Charcotia amundseni and Eusirus giganteus. For the latter species, we have assembled two mitogenomes from different genetic clades of this species. The lengths of Eusirus and Charcotia mitogenomes range from 15,534 to 15,619 base pairs and their mitogenomes are composed of 13 protein coding genes, 22 transfer RNAs, 2 ribosomal RNAs, and 1 putative control region CR. Some tRNAs display aberrant structures suggesting that minimalization is also ongoing in amphipod mitogenomes. The novel mitogenomes of the two Antarctic species have features distinguishing them from other amphipod mitogenomes such as a lower AT-richness in the whole mitogenomes and a negative GC- skew in both strands of protein coding genes. The genetically most variable mitochondrial regions of amphipods are nad6 and atp8, while cox1 shows low nucleotide diversity among closely and more distantly related species. In comparison to the pancrustacean mitochondrial ground pattern, E. giganteus shows a translocation of the nad1 gene, while cytb and nad6 genes are translocated in C. amundseni. Phylogenetic analysis based on mitogenomes illustrates that Eusirus and Charcotia cluster together with other species belonging to the same amphipod superfamilies. In the absence of reference nuclear genomes, mitogenomes can be useful to develop markers for studying population genetics or evolutionary relationships at higher taxonomic levels.To date, only one mitogenome from an Antarctic amphipod has been published. Here, novel complete mitochondrial genomes (mitogenomes) of two morphospecies are assembled, namely,  Smith, 1874  for both Eusirus cf. giganteus clades and the Qiamp DNA Minikit  for Charcotia amundseni following the manufacturer’s protocol. DNA concentration and quality have been checked with a Nanodrop ND-1000 Spectrophotometer  and a Qubit 2.0 fluorometer .DNA has been extracted from a pleopod of each specimen using the DNeasy https://www.geneious.com) by merging paired reads, removing duplicates and trimming of low-quality ends using the BBDuk trimmer in Geneious with the minimum quality set to 20. These pre-processed reads have then been used for de novo assemblies in MITObim v1.9.1  which belongs to the same superfamily as Charcotia and a partial 16S to COI sequence of Eusirus perdentatus have been used as seed references. The longest resulting contigs from the de novo assembly have been imported into Geneious and further assembled with the ‘map to reference’ approach with medium–low sensitivity and 50 iterations. Identity of the resulting consensus sequences have been verified with BLAST searches . Such partial stop codons are atypical features of mitochondrial protein coding genes  using an Illumina HiSeq2500 sequencing platform in the 2 × 125 bp mode. Samples were indexed separately as unique libraries. Reads have been quality-checked using FASTQC Andrews  and pre- Cameron . Transfe Cameron  in the M Cameron . Potenti Cameron .Supplementary Table 1). Nucleotide diversity (π) has been computed for each protein coding gene with DnaSP v6.12.03  as they share the same ground pattern in terms of their mitochondrial gene order (Kilpert and Podsiadlowski https://www.geneious.com) and trimmed with Bioedit v7.2.5 , Eusirus cf. giganteus (G2), and Charcotia amundseni is 15,558, 15,534, and 15,619 bp, respectively  which is within the range of complete mitogenomes from other amphipods   strand and 14 on the negative (–) strand while 17 genes are encoded on the + strand and 20 on the – strand in C. amundseni . A putative control region (CR) has also be identified in all three mitogenomes and is located between trnS2 and rrnL in Eusirus and between trnF and nad5 in C. amundseni. The mitogenome also contains 20 intergenic regions for E. cf. giganteus and 18 intergenic regions for C. amundseni. The whole mitogenomes of the two species show AT-richness of 61.9% for E. cf. giganteus and 68.7% for C. amundseni, respectively, which contributes to the positive AT skew (0.008 to 0.092) and negative GC skew (−0.317 to −0.201) values observed in the three mitogenomes  . The thrnad1 gene in E. cf. giganteus is observed while cytb and nad6 are translocated in C. amundseni as compared to the pancrustacean ground pattern . We furthermore also find shifts in the position of tRNAs and the control region in E. cf. giganteus and C. amundseni as compared to the pancrustacean ground pattern . While also trnG has been translocated in the three species investigated here, we find other tRNA gene strings consisting of trnA, trnS1, trnR, trnN, and trnE for E. cf. giganteus and trnS1, trnN, trnE, and trnF for C. amunseni . Similar with the pancrustacean ground pattern, the trnV is located between the rrnL and rrnA genes in E. cf. giganteus while trnC and trnV are inserted between these genes in C. amundseni .A translocation of E. cf. giganteus and C. amundseni have undergone multiple transpositions and rearrangements relative to the pancrustacean ground pattern .Results of the CREx analyses indicate that E. cf. giganteus and C. amundseni is ATG (Supplementary Table 2). Defining the protein coding gene boundaries following a tRNA results in a few partial or incomplete stop codons (T or TA). The AT content of the protein coding genes of the three amphipod mitogenomes is estimated as 59.6% for E. cf. giganteus (G1 and G2) and 67.3% for C. amundseni (Supplementary Table 4). The highest AT content is found in the third codon position of C. amundseni and the second codon position of E. cf. giganteus while the lowest AT content is observed in the first codon position in all three species. (Supplementary Table 3).The most frequent start codon in rrnS and rrnL) genes in the three mitogenomes are located on the negative (−) strand. In the two Eusirus species, the length of both RNAs is 681 bp and 871 bp, respectively (Supplementary Table 2). Unlike in E. cf. giganteus, the two mitochondrial rRNAs of C. amundseni are shorter (529 bp and 739 bp) (Supplementary Table 2). The mitochondrial rRNA genes of the two amphipod species in this study also show a high AT content with 69.7% for E. cf. giganteus (G1 and G2) and 70.8% for C. amundseni.The two ribosomal RNA (Supplementary Table 2). The AT content of tRNAs of E. cf. giganteus is 66.2% and 69.9% for C. amundseni . More specifically, the DHU arm is missing in trnS1, trnS2 and trnV of E. cf. giganteus  and trnS1, trnS2, and trnI of C. amundseni . We also find that the TΨC loop is absent in trnK, trnD, trnN, trnM, trnS2, trnI, and trnQ of E. cf. giganteus  and in trnD, trnH, trnL1, trnC, trnV, trnQ, trnK, and trnM of C. amundseni .In the three mitogenomes of this study, 22 tRNAs are present with a length ranging from 52 to 67 base pairs , nad5 (0.012), and nad1 (0.011)  and low ones for nad4 (0.002), nad3 (0.003), nad2 (0.004), and cox1 (0.005) with nad4 (0.002) being the least variable. We also find high variability in nad6 (0.569), atp8 (0.566), and nad2 (0.515) between C. amundseni and E. cf. giganteus (G1) and low variability in cox1 (0.279), cytb (0.328), and cox3 (0.342) . Moreover, between C. amundseni and E. cf. giganteus (G2), high variability is observed in nad6 (0.567), atp8 (0.560), and nad2 (0.515), while the lowest variability is found in cox1 (0.28), cytb (0.327), and cox3 (0.343) .When estimating nucleotide diversity (π) between the two Eusirus cf. giganteus G1 and G2 under family Eusiridae, cluster together. They belong to the superfamily Eusiroidea and are found to be closely related to both Epimeria frankei Beermann & Raupach, 2018 in Beerman, Westbury, Hofreiter, Hilgers, Deister, Neumann & Raupach, 2018 and Epimeria cornigera Fabricius, 1779  from the Iphimedioidea Boeck, 1871 superfamily. Similarly, Charcotia amundseni from family Lysianassidae Dana, 1849 is clustering together with Eurythenes magellanicus H. Milne Edwards, 1848 and Eurythenes maldoror d'Udekem d'Acoz & Havermans, 2015 , Hirondellea gigas Birstein & Vinogradov, 1955 , and Onisimus nanseni G.O. Sars, 1900  and all belonging to the superfamily Lysianassoidea.Phylogenetic analysis revealed that the phylogenetic grouping follows the superfamily identity and fall under different family groups . The twoGondogeneia antarctica Chevreux Onisimus nanseni G.O. Sars, 1900 from the Arctic .In the current study, we have assembled and annotated novel complete mitogenomes from two Antarctic amphipod species with a low coverage skimming sequencing approach. We have obtained very low percentages of ambiguities (<0.01%) illustrating that this cost efficient approach is very successful. Besides our study, only two complete mitogenomes from amphipods of the polar regions are currently available, namely, from All three newly obtained mitogenomes are with 15,534 and 15,619 bp at the middle range of reported lengths of published amphipod mitogenomes   provides information to choose mitogenes as most suitable markers for future phylogenetic studies of amphipods. The novel mitogenomes are certainly useful for future phylogenetic analyses as put the investigated species into phylogenetic positions matching superfamily and family identity.The current study provides three additional novel complete mitogenomes of Antarctic amphipod species and the first complete mitogenomes of the abundant amphipod genera Click here for additional data file.


Background: As the prevalence of obesity increases globally, appreciating the effect of donor and recipient (DR) obesity on graft outcomes is of increasing importance.Methods: In a cohort of adult, kidney transplant recipients (2000–2017) identified using the SRTR, we used Cox proportional hazards models to examine the association between DR obesity pairing (body mass index (BMI) >30 kg/m2), and death-censored graft loss (DCGL) or all-cause graft loss, and logistic regression to examine risk of delayed graft function (DGF) and ≤30 days graft loss. We also explored the association of DR weight mismatch  and <10 kg (D = R)) with each outcome, stratifying by DR obesity pairing.Results: Relative to non-obese DR, obese DR were highest risk for all outcomes . Donor obesity modified the risk of recipient obesity and DCGL [p = 0.001] and all-cause graft loss [p < 0.001] but not DGF or early graft loss. The known association of DR weight mismatch with DCGL was attenuated when either the donor or recipient was obese.Conclusion: DR obesity status impacts early and late post-transplant outcomes.  We also explored whether DR obesity status modifies the known relationship between DR weight mismatch and graft outcomes after kidney transplantation.In this study, we aimed to describe the changing prevalence of donor and recipient obesity at the time of transplantation and explore whether 2 were excluded, as these were assumed to represent coding errors.We conducted a retrospective cohort study of adult patients who received a first living or deceased donor kidney transplant in the United States (US) between 1 January 2000, and 31 December 2016, identified using the Scientific Registry of Transplant Recipients (SRTR) database. Exclusion criteria included those <18 years of age, those receiving a second transplant, or those missing either donor or recipient data for weight or body mass index (BMI). Donors and recipients with BMI values <10 and >100 kg/m2 versus ≤30 kg/m2 according to standard guidelines  and <10 kg (D = R) as per previous literature , stratifThe primary outcome was death-censored graft loss (DCGL). Graft loss was defined as need for return to chronic dialysis or repeat transplantation. Secondary outcomes included the composite of graft failure or death , delayed graft function (DGF), defined as need for dialysis within the first 7 days following transplantation, and early (≤30 days) graft loss. Censoring occurred at losses to follow-up and at the date of last follow-up.a priori. For the primary analysis, missing data was treated by case wise deletion.We adjusted for known literature predictors of graft loss including donor and recipient age, race, and sex, recipient end-stage kidney disease (ESKD) cause, dialysis vintage, pre-emptive status, cold-ischemia time (CIT), previous kidney transplant, human leukocyte antigen (HLA) mismatch (MM), peak panel reactive antibody (PRA), and recipient medical comorbidities including type 2 diabetes, hypertension, coronary artery disease and peripheral vascular disease. These co-variates were selected The SRTR data system includes data on all donor, wait-listed candidates, and transplant recipients in the US, submitted by the members of the Organ Procurement and Transplantation Network (OPTN). The Health Resources and Services Administration (HRSA), US Department of Health and Human Services provides oversight to the activities of the OPTN and SRTR contractors.Descriptive statistics were reported for baseline characteristics. Means and standard deviations and medians and interquartile range were used for continuous normal and continuous non-normally distributed variables. Baseline donor and recipient characteristics were reported for all patients in each of the DR obesity pairing groups.We examined temporal trends in the incidence of each DR obesity pairing at the time of transplantation over the study period.For the outcome of DCGL, we used a multivariable Cox proportional hazards model to determine the adjusted hazard ratio (HR) for DCGL for each DR obesity pairing , relative to NOD-NOR. Time to DCGL was demonstrated visually using Kaplan Meier survival curves. Proportionality was confirmed with visual examination of log-log plots.In a secondary analysis, we used a multivariable Cox proportional hazards model to determine the adjusted HR for all-cause graft failure for each DR obesity pairing , relative to NOD-NOR. Multivariable logistic regression was used to determine the adjusted odds ratio (OR) for the outcomes of DGF and early (≤30 days) graft loss associated with each DR obesity pairing relative to NOD-NOR. Finally, we determined if donor obesity modified the association of recipient obesity with each of DCGL, all-cause graft loss, DGF and early graft loss, by including an interaction term between donor and recipient obesity status in each regression model.For the outcome of DCGL, we used multivariable Cox proportional hazards models to determine the adjusted relative hazard ratio (HR) for each DR weight mismatch category relative to weight-matched DR (<10 kg absolute weight difference), stratified by DR obesity status. Weight-matched NOD-NOR was the reference category for all comparisons, irrespective of DR obesity status. Proportionality was confirmed with visual examination of log-log plots.We repeated the above analysis examining DR weight mismatch stratified by DR obesity status to examine the outcome of all-cause graft loss. We also examined the effect of combined DR obesity and weight mismatch on DGF and early graft loss, using multivariable logistic regression, adjusting for the same factors listed above.(i) Adjusting for era effect for the outcome of DCGL.(ii) Excluding donors and recipients with a BMI <18 for early and late graft outcomes.. donation after neurologic death (DND) status for the outcome of DCGL in deceased donor transplant recipients.(iii) Adjusting for donation after circulatory death (DCD) vs(iv) Adjusting for donor kidney side (right vs. left) for early and late outcomes.We repeated our primary analysis (DR obesity pairing) for the following:(i) Combined DR weight mismatch and obesity status using a reference category of weight-matched DR (D = R) within each DR obesity pairing (as opposed to D = R NOD-NOR).(ii) Combined DR weight mismatch and obesity status separately in living donors and deceased donors.(iii) Using DR height mismatch instead of weight mismatch. For this analysis, we categorized DR absolute height difference as >15 cm, 5-15 cm  and <5 cm (D = R), as per previous literature . A <5 cm2 and >40 kg/m2) to define DR obesity status; the reference category was patients with a BMI of 18–25 kg/m2.(iv) Using higher BMI cut points  for:p < 0.05 was deemed the threshold for statistical significance.Ethics approval for this study was provided through the Nova Scotia Health Research Ethics Board. All statistical analyses were performed using Stata version 13.1 . For statistical comparisons, a 2 and 27.7 ± 5.6 kg/m2, respectively, with 40.0% and 49.7% of donors and recipients noted to be obese, respectively. Median absolute DR weight difference was −2.10 kg (Q1-Q3 −19.26 to 14.80 kg); recipients being slightly larger than donors. Overall, DCGL occurred in 30,132 patients (12.6%), all-cause graft loss in 82,372 (34.9%), DGF in 83,374 (18.1%) and early graft loss in 4778 (2%). Median follow-up time was 4.15 years (Q1–Q3 1.97–7.71 years).Our final study cohort consisted of 238,895 kidney transplant recipients . BaselinThere was a decrease in the incidence of NOD-NOR from 62% to 45% over time . Of the Examining the effect of DR obesity status on DCGL (relative to NOD-NOR), the adjusted relative hazard was highest in the OD-OR pairing , Combined donor and recipient obesity (OD-OR) was also associated with the highest risk for all-cause graft loss, DGF and early graft loss, p = 0.001) and all-cause graft loss (p < 0.001), while no interaction was observed between donor and recipient obesity for DGF (p = 0.559) or early graft loss (p = 0.208).Donor obesity modified the risk of recipient obesity on both DCGL  and 30 kg  were protective against DCGL and D<R by 10–30 kg  and 30 kg  were risk factors for DCGL versus no weight difference, Amongst NOD-NOR, D>R was not protective against all-cause graft loss, but a larger recipient than donor was significantly higher risk than no weight difference, Amongst NOD-NOR, a 30 kg difference between donor and recipient (D<R) was the highest risk for DGF  relative to no weight mismatch, Results for early graft loss are shown in When we repeated the primary analysis adjusting for transplant era, we found that the effects of DR obesity persisted and were similar to those seen in our primary analysis. The adjusted relative hazard was highest in the OD-OR pairing , followed by NOD-OR . OD-NOR pairing was not associated with risk of DCGL.When we repeated the primary analysis excluding donors and recipients with BMI <18, the same trends were observed for both early and late outcomes .. DND status in deceased donor transplant recipients, we found no significant association between DCD status and risk of DCGL .When we repeated our primary analysis adjusting for DCD vsWhen we repeated our primary analysis adjusting for transplant kidney side, we found no significant association between right-sided donor transplants and risk of DCGL  or all-cause graft loss . A significant association was found between right-sided donor transplants and both DGF  and early graft loss .When we used a weight matched reference category within each DR obesity pairing , overall D>R was protective against DCGL and D<R was a risk for DCGL, Amongst the entire cohort, risk of DCGL increased as recipient height increased relative to donor, though not all results reached statistical significance . A donorThere was a trend towards increased risk of DCGL as the recipient-to-donor weight increased in most DR obesity pairings, though results did not always reach statistical significance . This an2  and >40 kg/m2  cut-offs, followed by NOD-OR . OD-NOR was not significantly associated with DCGL for either BMI cut-offs, (data not shown). Sample sizes were small in the OD-OR subgroup at BMI 40 kg/m2 (n = 203).Relative to NOD-NOR, risk of DCGL was highest for OD-OR using both >35 kg/mIn this study, we describe the changing demographics of obesity at the time of kidney transplantation and explore how DR obesity pairing impacts early and late graft outcomes. We also investigate whether obesity status modifies the known relationship between DR weight mismatch and graft outcomes after kidney transplantation.Previous studies have found a significant increase in the prevalence of overweight and obese recipients at time of transplantation , 16. We When examining the effect of DR obesity pairing on late graft outcomes, OD-OR and NOD-OR were both associated with risk of DCGL and all-cause graft loss; OD-OR was highest risk for both outcomes. Isolated recipient obesity has been linked to a multitude of adverse graft outcomes, including DCGL , 25, 26 Notably, risk of DCGL was more exaggerated than that of all-cause graft loss in both NOD-OR and OD-OR. This finding is in keeping with other studies which have shown a comparable mortality risk between obese recipients and those with a normal BMI , 6, 12. We found an increased risk of DGF when either the donor or recipient was obese, with the risk greatest in OD-OR. This is in agreement with previous retrospective studies which have separately correlated recipient and donor BMI with incidence of DGF , 13, 14.Our analysis demonstrates an attenuation of the protective effects of a larger donor than recipient , 24, 55 2 (Interpretation of the findings regarding obesity and graft outcomes requires caution. Although this study demonstrates the potential detriments of donor and recipient obesity on outcomes following transplantation, we do not suggest discard of obese donor kidneys or that obese recipients be declined access to transplantation. Evidence suggests that in most cases, kidney transplantation in obese patients affords better survival than remaining on dialysis . Glanton2 . Our stuWhile likely of benefit, there are insufficient data to assess the impact of pre-transplant interventions, such as planned weight reduction strategies, among potential recipients. The role of bariatric surgery in the dialysis population and transplant candidates is becoming an increasingly salient issue, with many studies showing promising results , 63, 64.2 as defined by earlier literature (2 limited the available sample sizes and the validity of the results. Additionally, we could not access any histologic parameters of the allograft such as implantation biopsy, percentage of global glomerulosclerosis, or health of the tubulointerstitium, which could provide important insights on histopathologic changes related to obesity. A prospective study at an appropriate center could allow for exploration of implantation biopsies at the time of organ retrieval. Moreover, immunosuppressive data including details regarding changes over time, are not robustly captured by the SRTR and were therefore not included in our multivariable models. Finally, we could not access specific causes of graft loss; these may have provided pathophysiologic explanations as to how DR obesity status influences early and late graft loss. As such, we could not establish the relative impact of specific factors for a given recipient on graft loss. We also could not access donors’ cause of death as this is not reliably reported in the SRTR.There are several limitations to our study for consideration. First, while BMI is often used as a surrogate marker of obesity and suitability for kidney transplantation, some studies have shown waist-to-hip ratio and waist circumference to be stronger predictors of cardiovascular death than BMI . Waist cterature . IdeallyIn summary, we report an increased proportion of obese donors and recipients between 2000 and 2017, with the greatest relative increase in OD-OR followed by NOD-OR. We demonstrate the combined exposure of an obese donor and obese recipient to be associated with the greatest risk of short and long-term complications after transplant. Finally, we demonstrate that donor and/or recipient obesity attenuates the protective signal typically seen in the setting of a larger donor-to-recipient size. Our findings highlight the importance of informed consent procedures for obese donors and transplant candidates. Further, our data indicate that obesity status should be considered when considering the implications of DR weight matching.


The quality standards for the export of chestnuts generate large quantities of rejected fruits, which require novel processing technologies for their safe industrial utilization. This study aimed to investigate the impact of high-pressure processing (HPP) and hydrothermal treatments (HT) on the physicochemical properties of rejected chestnut starch. Chestnuts were treated by HPP at 400, 500, and 600 MPa for 5 min and HT at 50 °C for 45 min. In general, all HPP treatments did not induce starch gelatinization, and their granules preserved the integrity and Maltese-cross. Moreover, starch granules’ size and resistant starch content increased with the intensity of pressure. Native and HT chestnut starches were the most susceptible to digestion. HPP treatments did not affect the C-type crystalline pattern of native starch, but the crystalline region was gradually modified to become amorphous. HPP-600 MPa treated starch showed modified pasting properties and exhibited the highest values of peak viscosity. This study demonstrates for the first time that after HPP-600 MPa treatment, a novel chestnut starch gel structure is obtained. Moreover, HPP treatments could increase the slow-digesting starch, which benefits the development of healthier products. HPP can be considered an interesting technology to obtain added-value starch from rejected chestnut fruits. Starch is a carbohydrate composed of two polysaccharides, amylose, and amylopectin, which are its principal components (≈99%) in dry weight. This plant-based ingredient is presented in the form of granules of different sizes, shapes, and diameters, depending on the botanical origin and source. In the European Union (EU), starch comes primarily from processing cereals and tubers such as wheat, maize, and potatoes . NonetheThe chestnut fruit is one of the EU’s most important tree nut crops. According to the official data , the aveChestnut kernel is rich in carbohydrates, namely in starch, which accounts for more than 60% of its dry weight , a valueThermal treatments are conventionally used to physically modify starch by applying temperatures from 50 to 140 °C and processing times between 15 and 960 min. Under these treatment conditions, rice, chestnut, pea, lentil, cowpea, and Dioscorea starches and gels undergo irreversible gelatinization viscosity, strength, and hardness changes, and their crystal structure is lost without destroying the granular structure while modifying starches’ thermal and functional properties ,12. TherRecently, several thermal and nonthermal innovative methods, such as infrared and microwave radiations , ultrasoHigh-pressure processing (HPP) is a nonthermal processing technology that has been used to study the modification of native starch properties from different food matrices, such as lentil, pea, quinoa, maize, and potato, by applying pressures from 100 to 600 MPa and processing times from 2 to 30 min ,15,16. TIn this context, this work aimed to study the impact of HPP at 400, 500, and 600 MPa on the starch from rejected chestnuts by evaluating their physical, chemical, thermal, mechanical, rheological, morphological, and structural properties.The XRD patterns of the chestnut starches are presented in FTIR spectra of native and modified chestnut starches showed a characteristic carbohydrate pattern . The absThe frequency sweeps  allowed On the other hand, the pasting profiles of treated starch showed different behaviors when compared to each other and with the native starch C. The naRegarding HPP treatments, the increase in pressure level led to additional modifications in starches’ pasting properties, setback, and breakdown viscosity . The maxHPP-600 MPa treated samples had the highest values of peak viscosity, trough viscosity, final viscosity, setback, and breakdown. The higher pressure of this treatment could force the entrance of free water into the starch granules since, as seen in the SEM images see , they inOn the other hand, breakdown increased significantly when the pressure increased from 400 to 600 MPa, showing that 600 MPa-treated starch pastes are highly susceptible to disintegration during the heating process, probably due to the formation of weaker structures. This parameter can be used to identify the stability of starch gels against shearing and high temperatures after gelatinization . The groRegarding the setback, this parameter increased significantly when the pressure increased from 400 to 600 MPa, revealing that pressure-treated starch pastes had a higher retrogradation tendency ,20. StarStarch fractions, RDS, SDS, TDS, and RS, of native and treated chestnut starches samples are shown in As shown in The increase of RS after HPP at 600 MPa  was alsoThe changes in birefringence of native and treated starch are shown in 32) between native and treated starch granules.On the other hand, no significant modifications were also observed in the chemical characterization of the starch samples, as the X-ray spectrometer (EDS) test gives average carbon and oxygen contents of 74.6 ± 1.0% and 25.4 ± 1.8%, respectively. Relatively to morphological changes of starch granules induced by the processing technologies, modifications after HT and HPP treatments were not found. Nonetheless, the results revealed significant differences in size and volume-surface diameter (d32) of the native samples registered a value of 5.9 ± 0.3 μm, with 80% of the population having 1.5 to 6.0 μm  previously reported also for chestnut starch [Thermal transition parameters showed significant differences in some parameters among the different treatments . DSC thet starch . On the t starch  when comIn the HPP treatments, both onset and gelatinization peak temperature values showed a decrease of about 1.3% and 1.0%, respectively compared to the native starch sample. Regarding the enthalpies (ΔH), the HPP and native starch samples presented similar values. However, the gelatinization peaks obtained in this study were lower than the obtained (68.0 °C) in  for HPP-The TGA parameters showed significant differences in all treatments, except for the mass loss at the second decomposition stage . The theThe most substantial mass losses occurred during the second step at approximately 277–298 °C, reaching a maximum decomposition temperature of 317.5 °C. This step could be attributed to the depolymerization and decomposition of starch, as it produced mass losses of around 65.0% in all treatments. These changes may result from some physicochemical modifications induced by the HPP treatments in starch samples. Nonetheless, these results also provide evidence that native and treated starches could withstand high process temperatures, suggesting their versatility to be used in the food industry. Finally, the third thermal step started at approximately 450 °C, with around 24.5% of the native and treated starch samples remaining undegraded as a charred residue. Similarly, the char residue of chestnut samples when heated over 400 °C was 30.9% in [The typical stress-strain curves obtained from the uniaxial compression measurements  show a uRelatively to the changes induced by the processing technologies, a significant decrease was observed in stress and strain at rupture after HT and HPP treatments . After tCastanea sativa Mill.) were obtained from an industrial unit in Portugal. Chestnuts were packed in net bags by the wholesaler and transported fresh to the laboratory, where they were immediately prepared for analysis.The rejected chestnut fruits of the variety “Martaínha” .The HPP treatments were conducted in a 55 L high-pressure pilot unit . Water was used to pressurize samples at a rate of 3 MPa sBefore and immediately after each treatment, two kg of chestnuts was randomly taken from each batch. Next, the chestnut fruits were peeled, the inner skin was removed, and the peeled kernels were cut into small pieces and ground, frozen at −80 °C for 24 h , and freeze-dried at −50 °C in a vacuum chamber for 48 h . Then, the freeze-dried samples were placed in a desiccator containing silica gel (~0% RH) for 6 h. Finally, the freeze-dried chestnuts were pulverized using a grinder  and were sifted to obtain a 40-mesh powder.g for 20 min at room temperature. After that, the supernatant was discarded, and the pellets were resuspended in 200 mL of distilled water. Finally, the slurry was again centrifuged, and the grey upper layer (containing fibers and proteins) was removed manually with a spatula. This last step was repeated 4 times to guarantee the total elimination of the grey layer.Starch was isolated from chestnut flours by the aqueous solution method described previously  with somv/v), filtered with a Whatman N° 5 filter paper, and dried in an oven  at 40 ± 0.2 °C for 15 h. The starch samples were ground using a grinder , screened through a 100-mesh sieve, and stored at room temperature in sealed and dried polyethylene bags for further analysis. The native starch and HT starch samples were analyzed and compared with samples subjected to HPP treatments.Finally, the starch was resuspended in 100 mL of ethanol at 99.5%  using a D8 Discover diffractometer  with Cu tube (λ = 1.5406 Å). The radiation was generated at 40 mA and 40 kV, as previously reported . The sca−1 at a resolution of 4 cm−1 and 24 scans per sample, as described [The chemical groups and bonding arrangement of constituents were determined by Fourier-transform infrared spectroscopy (FTIR) using a Bruker Alpha II FTIR spectrometer equipped with a diamond attenuated total internal reflectance (ATR). The measurements were recorded over 4000–400 cmescribed . This anPasting measurements were performed in an HR-1 rheometer  equipped with a Peltier plate  as described by Gómez et al. . Five grThe viscoelastic properties were evaluated by dynamic oscillatory measurements. Non-isothermal and frequency sweep analyses were carried out within the linear viscoelastic domain obtained from strain sweep (1% deformation—data not shown). The slurries were submitted to the same conditions used to evaluate the pasting behavior. Frequency sweeps were evaluated between 0.1 and 10 Hz. The elastic moduli (G’), viscous moduli (G”), complex moduli (G*) and tan δ were estimated.Differential Scanning Calorimeter (DSC) was conducted in an equipment DSC 6000 , and thermogravimetric analyses (TGA) were performed with an equipment TGA 4000  as described previously .csH and ΔpsH are the gelatinization enthalpies of native starch and pressurized starch, respectively.The degree of gelatinization (% G) was calculated using the following Equation (1), previously reported in .(1)% G=Starch dispersions (50 mg/mL) in distilled water were prepared. One drop sample (25 μL) was taken for microstructural analysis by polarized light microscope (PLM). For observing starch granules’ birefringence in the form of Maltese crosses, micrographs were captured at room temperature with a Nikon Instruments Wide-Field Upright Ni-E Microscope  equipped with a digital camera using a 50× objective, a polarizer, and a NIS-Elements Microscope Imaging Software. In addition, micrographs and the elemental composition of the starches were obtained using a desktop scanning electron microscope (SEM) coupled to a dispersive energy X-ray spectrometer (EDS)  as described previously .32) described in Equation (2).in is the number of particles with diameter id.The diameter and size of starch granules analysis were performed by measuring at least 300 granules in SEM micrographs using ImageJ software (v.1.46r for Windows). Measurements were used to calculate the mean diameter and particle size distribution to show frequency histograms. The average size was calculated considering the specific surface per unit volume (dThe simulated in vitro chestnut starch digestion assay was carried out using the digestible and resistant starch assay kit (K-DSTRS—Megazyme), as previously described . RapidlyStarch gels prepared by gelatinization of a 10% starch suspension in water at 95 °C for 30 min and stored for 24 h at 4 °C were used for mechanical analysis by uniaxial compression according to the method described previously  with somThe results were compared by analysis of variance (ANOVA) and Tukey’s test at a significance level of 5% using GraphPad Prism v6. Ink software. The data reported are expressed as the average of triplicate observations ± SD.HPP can be a helpful method to induce desirable modifications on the structural, granule size, pasting, thermal, mechanical, and color characteristics of chestnut starch. The HPP process is considered safe since it does not form toxic by-products. HPP-600 MPa treated starch can be used in products that require higher pasting properties and swelling power, setback, and breakdown viscosity, as well as gel structures with weaker and rapidly brittle tendencies. Nonetheless, HPP treatments used did not induce starch gelatinization. Chestnut starches may be used as an ingredient for food applications that require industrial processing at intermediate temperatures, such as those used in sterilization, pasteurization, and cooking methods. From a technological point of view, it was demonstrated here that HPP could be used to change chestnut starch characteristics and obtain ingredients with modified thermal and rheological properties that the food industry can use to develop products with novel textures and structures.


In comparison to alone corn starch and a combination of Arabic gum, thermal-ultrasound treatment increased the swelling power and solubility of samples. Treatment significantly (p < 0.05) decreased the syneresis of treated starch gels, especially at a temperature of < 45 °C, but paste clarity was increased at the higher temperature (65 °C). The enthalpy of treated samples was in the range 15.20–16.37 J/g. Sonication at 65 °C for 60 min had the most destructive effect on corn starch granules, but at 30 min granules were swollen only. FT-IR spectra of samples confirmed the physical modification of thermal-ultrasound treatment. The relative crystallinity index of samples changed in the range 21.88–35.42% and decreased with rising time and temperature. Sonication at 45 °C for 30 and 60 min produced starch-gum mixtures with different pasting properties. Thermal-ultrasound treatment in presence of gum can be a viable technique to modify starches with different functionality.This research extends the effects of a thermal-ultrasound treatment  on the physicochemical, structural, and pasting properties of corn starch in presence of Arabic gum. Treated samples had lower leached amylose compared with corn starch, but it was non-significant ( Native starch is usually modified chemically, enzymatically, genetically, and physically to develop starch-based food products. Nowadays, physical modifications are gaining importance in food industries due to the limited use of chemical agents, less processing time, and environment-friendly processing2.Starch is an abundant, low price, and natural hydrocolloid that possesses wide applications in food science; but due to the drawbacks of native starch causes limited use in some food applications4. Ultrasonication locally creates strong shear force, high temperature, and free radicals which change the structure and properties of starch. The extent of changes depends on the frequency and intensity of ultrasound, time, temperature, and moisture of the system, as well as the starch origin. In addition, ultrasound had been connected to the emerging concept of “green chemistry and technology” for environmentally friendly applications5.Ultrasound is one of the physical methods for the modification of starch. The use of ultrasound to modify the starch's functionality has increased in the last decades6. When both heat and ultrasound waves act simultaneously, high sensitivity on microbial cell walls occurs, causing damage to the cell structure, as a consequence of the called "additive effect". Thermosonication or thermal-ultrasound treatments are the terms that are usually applied to this technique7. In the previous work, we studied the effect of thermal-ultrasound treatment on the physicochemical and rheological properties of corn starch. Results showed that thermal ultrasound is a viable technique for starch modification compared to conventional thermal and ultrasound treatments4.Thermal treatment offers the potential to change starch functionality at a low-cost method. Pregelatinized starches are widely used for many foods as a major ingredient to provide thickening texture at temperatures below the gelatinization temperature8. Arabic gum is generally used as an emulsifier/or stabilizer in food systems. It is a weak polyelectrolyte that transfers carboxyl groups and can be applied as a dietary fiber. Due to the well-known structure of Arabic gum and the numerous researches about the effect of its in-model systems, this gum was selected.On the other hand, the engineered selection of hydrocolloids in starch-based products could be influenced by the physicochemical and rheological properties of starch. Hydrocolloids are often modified the functional properties of starch to overcome undesirable changes in food products during processing (such as breakdown of viscosity after shearing) and self-life (such as retrogradation) without chemical modification. Usually, if the starch was applied with a small content of hydrocolloids in food formulation, the desirable quality, and textural characteristics may be obtained that do not generally exhibit ideal functional properties for the preparation of food products9. Therefore, this study aimed to investigate the effect of thermal-ultrasound treatment in the combination of Arabic gum on the amylose content, swelling power and solubility, syneresis, paste clarity, differential scanning calorimetry, Fourier transform infrared spectra (FT-IR), scanning electron microscopy (SEM), X-ray diffraction (XRD), and pasting characteristics of corn starch.Today, dual modification of starch has been most attractive, because often the use of a single modification method is not complete and effective to improve the application and processing characteristics of native starchesThe leached amylose plays an important role in the further gelation and retrogradation of the starch paste. The amount of leached amylose was measured for treated samples, and the results are presented in Table p > 0.05). Arabic gum may be inhibited the leaching of amylose by the coverage of the granule's surface. This phenomenon was consistent with the previous results reported by Sheng et al.10 for tapioca starch-pullulan mixtures and Zhang et al.11 for corn starch and Arabic gum systems. Some researchers reported that the amount of leached starch polymer was significantly lower owing to the increased viscosity of the continuous phase by the presence of hydrocolloids, which prevent the diffusion of starch polymer from starch granules12. These findings were not confirmed for corn starch and Arabic gum mixtures due to lower viscosity of the gum in comparison to other gums such as xanthan and guar gums.It was observed that the amylose content of corn starch was 22.92 ± 0.25%. Primarily, Arabic gum (S-G) slightly decreased the leached amylose from corn starch (S); but this effect was non-significant (p < 0.05). Based on previous reports by Chan et al.13 and Falsafi et al.14, leached amylose increased after sonication which might be due to the amylose and amylopectin chain cleavages. In contrast, in this study, the amylose content of treated samples was decreased in presence of Arabic gum. This reduced trend could be discussed by starch molecules and Arabic gum interactions. Generally, leached amylose increased with increasing temperature from 25 to 65 °C. But the time of ultrasound had an unclear trend. Except for S-G4560, other sonicated samples showed non-significant differences at 0.05 (p > 0.05) compared with corn starch (S). The S-G4530 sample had higher leached amylose than the S-G sample. This phenomenon might be related to the cleavage of amylopectin and long amylose chains that increase the mobility of molecules for the reaction with iodine. In the case of S-G4560, it should be noted that starch molecules' interactions may be reduced by spectrophotometric measurement values. It should be noted that the lower leached amylose content can be modified by the other functional properties that require doing other tests.Results showed that treated samples (except S-G4530) had lower leached amylose compared with corn starch (S); but it was non-significant  during storage at 4 °C for 2 and 7 days Table .p < 0.05) decreased the syneresis of treated gels especially S-G2560 and S-G4530 samples compared with S and S-G. But retrogradation in these samples was observed after 7 days at 4 °C. The retrogradation properties of starches are indirectly influenced by the structural arrangement of starch chains within the amorphous and crystalline regions of the ungelatinized granule, which in turn, influence the extent of granule breakdown during gelatinization and the interactions that occur between starch chains during gel storage1. Thus, sonication at 25 °C for 30 min and 45 °C for 60 min and at a higher temperature of 45 °C resulted in increased syneresis and retrogradation tendency. This result may be to the appropriate conditions of corn starch and Arabic gum mixtures (S-G2560 and S-G4530) after sonication that inhibited retrogradation. Because at 25 °C for 30 min, ultrasound was not changed considerably structure of the S-G sample, moreover at 65 °C also due to the decrease in ultrasound effects with increasing temperature occurred similar phenomenon. As the high temperature in a compressed cavitation bubble was not a prerequisite for producing strong shear forces in the vicinity of the bubble. Increasing the reaction temperature allowed cavitation to be achieved at lower acoustic intensity. This was a direct consequence of the rising vapor pressure associated with the liquid heated15. At 65 °C, the normal gelatinization of corn starch achieved the leakage of starch molecules to the medium and caused retrogradation during storage. The results imply that the amount of amylose and amylopectin in starch gels is the main factor that plays a vital role in influencing the retrogradation properties. It should be noted that the effect of Arabic gum on the deterioration of starch molecular interactions also has been considered.The syneresis of all samples (except S and S-G samples) increased with increasing the time of storage to 7 days. The S and S-G samples showed lower syneresis during storage; but at the first, showed higher values. Ultrasonication significantly  by Arabic gum (0.25%) in S-G mixtures  and decreasing the starch content in all samples, caused lower water holding capacity that resulted in increasing syneresis in all S-G mixtures with and without treatment.Paste clarity is one of the most main functional characteristics of starch in food systems. Thus, the absorbance of the starch pastes for 2 and 7 days at 4 °C was measured. The results of the paste clarity of treated samples were reported in Table p > 0.05). Amini et al.16 reported that ultrasonication at temperatures below 45 °C decreased slightly the paste clarity; a profound increase was observed at the higher temperatures. They found that the sonicated samples were more transparent than the non-sonicated ones16. However, this statement was not in agreement with the result of this study and may be related to the existence of Arabic gum and biopolymer interactions between starch molecules and Arabic gum which can induce a higher level of light absorption. Increased solubility and decreased amount of starch granules (swollen form) resulted in higher clarity. So, the disintegration of corn starch granules at 65 °C may occur. But in some cases, the higher solubility of starch pastes by amylose and amylopectin chains caused the higher retrogradation during storage. Although, the electrostatic interaction of starch molecules with Arabic gum that forms interpolymeric complexes resulted in increased turbidity during storage.For the first time, paste clarity increased only at 65 °C for 30 and 60 min (decreasing absorbance). The effect of ultrasound was lower at a temperature lower than 45 °C .Although, other researchers also reported that the increasing clarity of oat starch paste after an ultrasound resulted in the increased solubility of starch and the decreased amount of starch granules remnants18. The swelling power and solubility of samples were reported in Table p < 0.05). The swelling power of thermal-ultrasound-treated samples significantly (p < 0.05) increased with increasing time and temperature of ultrasound. S-G6560 showed the highest value (34.02 ± 0.80%) at 85 °C. It has been reported that the increased swelling power is affected by ultrasound due to the breakdown of intermolecular bonds and starch granule aggregates, changes in the crystalline structure, and bonding of water molecules21.The swelling power and solubility are the main parameters that provide information on the quantity of biopolymer chain interactions in starch granules due to the amorphous and crystalline regions. The swelling power is well-defined as the capacity of molecules to hold water in the starch network by hydrogen bonds. In general, the rheological properties of starch are significantly affected by the swelling power and solubility of starchIn the case of solubility, the results showed a similar trend compared to swelling power reports. Ultrasound increased the solubility of samples and its effect was higher at 85 °C than at 25 °C. The solubility of S-G samples at 25 °C was 1.25 ± 0.34% and increased to 15.48 ± 0.76% after heating. This value was 1.41 ± 0.07% for S-G2560, and then significantly increased to 21.92 ± 1.24%. Therefore, thermal-ultrasound-treated corn starch and Arabic gum mixture at 25 °C for 60 min could be increased the solubility of the mixture by approximately 25% higher than one at 85. This effect was increased at the high temperature and time of the ultrasound. For example; S-G6560 showed a solubility of 37.43 ± 0.82% at 85 °C. This value increased by over 200% in comparison to the S-G sample. Although, it should be noted that the solubility of S and S-G samples at higher temperatures were 17.57 ± 0.75 and 15.48 ± 0.76%, respectively..16 found that the solubility index of alone corn starch sharply increased (about twofold and more) after ultrasonication at 65 °C, but there was no difference between the solubility of samples measured at 25 and 45 °C. Generally, the increased solubility of samples is attributed to the amylose-associated leakage outside the granules22. The amylose content results showed no significant between thermal-ultrasound treated samples and S-G, but the solubility of samples was significant at p < 0.05. On the other side, it is reported that the increased surface area of granules due to the pores and channels after ultrasound permits water molecules to diffuse more easily into the granules and results in the solubility increasing23. In the corn starch and Arabic gum mixtures, the electrostatic interaction of two biopolymers after treatment can influence this property. Therefore, corn starch and Arabic gum mixtures rearranged after thermal-ultrasound treatment and produced a new complex with higher solubility and swelling power properties.Amini et alIn comparison to S and S-G samples, Arabic gum might be decreased or increased the solubility and swelling power of corn starch. Results showed that these values of samples decreased in presence of Arabic gum which may be related to the substitution of gum with 0.25% of corn starch. Because the water-holding capacity of Arabic gum is lower than corn starch. But in a mixture of corn starch and Arabic gum after the ultrasound, the attracted results were calculated. Although, Arabic gum without treatment decreased the solubility and swelling power of corn starch at the higher temperature (85 °C). But this value was increased after thermal-ultrasound in all samples, especially in S-G6560 after heating at the elevated temperature. The different behavior of swelling power and solubility of S-G4560 sample may be related to the increased interactions involving amylose-amylose and amylose-amylopectin chains.Based on the ultrasound effect and temperature on corn starch and their effect on the Arabic gum structure and their biopolymer interaction, this treatment could be designed as a corn starch-Arabic gum mixture with higher swelling power.DSC results of thermal-ultrasound-treated starches are summarized in Table In the case of the treated sample, To, Tp, and ΔH were changed at 66.0–72.3 °C, 77.0–87.7 °C, and 15.20–18.13 J/g, respectively. Generally, To and Tp were increased, but ΔH decreased after thermal-ultrasound treatment, especially at the higher temperature (65 °C). The higher To, Tp, and ΔH values were related to the S-G6560, S-G4660, and S-G2560 samples, respectively. It may be concluded that ultrasound disorganized the structure of corn starch granules, but Arabic gum delayed the gelatinization by the coverage of the granule's surface. The results showed that the onset and peak temperatures were slightly shifted towards higher values for sonicated samples compared with control, except for the sample sonicated at 65 °C. But the sample sonicated at 65 °C had lower ΔH values compared with the non-sonicated one. The organization of the amylose and amylopectin components of starch plays an important role in the gelatinization of starches treated by ultrasound.14.Ultrasound waves induced a rearrangement of the molecular packing within the granule microstructure. A decrease in the enthalpy of sonicated oat starch was reported by Falsafi et al.The morphology of treated samples is studied by SEM microscopic observation Fig. . Based o4.At the higher temperature (65) for 30 min, starch granules were swollen, but at the longer time (60 min) approximately all of the granules changed and formed an amorphous matrix with some of the unchanged granules. In the case of S-G6560, it can be observed that the wrapping effect of Arabic gum on the cornstarch granules inhibited starch gelatinization. Although the temperature of ultrasound treatment (65 °C) is lower than the gelatinization temperature of corn starch, a combination of ultrasound and thermal treatment could promote the gelatinization phenomenon, resulting in increased gelatinization. Ultrasonication caused severe physical damage on the granular surface, by creating fissures or cracks, thereby increasing the ability of the granules to retain more waterThe FT-IR spectra of thermal-ultrasound-treated samples are compared in Fig. −1 ratios that are calculated in Table −1 ratio and the lower R1022/ 995 cm−1 absorbance ratio showed a higher relative crystallinity. These trends were observed in Table The crystallinity index of samples can be determined from the absorbance ratios of R1047/1022 and R1022/995 cm14. This phenomenon was in accordance with the observation of SEM images of some granules that initiated to loss of their integrity. The relative crystallinity of treated samples at 65 °C decreased with increasing time and the lower value was 21.88% for S-G6560  of thermal-ultrasound-treated samples were reported in Fig. 60 Table . In genep < 0.05) from 72.63 to 84.17 °C. Tmax increased from 73.22 to 75.51 °C with the addition of Arabic gum to corn starch. So, the Ts and Tmax increased with increasing temperature and time after treatment.The pasting properties of the treated corn starch-Arabic gum samples are studied as a function of thermal heating. The rheological parameters are calculated from pasting curves and reported in Table 24, Arabic gum was found to lower the peak viscosity and swelling power leading to a delay of retrogradation. These characteristics may be related to many parameters such as molecular structures, amylose and amylopectin interactions, and ionic charges of starch and hydrocolloids24. The maximum viscosity of treated samples increased from 25 to 45 °C and this value decreased from 45 to 65 °C again. S-G4530 samples had the highest value among others. Except for S-G4530, the B value of treated samples decreased after thermal-ultrasound treatment and showed the highest value in the S-G4530 and S-G6560 samples. The final viscosity  and Arabic gum were purchased from Sigma-Aldrich  and Daejung , respectively. The manufacturer has reported corn starch's composition as follows: 11.3% wt. moisture content and pH 5.2. All other chemicals were of analytical grade. Moreover, all solutions were prepared with distilled water.2 based on different conditions. Different temperatures (25–65 °C) and time (30 min and 60 min) of sonication were selected based on starch pasting during heating. Aimed at controlling bath temperature, a thermocouple was employed and cooled down to an appropriate temperature by adding a little iced water. Each treatment was carried out based on 5% wt. total biopolymer concentration and 95:5 biopolymer ratio (S:G) at the center of the sonication bath. After treatment, all suspensions were freeze-dried. The control sample was not sonicated (with and without Arabic gum); but freeze-dried after dissolving in water. The treated samples are named as follows: S-G2530 = treated at 25 °C for 30 min; S-G2560 = treated at 25 °C for 60 min; S-G4530 = treated at 45 °C for 30 min; S-G4560 = treated at 45 °C for 60 min; S-G6530 = treated at 65 °C for 30 min; S-G6560 = treated at 65 °C for 60 min; S-G = corn starch- Arabic gum mixtures without treatment; S = corn starch without treatment.The treatment of corn starch (S) was performed by ultrasound of starch with Arabic gum (G) combination. Firstly, Arabic gum (1.25 g) was slowly dissolved in distilled water (475 ml) and vigorous stirring with a magnetic stirrer. Then, corn starch (23.75 g) was added to the previous gum solution, and the solution was stirred continuously for 30 min at 23 ± 1 °C. The suspensions were treated in an ultrasound bath  at 30 kHz and a power of 270 W/cm26. 20 mg of starch sample (based on starch weight) was taken and 10 ml KOH 0.5 N was added to it. The suspension was mixed vigorously. The dispersed sample was transferred to a 100 ml volumetric flask and distilled water was added to it. 10 ml of starch solution was pipetted to the 50 ml volumetric flask and 5 ml HCL 0.1 N and 0.5 ml iodine reagent were added. Distilled water was added to 50 ml and absorbance was measured at 625 nm. The amylose content of samples was calculated based on standard curves of amylose solutions.The amylose content of the S-G samples was determined by the method of Sodhi and Singhg for 15 min26.S-G suspension (5% wt. concentration) was heated at 90 °C for 30 min in a water bath. After that, the sample was cooled to 4 °C and stored for 2- and 7-days storage at 4 °C. Syneresis was calculated based on the amount of released water (%) after centrifugation at 3200 × 27.Paste clarity of samples was determined at 4 °C after 2- and 7-days storage. Firstly, starch suspension (1% wt. concentration) was prepared and heated for 30 min at 95 °C. After cooling, the absorbance value of the starch paste was measured at 650 nm with a UV–visible spectrophotometer28. Briefly, starch-gum samples were suspended in distilled water to obtain 1% wt. total concentration. The suspensions were heated at 25, 45, 65, and 85 for 30 min with continuous shaking. After rapid cooling to room temperature, the samples were centrifuged for 20 min (2400 g) and the weight of sediment was measured (m2). Then, the precipitated paste and supernatant were dried at 110 °C to a constant weight . Swelling power (SP) and solubility (S) were calculated by Eqs. . 5 mg starch sample was weighed in a hermetic aluminum pan and distilled water was added to it until the starch suspension reached 50% wt. concentration. The sealed pan was transferred to the heating equipment of the DSC and an empty pan was applied as a reference. All samples were scanned from 20 to 120 °C with a 10 °C/min heating rate. The onset (To), Peak (Tp), and gelatinization enthalpy (ΔH) were calculated from thermograms30.The microstructure of the freeze-dried samples was examined by scanning electron microscope . A small amount of sample was fixed on the surface of the stub and dried at room temperature (23 °C) for one day. Then, all samples were coated with gold–palladium before observation. The image of the sample was taken at the range 2000 × and 3000 ×, and the applied voltage was 10 kV−1. All samples were mixed with KBr and the resolution was (4 cm−1)2.The infrared spectra of the freeze-dried samples were performed by an FT-IR spectrometer . The wavenumber was applied in the range 400–4000 cm31 with slight modification. Diffraction was performed on an X-Ray Diffractometer with Cu-Ka radiation (λ = 0.154 nm) at 40 kV and 40 mA. Scanning was done at a reflection angle of 5° (2θ) to 70° (2θ) with a rate of 0.05°/min. Relative crystallinity (RC) was calculated as the ratio of the crystalline reflation area to the overall diffraction area between 2θ values of 5° and 40°.X-ray diffraction patterns of the freeze-dried samples were obtained with an X-ray diffractometer  by the following method of Yang et al.The rheological properties of samples were studied by a rheometer  with the cone and plate measuring system . The sample temperature was precisely (± 0.01 °C) controlled by a Peltier-plate system and a physical circulating thermostatic water bath. Heating and cooling rates were selected based on preliminary experiments.S: the temperature at which complex viscosity  Thttps://www.sas.com/en_us/home.html). The mean of data was comprised of analysis of variance method (Proc GLM) at a significant level of 95% (p < 0.05). A least significant difference (LSD) was employed to determine the statistical differences among the mean values.The analytical determination was done by SAS 9.1 software version 2008 (This research studied the physicochemical, structural, morphological, and pasting properties of thermal-sonicated corn starch in presence of Arabic gum. Based on the results, amylose leakage, solubility, swelling power, syneresis of starch gels, paste clarity, and pasting characteristics were induced by thermal-ultrasound treatment in presence of Arabic gum. Moreover, the thermal properties and X-ray diffraction of corn starch changed after treatment. Scanning electron microscopy and FT-IR spectra of samples confirmed the modification of structural properties. Temperature and time are selected as key parameters in this modification method.Therefore, ultrasound treatment could be a suitable method for the modification of starch granules. On the other hand, currently, thermal treatment due to the improved thermal stability and decreased extent of retrogradation is of great interest as a physical modification technique. Moreover, it is well known that the addition of hydrocolloids improved starch functionality by altering its rheological/ structural and gelatinization properties. Therefore, thermal-ultrasound treatment of corn starch and Arabic gum mixtures offer opportunities for the modification of starch and new biopolymers with application in the food industries based on the suitable changing of ultrasound conditions.


To the editor,We read with great interest the recent article published in the Journal by Endo et al. , reportiThe authors must be congratulated for these very interesting findings in line with international sepsis guidelines to develop a more appropriate treatment system –4. BeyonFurther prospective studies are needed to clarify the real treatment effect of immediate ICU admission for patients suffering from septic shock.


The vaccine construct was evaluated as antigenic with VaxiJen Score of 0.6781, immunogenic with IEDB score of 2.89887 and non-allergenic. The 55.64 kDa construct was further evaluated for its physicochemical characteristics, which revealed that it was stable with an instability index of 16.24, basic with theoretical pI of 9.24, thermostable with aliphatic index of 86.72 and hydrophilic with GRAVY score of −0.256. The docking and molecular dynamics simulation studies of the vaccine construct with Toll-like receptor-3 revealed fair structural interaction  and complex stability. Further, the predicted induction of antibodies and cytokines by the vaccine construct indicated the possible elicitation of the host's immune response against the virus. The work is a significant attempt to develop next-generation vaccines against the infectious bursal disease virus though further experimental studies are required to assess the efficacy and protectivity of the proposed vaccine candidate in vivo.Infectious bursal disease virus is the causative agent of infectious bursal disease (Gumboro disease), a highly contagious immunosuppressive disease of chicken with a substantial economic impact on small- and large-scale poultry industries worldwide. Currently, live attenuated vaccines are widely used to control the disease in chickens despite their issues with safety  and efficiency . To overcome the drawbacks, the current study has, for the first time, attempted to construct a computational model of a multiepitope based vaccine candidate against infectious bursal disease virus, which has the potential to overcome the safety and protection issues found in the existing live-attenuated vaccines. The current study used a reverse vaccinology based immunoinformatics approach to construct the vaccine candidate using major and minor capsid proteins of the virus, VP2 and VP3, respectively. The vaccine construct was composed of four CD8  The VP2 polypeptide forms the major capsid of IBDV and carries the main immune determinants for eliciting neutralizing antibodies  is an economically significant and contagious poultry disease. IBD, also known as Gumboro disease, is caused by the double-stranded RNA virus (dsRNA) known as infectious bursal disease virus (IBDV). The virus belongs to the family Birnaviridae, replicates in the bursa of Fabricius (BF) in young chickens causing depletion of B-lymphocytes , 2. As atibodies . Due to tibodies . Segmenttibodies . Bound tAdequate control of IBD is possible only by following vaccination regimes as the highly contagious IBDV is a very resilient and persistent virus that survives in poultry houses despite stringent disinfection . DespiteMultiepitope-based vaccines (MEV) are peptide-based vaccines that consist of T cell and B cell epitopes and have the ability to trigger efficient cellular and humoral immune responses . MEV canhttps://www.ncbi.nlm.nih.gov/protein). Multiple sequence alignment was performed on the reference sequences obtained from NCBI using DNA star  with ClustalW parameters. The antigenicity of the reference sequences was evaluated using the VaxiJen v2.0 Server, using a 0.4 antigenicity threshold (http://www.ddg-pharmfac.net/VaxiJen/VaxiJen/VaxiJen.html) (The VP2 and VP3 protein sequences from 10 distinct IBDV strains  were obten.html) .In this study, human HLA alleles were considered instead of chicken HLA alleles because of the unavailability of the applicable data. Consequently, human-related data was utilized to predict the MHC epitopes of selected sequences , 31. Humhttps://services.healthtech.dtu.dk/service.php?NetCTL-1.2) for the generation of nine amino acid long fragments (+ T cell response. The Stabilized Matrix Base Method (SMM) prediction method of the IEDB tool (http://tools.iedb.org/mhci/) was used to identify the MHC-I HLA binding CTL/CD8+ epitopes out of the resulting nine amino acid long fragments (http://tools.iedb.org/immunogenicity/) for the evaluation of immunogenicity (The sequences which were found to be antigenic were further submitted to the NetCTL v1.2 server (ragments . The fraragments . The pargenicity .http://tools.iedb.org/mhcii/) to predict HTL epitopes interacting with MHC class II HLA alleles (http://crdd.osdd.net/raghava/ifnepitope/) with SVM (support vector machine) approach and the IFN vs. non-IFN predictive models (http://crdd.osdd.net/raghava/il4pred/)  . The selhttps://webs.iiitd.edu.in/raghava/abcpred/) to identify antigens that can trigger the production of antibodies by eliciting a B cell immune response. The server predicts linear B cell epitopes using an artificial neural network (The antigenic consensus sequences were subjected to the ABCPRED server ( network . The pothttp://tools.iedb.org/conservancy/) (https://www.ddg-pharmfac.net/AllerTOP/) was used to assess the allergenicity of the conserved epitopes and identify the non-allergic epitopes  . The Allepitopes , 42.+, CD4+, and B cell epitopes were identified using several immunoinformatic tools, as indicated above. To construct the IBD-MEV, these epitopes coupled with an adjuvant were linked with appropriate linker peptides. The CD8+/CTL epitopes were linked using an AAY linker, and the CD4+/HTL were connected using GPGPG linkers. The HEYGAEALERAG linker was used to join CTL epitopes with HTL epitopes, while the B cell epitopes were linked by KK linkers. An appropriate adjuvant, cholera toxin subunit B (CTB), was incorporated to the N terminal of the construct peptide using the EAAK linker. The adjuvant was included to enhance the immunogenicity of the vaccine construct (https://web.expasy.org/protparam/) determined the physical and chemical characteristics, such as the molecular weight (kDa), the number of amino acid residues, the theoretical isoelectric point (pI), the estimated half-life, the instability index, the aliphatic index, the hydropathicity, and grand average of hydropathicity (GRAVY) (The top candidates for CD8onstruct . The MEV (GRAVY) .http://bioinf.cs.ucl.ac.uk/psipred/) for prediction and analysis of the secondary structure  (https://prosa.services.came.sbg.ac.at/prosa.php)  . The resosa.php) , 50.http://hdock.phys.hust.edu.cn/) with default parameters (https://pymol.org/) and Discovery Studio Biovia 2021 (https://discover.3ds.com/). Molecular Dynamics Simulation by GROMACS 2021.1 was performed using OPLS-AA/L all-atom force field to study the stability of the complex  using the HDOCK server (rameters . The ser complex . The comhttp://www.jcat.de/), the vaccine construct was codon optimized using the Escherichia coli K12 strain as the host organism. The JCat adaptation was defined using the codon adaptation index (CAI) and GC content of the optimizes sequence (BamHI (GGATCC) was added to the 5′ end while XhoI (CTCGAG) restriction site was added to the 3′ end. SnapGene Viewer V3.2.1 (http://www.snapgene.com/) carried out the in-silico cloning of the optimized vaccine sequence into the pET-28a (+) expression vector system.Using the Java Codon Adaptation Tool (sequence . The idesequence . To the https://kraken.iac.rm.cnr.it/C-IMMSIM/) was used to model and evaluate the immune response of the vaccine construct for the specified vaccination program , yielding 86 VP2 and 37 VP3 CTL epitopes. The screened epitopes were examined with the VaxiJen v2.0 server for antigenicity (threshold ≥0.5). Among the predicted epitopes of VP2 and VP3 proteins, 47 and 16 epitopes showed considerable antigenic potential, with the highest antigenic score of 1.6076 and 0.8179 for VP2 epitope “TSYDLGYVR” and VP3 epitope “EAAANVDPL.” Following the assessment of immunogenicity using the IEDB tool, the epitopes were filtered to 26 VP2 and 8 VP3 immunogenic epitopes. Finally, the allergenicity and conservancy analysis was carried out using the AllerTop v2.0 server and IEDB conservation across antigen tool, where the allergenic and non-conserved epitopes were screened out, and only 15 VP2 and 2 VP3 CTL epitopes were regarded as concluding predicted epitopes .via filtration based on IEDB tool IC50 value (< 250) and VaxiJen tool antigenicity score (≥0.4). The 15-mer epitopes were further examined for IFN-gamma and interleukin inducer properties using IFN epitope and IL-4pred immunoinformatic tools. A total of 99 VP2 and 100 VP3 CD4+ T cell epitopes exhibited the property to induce IFN-γ, while only 25 VP2 epitopes and 16 VP3 epitopes exhibited IL-4 inducer properties. Finally, the antigenicity and allergenicity analysis was carried out using VaxiJen and AllerTop v2.0 servers, where the non-antigen and allergenic epitopes were screened out. 6 VP2 epitopes and 1 VP3 epitope were concluded as the most promising HTL epitope candidates for the final vaccine construct . The Immunogenicity analysis further filtered the epitopes to 14 VP2 and 4 VP3 Immunogenic epitopes. Among the immunogenic epitopes, only 9 VP2 and 3 VP3 B cell epitopes were assessed as non-allergenic and selected for the final vaccine construct, omitting the allergenic epitopes , >20 h in yeast, and >10 h in E. coli (in vivo). Moreover, a Z-score of −4.49 was obtained, signifying the high quality of the structure . The obtained CAI value of 0.99 and GC-content of 52.36% imply the effectiveness of IBD-MEV expression in the selected host. The predicted DNA sequence of the IBD-MEV construct was cloned into the pET-28a(+) expression system using the SnapGene. BamHI restriction sequence was incorporated at the N-terminal, and XhoI site was incorporated at the C-terminal of the construct . The immune response was studied for 45 days. With C-ImmSim simulation, in comparison to the primary reaction indicated by IgM, delivery of the IBD-MEV construct resulted in a considerable increase in the tertiary immune response. After receiving the vaccination, the B cell population produced memory cells that would keep the memory if the host became reinfected , histidine (1.5%) and lysine (8.6%). The aliphatic index, which is the proportional volume occupied by the protein's aliphatic side chains, determines the thermal stability of a vaccine construct, with higher aliphatic index values indicating thermostability over a wide temperature range , 61. TheZ score supported the vaccine's overall quality  system , 47. In  quality .G) value. The Gibbs free energy is essential to characterize the magnitude of an interaction occurring under certain circumstances in a cell. The more negative the value of the Gibbs free energy, the more energetically feasible the interaction is. Accordingly, a ΔG value of −295.94 kcal/mol indicates stable binding of IBD-MEV and TLR3. PDBSum revealed the existence of H-bond and salt bridge interactions between the IBD-MEV and TLR3  levels. Upon the first IBD-MEV administration, modest production of antibodies was simulated, whereas elevated production of antibodies was observed upon the second dose. Among the immunoglobulins, high IgG and IgM levels were simulated, constituting the primary response against the virus. In addition, IgG1 + IgG2, IgG1 and IgG2 comprising the secondary and tertiary response were also noted on vaccine administration. The antigen exposure increased the B lymphocyte count, particularly the memory B lymphocytes. The progressive rise in memory B lymphocytes and immunoglobulins with repeated administration of the antigen confirms the efficacy of IBD-MEV when the host is exposed over a prolonged period of time. The T helper (TH) response exhibited a similar response, with antigen exposure increase in memory cell count was predicted. In contrast, cytotoxic T cells maintained a modest level throughout the simulation. In this way, the IBD-MEV administration simulated an efficient humoral and cell-mediated immune response against IBDV. However, further research and experimental validation of the current study's findings are necessary to confirm and validate the safety, protectivity and efficacy parameters.By modeling the host's immunological response following vaccination, immune simulations give insight into the capability of the vaccine construct against the pathogen . The in Publicly available datasets were analyzed in this study. The names of the repository/repositories and accession number(s) can be found in the article/in-silico experiments. EH, RS, NG, and SA contributed to the manuscript reading and revision. All authors approved the submitted version.IG and NS contributed to the conception and design of the study. IG and AH wrote the first draft of the manuscript. JM and TA wrote sections of the manuscript. NC supervised the


Dietary compounds significantly affected starch enzymatic digestion. However, effects of dietary compounds on starch digestion and their underlying mechanisms have been not systematically discussed yet. This review summarized the effects of dietary compounds including cell walls, proteins, lipids, non-starchy polysaccharides, and polyphenols on starch enzymatic digestion. Cell walls, proteins, and non-starchy polysaccharides restricted starch disruption during hydrothermal treatment and the retained ordered structures limited enzymatic binding. Moreover, they encapsulated starch granules and formed physical barriers for enzyme accessibility. Proteins, non-starchy polysaccharides along with lipids and polyphenols interacted with starch and formed ordered assemblies. Furthermore, non-starchy polysaccharides and polyphenols showed robust abilities to reduce activities of α-amylase and α-glucosidase. Accordingly, it can be concluded that dietary compounds lowered starch digestion mainly by three modes: (i) prevented ordered structures from disruption and formed ordered assemblies chaperoned with these dietary compounds; (ii) formed physical barriers and prevented enzymes from accessing/binding to starch; (iii) reduced enzymes activities. Dietary compounds showed great potentials in lowering starch enzymatic digestion, thereby modulating postprandial glucose response to food and preventing or treating type II diabetes disease. Starch which is a polysaccharide composed of linear chains (amylose) or branched chains (amylopectin) is a major source of energy in the human diet. Starch digestion is accomplished by two type of enzymes in human gastrointestinal tract (GIT): (i) salivary and pancreatic α-amylases and (ii) intestinal brush border glucoamylases, maltase-glucoamylase, and sucrase-isomaltase . Amylaseca. 12–24 and DP ≥ 37, along with some chains with DP 25–36, perfectly-packed double helices and crystalline structures, V-type crystals, or densely-packed crystalline lamellae and more ordered reassembled aggregate structures  on enzymes activities, thereby slowing the enzymatic digestion of starch within pulse cells  was in the range of 1.75–2.15 mg/mL] and lowered starch digestion extent  proteins acted as physical barriers and restricted the interaction of enzymes with starch molecules  prolecules , 41;  dissolution in water and promoted lipid-starch entanglement , 60–62. During the preparation of starch-lipid inclusion complexes, the temperature, complexation time and modes, pH, NaCl, and cooling rate significantly affected the formation of the complexes –71. A hiCordyceps polysaccharides, Mesona chinensis polysaccharides, agar, xanthan gum and konjac glucomannan restricted starch disruption during the hydrothermal treatment and interacted with starch to form ordered structures, and in turn, lowered starch digestion extent , Camellia oleifera Abel. fruit hull, oolong tea, shaddock (Citrus aradise), Coriolus versicolor LH1, mulberry fruit, pumpkin (Cucurbita moschata) fruit, fermented puerh tea, green tea flower, corn silk, Acacia tortilis gum exudate, Chinese traditional medicine Huidouba, Mallotus furetianus, hemp (Cannabis sativa L.), Fagopyrum tartaricum, blackberry fruit, Rosa roxburghii Tratt fruit, Annona squamosa, wax apple, Chaenomeles speciosa seeds, and Momordica charantia, significantly reduced the activities of α-glucosidase or α-amylase, which showed great potentials in slowing starch enzymatic digestion  interacted with starch granules and restricted starch disruption during food processing –80; (ii)Effects of polyphenols on starch digestion are schematically shown in Polyphenols could interact with starch and form ordered starch structures, and in turn, lowering starch digestion as shown in via inhibiting enzymes activities.In addition to the compounds discussed above, other dietary compounds such as NaCl and phytosterols also affected starch digestibility , 117. NaThis review summarized effects of dietary compounds including cell walls, proteins, lipids, non-starchy polysaccharides, and polyphenols on starch enzymatic digestion and their underlying mechanisms were discussed. Dietary compounds lowered starch digestion through three pathways: (i) retained starch ordered structures or formed ordered assemblies chaperoned with these dietary compounds; (ii) formed physical barriers and prevented enzymes from accessing/binding to starch; (iii) reduced enzymes activities. Cell walls, proteins, and non-starchy polysaccharides restricted starch disruption during hydrothermal treatment and the retained ordered structures limited enzymatic binding. In addition, they encapsulated starch granules and formed physical barriers for enzymes accessing. Proteins, non-starchy polysaccharides along with lipids and polyphenols interacted with starch and formed ordered assemblies. Non-starchy polysaccharides and polyphenols showed robust ability to reduce activities of α-amylase and α-glucosidase. Comparing with cell walls, protein, and non-starchy polysaccharides, lipids and polyphenols had stronger ability to slow starch digestion.in vitro. Dietary compounds would be digested and absorbed in the gastrointestinal tract and in turn affected starch digestibility. Starch in vitro digestibility may quite different to in vivo digestibility. Accordingly, in vivo glycemic response is the most important property of starchy foods. Further studies are needed to investigate the roles of dietary compounds on starch in vivo glycemic response. In addition, different groups of people such as children, athletes, middle- and old-aged human have different requirements for starch digestion rate and extent. Targeted structuring food structures and starch digestion behaviors via complexation with dietary compounds remains of interest.Food systems are relative complex with cell walls, proteins, lipids, non-starchy polysaccharides, polyphenols, vitamin, minerals, sugar, salts, etc. Dietary compounds might interact with each other and affect starch digestion in complicated pathways. How the complex dietary compounds affected starch digestion in real foods systems must be further investigated. Currently, effects of dietary compounds on starch digestion were interrogated CC: conceptualization, literature analysis, reviewing, and editing. MS: reviewing and editing. YZ: supervision, writing, reviewing, and editing. BC: investigation, writing, and editing. YH: investigation and reviewing. MW: supervision, reviewing, and editing. All authors contributed to the article and approved the submitted version.The research was financially supported from project of the Scientific Research Innovation Program Xiyuanjiang River Scholarship of College of Life Sciences, Fujian Normal University (22FSSK004).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.


Artificial intelligence (AI) refers to computer algorithms used to complete tasks that usually require human intelligence. Typical examples include complex decision-making and- image or speech analysis. AI application in healthcare is rapidly evolving and it undoubtedly holds an enormous potential for the field of solid organ transplantation. In this review, we provide an overview of AI-based approaches in solid organ transplantation. Particularly, we identified four key areas of transplantation which could be facilitated by AI: organ allocation and donor-recipient pairing, transplant oncology, real-time immunosuppression regimes, and precision transplant pathology. The potential implementations are vast—from improved allocation algorithms, smart donor-recipient matching and dynamic adaptation of immunosuppression to automated analysis of transplant pathology. We are convinced that we are at the beginning of a new digital era in transplantation, and that AI has the potential to improve graft and patient survival. This manuscript provides a glimpse into how AI innovations could shape an exciting future for the transplantation community. Artificial intelligence (AI) refers to the use of algorithms (machine learning and deep learning) to perform tasks that are usually associated with human intelligence, “such as the ability to reason, discover meaning, generalize, or learn from past experience to achieve goals without being explicitly programmed for specific action” , 2. AI iPowered by increasing availability of healthcare data and rapid development of analytical techniques, AI is also growing exponentially in all areas of medicine, including solid organ transplantation. The pre- and post-transplantation patient care requires complex decision-making. In this context, AI can drive a real paradigm shift as it enables analyzing and synthesizing of huge amounts of data, and transforming them into clinical recommendations. AI-based classifiers have been principally explored for the optimization of four key areas: organ allocation and donor-recipient pairing, transplant oncology, real-time immunosuppression regimes, and precision transplant pathology. The aim of AI is to identify hidden trends and complex relationships within large datasets to obtain logical results while optimizing resources. AI is still in its infancy and, so far, we lack validated algorithms that could accurately drive organ selection, predict potential rejections or attenuate postoperative complications. Nevertheless, in the last few decades, AI applications have already contributed to lower incidence of rejection, and fine-tuning of the transplantation and organ preservation processes. In this review, we discuss emerging AI, machine learning and deep learning strategies applied to solid organ transplantation and their potential future applications .From an exclusively mathematical point of view, transplantation can be reduced to a list of problems in which the characteristics of the donor must be combined with the variables of the recipient in order to achieve one of the following three outcomes : the surThe allocation systems used by Eurotransplant in Europe, and the United Network for Organ Sharing (UNOS) in the US, are intended as objective and transparent procedures to make the best possible match , 4. The Organ allocation could also benefit from the Internet of Things (IoT). IoT refers to a network of interconnected smart devices such as smartphones, tablets, and laptops, but also wearables, cars, and data transmission devices . An IoT Organ allocation is strictly connected to donor-recipient matching. Although thoroughly analyzed and refined, the traditional donor-recipient matching models still leave room for improvement and could potentially benefit from AI. In 2013, Cruz-Ramirez et al. reported the use of AI artificial neural networks (AI-ANNs) to improve donor-recipient pairing. AI-ANNs analyzed data on 1,003 liver transplants including donor/recipient matching, graft retrieval and pre-transplant analysis . The folThe reports on impact of diabetes on the outcome of liver transplantation have been contradictory. Recently, Yasodhara et al. demonstrated the value of AI for successful liver donor-recipient matching, by including the metabolic status of the recipient . Based ohttps://www.transplantmodels.com/kdpi-epts/)   to maximTransplant oncology is defined as a combination of various fields of transplant medicine and oncology, aiming to extend the treatment limits of hepatobiliary cancer including hepatocellular carcinoma (HCC), cholangiocarcinoma or colorectal liver metastases , 19.In the past this discipline relied on simple variables such as the number of tumor lesions and their size. In recent years, transplant oncology was refined and a multitude of new variables identified as central, making AI a potentially important tool. Identification of key clinical and pathological variables is a crucial step in the use of AI for the prediction of tumor recurrence and graft survival after transplantation . AI has The Metroticket 2.0 score proposed by Mazzaferro and coworkers  predictsn = 739). This AI-based HCC-recurrence calculator (CoxNet-based) was then compared to alternative available recurrence risk scores . The CoxNet-based algorithm outperformed AFP by 0.118, MORAL by 0.130 and HALT-HCC by 0.102. These findings confirm, pending an external validation, that an AI-based calculator can generate a comprehensive prediction of post-transplant HCC recurrence with higher accuracy than alternative scores.Recently, the group lead by Prof. Sapisochin described the use of AI for predicting the post-transplant recurrence of HCC based on preoperative patient and tumor characteristics . To do tThe discovery of cyclosporine was a cornerstone of modern transplantation  and consMany factors come into play when choosing the optimal immunosuppression regimen, and the decision-making is complex. One relatively simple example of machine learning use is to predict the stable dose of tacrolimus in kidney transplant patients. Three studies compared the logistic regression approach to machine learning algorithms –33. All Taking a more general approach, Nitski et al. analyzed large retrospective datasets with machine learning algorithms to predict mortality in liver transplant patients . The modet al. used the transcriptomes of urinary cells from 220 patients to predict acute rejection based on kidney biopsies (Suthanthiran biopsies . The autbiopsies . Deep lebiopsies .AI can integrate high-complexity information from many sources into the decision-making tree used in individualized immunosuppression. A wealth of information about donors and recipients is still underutilized. Data from pre-transplantation histology, recipient’s genome, gene expression analysis, blood and urine analysis, and clinical observation can all deliver important clues on the state of a transplanted organ –41. AI cAI has proven highly efficient in image processing. An image contains a high density of structured and unstructured information that is often inaccessible to the untrained eye . A pathoIn liver transplantation, quick and reliable assessment of liver steatosis during procurement still presents a challenge. Recently, several groups have developed deep learning algorithms to assess the degree of steatosis in liver biopsies –49. PereAutomated image analysis, feature recognition, data extraction and deep learning models are everyday reality for the tech giants but have only partially reached precision pathology –53. RadiThe true potential of AI in healthcare has yet to be fully exploited and its application in solid organ transplantation is mostly under development. Some important limitations exist . Several