Does indocyanine green fluorescence angiography impact the intraoperative choice of procedure in free vascularized medial femoral condyle grafting for scaphoid nonunions? By Markus M, Raymund H, Andreas A, Aijia C, Wibke M-S, Theresa H and Ingo L. (2022) Front. Surg. 9:962450. doi: 10.3389/fsurg.2022.962450A Corrigendum on Incorrect Author NameIn the published article, the authors name were written as Mulica Markus, Horch Raymund, Arkudas Andreas, Cai Aijia, Müller-Seubert Wibke, Hauck Theresa and Ludolph IngoThe correct name order is (first name and surname).Markus Mulica, Raymund E. Horch, Andreas Arkudas, Aijia Cai, Wibke Müller-Seubert, Theresa Hauck, Ingo LudolphError in Figure LegendIn the published article, there was an error in the legend for The corrected legend appears below.After end-to-side anastomosis of the pedicle artery to the radial artery and ICG dye application. The ICG angiography signal indicates patency of the arterial vascular pedicle of the bone graft; ICG, indocyanine green; NIR, near-infrared.Text CorrectionBelow the sections of the article are listed and underlined to which a change was made:A correction has been made to the following section:Surgical technique:This sentence previously stated:The ipsilateral leg in six cases and the contralateral leg in one case were chosen for the MFC bone graft under tourniquet control .The corrected sentence appears below:The ipsilateral leg in six cases and the contralateral leg in one case were chosen for the MFC bone graft under tourniquet control.Surgical technique:This sentence previously stated:A straight and curved osteotome is used to divide the graft from the cortex. Care is taken to avoid separating the periosteum from the corticocancellous portion of the graft.The corrected sentence appears below:A straight and curved osteotome is used to divide the graft from the cortex. Care is taken to avoid separating the periosteum from the corticocancellous portion of the graft .Indocyanine green angiography:This sentence previously stated:“A further unique property of ICG dye is the short plasma half-life of 150–1,80 s due to its hepatic metabolism, allowing repeated injections.”The corrected sentence appears below:“A further unique property of ICG dye is the short plasma half-life of 150–180 s due to its hepatic metabolism, allowing repeated injections.”Indocyanine green angiography:This sentence previously stated:“After the application of SPY Elite, the ICG dye has an absorption maximum at 805 nm and an emission maximum at 835 nm.”The corrected sentence appears below:“The ICG dye has an absorption maximum at 805 nm and an emission maximum at 835 nm.”Postoperative rehabilitationThis sentence previously stated:“After 2 weeks, the palmar long-arm thumb spica splint was changed to a palmar long-arm thumb spica cast, and if swelling decreased to a tolerable level, it was recommended for additional 10 weeks.”The corrected sentence appears below:“After 2 weeks, the palmar long-arm thumb spica splint was changed to a palmar long-arm thumb spica cast, recommended for additional 10 weeks.”Results:This sentence previously stated:The mean follow-up time with CT scan was 9.9 months (range: 6–22 months) .The corrected sentence appears below:The mean follow-up time with CT scan was 9.9 months (range: 6–22 months).Results:This sentence previously stated:“In four cases, Kirschner wires were used for fixation of the graft, which were removed in all cases after 3 months.”The corrected sentence appears below:“In four cases, Kirschner wires were used for fixation of the graft, which were removed in all cases after 3 months .”Results:This sentence previously stated:“About 12.5 mg of ICG dye was initially injected through a venous line after harvesting the bone graft but before vascular pedicle division.”The corrected sentence appears below:“12.5 mg of ICG dye was initially injected through a venous line after harvesting the bone graft but before vascular pedicle division.”Results:This sentence previously stated:“Six patients underwent subsequent procedures, four of which underwent planned Kirchner wire removal and two underwent screw removal.”The corrected sentence appears below:“Six patients underwent subsequent procedures, four of which underwent planned Kirschner wire removal and two underwent screw removal.”The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.


K-means Clustering Analysis, and Discriminant Analysis for data processing. The data processing results indicated that the 44 valid indicators belonging to ten dimensions could be used to measure the level of vulnerability of SMEs whose performance was affected by the COVID-19 pandemic. The surveyed SMEs can be segmented into four clusters, namely resilient cluster, low vulnerability cluster, moderate vulnerability cluster, and high vulnerability cluster. Most of the surveyed SMEs belong to the moderate and high vulnerability clusters. The differences between the clusters were based on 16 indicators. These indicators include levels of supplier disruption and the SMEs’ market in which the SMEs operate or expect to operate. The results of this study help quantify how the pandemic could generate different levels of impact on each indicator that could depend on the business and what policymakers should consider as they contemplate the scale of the required intervention. Overall, this study contributes to the literature on the effects of the pandemic on SMEs by synthesizing the findings of studies on the impact of COVID-19 on SMEs. The study also determined the framework and the equation for measuring the level of SME vulnerability caused by the pandemic.This study has several purposes. First, identify indicators contributing to the performance of small and medium-sized enterprises (SMEs) that could be affected by the COVID-19. Second, formulate the framework to measure the level of vulnerability of SMEs. Third, assign the SMEs into several clusters. Data used in this research were collected through web-based closed questionnaires and short telephone interviews. This study used Content Validity Analysis, Analytical Hierarchy Process, Multi-Attribute Value Theory approach,  The negative impact of the COVID-19 pandemic has been recorded in every aspect of life, with economic, political, social, and psychological implications . AlthougGiven that Indonesian SMEs absorb approximately 97% of the total workforce in the economic sector, contributing about 61.41% to gross domestic product (GDP) in 2018 , it is cDespite the attempts by several studies to explain the impact of the pandemic on Indonesian SME performance, it was not easy to find research that explicitly studied the significant indicators and framework for measuring the impact of the pandemic and then clustering the SMEs based on the level of the impacts. Accordingly, this study seeks to provide insights into the following research questions.1.What indicators contribute to SME performance because of the COVID-19 pandemic?2.How should the framework be formulated to measure SME vulnerability during the pandemic?3.Should SMEs be assigned into clusters according to similar indicators reflecting the impact of the pandemic?Based on these three research questions, our study contributes to the emerging body of literature on the performance management measurement of SMEs such as  and the Recently, the negative impact of the COVID-19 pandemic on SME performance became a topic of interest for many researchers. In detail, According to (a) The pandemic has caused reduced labor productivity in an employee-SWE as employees cannot commute to work. It has also reduced the number of staff, reduced the number of working days, and increased work absenteeism as employees cannot return to work, or they refuse to work due to health concerns . In thisRelated to control over the working condition, according to •Flexibility and employees’ virtual life cycle ,•Use innovative methods to support employees and maintain their health and welfare ,•Use of staff safety measures and focusing on work conditions ,•Managers’ commitment ,•Selection and participation of the employee in decision-making (such as - creating an intimate atmosphere with employees and communicating with them by asking the question: (i) what factors cause your health to be good or bad here? (2) What factors can have a positive and not-so-positive effect on your health? (3) What factors can contribute to the health of the team/unit/employer?•Making changes based on organization assessment and data  In the production process, the pandemic has led to increased production costs, operational difficulties, permanent closure, operational disruption, underutilized or low production, deteriorating workflow and work environment .(c) In the market (on the demand side), the pandemic has led to decreased customer demand, sales, or orders, cancelation of export orders, and decreased sales turnover. However, on the supply side, the pandemic has led to difficulty in obtaining raw materials or services from suppliers; difficulty in supplier communications, increased cost of raw materials, logistical blocks, and supply chain disruptions . Supply-(d) Manufacturers are perpetually confronted with liquidity and profitability issues, and the COVID-19 pandemic has made them even more susceptible to economic shocks . During (e) In the financial condition of SMEs, the pandemic has led to decreased revenue, decreased profit, decreased financial liquidity, little cash on hand, reduced income, and cash flow risk or problems . General(f) In public infrastructure, the pandemic has led to a lack of transportation and un-operational services .(g) In the political and regulatory environment, the pandemic has led to operational difficulties in businesses and the need for financial assistance .The object of research was SMEs in the Central Java Province. These SMEs were sampled to test the framework for measuring the impact of the COVID-19 pandemic on SME performance. There were 104 SMEs located in Semarang, Kudus, Jepara, Pati, Pekalongan, Magelang, Surakarta, Solo, and Cilacap that were sampled. Among the 104 sampled SMEs, 62.50% were in the furniture sector, 9.2% in the culinary sector, 2.88% in the handicraft sector, and 25% in the garment sector. Most of the sampled SMEs (102 SMEs or 98.08%) have fewer than 100 employees, and only two SMEs (1.92%) have over 100 employees.This research employs non-probability convenient sampling to select the SMEs. The SMEs were selected from a community of individuals who were easy to reach or meet, such as friends, coworkers, classmates, and a WhatsApp group. The selection criteria also included their willingness to participate as respondents; they have been in operation for at least a year and were still operating throughout the COVID-19 pandemic. Although there are issues of generalizability in using the non-probability sample, developing research goals is scientifically warranted. Therefore, any sample coverage compromise is outweighed by the cost savings, convenience, target participant, and speed of response.This study also used non-probability purposive sampling to choose respondents who completed the validation and analytic hierarchy process (AHP) questionnaire. These respondents should have sufficient knowledge of the impact of the pandemic on SME performance. This research comprised seven respondents who were willing to participate as the panel of experts. Those seven respondents are representatives from the Office of Cooperatives, Small and Medium Enterprises, Central Java Province  and the indicators from previous measurement frameworks issued by organizations, such as the International Trade Centre (ITC) , EnterprTwo sources of data, primary and secondary data, were used in this research. The primary data sources were the results of the completed web-based questionnaire and short telephone interviews with the SME owner and a representative from the Office of Cooperatives, Small and Medium Enterprises, Central Java Province. The purpose of the interview is to clarify the results of filling out the questionnaire by SMEs so that the respondents who fill out the questionnaire and those interviewed are the same SMEs. Then, the secondary data is intended to complete the documents  that may be required based on the questionnaire results and interviews.Three types of questionnaires were developed in this research. The first was a validation questionnaire with a 4-point Likert scale  to assess the validity of the 54 indicators for measuring the impact of the COVID-19 pandemic on SME performance. Second, an AHP questionnaire with Saaty’s 9-point scale  assessedThe seven URL copies of the first and second questionnaires were distributed to seven respondents through their emails, which consisted of the representative of the Office of Cooperatives, Small and Medium Enterprises, Central Java Province. In this case, the seven respondents should fill out a validation questionnaire (first questionnaire) by giving a value with a range of 1–4 on each of the indicators asked. Furthermore, approximately 2 weeks later, the seven respondents had to fill out the AHP questionnaire (second questionnaires) with a value of 1–9 to assess the importance level of each dimension and indicator. Then, the 125 URL copies of the third questionnaires were distributed to the SMEs through the owners’ emails or other social media accounts. In this case, the owners of SMEs should fill out the questionnaire by giving a value in the range of 1–4 according to the condition faced by the SMEs asked by each indicator. Although email distribution is thought to limit distribution to individuals with computers and email accounts, this was not the case in this study as the respondents’ profiles matched the survey requirements. There were also short telephone interviews with the representative of the Office of Cooperatives, Small and Medium Enterprises, Central Java Province, and the SME owners to further investigate the reasons for choosing a specific value or scale in the questionnaire.Shortly, referring to Several different methods were used to analyze the data. The data from the first type of questionnaire were examined using content validity analysis . The datIn this study, the AHP questionnaire evaluated the level of importance of each dimension and indicator to measure the impact of the pandemic on SME performance. Data were initially processed using AHP with a disseminated pairwise questionnaire given to the panel of experts, consisting of seven respondents or decision-makers. Each of the seven decision-makers initially completed the pairwise comparison at dimension and indicator levels separately. Then, the geometric mean of an individual’s judgments of the level of importance of each dimension and indicator was used to obtain a single value for each dimension and indicator. The geometric mean is used to find a combination of the answer of all decision-makers. In this case, the geometric mean was used to avoid a biased attitude of decision-makers toward a particular importance level . FinallyAt level dimensions, based on the rearranged priority weight in descending order, the ranks of dimensions are as follows: SWE , overall health (OHE) (0.2412), availability of raw material (RMA) (0.1147), market and supplier disruption (MAK) (0.1131), political and regulatory environment (PRE) (0.0965), partnership (PAR) (0.0582), the disruption of building and machinery production process facilities (PPF) (0.0476), economic environment (EEV) (0.1131), public utilities (PUT) (0.0184), and public infrastructure (PIN) (0.0965). In detail, each indicator’s local and global priority weight can be seen in the In the case of a SWE, research conducted by Based on the local priority weight of each indicator and its measurement scale, the level of vulnerability of each SME during the pandemic can be assessed using the MAVT approach. Although MAVT includes different aggregation models, the simplest and most used one is the additive model  as repreAs seen in This study was only able to collect the results of filling out questionnaires from 104 SMEs from 125 SMEs or a response rate of 82.3%. So, based on this condition, the histogram and descriptive statistics of the total value given to each of the 104 SMEs, by considering all indicators simultaneously, can be seen in The average value of the level of vulnerability is 63.6382, with a median of 64.9706, a mode of the smallest value) 54.59, and a standard deviation of 8.798. The value of the level of vulnerability has a positive kurtosis value, indicating a “heavy-tailed” distribution.The K-means clustering algorithm segmented the level of vulnerability of SMEs because of the impact of the COVID-19 pandemic on SME performance. The values reflecting the SME performance for each of the 44 indicators were used as inputs in this algorithm. Referring to the value of the silhouette index (SI), the optimal number of segments equals 4 (four), meaning that four clusters have the highest SI value among other selected numbers of clusters . The average total vulnerability value of each cluster is shown in Referring to After conducting the clustering analysis to obtain the number of parts, the discriminant analysis was performed to determine any significant differences between the parts. The analysis also built a predictive model for each segment, group, or case membership through identification, using the best independent variables or indicators to distinguish between two or more segments, groups, or cases. These independent variables form a distinctive discriminant function .In this study, the discriminant analysis started with calculating Wilk’s lambda to test the equality of the groups’ means for the same variables or indicators. Wilk’s lambda value varies from 0 to 1, where 0 indicates the differences in the parts’ means, and one indicates the similarity of all the segment means. The smaller the lambda value, the more the variable contributes to the discriminant function , 2015. TThe next step was to check the critical discriminating variables by entering a variable into the SPSS software or removing it from the SPSS software  was arranged using SPSS software to predict the location of SMEs in a particular cluster. This function (FLDF) is frequently used for discrimination, classification, and prediction purposes under the usual basic statistical assumptions of multivariate normality of the independent variables, equality of variance and covariance matrices, and the relative equality of group sample sizes. Moreover, Fisher’s linear discriminant analysis technique was used to fit a predictive equation based on the measured variables for classifying new individuals and re-classifying the original data to interpret the predictive equation and better understand the relationships among the variables . The resBased on For example, the SME’s performance is as follows during the -19 pandemic:•The percentage of physically unsafe workers commuting to and from the workplace is 0–10%  (SWE2 = 4)•Most of the areas already have procedures to conduct self-inspections to identify hazards that could lead to the spread of COVID-19  (SWE15 = 2)•The percentage of imported raw materials is less than 5% (RMA1 = 1)•The negative impact of official government measures relating to health concerns for the overall population on your business sales caused sales of the product to decrease by more than 20% (MAK2 = 4)•The level of disruptions experienced by suppliers caused 50% or more of the main suppliers to be unable to supply input to the enterprise (MAK7 = 4)•The enterprise has two substitute suppliers that could deliver goods and services in case of disruption (MAK9 = 3)•Less than 25% of critical inputs and raw materials need to come from foreign suppliers (MAK10 = 1)•Effect of COVID-19 on economic activity has a high impact on the business or the markets you operate in, or you expect it to (EEV1 = 4)•The unemployment rates in the markets in which you operate are 5% to 25% (EEV2 = 4)•Restrictions to accessing public infrastructure have a significant impact on your business or the markets you operate in, or you expect it to (you have to close your operation) (PIN1 = 4)•Increased costs of using key public infrastructure have a moderate impact on business or the markets you operate in, or you expect it to   on the enterprise or on the market in which you operate (PRE1 = 3)•Increased uncertainty in the policy or regulatory environment has a significant impact on your business or the markets you operate, or you expect it to (you have to close your operation) (PRE2 = 4)According to this information and equations 1–4, each cluster’s vulnerability level can be calculated. The calculation results indicated that the total value for the levels of vulnerability for cluster 1 to cluster 4 is 155.3039, 167.4348, 188.2879, and -48.7982, respectively. The calculation results indicated that the SMEs belonging to cluster 3 have high vulnerability as the value for the level of vulnerability for cluster 3 is higher than the others.This research conducted a quantitative analysis to answer the first three research questions. The results demonstrated how to design a framework to measure SME vulnerability in terms of its performance caused by the effects of the COVID-19 pandemic. The results also demonstrated how to segment the SMEs based on the performance of the indicators that were impacted by the COVID-19 pandemic. The measurement framework consisted of 44 indicators belonging to 10 dimensions. It was conducted using the MAVT approach, and the segmentation was conducted using the K-means clustering algorithm and discriminant analysis. The data on the impact of the pandemic on SME performance was collected through online web-based questionnaires completed by 104 SMEs. Those SMEs were located in several regions in the Central Java Province. The segmentation generated four clusters: resilient cluster, low vulnerability cluster, moderate vulnerability cluster, and high vulnerability cluster. Most of the surveyed SMEs fell into the moderate and high vulnerability clusters.The differences between the clusters relied on 16 indicators. However, the differences between the low and moderate clusters relied on the ownership procedures for carrying out self-checks to identify hazards that could lead to the spread of the COVID-19 disease; the number of locations of suppliers or raw materials; and the level of impact of disruption of key public utilities on SME businesses. For comparison, most SMEs in the moderate vulnerability level already have procedures to conduct self-inspections. The market in which those SMEs operate was less affected by key public utility disruptions, and those SMEs have several suppliers in different locations. Consequently, if one of their suppliers cannot work because of policy restrictions or other operational reasons, the SMEs still have other suppliers to guarantee their production process. For example, the SMEs would have to use other suppliers who could deliver material if they could obtain material from their regular suppliers.The differences between the moderate vulnerability cluster and the high vulnerability cluster rely on the levels of the impact of uncertainty in policy or regulatory processes; unexpected rule changes; official government measures relating to health concerns; limitation to public infrastructure access, and the level of impact the number of physically unsafe workers’ commuting to and from the workplace has on the SME business or on the market in which the SME operates. The differences between moderate and high vulnerability clusters also rely on the negative impact of unemployment on the SME’s market, the number of substitute suppliers, and the main supplier’s supply route. On average, SMEs in the high vulnerability cluster have a moderate impact because they decreased their sales by more than 20%. The raw material supply for production was disrupted as they used 25–50% less imported raw material. Indeed, the capability of SMEs and the market in which the SMEs operate to manage the sudden changes in government regulations and the ease of SMEs in getting raw materials for production became important factors that differentiated between being a resilient or a high vulnerability cluster.This research contributes both to theory and practice. Theoretically, this research contributes to the literature on multi-criteria decision making, performance management, and the effects of the COVID-19 pandemic on SMEs in four ways. First, this research synthesized the findings of the reviewed studies of the impact of the pandemic on SME performance by grouping them into six main themes consisting of various SME-related issues, such as employee- SWEs, production processes, markets, and economic conditions, financial conditions, public infrastructure, and the political and regulatory environment. Second, this research synthesized the findings of the reviewed studies on the pandemic’s impact on SMEs by developing a framework based on multi-criteria decision-making for measuring the level of SME vulnerability caused by the effect of the pandemic on their operations. Third, this research found how the framework can help cluster SMEs into four main clusters: resilient, low vulnerability, moderate vulnerability, and high vulnerability. Accordingly, this research attempts to improve the understanding of the indicators in question: which indicators help differentiate the impact of the COVID-19 pandemic and provide a guide for future studies in this area. Fourth, in addition to clustering the SMEs, this research determined the equation to assess which cluster an SME can be placed in based on its indicator performance. Fifth, in addition to summarizing this research’s knowledge of the COVID-19 pandemic and SMEs, it outlined how this knowledge was acquired (methodology) and in which contexts the knowledge applies. These findings can help shape decisions about methodology and context in future work. Finally, this research identified gaps in the study domain of the impact of the COVID-19 pandemic on SME performance and suggested unique research questions and opportunities for meaningful future research to fill those gaps.Practically, the results of this study make recommendations for SMEs and the government. Using a measurement framework and the discriminant equation that resulted from this research, SMEs can understand their level of vulnerability in terms of specific impacts of the COVID-19 pandemic. Thus, SMEs can adapt to the new situation quickly and reduce damage. However, one of the most important conclusions of the current research is that supplier and market disruptions can make SMEs more vulnerable. To reduce SME vulnerability during the COVID-19 pandemic, the SME management or owner should proactively and informatively communicate with their suppliers and customers.The SMEs should also have a contingency plan to buy from numerous suppliers, changing from foreign to domestic suppliers. It is suggested that SMEs propose innovative marketing by adopting digital media and using the Internet for business operations. They should also manage customer loyalty as the pandemic has negatively affected business sales. By embracing digital media or the Internet, SMEs can present their products effectively despite customers being unable to visit their business premises. Consumers can have a thorough understanding of what products are available and which products they want. Consumers can communicate online with sellers about products without restraint during the pandemic. Furthermore, digital media enables users to display buyer testimonies, record the number of visitors, and make specific offers to consumers. These activities have proven effective in creating sales, attracting new customers, and maintaining SME performance.Moreover, to manage customer loyalty, SMEs should offer more reasonable prices given high unemployment levels or other changes in regulations that could affect their markets. The SME should also consider designing alternatives for customers in restricted areas, such as providing collection and delivery services. The SME management or owner should maintain long-term relationships with customers, which are vital to maintaining sales. Strengthening customer relationships may help SMEs to maintain their performance.It is recommended that the government consider the current situation and the level of SME vulnerability and reduce tax and other costs. Given their vulnerability, the government should offer SMEs a stimulus package to avoid enterprise closures and bankruptcies. The government should also assist SMEs in distributing their products or using SME services. The sudden changes in government regulations can affect SMEs or the markets they operate in or expect to operate. The most common type of assistance received by SMEs was the distribution of goods.Finally, we acknowledge some limitations of our study concerning the sample and employed techniques, which future research should address. First, this study was limited geographically. The sample in our study included a small number of cases, limited to only SMEs in several regions in the Central Java Province. Second, we only measured the impact of the COVID-19 pandemic on general SMEs and did not focus on particular sectors or industries. The inclusion of specific sectors or industries may identify a specific impact on how that sector or industry will be more severely affected than others. This limitation may also reveal an opportunity to compare resilient and vulnerable SMEs in different sectors or industries, thus generating a more reliable response. Future research could benefit from replicating our work in similar and dissimilar contexts: in each sector, business activity and size, and a wider geographical area could be considered, including a nationwide study. Such research could allow for more accurate measurements of the pandemic’s impact on each indicator’s performance based on sector or industry.Future studies could adopt a complementary regression approach (OLS and PLS) and the ISM approach regarding the quantitative analysis techniques. In this case, the OLS and PLS estimations could determine the relationship between one or more explanatory variables , and the SME financial performance during the pandemic. Finally, the ISM approach could help us articulate the mental models of the relationship between the indicators used in this research.The original contributions presented in this study are included in the article/The study protocol was reviewed and approved by the Review Board of Industrial Engineering Department, Diponegoro University. Written informed consent from the participants was not required to participate in this study in accordance with the national legislation and the institutional requirements.AS, NP, and AB conceived and designed the study. FP participated in the acquisition of data. AS, NP, and FP analyzed the data, gave advice on methodology, and drafted the manuscript. AS and AB revised the manuscript. AS was the guarantor of this work and had full access to all the data in the study and takes responsibility for its integrity and the accuracy of the data analysis. All authors read and approved the final manuscript.


Starch is the main carbohydrate source in most lab mouse diets. Its properties are influenced by feed processing. This determines how easily accessible it is to enzymatic digestion in the gastrointestinal tract of animals. In previous studies we have shown that there are differences between pelleted and extruded forms of a maintenance diet fed to mice regarding digestibility and microbiome. To complement these findings, the present study presents a morphological study of the starch particles throughout the passage along the gastrointestinal tract of C57BL/6J mice fed either pellets or extrudate. Samples were stained with Lugol’s iodine and examined via stereomicroscope and scanning electron microscope. Starch granules in the pelleted diet are mostly intact and compact, thus autoenzymatic digestion in the small intestine is less efficient than in the more accessible starch granules from the extruded diet. For both diet forms, starch accumulation in the caecum was observed, suggesting selective retention of praecaecally undigested starch for microbial fermentation. These findings allow for unique insights in murine starch digestion that are important to understand the digestive physiology of this species.Diet processing impacts on starch properties, such as the degree of starch gelatinization. This affects digestibility, as shown in laboratory mice fed either a pelleted or an extruded diet. In the present study, the morphology of starch particles throughout the digestive tract of mice was visualized. Thirty-two female C57BL/6J mice were used for a feeding trial. They were fed a commercial maintenance diet for laboratory mice, which was available in pelleted and extruded form, for seven weeks. The mice were sacrificed after the feeding period, and chyme samples were collected from five sites . Samples of diets, chyme and faeces were analyzed via stereomicroscopy (stained with Lugol’s iodine) and scanning electron microscopy (SEM). The starch granules appeared more compact in the pelleted diet, showing first signs of degradation only in the small intestine. The caecum content of both diets group was intensively stained, particles as well as fluid phase, indicating that it contained mainly starch. The SEM pictures of caecum content showed abundant bacteria near starch particles. This suggests selective retention of prae-caecally undigested starch in the murine caecum, likely the site of microbial fermentation.  Rodent species show a wide variety of adaptations to their respective diet spectrum. They are typically hindgut fermenters with a well-developed caecum , the comStarch properties, especially the structure of the starch granules, differ between the botanical sources. The structure of the granules may limit digestibility , dependiAccording to its digestive characteristics, starch can be classified into rapidly vs. slowly digestible starch . For exaAn increase in starch gelatinization by heat processing increases energy digestibility and thus growth performance in pigs  and miceThe kinetics of starch degradation and digestion have been thoroughly investigated in livestock, as described above. There are species differences related to the functional morphology of the gastrointestinal tract. In mice, which are commonly used as laboratory animal, basic information on starch digestion is lacking. Because of the influence of starch digestion on energy utilization and intermediary metabolism ,13, suchEthical approval for the use of animals was obtained from the Ethics Committee of the Veterinary Faculty of the Ludwig-Maximilians-Universität München (reference no. 169-03-05-2019). Data on digestibility and microbiome from this study were reported previously ,21.For the trial, 32 eight-week-old C57BL/6J mice were used . Female mice were chosen so that pair-housing for the duration of the trial was possible. Mice were kept in a specific-pathogen-free facility . Feed and water were available ad libitum. After adaptation to the surroundings, the mice were allocated randomly to two groups: Group PEL was fed a commercial maintenance diet for laboratory mice in pelleted form, group EXT received the same diet in extruded form. The diets were purchased from the same manufacturer and were labelled as identical maintenance diet for laboratory mice, available in pelleted and extruded form. Wheat was the major starch source in both diets.A digestibility trial was conducted as described previously . After sDiet samples were ground, dried and analyzed in for gross energy  and crude nutrient content  by standard methods . DietarySamples of both diets were crushed, stained with Lugol´s iodine and examined microscopically . Of four animals per diet group, gastrointestinal content from different sites  was collected from the fresh carcasses. Faeces was collected from the cages. g, 5 min; Eppendorf 5810R, Eppendorf AG, Hamburg, Germany). The phase of sediment stained dark blue with Lugol´s iodine  and markers inserted in Adobe Illustrator® . The chyme and faeces samples were mixed with distilled water (1:5) for pH measurement (pH data reported previously ). After s iodine  was used®, Adobe Inc., San Jose, CA, USA). Marker symbols were added if necessary .Samples of diets, gastrointestinal content (sampling sites see above), and faeces were used for scanning electron microscopy . From the diluted samples described in the stereomicroscopy section, 100 µL were transferred on a round glass slide attached to an aluminum sample holder with a carbon glue pad . The sample was then sputtered using the Balzers Union SCD 040  with the sample holder on 6 cm height. The slide was sputtered with gold-palladium coating with 15 mA for 310 sec until achieving a layer thickness of 12 nm. After this preparation, the sample holders were inserted into the SEM and examined with 10 kV. The SEM pictures were color corrected and adjusted for brightness and contrast (Adobe PhotoshopDiet composition is summarized in Staining the intact pellets and extruded kibbles with Lugol´s iodine resulted in blue coloration, showing the presence and distribution of starch in the diets . The extAfter centrifugation, there were blue areas in the sediment in the diet and chyme samples from the stomach, small intestine and colon (example diet: Stereomicroscopy images show starch particles stained by Lugol´s iodine in blue, enabling a qualitative description. The figures presented for publication were chosen representative for the respective sampling site. Microscopic evaluation of the diets showed a high number of small, round stained particles in diet PEL. Diet EXT contained stained particles of irregular shape and also a bluish stain in the fluid phase . In the stomach content, the blue-stained particles were similar to those in the respective diet regarding amount and shape. EXT stomach samples showed few small, round stained particles, large stained particles and a bluish haze around the particles . Chyme from the anterior small intestine of group EXT mice contained a much lower number of stained particles visible than in the stomach samples . In grouCaecum content samples from both diet groups were difficult to get into focus using the light microscope . The fluIn the colon content, a smaller amount of stained material was found compared to the other gastrointestinal samples . PEL samFaecal samples also did not contain many starch particles. The single particles that were stained in those samples were of irregular shape, but relatively compact and without a smear or haze in the fluid phase . There wThe focus of the SEM visualization was on the starch particles in the different samples. For each sample or sampling site, a representative figure was chosen for publication. diet PEL, the starch particles were visible as compact, round structures (In ructures A, while ructures B. Stomach content samples showed starch particles shaped similarly to the respective diet sample . In bothStarch particles in the anterior small intestine of both diets showed the beginning of disintegration with small pinholes . In the In the caecum content of both diet groups, crystalline rectangular structures were found . Figure Stereomicroscopy and SEM images show the morphology of starch particles, indicating differences between the diets and changes throughout the gastrointestinal tract. The shape of the starch in the pelleted diet was typical for cereal starch in a processed feed ,15. TherStomach content showed a similar morphology of starch particles as in the diets. Bacteria were present as depicted on the SEM images of stomach content . This isThe SEM pictures from small intestinal content displayed the beginning enzymatic digestion of the starch granules by pancreatic amylase. Pinholes appeared as a first sign of damage to the granules , especiaAddition of Lugol´s iodine lead to complete blue or blue-violet staining of the caecum content samples, indicating a high abundance of starch in this compartment . Every pIn the colon content samples, the abundance of starch particles was much lower than in the previous gastrointestinal sites. However, the samples from the PEL group showed diffuse staining of starch in the soluble phase and larger, irregularly shaped particles. This suggests that there was a part of the starch escaping both auto-enzymatic digestion in the small intestine and microbial fermentation in the caecum. Either the larger starch particles were not retained in the caecum for fermentation, as speculated above for the main amount of starch, or it may be resistant starch not even degraded by the microbes.Faeces samples did hardly contain any stained starch particles at all. This is in accordance with the ≈99% apparent total tract digestibility of starch in both diet groups. Starch digestion and fermentation seem to take place in the small intestine and the caecum, utilizing nearly the entire amount ingested. The present morphologic study shows differences in the ratio of these two processes due to diet processing.The morphology of starch particles in the diet differs according to diet processing. This difference influences the morphological changes of starch during the digestive process in mice, as observed via stereomicroscope and SEM. The number of starch particles in the posterior small intestine and the caecum suggests differences in small intestinal starch digestibility according to processing. The accumulation of starch, combined with the presence of bacteria, in the caecum suggests the selective retention of starch for microbial fermentation in the murine caecum.


With this book, Jost Reischmann presents an impressive collection that has the potential to become a “must-have” for people who deal with adult education in an international context. The emeritus professor from Bamberg (Germany) has compiled key texts covering more than 100 years of comparative and international adult education research, ranging from its early forms to the present. The earliest item in the collection is from 1900 by Michael E. Sadler from Britain; it addresses the still pertinent question of what we can learn for our own practice from studying foreign education systems. Sadler’s text demonstrates that an international perspective already existed at the beginning of the professionalisation of the field of adult education. One of the most recent texts, co-authored by Qi Sun (USA/China) and Elizabeth Erichsen (USA) is from 2012. They raise the question of how to bridge the Western and Eastern worlds of adult education – a question perhaps even more relevant and important than ever in these war-ridden times.The colourful spectrum of 30 seminal texts is presented in eight sub-sections, spanning the following categories: history/development; travellers and their reports; international/programme reports/country reports/juxtaposition; comparative studies; international organisations and institutions; lessons learned; epilogue 2000–2020; and observations/perspectives. Each of the items in the collection is preceded by an introduction of the respective author(s) and a few editorial remarks. These introductions help the reader access the texts, although many of the featured authors are well-known to scholars in the field. Some readers might have wished for the editorial remarks to be longer, since they are quite insightful. The value of this book should not be underestimated, because to my knowledge this is the first time that classic texts of the field of international and comparative adult education are brought together in one volume. In this respect, this anthology will be a valuable resource for teaching.One criticism, however, is that there are too many White, Western, English-speaking men represented in this volume. To be fair, Reischmann himself addresses this issue by pointing out that the compilation reflects how international and comparative adult education research was visibly set up decades ago. Here it would take more in-depth historical research and effort to make significant contributions by women or non-Western countries more visible. Thus, the whole volume can also be understood as an invitation to dig deeper and search for perhaps lost or hidden traces.The significant increase of contributions by women among the more recent texts greatly enriches the book. In this regard, I would like to point out a very interesting article by the Serbian scholar Katarina Popovic at the end of the volume. However, equal gender representation is still far from being achieved, as is equal representation of the Global North, Global South, Global West and Global East. There is still a lot of work to do for the field in order to become truly international beyond anglophone international.At the end of the more than 300 pages of the volume, Jost Reischmann offers his own observations and perspectives. He also critically reflects on how the texts were collected for this publication. His honest and critical discussion of the limitations of the book will inspire future generations of authors who want to engage in a similarly bold endeavour. Information is also provided on the current state of international comparative research and where the journey of the field might lead in future. While he does not idealise the situation, he provides a rather critical inventory.After two pandemic COVID-19 years with many travel restrictions and even closed borders, I was struck by the observations of how important travel is for international comparative research and what role international friendships have played in both the past and the present for everyone involved. In this respect, the articles and the entire volume do not represent a sober, distanced analysis of a cold-blooded scholar, but a committed and humane plea for an international dimension in adult and continuing education that goes beyond competition and country comparisons à la PISA. For example, some of the contributions are related to peace education, an issue many of us have lost sight of in light of the prominence of economic development. Overall, the personal engagement and empathy of the editor Jost Reischmann comes through very strongly.It will be exciting to see how comparative and international adult education research and practice will continue to develop over the next few decades. The achievements of previous generations should not be intimidating, although they are impressive, as this volume demonstrates. This book is highly recommended to readers who are interested in the history of the field of adult education and/or who wish to get an overview of the key contemporary issues in the field and want to do international research. This volume constitutes a truly essential contribution, although the history and histories of the field are certainly even more pluralistic than the volume has been able to capture. The present and the next generations of researchers should build on this valuable book and take it as an invitation to shed more light on other houses and rooms not known to all of us yet.


The aim of this study was to explore a new model of clinical decision-making to predict the occurrence of clinically significant prostate cancer (csPCa).The demographic and clinical characteristics of 152 patients were recorded. Prostate-specific antigen (PSA), PSA density (PSAD), adjusted PSAD of peripheral zone (aPSADPZ), and peripheral zone volume ratio (PZ ratio) were calculated and subjected to receiver operating characteristic (ROC) curve analysis. The calibration and discrimination abilities of new nomograms were verified with calibration curve and area under the ROC curve (AUC). The clinical benefits of these models were evaluated by decision curve analysis and clinical impact curves.p = 0.0284) compared with the base model. In addition, the new model was better than the base model for predicting csPCa in the low or medium probability while the number of patients with csPCa predicted by the new model was in good agreement with the actual number of patients with csPCa in the high-risk threshold.The AUCs of PSA, PSAD, aPSADPZ, and PZ ratio were 0.521, 0.645, 0.745, and 0.717 for prostate cancer (PCa) diagnosis, while the corresponding values were 0.590, 0.678, 0.780, and 0.731 for csPCa diagnosis, respectively. All nomograms displayed higher net benefit and better overall calibration than the scenarios for predicting the occurrence of csPCa. The new model significantly improved the diagnostic accuracy of csPCa (0.865 vs. 0.741, This study demonstrates that aPSADPZ has a higher predictive accuracy for csPCa diagnosis than the conventional indicators. Including aPSADPZ, PZ ratio, and age can improve csPCa diagnosis and avoid unnecessary biopsies. Prostate cancer (PCa) has become the second most common male cancer that affects approximately 375,000 men/year worldwide . The incAll patients were counseled about the risks of the procedure, and then, they signed a consent form that included permission to use their clinical data for research. Ethical approval was obtained from the Institutional Review Board of The First Affiliated Hospital of Soochow University.−1, 27 were not able to undergo MRI examination, and the remaining 689 received a transperineal PB. Among them,139 with PIRADS 2, 181 with PIRADS 4, and 217 with PIRADS 5 were excluded, and 152 with PIRADS 3 were included in this study. The patient selection flowchart is shown in In this retrospective cohort study, patients with PCa were recruited at The First Affiliated Hospital of Soochow University  from July 2016 to June 2020. A total of 824 male patients presented to our institution for prostate biopsy (PB). Of these patients, 45 had prior treatment, 63 had prostate-specific antigen (PSA) > 100 ng ml−2, 800 s mm−2, 1,000 s mm−2, and 1,500 s mm−2), with diffusion-sensitizing gradients applied along the x-, y-, and z-axes. Dynamic contrast-enhanced (DCE) imaging was conducted through a 3-dimensional T1-weighted gradient-echo volumetric interpolated breath-hold examination, and was in the same plane as the 3D T2W sequence. Then, an intravenous contrast agent  was administered at 1 ml kg−1 body weight and 2.5 ml s−1 injection rate. The MR Tissue4D software  was used to construct perfusion curves. The details of the imaging protocol are shown in All patients were subjected to a 3-T magnetic resonance (MR) scanner . The 18-channel body and standard spine array coils were employed for signal reception. The transverse T1-weighted turbo spin-echo (TSE) images, as well as the transverse, coronal, and sagittal T2-weighted TSE images of the prostate and seminal vesicles were acquired. The apparent diffusion coefficient was obtained from diffusion-weighted imaging (DWI) and was calculated using a 2-dimensional echo planar imaging sequence with multiple b-value acquisitions  and systematic biopsy (SB) were performed on all patients. During TB, the DICOM data of mpMRI images .The patients’ age, pre-biopsy PSA, free/total PSA(f/tPSA), and pathological features were included in the study. The included MRI characteristics were PIRADS scores, prostate volume (PV) [prostate volume (PV) = 0.52 × height × length × width]  and area under the receiver operating characteristic (ROC) curve (AUC), respectively. The nomograms were also validated using an internal validation cohort . The clinical benefits of these models were determined by decision curve analysis (DCA). In this case, we focused on 10%–40%, in which clinical decision-making is particularly difficult. The AUCs of both models were compared using methods described previously . Other statistical tests were conducted with SPSS v22.0  and MedCalc v18.2.1 . All reported p-values were two-sided and the level of statistical significance was set at p < 0.05.Categorical and continuous variables were analyzed using the Pearson’s chi-squared test and Mann–Whitney eviously . In DCAsOverall, 19.1% of patients (29/152) had histologically confirmed PCa, while 11.8% (18/152) had histologically confirmed csPCa. The clinical data of all patients are summarized in As shown in Z value: 3.488, p < 0.01; aPSADPZ vs. PSAD, Z value: 3.169, p < 0.01) and csPCa diagnosis . The AUCs between aPSADPZ and PZ ratio for PCa diagnosis  and csPCa diagnosis  had no statistical difference.ROC curve analysis revealed that the AUC for aPSADPZ in the diagnosis of PCa and csPCa was 0.745 and 0.780, respectively. Compared with other parameters, PSAD was 0.645 and 0.678, PZ ratio was 0.717 and 0.731, and PSA was 0.521 and 0.590, respectively Figure 3p = 0.0931; csPCa: 0.865 vs. 0.741, p = 0.0284) for predicting csPCa   showed that the PZ ratio could be used as a predictor of PCa. We believe that PVI and PZ ratio have the same diagnostic efficacy because they both represent the percentage of the PZV in the PV. Thus, we only chose PZ ratio for PCa prediction. Koo et al. . Further validation of the new model for diagnosing csPCa indicated its excellent performance. In the defined region of interest (10%–40% probability), which means difficulty in making clinical decisions, the net benefit of the new model is higher than that of the base model in the DCA. It means that when the probability of csPCa is moderate or low, which makes it difficult to make a clinical decision as to whether to biopsy or not, the new model can increase the rate of detection for csPCa and avoid unnecessary biopsy. The new model is more suitable for guiding clinical decision-making in men with PIRADS 3. On the other hand, we found a good calibration between the actual and predicted probabilities of the new model in the region of high probability. Taken together, for low or medium probability populations, the new model can detect more csPCa and reduce unnecessary biopsies, while for high probability populations, it will not miss csPCa and cause adverse outcomes.Eastham et al.  reportedOur study has several limitations: (1) This was a retrospective study performed at a single institution with a possible risk of selection bias. (2) PIRADS scores are dependent on the experience of the radiologist, and may vary from physician to physician. (3) The definition of csPCa used in this study does not include all clinically significant diseases, in that ISUP GG1 with a high tumor volume load may be significant and ISUP GG2 with a low tumor volume load may be insignificant. (4) We did not consider an upgrade or a downgrade of Gleason scores in specimens after radical prostatectomy, which may be a limitation for the determination of csPCa.In summary, aPSADPZ has a higher predictive accuracy for the diagnosis of PCa and csPCa in biopsy-naïve men with PIRADS 3 than the conventional indicators, which may decrease the risk of misdiagnosis and reduce the number of unnecessary biopsies. The prediction model of aPSADPZ, PZ ratio, and age can improve csPCa detection, increase diagnostic accuracy, and avoid unnecessary biopsies.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by the Institutional review board of The First Affiliated Hospital of Soochow University. The patients/participants provided their written informed consent to participate in this study.CH helped in project development and data analysis, and wrote the manuscript. FQ was involved in project development and data collection, and wrote the manuscript. DJ was involved in project development and data analysis and wrote the manuscript. JP and XW helped in data analysis. ZC performed the statistical analysis. XW helped in the drafting of the manuscript. XZ, LG, and JH helped in data collection. YH helped in project development and edited the manuscript. All authors contributed to the article and approved the submitted version.This work was supported by two grants from the Key Research and Development Program of Jiangsu Province (No. BE2020654 and No. BE2020655) and a grant from the General Program of Jiangsu Health Commission (No. H2019040).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The as-prepared materials were characterized by X-ray diffraction, scanning electron microscopy, and UV-Vis diffuse reflectance spectroscopy. It was also found that RbNbTeO6 with β-pyrochlore structure was not able to photocatalyze the reaction. Enzymatic hydrolysis of the obtained graft copolymers proceeds with the formation of peptides with a molecular weight (MW) of about 20 and 10 kDa. In contrast to collagen, which decomposes predominantly to peptides with MW of about 10 kDa, the ratio of fractions with MW of about 10 kDa and 20 kDa differs much less, their changes are symbatic, and the content of polymers with MW of more than 20 kDa is about 70% after 1 h in the case of graft copolymers. The data obtained indicate that synthetic fragments grafted to the collagen macromolecule do not prevent the hydrolysis of the peptide bonds but change the rate of polymer degradation. This is important for creating network matrix scaffolds based on graft copolymers by cross-linking peptides, which are products of enzymatic hydrolysis.Graft copolymerization of methyl methacrylate onto cod collagen was carried out under visible light irradiation (λ = 400–700 nm) at 20–25 °C using the RbTe The creation of new generation materials with required performances and high reliability is inextricably linked with the use of new approaches. Much attention in recent years has been paid to investigations related to the principles of green chemistry. Photocatalytic complexes based on metal oxides are an environmentally friendly alternative to chemical sources of active particles in the conversion of various chemicals ,2. TheirTheoretical and experimental studies that make it possible to develop fundamentally new ways to obtain the creation and application of environmentally friendly technologies with the required properties are an urgent task. An actively developed strategy in this direction is the development of compositions based on large-scale synthetic polymers and natural origin polymers. The main advantage of these materials is the unique combination of the component properties assembled in a certain structure. One of the most important consumers of such materials is regenerative medicine associated with the stimulation of cellular/tissue regeneration ,32,33,34•OH), are formed in aqueous solutions in the presence of metal oxides under ultraviolet or visible light irradiation . Ap. Ap56]. The obtained results of the enzymatic hydrolysis of GCMC are important for modeling the process of creating network matrix scaffolds based on them by cross-linking peptides, which are products of enzymatic hydrolysis. It is important that the destruction of GCMC is longer compared to that of collagen. The decrease in the rate of hydrolysis is obviously associated with steric hindrances during the interaction between the active site of the enzyme and the grafted copolymer . The gra1.5W0.5O6, CsTeMoO6 and RbNbTeO6 complex oxides with β-pyrochlore structure to evaluate their photocatalytic activity. It was demonstrated that the RbTe1.5W0.5O6 and CsTeMoO6 materials are capable of photocatalyzing the formation of graft polymers PMMA–collagen from the collagen and MMA mixture under visible light irradiation (λ = 400–700 nm) at 20–25 °C. This was confirmed by GPC and elemental analysis. The use of the RbNbTeO6 complex oxide did not allow for the obtainment of noticeable amounts of grafted MMA onto collagen under the reaction conditions.A series of photocatalytic graft copolymerization experiments was carried out using the RbTeMoreover, the enzymatic hydrolysis of the resulting graft copolymers was carried out. It was shown that PMMA-collagen graft copolymers rapidly undergo hydrolysis to peptides with MW of about 20 kDa and predominantly with MW of about 10 kDa. In contrast to collagen, which decomposes predominantly to peptides with MW of about 10 kDa, the ratio of fractions with MW of about 10 kDa and 20 kDa differs much less, their changes are symbatic, and the content of polymers with MW of more than 20 kDa is about 70% after 1 h in the case of graft copolymers. Monitoring the process of enzymatic hydrolysis for 3 days indicates a gradual decrease in the content of polymer with MW of more than 20 kDa to almost zero values and a decrease of MW to 20 and 10 kDa. The obtained results allows for the conclusion that synthetic fragments grafted onto the collagen macromolecules do not prevent the hydrolysis of peptide macromolecules but change the rate of polymer degradation. This investigation shows the attractiveness of the prepared materials for the creation of scaffolds in tissue engineering.The demonstrated advantages of graft copolymers of methyl methacrylate onto collagen, obtained using novel photocatalysts, indicate the possibility of constructing biogels based on them by introducing additional components to obtain three-dimensional structures and test cytotoxicity. These studies could be a continuation of the presented work.


The development of novel and sustainable food products, such as cheese- and meat analogues, requires a better understanding of the use of less refined ingredients. We investigated the distribution of water between the protein and starch phase of doughs and heat-induced gels made from air-classified faba bean fractions by developing a method suited for investigation of such multi-component ingredients. The moisture contents of the protein and starch phases in the dough were determined using a method based on partial sorption isotherms of mixed doughs of protein- and starch-rich fractions at high water activity. Water content of the protein phase is higher than that of the starch phase in dough, showing that protein takes up more water than starch at room temperature. Also, the moisture content of the protein phase in the gels was calculated using a model based on the denaturation temperature of legumin. From the experiments and the modelling, it became evident that the moisture content of the protein phase in the gel is lower than the moisture content of the protein phase in the dough, showing the importance of considering moisture migration from the protein to the starch during heating.  •Water distribution among phases in doughs and gels is measured “in-situ”.•Addition of starch increases water content of protein phase in doughs.•Water migrates from protein to starch after initial starch gelatinization. This understanding is especially important in soft-solid products like cheeses and meat but even more so for the plant-based alternatives of those products. Thus far, the products are mainly based on soy, pea or wheat, but interest in the use of other raw materials is increasing. Faba beans are considered as one of the promising new crops to provide healthy plant proteins . It is tMeat and cheese analog products are characterized by having a dry matter content of around 20–40% in the water phase, which gives high water activity. Besides, multiple aqueous phases can be present in those products. The water content in each phase of such materials has a large influence on properties such as gelling behavior and thereby on the properties of the final product. Thus far, research on the influence of starch on protein gelation and vice-versa, as well as research on the influence of water content on product properties of soft-solid products, is often limited to the use of pure components, meaning isolates . The useStarch gelatinization is a clear example of the effect of water content on food properties. Although the initial gelatinization of starch occurs at a gelatinization temperature independent of the moisture content, the magnitude of gelatinization at said temperature decreases with the water content . In caseaw > 0.96). This high aw is relevant when considering products like meat and cheese analogues that have a moisture content between 40 and 80% The aim of this research is to determine how starch and protein content influence the water distribution in unheated doughs and heat-induced gels that are prepared from mixtures of mildly refined ingredients. For this, we developed new methods for the determination of the water distribution in doughs at room temperature and for gels at elevated temperatures that do not depend on pure components that are otherwise difficult to obtain in the same, native form in which they are present in the mildly refined fractions. The method for the doughs combines fundamental principles of sorption isotherms with mass balances. Modelling is used to calculate the contribution of each pure component, which is then transferred into a sorption isotherm for the pure component at high water activity (−1 (db.) while ensuring that protein content is high enough to allow the detection of its denaturation.Faba bean Meal (FM) is taken as an exemplary material. FM can be dry fractionated, delivering protein and starch enriched fractions with native properties. This ensures that neither protein nor starch are denatured or otherwise influenced by the fractionation method, therefore retaining their native functionality. Furthermore, FM contains enough starch to allow a starch content range in mixed doughs of 0.09–0.66 g g23h−1. The composition of the protein-rich fine fraction (Protein Fraction - PF) and the starch-rich coarse fraction (Starch Fraction - SF) is shown in Faba bean Meal HOMECRAFT®Pulse 3101 (FM) was supplied by Ingredion . FM had a protein content of 29% (N-conversion factor = 6.25). FM was air classified using a Hosokawa Multi Mill . The classifier wheel speed was set to 7000 rpm and the air flow to 70 m−1 as w/w % on d.b., unless specified otherwise. Mixtures were combined with distilled water to create doughs with different moisture content (36–66% wet basis), for which the moisture content of the powders was taken into account. Moisture content or dry matter content are expressed in g g−1 on wet basis, unless specified otherwise. Doughs were stored in vacuum-sealed bags at 4 °C for 48 h to allow water distribution to reach equilibrium.PF and SF were mixed at different ratios to vary starch content (9–70% d.b.). Starch content will be expressed in g g2.1aw) of the doughs was measured using an Aqualab TDL water activity meter . Approximately 3 g of sample were used for each measurement. The measuring temperature was set to 25 °C with a deviation of 0.05 °C, ensuring constant measuring conditions.Water activity , unless specified otherwise.Moisture content (mc) of all doughs was determined by oven drying. Dough samples were dried in aluminum cups at 105 °C for 24 h. Moisture content was calculated according to Equation 2.3−1 to 160 °C. After cooling, the cycle was repeated. TRIOS software was used to analyze the obtained thermograms and to identify the peak temperatures of the protein denaturation and the enthalpy change of the initial peak of starch pasting (G peak). ΔH was obtained by adjusting for the amount of starch present in the sample usingH is the enthalpy change per overall sample mass in J g−1, mc is the overall moisture content in g g−1 (wb.) and sc is the starch content in g g−1 (db.).Differential Scanning Calorimetry (DSC) was used to determine the denaturation temperature of the proteins and the degree of starch pasting. Dough samples were degassed in an ultrasonic water bath for 15 min 60 mg was transferred to High Volume Pans . The pans were placed in the DSC  where they were first equilibrated at 20 °C until the temperature was constant. Samples were then heated with a ramp of 5 °C min2.4mc is the overall moisture content of the sample in g g−1 (wb.), aw is the water activity, sc is the starch content in g g−1 (db.) and a, b, c and d are model parameters. For the model of the gel, the same method was used with the model Equations Td is the denaturation temperature of legumin in °C, mc is the overall moisture content of the sample in g g−1 (wb.), sc is the starch content in g g−1 (db.) and e, f, g and h are model parameters. The residuals of each fit were checked for correlation in R. The summary tables of each model can be found in the Supplementary information. The best fit was chosen based on the value of All measurements are shown as individual data points in the graphs. Multiple Linear Regression was used to fit the data in R (Version 3.6.1). For the dough, the model Equations 3aw of the dough. At moisture contents higher than 40%, the water activity of the product is between 0.9 and 1 and their relation can be approximated well by a straight line. The shape of the sorption isotherm of starch and protein only deviates from a linear relation at aw < 0.95 (e.g. gelation). To determine the distribution of moisture at higher temperatures, a method based on the denaturation temperature of the protein is proposed. As the denaturation temperature of protein depends on the moisture content of the protein phase, the first can be used to determine the latter if the relation is known. We model the relation by extrapolating the measured denaturation temperature of protein of the mixed gels to a protein phase containing no starch, yielding the moisture content of the protein phase in the mixed, heat-induced gel.Starting point of the method to determine the distribution of moisture among phases of a starch-protein blend at room temperature  presented in this paper is the fact that the water activity of such a blend is determined by both the overall moisture content and the composition of the dough  Fig. 1)Fig. 1). w < 0.95 . This siG peak)   as a measure of the moisture content of starch in the dough.Next to the denaturation temperature of protein, the gelatinization of starch can also be monitored. If sufficient water is available, starch granules fully gelatinize at the initial gelatinization temperature , resultiG peak)  in a DSCng peak) . The pos present . Accordi44.1In this study, protein-rich fractions (PF) and starch-rich fractions (SF) were mixed to obtain doughs that vary in protein and starch content. Besides, water addition was used to change the water contents. Since PF and SF used in this study were obtained via dry fractionation, it is assumed that starch granules will remain intact . This prmc) and water activity (aw) of 155 dough samples with different starch and protein contents and added amounts of water were measured  and the dry based starch content (sc) of the samples can be expressed as sc + pc = 1. This means that protein content was not varied independently of starch content and is therefore not used as an independent variable. Equation mc is the overall moisture content of the sample in g g−1 (wb.), aw is the water activity, and sc is the starch content in g g−1 (db.). This optimized fit resulted in The potential influence of the starch content on the correlation between the moisture content and the water activity can be incorporated in a model via Equations ormation . Fittingmcp(dough), Equation mcs(dough), Equation mci(dough) is the moisture content of the protein or starch phase in the dough in g g−1 (wb.) and aw is the water activity (−) of the sample. These equations are given as lines in aw, according to literature: In a study on several raw legume flours , sorption isotherms were measured, for all of which this deviation only occurred at aw < 0.8 and mc < 0.13 g g−1 (wb.) (aw > 0.9 and mc > 0.15 g g−1 (wb.) at 30 °C  . For corat 30 °C . All sam−1), an increase of the starch content from 0.09 to 0.7 g g−1 (d.b.) leads to an increase in moisture content of the protein phase of 0.11 g g−1 (22%). The same increase in starch content at higher overall moisture content (0.61) only causes an increase of 0.07 g g−1 (9%). As the overall moisture content increases and the aw approaches 1, the sample approaches a regime of excess water, where a change in starch content will not have an influence on the moisture content in protein, as both the moisture content in starch and protein will be equal to the overall moisture content.In 4.24.2.1H) associated with the reaction. mcs(dough) (red), one with an intermediate mcs(dough) (green) and one with a high mcs(dough) (blue). There are three peaks visible in all three thermograms. The first peak is the initial gelatinization of starch, also called the G peak (M1), especially at low moisture content, which represents the melting of the starch. This peak was not identified in this research.The starch gelatinization as well as the protein denaturation were analyzed using DSC. From the thermograms of the DSC  we can ge G peak , which oe G peak . For mose G peak . The sece G peak . DSC mea4.2.2G peak (the excess water gelatinization peak) occurred at 73.4 °C (±2.4 °C) (data not shown). The peak temperature did not correlate with the overall moisture content or the moisture content of starch in the dough (Equation yw) ) on the gelatinization temperature for yw > 0.3 g g−1. They do, however, show a linear relation of the melting temperature of starch to the mass fraction of water, which describes the peak temperature of the M1 peak. In this paper, the M1 peak could not be identified, as its position (T) and size (ΔH) depend on the moisture content and it can overlap with the denaturation peak of vicilin and potentially also legumin. The possible effects of this on the interpretation of the denaturation temperature of legumin (Td) are discussed towards the end of Section For the samples analyzed, the Equation   are underestimated by the linear regression, while the low starch content samples are mostly overestimated . Therefore, in H is shown over mcs(dough), which is derived from Equation HStarch and mcs(dough) yields an mcs(dough) starch always fully gelatinizes during the initial gelatinization and therefore ΔH becomes constant (mcs(dough) investigated here, as (H of 13.4 ± 0.6 J g−1 and 13.4 ± 2.0 J g−1 for wheat starch at a moisture content of 0.91 g g−1 and 0.9 g g−1 respectively. The extrapolation of the current data set to mcs(dough) = 0.9 g g−1 yields a ΔH of 14.68 J g−1, indicating the validity of our data and the linear correlation of mcs(dough) and ΔH. For samples with low moisture content of starch in the dough, the starch does not fully gelatinize at the temperature of the G peak but undergoes further transition at higher temperatures. The degree to which starch gelatinizes at this temperature depends on the initial water content of the starch (mcs(dough). At mcs(dough) below 0.3 g g−1, no gelatinization occurred at the initial gelatinization temperature.In constant . This mohere, as  and  seems to be comparable for vicilin and legumin in the studied range  against the overall moisture content of the sample. By changing the starch content, the denaturation temperature of legumin decreased by maximally 5.12 °C, when using blends with an overall moisture content of 0.47 g g−1.Td can be incorporated in a model via Equations Td is the denaturation temperature of legumin in °C, mc is the overall moisture content of the sample in g g−1 (wb.) and sc is the starch content in g g−1 (db.), resulting in an The potential influence of the starch content on the correlation between the moisture content and ormation . Fittingmcp(dough), setting sc to 0 after solving for mc yields the moisture content of the protein phase in the gel (mcp(gel)):mcp(gel) is the moisture content of the protein phase in the gel in g g−1 (wb.) and Td is the denaturation temperature of legumin in °C. This relation is shown in Td with increasing moisture content until 0.6 g g−1 and a constant Td above 0.6 g g−1. Here we found a similar dependency of the denaturation temperature on moisture content in the protein phase as reported by Td of mildly refined faba bean fractions also does not decrease for moisture contents above the maximum moisture content used in this study.Similarly to the approach used to determine the −1 the trend becomes less evident. This either means that the influence of starch on the moisture content of protein at denaturation is limited at high moisture contents (as is the case at room temperature), or that the influence of moisture content in protein on denaturation temperature becomes smaller at overall moisture contents >0.6 g g−1. The latter was also found to be true by −1 (db.), which is equal to 0.6 g g−1 (wb.).In M1 peak) was not identified in this research. It potentially overlaps with the Td peak and interferes with the analysis. M1 peak is rather broad and not a sharp peak like the G peak or the peaks for protein denaturation observed in this study. Such overlap is most likely at the lowest overall moisture content and starch content, as these conditions lead to the lowest values of mcs(dough)), which in turn lead to a high M1 temperature. However, this also decreases the overall enthalpy of the starch gelatinization (since there is less starch in the sample), thereby decreasing the influence of the M1 peak on the analysis of the denaturation peak of legumin and likely making this overlap less relevant. There is, however, the possibility of relevant overlap of the legumin peak and the M1 peak at low moisture contents (0.47 g g−1) and intermediate starch contents (purple points), as these conditions lead to a relatively low mcs(dough), causing the M1 peak to increase in height and appear at higher temperatures, and also lead to a smaller peak for the denaturation of legumin, as there is less protein present as the starch content increases. This could be the cause for the deviation of these samples from the rest of the data, observed in It is important to note that the starch melting peak (tents 0.4 g g−1 an4.3G peak), the redistribution of water must occur later, at higher temperatures. We suggest that this occurs during starch melting, which takes place at those higher temperatures. This is represented by the M1 peak that most likely overlaps with the denaturation peaks of vicilin and legumin and can therefore not be detected. Melting of starch modifies the affinity of starch for water, creating a force “pulling” the water to the starch phase. Simultaneously, denaturation of protein exposes hydrophobic sites, creating a force “pushing” the water to the starch phase.The comparison of the moisture content in the protein phase in the ingredients studied at room temperature  with the5−1 and 0.28 g g−1 more water than starch. The amount of water associated with the protein phase in the gel is up to 0.12 g g−1 less than in the dough, showing the amount of water that migrated from the protein phase to the starch phase upon heating. The enthalpy change of the initial starch gelatinization correlates reasonably well with the calculated moisture content of the starch phase in the dough. Therefore, no or limited redistribution of moisture occurs between the starch and protein phase during the initial starch gelatinization, but at higher temperatures, during the melting of starch crystals.The distribution of water between the starch and protein phase in doughs and gels of mixed mildly-refined fractions of faba bean flour was determined in a moisture content range relevant for soft-solid foods such as plant-based meat and cheese alternatives. Quantification of the moisture content distribution was achieved by applying models based on established concepts such as sorption isotherms, mass balances and the moisture dependence of starch gelatinization and protein denaturation. The model based on sorption isotherms was used to determine the water distribution in a dough at room temperature, while the model based on the moisture dependence of protein denaturation determines the water distribution at elevated temperatures when protein denatures and gelatinizes. In the dough, protein takes up between 0.12 g gThis paper shows that it is possible to derive properties of components present in a flour or enriched fraction without having the components as pure ingredients. Such an approach will become more important when focusing on the use of enriched fractions rather than pure ingredients in future food applications. These findings have implications for the further development and design of production processes for aforementioned plant-based meat and cheese alternatives. The methods presented here can be used to predict and control ingredient properties that determine process parameters such as processing temperature. Furthermore, they underline the limitations of using overall moisture content without understanding water uptake and distribution in the individual components, all of which becomes even more important when using less refined ingredients.Jan M. Bühler: Conceptualization, Data curation, Formal analysis, Methodology, Writing – original draft, Writing – review & editing. Atze Jan van der Goot: Conceptualization, Supervision, Writing – review & editing. Marieke E. Bruins: Conceptualization, Supervision, Writing – review & editing.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.


Occasional chipping can still occur with zirconia material despite its high strength. Emergency repairs can be accomplished using zirconia primer, adhesive agent, and resin composite when the fracture of zirconia exposes the zirconia framework. Phosphate-containing primers play an important role in zirconia surface treatment. The objective of this investigation was to evaluate the effect of multiple applications of phosphate-containing primer on shear bond strength between zirconia and resin composite. In this case, 78 zirconia discs were sandblasted by alumina particles; the zirconia was then randomized into six groups for single application and multiple applications of phosphate-containing primer according follows; group 1: no application, group 2: one application, group 3: two applications, group 4: three applications, group 5: four applications, and group 6: five applications. Adhesive was applied on the zirconia surface and the resin composite was bonded. Shear bond strength was assessed using a universal testing machine. The de-bonded surface was examined using a stereomicroscope. The shear bond strengths were statistically analyzed with one-way ANOVA and Bonferroni. Group 1 had the lowest shear bond strength with a significant difference compared to groups 2–6, whereas group 4 had the highest shear bond strength, with no significant difference compared to groups 5–6. The failure mode revealed 100% adhesive failure in all groups. In conclusion, to maximize shear bond strength at zirconia and resin composite interfaces, sandblasted zirconia surfaces should be treated with three applications of phosphate-containing primer prior to the adhesive agent. When stress is applied, tetragonal is transformed into monoclinic. Transformation toughening from tetragonal to monoclinic provides an increase in zirconia’s volume, preventing the fracture from propagating and improving its mechanical characteristics. Three mol% yttria was used in the first-generation zirconia. It has great strength but also high opacity due to the birefringence of the noncubic phase. However, the esthetics of second-generation zirconia were still inadequate. The third generation has a greater yttria contents, for example 4 or 5 mol%, resulting in increased non-birefringence of the cubic phase. Although the translucency has improved, zirconia undergoes less stress transformation resulting in a decreased strength and toughness [Zirconia is a polycrystalline solid with high strength. The three major phases are temperature-dependent: monoclinic at ambient temperature, tetragonal at roughly 1170 °C, and cubic at approximately 2370 °C, where zirconia displays phase transformation toughening characteristics, changing phase as temperature varies. At room temperature, yttria oxide  chemical bond: apply primer, silanes or universal adhesive, etc., and (iii) mechanicochemical bond: tribochemical silica coating [Despite zirconia being a tough material, there have been occasional functional fractures, with chipping in about 6.25% of cases . In some coating .Zirconia primer is a soluble monomer in a solvent. A monomer is composed of three components: (i) a polymerizable functional group (PG) that can react during polymerization, (ii) an adhesion promoting group (AG) that can bind to the adherend and can consist of a sulfur atom, carboxylate or phosphate group, and (iii) a connecting group, acting as a link between PG and AG, where carboxylate or phosphate-containing monomers can be bonded to dental hard tissue, and non-precious metal alloy . PreviouIn some circumstances, chairside zirconia defection repair is possible. The most common procedure for achieving high zirconia bond strength was the use of sandblasting to obtain a mechanical bond, followed by the use of a zirconia primer and bonding agent . Mahgoli3. The manufacturer’s instructions were followed for sintering the zirconia specimens. Zirconia samples were positioned 1 mm above a PVC tube that contained type IV gypsum. The sample was polished using silicon carbide paper with a 600-grit  on an automated polishing device  at 2 kg/cm2 force, 100 rounds/min, under running water for 120 s.A pre-sintered zirconia disc  was sectioned into 78 rectangular specimens, each measuring 6 × 4 × 3mm2O3) with 50 μm particles for 10 s at 0.2 megapascals (MPa) pressure perpendicular to the zirconia surface . Running water was used to rinse off sandblasted debris on the specimens. A 20-min ultrasonic cleaning procedure was performed on the samples in distilled water. .A zirconia specimen was subjected to sandblasting using aluminum oxide (AlA phosphate-containing primer (Clearfil ceramic primer plus (CPP), Kuraray Noritake, Tokyo, Japan) was used , and theGroup 1: no primer (control group)Group 2: one application of primerGroup 3: two applications of primerGroup 4: three applications of primerGroup 5: four applications of primerGroup 6: five applications of primerOne-sided tape  with a thickness of roughly 80 μm was cut to a width and length of 10 mm, and a 2 mm-diameter hole was then punched. To make it simple to remove, a circular hole was reached by cutting the side of the tape. After one-sided tape was attached to the zirconia surface, primer was applied onto the zirconia surface with disposable micro brush , then the excess primer built up around the border of the tape loop was blotted off using a new micro brush. After 1 min, air was blown from a triple syringe, that was free from water and oil mist, from a mobile dental unit  with a pressure of 40–50 pounds per square inch at a distance of approximately 10 mm from the zirconia surface, until an absence of movement of the primer was observed and it was totally dry. The process was repeated until the number of primers in each group had been applied.The zirconia surface was coated with adhesive agent  using a disposable micro brush . The extA template  with a height of 2 mm and a diameter of 2 mm was fitted to the zirconia surface by aligning the hole of the template to the hole of the one-sided tape; the resin composite  was then pushed into the template until full . The temA universal testing device  was used to evaluate the shear bond strength of the specimens. The shearing blade was positioned parallel to the intersection of the zirconia and resin composite. A shear pressure of 0.5 mm per min was set until fracture occurred . The sheThe fractured surface of the specimen was examined using a stereomicroscope at a magnification of 15×  to determine the mode of failure, which is divided into 3 types. (1) Adhesive failure happens, when zirconia and resin composite fail to adhere to one another. This occurs when the zirconia surface has no resin composite remnants. (2) Cohesive failure happens, when the failure occurs within the resin composite. This occurs when the entire surface of the zirconia is coated with resin composite.(3) Mixed failure happens, when adhesive and cohesive failures occur together. This happens when a remnant of resin composite remains adhered to the zirconia surface.IBM SPSS Statistics 25.0  was used to determine the quantitative data from 6 independent groups with a confidence level of 95%. The Kolmogorov-Smirnov test was used to determine normality, whereas the normal distribution was tested with one-way ANOVA and Post-hoc with Bonferroni.In this study, no specimens were de-bonded before shear bond strength was tested (prematurely failed specimen) in all the groups.p < 0.05). Group 4 had the highest shear bond strength, with no significant difference compared to group 5 and group 6 (p > 0.05).In The failure mode was as indicated in The aim of this investigation was to evaluate the effect of multiple applications of phosphate-containing primer on the shear bond strength of zirconia and resin composite. It was observed that three applications established the highest shear bond strength, which was significantly different from one application and two applications. However, applying more than three applications showed no statistically significantly difference in shear bond strength compared to three applications. Therefore, the null hypothesis was rejected.Currently, zirconia surface treatment before repairing restoration can be performed using several methods. The most common method of gaining the best retention is to obtain both mechanical and chemical retention. Sandblasting is the most common surface treatment for obtaining mechanical retention of zirconia . ChemicaThe main zirconia bonding monomer in use has been 10-MDP as it promotes bonding with both resin composite and zirconia . This isBased on the results, it was found that one application and two applications of phosphate-containing primer prior to the adhesive agent performed better than adhesive alone. This could be because 10-MDP, a phosphate monomer, was chemically bonded to the outermost surface of zirconia . A phospThe de-bonded surface was examined under a stereomicroscope after shear bond strength inspection. All groups were determined to have had adhesive failure as their mode of failure. Therefore, the shear bond strength achieved in this investigation, with all adhesive failures, was the true strength of the zirconia and resin composite interface and was considered to be a true indication of bond strength between these materials ,28.This study has limitations. The incubated specimen could only interpret the shear bond strength of zirconia and resin composite 24 h after bonding. Thermocycling could be performed to evaluate the durability of bonding between zirconia and resin composite to assess long-term adhesion in a future investigation.To maximize shear bond strength at zirconia and resin composite interfaces, sandblasted zirconia surfaces should be treated with three applications of phosphate-containing primer prior to the adhesive agent.