period. The mixtures were incubated at 70 °C for 2 h with a magnetic stirrer to fully mix the starch and phenolic compound. The paste was cooled to 60 °C before being subjected to ultrasonically for 0 or 30 min with interval pulses of 4 s and an amplitude of 20%  in an ice bath. The mixture was cooled to 25 °C. The mixture was then incubated at 4 °C for 48 h before being centrifuged at 3000× g for 10 min. The precipitate was washed three times with absolute ethanol and dried for 24 h at 40 °C. The native starch was used to compare.The starch–phenolic complexes were prepared from the mixture of each phenolic and starch according to the method explained by Zhang et al. . In a nug for 15 min. The supernatant (500 μL) was combined with distilled water (15 mL) and iodine solution (2 mL). The absorbance (Abs) was measured at 690 nm using a UV–VIS spectrophotometer . The CI values were calculated using the following equation:The CI value was determined according to the method of Tang and Copeland . In brieg/10 min). The glucose content in the supernatant was quantified using the 3,5-dinitrosalicylic acid (DNS) method, and the RDS, SDS, and RS were calculated using the following equations:The contents of rapidly digestible starch (RDS), slowly digestible starch (SDS), and resistant starch (RS) were determined using Englyst et al.’s procedure . In a ce−1 were used to determine the IR absorption in the range of 500–4000 cm−1.FTIR analysis was conducted using a Bruker Model Vector 33 FTIR spectrometer  . Thirty-1H-NMR analysis, native starch and starch–phenolic complexes (10 mg) were dissolved in 0.7 mL of deuterated dimethyl sulfoxide (DMSO-d6) and transferred to 5 mm NMR tubes for 1H-NMR spectroscopy analysis at 500 MHz with a Varian NMR spectrometer  to record the spectra at 25 °C with a 5 mm CryoProbeTM probe following standard Varian Pulse Sequences. Top Spin NMR software  was used to process the NMR spectra [For  spectra .The XRD pattern of the samples was analyzed by an X-ray diffractometer  .The starch granules were adhered to a circular aluminum specimen stub with adhesive tape. After being vertically coated with gold–palladium, the samples were examined using a scanning electron microscope  at a 5 kV accelerator potential .w/v), 9 mL) was added to an aluminum pan and allowed to equilibrate for 6 h before analysis. The pan was heated at a rate of 10 °C/min from 5 °C to 250 °C. Measurements were made of the onset temperature (To), peak temperature (Tp), ending temperature (Tend), and gelatinization enthalpy (ΔH).The thermal property of starch–phenolic complexes was evaluated using a differential scanning calorimeter . The starch slurry (1% (w/v), 2 mL) were immediately transferred between the parallel plates of the rheometer and preheated to 90 °C according to a previous method of Thirumdas et al. [The viscoelastic properties of starch–phenolic complexes were determined using the rheometer . The starch slurries  was mixed with 20 mL of distilled water or mustard oil and stirred for 30 min at 25 °C to determine WAC and OAC. The slurry was centrifuged for 10 min at 3000× C or OAC . WAC andg/15 min) after the samples were cooled to room temperature. The supernatant was decanted into moisture cans that had been pre-weighed. The swelling index was used to express the weight gain. The solubility index was calculated by dividing the percentage of soluble solid in supernatant by the sample weight. Swelling index and solubility index were both expressed as g/g.In pre-weighed centrifuge tubes, starch samples  were mixed with 10 mL of distilled water . The stav/v). The results were expressed as a percentage of inhibition [The 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging activity of samples was determined by measuring the decrease in absorbance at 515 nm. A UV–VIS spectrophotometer  was used to detect absorbance in 1 cm path length cuvette against methanol in aqueous solution . Comparison of means was carried out by Duncan’s multiple range test. The SPSS for Windows 17.0 software  was used.All experiments were carried out in triplicate, and data were collected in the form of mean ± standard deviation (SD). A probability value of p < 0.05). This could be due to the fact that, when amylose molecules were helped by US, a variety of phenolic compounds with varied degrees of hydrophilicity may interact with them more favorably than pure gallic acid and sinapic acid. According to Li et al. [p < 0.05) (p < 0.05), particularly when water was used as a medium with the aid of US  . It was id of US . The comIndeed, the inclusion of phenolics increased the RS and decreased starch digestibility by reducing the activities of digestive enzymes. A V-type amylose inclusion complex is produced by non-covalent interactions between starch and polyphenols that may evade digestion in the small intestine and prevent or treat diabetes and obesity. Meanwhile, starch granules may be employed as an encapsulated delivery matrix to keep polyphenols stable throughout the manufacturing and digestion processes if polyphenols can be kept there by interacting with starch molecules. The digestibility of the starch–polyphenol combination may affect polyphenol release in the human digestive system, thereby improving polyphenol bioaccessibility and health benefits. Most polyphenols with phenolic hydroxyl groups are likely to form hydrogen bonds, hydrophobic interactions, and electrostatic or ionic interactions with starch molecules, resulting in changes in starch digestibility and subsequently affecting starch nutritional properties and phenolic compound release . Phenoli−1. The presence of intense peaks adjacent at 1450–1600 cm−1 was attributed to benzene ring bond stretching, while the bands near 1200–1300 cm−1 were caused by C-O/C-C stretching vibrations [−1. The stretching of aromatic rings caused FTIR absorption bands to appear at 3313, 2925, 1641, 1539, 1410, 1365, 1240, 1148, 1077, 1014, and 664 cm−1 for the starch–phenolic complexes. Interestingly, new signals appeared at 1685 and 1447 cm−1, indicating the presence of a phenolic compound–starch interaction [−1. Starch–MP complexes exhibited absorption bands at 3314, 2926, 1641, 1516, 1411, 1365, 1240, 1148, 1077, 1013, 1077, 1013, 997, and 930 cm−1. Peaks at 2925 cm−1 and 1654 cm−1 showed the stretching vibrations of C-H and carbonyl groups, respectively. The peaks at 1601, 1515, and 1471 cm−1 were attributed to the stretching vibration of the aromatic rings, while the anhydroglucose ring C-O stretch of C-O-H had a band at 1082 cm−1 [−1 has been shown to be sensitive to the crystalline/ordered and amorphous structures of the starch surface, respectively. The FTIR spectra of gallic acid and sinapic acid revealed C=O stretching vibrations at 1697 cm−1, and additional strong signals at 3276 cm−1 and 3520 cm−1, which were assigned to C-H stretching vibration on unsaturated carbon and phenolic hydroxyl stretching vibrations, respectively. FTIR spectra of gallic acid and starch appeared in the mixture of gallic acid and starch; the C-O stretching vibration of the anhydro-glucose moiety at 1047 cm−1, 1081 cm−1, and 1022 cm−1, and additional strong signals at 3320 cm−1 and 2932 cm−1 that were assigned to O-H and C-H stretching vibrations [−1 was acquired in order to distinguish the variations in the molecular order structure of the native and treated starch surfaces [brations . The absbrations . The dec1H-NMR spectra, potentially masking the peaks of other functional groups. However, employing DMSO-d6 as the solvent will result in an excellent separation of the signal peaks in the 1H-NMR spectrum of starch. As a result, 1H-NMR spectroscopy can be used to investigate the interaction between starch and phenolics  at 0–12 ppm  on the surface morphology of the starch–phenolic complex were studied using SEM . The nato), melting temperature (Tp), end temperature (Tend), and enthalpy (ΔH) compared to the native starch (p < 0.05), indicating the formation of a more ordered structure. Starch–gallic complexes had the highest gelatinization temperature and energy (Tp and ΔH) among the phenolics used, implying a denser molecular structure of the resulting complex. These findings are most likely explained by phenolic acid interacting with the starch–water matrix during complex formation, resulting in a shift in gelatinization temperature [perature . Gallic perature . This phperature . Phenoliperature . This maperature .o, Tp, and Tend between the PAW–hydrothermal-made complex and the complex prepared using water as a medium with the aid of US , the WAC of all starch–phenolic complexes was significantly reduced to 6.33–8.68 g/g. Due to the fact that the hydrogen bond was primarily responsible for the interaction between starch and phenolic compound, the inability of the starch moiety to interact with water may explain the low WAC of the resulting starch–phenolic complexes. Starch–MP complexes had the highest WAC among the phenolic-treated samples, followed by gallic complexes and sinapic complexes (p < 0.05). This indicated that the type of phenolic substance used had an impact on the WAC of the resulting complexes. The numerous phenolic constituents in MP with varying degrees of hydrophobicity may interact with starch molecules rather than hydrophilic gallic acid and sinapic acid. It should be noted that the PAW-treated starch, before conjugating with each phenolic compound by hydrothermal treatment, had the lowest WAC (p < 0.05), whereas all samples treated with ultrasound had the largest WAC (The WAC and OAC of the untreated and phenolic-treated starches are shown in gest WAC . The lesp < 0.05), indicating that the formation of starch–phenolic complexes could enhance the interaction with lipids. The highest OAC was observed in all starch–MP complexes (4.22–4.37 g/g), followed by starch–gallic complexes (3.36–3.87 g/g) and starch–sinapic complexes (2.29–2.66 g/g) (p < 0.05). This may be related to the large number of hydrophobic polyphenols found in MP that can hydrophobically interact with lipids. According to Li et al. [All starch–phenolic complexes had a significantly higher OAC than native starch . The hydration property of starch–phenolic complexes, as demonstrated by the WSI, supported this observation (The water solubility index (WSI) and swelling power (SP) of native rice starch and its complex with phenolic compounds are presented in ervation . Previouervation , indicatp < 0.05). The higher antioxidant potential of starch–phenolic complexes was caused by an interaction between starch and phenolic compounds, which varied depending on the structure–activity relationships of the complexes [p < 0.05). As a result, the phenolic type governed the radical scavenging activity of the starch–phenolic complex. This study supports the findings of Van Hung et al. [omplexes . The stag et al. , who foug et al. .1H-NMR, XRD, and DSC analyses revealed that all starch–phenolic complexes formed V-type complexes. In comparison to native starch, the starch–phenolic complexes exhibited increased, DPPH radical scavenging activity, which could be due to the formation of non-inclusive complexes. Overall, the US-assisted hydrothermal treatment produced more complexes than other methods, resulting in the improved molecular inclusion of starch–phenolic complexes and increased in vitro antioxidant activity. This study addressed a novel strategy for improving rice starch–polyphenol inclusions, which may increase interest in the food industry in using novel polyphenol-based starchy functional food ingredients. However, the large-scale manufacturing of the inclusion complex between rice starch and phenolics is required for industrial applications. The release of phenolic compounds from rice starch–phenolic conjugates, as well as the storage stability and usability of the rice starch–phenolic complex generated by this method in food products, will need to be researched further in the future.The CI and in vitro digestibility of the rice starch–phenolic complexes varied according to phenolic type  and method of production . The starch complexed with MP assisted by ultrasonication at a 20% amplitude for 30 min had the highest CI value (77.11%) and RS content (88.35%). FTIR,


We aimed to investigate the clinical characteristics and risk factors for graft rejection after keratoplasty in Japanese patients. We enrolled 730 cases (566 patients) of penetrating keratoplasty , Descemet’s stripping automated endothelial keratoplasty , non-Descemet’s stripping automated endothelial keratoplasty , and Descemet membrane endothelial keratoplasty . The incidence, clinical characteristics, and possible risk factors for graft rejection were analyzed. Graft rejection occurred in 65 cases . The incidence rate of rejection was highest with PK (3.45/100 person-years), followed by DSAEK (2.34), nDSAEK (1.55), and DMEK (0.24). Cox regression analysis revealed keratoplasty type, younger age, indications (such as failed keratoplasty and infection), and steroid eyedrop use as possible risk factors. In the multivariate model adjusting baseline characteristics, PK and DSAEK had significantly higher hazard ratios (HRs) than DMEK . Although not statistically significant, the HR estimate of nDSAEK to DMEK  indicated higher HR in nDSAEK than in DMEK. DMEK is the favorable option among the four surgical procedures to avoid graft rejection after keratoplasty. Additionally, we9 and others11 eliminated Descemet stripping for bullous keratopathies in non-Fuchs type corneal endothelial dystrophy and referred to the modified procedure as non-Descemet Stripping Automated Endothelial Keratoplasty (nDSAEK)9. Moreover, both DSAEK and nDSAEK have proven quite effective for endothelial dysfunction, with rapid visual recovery and minimal induced astigmatism13.Over the past two decades, new lamellar keratoplasties, including Descemet stripping automated endothelial keratoplasty (DSAEK) and Descemet membrane endothelial keratoplasty (DMEK), have been developed to avoid complications caused by conventional penetrating keratoplasty (PK)14, the number of DSAEK and DMEK procedures has dramatically increased in the past two decades, and the number of DSAEK and DMEK procedures was almost comparable by the end of 2021 in the U.S.15. Recently, we reported a significant reduction in PK procedures while DSAEK/nDSAEK and DMEK procedures have significantly increased in our hospital17. Although these modern lamellar keratoplasties may reduce the incidence of immunological corneal graft rejection episodes, graft rejection and subsequent graft failure still occur, even after lamellar surgeries18. However, the incidence and characteristics of graft rejection after nDSAEK remain unclear.Although PK remains a viable optionThis study aimed to investigate the clinical characteristics, risk factors, and probability of immunological graft rejection after keratoplasties, including PK and other novel lamellar keratoplasties (DSAEK/nDSAEK and DMEK), in Japanese patients.Table Table Table Table Table Table P = 0.018, DSAEK; P = 0.022, nDSAEK; and P < 0.001, DMEK). Additionally, no significant difference was observed between DSAEK and nDSAEK . The DMEK group had the lowest hazard estimate of rejection, and significant differences were observed between this group and the other three groups .Figure P < 0.001, 0.005, 0.014, 0.021, and < 0.001, respectively). In the multivariate model with baseline characteristics, the surgical procedure, age, and indications (failed keratoplasty and infection) remained after backward variable selection. For surgical procedure, PK and DSAEK had significantly higher HR than DMEK , and the HR estimate of nDSAEK to DMEK  indicated higher HR in nDSAEK than DMEK, although it was not statistically significant. Moreover, younger age, indication for failed keratoplasty, and infection were identified as risk factors at baseline . In the multivariate model with eye drops, significant effects of eye drops at rejection or last visit (P = 0.019) were observed after adjustment for baseline risk factors. Compared to eye drop non-users at rejection or last visit, a higher risk of rejection was observed in eye drop users .Table The results of subgroup analyses on rejection episodes by demographics, indication for keratoplasty, and simple/combined keratoplasty and graft size that correspond to Tables P = 0.018, DSAEK; P = 0.022, nDSAEK; and P < 0.001, DMEK). Most notably, no significant difference was observed between DSAEK and nDSAEK . The DMEK group had the lowest hazard estimate of rejection, and significant differences were observed between this group and the other three groups . These results are consistent with those of previous studies25, thus confirming the excellent advantages of a lower rejection rate of endothelial keratoplasties compared with conventional PK25; DMEK, in particular, showed the lowest incidence rate of graft rejection, clearly indicating the superiority of this procedure19. To the best of our knowledge, this study is the largest case series of recent keratoplasties in Japan.This study investigated the clinical characteristics, risk factors, and probability of immunological graft rejection after keratoplasty, including PK, DSAEK, nDSAEK, and DMEK in Asian patients. We showed that graft rejection episodes occurred in 65 of the 56 patients  who underwent keratoplasty. In the assessment of each keratoplasty technique, PK had the highest rejection rate  than other types of surgeries, followed by nDSAEK , DSAEK , and DMEK  Table . For imp26: (a) The transplanted tissue is inserted into the anterior chamber and has no exposure to the surface, where antigen-presenting cells and antibodies are present. Hence, anterior chamber-associated immune deviation may be effective. (b) A significant reduction in the number of sutures connecting the host and donor tissues may lead to fewer suture-related rejection episodes. (c) The absence of direct contact between the host stromal vessels and transplanted tissue disrupts the immune effector and effector arcs. (d) Reduced immunogenicity of the donated tissue due to the absence of donor epithelium and the majority of the stroma.The reasons for lower graft rejection after endothelial keratoplasty are as follows33. Several reports support the advantages of nDSAEK, particularly for failed PK, as stripping Descemet’s membrane of failed PK may cause PK wound separation or weakness29. The histology and in vivo observation of the residual host endothelial cells after nDSAEK have already been thoroughly studied, including decreased density, loss of pump function, apoptosis, and altered morphology in a rabbit model by in vivo confocal microscopy34. Additionally, in vivo laser confocal microscopy in human studies after nDSAEK can detect subclinical corneal abnormalities, including subepithelial haze, host-recipient interface haze, host stromal needle-shaped materials, and host-recipient interface particles with characteristic giant particles35. Using immunohistochemistry and transmission electron microscopy, 2 weeks after nDSAEK in a rabbit model, host endothelial cells appeared to be morphologically altered, occasionally detached from the adjacent Descemet membrane, extending into the graft stroma or engulfing strands of the grafted stroma at the interface36. However, the rate of graft rejection after nDSAEK has not yet been reported. Herein, we reported for the first time that the rate of graft rejection following nDSAEK was almost identical to that after DSAEK by a HR similar to that of the multivariate model without eye drops  (Table P = 0.829), indicating that the presence of host Descemet’s membrane showed no difference between nDSAEK and DSAEK in terms of rejection.Clinical outcomes of nDSAEK have been reported to be similar to those of DSAEKIn this study, signs of immunological rejection by slit-lamp biomicroscopic observation at diagnosis in PK, DSAEK, nDSAEK, and DMEK included conjunctival hyperemia , diffuse corneal edema , and keratic precipitates  (Table P = 0.019) were observed; steroid eye drop users had a significant risk of graft rejection compared to non-users of eye drops . According to the postoperative treatment regimen in the “In this study, we investigated the risk factors for graft rejection Table . In the One limitation of this study was the difference in the background diseases of keratoplasty between Japan and other countries. In Western countries, Fuchs corneal endothelial dystrophy accounts for most of the cases of endothelial dysfunction; however, in our study, failed keratoplasty (23.6%), argon laser iridotomy (17.1%), pseudophakic bullous keratopathy (11.2%), and glaucoma surgery (10.7%) were the leading causes, and Fuchs corneal endothelial dystrophy (6.6%) was relatively rare. Nonetheless, this study is the largest keratoplasty case series in Japan and may contribute to the understanding of graft rejection in keratoplasty, which remains a severe challenge for ophthalmologists.In conclusion, our study revealed that the type of keratoplasty was the most significant factor for graft rejection in our cohort. PK showed the highest rejection rate, followed by nDSAEK and DSAEK. Additionally, DMEK showed a relatively low incidence rate of graft rejection, confirming the superiority of this procedure over other types of keratoplasty. The presence of the host Descemet’s membrane showed no difference between the nDSAEK and DSAEK groups in terms of rejection episodes. Considering that patients who are asymptomatic exist in about half of the rejection cases, ophthalmologists should be aware of the diagnosis of rejection episodes during routine postoperative examinations.This retrospective chart review was approved by the Ethical Committee of Kanazawa University Graduate School of Medical Science , and the work was compliant with the Health Insurance Portability and Accountability Act of 1996 and consistent with Good Clinical Practices. It adhered to the tenets of the Declaration of Helsinki, and written informed consent was obtained from all the patients.Anonymized data from consecutive cases of all types of corneal transplantation, including PK, anterior lamellar keratoplasty (ALK), DALK, DSAEK, nDSAEK, and DMEK, in two participating centers in Japan  between January 2006 and December 2020 were collected. However, cases of ALK (N = 6) and DALK (N = 33) were excluded from this study; statistical analysis was impossible due to the small sample size. Cases with patients younger than 40 years old were excluded from this study because these cases were relatively rare in Japan and sometimes quite complicated with multiple surgical histories, which may lead to misinterpretation of the whole data. Cases without chart information regarding the type of eye drop at the time of rejection or the final follow-up visit were also excluded. Additionally, cases with less than 3 months (90 days) of follow-up data were excluded, leaving 730 cases for the analysis of 566 patients. The medical records of these patients were reviewed. Notably, data, including recipient age, sex, diagnosis, types of keratoplasties, surgical histories, duration of follow-up, simultaneous surgeries at the time of keratoplasty, systemic comorbidities , ophthalmic histories , clinical symptoms, final outcome regarding failure or success of the graft, and types of steroidal medications at the time of rejection or final follow-up visit, were analyzed. Moreover, slit-lamp presentations, including conjunctival hyperemia, corneal edema, keratic precipitates, vascularization of the cornea, peripheral anterior synechia, and rejection line, were recorded for patients with graft rejection. Graft failure was defined as an irreversible loss of central corneal clarity with stromal thickening from any cause with or without an endothelial rejection line, inflammation including keratic precipitates, cells in the stroma, and an increase in aqueous cells from a previous visit.For the algorithm used to choose between nDSAEK/DSAEK and DMEK, nDSAEK/DSAEK was the preferred procedure in earlier cases performed between 2006 to 2010, when DMEK was not yet available. Also, nDSAEK/DSAEK was chosen in cases with complex eyes, such as too thick cornea, poor iris visibility, too shallow anterior chamber, and iris defect. DMEK was selected for Fuchs corneal endothelial dystrophy and other types of endothelial dysfunction with good iris visibility and sound posterior capsule.37 or NS Endo-Inserter 38. Domestic eye bank donors dissected with a microkeratome  or precut DSAEK donors internationally shipped from a US eye bank  with a diameter of 8.0 mm were used in most cases. For nDSAEK, neither Descemet’s membrane scoring in a circular pattern nor Descemet’s membrane stripping was performed. DMEK was performed as previously described using a pre-stripped pre-punched pre-loaded donor from a US eye bank  with a diameter of 8.0 mm43.Three trained surgeons performed the keratoplasty surgeries at Kanazawa University Hospital (AK and HY) and Yokohama Minami Kyosai Hospital (TH). PK was performed conventionally with a 10–0 nylon suture using either a running suture or an interrupted suture technique. In most cases, a corneal trephine with a diameter of 7.5 mm with a 7.75-mm donor punch was used for PK. DSAEK was performed as previously described using a double glide  donor insertion techniquePostoperatively, topical 0.5% levofloxacin and topical 0.1% betamethasone were applied five times daily for 1 week, then tapered to four times daily for 6 months, provided they did not indicate steroid-induced glaucoma. After 6 months, topical 0.1% betamethasone was changed to soft steroids, including 0.1% fluorometholone, thrice daily. Moreover, following 1 year, the eyes were usually maintained on once-daily steroid dosing indefinitely as long as no signs or symptoms of graft rejection occurred. In eyes with steroid-induced intraocular pressure (IOP) control problems, topical 0.1% betamethasone was usually changed to a soft steroid, such as 0.1% fluorometholone, and dosing was adjusted as needed to adequately lower IOP. Glaucoma agents were added if necessary. For cases of endothelial keratoplasties, including DSAEK, nDSAEK, and DMEK, 0.1% bromfenac eyedrop two times daily was used for 1 month to prevent postoperative cystoid macular edema.At the time of a rejection episode, topical 0.1% betamethasone was prescribed eight times daily, approximately hourly while awake and oral prednisolone was added in cases where graft rejection seemed severe. The dosage of topical 0.1% betamethasone was maintained for 1 week and gradually tapered to 3–4 times a day for several months. In cases with severe rejection, oral prednisolone or intravenous administration of betamethasone was used.Demographics and other baseline characteristics were summarized with appropriate descriptive statistics, such as mean (SD), by the surgical procedure group, PK, DSAEK, nDSAEK, and DMEK groups. Eye drops at rejection or the last visit and graft outcomes were also summarized. In this analysis, the date rejection was first diagnosed was recorded as the date of the “event” or eyes that did not experience a rejection episode, and the date of the most recent follow-up exam with no evidence of rejection was used to determine the length of follow-up. The findings and graft outcomes were summarized for cases with a rejection episode. To evaluate heterogeneity in demographics and other characteristics among surgical procedures, the Kruskal–Wallis test for continuous variables and Chi-square test for categorical variables were used. Additionally, the incidence rate of rejection was calculated as the time interval after keratoplasty using the person-year method. The time to rejection from keratoplasty was graphically described by the surgical procedure group using the Kaplan–Meier curve. HRs between the groups were estimated using Cox regression, and the curves were compared using the log-rank test. Univariate and multivariate Cox proportional hazards regressions were applied to detect risk factors for rejection episodes. Moreover, the multivariate model with baseline characteristics included surgical procedure, age, sex, hypertension, diabetes mellitus, herpetic keratitis, glaucoma with or without surgery, prior keratoplasty in the opposite eye, indications for keratoplasty, combined surgery, and graft size as exploratory variables, which were selected by backward elimination. Eye drops at rejection or the last visit were included in the multivariate model with baseline characteristics.P < 0.05. Statistical analyses were performed using R, version 4.2.144.Statistical significance was set at Supplementary Information.