White salted (udon) noodles are one of the major staple foods in Asian countries, particularly in Japan. Noodle manufacturers prefer the Australian noodle wheat (ANW) varieties to produce high-quality udon noodles. However, the production of this variety has reduced significantly in recent years, thus affecting the Japanese noodle market. Noodle manufacturers often add tapioca starch to compensate for the flour scarcity; however, the noodle-eating quality and texture are significantly reduced. This study, therefore, investigated the effect of the addition of porous tapioca starch on the cooking quality and texture of udon noodles. For this, tapioca starch was initially subjected to enzyme treatment, ultrasonication, and a combination of both to produce a porous starch where a combined enzyme –ultrasound treatment (20 kHz) yielded a porous starch with increased specific surface area and better absorbent properties which are ideal for udon noodle manufacturing, Later, udon noodles were prepared using three varieties of ANW, a hard Mace variety, and commercial wheat flour by incorporating the prepared porous tapioca starch at a concentration of 5% and 10% of dry ingredients. Adding this porous starch resulted in a lower cooking time with higher water absorption and desirable lower cooking loss compared to the control sample with 5% of the porous starch chosen as the optimum formulation. Increasing the level of the porous starch reduced the hardness of the noodles whilst maintaining the desired instrumental texture. Additionally, a multivariate analysis indicated a good correlation between responses’ optimum cooking time and water absorption capacity as well as turbidity and cooking loss, and a cluster analysis grouped noodle samples prepared from different varieties into the same clusters based on the porous starch added, indicating the possibility of different market strategies to improve the quality of the udon noodles produced from different wheat varieties. Noodles are traditional cereal-based products popular throughout the globe and highly consumed in Asian countries. The major factors leading to the popularity of Asian noodles are affordability, convenience, and long shelf life . NoodlesTo help maintain the high-quality udon noodle production market in Japan, it would be beneficial to understand the significance of starch quality and its modification on noodle quality. Noodle eating quality and texture are the significant aspects of high-quality udon noodles . These nNative wheat starch shows bimodal size distribution with large A-type and small B-type granules with a lenticular and spherical morphology, respectively . TypicalTapioca starch is known to have numerous industrial and food applications owing to its low cost and high expansion characteristics and is reported to confer an elastic texture to noodles when modified by means of physical or chemical methods ,22. The Hifumiya Udon Noodle House, Perth, WA, supplied the commercial flour for standard udon noodle preparation. The ANW  and hard (Mace) wheat varieties were obtained from Intergrain Pty Ltd., Bibra Lake, WA, and were milled and passed through a sieve to attain a particle size <180 µm in a laboratory facility at the Intergrain. Tapioca starch and salt were purchased from Coles, Waterford Plaza, WA. Alpha-amylase (Sigma A6255 from porcine pancreas) was obtained from Sigma-Aldrich .Three different treatments, viz enzyme treatment, ultrasonication, and a combination of both, were used to prepare the porous tapioca starch, as discussed by Majzoobi, Hedayati, and Farahnaky (2015) , with slg for 20 min at room temperature. The pellet obtained was recovered and washed three times using distilled water and dried in an oven  at 80 °C for 12 h. The dried pellet was ground, sieved to pass 100% through a 125 µm sieve, and stored vacuum-packed for further analysis.The prepared starch slurry (100 mL) was subjected to two concentrations of α-amylase enzyme, viz. 0.4% and 0.6%. The mixtures were placed in a water bath of 45 °C for 24 h for starch hydrolysis and then centrifuged at 3000× g for 20 min at room temperature and then dried in an oven  at 80 °C for 12 h. The dried pellet was ground to pass 100% through a 125 µm sieve and stored vacuum-packed for further analysis.The prepared starch slurry (100 mL) was subjected to ultrasonication  for 40 min using two different frequency settings: high frequency (48 kHz)/low power (60 W) and low frequency (20 kHz)/high power (100 W) at a constant amplitude of 100%. The temperature of the ultrasonication bath was maintained at 40 °C. The pellet was recovered after centrifugation at 3000× For preparing the porous starch by the combined enzymatic–ultrasound treatment, the prepared starch slurry was first treated with α-amylase (0.4% and 0.6%) , and theThe surface morphology of the prepared porous starch samples was imaged under a scanning electron microscope  in high vacuum mode with a 5 kV voltage and 5–10 mm working distance (WD) after platinum coating.The flour from Australian wheat cultivars and the controls  were blended with different proportions of porous tapioca starch (5 and 10% of the dry ingredients) to make the noodles. The dough crumb was made by adding a calculated amount of water and salt solution to the wheat flour–porous tapioca starch blend in a mixer. The water addition was decided based on the flour moisture content of each wheat variety using mass balance equations  . The cruThe optimal cooking time (OCT) was determined in duplicate according to the AACC-approved method 66.50.01 . BrieflyExactly 20 ± 0.05 g of freshly prepared noodles with a strand length of 20 cm were boiled in 300 mL distilled water to their OCT as described above. The cooked noodles were then drained, weighed, and the water absorption upon cooking was determined in duplicate . Water aExactly 20 ± 0.05 g of freshly prepared noodles of a strand length of 20 cm were boiled in 300 mL of distilled water to their OCT as described in The three-strand cutting system was used to determine the force required to cut through the cooked and cooled noodles with a strand length of 4 cm. A texture analyzer TA.XT2i  calibrated using 5 kg of load cell with a cutting probe of 33 mm diameter was used for the test. The equipment was set to pre-test, test, and post-test speeds of 2.0, 2.0, and 1.0 mm/s, respectively. The analysis was carried out in triplicate for each cooked sample .The turbidity of cooked noodles with a strand length of 20 cm was analyzed as per the method described by Jeon et al. . Exactlyp ≤ 0.05 was considered significant. A correlation analysis, principal component analysis (PCA), and cluster analysis were performed on the complete dataset using R software  with corrplot , prcromp , and factoextra packages, respectively. Scripts were written in R and ‘fviz’ and ‘ggplot2′ functions were used to visualize the multivariate analyses outputs.The data were analyzed using SPSS Version 16 software using a two-way analysis of variance (ANOVA), followed by pairwise comparisons based on marginal means and adjustment with the Bonferroni method where a SEM images of porous tapioca starch granules prepared using the different enzyme concentration and ultrasonication settings are presented in Native tapioca starch granules a generalThe quality attribute values obtained for the udon noodles for each variety of wheat used and the amount of porous starch added is depicted in p < 0.05) depending on the wheat variety used and the amount of porous starch added, except for WAC, where only the wheat variety was the significant factor. The interaction effects were also significant for all the responses except turbidity and texture.The results of the two-way ANOVA  conducteFurther, pairwise comparisons were made between the factors to determine the significant difference between the means among the two factors studied, viz., the wheat variety and level of porous starch added .Cooking time is important for determining noodle quality and consumer acceptability as it decides whether the noodle is undercooked or overcooked . Figure p < 0.05) to 10.35 min. At the same level of porous starch, the cooking time for noodles prepared from Zen and Kinsei varieties, which are the ANW varieties, was the shortest. A pairwise comparison among the wheat varieties at a specific concentration of porous starch showed no significant differences between the ANW Kinsei and Zen varieties at both 5 and 10% porous starch  on the WAC values, whereas the wheat variety and the interaction term had a significant influence. The WAC values obtained were then compared for each variety of wheat used for a specific concentration of porous starch added  in the cooking loss values obtained for noodles prepared from Mace, Ninja, and Zen varieties  of both the wheat variety and level of porous starch addition on the turbidity values; however, the interaction effect was insignificant  was employed to obtain a linear and unsupervised visualization of the results by reducing the original data dimension by the orthogonal transformation of the vector space. A variance bar plot and scree plot were generated to visualize the importance of principal components (PCs) created based on the amount of variation they covered . Two PCsIn contrast, cooking loss and turbidity vectors diverged from OCT, indicating a strong negative correlation. The biplot also depicts the scores of each sample studied, and their positions within the four quadrants indicate their possible relation. For instance, N5, N10, K5, K10, and M10 are all closely located to each other, meaning they have similar PC scores.Prior to the cluster analysis for classifying the data samples into groups of similar objects, a distance or dissimilarity matrix was created c using tFor further understanding the similarity among different groups of data, K-means clustering was employed by partitioning the dataset into a set of two and three groups d,e afterThis study demonstrated the new knowledge on adding porous tapioca starch to wheat flour in udon noodle formulation and showed the improved noodle-cooking and texture quality apparent from a reduced optimum cooking time and increased water absorption capacity with cooking loss within acceptable limits. It was evident that wheat varieties with different inherent properties produced noodles of acceptable quality upon adding porous starch at different concentrations. Upon evaluating the quality parameters of noodles, it was concluded that a 5% addition of porous tapioca starch was the most desirable. However, the findings from this study are limited to the most popular wheat classes for udon-making. Still, it allows for exploring other classes, such as APWN or combinations of ANW/APWN, using a similar study design. The current findings could be valuable for noodle manufacturers to produce udon noodles from hard and soft wheat flour by adding starch with varied porosity and achieving desirable features. We suggest further research on the eating quality (noodle sensory properties) of udon noodles with the added porous tapioca starch, and investigations of interactions between wheat flour components and porous starch in the noodle matrix.


ADC1 > ADC0 in the right visual cortex and left dentate nucleus, positively correlated with multiple abnormal perinatal and neurodevelopmental parameters. The van Rooij score was significantly higher in children presenting with sleep disorders. Conclusions: ADC values could be used as prognostic biomarkers to predict children’s neurodevelopmental outcomes. Further studies are needed to address these crucial topics and validate our results. Early and multidisciplinary perinatal evaluation and the subsequent re-assessment of children are pivotal to identify physical and neuropsychological disorders to guarantee early and tailored therapy.Background: Hypoxic-ischemic encephalopathy (HIE) is a severe pathology, and no unique predictive biomarker has been identified. Our aims are to identify associations of perinatal and outcome parameters with morphological anomalies and ADC values from MRI. The secondary aims are to define a predictive ADC threshold value and detect ADC value fluctuations between MRIs acquired within 7 days (MR0) and at 1 year (MR1) of birth in relation to perinatal and outcome parameters. Methods: Fifty-one term children affected by moderate HIE treated with hypothermia and undergoing MRI0 and MRI1 were recruited. Brain MRIs were evaluated through the van Rooij score, while ADC maps were co-registered on a standardized cerebral surface, on which 29 ROIs were drawn. Statistical analysis was performed in Matlab, with the statistical significance value at 0.05. Results: ADC0 < ADC1 in the left and right thalami, left and right frontal white matter, right visual cortex, and the left dentate nucleus of children showing abnormal perinatal and neurodevelopmental parameters. At ROC analysis, the best prognostic ADC cut-off value was 1.535 mm Hypoxic-ischemic encephalopathy (HIE) is a severe pathology affecting 0.5–1/1000 live births in Western countries, presenting a mortality rate varying between 10 and 60% and neurodevelopmental sequelae affecting nearly 23% of children , and theLiterature has shown that therapeutic hypothermia can improve patients’ prognoses and has become routine practice in the field of therapy for HIE ,3,7. VarIdentifying early and non-invasive biomarkers to predict children’s prognoses and neurodevelopmental outcomes is particularly complicated in children with moderate disease, and it is crucial to provide fact-based awareness to worried parents and to plan an early, multidisciplinary, and tailored treatment for patients ,13,14,15The primary objectives are to identify associations between both the neurodevelopmental outcome of hypoxic-ischemic encephalopathy at 1 year and the perinatal clinical-laboratory parameters with (a) brain anomalies in MRI, scored by van Rooij et al. , and (b)The secondary objectives are (c) to identify an ADC threshold value to differentiate patients in relation to their prognosis; (d) to detect fluctuations in brain ADC values between MRIs acquired within 7 days (MRI0) and at 1 year (MRI1) of life; and (e) to correlate fluctuations in ADC values with perinatal and neurodevelopmental parameters.Our retrospective observational study was conducted in accordance with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was approved by the Institutional Review Board and the Research Ethics Committee of the Bambino Gesù Hospital of Rome . Written informed consent was obtained from the parents of all individual participants included in the study before MRI scans and before therapeutic procedures.Patients were retrospectively and consecutively recruited from the archive of our institution by a neonatologist with 30 years of experience in the time frame 1 January 2013 to 30 June 2020. Inclusion criteria encompassed: gestational age between 36 and 40 weeks, diagnosis of HIE made at birth, therapeutic hypothermia performed within 6 h of birth, and high-quality MRI performed within 7 days and at 1 year of birth, including at least T2WI and DWI/ADC sequences. The parameters used to define high-quality MRIs were as follows: absence of motion degradation, absence of significant artifacts that could have impaired the exam evaluation, and sequences covering the entire brain. Exclusion criteria were: significant comorbidities, such as intracranial or systemic tumors, infections, or severe malformations; maternal risk factors, such as drug or alcohol abuse; and incomplete data, including perinatal clinical data, laboratory data, and neurodevelopmental data at 1 year.The following patients’ data were collected and reported in an anonymized database: demographic characteristics; gestational age; eutocic or dystocic delivery ; perinatal therapies; perinatal complications ; perinatal laboratory values ; ten-minute Apgar score; children’s neurodevelopment at 1 year, scored using the Bayley III coded scale ; and quaThe final cohort of patients consisted of 51 subjects presenting with moderate HIE .Newborns were either placed on their backs in carrying mats , which can ensure the maintenance of the position and avoid motion artifacts or were sedated. Infants requiring mechanical ventilation and/or anticonvulsant therapy received an increase in sedative and/or anticonvulsant dosage before the scan. Ear protectors were placed in patients’ ears before scanning. The temperature was kept stable, and vital signs, such as heart rate and oxygen saturation, were monitored by a pediatric anesthesiologist with 30 years of experience.Brain MRIs were performed within 7 days and at 1 year from birth, following therapeutic hypothermia, on the same 3T scanner  with a 32-channel brain coil (L-W-H: 440 mm 330 mm 370 mm) and using the following protocol: axial TSE T2 ; coronal TSE T2 ; axial DWI ; and 3D T1 MPRAGE .Brain MRIs were evaluated and scored with the van Rooij score  by two pADC maps were generated from DWI sequences in all newborns and then co-registered on a standardized cerebral surface, which is widely used in pediatric studies . On the Statistical analysis was performed in Matlab, with the statistical significance value at 0.05.To identify correlations of both patients’ perinatal parameters and neurodevelopmental outcomes with imaging findings from the MRI acquired within 7 days scored by the van Rooij score, a logistic regression analysis was performed; to identify associations of both patients’ perinatal parameters and neurodevelopmental outcomes with ADC values measured in the ROIs, we performed a linear regression analysis.Receiver operating characteristic (ROC) analyses were realized for each ROI in relation to the perinatal clinical and laboratory parameters and in relation to the neurodevelopmental parameters at 1 year. The ADC threshold value to differentiate patients in relation to their prognosis was calculated by using the maximum Youden J index.t-test. To identify possible ADC differences in MRIs acquired at 1 year of life among subjects in relation to perinatal and neurodevelopmental parameters, a linear regression analysis was performed.For longitudinal analysis, ADC0 (ADC of MRI0) and ADC1 (ADC of MRI1) were firstly regrouped by each perinatal and neurodevelopmental parameter. To detect fluctuations in brain ADC values between MRI0 and MRI1, we compared ADC0 and ADC1 values for each ROI using a paired The final cohort of patients consisted of 51 subjects presenting moderate HIE . PatientIn patients presenting with signal abnormalities at MRI0, the median van Rooij score was 3.1 ± 2.7 (SD/standard deviation).No significant correlations were found between the van Rooij score and the perinatal parameters.p < 0.014).A significant correlation was identified between the van Rooij score and the evidence of sleep disorders , showing motor abnormalities at Bayley III (p < 0.015), and needing physiokinesitherapy (p < 0.044); in the right thalamus in patients presenting with sleep disorders (p < 0.041) and showing motor abnormalities at Bayley III (p < 0.021); in the left frontal white matter in patients presenting with sleep disorders (p < 0.022) and showing motor abnormalities at Bayley III (p < 0.014); and in the right frontal white matter (p < 0.046) and in the left dentate nucleus in patients presenting with motor abnormalities at Bayley III (p < 0.028)  .2/s × 10−6 in the ROI drawn in the right frontal white matter, the outcome parameter with the highest area under the curve (AUC) (0.856) was the presence of sleep disorders at 1 year, presenting a sensitivity of 80% and a specificity of 86% . ADC1 values were higher compared to ADC0 in the right visual cortex and left dentate nucleus and positively correlated with multiple abnormal perinatal parameters and compromised neurodevelopmental outcomes.We found some significant correlations between perinatal and outcome parameters and imaging. In particular, the van Rooij score was significantly higher in children presenting with sleep disorders at 1 year of life, and ADC0 was significantly lower in children showing abnormal perinatal parameters and compromised neurodevelopmental outcomes in the left and right thalami, left and right frontal white matter, right visual cortex, and left dentate nucleus. The optimal ADC cut-off value was identified in the right frontal white matter  (0.856) was the presence of sleep disorders at 1 year, presenting a sensitivity of 80% and a specificity of 86%.Finally, in ROC analysis and for the cut-off of 1.535 mmThe results of the ROC curve, together with the results of the ADC analysis and the van Rooij score, are particularly interesting since the presence of sleep disorders seems to be the most consistent and relatable parameter investigated, even if this pathology is rarely assessed in HIE patients.In particular, we only included patients presenting with high-quality MRIs acquired within 7 days. The identification of lower ADC values in MRIs performed within 7 days indicated restricted diffusion in areas that are extremely sensitive to hypoxic-ischemic insult and corresponded with cytotoxic oedema, leading to irreversible lesions secondary to cell death . The MRIADC1 values tend to diffusively grow across the ROIs, and a significant increase in ADC1 values compared to ADC0 values in the right visual cortex and the left dentate nucleus was observed for both multiple outcome and perinatal parameters.In literature, the difference between MRIs acquired within and after 7 days of birth extensively described an increase in ADC values in relation to the pseudonormalization phenomenon ,41, but The identification of an increase in ADC values in MRIs performed at 1 year, compared to ADC values performed within 7 days, is related to a persistent and significantly high ADC value. Its correlation with perinatal and outcome parameters at 1 year excludes normalization and suggests, instead, an ischemic scar in different brain areas following HIE.Accordingly, the correlation of ADC1 values increased with multiple abnormal perinatal and outcome parameters, suggesting that the severity of the HIE is a key factor in defining brain damage. On the other hand, the reduced number of brain areas identified in MRI1, compared to the higher number of areas identified in MRI0, may be explained by the proven effectiveness of therapeutic hypothermia, which reduces cerebral injury burden and improves patients’ prognoses ,7.The crucial importance of identifying prognostic biomarkers in HIE and of correctly diagnosing and classifying neonates according to the severity of their pathology fueled a vast amount of literature, some of which efficiently applied AI to provide quantitative findings to stage neonates affected by HIE . Our resThe first limitation of the present study is the absence of a group of patients matched for HIE severity, age, and sex who did not undergo therapeutic hypothermia. Therapeutic hypothermia has been proven to significantly improve pediatric patients’ prognoses, and therefore, it is not ethically acceptable to randomly assign patients to therapy or placebo in case of hypothermia indications. The second limitation is the imbalance between patients with good prognoses and patients presenting with severe prognoses at 1 year. These data are justified by the positive effects of therapeutic hypothermia and by the strict protocols that our institution applied to guarantee early diagnosis and therapy to children.2/s × 10−6, measured in the right frontal white matter, presented a sensitivity of 80% and a specificity of 86% when predicting children’s prognoses at 1 year of life. ADC1 values tended to globally increase, compared to ADC0 values, with particular evidence in the right visual cortex and left dentate nucleus, and were positively correlated with multiple abnormal perinatal parameters and compromised neurodevelopmental outcomes. The van Rooij score was significantly higher in children presenting with sleep disorders at 1 year of life.ADC values in MRI0 were significantly lower in children showing abnormal perinatal parameters and compromised neurodevelopmental outcomes in the left and right thalami, left and right frontal white matter, right visual cortex, and left dentate nucleus. In particular, at ROC analysis, an ADC threshold value of 1.535 mmOur study highlights the need for a comprehensive MRI study of HIE and underlines the importance of the DWI/ADC sequence for children’s evaluations. ADC values can be used as prognostic biomarkers to predict children’s neurodevelopmental outcomes and provide parents with the most-required information related to patients’ prognoses, which can help them understand and agree with the medical personnel on the best therapy for their children. Further studies are needed to address these crucial topics and validate our results.Moreover, the results suggest the key importance of early and multidisciplinary perinatal evaluation and subsequent re-assessment of children to identify physical and neuropsychological disorders to guaranteeearly and tailored therapy.


Osteoporosis is a chronic multifactorial condition that affects the skeletal system, leading to the deterioration of bone microstructure and an increased risk of bone fracture. Platelet-derived biomaterials (PDBs), so-called platelet concentrates, such as platelet-rich plasma (PRP) and platelet-rich fibrin (PRF), have shown potential for improving bone healing by addressing microstructural impairment. While the administration of platelet concentrates has yielded positive results in bone regeneration, the optimal method for its administration in the clinical setting is still debatable. This comprehensive review aims to explore the systemic and local use of PRP/PRF for treating various bone defects and acute fractures in patients with osteoporosis. Furthermore, combining PRP/PRF with stem cells or osteoinductive and osteoconductive biomaterials has shown promise in restoring bone microstructural properties, treating bony defects, and improving implant osseointegration in osteoporotic animal models. Here, reviewing the results of in vitro and in vivo studies, this comprehensive evaluation provides a detailed mechanism for how platelet concentrates may support the healing process of osteoporotic bone fractures. Osteoporosis is a systemic metabolic disorder causing a decrease in bone mineral density (BMD) and microstructural impairment . Accordiγ) [γ in the enhancement of osteoclastic activation through the receptor activator nuclear factor kappa B ligand (RANKL) signaling pathway [The mechanism of osteoporosis is caused by a disbalance in the bone remodeling cycle with more resorption which results in trabecular bone loss, thinning in the cancellous bone, reduced cortical thickness, and enhanced porosity . These pγ) . Studies pathway , 12. The pathway –15.Among the pharmacological treatments approved by the FDA, bisphosphonates are one of the main choices used to reduce the risk of spine and hip fracture by approximately 50% . HoweverTherefore, although the current medications have exerted satisfactory results, their adverse effects have encouraged researchers to seek novel approaches for the treatment of osteoporosis and its related fractures. Since osteoporosis management should be based on tissue regeneration principles –20, therIn light of novel therapeutic methods utilized in osteoporosis management, the aim of this review article was to evaluate the current evidence based on existing literature concerning the therapeutic effect of PDBs on osteoporosis treatment. The second goal was to provide new insights to further enhance the efficacy of these approaches for future clinical applications, with a main focus on the most recent advancements, possible challenges, and future prospects.Nowadays, PDBs are a promising treatment option in regenerative medicine strategies with primary research focusing on their development and improvements , 26. PlaPDBs are classified based on their preparation protocol and whether or not an anticoagulant is added during their preparation . The firIn 2017, the low-speed centrifugation concept (LSCC) was introduced . AccordiSeveral studies have demonstrated the effectiveness of platelet concentrates for the treatment and management of osteoporosis Tables  and 3 2, 56–64. th week after the first injection [In this section, our aim is to provide a thorough evaluation of the outcomes related to the use of PDBs for osteoporosis when administered throughout the body. In this regard, Sheu et al.  have recnjection . The micnjection . In all njection  concludenjection , PRFr wanjection . Both thnjection , 23. In njection . Althougnjection  performenjection , 23; howSince MSCs therapy for the treatment of osteoporosis is relatively expensive and more complicated than the utilization of platelet concentrates , Liu et In addition to the aforementioned studies evaluating the efficacy of PDBs in the treatment of osteoporosis through IV injection, one study has utilized the bone marrow transplantation approach to assess the efficacy of PDBs on osteoporosis. In this study , NIH3T3 In addition to the systemic administration of PDBs, their local administration has also been extensively discussed in the literature. The ensuing sections present a comprehensive evaluation of the outcomes associated with the local administration of platelet concentrates.The treatment of local bony defects and fractures in patients with osteoporosis can be quite challenging due to the reduced capacity of bone regeneration and weakened strength of the bone. However, the local application of PDBs has been shown to have a positive impact on bone structure, accelerating the healing process and promoting bone regeneration.β-tricalcium phosphate (β-TCP) sponge was compared to PBS + gelatin/β-TCP sponge and the control group (defects with no treatment) for the treatment of an osseous defect in the third lumbar vertebral spine. The micro-CT results indicated that by the 4th week, bone tissue was observed in both the PRP + gelatin/β-TCP sponge and the PBS + gelatin/β-TCP sponge groups. Nevertheless, there was a significant increase in the bone volume in the group treated with PRP compared to the group treated with PBS at 8 and 12 weeks postop (P < 0.05) [β-TCP sponge had significantly higher stiffness (P < 0.05) [P > 0.05) [In order to manage the vertebral bone defects in osteoporosis, Cho et al.  evaluate < 0.05) . This sh < 0.05) . Moreove < 0.05) . The sam > 0.05) . Amid th > 0.05) , 60. Tho > 0.05) , 23, 37,In another study by Engler-Pinto et al. , the appμL), or/and BMSCs (1 × 106 cells). Based on the micro-CT results, the only groups that showed significant improvements between the 42nd and 7th day postoperatively in trabecular number, trabecular separation, trabecular connectivity density, and BV/TV ratio were the groups treated with PRP-alone and PRP + BMSCs , However, it is shown that the combined application of PDBs and MSCs may not necessarily induce synergistic effects . In a stOsteoporosis can also affect the bone microarchitecture which also results in more complex healing of fractures and osseous defects . Since i2 nanoporous modification with PRP on implant stability in an osteoporotic rat model. Prior to implant placement, 0.1 mL/leg PRP was injected into the bone marrow cavity of the tibias of each rat, and the implants were placed in the medullary canal of the tibias [2 nanoporous modification could significantly enhance osseointegration (P < 0.05). In addition, the combined application of PRP and the modified implants showed significantly better results in most of the measurements, including bone volume to total volume ratio, trabecular number, trabecular spacing, and trabecular connectivity density [In this regard, Zhu et al.  have inve tibias . The res density . Accordi density . These r density . ArguablConcerning the efficacy of PRP on the osseointegration of titanium implants, in another study by Qiao et al. , the latP < 0.05) [P < 0.05) [Moreover, Sun et al.  evaluate < 0.05) . However < 0.05) . The hig < 0.05) . The res < 0.05) , 64. Thi < 0.05) , 62, 64.μm) had significantly less gap width compared to the sole application of calcitonin with implants (1.85 ± 0.52 μm) and the group of implants alone (5.98 ± 0.74 μm) (P < 0.001). Moreover, upon assessment of the percentage of implant surface area covered with bone, it was similarly demonstrated that the group containing both calcitonin and PRF (95.68 ± 2.7%) had significantly higher values compared to the sole application of calcitonin with implants (54.26 ± 4.1%) and the group of implants alone (21.76 ± 4.8%) (P < 0.001). The authors have concluded that the combined application of the local PRF and systemic calcitonin can be an effective technique to accelerate and enhance bone regeneration and osseointegration around bone implants [Among the aforementioned studies assessing the impact of PDBs on osseointegration –64, no simplants . The varimplants  were morimplants –64.As mentioned previously, numerous studies have explored the use of systemic and local administration of PDBs , 56–64. The systemic administration of platelet concentrates has demonstrated potential for enhancing bone microstructure in a generalized manner, leading to improved bone healing and regeneration throughout the skeletal system. Consideration may be given to systemic administration as a supplementary therapy to promote overall skeletal health. On the other hand, local administration of platelet concentrates has shown notable benefits for osteoporotic bone structures. It promotes bone regeneration and osseointegration in proximity to bone implants, while also stimulating osteogenic differentiation and counteracting the propensity toward adipogenic differentiation within the bone structure. The utilization of local administration can be contemplated as an adjunct treatment option for targeted enhancement of bone regeneration and osseointegration.Given the extent of the disease and patient-specific factors, the choice between local and systemic administration of PDBs should be carefully considered. Further investigation is needed to better understand the nuances associated with each approach, to assess the magnitude of their effects, and to achieve more conclusive results.β-catenin pathway. BMPs activate RUNX2 through phosphorylation of SMAD1/5/8, while Wnt proteins increase RUNX2 levels via β-catenin stabilization or protein kinase Cδ [Bone hemostasis or remodeling is a continuous process in which new bone tissue is formed by osteoblasts through bone formation, and mature bone tissue is broken down by osteoclasts through bone resorption  Figure . Osteoblinase Cδ . On the inase Cδ . RANKL, inase Cδ .α (TNF-α). These compounds directly stimulate greater formation and activity of osteoclasts. The reduced levels of OPG also allow for stronger binding of RANKL to RANK, further facilitating increased osteoclastogenesis and bone resorption [γ plays a crucial role by promoting adipogenic differentiation of BMSCs by regulating the expression of adipogenic genes [In contrast to bone hemostasis, osteoporosis is caused by an imbalance in the bone remodeling process. Osteoporosis leads to a decrease in the secretion of OPG by osteoblasts and an increase in the expression and secretion of RANKL, interleukin 1(IL-1), IL-6, IL-11, and tumor necrosis factor sorption . In addiic genes .γ and leptin which are indicators of adipogenic differentiation. On the other hand, the transcriptional and translational markers of osteogenic differentiation  enhance due to the presence of platelet concentrates [β (TGF-β). It has been demonstrated that PDGF can induce osteoblast proliferation and differentiation [β1 has been shown to have inhibitory effects on adipogenic differentiation while also exhibiting positive effects on osteogenic differentiation [According to the existing evidence, PDBs seem to reverse osteoporosis by enhancing the number of osteoblast-like cells and inducing osteogenic differentiation while inhibiting adipogenic differentiation . The traentrates . In addientrates . PDBs alentrates , includintiation , 80. Morntiation . Furtherntiation , 82–84. ntiation , 85. In ntiation , 3T3-L1 ntiation . On the ntiation . This prntiation .The potential therapeutic effects of platelet concentrates specifically in osteoporotic patients can also be explained by the fact that platelets' function and morphology tend to exhibit deviations from normal function in the population of people with osteoporosis . The evaBased on the evidence concerning the importance of platelet function and morphology in patients with osteoporosis , it can To evaluate the suitability of PDBs for treating osteoporosis, it is important to compare their efficacy, safety, and adverse effects with the established pharmacological treatment approaches currently used. Since bisphosphonates are widely used as the standard treatment options for osteoporosis in clinical practice , we haveRegardless of their safety and adverse effects, bisphosphonates have been extensively studied and proven to effectively reduce the risk of bone fractures. However, their efficacy can vary depending on various factors such as bone density, age, and other individual risk factors . On the In terms of safety and adverse effects, PDBs are generally considered safe and have a low risk of adverse effects. This is primarily due to their autologous nature, which reduces the chances of immune reactions , 47. HowUntil now, no study has comprehensively reviewed platelet concentrates and their effect on osteoporotic defects. Undoubtedly, outcomes from these studies decisively suggest the beneficial effects of platelet concentrates to minimize the detrimental impact of osteoporosis and also improve the healing process of bone , 56–64. In addition, outcomes from the administration of the new generation of liquid platelet concentrates called I-PRF have shown promising outcomes in regenerative medicine, especially bone tissue regeneration , 23, 37.Furthermore, this review article showed that many more studies were conducted on the local administration of PDBs in comparison to their systemic administration. Even though the local administration of platelet concentrates has shown positive results in all the studies , 57–64, Considering the limitations of this review, it can be concluded that both the local and systemic administration of platelet concentrates can have a beneficial effect on osteoporotic bone structures. However, the magnitude of such an effect and the choice of systemic versus local administration of platelet concentrates are dependent upon the vastness of the disease. Based on the molecular and cellular mechanisms regarding the effects of platelet concentrates on osteoporosis, arguably, PDBs can reverse adipogenic differentiation towards osteogenic differentiation. Although the results of the existing studies seem promising, it must be emphasized that all studies to date were conducted using in vitro and nonhuman in vivo models. Therefore, further future clinical studies are needed to ensure the clinical efficacy of platelet concentrates in patients diagnosed with osteoporosis.


N-methylmorpholinium salts with varying N-alkyl chains and Cl−, OAc− and OH− as counter ions have been synthesized and investigated for their ability to dissolve cellulose, aiming at elucidating solvent structural features affecting cellulose dissolution. Synthesis procedures have been developed to, to a high extent, rely on conversions in water and microwave-assisted reactions employing a reduced number of work-up steps and ion-exchange resins that can be regenerated. Water solutions of morpholinium hydroxides proved capable of dissolving cellulose, with those of them possessing alkyl chains longer than ethyl showing surprising dissolution ability at room-temperature. Morpholinium acetates behaved as ionic liquids, and were also capable of dissolving cellulose when combined with DMSO. The obtained cellulose solutions were characterized according to their chemical and colloidal stability using 13C NMR spectroscopy, size exclusion chromatography and flow sweep measurements, while the ethanol coagulates were investigated in terms of crystallinity using solid state NMR. In contrast, the morpholinium chlorides obtained were hygroscopic with high melting points and low solubility in common organic solvents e.g., acetone, DMSO and DMAc, thus lacking the ability to swell or dissolve cellulose.A series of  N-methylmorpholinium salts with varying N-alkyl chains and Cl−, OAc− and OH− as counter ions have been investigated for their ability to dissolve cellulose aiming at elucidating solvent structural features affecting cellulose dissolution.A series of  However, cellulose does not melt4 as its melting point is higher than its degradation temperature.5 Consequently, one critical prerequisite for the processing of this important polysaccharide  is its dissolution – a highly challenging process due to the extensively stabilized hierarchical organization of cellulose. Equatorially positioned hydroxyl groups in a cellulose chain promote, both intramolecular H-bonding within the chain as well as intermolecular H-bonding between the neighboring chains. The former leads to flat chain conformation, stiffness, and the tendency to crystallize while the latter stabilizes a sheet-like structure and promotes stacking of the sheets on top of each other through exclusion of water and van der Waals interactions . Thus, cellulose is amphiphilic and has highly ordered supramolecular structure extending to organization in semicrystalline fibrils. These fibrils are further arranged in a layered hierarchical morphology of a cellulose fiber making it largely insoluble in the most commonly used solvents. Hence, the main challenge is to develop a solvent capable of overcoming the mentioned amphiphilicity and preventing attractive interactions in a dissolved state.Cellulose, being the most abundant biopolymer on Earth, occurs naturally as the main structural polymer of the cell wall in higher plants as well as in algae, tunicate and bacteria. Since it is biodegradable, biocompatible and possesses thermal and chemical stability,2/NaOH(aq) is used as a derivatizing solvent in which cellulose is transformed to NaOH(aq) soluble cellulose xanthate. However, CS2 is toxic and flammable polluting agent. In lyocell process, N-methylmorpholinium-N-oxide (NMMO) monohydrate which is non-toxic, fully biodegradable and fully recyclable is being used.6,7 But this solvent is prone to exothermic and oxidative reactions since it is a strong oxidant and is sensitive to alkylating and acylating agents and redox-active transition metal ions.8 Development of ionic liquids capable of dissolving cellulose9–11 should also be mentioned in this context as it has opened new avenues for shaping and modifying cellulose,12,13 with the recycling of the solvent remaining as one of the main challenges. N,N-dimethylacetamide (DMAc)/LiCl is another well-studied solvent mainly used in gel permeation chromatography (GPC) for evaluating molecular weight distribution of cellulose14 as well as for its homogeneous functionalization. Yet, since traces of water or impurities hamper its potential for cellulose dissolution, its application in industrial scale has not been possible.15,16 Therefore, there is a need to overcome the aforementioned setbacks with the already existing solvents and promote sustainable processes which makes aqueous cellulose solvents particularly attractive.In this regard, two dissolution systems have been of particular commercial importance. In viscose process, CS17,18 However, most of the untreated cellulose showed partial dissolution. Later on, application of different additives such as ZnO, urea, thiourea and polyethylene glycol was evaluated aiming at dissolution enhancement.19–23 Even though NaOH is inexpensive and easily recycled, limited solvent concentration range needed for cellulose dissolution, required low temperature, low dissolution capacity for high-molecular weight cellulose and, instability of solutions over time remain as major disadvantages of this system.17,24,25 Yet, another group of aqueous hydroxide solvents that has been the subject of extensive studies is quaternary ammonium hydroxides, initially patented by Lilienfeld.26 Later, a number of quaternary ammonium hydroxides (QAHs) were reported to be capable of dissolving cellulose, namely, tetramethylammonium hydroxide (TMAH),27 tetraethylammonium hydroxide (TEAH),28 tetrabutylammonium hydroxide (TBAH),29 benzyltrimethylammonium hydroxide (Triton B) and dimethylbenzylammonium hydroxide (Triton F).30,31 Apart from hydroxides, a few other anions were combined with QAs, some of combinations showing a promising dissolution ability, such as tetrabutylammonium fluoride (TBAF)/DMSO,32 tetrabutylammonium acetate (TBAOAc)/DMSO,33 triethylmethylammonium carboxylates,34,35 tetraalkylammonium trialkylphosphates36,37 and tetraalkylammonium chlorides as well as their mixture with DMA.38In early 1930s, Davidson discovered that NaOH(aq) is able to dissolve cellulose in limited range of concentrations and at low temperatures.N,N-dimethylmorpholinium hydroxide (NDMMOH(aq)) showing improvement in terms of dissolution capacity and stability of the dissolved state (in relation to NaOH(aq)).39 In continuation to that work and aiming towards better understanding of the structural requirements of a solvent pertaining to enhanced cellulose dissolution, it was of high interest to investigate other morpholinium derivatives combined with not only hydroxides but also other counter ions, such as Cl− and OAc−, both of them earlier reported as components in a number of efficient cellulose solvent.38,40–46 In this work, we hypothesize that the N-chain length of the morpholinium cation, as well as the nature of the counterion, critically affect solvent ability to dissolve cellulose.Inspired by the NMMO, while striving for water-based hydroxides, our group developed a new aqueous morpholinium-based hydroxide solvent, −, OAc− or Cl− anions and assessment of their potential towards cellulose dissolution, seeking to relate structural features to required dissolution conditions and the stability of the dissolved state. Even though use of some aprotic organic solvent could not be avoided, the synthetic procedure reflects our efforts to, as far as possible, maximize use of water-based steps, reusable ion-exchange resins and microwave-assisted reactions along with a minimized number of work-up steps.Thus, we here report the development of several morpholinium derivatives with varying alkyl chain length combined with OH3 g−1 (measured by pulp dissolution in bis(ethylenediamine)copper(ii) hydroxide solution (CED) using capillary viscosimetry according to the SCAN-C 15:99 method) was provided by Domsjö. N-Methylmorpholine, allyl chloride bromoethane, 1-bromopropane, diethyl ether, iodomethane, 1-bromobutane and anhydrous DMSO were purchased from Sigma-Aldrich. 1-Bromoheptane were purchased from Merck and 1-bromoheptane was purchased from Alfa Aesar. Acetonitrile was provided from VWR Chemicals. Purolite SGA550OH (1.10 equiv. OH− per L) as well as Amberlite-IRA410 chloride form (1.25 equiv. Cl− per L) were used as the anion-exchange macroporous resin and washed with methanol before packing the column. Acetic acid and HCl were purchased from Fisher Scientific . All the chemicals were used as received without further purification. Silver(i) oxide was purchased from Alfa Aesar and used as received. Methanol, isopropanol, THF, ethyl acetate and acetone were provided by Friedrich-Schiller-Universität Jena.Acid washed cellulose powder from spruce with DP ∼ 350 was purchased from Fluka (product no. 22182) and dried at 60 °C in a vacuum oven for 4 h prior to use. Sulfite dissolving grade pulp from softwood with intrinsic viscosity 442 cmN-methylmorpholine (0.2 mol), 1-bromoalkane (0.25 mol) and acetonitrile 120 ml were added to a round bottom flask and depending on the reactivity of the corresponding 1-bromoalkene, different temperature (between 70 and 80 °C) and reaction times  were required as provided in detail in ESI.In a typical synthetic procedure, N-heptyl-N-methylmorpholinium bromide (HMMorBr) followed a different procedure, namely a microwave-assisted reaction due to the low reactivity of 1-bromoheptane. N-Methylmorpholine , 1-bromoheptane , and 9 ml acetonitrile were added and mixed well. The reaction was performed in capped microwave vials  using a Biotage Initiator-8 microwave synthesizer. The temperature was set to 90 °C for 2 h with stirring rate of 780 rpm and a pre-stirring of 10 s.The synthesis of A general synthesis of MorCl chlorides started from their bromide precursors. A column was packed with Purolite SGA550OH ion exchange resin with the mole ratio of 2 : 1 resin to MorBr. The desired bromide salt was dissolved in methanol to the final concentration of 0.1 M and passed through the column with the flow rate of 1 drop per second. Later, the column was washed with 400–500 ml of methanol and the solution was neutralized with 1 M HCl. Subsequent removal of the solvent using rotatory evaporation and later vacuum drying gave white hygroscopic salt. For more details on the synthesis of each salt, the reader is referred to the ESI.†The synthesis of MorOAc started from MorBr followed by an ion-exchange of bromide to hydroxide using Purolite SGA550OH as mentioned above. After washing the column with 400–500 ml methanol, stoichiometric amount of 1 M acetic acid was added to the hydroxide solution and the mixture was stirred vigorously overnight. The excess of the solvent was removed using a rotatory evaporator and the yielded light-yellow solution was further dried in vacuum oven at 60 °C for 72 h. The water content measured by Karl-Fischer titration varied between 0.76 and 2.06 wt%.et al., 2021). Typically, 0.06 mol of MorBr was added to 15–20 ml distilled water in a 45 ml centrifuge vial and 0.04 mol of silver(i) oxide (9.26 g) was added to the solution. The vial was sealed tightly to avoid further contact with air and the mixture was stirred at room temperature for approx. 5 h. Colored precipitates of silver bromide were formed as soon as stirring began and by the end of the reaction, the excess grey silver(i) oxide remained unreacted. Lastly, the obtained solution was centrifuged, and the supernatant containing MorOH(aq) was isolated and kept refrigerated.Aqueous solutions of MorOH were synthesized using our previously reported protocol  concentrations from 0.8–2.3 M was prepared by diluting the concentrated solvent with distilled water. The desired amount of cellulose powder was added to each solution to a final concentration of 3 wt% and stirred at room temperature for 5 min to yield a well-dispersed suspension. The suspension was then placed in a freezer at −25 °C for 20 min, after which it was thawed under constant stirring to remove any ice formed and thereby yield a transparent solution.To investigate pulp dissolution, 1 wt% pulp was added to 2 M EMMorOH(aq) and stirred at room temperature. After 20 minutes a droplet of the solution was taken for investigation using an optical microscope.Cellulose solutions were prepared according to the method described above. Then the solutions were added to large excess of ethanol and stirred for a few minutes. Then the solutions were filtered, and the precipitates were added again to ethanol and stirred properly, filtered, and washed with excess of ethanol to ensure solvent removal. Finally, the samples were air dried.1–2 mg of the synthesized salt was weighed using Sartorius ME36 S and the elemental analysis was performed by HEKAtech Euro EA3000 analyser.Melting point of the solids was measured using a Mettler Toledo HS1 hot stage controller equipped with HS84 DSC microscopy cell and a Zeiss microscope to monitor the melting of the crystals.2O) were obtained with Bruker Avance 500 MHz spectrometers with 16 scans for 1H NMR (500 MHz) and up to 1024 scans for 13C NMR (125 MHz) at 25 °C.NMR spectra of the synthesized MorBr, MorOAc and MorCl (in Dd6 or D2O) were obtained on a Varian (400 MHz) spectrometer equipped with One NMR probe at 25 °C.NMR spectra of the synthesized NDMMI and MorOH , a cell without diaphragm and Karl-Fischer-Reagent  were used for the water determination. The water content is reported in ppm.Concentration of the obtained MorOH(aq) was determined using an SI analytics autotitrator. 1 ml of the MorOH(aq) was diluted with 30 ml of distilled water and titrated against 1 M HCl. The concentration was calculated using the titrant volume at the equivalence point.Dissolution of cellulose was investigated using microscopic observations (ZEISS SteREO Discovery.V12) by placing a small droplet of the solution on a slide glass that was pressed using a cover slip in a microscope using cross-polarized light equipped with a camera at ambient temperature. Dissolution was confirmed when no particles could be detected, whereas the solubility limit was reached as soon as a crystal could be observed.13C NMR measurements and spectra were collected every 1 h over 22 h on the same sample.To assess the stability of cellulose solutions in MorOH(aq) as they were prone to color change over time , freshly−1 were measured using a TA Discovery Hybrid Rheometer (HR-3), with a sandblasted 40 mm plate–plate geometry with a gap of 500 μm and the temperature was controlled with a Peltier plate with circulating cooling liquid. Samples were measured directly after dissolution, a water-filled solvent trap was used to avoid solvent evaporation while running rheology measurements and the rheometer was brought to the desired temperature without pre-shearing. In addition, increasing temperatures was conducted in series on the same sample.Flow sweep measurements of cellulose solutions in different solvents at 0, 25, 50 and 55 °C at shear rates of 1–500 sWhen running measurements using morpholinium acetates silicon oil was applied around the border of the geometry after applying the selected gap as well as the solvent trap to avoid the moisture uptake.−1 operating at 70 °C. Pullulan polysaccharides obtained from Polymer Lab with molecular masses of 708 000, 344 000, 200 000, 107 000, 47 100, 21 100, 9600 and 6100 Da were used as calibration standards.A chromatography system from Polymer Laboratories, comprised of a PL-GPC 220 with an RI detector, was employed for SEC. It included a set of guard column mixed-A 20 μm (7.5 × 50 mm) and 2 mixed-A 20 μm (300 × 7.5 mm), also from Polymer Laboratories, connected in series. The mobile phase contained 0.5 w/v% LiCl/DMAc with flow rate of 1 ml minPrior to analysis, 25 mg of the sample was solvent-exchanged 3 times with 5 ml of methanol for 30 min, followed by a further 3 time solvent exchange step using DMAc for 30 min. The excess of DMAc was then removed and 5 ml of 8% (w/v) LiCl/DMAc was added and left overnight at ambient temperature with mild magnetic stirring. This sample was thereafter diluted with 20 ml of DMAc.1H decoupling with a ‘‘spinal64’’ decoupling scheme at 67 kHz was applied during the acquisition. The cross-polarization (CP) contact time was set to 1.5 ms and the repetition time to 2 s. CP spectra for comparison were recorded with 4000 signal accumulations. The crystallinity was estimated according to Sparrman et al.47 using 128 signal accumulations using the integral of C1.Regenerated cellulose was subjected to solid-state NMR experiments carried out on a Bruker Avance III 500 MHz spectrometer equipped with a 4 mm HX CP MAS probe. Experiments were recorded at a magic angle spinning (MAS) rate of 10 kHz and the temperature was set to 298 K. −, Cl− and OAc− as counterions following the general procedure shown in In continuation to our previous work on NDMMOH(aq) as a cellulose solvent, a series of morpholinium cations with different alkyl chains were synthesized and combined with OHThe obtained hydroxides were investigated for the ability of their aqueous solutions to dissolve cellulose. More specifically, the dissolution of 3 wt% cellulose (the amount commonly dissolved by the previously studied aqueous hydroxides) by the aqueous hydroxides was assessed using freeze–thaw method or stirring the solution at room temperature followed by polarized light microscopy studies. Freeze–thaw method is commonly employed to enable cellulose dissolution in aqueous hydroxides, restricted to low temperatures and possibly dependent on the impact of freezing and thawing on cellulose morphology. All the synthesized compounds dissolved cellulose in a concentration range of 1–2.3 M by freeze–thaw method , showed that in all of the solvents maximum 7 wt% of cellulose could be dissolved similar to NDMMOH(aq) reported in the previous study.13C NMR showed no detectable indications of degradation  from 1.3 M MPMorOH(aq) and 1.3 M BMMorOH(aq) after 24 h storage at room temperature as well as untreated cellulose as a reference did not show any significant degradation of cellulose in any of the solvents . A very 50,51 Interestingly, as the alkyl chain length increased the water content decreased except for MPMorOAc. Similar effect of alkyl chain length was reported for other types of ionic liquids: the increase in alkyl chain length and thus increase in hydrophobicity resulted in lower water uptake.52–54All the synthesized MorOAc , were li55 making it accessible also for larger ions, as well as enhancing the mass transport by decreasing the viscosity of MorOAc.56,57 In addition, it has been shown that solvation of IL ions by DMSO increases conductivity and ion mobility resulting in dissociation of ions.58 The DMSO solutions of acetates were yellow prior to cellulose addition and as the concentration of cellulose in the solution increased, an increase in viscosity was observed while the solution turned browner as represented in Surprisingly, none of the MorOAc were able to dissolve cellulose over a large temperature range, even at temperatures as high as 120 °C where they showed ionic liquid behavior. Even though MorOAc exhibit good mobility at elevated temperature (behaving as ionic liquids), their ions seem not to be capable of penetrating and accessing cellulose structure, most probably due to large ion sizes (where hydration with water is probably one of the contributing factors). However, in combination with DMSO, a strong swelling agent, with molar ratio of 1 : 4.6 MorOAc/DMSO dissolution was achieved at 120 °C within 15 minutes  than EMMorOAc despite containing less water. Surprisingly, in contrast to the hydroxides, the dissolution ability of acetates does not seem to be improved by increasing the length of the alkyl chain. Studies on imidazolium ILs in which the increase in alkyl chain length was shown to lead to decreased cellulose dissolution,62–64 interpret this observation as a result of a steric hindrance for the anion interaction with cellulose; thus, the shorter alkyl chain of the cation would allow for a stronger interaction between the IL and cellulose. In similar studies, it has been argued that the smaller cation would permit more anions to enrich in proximity of the polymer promoting dissolution.62 However, in case of these particular morpholinium-based solvents further detailed investigation is needed, taking also into consideration the amount of water bound by the IL.Similarly, the high temperature required for cellulose dissolution in ILs has been previously reported to promote dissociation of the ion pairs promoting, in turn, the interaction between the anion and cellulose hydroxyl groups while the cation possibly associates with cellulose hydroxyl oxygens affecting hydrogen bonding ability of cellulose.r 2.06%, , showed Similar to MorOH(aq), SEC results on cellulose precipitated from EMMorOAc/DMSO and BMMorOAc/DMSO  revealed†e.g. BMIMCl) and salts in aprotic organic solvent  the presence of water is well-known to hamper the dissolution.62,65 On the other hand, explanation for the insolubility in the polar aprotic solvents might be found in the inability of these solvents to dissociate the ion pairs (probably due to the strong interaction of selected morpholinium cations with chloride). Previous results on cellulose dissolution in quaternary ammonium fluoride (QAFs) showed a correlation between the dissolution of these salts in an aprotic polar solvent such as DMSO and their ability to dissolve cellulose: their dissociation in DMSO was pointed out as requirement for an effective interaction with cellulose anhydroglucose units.66When it comes to the prepared chloride salts , all com−1 at 0, 25, 50 and 55 °C. As shown in 67 showed that in NaOH cellulose always shows shear thinning behavior indicative of cellulose aggregates existence within the solution. However, when mixed with either TMAH or Triton B, it showed non-Newtonian behavior at high temperatures. In addition, cellulose in TMAH(aq) showed possible aggregation at low temperatures. Therefore, the obtained results in this study prove enhanced temperature stability of the dissolved state in both MorOH(aq) as well as MorOAc/DMSO. Not surprisingly, the MorOH(aq) solutions have lower viscosity than MorOAc/DMSO that also show higher viscosity dependency on temperature. It is worth mentioning that few distorted points are observed in In order to obtain information on the stability of the cellulose solutions in the obtained hydroxides and acetates at different temperatures, a series of flow sweep measurements were run applying shear rate of 1–500 st–g” conformation of the C6–OH group for the crystalline parts of cellulose I had changed into a “g–t” conformation of cellulose II.68,69 According to previous reports, formation of cellulose II is indicated when two characteristic peaks at ca. 107 and 87.5 ppm appear.70–74 Indeed, for the samples regenerated from MorOH(aq) a shoulder at 107.1 and a new peak at 87.7 ppm appear besides the increase in the peak intensity at 84 and 62.74 ppm corresponding to amorphous cellulose. However, cellulose regenerated from MorOAc/DMSO does not show the appearance of the two aforementioned cellulose II peaks, yet an increase in intensity of the peak at 84 and 62.1 ppm indicative of amorphous cellulose. Enhanced formation of crystalline regions during coagulation in the presence of water has been previously reported and attributed to a faster diffusion of solvent in the aqueous media promoting formation of crystalline aggregates, along with enchanced relaxation of cellulose chains during drying in the presence of water.75,76 The main difference between the coagulation from hydroxides and acetates when ethanol is used as coagulant in this study is, thus, probably related to their water content leading to faster diffusion of hydroxides allowing for crystalline material (cellulose II) to be obtained.According to 47 This method estimates the crystallinity using the integrals obtained from two different pulse sequences optimized for the difference in 13C T1 relaxation times for amorphous and crystalline cellulose. Here, the C1 integrals were used since the C4 and C2,3,5 peaks were overlapping. The estimated crystallinity for the reference cellulose was 0.44 which decreased upon dissolution in MorOH(aq) and MorOAc/DMSO. The estimated values were as follows: 0.36 for regenerated cellulose from BMMorOH(aq) and MPMorOH(aq), 0.29 and 0.23 for regenerated cellulose from BMMorOAc/DMSO and EMMorOAc/DMSO respectively.Degree of crystallinity was calculated using solid state NMR according to the previously reported method.With the ability of the MorOH and MorOAc/DMSO to dissolve cellulose and generate stable solutions established, it was highly interesting to attempt dissolving cellulose pulps.When 1 wt% pulp was added to EMMorOH(aq), the fibres were swollen and showed ballooning effect  which isIn summary, varying the alkyl chain length and the counterion, provided some valuable insights in structural features governing ability of morpholinium derivatives to dissolve cellulose. While ability to interact with cellulose  is important, the accessibility of the structure seems to be the prerequisite allowing for interactions and thus, being completely decisive. Only structures capable of swelling cellulose were successful solvents: alkaline solutions of morpholinium hydroxides and DMSO-solutions of morpholinium acetates. Insolubility of chlorides in strong swelling agents  also prevented interaction with cellulose. Once access to the cellulose structure and thus cellulose–solvent interactions were enabled through swelling, length of the alkyl chain became important, but showed, interestingly enough, different effects in water and DMSO systems. In water, where stabilizing hydrophobic regions of cellulose is important, the increased chain length provided both a somewhat expanded concentration range for dissolution and a room temperature solubility . In the DMSO/MorOAc systems, on the other hand, the increased length of the alkyl chain (butyl and heptyl) led to a decreased amount of bound water, but possibly also to a sterical hindrance for cellulose–anion interactions resulting in varied dissolution effects. In general, though, MorOAc/DMSO showed higher dissolution capacity compared to the MorOH(aq) along with a lower crystallinity upon coagulation with ethanol. While the lower crystallinity of cellulose coagulated under principally water-free conditions has been observed before, the question of the factors limiting dissolution capacity in aqueous cellulose solutions calls for further investigation.−, OAc− and Cl− to assess their ability towards cellulose dissolution. MorOH(aq) were able to dissolve cellulose by freeze–thaw method while chain lengths longer than ethyl enabled room-temperature dissolution. As a result of alkyl chain length increase the solvent concentration required for room-temperature dissolution decreased. It is assumed that the increase in hydrophobicity of the cation enhances hydrophobic interaction between the cation and cellulose thus preventing cellulose chain reassociation. Morpholinium acetates solely did not dissolve cellulose despite increase in the temperature but required combination with a strong swelling agent DMSO to dissolve cellulose at 120 °C. Increase in alkyl chain length of acetates affected both their tendency to retain water and possibly also ability of the acetate anion to interact with cellulose through an increasing steric effect. In spite of decrease in water content a lower dissolution ability was observed when alkyl chain length increased. The highest amount of dissolved cellulose was 14 wt% reported for EMMorOAc/DMSO while in MorOH maximum 7 wt% cellulose could be dissolved. Yet, all the prepared morpholinium chlorides had high melting points and were not soluble in common organic solvents such as acetone, DMSO or DMAc, failed in dissolving cellulose. This work has expanded the knowledge on the design of aqueous and organic morpholinium-based solvents while the easy synthesis, increased dissolution capacity and possibility of cellulose dissolution in MorOH(aq) make them appropriate for further research and application in cellulose field.A series of morpholinium cations were combined with OHShirin Naserifar: conceptualization, formal analysis, investigation, writing – original draft, visualization. Andreas Koschella: conceptualization, supervision, writing – review & editing. Thomas Heinze: conceptualization, writing – review & editing. Diana Bernin: methodology, investigation, writing – review & editing. Merima Hasani: conceptualization, supervision, project administration, funding acquisition, writing – review & editing.There are no conflicts to declare.RA-013-D3RA03370H-s001


The model reliably captured the seasonal pattern of LAI dynamics for different treatments in terms of genotypes, plant densities, and water–nitrogen managements (correlation coefficient: 0.82 to 0.98). With appropriate adaptations, this framework can be adjusted to any type of sensors to estimate various traits for various species (including but not limited to LAI of wheat) in associated disciplines, e.g., crop breeding, precision agriculture, etc.It is valuable to develop a generic model that can accurately estimate the leaf area index (LAI) of wheat from unmanned aerial vehicle-based multispectral data for diverse soil backgrounds without any ground calibration. To achieve this objective, 2 strategies were investigated to improve our existing random forest regression (RFR) model, which was trained with simulations from a radiative transfer model (PROSAIL). The 2 strategies consisted of (a) broadening the reflectance domain of soil background to generate training data and (b) finding an appropriate set of indicators (band reflectance and/or vegetation indices) as inputs of the RFR model. The RFR models were tested in diverse soils representing varying soil types in Australia. Simulation analysis indicated that adopting both strategies resulted in a generic model that can provide accurate estimation for wheat LAI and is resistant to changes in soil background. From validation on 2 years of field trials, this model achieved high prediction accuracy for LAI over the entire crop cycle (LAI up to 7 m The estimation of leaf area index (LAI) has long been intensively studied in plant sciences, agronomy, and remote sensing communities. The LAI sets the canopy capacity for crop photosynthesis and transpiration and can be used as an indicator of crop health condition and crop growth rate. The direct measurement of LAI is destructive, labor-intensive, and time-consuming but more accurate; thus, it is commonly used to provide ground truth for developing indirect methods ,2. With Retrieval methods to predict crop traits  from sensing data are independent from cameras (or sensors) and platforms used to capture sensing data. According to the means to establish the relationship between spectral signal and crop trait, these methods can be divided into 3 main categories: (a) empirical methods, when a relationship between the crop trait and the raw sensing data or/and their derived vegetation indices (VIs) is established with experimental data; (b) physical methods, when this relationship corresponds to the cause–effect relationship built within a radiative transfer model (RTM) ; and  considering multiple soil reflectance when generating synthetic training data ,25 and , each with 7 rows and a 25-cm row spacing. For Exp16, the sowing occurred on 2016 May 21 and plant emergence occurred approximately 10 d after sowing. For Exp19, the sowing occurred on 2019 May 15 and plant emergence occurred approximately 5 d after sowing. The phenology of each plot on each UAV-based phenotyping date was recorded using a decimal Zadoks score  in 2016 (Exp16) and 2019 (Exp19), and UAV-based phenotyping was undertaken along with field measurements . Differ2) and were taken in 84 plots  for Exp16 and 72 plots  for Exp19. Within each block (defined by water and nitrogen application), all treatments (genotype or genotype × density) were randomized using the corDiGGer method provided in a free R package, DiGGer. For Exp16, quadrat harvest and UAV phenotyping did not always occur within 3 d of each other. Unmatching LAI measurements on UAV phenotyping dates were interpolated with a fitted piecewise function based on all observed LAI from quadrat harvests across growing season (7 or 8 harvesting times were used for each selected plots from leave development to end of grain filling). The piecewise function is consisting of using a logistic function and beta function before and after LAI reaching its maxima, respectively. A detailed description for the implementation of this method can refer to the Supplementary Materials in our previous work ), leaf carotenoid content , leaf water content or leaf equivalent water thickness , leaf dry matter content , average leaf inclination angle , leaf area index , hot spot parameter , solar zenith angle , and relative azimuth angle . Parameters for the leaf anthocyanins content , leaf brown pigment , and viewing zenith angle  were fixed to 0.The PROSAIL model  was usedous work . The parA subset consisting of 40,000 combinations  of input parameter values was randomly sampled from the defined parameter space and then further combined with soil reflectance from defined soil backgrounds to run PROSAIL and simulate canopy reflectance. The soil reflectance of the soil background used in the training set was simulated with the default soil reflectance provided in PROSAIL by adjusting 2 soil factors , while that used in the test set was corresponding to a specific measured soil reflectance of test soils (see details in the “Improving the baseline model with “strategy 1”” section). The soil reflectance and the combination of parameter values were combined randomly in each training set. To mimic measurements from the sensor mounted on the UAV platform, the output bidirectional reflectance from 400 to 2,500 nm at 1-nm interval was resampled into band reflectance of the 5 bands based on spectral response coefficient provided by MicaSense . The re2(n_features), where n_features represents the number of predictive variables of the RFR model), and (c) the minimum number of samples required at a leaf node (min_samples_leaf = 1). The values of these 3 hyperparameter were determined on the basis of grid search and cross-validation as described in our previous work [https://scikit-learn.org/stable/).In this study, the RFR was chosen as the predictive model to predict LAI, as RFR is less prone to overfitting than some non-ensemble methods and can provide robust predictions because of its attributes, i.e., ensemble mechanism, sample disturbance, and attribute disturbance . Three kous work . Both inThe baseline RFR model was trained on synthetic data using the soil background with a single soil reflectance (“defaultSingle”) and using the 5 band reflectance as model inputs (“Ref”) .wet) and dry (Rsoildry) conditions. In PROSAIL, possible variation of soil reflectance can be accounted for by a wetness factor (psoil) (used to mix the wet and dry soil) and a multiplicative brightness factor (asoil) [dry + (1 − psoil) × Rsoilwet) [The strategy 1  was first investigated to improve the baseline model to perform robustly in different soil backgrounds. PROSAIL provides a default soil with standard soil reflectance under wet (Rsoil (asoil) . The refsoilwet) .For strategy 1, 3 sets of soil backgrounds were used in the synthetic training set . The 3 boundaries of soil reflectance in training soil backgrounds were generated with the equation mentioned above by specifying psoil and asoil: sim1 , sim2 , and sim3   was then investigated to improve the baseline model to make it insensitive to changes in soil backgrounds. In this study, in addition to the 5 band reflectance, 7 VIs Table  were conGiven the defined ranges of input parameters in PROSAIL, a global sensitivity analysis was conducted on the basis of the extended Fourier amplitude sensitivity test (EFAST)  to calcuFor strategy 2, 7 sets of canopy-spectral inputs were considered to combine band reflectance and VIs based on sensitivity results, i.e., Ref, RefVI, VI, VIc1, VIc2, VIc3, and VIc4. The “Ref” corresponded to the reflectance of the 5 bands in RedEdge camera. The “RefVI” corresponded to the reflectance of the 5 bands in addition to 7 VIs. The “VI” corresponded to the 7 VIs. The NDVI, NDVIre, CIre, and MSRre were excluded from the 7 VIs step by step to determine the most effective combination of VIs for LAI predictions, resulting in another 4 input sets: VIc1 , VIc2 , VIc3 , and VIc4 . The lower number of features simplifies a predictor and reduces possible combinations leading to a same output, which in turn will reduce the prediction uncertainties. Therefore, we intended to choose a predictor with lower number of features on the basis of maintaining good prediction as the others.On the basis of different combinations of 2 strategies, 21 synthetic training sets  were generated in total (Table r) measures the correlation between the observation and its prediction, which is useful to evaluate the degree to which the movement of observed (or known) LAI is captured in predicted LAI, especially in predicting seasonal dynamics of LAI. The determination coefficient (R2) measures the proportion of the variance in observed (or known) LAI explained by predicted LAI in the linear regression setting, which is suitable to account for the ability of the RFR model to predict LAI for a wide range of conditions. Both root mean square error (RMSE) and RRMSE (a ratio of RMSE divided by the mean of observed (or known) LAI) evaluate the prediction bias of the RFR model, measuring the average absolute and relative error between the known (or observed) LAI and its prediction estimated with the RFR model, respectively. The empirical cumulative density distribution (ECDF) of prediction bias  as well as the derived percentage of samples overestimated (POE) and mean bias error (MBE) were also calculated for bias uncertainty analysis. The POE is a ratio of the number of samples with positive prediction bias divided by the total sample number, presenting in percentage format by times 100. All metrics were calculated in R 3.6.0.A series of statistical metrics were used to evaluate the RFR model’s performance from 3 aspects: correlation, fitness, and bias. The Pearson correlation coefficient (https://zenodo.org/record/6265730). These soil samples vary in color (from dark to white) and texture  . The soil reflectance profile  of each soil samples was measured with an ASD spectrometer  after a standard preprocessing  in the laboratory [The soil reflectance of 10 soil samples from the Biomes of Australian Soil Environment (BASE) project  was seley) Table , and detboratory . For thi2 m−2, and a high proportion of soil background was exposed in the UAV-based multispectral images. To evaluate the RFR model’s practical performance for different soil backgrounds, we used the background correction method proposed by Chen et al. [In Exp16, all wheat canopies were at seedling stage on June 8  when the first flight was conducted. Destructive quadrat harvests were conducted for 84 selected plots on the same date to obtain ground-truth LAI . At this stage, the LAI was not more than 0.3 mhttps://biometris.github.io/statgenHTP).The RFR models were further tested on all experimental data collected in 2 field experiments to evaluate the prediction accuracy of (a) LAI at different growing stages, (b) the spatiotemporal variation of LAI across the growing season, and (c) the dynamics of genotype-specific LAI along growing season and related heritability under different treatments. On the basis of analysis for experimental data described above, there were 11 (in Exp16) and 4 (in Exp19) observed LAI for each studied plot in the whole growing season. The observed LAI and their predicted values were reorganized on the basis of phenology to evaluate the model’s performance in predicting LAI at different growth stages. On the basis of UAV-based phenotyping dates, the spatiotemporal variation of observed and predicted LAI was mapped in sequence across growing season. In addition, the best linear unbiased prediction (BLUP) model was applied to fit the genotype-specific predictions of LAI (both observed and predicted), which were then used to evaluate model’s performance in predicting the seasonal dynamics of LAI for each treatment varying in genotype, plant density, and water–nitrogen management. According to BLUP analysis results, related heritability and variance components were calculated for each date under different treatments. The BLUP analysis was conducted with the free R package, statgenHTP, available online  after mean–standard deviation normalization . The R2 dropped to 0.7 (soil1 and soil8), 0.4 (soil9), and 0.2 (soil10)  Fig.  as the d10) Fig. .R2 from 0.7 to 0.8) but did not improve the performance when tested on soil8 to soil10, while the defaultmulti2.Ref model achieved similarly good performance (R2 = 0.8) when tested on soil1 to soil9 and less accurate prediction (R2 = 0.6) when tested on soil10 , which were poorly predicted by the defaultSingle.Ref model  the VIc3 input was most stable across soils, especially for extreme soils, although it was slightly more sensitive than VIc1 and VIc2 in general S2, and (2 m−2) via background soil adjustment as described above. The performance of 4 models was compared to investigate improvements on LAI prediction contributed from 2 proposed strategies . The 4 models  were combined from the baseline and best set of training soil background as well as canopy-spectral inputs. The performance comparison of these models was presented in Table The established RFR models trained over synthetic training sets were tested on experimental and augmented data for different soil backgrounds. The augmented data were generated from the original experimental data collected at the early growth stage  when tested on different soil backgrounds (Table 2 m−2 and maximum bias within 1.5 m2 m−2) than the other backgrounds (with RMSE over 1 m2 m−2 and maximum bias up to 5 m2 m−2)  Table S3. The s2 m−2, while the defaultSingle.VIc3 model reduced to a smaller range of 0.04 to 0.22 m2 m−2  was more effective at predicting LAI across soil types than strategy 1 . Compared with defaultSingle.Ref, the defaultMulti2.Ref model reduced the range of RMSE from 0.5–2.99 to 0.12–0.59 mThe baseline model  and the model with the best simulation performance  were further tested on experimental data collected in 2 field experiments to evaluate the model’s practical performance in predicting LAI at different growth stages across the growing season. Compared with the defaultSingle.Ref model, the improvement of LAI prediction from the defaultMulti2.VIc3 model mainly occurred in LAI < 2 irrespective of growth stage S4, which2 m−2  and magnitude (expressed in MBE) of prediction bias: decreasing from seedling growth to stem elongation, maintaining a relative low value until flowering, and increasing from flowering to ripening Fig. . This ser of 0.77 to 89) during growing season except at the seedling growth stage (r = 0.59)  was smaller for sparse canopies at early  and late stages  but was larger for dense canopies from stem elongation to milk development (RMSE of 0.69 to 0.89 m2 m−2). By contrast, the RRMSE was larger for sparse canopies and smaller for dense canopies.The defaultMulti2.VIc3 model provided prediction of LAI strongly correlated to observed LAI  Fig. , which wR2 of 0.70 to 0.77 and RRMSE of 27% to 32%; Fig. R2 of 0.73 to 0.89 and RRMSE of 41%; 2 m−2, while on experimental data, the prediction bias fluctuated in a smaller range (−1.84 to 2.53 m2 m−2), with more samples overestimated (about 75%) than underestimated (about 25%)  can be better estimated from canopy reflectance than GAI or LAI.In growing crops, the canopy reflectance captured using sensors results from the characteristics of the canopy, which consist of all aboveground components including leaves, stems, and reproductive organs  . The prePrevious studies have confirmed the temporal consistence of predicted LAI dynamics from multisource data collected from different satellites ,25. HoweThe reflectance profiles of the different soils used in the defaultMulti2 training soil background were linearly correlated. Incorporating multiple soil reflectance without linear correlation is possible to further improve the robustness of model performance by increasing the diversity of the soil training set. In addition to the approach used to simulate diverse soil reflectance spectra, some soil reflectance models, such as the Price model  and GSV 2 for Exp16) used for aggregation was similar to the resolution of satellites such as CubeSat (3 m × 3 m). Hence, this method could be used with UAV-based images to produce ground truths of LAI to validate satellite-based estimates. Furthermore, this generic model is theoretically able to produce reliable prediction of wheat LAI directly from high-resolution satellite images given its background-resistant attribute, which should be able to deal with mixed pixels . The increasing spatial resolution enables a more accurate capture of details in the canopy, but the RTM-based method is not suitable to apply to make prediction directly on pixels, unless the pixel size is big enough to represent a canopy. On the basis of our understanding, the minimum area is 50 cm × 50 cm for wheat canopy. This is the reason that we applied our RFR model trained on PROSAIL simulations on plot mean reflectance to predict plot-scale LAI. To enhance the advantage of images with sub-centimeter resolution, different non-RTM-based approaches were investigated to estimate LAI with pixel values [In the practical validation of this study, the prediction was computed from plot reflectance and derived VIs. The plot area , provided that appropriate PROSAIL input parameters and effective VIs are defined for the target trait and/or the target species.In this study, we applied a hybrid method to establish the predictive model to predict wheat LAI by training RFR models over synthetic data simulated by PROSAIL without any ground calibration. Two strategies  were investigated to reduce the sensitivity of the RFR model to background variation for LAI prediction. Both strategies presented to improve the robustness of prediction accuracy on unseen synthetic data in different soil backgrounds, while improving canopy-spectral inputs appeared to be more effective and robust. The improved RFR model , which adopted an extended reflectance domain of training soil background and a soil-insensitive input set with fewer canopy-spectral indicators, was proved to be resistant to background variation on synthetic data. On the basis of validation in field experiments, this defaultMulti2.VIc3 model presented stable prediction accuracy for low LAI retrieved from the original image and augmented images even in extreme soil background. In addition, this model achieved similar prediction accuracy for LAI at different growth stages, with relatively larger RMSE in mid-season from stem elongation to milk development (dense canopies) and smaller RMSE at early and late stages (sparse canopies). Moreover, this model produced predicted LAI strongly correlated to their observations, reliably capturing the seasonal pattern of LAI dynamics under different treatments in terms of genotypes, sowing densities, and water–nitrogen managements. As discussed above, the prediction retrieved from spectral images generally corresponds to GAI  and only represents LAI in the case that green leaves are separated from the other green organs . This explains a quasi-systematic overestimation of “LAI”  predicted with the RFR models in this study. Overall, the good prediction of the defaultMulti2.VIc3 model obtained from synthetic, augmented, and experimental data indicated that a background-resistant model can be established using simulation data. This ready-to-use background-resistant model can enable a stable and accurate GAI prediction from isolated UAV-based multispectral images over wheat growing season for diverse soil backgrounds in field conditions.