R. officinalis and L. dentata have been widely used due to their antioxidant activity. However, due to their high volatility, the loading of EO into polymeric nanocapsules (NC) represents an efficient way of retaining their effect in future topical administration. In this way, the quantitative determination of EO incorporated into NC is necessary for simultaneous monitoring of the main components of the EO during the nanoencapsulation process as well as for precise and exact dosing of the components used during the performance of in vitro and in vivo biological tests. In this study, EO were isolated by hydrodistillation in a Clevenger-type apparatus and characterized by GC-MS and GC-FID analyses. The major constituents of EO-R. officinalis were camphor (39.46%) and 1,8-cineole (14.63%), and for EO-L. dentata were 1,8-cineole (68.59%) and β-pinene (11.53%). A new analytical method based on GC-FID for quantification of free and encapsulated EO was developed and validated according to ICH. Linearity, limit of detection and quantification, and intra- and interday precision parameters were determined. The methods were linear and precise for the quantification of the main components of EO. The EO were encapsulated by nanoprecipitation and were analyzed by the GC-FID method validated for their direct quantification. The NC size was 200 nm with homogeneous size distribution. The quantification of the incorporated EO within a NC is an important step in NC characterization. In this way, an encapsulation efficiency of at least 59.03% and 41.15% of total EO-R. officinalis and EO-L. dentata, respectively, was obtained. Simple, repeatable, and reproducible methods were developed as an analytical tool for the simultaneous quantification of the main components of EO loaded in polymeric nanocapsules as well as their monitoring in biological assays.The essential oils (EO) of  Rosmarinus officinalis  has antioxidant [α-pinene [Lavandula dentata (EO-L. dentata), belonging to the same family Lamiaceae, have been widely used because of their pharmacological effects as an anticonvulsant and antidepressant [Essential oils (EO) have been used for years in pharmaceuticals, cosmetics, and food products due to their health benefits , as antiioxidant , 10, antioxidant , anti-inioxidant , 13 propα-pinene . Similarpressant , sedativpressant , and antpressant . These bpressant .However, EO are highly volatile and can decompose easily due to direct exposure to heat, moisture, light, or oxygen . Nanoencin vitro and in vivo biological tests.On the other hand, the chemical characterization and the quantitative determination of EO incorporated in NC arise as a need for the simultaneous monitoring of the main components of the EO during the nanoencapsulation process and the precise and exact dosing of the components used during the performance of In this sense, the quantification of EO by HPLC has been limited by the high volatility and low UV absorptivity that most of these components have, presenting a greater application in the analysis of its nonvolatile components or other natural products  , 25. In Gas chromatography with a flame ionization detector (GC-FID) represents an analytical technique suitable for the qualitative and quantitative analysis of EO since it offers high sensitivity, great stability, and an exceptionally high linear dynamic range that allows the analysis of volatile components of the EO at very low concentrations or at trace levels , 30. To R. officinalis and L. dentata for future application as an antioxidant agent in biological assays.The main objective of this work was to develop and validate an analytical method by GC-FID by direct injection for the simultaneous quantification of the main monoterpenes of free and nanoencapsulated EO of R. officinalis and L. dentata were collected from Monterrey, N. L., Mexico. The specimens were identified in the Herbarium of the School of Biological Sciences, Universidad Autónoma de Nuevo Leon, Mexico. Dichloromethane , methanol , acetone , and isopropyl alcohol  were of HPLC grade. Purified water was from a Milli-Q water-purification system . 1,8-cineol (>98%), β-pinene (98.5%), camphor (>95%), 4-allylanisole (98%), and linalool (>95%) were of GC grade . The standard solution was n-alkanes . Eudragit EPO, an NC-formed polymer, was obtained from Evonik Industries, Germany.R. officinalis  and L. dentata (EO-L. dentata) by hydrodistillation using a Clevenger-type apparatus for 4 h. The essential oils obtained were stored in a sealed vial at −4° C until chromatographic analysis. The yield percentage was calculated as weight (g) of essential oils per 100 g of the plant.The essential oils were isolated from the aerial parts of fresh plants of µm). Helium (99.99%) was the carrier gas at a flow rate of 0.5 mL min−1. Data acquisition was performed in the scan mode. The ionization source temperature was 230°C, quadrupole temperature was 150°C, and injector temperature was 220°C. The oven temperature was programmed as follows: 35°C for 9 min, increased from 35°C to 150°C at 3°C min−1, held at 150°C for 10 min, increased to 250°C at 10°C min−1, increased at 3°C min−1 to 270°C, and held at 270°C for 10 min. The samples were injected as mentioned above. Components were identified by comparing retention indices relative to C8–C20 n-alkanes, and the mass spectra were compared with the mass spectra from the US National Institute of Standards and Technology (NIST) library and the reference data [The composition of volatile constituents of the essential oil was analyzed using a gas chromatograph 6890N  equipped with a 5973 INERT mass selective spectrometer (ionization energy 70 eV) and an HP-5MS column . The oven temperature was programmed as mentioned above. The detector and injector temperatures were 280°C and 220°C, respectively. The carrier gas was helium (99.99%) at a flow rate of 0.5 mL min−1. Essential oil samples (2 μL) were injected using the split mode. The percentage composition of EO was calculated using the peak normalization method.The GC-FID analysis of the EO was performed with a gas chromatograph Clarus 480  equipped with a flame ionization detector and an Elite-5 capillary column (30 m × 0.25 mm × 0.25 −1) prepared from the two main components of each essential oil in the following concentrations: EO-R. officinalis, 1,8-cineol (20 mg·mL−1) and camphor (30 mg·mL−1) and EO-L. dentata, β-pinene (7 mg·mL−1) and 1,8-cineol (43 mg·mL−1).Standard solutions were prepared by dilution of a stock solution (50 mg·mLµg·mL−1) and 4-allylanisol (100 µg·mL−1) as internal standards for the EO-R. officinalis and EO-L. dentata, respectively. Standards were stored at −4°C and protected from light until use.The working solutions were prepared in methanol in a concentration working interval using linalool . For the R. officinalis essential oil, the oven temperature was held at 60°C for 1 min, increased at 10°C min−1 to 160°C, increased at 20°C min−1 to 200°C, and finally increased at 15°C min−1 to 230°C (and held) for 1 min. While for the L. dentata essential oil, the oven temperature was held at 70°C for 1 min, increased at 8°C min−1 to 130°C (and held) for 1 min, increased at 17°C min−1 to 170°C, and finally increased at 25°C min−1 to 230°C. The detector and injector temperatures were 280°C and 220°C, respectively. The carrier gas was helium (99.99%) at a flow rate of 1.0 mL·min−1. The injection volume was 2 μL using the split mode.The quantitative analysis of the main components used as standard solutions and present in nanocapsules (NC) was performed by GC-FID by direct injection using a gas chromatograph Clarus 480  equipped with a flame ionization detector and an Elite-5 capillary column , limit of quantification (LOQ), and accuracy and precision (intra- and interday) according to International Conference on Harmonisation guidelines .μg·mL−1 in triplicates. The linearity was evaluated by calculation of a regression line using the least squares method.The linearity was determined by calculating a regression line from the plot of the peak area versus concentration in a range from 10 to 160 σ is the standard deviation of the response and s is the slope of the calibration curve. The residual standard deviation of the line regression or the standard deviation of y-intercepts of the line regression may be used as the standard deviation.The LOD and LOQ were calculated from the calibration curve according toR. officinalis and β-pinene and 1,8-cineol in the EO-L. dentata was performed by analyzing the NC loaded with EO added with five levels of total concentration of standards (range 10–160 μg·mL−1) in triplicates. The average concentration value obtained for each level was compared with the theoretical value, which was considered to be 100%, and the SD was determined.Accuracy was determined by calculating the recovery percentage using the standard addition method. The determination of the concentration of 1,8-cineol and camphor in the EO-Precision was evaluated in terms of repeatability (intraday precision) and intermediate precision (interday precision) and was expressed by percentage recovery and the SD for each main component.μg·mL−1) with six replicates each, during a single day. The intermediate precision was evaluated for repeatability during three different days.Repeatability was determined by analyzing EO-loaded NC added with three levels of concentration ) under magnetic stirring at room temperature. The organic solution was added to 20 mL of the aqueous phase (Milli-Q water) under moderate magnetic stirring (125 rpm). Finally, the organic solvent mixture was eliminated by dialysis. Briefly, the suspension was transferred to a membrane of regenerated cellulose Spectrum/Por , which was placed in a container with distilled water in agitation at 25°C during 2 hours with two changes of water. NC characterization was carried out to determine mean size, zeta potential, and polydispersity index (PDI) by dynamic light scattering (DLS)  at 25°C. The stability of NC was determined from the particle size during 8 weeks (25 ± 2°C) in terms of means size and the PDI.EO-loaded NC were prepared according to the nanoprecipitation method developed by Fessi et al. . The orgR. officinalis and L. dentata in the NC was determined indirectly. The NC dispersions were centrifuged at 25,000 rpm at 3°C for 2 h . The supernatant was removed and the pellet was washed thrice with methanol to ensure the complete solubilization of monoterpenes. Methanol solutions were analyzed by the previously validated GC-FID method in order to quantify the monoterpenes in NC. Finally, the %EL (3) and %EE (4) were derived as follows:Once the chromatographic methods were development and validated, the amount of EO-R. officinalis and L. dentata, respectively. The yield of EO as well as their variations according to the origin of the plant has been reported in different investigations [R. officinalis essential oil was higher than that reported by Bekkara et al., with a yield of 0.8% for the plant from Algeria [L. dentata from Morocco [Rosmarinus EO from Tunisia could be attributed to variations in climatic conditions [In the present study, the EO were obtained by hydrodistillation with a yield percentage of 0.72 ± 0.19% (w/w) and 0.53 ± 0.29% (w/w) for igations . The yie Algeria , while t Morocco . This va Morocco . For exanditions .R. officinalis and L. dentata, respectively, are presented.Essential oils were analyzed by GC-MS and GC-FID to identify their constituents. In R. officinalis essential oil were identified. The EO-R. officinalis composition was characterized by the presence of oxygenated monoterpenes (62.34%) represented mainly by camphor (39.46%) and 1,8-cineole (14.63%)  .L. dentata essential oil, 16 components were identified; the principal constituents were oxygenated monoterpenes (80.71%) and hydrogenated monoterpenes (16.19%); the main constituents were 1,8-cineole (68.59%) and β-pinene (11.53%) (In (11.53%) .The retention time, retention indices, and chemical composition of essential oils are presented in R. officinalis essential oils 1,8-cineole (43.77%), camphor (12.53%), α-pinene (11.51%), β-pinene (8.16%), and camphene (4.55%) as the main constituents [L. dentata leaves, 1,8-cineole (33.54%) and camphor (18.9%) [Rašković et al. identified in tituents . A lowertituents . Touati  (18.9%) .The above data agree with the assertion that the composition of the essential oil depends on several factors, such as climate and soil; hence, there may be differences in the percentage of its components.The validation of the method for the quantification of the two main components in EO was performed to know the linearity, precision, and accuracy of the chromatographic method for the quantification of the peak components of EO-loaded NC. The chromatographic conditions and performance parameters were adjusted to provide a simple analysis with the best peak resolution, reducing run time and lowering the cost of validation and analysis of essential oils.The regression equation, the correlation coefficient, LOD, and LOQ of each main component used as standards were established and are shown in μg·mL−1 and 0.15 and 3.88 μg·mL−1 for EO-R. officinalis and EO-L. dentata, respectively  [in situ properties of the NC-polymer determine the %EE of essential oil components. For example, Lugo-Estrada et al. used a headspace solid-phase microextraction GC-FID method to demonstrate that the %EE of Thymus vulgaris essential oil in NC of ε-polycaprolactone was close to 96% [The nanoprecipitation technique described by Fessi et al.  was usedctively) . The rese to 96% .The results of %EL obtained in the present work may be due to the volatile nature of the EO and were in agreement with the findings on the loading of oregano essential oil in chitosan nanoparticles, which have been reported by Hosseini et al. They developed formulations of chitosan nanoparticles with oregano essential oil with a percentage of encapsulation loading in a range of 1.32 to 2.12% . The hydFinally, a number a studies employing UV-VIS spectroscopy have been conducted to investigate encapsulation efficiency and loading capacity of EO-NC. A disadvantage of these UV techniques is that they generate an overlap of essential oil components signal, which may obtain an overestimation, and the UV-vis methods used have not been previously validated.R. officinalis and L. dentata were determined. β-pinene, 1,8-cineole, and camphor were identified as the main components of the two essential oils. In this study, the validated analytical method allowed the simultaneous quantification of two main components of each nanoencapsulated essential oil, allowing the direct monitoring of these components in biological tests in vitro and in vivo. Hence, it is of great importance, due to the lack of analytical methods by direct GC-FID, to analyze these nanoencapsulated essential oils reported in the literature.In this study, the chemical compositions of the essential oils from leaves of


Tamarindus indica L.) seed (TSP) by acidic hot water extraction and ethanol precipitation. It was composed of 86.2% neutral polysaccharide, 5.4% uronic acid and 1.3% protein. The molecular weight of TSP was estimated to be about 1735 kDa, with glucose, xylose, and galactose in a molar ratio of 2.9:1.8:1.0 as the major monosaccharides. The steady shear and viscoelastic properties of TSP aqueous solutions were investigated by dynamic rheometry. Results revealed that TSP aqueous solution at a concentration above 0.5% (w/v) exhibited non-Newtonian shear-thinning behavior. Dynamic oscillatory analysis revealed that 10% (w/v) TSP showed as a “weak gel” structure. Apparent viscosities and viscoelastic parameters of TSP solutions decreased drastically in an alkaline solution of pH > 10, but slightly influenced by acidic solution, high temperature and the presence of salt ions and sucrose. These results indicated that TSP possessed excellent pH-resistance and thermo-stability, which might be suitable for applications in acidic beverages and high-temperature processed foodstuffs.A polysaccharide was extracted in high yield from tamarind ( Tamarindus indica L.) is an evergreen large tree of the genus Tamarindu of the familiy Caesalpinioideae, native to Southeast Asia, India and Equatorial Africa, which are subtropical and tropical regions [d-glucan backbone with α--d-xylose branches that are partially substituted with β--d-galactose [Tamarind -backbone . XG showbackbone . When pabackbone . Additiobackbone . Mixturebackbone .+, K+, Ca2+) and sucrose (10–30%). The chemical components of the studied TSP were also characterized because it was isolated from tamarind seeds collected from Yunnan, China and has not yet been reported before.The current study aimed to systematically investigate the rheological change and stability of TSP solutions with respect to food processing factors. The factors studied were set over a wide range of levels, for example, TSP concentrations (0.5–10%), pH (1–13), temperature (5–85 °C), salt ions (Naw/w), higher than that reported by Nayak et al. [The extraction yield of TSP was determined to be 54.6%  stretching vibration of polysaccharides and water involved in hydrogen bonding [−1 corresponds to the methylene group (C-H) stretching vibration peak characteristic of polysaccharides [−1 and 1374 cm−1 refer to the presence of carbonyl or carboxylic acid groups (C=O) [-1 implies that TSP is pyran-glycosylated [−1), the polysaccharide exhibited an obvious characteristic absorption at 897 cm−1, which was assigned to d-galactopyranose [−1 could represent d-glucopyranose. bonding . The abscharides . The absps (C=O) ,22. The osylated . In the pyranose . The absThe apparent viscosity of TSP solutions at different concentrations is shown in η represents the apparent viscosity (Pa·s); η0 is the zero shear viscosity (Pa·s); −1); wλ represents the relaxation time (s); n is the shear-thinning index, where n < 1 indicates a shear-thinning behavior of polymers [According to the flow curve, the flow properties of TSP solutions could be further described with the Williamson model  as follopolymers .2 = 0.9164–0.9999). The solution behavior transformed from Newtonian to shear thinning at a critical shear rate (wλ). The −1, respectively. The decrease of η0 increased with the increase of concentration, indicating the establishment of a greater number of links between the biopolymer molecules, which depended on the molar mass and inter-chain interactions [The fitted parameters of the Williamson model for TSP solutions are shown in nditions . The sheractions .These results were consistent with most of the studies on rheological behaviors of polysaccharides such as xanthan gum ,32 and -w/v) TSP solution, the G′ was lower than the G″ in the tested frequency range, indicating a fluidic behavior. When the concentration increasing to 4%, 8%, and 10% (w/v), the G′ and G″ increased and crossed at a frequency of 80, 25 and 7 rad/s, respectively. This indicates that the TSP solution transformed from viscous behavior to a more elastic behavior with increasing concentration [Polysaccharide solutions and gels are usually characterized by the storage modulus G′ and the loss modulus G″ to evaluate their viscoelastic properties. In general, if G′ < G″, the solution has prevalently viscous properties, which are observed to be more ‘‘liquid-like”. When G′ > G″, the system will exhibit prevalent elastic properties ,36,37,38ntration . The TSPntration .The mechanical loss of the TSP solution during oscillation measurements can be reflected by loss tangent (tan δ = G″/G′), which is a measure of the energy lost compared to energy stored in a cyclic deformation . When taw/v) in different pH solutions. It shows that the G″ was higher than G′ over the entire frequency range and at different pH values. No intersection between the G′ and G″ curves implies that the pH change destroyed the weak gel structure of TSP, giving a viscous system.The apparent viscosities of TSP solutions at different pH values ranging from 1 to 13 are presented in w/v) TSP solution with temperature are shown in −1 decreased from 3.01 to 0.13 Pa.s as the temperature increased from 5 to 85 °C. It could be speculated that TSP adopts a partial self-associated conformation in water due to hydrogen bonding and polymer entanglements at low temperatures. As the temperature increased, a transition progressively took place, from a partially ordered random broken helix conformation to a disordered random coil conformation [The apparent viscosity changes of 2% (ormation . As a reormation . This isormation . Furtherormation .w/v) tended to present a gel-like behavior at low temperature (5 °C), and a liquid-like one at high temperature (45 °C).The effects of temperature on storage modulus G′ and loss modulus G″ of TSP are shown in η is the apparent viscosity (Pa.s); η0 is a pre-factor (Pa.s); R is the ideal gas constant (8.314 J·mol−1·K−1); T is absolute temperature (K); and Ea is the activation energy (kJ/mol) for viscous flow [The apparent activation energy (Ea) for viscous flow was applied to investigate the temperature dependence of TSP solutions. Ea can describe the influence of absolute temperature on several chemical and physical processes according to the Arrhenius’ law (Equation (2)) . The equous flow .w/v) TSP solution as shown in w/v) TSP solution, which were 32.208, 24.435, 19.388 kJ/mol at the shear rates of 2, 60, or 200 s−1, respectively. It is indicated that the temperature dependence of the apparent viscosity of TSP solutions was gradually lessened with the increase in shear rate.In this model, by plotting of lnη against the inverse of temperature (1/T), a straight line could be obtained to calculate the apparent activation energy of 2.0%  were purchased from Sigma-Aldrich Co. . Ethanol, phenol, citric acid, boric acid, acetonitrile, NaNO3, trifluoroacetic acid TFA, HCl, H2SO4, NaOH, KBr, NaCl, KCl, CaCl2 and sucrose were purchased from Yuanye Bio-Technology Co. . All reagents used were of analytical grade unless otherwise specified.Tamarind seeds were collected from Yunnan, China. Monosaccharide standards (w/v) at 25 °C for 6 h. The residue was collected by centrifugation  and then dried. A portion (10.0 g) of the treated sample was extracted with citric acid solution  with constant stirring at 80 °C for 20 min. After centrifugeation , the supernatant was collected and precipitated with ethanol at the ratio of 1:1 (v/v), and kept at 4 °C for two hours. The precipitate was then vacuum dried to a constant weight. The yield of TSP was determined by the following equation:Peeled tamarind seeds were firstly milled into 80-mesh flour, and then treated with 80% ethanol  were used for calibration.Molecular weight (Mw) of TSP was determined by high performance size exclusion chromatography (HPSEC) employing Ultrahydrogel™ 500 and Ultrahydrogel™ 2000 columns . The TSP sample (2 mg/mL) was prepared with 0.1 mol/L NaNOThe monosaccharide composition of TSP was determined on a HPLC system coupled with a UV detector (Waters) via pre-column derivatization with 1-phenyl-3-methyl-5-pyrazolone (PMP) according to Strydom’s study  with sev−1 and resolution of 16 cm−1. The transmission of the samples was measured in 7 mm diameter KBr pellets.The samples were analyzed using FT-IR  with a spectral range of 400–4000 cmw/v) (pH 6.87 ± 0.02). The effects of salt ions  and sucrose  on the rheological parameters of TSP were conducted at a concentration of 2.0% (w/v) TSP. The samples at 2.0% (w/v) were also studied using different pH buffer solution . All the samples were prepared by stirring for 1 h at 80 °C and then resting for 12 h before analyses.TSP samples were dissolved in distilled water at a series of concentrations of 0.5%, 1.0%, 1.5%, 2.0%, 4.0%, 8.0%, and 10.0% (−1) and a decreasing shear rate (1000–1 s−1) at 25 °C. Viscoelastic behaviors of samples were evaluated with respect to angular frequency (0.1–100 rad/s) at a strain of 2% at 25 °C. For the thermostability study, temperature sweeps were performed by heating from 5 to 85 °C, and subsequent cooling from 85 to 5 °C at 5 °C/min and at a constant shear rate .Rheological characterization was carried out on a Discovery HR-3 rheometer (TA Instruments) with a stainless flat plate geometry (diameter = 40 mm). The measuring gap was set as 1000 μm. The temperature was controlled by a circulating water device, which was coupled to the Peltier system (a temperature control system). During the temperature variation experiments, the system was covered with a thermal insulation cover to prevent water evaporation. Before all rheological measurements, samples were loaded onto the plate of the rheometer and allowed to reach equilibrium (±0.5 °C) for 5 min. Viscosity curves were obtained by applying an increasing shear rate (1–1000 sp < 0.05.The TRIOS software (Version 3.3.0.4055), which plugged with several fitting models , was employed for the rheological data. ORIGIN 8.6 software was employed to process the rheological results. All experiments were done in triplicate. The differences between data were analyzed by Tukey’s tests and considered different at a significant level of This study investigated the chemical components and rheological properties of the polysaccharide from tamarind seed collected from Yunnan, China. The main monosaccharides of TSP with a Mw of 1735 kDa were glucose, xylose and galactose at a molar ratio of 2.9:1.8:1.0. TSP presented pseudoplastic behavior in water solution. The pH-resistance of TSP solution viscosity was excellent in the range of pH 1–10. The apparent viscosity of the TSP solution decreased with increasing temperature and ion concentration, but increased with sucrose concentration. Temperature, pH, salt ions, as well as the sucrose concentration were identified to slightly affect the rheological properties of TSP. With the aim of investigating the application of TSP in acidic beverages, high temperature processed foodstuffs, high-salt and high-sugar foods as thickener and stabilizer, further studies will focus on the interaction of TSP with food components.


Fragaria × ananassa Duch.) cultivars  produced in the western region of Portugal  were evaluated. From the obtained, results no significant differences (P > 0.05) in nutritional composition were detected in all of the cultivars; with the exception of lower protein content observed in cv. “Portola” . Regarding the a* value of whole strawberry fruits, no significant differences (P > 0.05) were found in any of the cultivars, which revealed a similar redness. The cv. “Endurance” revealed the highest bioactivity content compared to the other cultivars. Overall, these results provide important information about the high quality of strawberry produced in the western region of Portugal and may be used as a tool for adding value to a functional food in the Mediterranean diet due to the phytochemical composition and nutritional value of strawberry fruitsIn this study, nutritional composition , physicochemical properties , phytochemicals , and antioxidant capacity  of three strawberry ( Fragaria × ananassa Duch.) belong to the family of Rosaceae and genus Fragaria, and the growing area has been increasing all over the world. In Portugal, strawberry production increased from about 2600 tonnes in 2007 to 9347 tonnes in 2017 [Ribatejo and Algarve [Strawberry fruits , texture, soluble solid content (SSC), and titratable acidity (TA); through analysis of phytochemical properties by phenolic (TPC) and anthocyanin content (AC); and through analysis of antioxidant capacity by DPPH scavenging activity and ferric-reducing power activity (FRAP). Therefore, this research encompasses relevant findings regarding the strawberry cultivar quality produced in Portugal.In the present study, three strawberry cultivars  produced in the western region of Portugal were assessed in terms of nutritional composition and overall quality through analysis of physicochemical attributes such as colour (Fragaria × ananassa Duch.) cultivars  were obtained from the fruit and vegetable farm Frutas Classe in the western region of Portugal . The strawberry harvest time/moment was carried out by producers based on commercial maturation  and evaluated through sensory analysis . Three hundred and thirty fruits (≈7 kg) were picked and transported to a laboratory (5 °C) where, after discarding damaged fruits, about 300 fresh and whole strawberries (≈6.6 kg) were classified, as “Extra category” according to the official Portuguese method [n = 3 × 30 × 3).Three strawberry . Methanol HPLC grade was purchased from Pronalab  and Fisher-Scientific ; cupric sulfate (II), titanium dioxide, sulfuric acid 95–97%, Folin-Ciocalteu’s phenol reagent, chloride hexahydrate, petroleum ether, and gallic acid (anhydrous) were from Merck ; methyl red, sodium hydroxide pellets, L-tryptophan, sodium sulfate, ammonium sulfate, sodium carbonate, potassium chloride, cyanidin 3-glucoside, silver nitrate, and hydrochloric acid 37% were from Sigma-Aldrich ; acetic acid was from ACROS Organics ; sodium acetate was from VWR Prolabo Chemicals ; and 2,2-diphenyl-1-picrylhydrazyl (DPPH) was obtained from Alfa Aesa N × 6.25) according to AOAC Official Method 920.152. The fat was determined by extracting 5 g of sample with petroleum ether using a Soxhlet apparatus according to AOAC Official Method 963.15. The ash content was obtained by incineration at (600 ± 15) °C, and carbohydrates were calculated by difference: 100 − (g moisture + g protein + g fat + g ash). Moreover, total energy was calculated using the following equation:The proximate composition  of strawberry cultivars was determined by Association of Official Analytical Chemists (AOAC) International methods . The cruThe proximate values were calculated from three measurements of each samples group and presented as percentages (%).Titratable acidity (TA) was measured according to the International Standard Organization (1998) , based oStrawberry soluble solid content (SSC) was measured after homogenization in a Yellow line DI 25 basic polytron  and was measured in a refractometer . Three determinations per sample group replicate were carried out, and the result were reported as °Brix.L* = 97.10, a* = 0.19, and b* = 1.95) and the illuminate D65 (2° observer). CIE colour space coordinates, L*a*b* values, were determined, where the L* values represent the luminosity of samples (0 for black to 100 for white) and where a* and b* values indicate the variation of greenness to redness (−60 to +60) and blueness to yellowness (−60 to +60), respectively. Tonality was expressed as hue (°h) (Equation (2)) and was calculated as follows:Colour measurements of superficial and internal strawberry fruits  were evaBearing in mind the measurement section of strawberry fruits , ten meaThe texture was determined according to the modified method described by Tylewicz, Tappi, Genovese, Mozzon, and Rocculi . Strawbev/v)), and after 4 min, 80 µL of Na2CO3 solution ) was added. The reaction occurred for 2 h at room temperature, and the absorbance of the mixture was measured at 750 nm using a microplate reader . Gallic acid was used to prepare a standard calibration curve. TPC results expressed as milligrams of gallic acid equivalents per 100 g of strawberry fruits (mg GAE/100 g) resulted from the average of three measurements per sample group.Total phenolic content (TPC) was determined using the Folin–Ciocalteu method  and adap® Instruments, Winooski, VT, USA) of both buffers is proportional to the anthocyanin content. Also, measurements of absorbance at 700 nm were taken into account for corrections due to presence of interfering compounds. The results were expressed as mg cyanidin-3-glucoside per 100 g of strawberry fruits as in the following Equations (3) and (4):average is molecular mass for cyanidin-3-glucoside (449.2 g/mol); FD is the dilution factor; Anthocyanin content (AC) of strawberry cultivars was determined by pH difference . Briefly® Instruments, Winooski, VT, USA). The percentage of inhibition was expressed as radical scavenging activity (% RSA).DPPH scavenging activity was determined according to methodology reported by Custódio et al. . Briefly3 in a 96-well microplate. By freshly mixing acetate buffer, TPTZ, and ferric solutions at ratio of 10:1:1, the final working FRAP reagent was incubated at 37 °C in dark. Briefly, 2 µL of sample was added to 198 µL of FRAP reagent and allowed to stand at 37 °C in dark for 30 min, at which time the increase in absorbance at 593 nm was measured in a microplate reader. Standard curve was performed using FeSO4 solution (0.1–1.0 mM), and results were expressed as mM of FeSO4 per 100 g of strawberry.Ferric-reducing antioxidant power (FRAP) was measured by the method of Benzie and Strain  and of BIn DPPH scavenging activity and ferric-reducing antioxidant power (FRAP) methodologies, three measurements from each sample group were taken.P < 0.05) between sample groups of strawberry cultivars were determined according to Tukey HSD (Honestly Significant Difference). Pearson correlation coefficients were also generated between the quality attributes evaluated: nutritional, physicochemical, phytochemical, and antioxidant capacity.In this study, the obtained data are expressed as mean values and standard deviation (SD). All data underwent analysis of variance (ANOVA) using Statistica™ v.8.0 Software from Statsoft  . StatistIn accordance with P > 0.05) in nutritional composition with the exception of protein content, where the cv. “Portola” denotes a lower value (0.570 ± 0.033%), P < 0.05) compared to cv. “Primoris” and cv. “Endurance”. The carbohydrates ranged between 9.110% and 12.430% with no significant difference (P > 0.05) between the three strawberry cultivars.The strawberry cultivars showed no significant difference  was observed in all the fruit’s cultivars. The cv. “Portola” and cv. “Primoris” attained the lowest and highest values of titratable acidity, (0.572 ± 0.047) g citric acid/100 g and (0.809 ± 0.011) g citric acid/100 g, respectively. The study reported by Lan, Zhang, Ahmed, Qin, and Liu [The titratable acidity of strawberry fruits results from organic and nonvolatile acids, which influence the cellular pH . By obse and Liu  reveals  and Liu ,32. AddiFurthermore, differences between titratable acidity of strawberry cultivars could be possible due to differences in maturity at harvest, to differences between the growing conditions, to environmental factors, and to processing techniques of various fruits ,33,34.P < 0.05) between soluble solid content of two strawberry cultivars was attained, about 2 °Brix and 4.3 °Brix, in a German cultivar (cv. Brandenburg) and an American cultivar (cv. Sweet Charlie), respectively. Indeed, the strawberry SSC is influenced by several factors, including genetics, climate, water management, and other cultivation practices as referenced by Wold and Opstad [The main compounds of soluble solid content of fruits are organic acids and sugar, with the sweetness depending on sugar content . A strawd Opstad .R2 = 0.6910 (P = 0.0001).The correlation between titratable acidity and soluble solid content in different strawberry cultivar was analysed, and the results showed that both quality parameters were positive correlated with coefficient During the strawberry postharvest, the main quality attributes that contribute towards consumer acceptability are the attractive red colour and the sweetness and fruity flavour.Differences between the fruit zone colour measurements of three strawberry cultivars  can be observed in P > 0.05) was denoted in any of the strawberry cultivars, which revealed the typical red colour of these fruits. By contrast, the interior of cv. “Portola” recorded the lowest a* value , describing less redness in this particular cultivar of the fruit.Regarding the fruits’ surface zone colour, no significant difference  was expressed in about 50% of firmness compared to the values obtained in cv. “Primoris” and cv. “Portola”. These findings highlight the softening texture of this strawberry cultivar. Internal strawberry firmness denoted a reduction in maximum force, 20% lower in cv. “Primoris” and “Portola” than observed in the surface section in both fruits. The strawberry cv. “Portola” has a similar value of firmness to that observed by Ramos et al. [P > 0.05) in both evaluated texture attributes regarding the moisture and firmness achieved in three fruit cultivars .Comparing the studied strawberry, produced in the western region of Portugal, cv. “Endurance” exhibited the lowest value of firmness in both fruit measurement sections, (0.612 ± 0.270) N and 0.431 ± 0.240) N in surface and internal fruit zones, respectively. This significant difference  and anthocyanin content (AC) of three strawberry cultivars is shown in P < 0.05) phenolic content, which ranged from 607 to 1314 mg GAE/100 g. In the literature, higher phenolic content is considered to be favourable, since it is an indicator of natural health-promoting bioactive compounds [All the studied strawberry cultivars presented a significant (ompounds .P < 0.05) when compared to cv. “Primoris” and cv. “Endurance” (942 ± 96) and (1314 ± 89) mg GAE/100 g, respectively). Furthermore, our results are similar to those reported by Lester, Lewers, Medina, and Saftner [The strawberry cv. “Portola” exhibited the lowest value of TPC (605.698 ± 28.118) mg GAE/100 g,  Saftner  in the s Saftner . In this Saftner , fruit cP < 0.05) in cv. “Endurance” ((2.411 ± 0.009) mg/100 g) when compared to cv. “Primoris” and cv. “Portola” ((2.09 ± 0.01) and (2.18 ± 0.02) mg/100 g respectively). In this study, the cv. “Endurance” demonstrated a correlation between the anthocyanin content and phenolic content. On the other hand, the studied strawberry cultivars presented a higher AC compared to Fragaria chiloensis Mill, known as Chilean strawberry, that contained a lower AC of 1.10 mg/100 g and 1.16 mg/100 g in 2011 and 2012, respectively, as reported by Saavedra et al. [Total anthocyanins followed the expected pattern as considerable amounts are mainly found in the red fruit . The mosa et al. .Rubus ulmifolius is a major contributor to the antioxidant capacity of this fruit. However, the presence of anthocyanins and their antioxidant properties can vary considerably between species and fruit cultivars [In agreement with the results described above for TPC, the anthocyanin content of cv. “Endurance” was clearly higher than that of the other cultivars. In a recent study, Elisia, Hu, Popovich, and Kitts  showed tultivars ,52.Strawberry fruits prove to be an excellent and natural source of dietary anthocyanins that can lead to health benefits ,54.For the evaluation of food antioxidant capacity, different methodologies are used to obtain valid results because antioxidant compounds present different reactions of mechanisms with possible synergistic interactions ,56 depenThe DPPH free radical scavenging activity of strawberry cultivars ranges from 42.0 ± 2.3% to 51.8 ± 5.1%. The values reported in the current study were generally higher than those reported by Wang, Wang, Ye, Vanga, and Raghavan  for the P < 0.05) in ferric-reducing antioxidant power (FRAP) was observed between strawberry cultivars. The cv. “Endurance” showed the highest value ((72.4 ± 8.1) Eq mM FeSO4/100 g) when compared to cv. “Primoris” ((58.8 ± 0.9) Eq mM FeSO4/100 g) and “Portola” ((38.2 ± 1.4) Eq mM FeSO4/100 g). The study developed by Rekika, Khanizadeh, Deschênes, Levasseur, and Charles [R2 = 0.9831, P = 0.017) was found between the FRAP and anthocyanin content for the cv. “Endurance” only but not for the other two cultivars. Overall, cv. “Endurance” strawberry recorded the highest TPC and anthocyanin contents consistent with the highest antioxidant activities, especially for FRAP  produced in the western region of Portugal was performed. All the studied strawberry cultivars exhibited a natural source of health-promoting properties through phytochemical and antioxidant screening and testing for nutritional value. The “Endurance” strawberry cultivar was characterized by the highest level of antioxidant compounds, expressed by total phenolic and anthocyanin content. These antioxidant compounds may have useful applications as functional ingredients in foods. In this sense and for the development of functional ingredients, the economic value of this cultivar produced in Portugal should be enhanced, with interest for producers and consumers. Identification should be made of phenolic compounds as biomarkers to better understand the influence of the bioavailability of these compounds on promoting good health. Moreover, these findings will be important for promoting the Mediterranean diet and for consumers who choose to have a daily intake of foods rich in antioxidants.


Firstly, according to the adsorption efficiency, two sorbents imidazolium chloride-butylimidazolium chloride-based silica (Sil@BIm-Im) and imidazolium chloride-hexylimidazolium chloride-based silica (Sil@HIm-Im) were selected. The RSM was introduced to optimize adsorption conditions such as methanol/water ratio, time, and pH. Sil@HIm-Im, which had the highest adsorption efficiency, was used in SPE as a sorbent. After 2.0 mL of loading samples, washing solvents were optimized as 6.0 mL and 4.0 mL of water for corn and peanut, 2.0 mL of acetonitrile, and 3.0 mL of methanol. 3.0 mL of methanol/acetic acid (2.0% vol.) was investigated as an elution solvent. Finally, 0.009  Aflatoxins (AFs) such as B1, B2, G1, and G2 are natural secondary metabolites that are produced by molds –5.18 column to detect aflatoxins in 71 rice samples, and 1.89 ng/g of AFB1 was found in all samples [μg/L [Various methods have been published to reduce or detoxify aflatoxins; however, no treatment has been found to be effective against aflatoxins . Several samples . Herzalles [μg/L . Zahoor es [μg/L .In the previous method, large amount of solvents especially organic solvents were regulated as another kind of pollutants in the process. So, solid-phase extraction (SPE) as one of the most convenient and high-performance separation technologies can help minimize the use of organic solvents . In ordeVentura et al. used an Oasis HLB SPE cartridge with HPLC/MS to detect four aflatoxins in a herb, 2.0 mL of methanol/water  was used as a washing solvent, and 4.0 mL of methanol/water  was used as an elution solvent . Liu et π − π interactions between analyte and functional groups of the ionic liquids, are widely applied [However, low- or nontoxic solvent/sorbents are still needed urgently. Therefore, ionic liquids (ILs) were introduced and received many attentions. ILs, as green solvents with excellent chemical properties , are alr applied . Some re applied , 32.In this research, AFB1 was adsorbed using bifunctional ionic liquid-based silicas. During the adsorption, surface response methodology (RSM) with the Design-Expert software optimized three variable conditions such as methanol/water ratio, adsorption time, and pH. Finally, the sorbent isolated AFB1 from extracts of moldy corn and peanut with the SPE method. The work is expected to develop the SPE method based on unique sorbent and extend their potential application in the separation and purification of other compounds.μm), (3-chloropropyl)trimethoxysilan (98%), imidazole (99%), 1-methylimidazole (99%), 1-ethylimidazole (98%), 1-butylimidazole (98%), 1,2-dichloroethane (99%), 1,4-dichlorobutane (98%), 1,6-dichlorohexane (99%), and aflatoxin B1 (>98%) were purchased from Aladdin Inc. . The HPLC grade of acetonitrile and methanol was from CINC High Purity Solvents Co. Ltd. . Other organic solvents such as acetone, ethanol, toluene, and triethylamine were supplied by Beilian Company , and purities were higher than 99.0%. Ultrapure water was produced by a purification machine , and all organic solvents should be filtered before use.Silica  with a heating rate of 10°C/min under N2. The chromatographic conditions were as follows: HPLC  with a TC-C18 column , and acetonitrile/water  was used as the mobile phase. The flow rate, UV wavelength, injection volume, and column oven temperature were 0.8 mL/min, 365 nm, 5.0 μL, and 35°C, respectively.The characteristics of all obtained IL-based silicas were analyzed by FT-IR  in the range of 400–4000 cmμg/mL of aflatoxin B1 in methanol within 5.0 min at ambient temperature by the liquid-solid adsorption method and the adsorption amounts of all sorbents were detected by analyzing the concentration in liquid layers.First of all, 0.1 g of all IL-based silicas mixed with 1.0 mL of 0.1 Then, the adsorption conditions were optimized by Design-Expert software . The BBD model in RSM was used, and according to physical and chemical properties of aflatoxin B1, three major factors such as methanol/water ratio, adsorption time, and pH, which can significantly affect the maximum adsorption amount, were selected. Three factors of the BBD were designated A, B, C and divided into three levels in Peanut and corn were stored under a high moisture aerobic ambient at 30°C for a month. Then, the moldy samples were ground to powder, and 25.0 g of them were dipped in 50.0 mL of methanol over 24 hr. The obtained extracts were filtered and stored at 4°C for further analysis.−1 and this peak belonged to the –OH group. In Sil@Cl, the –OH peak decreased and C-Cl peak at 695 cm−1 appeared. After modification, the IL-based silicas showed the appearance of peaks nearby 1565 cm−1 which is the fingerprint region of IL groups, and the C-Cl peak disappeared. Moreover, the vibration range of C-H group in alkanes is 2850–3000 cm−1. So, the peaks at 2917 cm−1 belonged to the carbon chain on the IL group, also the peak area increased with the carbon chain length increasing [In the FT-IR spectra , silica creasing , 34.Thermogravimetric analysis (TGA) can determine the thermostability of the additional groups on silica with the weight loss. μg/mL. Good linearity was obtained, and the linear correlation equations were y = 1 × 10−7x − 4643 (R2 = 0.994) (y is peak area and x is the concentration>).First of all, the calibration curves were constructed using the chromatographic peak areas measured at several increasing concentrations of aflatoxin B1 ranging from 0.001 to 10.0 π − π interactions. Also, the hydrophobicity of the carbon chains between two IL groups had strong interaction on aflatoxin B1. In this case, IL-based silicas obtained much more adsorbed amount than C18. In addition, the carbon chain on the end of the IL group also had hydrophobicity. However, when the chain was too long, it would swing and may cover the inner IL group to weaken the effect and break chemical bonds. So, from the results, the adsorption amounts on IL with long carbon chain decreased. Hence, Sil@BIm-Im and Sil@HIm-Im were selected, and the optimized adsorption conditions of them were design by RSM.According to the results from the designed experiments by software, the model proposed for the response of the adsorbed amounts of aflatoxin B1 was determined as Equations :(1)Y=0.3F values higher than 39.59 and Prob>F less than 0.05 indicated that the models were significant. The value of R2 = 0.9941 for Equation  and acetonitrile/acetic acid (2.0% vol.) with a higher eluting strength were used as elution solvents. The results showed that 3.0 mL of methanol/acetic acid (2.0% vol.) had more efficiency than acetonitrile/acetic acid (2.0% vol.) and could elute all aflatoxin B1 from the sorbent. In corn and peanut extract solutions, a certain concentration of aflatoxin B1 was spiked and analyzed to calculate the recoveries. Assays of repeatability calculated as relative standard deviations (RSDs) were performed with Sil@HIm-Im by SPE process 5 times in a 5-day period. The recoveries and RSDs are presented in μg/g and 0.023 μg/g of aflatoxin B1 were obtained in corn and peanut extracts. The low deviation error, stable characteristics, and application demonstrated the sorbent to be a viable alternative tool for further researches.In this study, bifunctional ionic liquid-based silicas were created and applied in SPE to isolate aflatoxin B1 from moldy corn and peanut extracts. According to the adsorption amount by the standard solution, more aflatoxin B1 was adsorbed on Sil@BIm-Im and Sil@HIm-Im. With the designed experiment of RSM, Sil@HIm-Im was selected as the SPE sorbent, and the optimized conditions were methanol/water , 29.73 min of adsorption, and pH = 6.8. In addition, the ambient temperature was evaluated, and the results proved Sil@HIm-Im to be the SPE sorbent. Finally, washing by water and acetonitrile and eluting by 3.0 mL of methanol/acetic acid (2.0% vol.), 0.009


Notch signaling dysregulation is implicated in the development of pancreatic adenocarcinoma (PDAC). Tarextumab is a fully human IgG2 antibody that inhibits Notch2/3 receptors.Notch3 gene expression and tarextumab anti‐tumor activity, patients were also divided into subgroups of low, intermediate, and high Notch3 gene expression. Primary endpoint was overall survival (OS) in all and in patients with the three Notch3 gene expression subgroups ; secondary end points included progression‐free survival (PFS), 12‐month OS, overall response rate (ORR), and safety and biomarker investigation.Aphase 2, randomized, placebo‐controlled, multicenter trial evaluated the activity of tarextumab in combination with nab‐paclitaxel and gemcitabine in patients with metastatic PDAC. Patients were stratified based on ECOG performance score and Ca 19‐9 level and randomized 1:1 to nab‐paclitaxel, gemcitabine with either tarextumab or placebo. Based on preclinical and phase Ib results suggesting a positive correlation between P = .0985). No difference observed in OS in the Notch3 gene expression subgroups. PFS in the tarextumab‐treated group (3.7 months) was significantly shorter compared with the placebo group (5.5 months) . Grade 3 diarrhea and thrombocytopenia were more common in the tarextumab group.Median OS was 6.4 months in the tarextumab group vs 7.9 months in the placebo group (HR = 1.34 , The addition of tarextumab to nab‐paclitaxel and gemcitabine did not improve OS, PFS, or ORR in first‐line metastatic PDAC, and PFS was specifically statistically worse in the tarextumab‐treated patients.NCT01647828. More than half of those at diagnosis have stage IV disease for which the 5‐year overall survival is 3%.Rg5, a marker of developing pericytes, and facilitated pericyte recruitment to endothelial cells. Loss of Rg5 has been reported to reduce tumor hypoxia and to normalize vasculature.Notch3 gene expression levels in these pancreatic tumor models were also found to be associated with increased sensitivity to the combination of tarextumab and gemcitabine. Based on the preclinical data, our hypothesis was that PDAC patients with higher levels of Notch3 gene expression in tumor cells would have an enhanced potential for therapeutic benefit from the addition of tarextumab to standard therapy.Tarextumab (OMP‐59R5) is a fully human IgG2 antibody against the Notch2 and Notch3 receptors.Notch3 were noted to have a PFS of 6.6 months and OS of 14.6 months. These results were deemed to compare favorably to reported PFS of 5.5 months and OS of 8.5 months in patients treated with gemcitabine and nab‐paclitaxel.In a phase Ib study of N = 38 patients with previously untreated metastatic PDAC, tarextumab was evaluated in combination with nab‐paclitaxel and gemcitabine. The recommended phase 2 dose (RP2D) was determined to be 15 mg/kg with standard doses of the cytotoxic agents. Diarrhea, fatigue, and anemia were the most common tarextumab‐related toxicities, and the events were mostly Grade 1 or 2. The overall response rate (CR + PR) was 29%.Given the encouraging preclinical data, tolerable safety profile and the favorable PFS and OS results in the phase Ib study, a randomized phase II study comparing gemcitabine, nab‐paclitaxel with either tarextumab or placebo was initiated in patients with previously untreated metastatic PDAC.22.1Notch3 gene expression levels: Notch3 ≥ 25th percentile; Notch3 ≥ 50th percentile; Notch3 ≥ 75th percentile and all patients irrespective of Notch3 expression levels.This was a prospective, multicenter, randomized, double‐blinded, placebo‐controlled phase II study in patients with untreated metastatic PDAC. Patients were randomized in 1:1 ratio to receive either nab‐paclitaxel, gemcitabine and placebo or nab‐paclitaxel, gemcitabine and tarextumab . Secondary endpoints included progression‐free survival (PFS), overall response rate (ORR), duration of response (DOR), and CA19‐9 response.Exploratory endpoints not reported herein included expression levels of epidermal growth factor receptor (EGFR), placental growth factor (PLGF), epithelial neutrophil‐activating peptide (ENA 78), and other Notch‐related genes in the serum obtained at baseline and disease progression. Circulating tumor cells (CTCs), microRNAs, and circulating endothelial cells were also evaluated and will be reported separately.Tumor assessments were assessed by RECIST version 1.1 every 8 weeks using computed tomography or magnetic resonance imaging. Adverse events were graded using the National Cancer Institute Common Terminology Criteria for Adverse Events (CTCAE), version 4.02.Notch3 analysis at study entry.Individuals (age > 18 years) with newly diagnosed, pathologically confirmed stage IV PDAC were enrolled. Eligibility criteria also included the presence of measurable disease according to RECIST version 1.1 and Eastern Cooperative Oncology Group (ECOG) performance status of 0 or 1. In additions, patients must have had formalin‐fixed, paraffin‐embedded (FFPE) tumor tissue from metastatic sites, either archived or fresh core needle biopsied for 9/L, hemoglobin ≥ 9.0 g/dL, platelets > 100 × 109/L , serum creatinine ≤ 1.5 mg/dL or calculated creatinine clearance ≥ 60 mL/min using the Cockcroft and Gault formula, bilirubin ≤ 1.5 × upper limit of normal (ULN), alanine aminotransferase (ALT) ≤ 3 × ULN, aspartate aminotransferase (AST) ≤ 3 × ULN), PT/INR ≤ 1.5 × ULN, aPTT ≤ 1.5 × ULN.Patients were required to have adequate organ function as defined by the following factors: absolute neutrophil count ≥ 1.5 × 10Patients were excluded for the following reasons: neuroendocrine tumors of the pancreas, brain metastases, prior therapy for stage IV PDAC, known human immunodeficiency virus (HIV) infection, and major surgery <4 weeks prior to the first treatment. In addition, patients with serious or unstable concomitant systemic disorder incompatible with the study such as active infection, arterial thrombosis, and symptomatic pulmonary embolism were ineligible as were patients with any disorder that would significantly compromise protocol compliance.2.22 and gemcitabine 1000 mg/m2 were administered on Days 1, 8, and 15 of every 28‐day cycle. Tarextumab or placebo was dosed at 15 mg/kg and administered on Days 1 and 15 of every 28‐day cycle. On days when tarextumab, nab‐paclitaxel and gemcitabine were given, tarextumab was administered first, then nab‐paclitaxel followed by gemcitabine. All agents were dosed until either disease progression or limiting toxicity occurred.Nab‐paclitaxel 125 mg/m2.3P‐value for treatment effect were generated using a stratified Cox proportional hazards model.Overall survival was the primary efficacy endpoint of this study and was defined as the time from randomization until death. The hazard in the control arm was 0.09 (median 8 months) and hazard in the tarextumab arm 0.07 (median 10 months). No treatment cross‐over was permitted in the study. The Kaplan‐Meier method was used to estimate both the survival curves and the median survival time. The 95% confidence intervals for median survival times and Final analysis of the study was planned to take place at the point when 104 progression events had occurred or 10 months after the completion of enrollment, whichever occurred first. This would ensure the study had 75% power to detect a hazard ratio of 0.67 (improvement in median PFS from 5.5 months to 8.2 months) and 80% power to detect a hazard ratio of 0.65 (improvement in median PFS from 5.5 to 8.5 months) in the intention‐to‐treat (ITT) population with an associated total one‐sided type 1 error of 0.10. The data cutoff for the final analysis of survival was 6 months after the data cutoff for the final analysis of PFS or when 104 deaths have been observed, whichever occurred first.Data were combined from all participating study sites for the analyses. All statistical testing was two‐sided and was performed at the 0.05 significance level. For continuous variables, descriptive statistics included the mean, SD, median, minimum, maximum, and the number of non‐missing values. For categorical variables, descriptive statistics included counts and percentages per category.Notch3 gene expression analyses were conducted as follows; Notch3 gene expression correlated with efficacy in preclincial models. Ten primary patient derived pancreas cancer tumor xenografts were tested for efficacy in response to gemcitabine and tarextumab. Significant correlation was found between the levels of tumor‐derived Notch3 and the efficacy of tarextumab. Responder tumors had higher levels of Notch3 compared to nonresponders when treated with the combination of chemotherapy and the antibody. Subsequently data from the phase Ib clinical trial evaluated 32 patient samples from 40 patients enrolled in 6 dose levels of tarextumab (ranging from 2.5 to 15 mg/kg) with an 80% success rate for Notch3 gene expression adjudication. A trend was observed for the higher levels of Notch3 and increased time to tumor progression. Based on these collective preclinical and clinical data Notch3 gene expression subgroups  were chosen to best differentiate outcome for the randomized phase II trial.2.4The study was conducted in accordance with the Guideline for Good Clinical Practice, the ethical principles of the Declaration of Helsinki, and was approved by the institutional review board at every site. All patients provided written informed consent before enrollment.33.1Notch3 expression levels. The study was subsequently terminated in March 2016 by the sponsor due to futility.A pre‐planned interim efficacy and safety analysis was conducted by an independent Data and Safety Monitoring Board (DSMB) on data from N = 172 patients treated by January 2016 data cutoff date. From a safety standpoint, the DSMB identified no unexpected safety signals but noted worse RR and PFS in the tarextumab treatment group and a strong trend toward lack of OS benefit in the tarextumab treatment group, irrespective of One hundred and seventy‐seven patients were enrolled in the study in 25 centers throughout the United States from July 2014 to March 2016  and 4.2 months  for patients in the tarextumab treatment group and the placebo group, respectively. The patients treated with tarextumab received a median of 6.0 doses . The patients in the placebo group received a median of 9.0 doses . Two placebo patients were lost to follow‐up and two tarextumab‐treated patients withdrew consent.3.2P = .09). No statistically significant difference was observed in OS in patients with Notch3 ≥ 25th percentile, Notch3 ≥ 50th percentile, or Notch3 ≥ 75th percentile  in the tarextumab group compared with 7.9 months  in the placebo group . The PFS in the tarextumab treatment group was significantly shorter compared with the placebo group . No statistically significant difference was observed in PFS in patients with Notch3 ≥ 25th percentile, Notch3 ≥ 50th percentile, or Notch3 ≥ 75th percentile.The median PFS was 3.7 months  in the tarextumab group and 5.5 months  for the placebo group  between the placebo‐treated group  compared with the tarextumab‐treated group  (Table There was no significant difference in ORR (P = .99).The median duration of response (DOR) was 3.7 months  in the tarextumab group and 3.6 months  in the placebo group. No statistically significant difference was observed in the DOR between the two groups (P = .15) in response between the placebo group (47.7%) and the tarextumab‐treated group (37.1%).CA19‐9 response was defined as a decrease of 50% or more in baseline CA19‐9 at any time post‐baseline. There was no statistically significant difference (3.3Treatment‐emergent adverse events (TEAEs) are summarized in Table Fifty‐one (60%) patients in the placebo and N = 58 (66.7%) patients in the tarextumab group reported one or more serious AEs (SAE). In the tarextumab group, 22 (25.3%) patients had Grade 3 and 3 (3.4%) patients had Grade 4 SAE. Fourteen (16.1%) SAEs in the tarextumab‐treated group and 16 (18.8%) in the placebo‐treated group resulted in patient death; none of these SAEs were considered related to study drug treatment.TEAEs in 8 tarextumab‐treated patients resulted in treatment interruptions and 6 patients experienced tarextumab dose reductions due to TEAEs. TEAEs led to treatment discontinuation in 7 patients. A total of 126 (73.3%) patients died within 30 days of study discontinuation, 69 (79.3%) tarextumab‐treated patients and 57 (67.1%) placebo‐treated patients. None of the deaths were adjudicated as related to tarextumab.4Notch2 and Notch3 expression, increased apoptotic cell death, decreased tumor cell density, and increased vessel perfusion and decreased hypoxia intratumorally.Notch3 were noted to be significantly higher in responders compared to nonresponders, suggesting that higher Notch3 expression may be a useful biomarker of sensitivity to tarextumab treatment.Strong preclinical evidence with patient‐derived xenograft (PDX) pancreatic models and phase Ib trial data provided a compelling rationale for the clinical evaluation of Notch signaling inhibition combined with gemcitabine and nab‐paclitaxel therapy in a randomized phase 2 trial.Notch3 expression, PFS and OS were 6.6 and 14.6 months, respectively.In view of the encouraging preclinical findings, early phase trials were initiated in metastatic PDAC and extensive stage small cell lung cancer. Results from both phase Ib clinical trials were potentially promising, with reported response rates of 84% and 74% in the small cell lung and pancreatic cancer trials, respectively.However, both the small cell lung cancer and PDAC randomized phase II clinical trials failed to meet their primary objective of a statistically significant improvement in OS. In the trial reported herein in PDAC, the PFS for the tarextumab treatment group was shorter compared to the placebo group. Analysis of the Notch3 subgroups also found no difference in PFS and OS between the subgroups. To summarize, we found no benefit in adding tarextumab to standard cytotoxic therapy in this randomized phase II trial of patients with metastatic PDAC, with a statistically significant decrease in median PFS and concerning negative trend in OS for some pre‐specified subgroups. It is possible that some of the worse outcome was attributed to higher toxicity in the tarextumab vs placebo‐treated patients resulting in a lower median treatment duration (2.6 vs 4 months) and lower median number of treatment doses (6 vs 9 doses).The discordances between the preclinical along with the early clinical development  results and the randomized phase II results are concerning and may be attributed to differences in xenograft development, the patient population in the clinical trials, as well as the pleotropic nature of the Notch receptors and unrecognized contributions from the PDAC stroma. The human xenograft tumors used for the preclinical heterotopic implant model were obtained from stage III PDAC patients without metastases whereas the clinical trial treated metastatic PDAC patients. Compared to heterotopic models, orthotopic PDAC models, where tumor cells are implanted directly into the pancreas, retain a greater proportion of stromal components and develop locoregional and distant metastases.Notch1 inhibition has also been reported to cause an increase in liver metastases from neuroblastoma and breast cancer cells and may support early angiogenesis and growth of micrometastases within the liver.Notch3 subgroups. Further analyses of the exploratory biomarkers, including Notch‐related genes, CTCs, and circulating endothelial cells collected in this trial are ongoing and may be informative.This randomized phase II clinical trial also found no significant difference in PFS and OS between the low, intermediate, and high The exact role of Notch signaling in PDAC remains an area of significant debate, with some evidence supportive of an oncogenic role while other results have been more suggestive of its function as a tumor suppressor. Notch receptors and ligands have been found to be overexpressed in human and mouse PDAC cells, and have been implicated in the progression of pancreatic intraepithelial neoplasia (PanIN) lesions.The discrete, collective, and relative contributions of the individual Notch receptors to tumor development in PDAC patients remain to be resolved. Further research into individual Notch inhibitors and agonists may help guide future clinical trials involving the Notch pathway and cytotoxic chemotherapy. To additionally note, a randomized phase II trial evaluating an anti‐Delta‐like ligand 4 (DLL4) targeted agent (demcizumab), which is an inhibitor of the Notch pathway or placebo, combined with gemcitabine and nab‐paclitaxel observed no improvement in the primary endpoint of PFS compared to standard chemotherapy and similarly there was no difference in overall survival (HR 1.02).To sum up, the addition of tarextumab to gemcitabine and nab‐paclitaxel in untreated advanced PDAC did not improve outcomes over standard therapy, and specifically PFS was statistically worse in the tarextumab‐treated group. This trial provides significant insights into the importance of preclinical modeling in optimal and relevant model systems and underscores the need for randomized evaluation of experimental agents.J. Bendell: Research grant from OncoMed for performance of the study covered by the submitted work; payment to her institution for consulting/advisory services and/or clinical trial activities from the following for activities outside of the study covered by the submitted work: Bristol Myers Squibb, Roche, Merck, Taiho Oncology, Amgen, Genentech, Merrimack, Celgene, MedImmune, Seattle Genetics, Daiichi Sankyo, Janssen, Translational Drug Development, Five Prime Therapeutics, Moderna Therapeutics, Tolero, Evelo Biosciences, Array Therapeutics, Forma Therapeutics, Tanabe Research Laboratories, BeiGene, Continuum Clinical, Cerulean, AbbVie, AstraZeneca, EMD Serono, Ipsen Biopharma, Incyte, Novartis, Eisai, Pfizer, Millennium, Imclone, Boston Biomedical, CALGB, Acerta Pharma, Lilly, Gilead Sciences, Leap Therapeutics, Macrogenics, OncoMed Pharmaceuticals, Takeda Pharmaceuticals, Rgenix, Novocure, Merus, NV, Blueprint Medicine, Array Biopharma, ARMO Biosciences, Agios. From time to time, the companies listed have reimbursed Dr Bendell for travel expenses and/or provided meals at meetings held in connection with her services. A. Bullock: Consulting/Advisory Boards: Eisai, Exilexis, Taiho. N. LoConte: Advisory Boards: Celgene, Bayer. Consultant: Abbvie, AstraZenica. D. Sohal: Consulting: Perthera. Honoraria: Foundation Medicine. Travel/Accomodation/Expense reimbursement: Foundation Medicine. Research funding: Agios, Bayer, Bristol‐Myers Squibb, Celgene, Genentech, Incyte, Loxo, Novartis, OncoMed. J. Strickler: Consulting/Advisory: Amgen, Genentech‐Roche, Bayer, Celgene, Chugai, AstraZenica, Seattle Genetics, OncoMed. Research Funding: Amgen, Abbvie, Gilead Sciences, Roche/Genentech, Exelixis, OncoMed, Sanofi, Regeneron, MedImmune, Cascadian Therapeutics, Seattle Genetics, Macrogenics, Leap Therapeutics, Nektar. A. Wang‐Gillam: Advisory Boards: Ipsen, Merrimack, BMS, Tyme, Repugene, Jacobio, Vicus. Research funding: BMS. Biomed Valley, Pfizer, Halozyme, AstraZeneca, Bayer, Xcovery, Novartis, Lily, Aduro, Verastem. Tyme, Boston Biomedical, Newlink Genetics, Precision Biologicis. K. Yu. Consulting/Advisory: Halozyme, Ipsen. Research Funding: Halozyme, BMS. A. Kapoun: Employee OncoMed. L. Zhou: Pain consultant to OncoMed. Stock ownership: OncoMed. J. Dupont: Employee OncoMed. Stock ownership: OncoMed. E. Holmgren: Employee OncoMed. Stock ownership: OncoMed. E. O'Reilly: Research funding to MSK: Genentech, Roche, BMS, Halozyme, Celgene, MabVax Therapeutics, ActaBiologica, OncoMed, Momenta Pharmaceuticals, Parker Institute, AstraZenica, Silenseed, Incyte, Pfizer, Polaris, Lustgarten Foundation, NCI‐CTEP. Consulting/Advisory: Cytomx, BioLineRx, Targovax, Halozyme, Celgene, Bayer, Loxo, Polaris. All remaining authors have declared no conflicts of interest.Zishuo Ian Hu: Writing–original draft and writing–review and editing, formal analysis. Johanna C. Bendell: Investigation, funding, acquisition, formal analysis and resources, project administration. Andrea Bullock: Investigation, formal analysis and resources. Noelle K. LoConte: Investigation, formal analysis and resources. Hassan Hatoum: Investigation, formal analysis and resources. Paul Ritch: Investigation, formal analysis and resources. Hugo Hool: Investigation, formal analysis and resources. Joseph W. Leach: Investigation, formal analysis and resources. James Sanchez: Investigation, formal analysis and resources. Davendra PS Sohal: Investigation, formal analysis and resources. John Strickler: Investigation, formal analysis and resources. Ravindranath Patel: Investigation, formal analysis and resources. Andrea Wang‐Gillaam: Investigation, formal analysis and resources. Irfan Firdaus: Investigation, formal analysis and resources. Kenneth H. Yu: Investigation, formal analysis and resources. Ann M. Kapoun: Conceptualization, funding acquisition, investigation, methodology, formal analysis and resources. Eric Holmgren: Conceptualization, funding acquisition, investigation, methodology, formal analysis and resources. Lei Zhou: Conceptualization, funding acquisition, investigation, methodology, formal analysis and resources. Jakob Dupont: Conceptualization, funding acquisition, investigation, methodology, formal analysis and resources. Vincent Picozzi: Conceptualization, investigation, methodology, formal analysis and resources. Vaibhav Sahai: Investigation, formal analysis and resources. Eileen M. O'Reilly: Conceptualization, funding, acquisition, investigation, methodology, project administration, supervision, writing–original, and writing–review and editing. Precis: A phase 2 study of tarextumab, an anti‐Notch 2/3 inhibitor, in combination with gemcitabine and nab‐paclitaxel in untreated advanced PDAC did not improve outcomes over standard therapy. PFS was statistically worse in the tarextumab‐treated group.


Prunus persica L.) is a diploid species and model plant of the Rosaceae family. In the past decade, significant progress has been made in peach genetic research via DNA markers, but the number of these markers remains limited.Peach , 114,227~178,968 small insertion/deletions (InDels), 8386~12,298 structure variants (SVs), 2111~2581 copy number variants (CNVs) and 229,357~346,940 simple sequence repeats (SSRs) were detected and annotated. To demonstrate the application of DNA markers, 944 SNPs were filtered for association study of fruit ripening time and 15 highly polymorphic SSRs were selected to analyze the genetic relationship among 221 accessions.The results showed that the use of high-throughput sequencing to develop DNA markers is fast and effective. Comprehensive identification of DNA markers, including SVs and SSRs, would be of benefit to genetic diversity evaluation, genetic mapping, and molecular breeding of peach. Prunus persica, 2n = 16) is a member of the family Rosaceae, subfamily Prunoideae, and currently is widely grown in China, America, Italy, Spain, Japan, and other countries. In the past decade, the development of molecular markers for use in plant genetic research has become essential for geneticists and breeders. Thus, various approaches have been explored and applied in peach, such as restriction fragment length polymorphism markers  (release version 1.0), and a final set of 1,166,551 SNPs, 44,245 SVs, 12,302 CNVs, and 141,895 SSRs were identified, resulting in an average of 5351.1 SNPs per Mb, 202.71 SVs per Mb, 56.4 CNVs per Mb, and 634.43 SSRs per Mb, respectively. Based on the consensus sequence, the polymorphic loci between the identified genotype and the reference were filtered. The polymorphic DNA markers were classified into five groups: SNPs, InDels, SVs, CNVs and SSRs.Next, we analysed the number of genetic variation across each chromosome. We found that the number of polymorphic DNA markers varied across each chromosome Fig. . Most ofArabidopsis thaliana (0.83) [The SNP annotation showed that approximately 4.49 to 7.28% of the total SNPs were located in the coding DNA sequence (CDS) of these six genomes (Table a 0.83)  and ricea (0.83)  and simia (0.83) . In addi  and ricWe further analyzed the annotation of the so-called large-effect SNPs  of them were found to be detected in all six accessions  of all tri-nucleotide repeats. CG/GC and CGC/GCG/CGG/CCG/CGC/GCC were the least repeats of di-nucleotide and tri-nucleotide repeats, respectively. The result indicated A/T nucleotide exhibited a strong bias among SSRs, similar with the study reported before , 18.Of all SSRs, 25,037 17.64%) were located in the 7773 genes. Among them, the number of SSRs in CDS was 8412 (33.60%), and there were 800 in 5’untranslated region (UTR), 630 in 3’UTR  of this association was found in the exon of Prupe.4G171900 which encoded a glutamate receptor protein. And the location has a close distance (< 1 Mb) with the candidate gene Prupe.4G186800 of fruit maturity by another study [We identified a clear year-stable signal in 2011 and 2012 associated with fruit maturity date on Chr. 4, although the association signal in 2012 was lower than the adjusted To detect SSRs with high polymorphism, 2034 SSRs of all 141,895 loci showing polymorphism among the 6 resequenced peach accessions were retained. Next, 1334 (65.6%) mononucleotide repeats were excluded because the loci may have resulted in weak PCR products. Finally, the loci that were detected in more than five accessions were identified for subsequent analysis.The remaining 194 SSRs were used to design primers to test their polymorphism in 21 peach accessions. However, the primer design of 7 SSRs failed due to the high sequence similarity of the flanking sequence of these SSRs with multiple regions in the genome. In addition, a total of 23 primer pairs generated unfavorable amplification products. Thus, 164 SSR primer pairs  compared with those of the previous study, which included different species, such as P. persica, P. ferganensis, P. kansuensis, P. davidiana, and P. mira.In the study, we identified 44,245 SVs, 12,302 CNVs, and 138,476 SSRs across 8 chromosomes in peach with high efficiency via whole-genome sequencing  [Interestingly, SVs were the main element affecting the function of genes associated with key agronomic characteristics in peach, such as flesh color  and fruiSSRs/Mb) . The abuFrequency analysis of various nucleotide repeats of SSRs in the peach genome revealed that mononucleotides were the most abundant SSR , followed by di-, tri-, etc. . DNA purification was performed using RNase I  before sequencing. DNA quality and concentration were measured with a NanoDrop 2000 UV spectrophotometer . The DNA concentrations for sequencing and PCR amplification were diluted to 200 ng/μL and 20 ng/μL, respectively.The genome was sequenced using the Illumina 2500 platform  with a 150 bp pair-end. The adaptor and low-quality sequences were filtered, and all clean reads were aligned to the peach reference genome v1.0  using BWFruit maturity date of 221 peach accessions  was carried out using WEGO .P. persica ‘08–9-107’ using an RNA Extraction kit , following the manufacturer’s protocol. The method for mRNA enrichment, double-stranded cDNA synthesis, digestion, PCR amplification, cDNA library construction, RNA sequencing, data filtering, and the number of fragments per kilobase of exon per million fragments (FPKM) calculation were previously described by Cao et al. [Total RNA was extracted from different tissues, including leaves, flowers, fruit, roots, phloem, and seeds, of o et al. .10P = 4.97 for fruit maturity).To demonstrate the application of different variations, we obtained SNPs from 9.6 Mb to 17.1 Mb on Chromosome (Chr.) 4 according to the previsous QTLs of fruit ripening time , then fiThe primer pairs were designed using Primer 5.0  with the following settings: primer length between 18 and 27 bp, GC content of 40–60%, optimum annealing temperature of at least 50 °C, and PCR product size ranging from 100 to 500 bp. M13 sequences were added to the 5′ end of all the primers . The M13 primers were used to amplify 187 SSR loci in 21 peach accessions. Fifteen fluorescent primer pairs were synthesized using Oligo 192 to analyze genetic relationships among 221 peach accessions.PCR amplification with M13 primers was performed with a GeneAmp PCR System 9700 . The reaction mixture had a total volume of 10 μL and contained 20 ng of template genomic DNA, 0.8 μL of 2.5 μM dNTP, 0.6 μL of each primer at 100 μM, 1 μL of 10× buffer, 0.1 μL of 5 U/μL Taq polymerase, 0.6 μL of 5 μM HEX and 6 μL of sterile water. The PCR conditions were 95 °C for 5 min; 30 cycles of 30 s at 95 °C, 30 s at the annealing temperature of each primer pair at 56 °C, and 30 s at 72 °C; 10 cycles of 30 s at 95 °C, 30 s at 53 °C, and 30 s at 72 °C; and a final step at 60 °C for 30 min. The PCR amplification conditions for fluorescent primers were the same as those described above, but without 0.6 μL of 5 μM HEX in the 10 μL reaction mixture.The polymorphism of the SSR markers was detected using a 3730xl DNA Analyzer . Denaturation conditions were 95 °C for 5 min. The samples were prepared by mixing 1.0 μL of PCR products with 8.5 μL deionized formamide and 0.5 μL ROX-500. The SSR fragment sizes were analyzed with GeneMapper 5.0 .We consulted the literature published in the past few decades and selected 15 highly polymorphic SSR loci based on allele number among different peach varieties. Among them, nine  were selected from the published report by Chen et al. , five (CA), number of private alleles (NPA), Shannon’s information index (I), and genetic distance (GD), were all estimated with POPGENE v1.31 [The molecular diversity parameters, such as the number of alleles per locus  method. We performed statistical test using bootstrap test, and the No. of bootstrap replication was set to 1000.Additional file 1: Figure S1. The statistics of synonymous and nonsynonymous SNPs (a) and large-effect SNPs (b), which could affect the gene function in different peach accessions. Figure S2. GO annotation of genes containing large-effect SNPs. The GO results are summarized in three main categories: biological process, cellular compartment, and molecular function. Figure S3. The NA, NPA, I, and GD index of genotyping in 36 peach accessions using SSR markers developed in the study and reported previously. NA indicates the number of alleles per locus; NPA indicates the number of private alleles; I indicates Shannon’s information index; and GD indicates gene diversity. Figure S4. The NA, NPA, I, and GD index of genotyping in 36 peach accessions using SSR markers developed in the study and reported previously. Table S1. A total of 221 peach accessions were collected to evaluate genetic diversity and perform association analysis. Table S2. The number and percent of different nucleotide repeats located in CDS and UTRs. Table S3. The location of 164 SSRs and their primer sequences designed in this study. Table S4. Polymorphism and allele number estimation of PCR product amplified with 164 SSRs from 21 peach accessions. Table S5. Polymorphism of 15 SSR markers amplified from 221 peach accessions. Table S6. Number of alleles per locus and diversity index detected by 15 polymorphic SSRs among 221 peach accessions. Table S7. Polymorphism comparisons among 36 accessions amplified using SSR markers developed in this study and reported previously.