Group A (control) was not exposed to contaminants. The following tests specimens were contaminated with saliva and silicone indicating paste. Group B was coated with ceramic primer, then subjected to contamination. Groups C, D, E, F, G, and H were contaminated; cleaned with water rinse, Ivoclean, air particle abrasion, hydrofluoric acid, KATANATM Cleaner and ZirCleanTM, respectively, and then coated with ceramic primer and bonded to dual cure resin cement cylinders. All the specimens were subjected to artificial aging and surviving specimens were subjected to the SBS test. For statistical analysis, ANOVA and multiple comparison methods at the 0.05 significance level were used. There was no statistically significant difference among Ivoclean (21.48 ± 2.90 MPa), air particle abrasion (21.92 ± 2.85 MPa), and the control group (24.68 ± 5.46). The application of ceramic primer before contamination did not preserve the SBS of resin cement to zirconia. Cleaning the contaminated zirconia surface with hydrofluoric acid (15.03 ± 3.63) or KATANATM Cleaner (17.27 ± 7.63) did not restore SBS to the uncontaminated state, but it was significantly higher than simply rinsing with water (12.46 ± 5.17) or the use of ZirCleanTM (11.59 ± 5.53). The bond strength of resin cement to zirconia was influenced by cleaning methods.The aim of this study was to evaluate the effect of different cleaning methods on the shear bond strength (SBS) of resin cement to contaminated zirconia specimens. Eighty rectangular-shaped specimens (2 × 5 × 10 mm) were fabricated from Zirconia blocks (IPS e.max ZirCAD) and randomly divided into 8 groups ( There has been a significant increase in the use of zirconia-based restorations due to their high mechanical properties, excellent biocompatibility, ease of fabrication, and acceptable esthetics ,2. The lIn addition, exposure to contaminants  during the clinical try-in of indirect restorations is inevitable. Contamination negatively affects the quality of the bond strength between the resin cement and the zirconia surface ,8,9. Rin2O3) is used to clean contaminated surfaces and increase surface energy, which effectively restores the original bond strength [Cleaning the contaminated surface with simple water rinse showed ineffective results in restoring the bond strength . Severalstrength ,14,15. Wstrength .TM , or [TM Cleaner . Ivoclean is a highly alkaline (pH = 13) solution applied extraorally on zirconia surfaces for cleaning before cementation. This is a ceramic cleaner that has been shown to effectively clean contaminated surfaces [TM is also an alkaline cleaning gel composed of potassium hydroxide, which breaks the ionic bond formed between the zirconia surface and the organic material from saliva [TM Cleaner is a mild acidic (pH = 4.5) cleaner containing 10-methacryloyloxdecal dihydrogen phosphate (10-MDP) salt and can be used for intraoral or extraoral applications. 10-MDP has a hydrophobic group that bonds to contaminants and a hydrophilic group that makes it easily removed by water rinse [Chemical cleaning methods for contaminated zirconia have also been reported. They are safely applied without an adverse effect on the mechanical properties of zirconia. Phosphoric acid has been effective in removing organic contaminants, but X-ray photoelectron spectroscopy proves that the presence of phosphorous residue which might influence the bonding negatively . HydroflUSA), or  KATANATMsurfaces ,20. Thisine pH =  solutionsurfaces . ZirCleaine pH =  solutionine pH =  solutioner rinse . Despiteer rinse .Before bonding, it is recommended to apply a chemical promotor as a ceramic primer that contains 10-MDP on the zirconia surface to enhance the bonding to resin cements . 10-MDP TM Cleaner and ZirCleanTM, have been tested in dry conditions [TM Cleaner and ZirCleanTM) with conventional techniques . In addition, to test the impact of applying 10-MDP ceramic primer prior to contamination, as recommended by Angkasith et al. [Recently introduced cleaning materials, such as KATANAnditions ,25, and nditions ,26. Consh et al.  The firs2O3) powder at 2.0 bar and at a 10 mm distance for 20 s. . Later, they were ultrasonically cleaned in distilled water for 5 min, then dried with a stream of air.Pre-sintered zirconia blocks  were sectioned into eighty 2 × 5 × 10 mm specimens using a low-speed diamond saw  under water coolant. All specimens were polished with multiple silicon carbide papers  at 300 rpm for 20 s each. Then, specimens were sintered in a Vita ZYrcomat T furnace  according to the manufacturer’s instructions. Specimens were embedded in chemically polymerized acrylic resin  for handling purposes during the shear bond strength test. The bonding surfaces of the specimens were inspected for any acrylic flashes and polished using 1200 grit carbide paper to remove all residues. Specimens were subjected to air particle abrasion with 50 µm Aluminum oxide (Aln = 10) according to the cleaning methods. In the control group (group A), 10-MDP ceramic primer  was applied using a micro-brush with agitation for 10 s and left for 60 s and then excess primer was dispersed using a dry-air stream for 5 s. For contamination, saliva was collected from a healthy male individual who refrained from eating, drinking, and brushing for 2 h before the collection process . In group B, specimens were coated with 10-MDP ceramic primer before exposure to contaminants, followed by contamination with human saliva, which was applied to zirconia surface and spread with a micro-brush for 2 min before rinsing with water and drying. Then, inorganic contamination was carried out by applying a layer of silicone indicating paste  under 1 kg load and it was removed from the surface once it set (3 min). In groups C, D, E, F, G, and H, zirconia specimens were contaminated with saliva and silicone indicating paste, as mentioned above. Cleaning protocols were performed as described in the following. In Group C, specimens were only rinsed with water for 15 s and dried. In Group D, Ivoclean was applied using a micro-brush and left to react for 20 s and then rinsed with water thoroughly and dried. In Group E, specimens were subjected to additional air particle abrasion with 50 µm Aluminum oxide (Al2O3) powder at 2.0 bar and at a 10 mm distance for 20 s, then rinsed with water and dried. In Group F, specimens were treated with 9.6% hydrofluoric acid for 30 s and then rinsed with water and dried. In Group G, KATANATM Cleaner was applied to the specimens and rubbed using a micro-brush for 10 s, then rinsed with water and dried. In group H, a thin layer of ZirCleanTM was applied using a delivery tip, left for 20 s, and then rinsed with water and dried. A split Teflon mold was placed on the zirconia surface to produce a cylinder with the following dimensions: 4.25 mm diameter and 4 mm height. All specimens were dried with a dry-air stream then coated with 10-MDP ceramic primer as described earlier . Self-adhesive resin cement  was injected into the mold and light cured for 40 s using an E-Morlit curing light  delivering a power of 1200 mW/cm2. The mold was disassembled carefully after light curing and any cement flashes were carefully removed using a sharp scalpel. Then, specimens were subjected to 5000 thermal cycles of artificial ageing at a temperature between 5 and 55 °C, which represents a 6-month intraoral simulation . Each cycle took about 1 min to complete. After that, specimens were randomly divided into 8 groups (Shear bond strength (SBS) was measured using the universal testing machine . The load was applied to the interface of the zirconia-resin cement at a crosshead speed of 1 mm/min until failure .p-value of < 0.05. Two-tailed tests were assumed throughout the analysis for all statistical tests.All the data were subjected to statistical analysis. Statistical analysis was performed using Statistical Package for the Social Sciences SPSS (version 20), while Microsoft Office Excel 2010 was used for data handling and graphical presentation. One-way analysis of variance (ANOVA) was used to compare the mean shear bond strength of different groups. The post hoc tests used Bonferroni method for comparison between tests groups. To compare each group with the control group, Dunnett’s test was used. The result was considered significant at a Out of 80 specimens, 64 survived thermocycling. Three groups did not have any specimens that failed after thermocycling: control (A), Ivoclean (D), and air abrasion (E) groups. On the other hand, all the B group specimens, which were treated by applying primer only before contamination, failed during thermocycling.TM Cleaner group G (17.27 ± 7.63), and ZirCleanTM group H (11.59 ± 5.53). The mean shear bond strength values in MPa and standard deviation were as follows: the control group A (24.68 ± 5.46), water rinsing group C (12.46 ± 5.17), Ivoclean group D (21.53 ± 2.74), air particle abrasion group E (21.92 ± 2.85), hydrofluoric acid group F (15.03 ± 3.63), KATANAp < 0.001), as presented in The Shapiro–Wilk test was used to test the normality hypothesis of all the quantitative variables for a further choice of appropriate parametric and non-parametric tests. All the variables were found to be normally distributed, allowing the use of parametric tests. Levene’s test of homogeneity of variance was also applied. A one-way ANOVA showed highly statistically significant differences between the groups (The first null hypothesis that there is no significant difference in the shear bond strength of resin cement to contaminated zirconia after using different cleaning methods was rejected. The application of 10-MDP ceramic primer before contamination (group B) did not preserve the SBS and all the specimens failed during thermocycling, so the second null hypothesis was also rejected.TM groups, but they were statistically similar to hydrofluoric acid and KATANATM Cleaner groups. ZircleanTM group was the weakest among all groups and it was statistically similar to water rinsing. To compare each test group with the control group, Dunnett’s test showed that the SBS of control group was statistically similar to that of the Ivoclean and air particle abrasion groups, but significantly higher than that of the rest of the groups .Multiple comparisons between test groups were performed with the Bonferroni post hoc test. The result showed that the mean SBS of Ivoclean and air particle abrasion groups were significantly higher than water rinsing and ZirCleanTM Cleaner, and ZirCleanTM. Exposure to contaminants significantly influence the bond strength (p < 0.05). Only Ivoclean and air particle abrasion were able to restore the shear bond strength of resin cement to zirconia to the uncontaminated (control) state. The first null hypothesis that there is no significant difference in the shear bond strength of resin cement to contaminated zirconia after using different cleaning methods was rejected (p < 0.001). We also tested the hypothesis that the application of 10-MDP ceramic primer prior to contamination will preserve the bond strength, this hypothesis was also rejected, as none of the specimens survived after artificial ageing.The durability of the bonding of zirconia restorations is important for long-term success . In the The application of ceramic primer containing 10-MDP on the cleaned zirconia surface is recommended for increasing bond strength . The phoTM Cleaner is an acidic material (pH = 4.5) containing 10-MDP salts that act as a surfactant to remove hydrophobic contaminants [TM is a ceramic cleaner solution containing potassium hydroxide with high alkalinity (pH > 13), which neutralizes acids in organic contaminants and cleans them [TM Cleaner was more effective in restoring the SBS (17.27 MPa), while ZirCleanTM showed the lowest performance amongst all groups (11.59 MPa). There are limited studies available in the literature about the effectiveness of KATANATM Cleaner or ZirCleanTM as cleaning methods [TM and KATANATM Cleaner and found no significant difference in SBS [TM Cleaner and ZirCleanTM. In our study, we used thermocycling to perform artificial ageing for 5000 cycles, which was not used in the aforementioned study, which might explains the different results [TM Cleaner groups with two different resin cements. Awad et al. [TM cleaners are effective methods for the decontamination of a zirconia surface exposed to saliva and blood. In our study, we found a statistically significant difference between Ivoclean and KATANATM cleaners after thermocycling. Among the reasons for this difference is the use of different ceramic primers and resin cements in all the studies. In a meta-analysis [Angkasith et al.  recommenaminants . ZirCleaans them . In the ity pH > , which n methods ,25,26. Aity pH > , which nity pH > , which nd et al.  and Tianl groups .59 MPa. ity pH > , which nl groups .59 MPa. ity pH > , which nanalysis .One of the limitations of our study was using a shear bond test instead of a microtensile bond test, which has more uniform stress distribution at the bonding interface. However, the shear bond test is commonly used for the assessment of ceramic bond strength and provides an acceptable ranking of the test groups. Another limitation is that specimens were not analyzed under a microscope to study the original, contaminated, and treated zirconia surfaces, or to categorize the failure mode.TM Cleaner or hydrofluoric acid did not restore SBS to the uncontaminated state, but it was significantly higher than simply rinsing with water or the use of ZirCleanTM. Artificial ageing with thermocycling is important to stress the bond strength and validate the bond strength between zirconia and resin cement.From this in vitro study, the following conclusions were drawn. The contamination of zirconia restoration with saliva and silicone indicating paste significantly reduced the shear bond strength of resin cement to zirconia. Ivoclean and air particle abrasion were able to restore the SBS of resin cement to zirconia, similar to the uncontaminated control group. The application of ceramic primer to the zirconia surface before contamination did not preserve the SBS of resin cement to zirconia. Cleaning the contaminated zirconia surface with KATANA


Buckwheat hulls which are rich in fiber are good ingredients to increase the nutritional value of food products. The aim of this study was to determine the effect of the applied additives in the form of fiber and apple juice on the properties of both potato and corn starch . In order to characterize the rheological properties of kissel, the pasting characteristic was measured. In the obtained gels, the basic quality parameters were determined. The analysis of texture, color parameters, and also total polyphenol content were determined. Buckwheat hulls, in addition to their high fiber content, are a valuable source of phenolic compounds and can be a great additive in starch desserts. The addition of buckwheat hulls and apple juice improved the nutritional value of the final products but also caused changes in the technological qualities: it increased the initial temperature of potato starch mixtures (by approx. 9 °C); it decreased the viscosity of cold desserts (from 8 to 55%); and increased the hardness of the final product by more than 7 times. In the case of other starches, the recorded changes were much smaller than for potato starch-based products. Starch is a reserve material of many plants, and from a chemical point of view, it is a semi-crystalline polysaccharide composed exclusively of D-glucose monomers connected by α-glycosidic bonds. Starch granules contain two fractions of polysaccharide chains: unbranched amylose (AM) and branched amylopectin (AMP). AM is composed of relatively long, linear anhydroglucose chains connected in about 99% by α-1,4)-glycosidic bonds and in a maximum of 1% by branching α-1,6)-glycosidic bonds. In turn, the branched structure of AMP results from a much larger amount of α--glycosidic bonds, which is estimated at approximately 5% ,4-glycos. The exc-glycosidDesserts are a wide assortment of sweet food products which include jellies, kissels, puddings, creams, mousses, and ice creams, as well as confectionery products. These foods can be served both cold and hot . Kissel A specific form of raw material that is used is raw by-products, which in the aspect of one industry is a production residue, but in another is a valuable source to be reused in an efficient manner. By-products rich in fiber are important as health-promoting components. Buckwheat hulls are a good ingredient to increase the nutritional value of food products. They have more bioactive compounds than buckwheat flour. Buckwheat hulls were used as an additive in products as a component to noodles or yogurt ,34.The effect of the addition of buckwheat hulls on the rheological properties of gels based on normal and waxy potato starch was studied in our previous work . In thosThe experimental material consisted of: normal potato starch (PS) , waxy potato starch (WPS) , normal corn starch (CS) , waxy corn starch (WCS) , organic buckwheat fiber (BH) , and concentrated apple juice (CAJ) . The apple juice (AJ) was prepared by diluting the concentrate with water in a ratio of 1:1. Buckwheat fiber (BH) contains 100% of the ground roasted buckwheat hulls from controlled organic farming and has the following parameters: 4.5% protein, 3.1% carbohydrates, and 0.6% fat.Dry matter: Determination of the dry matter content in the preparation of starch and buckwheat fiber was carried out in a dryer . This method consists of the evaporation of water from the product sample in the process of drying at 130 °C for 60 min and determining the residual dry matter by weight.Fiber content: According to AOAC (2006) , the fibBrix value: Apple juice solution added to the examined samples (apple juice diluted with water 1:1) was established using a PAL-1 refractometer  with a Brix scale (%). The results were averaged, and the standard deviation was calculated.pH: The pH of the prepared apple juice solution was measured using a Crison Instruments S.A. pH-meter .Fruit gels (kissel) were produced under laboratory conditions. The ingredients used in the production of kissel are listed in ® GmbH & Co. KG, Duisburg, Germany) with the procedure according to Adamczyk et al. (2020)  was determined as one of the texture parameters .Quantitative color measurements were conducted using an UltraScan VIS spectrophotometer  according to the CIE Lab model using diffuse/8° geometry with automatic mirroring on and off. The bandwidth in the optical system was 10 nm and the range was from 360 nm to 780 nm. The spectrophotometer recorded L*, a*, and b* coordinates defined as: lightness where 100 is white and 0 is black (L*), redness+/greenness− (a*), and yellowness+/blueness− (b*). Measurements were made in triplicate. The mean values of the measurements were calculated taking into account the standard deviations .The methanol extract was prepared for analysis of the total polyphenol content and antioxidant properties. Fresh kissel samples (10 g) were treated with a 70% methanol solution (20 mL). The extraction process was carried out using an ultrasonic bath  (30 min at 25 °C). After this process, the samples were centrifuged for 10 min at 7000 rpm. The obtained supernatant (methanol extract) was used for further analysis.w/v) sodium carbonate solution (1.0 mL). The absorbance of the samples was measured at 765 nm against distilled water using a spectrophotometer . Measurements were performed in triplicate. The total polyphenol content was expressed as gallic acid equivalents (GAE) in milligrams per 100 g of kissel .The total polyphenol content in kissel was assessed using the Folin–Ciocalteu phenol reagent with the method described by Singleton and Rossi (1999) . The rea+ cation radical. The reaction mixture consisted of adding the sample (0.03 mL) and the ABTS radical solution to the water (3.0 mL). The absorbance at 734 nm, against distilled water, was measured after 6 min of reaction using a spectrophotometer . Measurements were performed in triplicate.According to Re et al. (1999) , the antThe scavenging activity was measured according to the elimination of DPPH  free radicals . The reaStatistical analysis of the results was performed using Statistica v.13.3 . For all determinations, one-way ANOVA was carried out using Duncan’s test at a confidence level of α = 0.05.The dry matter content of analyzed starches were in range 82.32–89.22% and buckwheat fiber was at the level of 89.40%. The prepared apple juice (AJ) used in formulation showed the following parameters: pH 3.45 and 36.10% Brix. The buckwheat hulls had 71.40 g/100 g total dietary fiber (TDF) and included insoluble dietary fiber (IDF) 62.06% and soluble dietary fiber (SDF) 11.55%.Pasting property parameters of potato and corn starches and the designed desserts were summarized in 0) for PS (61.2 °C) had smaller value in comparison to juice systems present  (0 parameter was a higher temperature (70.1 °C) than in the starch without additives (61.2 °C). Regardless of whether buckwheat fiber was present in the system with normal potato starch with juice or not, its effect on this parameter was not observed. A similar dependence of the T0 parameter was noted in the samples with WPS. Consequently, the presence of apple juice increased the temperature of the beginning of pasting from 67.6 °C (WPS) to 70.0–70.1 °C.The beginning of pasting (T+ 20%AJ) . This memax) (1957.0 BU) in comparison with waxy starch (1387.0 BU).The studied normal potato starch samples reached a higher value of peak viscosity (ηmax) of PS (1957.0 BU) decreased in systems with apple juice by about 75% (507.0–518.5 BU) and by about 4% in the WPS samples (from 1387.0 BU to 1328.0 BU). The higher temperature at maximum viscosity (Tŋ max) was noted in PS with juice and fiber (80.7–81.4 °C), which was higher than PS (66.7 °C). The same effect was observed in the case of waxy potato starch but differences between temperatures were lower, about 3 °C .The maximum viscosity , and in the PS samples with AJ and BH, from 518.5–507.0 BU to 477.5–488.5 BU (about 30.0 BU). In the waxy potato starch, viscosity decrease was similar in the control sample (from 1387.0 BU to 575.0 BU) and the waxy starch with juice and fiber (from 1328.5–1341.0 BU to 400.5–407.5 BU).The highest breakdown parameter was observed in the PS sample (1325.0 BU), and this value was significantly reduced when the juice was present in the normal potato starch system (66.5–70.5 BU). The opposite effect was noted in the waxy potato starch system. The addition of apple juice caused an increase in the BD parameter of the WPS (from 904.0 BU to 1079.0–1094.5 BU).Setback values were higher for the normal potato starch system than for waxy starch. The addition of apple juice caused an increase of setback parameters in PS, from 70.5 BU to 209.5–211.5 BU, and in WPS, from 7.5. BU to 32.5–34.5 BU.The normal potato starch with juice showed lower final viscosity values (649.5–658.0 BU) compared to the control sample (706.0 BU).The temperature of the beginning of pasting of normal corn starch was different than in the case of normal potato starch. Namely, the addition of buckwheat hulls and juice caused a decrease in this parameter, not an increase. A decrease in this temperature, along with the addition of juice and fiber, was observed in waxy corn starch. In both cases, normal and waxy corn starch had a higher peak viscosity when compared with the control starch samples (CS and WCS).50 °C) of corn starch and starch with additives had higher values than peak viscosity values (ηmax), as opposed to that in normal and waxy potato starch.The final viscosity of normal corn starch (CS) was different than in natural potato starch (PS) because, in this case, the control sample (CS) had a lower value of viscosity at 50 °C (191.5 BU) than corn starch combined with juice and fiber (211.0–224.0 BU). On the other hand, the final viscosity  to 110.0–118.5 BU (WCS + AJ and WCS + BH + AJ).The results of the texture analysis of fruit gels with buckwheat fiber are presented in The addition of apple juice and fiber to potato and waxy potato starch changed the hardness of starch gels. The hardness of 5%PS increased from 0.044 N to 0.330 N in the sample with juice (5%PS + 20%AJ). Nevertheless, the presence of fiber in fruit gel decreased the hardness to 0.180 N (5%PS + 0.05%BH + 20%AJ) and 0.100 N (5%PS + 0.10%BH + 20%AJ). The opposite effect was observed in waxy potato starch mixtures . The conIn the samples of corn starch gels, the effect of the addition of apple juice and fiber on the hardness of the gels was also observed . A clearw/w) potato and waxy starches and additives such as apple juice (20%) and buckwheat fiber (0.05 and 0.10% in formulation). The color parameters were measured not only for the designed kissel, but also for the starch gels without the addition of apple juice and buckwheat hulls, in order to observe the influence of the botanical origin and type of starch on the value of L*, a*, and b* parameters.The Potato starch gels were characterized by a higher L* parameter in the case of waxy starch (76.07) than in the case of normal starch (70.72), which means that the WPS sample had a greater share of white color . The addParameter a* indicates that samples with juice and fiber had more redness (a* > 0) compared to the starch gel (a* < 0) because their parameter had values in range 1.87–3.01. The presence of BH in the PS gel had a significant impact on the b* parameter, where the sample with juice (5%PS + 20%AJ) had more yellowness (11.80) than samples with BH (5%PS + 0.05%BH + 20%AJ and 5%PS + 0.10%BH + 20%AJ), b* parameter 9.67 and 9.43, respectively.Corn starch gels  had lower values of the L* parameter   than thoThe total content of polyphenols in the tested samples are presented in The obtained starch-based desserts showed antioxidant capacity, which was determined using ABTS cation and DPPH radicals. As in the case of the total content of polyphenols, and in the study of the antioxidant capacity of desserts based on potato and corn starch, the main role of the additive with antioxidant properties was played by apple juice. The addition of buckwheat fiber caused a slight increase in these values, but it was not statistically significant.The quality of the final product is affected by many factors, such as the conditions of preparation, the way it is packaged, as well as storage. The parameters of the raw materials used in production and their mutual proportions also play an important role. According to the Niechlów. P.P.Z. S.A. , the wat0 parameter was higher than in normal or waxy potato starch without additives  to a 4.8% potato starch solution increased T0 by 2.2 °C, and the effect was statistically significant [max than waxy starch  gelatinized the acidic potato starch system with juice which re-associated and formed a network structure slower than the control did. Moreover, it confirms that the final viscosity of the normal or waxy potato starch without additives forms more rigid gels than samples with juice and fiber additions [The normal potato starch with juice showed lower final viscosity values than the control sample . This indditions . The sam0 parameter and increased the final viscosity of waxy corn starch mixtures  contained phenolic compounds, which was confirmed by spectrophotometric analysis . The addThe presence of apple juice and fiber in the blends had an impact on potato and corn starch pastes and gels. The addition of apple juice as well as dietary fiber affected the rheology and texture of the final product. When designing desserts with starch as a base, these are very important parameters that directly affect the consumer acceptance of the food. The presence of acidic juice in waxy corn starch pastes contributed to the reduction of the final viscosity of the tested systems. The addition of buckwheat hulls to kissel enriched the food product in fiber and phenolic compounds. Thus, the addition of buckwheat hulls and apple juice improved the nutritional value of the final products but also caused changes in the technological qualities (hardness and color). The results obtained open up possibilities for further research on the enrichment of food with nutritional health-promoting and functional components, as well as the use of raw by-products rich in micro- and macroelements, polyphenols, and fiber valuable to our health.


The objective of this work is to compare the changes in lotus rhizome starch (LRS) subjected to single modifications by MI  and IR , and dual modification by changing the treatment sequence, i.e., microwave followed by irradiation (MI-IR) and irradiation followed by microwave (IR-MI). The amylose content of native and modified LRS varied from 14.68 to 18.94%, the highest and lowest values found for native and MI-LRS, respectively. IR-treated LRS showed the lowest swelling power (4.13 g/g) but highest solubility (86.9%) among native and modified LRS. An increase in light transmittance value suggested a lower retrogradation rate for dual-modified starches, making them more suitable for food application at refrigeration and frozen temperatures. Dual-modified LRS showed the development of fissures and dents on the surface of granules as well as the reduction in peak intensities of OH and CH2 groups in FTIR spectra. Combined modifications (MI and IR) reduced values of pasting parameters and gelatinization properties compared to native and microwaved LRS and showed improved stability to shear thinning during cooking and thermal processing. The sequence of modification also affected the rheological properties; the G′ and G″ of MI-IR LRS were lower  than the IR-MI sample , giving it a soft gel texture. Nevertheless, dual modification of LRS by combining MI and IR made more significant changes in starch characteristics than single modifications.A comparative study between two novel starch modification technologies, i.e., microwave (MI) and  Nelumbo nucifera Gaertn.) is an aquatic perennial of the Nelumbonaceae family, mainly grown in South Korea, China, India, Thailand, Australia, and Japan [Starch is an edible, biodegradable, renewable, inexpensive, and abundantly available natural polymer ,2. It hand Japan . Lotus rnd Japan . Comparend Japan ,8. Howevnd Japan ,10.Native or unmodified starches do not have the desired characteristics for industrial use due to some of their inherent limitations, such as weak heat and shear resistance, easy thermal decomposition, higher viscosity, easy retrogradation, and low light transmittance ,11. ThesUnlike conventional thermal processes, microwave heating is a multi-physical field phenomenon that involves the non-ionizing radiations generated by a high-frequency magnetic field. These radiations cause dipole oscillation and friction in the substance, resulting in direct heat conversion, known as the dielectric effect. The process has the advantages of faster heating and processing, high penetration, and energy efficiency . Microwaγ-irradiation treatment involves direct exposure to electromagnetic rays. It does not cause a significant temperature increase, involves little sample preparation, is faster, and does not rely on any form of catalyst [γ-irradiation processing has been shown to produce free radicals that can induce structural changes and starch fragmentation resulting in physicochemical changes in starchy food, such as low viscosity and high water solubility [On the other hand, catalyst . The prilubility .γ-irradiation  treatments on LRS when applied in combination was compared with individual treatments. Additionally, dual modifications were carried out by changing the sequence of thermal and non-thermal treatment to observe their effect on different characteristics of starch.In some instances, a single modification of many starches has been found insufficient to optimize their functionality that could meet various industrial needs ,19. TherLotus rhizomes were procured from the local market in Sirsa, Haryana, India. All the chemical reagents used were of analytical grade.g for 10 min and the supernatant was withdrawn. The sediment was washed five times to purify lotus rhizome starch (LRS), dried in a hot-air oven  at 45 °C for 24 h, pulverized, and sieved through 100-mesh size, and the fine powder was stored for further analysis.The starch was isolated from lotus rhizomes following the method described by Singh et al.  after liThe proximate composition  of the native LRS was analyzed using AOAC methods . The samThe method of Deka and Sit  was follγ-irradiation using the method of Punia et al. [The LRS samples (50 g) were treated with a et al. . At roomγ-irradiation treatment as described earlier. After irradiation, a dual-modified LRS sample (MI-IR) was powdered, sieved, and stored until further studies.The dried microwaved LRS (MI) (50 g) was subjected to γ-irradiated LRS (IR) (50 g) was subjected to microwave treatment as described earlier. After microwaving, a dual-modified LRS sample (IR-MI) was dried, powdered, and stored for further studies.The The amylose content of native and modified LRS was determined using the method described by Williams et al.  with ming for 30 min. The supernatant was then poured into a pre-weighed moisture dish, dried in a hot-air oven  at 100 °C, cooled, and weighed again. Additionally, the weight of swollen starch sediment was noted. The swelling power (g/g on a dwb) and solubility were determined as follows:The swelling power (SP) and solubility of native and modified LRS were determined using the method published by Leach et al.  with minThe transmittance of native and modified LRS was measured using the method of Perera and Hoover . BrieflyScanning electron micrography  was carried out with a drop of starch–ethanol suspension (1%) applied to an aluminum stub using both-sided adhesive tape, at an accelerating potential of 10 kV with a magnification power 1000×.−1 resolution was used to obtain the vibrational spectra of all LRS samples. With the air taken as a background, 45 scans of each sample were carried out in the mid-infrared band 4000–450 cm−1. Each sample was repeated at least three times to obtain spectra in terms of absorption.Attenuated total reflection–Fourier-transform infrared spectroscopy  with diamond crystal cell ATR and inbuilt IR -Solution software at 2 cmUsing an X-ray diffractometer  operating at 45 kV and 40 mA, a wavelength of 0.154 nm was used to record the X-ray pattern of LRS samples. Diffractograms were acquired at 25 °C over a 2θ range of 10–50 with a step size of 0.02 and a sampling interval of 10 s. The relative crystallinity of the LRS was calculated using the equation:A Rheometer  with an in-built starch cell was used to examine the pasting properties of native and modified LRS samples. The starch suspension (1.2 g LRS + 13.8 g distilled water) was equilibrated at 50 °C for 1 min, then heated from 50 to 95 °C at 6 °C/min, and then held at 95 °C (2.7 min). The suspension was then cooled to 50 °C at the same rate and held for 2 min (at 50 °C). Pasting temperature (PT), pasting viscosities (peak viscosity (PV), breakdown viscosity (BV), trough viscosity (TV), setback viscosity (SV), and final viscosity (FV)) were obtained from the pasting graph.To), peak temperature (Tp), conclusion temperature (Tc), and gelatinization enthalpy (∆Hgel) were all determined automatically.The thermal properties of LRS samples were determined using a Differential scanning calorimeter (DSC) . A starch–water suspension having 70% water was loaded into a 40 µL aluminum pan, hermetically sealed, and equilibrated for 1 h at room temperature. The sample pan was then heated from 20 to 250 °C at a rate of 10 °C/min. The onset temperature (w/w in distilled water) was prepared, stirred manually, heated , and stirred again for 3 min. After cooling at room temperature and loading on the rheometer ram, the frequency sweep measurements were performed from 0.1 to 100 rad/s at 25 °C and 2% strain  using the Modular Compact Rheometer  equipped with a parallel plate system (4 cm diameter). The G′ (storage modulus), G″ (loss modulus), and tan δ (loss tangent) were recorded at an angular frequency of 6.28 rad/s.The frequency sweep tests of all LRS samples were performed as per the method of Kaur and Singh  with sliThe data presented in the tables were analyzed in triplicate, and single-factor analysis of variance (ANOVA) was carried out for the experimental results. Duncan’s multiple range tests (DMRT) using SPSS 20.0 software  were used to determine the significant differences between the data.The total yield of native LRS was 4.0 g/100 g and the proximate composition showed a moisture content of 10.32 ± 0.58% (wet basis), while fat, protein, crude fiber, ash content, and purity were 0.20 ± 0.03%, 0.66% ± 0.11%, 0.27 ± 0.05%, 0.19 ± 0.01%, and 98.25 ± 1.15% (dry basis), respectively.γ-irradiation, which could be due to the partial degradation/depolymerization of amylose resulting from heat generated during microwaving. Furthermore, increased amylose leaching in microwaved samples favored its complexing with lipids and proteins [γ-irradiation can cause random scission in the glucosidic chains and produce short amylose units and linear chains from the branched amylopectin [The amylose content is a primary quality characteristic of starches which governs their different properties and ultimate end-use purposes. The amylose content of native, single-modified , and dual-modified (MI-IR and IR-MI) LRS was found to be 18.94%, 14.68%, 16.55%, 17.58%, and 18.86%, respectively . The amyproteins , ultimatlopectin , brown rlopectin , and arrlopectin  after irγ-irradiation of lotus seed starch, respectively. The reduction in SP after modification involving heat treatments (microwave) can be due to the destruction of the starch granular structure, resulting in amylopectin chain degradation. The heating presumably also results in re-arrangements leading to the more random distribution of crystalline regions within the starch granules [Swelling describes the capability of starch granules to trap and hold water within their structure and mainly depends on the amylopectin content of starches than their amylose content . The resgranules . Furtherp ≤ 0.05) with increasing temperature from 60 to 90 °C (data not shown). At 90 °C, the highest and the lowest solubility were recorded for single-modified IR-starch (86.9%) and native LRS (9.63%), respectively. During MI treatment, starch granules rupture and are exposed due to partial gelatinization which helps in the leaching and solubilizing of amylose and low-molecular-weight amylopectin resulting in the increased solubility of modified starches [In comparison to MI treatment, IR resulted in more reduction in the SP of modified starches. This reduction in swelling after IR treatment might be due to the amylopectin fragmentation by free radicals and reduction in starch and denatured protein matrix, preventing water diffusion into the starch matrix ,34. Kerfstarches .γ-irradiation. The increase in solubility by IR treatment could be related to the degradation of starch structures and the production of low-molecular-weight fractions having a greater affinity for water, thereby elevating the solubility [γ-irradiation treatment of different starches [γ-irradiation treatment of lotus seed starch and talipot starch.Additionally, a manifold increase in solubility was observed in dual-modified starches involving lubility . Mohd Adlubility  also repstarches ,15. Somep ≤ 0.05) increased after single and dual modifications; the highest value was observed for IR-MI samples. Microwave and γ-irradiation caused starch degradation to smaller/simple sugars such as dextrin, maltose, glucose, etc., which have a higher affinity for water than starch [The ability of solids  to entrap water or oil against gravity define their water absorption capacity (WAC) and oil absorption capacity (OAC). The WAC of native and modified LRS ranged from 1.62 to 2.00 g/g . It was n starch ,38. Highn starch . The modn starch . Similarn starch . Single-The change in transmittance of all LRS samples is shown in p ≤ 0.05) compared to the native counterpart. The degradation of starch molecules in different-molecular-weight amylose may contribute to the packing of the starch paste after MI treatment, increasing the opacity and affecting the paste clarity [Upon microwaving, the light transmittance decreased significantly  higher than that of the native and MI-treated LRS. The synergistic action of MI and IR might decrease swollen starch granules, followed by the gelling and splitting of amylopectin chains, thus increasing light transmittance. Furthermore, due to reduced retrogradation, the light transmittance of dual-modified LRS was enhanced. The enhanced paste clarity suggests that modified starch could be used in different frozen food products and pie fillings.t values . It was γ-irradiation. Similar morphological effects after γ-irradiation were reported on talipot stem starch [γ-irradiation than C-type), and moisture content might affect the resistance of starch granules against rupturing [γ-irradiation, resulting in its rupture.A scanning electron microscope (SEM) plays a vital role in examining and comparing the surface characteristics of native and modified starch granules. The SEM micrographs of native, single-modified (MI and IR), and dual-modified (MI-IR and IR-MI) LRS are presented in m starch  and lotum starch . Some faupturing . The sur−1, (ii) 800−1300 cm−1 (the fingerprint zone), (iii) 2800–3000 cm−1 (C−H stretch zone), and (iv) 3000–3600 cm−1 (O−H stretch zone). The main absorption peaks of native LRS were observed around 3292.90, 2932.64, 1644.83, 1337.23, 1076.75, 994.97, and 524.24 cm−1. The broad and strong characteristic absorption band around 3292.90 cm−1 (native), 3290.81 cm−1 (MI), 3293.46 cm−1 (IR), 3276.05 cm−1 (MI-IR), and 3292.48 cm−1 (IR-MI), attributed to-OH stretching [−1 by a stretching vibration in all LRS samples showed the presence of CH2 deformation [2 groups’ stretching vibration. The intensity of the peak at 1644.83 cm−1, corresponding to the H–O–H bending vibration in water molecules of the starch amorphous region [−1 and 1149 cm−1 were due to CH2 bending and C-O-O twisting [−1 represented the presence of α-1,4glycosidic linkage and C-O-C stretch [An FTIR spectrum represents the bands corresponding to stretching, bending, and deformation related to the main functional groups present in the starch granule. The FTIR spectra of native and single- and dual-modified LRS are presented in ormation . In dualtwisting , respect stretch . As show stretch , while d stretch .γ-irradiation treatment did not cause a remarkable change in the intensity of absorption peaks which might be due to the low moisture present in the starch or the lower dose of irradiation used in the processing of LRS [γ-irradiation, the destruction of chemical bonds by high energy radiations was signified by the changes in the FTIR spectra of the OH and CH2 stretching and H–O–H and C–O–H bending vibration. During dual modification, unstable reactive agents  were produced from the water present in the starch, which decreased the peak intensities corresponding to OH and CH2 groups [After MI treatment, the peak intensity decreased significantly and became wider. It is reported that inter- and intra-molecular hydrogen bonding are enhanced during microwave processing which is also evidenced by the increase in the gelatinization onset temperature reported in thermal measurements . The samg of LRS . Howbeit2 groups .γ-irradiation might destruct the crystalline phase through the molecular depolymerization by free radicals which split the amylopectin units and decrease the total crystallinity [Moreover, the internal changes in the degree of order (DO) which refers to the RC can be calculated using the ratio of 1047/1022, while the degree of double helix (DD) can be calculated by using the ratio of 995/1022, based on the FTIR spectra of starches . The 104allinity . The resallinity . The amyθ), epitomizing a typical type-A starch pattern. Similar results for native LRS ) have been reported earlier [γ-irradiation treatment probably degrade the amorphous lamella, promote the debranching of amylopectin, and degrade amylose into smaller molecules. These changes result in reorganization and increase the crystallization of starch molecules, providing XRD patterns with high-intensity peaks. Earlier, Chung and Liu [X-ray diffractometry is used to demonstrate the presence and characteristics of the crystalline structure of starch granules. Starch has been demonstrated to have four different crystalline patterns using XRD . The packing arrangements of the double helix in amylopectin and the hydration levels are used to distinguish the A and B crystalline patterns. Because the double helix is packed closely, the A-type is less hydrated, whereas the B-type has a more hydrated helical core.  and Liu  also fou and Liu . Some fa and Liu .γ-irradiation-treated lotus seed starch by Punia et al. [The relative crystallinity (RC)of native LRS was 28.2%, which was higher than that of single- and dual-modified LRS A–E. The a et al. . This dea et al. ,38, and p ≤ 0.05) decreased PV, BDV, and SBV but a significant (p ≤ 0.05) increase was observed in PT, TV, and FV. The reduction in PV after MI treatment can be due to the degradation of polysaccharides and reduction in the swelling power of starch granules [γ-irradiation significantly (p ≤ 0.05) decreased the PT and all pasting viscosities of IR-LRS, which showed the lowest values in comparison to native as well as single (MI) and dual (MI-IR and IR-MI)-modified LRS. The lower PT, PV, and SBV connote decreased resistance to swelling and rupturing of starch granules. A similar decrease has also been reported in lotus seed starch and talipot stem starch [The pasting profile of native and modified LRS samples is shown in granules . A similgranules . The lowgranules ,40, whilm starch ,15. Thisp ≤ 0.05) pasting viscosities compared to their native and MI-treated counterparts. However, the PT of dual-modified LRS was increased significantly (p ≤ 0.05). The degradation of the starch chain during dual treatment resulted in a significant drop in starch swelling power, resulting in a lower PV of dual-modified LRS. Aaliya et al. [The dual-modified (MI-IR and IR-MI) LRS showed significantly decreased  of native LRS were 28.9, 78.05, and 139.8 °C, respectively. In one earlier study, Sukhija et al. [To, Tp, and Tc of 68.30, 72.04, and 76.81 °C, respectively, for native LRS. The thermal characteristics of starch can be affected by many factors such as amylose–amylopectin ratio, chain distribution, double-helix order, and molecular arrangement of the crystalline region [To and Tc showed no significant (p ≤ 0.05) difference, but Tp increased significantly (p ≤ 0.05) after both single modifications and the highest value (86.7 °C) was observed for MI-treated LRS. This increase after MI treatment can be attributed to re-arrangement within the crystalline and amorphous regions in starch granules, which possibly strengthened the amylose–amylopectin and amylose–amylose interactions and resulted in the limited hydration and swelling of MI-treated starch [γ-irradiation, the significantly (p ≤ 0.05) increased Tp can be attributed to the formation of smaller molecules  due to degradation and is consistent with the increasing soluble content. The monosaccharides present in starches have been reported to elevate their gelatinization temperature [The thermal properties of native, single-, and dual-modified LRS are shown in e region . Compared starch . Similard starch . Some otd starch . After γperature . Previouperature .To increased but Tc and Tp decreased for dual-modified (MI-IR and IR-MI) LRS. To and Tc are related to the melting temperatures of the weakest and strongest crystallization in starch, respectively [To. Additionally, different modifications leading to different compactness of starch granules can affect the gelatinization temperatures of modified starches [Compared with native, ectively . After dstarches .Hgel) measures the overall crystallinity of the amylopectin and indicates the loss of molecular order within the granule [gelH of native LRS was 253.1 J/g  treatments. The increase in ΔgelH indicated that a single treatment disrupted the amorphous region of starch. On the other hand, a decrease in ΔHgel can be attributed to the destruction of the double-helix structures [The enthalpy of gelatinization , which revealed their elastic nature. The magnitude of G′ and G″ increased with increasing angular frequency; G″ showed a more significant increase than G′. No cross-over between G′ and G″ was observed, indicating the stability of these starch pastes over the applied frequency range (0.1–100 rad/s). After MI treatment, the value of G′ and G″ increased over the angular frequency range compared to native LRS. This increase can be due to microstructural and conformational changes in LRS due to gelatinization and cross-linking of the molecular chains leached out of the starch during MI processing [The rheological behavior of the starch gel plays an important role in determining the processing ability, texture, and eating quality of foods prepared using different starches. The experimental data and frequency curves produced from frequency sweep tests are presented in ocessing . A consiocessing . Upon IRocessing .p ≤ 0.05) increase in G′ but a significant (p ≤ 0.05) decrease in G″ compared to native LRS. Additionally, both dual-modified LRS samples showed significantly (p ≤ 0.05) lower and higher values of G′ and G″ compared to microwaved and γ-irradiated LRS, respectively. The increase in the G′ value of dual-modified LRS might be attributed to the enhanced stability of the granular integrity caused by the bond strengthening in the swollen granules [Both dual modifications showed a significant (granules . A tan δγ-irradiation significantly changed the properties more than single modifications. A combined effect of microwave and γ-irradiation resulted in the development of fissures and dents on the surface of starch granules. Additionally, the treatments reduced the peak intensities of OH and CH2 groups in FTIR spectra. An increase in the light transmittance value suggested a low retrogradation rate for dual-modified starches, making them more suitable for food application at refrigeration and frozen temperatures. Dual-modified LRS also showed remarkably lower values for the gelatinization and pasting properties but improved stability to shear thinning during cooking and thermal processing.The modification of LRS using thermal and non-thermal methods made a noticeable change in the characteristics of starch and starch gels. Nevertheless, the dual modification of LRS by combining microwave and γ-irradiation can be effectively used for modulating different characteristics of native starches. Since the safe dose limit for γ-irradiation suitable for human consumption is 10 kGy, combining it with other treatments such as microwave enhances the effect and usage of γ-irradiation in starch modification synergistically. Therefore, it can be concluded that these modifications can be applied in combination at a lower dose level and can produce modified starches with significantly altered properties desirable for diverse food and non-food applications.In addition, some apparent changes in the starch characteristics after dual modification could be found owing to the sequence effect, such as amylose content decreasing more in MI-IR-treated LRS compared to IR-MI-treated LRS. The pasting properties of MI-IR starch were significantly lower than the IR-MI sample, whereas for transition temperatures, the trend was reversed. The rheological properties were also affected by modification sequence; the G′ and G″ of MI-IR LRS were lower than IR-MI starch, giving it a soft gel texture. From this study, it can be concluded that microwave and


Thickness swelling (TS) at 24 h of the panels was reduced from 36.16% to 28.37% when 10 wt.% starch was added. These results showed that giant reed–gypsum–starch particleboards can be manufactured with physical and mechanical properties that comply with European standards for use in building construction.This paper analyzes the properties of composite particleboards made from a mix of giant reed with gypsum plaster and starch as binders. Experimental boards were manufactured with a 10:2 weight ratio of giant reed/gypsum plaster particles and different amounts of starch. Giant reed particles used were ≤0.25 mm. The mix was pressed at a temperature of 110 °C with a pressure of 2.6 MPa for 1, 2, and 3 h. The results showed that the boards manufactured with longer times in the press and with 10 wt.% starch achieved the best physical and mechanical properties, obtaining a modulus of rupture (MOR) of 17.5 N/mm The use of wood is only expected to increase by 30% in the energy sector within this decade [The world is facing a shortage of wood as a row material. In the last 30 years, forest area decreased from 32.5% to 30.8% of the total land, representing a net loss of 178 million hectares [The most common wood board on the market is particleboard, which is obtained by binding wood particles with an adhesive, usually urea–formaldehyde (UF). In the construction sector, several types of particleboards include gypsum plaster as an inorganic glue (gypsum plasterboard—GPB). These panels have the advantages of no formaldehyde emission, combustion blocking off, and less loss of heat exchange . HoweverIn order to reduce the use of wood and replace it with other lignocellulosic materials in GPB, several investigations have been focused on using agricultural residues: banana fiber and rice straw , paper cCurrently, gypsum boards have a high market share since they are commonly used in the finishing of interior walls and ceilings. GPB made from agricultural residues is more environmentally friendly and could replace traditional gypsum boards. It is, however, necessary to improve their quality by making them more resistant and durable.Arundo donax L.) is one of the largest types of grass growing in the Mediterranean region; it is a wild plant that grows annually, reaching average heights of 4 m and a mean thickness of 4 cm. It was used in building construction in many Mediterranean countries; however, it is today in disuse and has been replaced by different types of wood. Currently, reeds grow unchecked and at a great rate. When reeds colonize riverbanks, the riverside vegetation is impoverished, and infrastructures that cross watercourses are blocked, making drainage difficult. When the water level rises more than usual, this leads to flooding that causes environmental, economic, and material damage. These problems force the competent authorities to make significant economic investments in cleaning and clearing this plant waste [Giant reed  with gypsum plaster and starch following a method based on the wood industry dry process but with variations  so that it can be produced in the particleboard industry and, therefore, counteract the high dependence on wood imports using an easily renewable resource such as giant reed. By controlling this reed, a more sustainable and formaldehyde-free particleboard can be obtained, which would reduce pressure on forest resources and create new job opportunities.The aim of the present research was to study the manufacturability of particleboards made from giant reed (Arundo donax L.), calcium sulfate hemihydrate (gypsum plaster), and different amounts of potato starch (Solanum Tuberosum L.).The materials used in the manufacturing of the particleboards were giant reed  without any additives with an apparent density of 2330 ± 20 kg/m³ was mixed with the giant reed. Potato starch from the food industry with a purity of 90% and a bulk density of 320 ± 15 kg/m³ was added to the gypsum and giant reed. This starch is a mixture of amylose and amylopectin (both polysaccharides), and it typically contains large oval granules and gels at a temperature of 58–65 °C.Commercial gypsum plaster (CaSOThe method followed was based on the wood industry dry process but with variations (no pretreatments and different parameters at the hot press).The experimental boards were manufactured with a 100:20 proportion by weight of giant reed/gypsum, adding different amounts of starch . 3 .First, particles of giant reed, starch, and gypsum were dry-mixed. Then, 10% water was sprayed in relation to the weight of the giant reed particles in a laboratory glue blender mixer with rotating blades and a volumetric capacity of 100 dmAfterward, the mat was formed manually in a mold with dimensions of 400 × 600 mm . Then, iParticleboards were single-layered with an approximately thickness of 7 mm. Characteristics of the panels are shown in For each panel type and time, four replicates were made. Therefore, 36 particleboards were manufactured in total.The method followed was experimental. The tests were conducted in the Materials Laboratory of the Higher Technical College of Orihuela at the Miguel Hernández University of Elche.In order to characterize the mechanical, physical, and thermal properties of each of the boards being studied, samples  were cutThe moisture content of the material was measured with a laboratory moisture meter , the water immersion test was carried out in a heated tank, and the mechanical tests and density were performed with a universal testing machine .For the statistical analysis, SPSS v. 28.0 software  was used. Analysis of variance (ANOVA) was performed, and, for the mean values of the tests, the standard deviation was obtained.3; therefore, they can be considered as high-density particleboards. The panels with the highest density were the 20:10 type, which included 10% starch in their manufacture. Longer times in the hot press resulted in more density.Mean density of the boards ranged between 925 and 1095 kg/mMeanwhile, the 20:10 type had lower values of TS and WA than the remaining experimental panels. Increasing time in the hot press also improved the TS and WA results. This was probably related to the increase in density, since there were fewer gaps between the particles that could be filled with water.Thermal conductivity seemingly decreased with the addition of starch and longer pressing times, but this could not be concluded. Panels manufactured with more than 5% starch for 2 h had the lowest conductivity values. Given the standard deviation of the results, it is possible that pressing the panels for more than 2 h would not have improved the results when starch was added.2.MOR values of the experimental panels can be seen in 2 of MOE.The MOE results showed in 2. The standard deviation in types 20:0 and 20:5 of the results prevent concluding that increasing the pressing time between 2 and 3 h improved the results.From the results of IB in p-value < 0.05) with the panel type and the pressing time except for IB, which was only influenced by the panel type.Statistical analysis of 2 and an IB value of 0.28 N/mm2 can be considered as particleboards for general use in a dry environment (grade P1). Particleboards that can be used in the manufacture of furniture (grade P2) have to reach an MOR of 11.0 N/mm2, an MOE of 1800 N/mm2, and an IB of 0.40 N/mm2. For nonstructural boards in a humid environment, the minimum requirements are 15.0 N/mm2 for MOR, 2050 N/mm2 for MOE, 0.45 N/mm2 for IB, and 17% for TS at 24 h.The European standards  establisIn the present study, boards manufactured with less than 10% starch did not reach the minimum mechanical values to be commercialized. The selection of a particle size of less than 0.25 mm for the manufacturing of the boards was based on our previous experience and the existing literature, since smaller particle sizes resulted in better properties .The process followed in the research was slightly different since GPBs are not usually pressed or heated. Particleboards that follow a dry process usually require a pretreatment that consists of drying the material until it reaches a maximum of 4% moisture content. In the present study, there was no need for pretreatments, and the material could be used with a 8% moisture content.Eucalyptus sp. and Pinus massoniata with citric acid (CA) with a targeted density of 1200 kg/m3 and dimensions of 300 × 300 × 10 mm. They reduced the moisture content of the GPB mats to about 2–3% in a dryer at 45 °C before pressing at room temperature the particleboards. Kim [Kim et al.  manufactrds. Kim  used theThis lower gypsum content is not enough for the binding of the particles. If the method used was cold pressing, the particles would have disaggregated. Therefore, since type 20:0 resulted in stable particleboards, some self-binding could have happened in the hot press within the giant reed in the absence of starch. The elucidation of this process is very complex with multiple theories such as the glass transition of cellulose, hemicellulose, and lignin , the staIn comparison with binderless particleboards, some authors indicated that a high temperature of at least 180 °C and high pressures of 3.5 MPa are needed in order to manufacture the boards . Others It is feasible to manufacture particleboards made from giant reed, gypsum plaster, and starch that have good mechanical properties according to the European standards.Through the addition of starch and increasing the pressing time of the experimental panels, better mechanical and physical properties were obtained. With 10% starch and a pressing time of 2 or 3 h, the panels reached the P2 classification for furniture production.Using giant reed waste in manufacturing particleboards would be beneficial in terms of the environment and energy efficiency since less energy is required than the conventional process.


The current approach to identifying significant subgraphs relies on hierarchical clustering, which can be used to inform clinicians about important pathways involved in the disease or phenotype of interest. The reliance on a hierarchical clustering approach can hinder subgraph quality by biasing toward finding more compact subgraphs and removing larger significant subgraphs. This study aims to introduce new significant subgraph detection techniques. In particular, we introduce two subgraph detection methods, dubbed Correlated PageRank and Correlated Louvain, by extending the Personalized PageRank Clustering and Louvain algorithms, as well as a hybrid approach combining the two proposed methods, and compare them to the hierarchical method currently in use. The proposed methods show significant improvement in the quality of the subgraphs produced when compared to the current state of the art.Chronic obstructive pulmonary disease (COPD) is one of the leading causes of death in the United States. COPD represents one of many areas of research where identifying complex pathways and networks of interacting biomarkers is an important avenue toward studying disease progression and potentially discovering cures. Recently, sparse multiple canonical correlation network analysis (SmCCNet) was developed to identify complex relationships between omics associated with a disease phenotype, such as lung function. SmCCNet uses two sets of omics datasets and an associated output phenotypes to generate a multi-omics graph, which can then be used to explore relationships between omics in the context of a disease. Detecting  Discovering significant subgraphs within multi-omics networks, such as those produced by methods such as sparse multiple canonical correlation network analysis (SmCCNet)  is a chronic lung condition which causes expiratory airflow limitation and respiratory problems, and has recently been the fourth leading cause of death in the United States  or forced expiratory volume in 1 s percent predicted (FEV1%)  to calculate correlation between a pair of biomarkers or omics features, such as proteins and metabolites, in the context of a disease marker, such as forced expiratory volume in 1 s   algorithm, dubbed Correlated PageRank, to find significant subgraphs. PageRank is a local graph clustering method that is commonly used for web page ranking, social networks, and recommendation systems , has previously been used for complex disease analysis. PPC calculates PageRank scores for each node in a graph, then uses those scores to identify a community around a user-specified seed node. Kohler et al. used it to search in the interactome for the prioritization of candidate disease genes  be a weighted undirected graph with vertex set V and edge set E. We assume that G is a simple graph, with no multiple edges connecting nodes. We define edge set E = {, w) | vi, vj, ∈V} , where w = f, 0 ≤ w ≤ 1 represents an edge weight defined by a function f. Each node vi ∈ V has a corresponding data vector n vertices V, we define a data matrix V. We also define a target vector, Y ∈ Rm.In this section, we give a formal definition of the problem. Let G′ =  be a subgraph of G, where S ⊆ V and X′. The correlation ρ of a subgraph is defined as the Pearson correlation between the first principal component of the data matrix X′ corresponding to the set of nodes S, PC1s, with the target variable Y, as shown below in Equation 1. PC1s is used to represent the data matrix X′ as a single vector to facilitate comparison to the target variable. While there are other measures that can be used to represent correlation with a target variable, such as Spearman correlation or Kenall correlation, we chose Pearson correlation to match the measure used by Mastej et al. to facilitate comparison between findings  with maximal correlation and cohesion among all subgraphs of G. With the significant subgraph detection problem, given a graph G, we want to find a significant subgraph which optimizes a bi-criteria function reflecting correlation and cohesion, such that a significant subgraph is maximally correlated to Y while also maximally cohesive topologically. A subgraph identified by significant subgraph detection, relative to other subgraphs, will have high connectivity within the subgraph, low connectivity outside of the subgraph, and high correlation to the target variable Y.We define a significant subgraph as the subgraph As defined above, significant subgraph detection is a constrained graph clustering problem with correlation as the constraining balancing factor, and considering any balancing factor for graph clustering has been shown to be an NP-Hard optimization problem  is the steady state distribution of a random walker, α ∈  specifies the teleportation probability, s is the teleportation set, and W is the random walk transition matrix  in the sweep-set, and the set with lowest conductance is selected.The steady state vector, which is also called the PageRank vector, is used to sort the vertices from higher to lower probability-per-degree, which represents the probability of a node being visited by the random walker. This produces the sweep-set, a set of PPC results are affected by a variety of user-selected parameters. The seed set determines the nodes around which a cluster is formed. Selection of the set of seed nodes can be done based on node degree, with high degree nodes being selected to act as hub nodes, or the selection can be informed by biological function, with nodes corresponding to biological markers suspected of being highly correlated to the disease being selected. The teleportation probability affects the distance from the seed set the random walker will explore, with a higher teleportation probability resulting in a higher emphasis on near the seed set, and a lower probability producing larger diameter clusters. The termination factor  determines the length of the search domain.sequential and simultaneous. In Section Subgraph Pruning we introduce two approaches to pruning the subgraphs produced in the previous step, which we refer to as threshold and nesting. The nesting approach to pruning is further split into two approaches, called graph nesting and subgraph nesting.The traditional PPC approach to clustering lacks consideration for correlation to the phenotype. While subgraphs identified by the algorithm will be densely connected, this does not capture the full relationship between omics and the phenotype. In order to better identify important subgraphs, correlation between a given set of omics and the phenotype is calculated and incorporated. Correlated PageRank consists of two main steps, a subgraph identification step where significant subgraphs are identified based on the calculated PageRank score, and a pruning step which serves to decrease the size of subgraphs produced such that the algorithm produces smaller subgraphs while maintaining connectivity and correlation. In Section Subgraph Identification we introduce two approaches to incorporating correlation into the subgraph identification step of Correlated PageRank, dubbed G to be the sum of degrees of the nodes in G, shown in Equation 3. Conductance, shown in Equation 4  and omics-phenotype correlation (ρ). We define volume of kP is a user set weight, such that kP ≤ 1, which sets the proportion of conductance and correlation in the combined objectective function Φ+ ρ.Two methods were used for subgraph identification, referred to as sequential and simultaneous. In the sequential approach, the conductance (Φ) was calculated during the sweep cut procedure to generate highly connected subgraphs. The omics-phenotype correlation (ρ) was then calculated for each subgraph as in Equation 1, and those with the highest correlation were chosen as the best subgraphs. In the simultaneous approach, conductance and correlation are combined into a single objective function as a weighted sum, shown in Equation 5, replacing conductance during the sweep cut procedure. Subgraphs produced by Correlated PageRank are very large and may contain weak edges between features. To improve subgraph quality, we explored methods for shrinking the size of the identified subgraph, removing weaker edges and improving correlation. Two pruning methods are applied, threshold and nesting.In the threshold pruning approach, a threshold is chosen, and any edges with an edge weight lower than the threshold are removed. Isolated nodes and smaller fragments resulting from this edge removal are also removed from the subgraph, resulting in a smaller, more strongly correlated subgraph. While a similar pruning approach is applied during the SmCCNet procedure to produce the global graph, the thresholds used are intentionally small to avoid over-pruning and fragmenting the network prior to downstream analyses. To choose the optimal threshold, a grid search approach is used. Different thresholds in the range of edge weights are tested, with the optimum threshold resulting in the highest omics-phenotype correlation and an appropriate ratio between omics, informed by the biological context of the omics and disease of interest. This approach to pruning is naïve, as it removes all edges classified as weak without considering their effects on the overall quality of the subgraph. While a grid search technique was applied to find an optimal threshold that led to the highest quality subgraph, this remains a heavy-handed approach to decreasing subgraph size.G′ was identified, it is removed from the global network G, and Correlated PageRank was applied to the resulting network G\G′. In subgraph nesting, the top subgraph is used as the input to the next iteration of Correlated PageRank. We expect the nesting approach to be a more suitable way to decrease subgraph size. In contrast to the threshold approach, the nesting approach iteratively applies the same Correlated PageRank algorithm to subsequent subgraphs; correlation to the phenotype is considered throughout the process, and smaller subgraphs are generated in a more informed way. Within the two sub-approaches, we expect subgraph nesting to perform better, as it continues searching for stronger subgraphs within an already known strong subgraph.In the nesting approach, the Correlated PageRank algorithm is iteratively applied to produce progressively smaller subgraphs. Two nesting sub-approaches were investigated, graph nesting and subgraph nesting. In graph nesting, once a top subgraph As before, we begin with an overview of the traditional Louvain algorithm, then introduce our changes. The Louvain algorithm is a two-phase heuristic graph clustering algorithm, consisting of an optimization phase followed by a merging phase , which is a measure of connectivity within a subgraph compared to the expected connectivity if all edges were randomly assigned. Similar to conductance, which was used in the Correlated PageRank method, it aims to capture connectivity within subgraphs. By optimizing for connectivity, the Louvain algorithm optimizes subgraphs such that nodes are well connected within a subgraph, and less connected between other subgraphs, effectively finding connected communities within a network.kL, a weight parameter to control the effect of modularity and correlation in the hybrid objective function, such that kL ≤ 1. The hybrid objective function, Equation 9, allows the algorithm to optimize subgraphs such that they are well connected (high modularity) and well correlated to the phenotype (high omics-phenotype correlation). Different weights were tested using a grid search method to find the optimal balance between the quality metrics.To optimize this algorithm for an omics dataset, where both connectivity and correlation to a phenotype are important, Correlated Louvain uses the weighted sum of modularity, Q (Equation 6), and Pearson correlation, ρ (Equation 1) in a hybrid objective function. We define As the Correlated Louvain algorithm produces a partitioning of the graph, which consists of a set of subgraphs, a separate subgraph identification step is not necessary with this method, unlike Correlated PageRank. During our testing, subgraphs produced by this method were small in size, and thus pruning was also not necessary, but would follow a similar procedure to those outlined in Section Subgraph Pruning. The expected size of a significant subnetwork depends heavily on application; in our case study this was informed by the biological processes and literature surrounding COPD. While subgraphs in our tests were not large enough to necessitate further pruning, this may not always be the case with every application.i is defined as the difference between the correlation of the subgraph containing the node i, S, and the subgraph excluding the node i, S', and its relative contribution αi is the ratio of its contribution to that of the node with the largest contribution, αmax.A hybrid approach utilizing both Correlated Louvain and Correlated PageRank to generate significant subgraphs was explored. The Correlated Louvain approach described in Section Correlated Louvain, is first utilized to generate a partitioning for the global graph generated by SmCCNet. Correlation to the phenotype is calculated for all non-singleton subgraphs, and the subgraph with the highest correlation is used to seed the Correlated PageRank algorithm. Teleportation values for the nodes in the seed set are weighted by their relative contribution to the subgraph's correlation, as shown in Equation 10. The contribution of node The Correlated PageRank algorithm produces a top subgraph, which is then partitioned again using Correlated Louvain. The cycle, depicted in By using the Correlated Louvain algorithm to generate candidate seed nodes for the Correlated PageRank algorithm, the need to pre-select a seed node, whether randomly or based on biological intuition, is bypassed, allowing for a more systematic selection of a good set of seed nodes. This, in turn, should allow the Correlated PageRank algorithm to perform better. Repeating this process has a similar outcome to nesting and pruning, in that it iteratively decreases the size of the network such that the remaining nodes generate strongly correlated and well-connected subgraphs of an appropriate size.Subgraph identified by the above approaches may have significant overlap. Identifying the unique subgraphs from a pool of significant subgraphs is an important task when considering the problem of identifying pathways from a multi-omics network. We developed a method to visually compare two subgraphs, allowing for easy identification of the similarity of two subgraphs, which we discuss below.i, as shown in Equation 11, where E(i) represents the set of all unique edges in the graphs G1 and G2- connected to node n, d(e) represents the edit distance between edge e in G1 and G2, and w is the weight of edge e in graph Gi. Edit distance quantifies the similarity between two graphs by counting the minimum number of edits needed to make the two graphs match; a higher edit distance corresponds to more edits and lower similarity, whereas an edit distance of 0 signifies identical graphs.Two measures were used to assess the similarity of two subgraphs, computed using the edit distance, or Levenstein distance of node 1 (left) and G2 (right) in lev(d) = lev(e) = ∞. Looking at node c, which exists in both graphs, lev(v) = 4; of the 4 unique edges connected to c in either graph, one edge, bc, has a different weight, and three edges, ac, cd and ce, only exist in one graph. Similarly, lev(a) = 1, since edge ab exists in both graphs with equal weight while edge ac only exists in G2. The sorted edit distance vector for the sample graphs is as follows:As an example, consider the sample graphs GThis can be visualized as a heatmap to quickly assess and compare the similarity of multiple pairs of graphs. For the above sample, the heatmap shown in 1 and G2 to their union, and is a quantitative measure that can be used to assess how similar or dissimilar they are. A higher Jaccard index implies higher similarity.We also assess similarity using the Jaccard index, J, as shown below in Equation 12. The Jaccard index is the ratio of the intersections of two graphs, GGraph similarity is primarily used to find unique subgraphs; the Correlated PageRank method will generate different subgraphs given different seed nodes, but some of these subgraphs may be very similar. Similar subgraphs are not informative as they uncover the same biological pathways. To find unique subgraphs, and thus unique pathways, different highly correlated subgraphs are compared, and those showcasing significant dissimilarity are selected for further analysis. Significant dissimilarity is discovered by plotting the Jaccard indices and visually identifying a steep drop in the index values indicating a significantly dissimilar subgraph.Correlated PageRank was implemented using Python 3.8. Correlated Louvain was implemented in C++ and exposed to Python as a module. All testing was done using Python 3.8. The graph used in our case study was generated using the SmCCNet R package, version 0.99.0, and exported to be used with the NetworkX and igraph Python packages during testing. Tests were conducted on an Intel Core i9-11900K. Code for our proposed methods is available on GitHub at bdlab-ucd/correlated-louvain. The datasets used in our case study, Section Experimental Evaluation: A Case Study, is available from COPDGene; while it is a public dataset, it is made available by request with a submitted proposal detailing the intended usage of the dataset.1% measurements, which is commonly used for COPD diagnosis and severity evaluation. All measurements were taken from 994 subjects common across the two omics datasets and the phenotype dataset. Using the same dataset Mastej et al. reported two omics subnetworks, one with 13 proteins and 7 metabolites having −0.34 correlation (p = 2.5 * 10−28) to lung function, and another with 13 proteins and 10 metabolites having −0.27 correlation (p = 2.6 * 10−17) to percent emphysema  dataset consists of FEVFor each of the approaches we introduced, we first conducted behavioral tests to optimize each approach individually. The top subgraphs produced by each approach, as well as those produced by the current hierarchical approach, were compared. The results reported below were produced by running the experiment once for each set of parameters.1% phenotype, for the same set of subjects, as described above. SmCCNet weights, which control the weight of different features when calculating canonical correlation during the SmCCNet algorithm, represented as a-b-c, were explored using the Correlated PageRank approach, detailed below, and the optimal set of weights was then used to generate the same graph used in all final comparisons.All tests were run using the same protein-metabolite omics dataset and FEVOur primary measure of subgraph quality was correlation to the phenotype, ρ (Equation 1), with a higher absolute correlation indicating a more significant subgraph which better describes the phenotype. We also report conductance, Φ (Equation 4), to summarize connectivity within each subgraph relative to the global network. Subgraph size is also reported, which can be an indication of subgraphs which are likely too small or too large to be of importance. While appropriate subgraph size will depend on the specific omics used and intended application, subgraphs with hundreds of nodes are likely too broad to be informative, and subgraphs with very few nodes are potentially too narrow in scope and ignore important participants in the pathway they describe.For each of the three proposed approaches, different parameters needed to be tuned to find the optimal subgraphs, the results of which are discussed below.Correlated PageRank is affected by factors such as tolerance (ϵ), teleportation factor (α), the selected seed node, and the weights used in the SmCCNet algorithm to generate the global graph. Tolerance, teleportation factor, and SmCCNet weights were studied using a grid search method, testing different values to find an optimal set of parameters. Seed nodes were selected at random to study their influence on the resulting subgraphs' correlation and conductance.Correlated PageRank consisted of two similar but distinct approaches, sequential and simultaneous as discussed in Section Subgraph Identification, which are discussed separately in Sections Subgraph Identification–Sequential Approach and Subgraph Identification–Simultaneous Approach. The size of subgraphs identified by Correlated PageRank necessitate pruning, which is discussed in Section Subgraph Pruning.*10- 2, the subgraphs generated were large (419 nodes) and the absolute correlation was small (0.14), whereas when ϵ > 1*0−3, the tolerance stops affecting size and correlation significantly. As mentioned before, the PageRank search continues until the difference between PageRank scores in two consecutive iterations is below ϵ. When ϵ is lowered, the random walker can visit more nodes on the graph, and thus subgraph size and correlation increase.The effects of tolerance (ϵ) on the Correlated PageRank subgraph size and conductance are shown in p = 7.93 * 10−21), which is about 1.5 times higher than the previous hierarchical results with the same graph .* 10−1-1 * 10−8 and α in the range of 0–0.15. The absolute correlations of the subgraphs produced from the 1-10-10 graph were about twice those of the 1-5-5 subgraphs, with conductance being about a third. SmCCNet weights are applied to the canonical correlation to adjust the relationship between different features. Larger b and c values create a stronger correlation between each of the omics and the phenotype compared to the correlation between the two omics. This has the effect of pruning the weak edges in the global graph generated by SmCCNet, resulting in stronger edge weights overall, and higher quality subgraphs when Correlated PageRank is applied. This experiment was also conducted with SmCCNet weights of 1-11-11 and 1-1-1, both of which resulted in small global networks not suitable for subgraph identification, at 32 and 228 nodes, respectively. SmCCNet weight, as seen here, can have a significant effect on the subgraphs found downstream. The 1-10-10 set of weights produced the most favorable results, so it was used for all further experiments.*10−4, then selecting seed nodes from subgraphs with |ρ| > 0.33. These seeds produced subgraphs with stronger correlation and lower conductance, as expected.We repeated these experiments with only strong seeds, shown in Two pruning approaches were tested, with the goal of reducing subgraph size while maintaining quality. Results from these approaches under different conditions are summarized below.Two nesting approaches were investigated, global and subgraph nesting. Global nesting consists of removing the top subgraph from the global graph, then applying Correlated PageRank to the remaining graph. Subgraph nesting instead isolates the top subgraph and applies Correlated PageRank to it instead of the global network. To obtain high correlation subgraphs, strong seeds were chosen at each iteration.kL, which we studied using a grid search. Additionally, as Correlated Louvain is a global clustering approach, we studied the distribution of correlations of the clusters generated by the algorithm to better understand the quality of clusters generated by the algorithm. Finally, we studied the behavior of the algorithm at different levels in the hierarchy to understand how the partitionings generated evolve as the algorithm progresses.The Correlated Louvain method is affected by the weight used in the objective function kL was set to 0.2, which produced a top subgraph with ρ = −0.29 (p = 1.28 * 10−20). We see, however, that all subgraphs produced are much smaller than those produced by the Correlated PageRank method. While this forgoes the necessity to prune the resulting subgraphs, it also may heavily limit the useful information which can be extracted from this subgraph. The largest subgraph produced was of size 39, but correlation drops to 0.24 (p = 4.23 * 10−14).The primary parameters to adjust in the Louvain algorithm implementation were the weights used in the objective function, controlling the balance between modularity and correlation in the produced subgraphs. A grid search was applied to a range of weights, the results of which are summarized in kL = 0.8, also has the lowest conductance at 0.94, while all other weights generate subgraphs with 0.99 conductance and <10 nodes. This also extends to the Correlated PageRank results, where much larger subgraphs result in significantly lower conductance. The size of subgraphs is likely the key contributing factor the high conductance; since the global network consists of many subgraphs, and connections within a small subgraphs are inherently limited, conductance may highlight weak inter-subgraph connections due to the sheer number of subgraphs in comparison to the small number of intra-subgraph connections. We don't believe this affects subgraph quality, as conductance is only used for comparison between methods and does not affect the algorithm's performance.Across all tests, we see alarmingly high conductance. However, we see an increase in conductance which correlates with the increase in network size; the largest subgraph, generated by The distribution of absolute correlations, shown in L = 0.8), which is also the partitioning which resulted in larger but less correlated top subgraphs. This is possibly due to the larger effect modularity has outcompeting correlation, resulting in merges which sometimes reduced correlation, but likely lead to a more interconnected subgraph.The Louvain algorithm, similarly to other hierarchical approaches, generates graph partitions at multiple levels, which each iteration of the two phases generating a new level in the hierarchy. While the final level should provide the optimal partitioning of the graph, and thus the best subgraphs, intermediate levels may be informative. To study the behavior of the algorithm, the correlation of all intermediate subgraphs that merged to form a subgraph in the final partitioning were plotted. Two examples are shown in *10−6 was used for all trials. Different weight values for the Correlated Louvain algorithm, kL, were tested.As we saw in both Correlated PageRank approaches, the teleportation factor has little effect on correlation, primarily affecting subgraph size. However, we see that for α values <0.04, the effects of teleportation have a less pronounced effect. As such, an α value of 0.04 was selected for these tests. Similarly, a tolerance factor of 1kL = 0.2, while also being larger than the sub-10-node subgraphs produced by the Correlated Louvain method. Unfortunately, there doesn't appear to be a pattern between weights and correlation, with both low and high kL values producing highly correlated subgraphs of similar size and conductance.A grid search technique similar to that used with the Correlated Louvain algorithm was used to test the effect of weight on the hybrid approach. The effect of different weights on the most correlated subgraph produced during the Correlated PageRank step is summarized in The hybrid approach terminates when the subgraphs produced by the Correlated PageRank step stop changing in size. However, the most correlated subgraphs were produced during intermediate steps. L = 0.8 which produced a more comparably sized subgraph while still maintaining a higher correlation.The hybrid approach appears to combine the best properties of both methods, and further improves on them. Correlation values are higher than those produced by the Correlated Louvain method, and similar to or better than those produced by the Correlated PageRank approach. Notably, correlation values produced by the hybrid approach are a significant improvement over those produced by the state of the art hierarchical approach, achieving a maximum |ρ| = 0.44, compared to the maximum |ρ| = 0.33 seen with hierarchical clustering, while maintaining a similarly sized subgraph. Subgraphs produced by this method are much smaller than those produced by the Correlated PageRank approach while not being as restricted in size as those produced by the Correlated Louvain method. They are similarly sized to those produced by the hierarchical approach and are an appropriate size for biological analysis.p = 1.22 * 10−29) was selected as the reference subgraph, and all other subgraphs were compared to it. To find unique subgraphs, the reference subgraph was compared to all other subgraphs, and the resulting Jaccard indices were ranked. High Jaccard indices indicates a subgraph highly similar to the reference subgraph, which was removed from later comparisons, while a sudden drop in Jaccard indices indicated the first significantly different subgraph, which was used as the next reference subgraph. This process was repeated until all top subgraphs exhausted; any subgraphs not considered highly similar to a reference node are sufficiently unique and can be used for further biological analysis.Using a pool of significant subgraphs identified by the Correlated PageRank approach, we applied our subgraph comparison approach to identify a set of unique subgraphs, which can be used for downstream analysis and applications. The subgraph with the highest correlation to the phenotype, seed node 175 with ρ = 0.35  and editing manuscript. YZ, KK, LL, RB, and FB-K provided suggestions for improving methodology, formalizing problem, editing manuscript, and evaluating results. WL provided and helped prepare dataset for example application (COPD). All authors contributed to the article and approved the submitted version.This work was supported by the National Institutes of Health (NIH), National Heart, Lung, and Blood Institute (NHLBI) R01 HL152735 and R01 HL137995. The COPDGene project described was supported by Award Number U01 HL089897 and Award Number U01 HL089856 from NHLBI. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NHLBI or the NIH.The content is solely the responsibility of the authors and does not necessarily represent the official views of the NHLBI or the NIH.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.