Comparing Different Chemometric Approaches to Detect Adulteration of Cold-Pressed Flaxseed Oil with Refined Rapeseed Oil Using Differential Scanning Calorimetry.

Flaxseed oil is one of the best sources of n-3 fatty acids, thus its adulteration with refined oils can lead to a reduction in its nutritional value and overall quality. The purpose of this study was to compare different chemometric models to detect adulteration of flaxseed oil with refined rapeseed oil (RP) using differential scanning calorimetry (DSC). Based on the melting phase transition curve, parameters such as peak temperature (T), peak height (h), and percentage of area (P) were determined for pure and adulterated flaxseed oils with an RP concentration of 5, 10, 20, 30, and 50% (w/w). Significant linear correlations (p ≤ 0.05) between the RP concentration and all DSC parameters were observed, except for parameter h1 for the first peak. In order to assess the usefulness of the DSC technique for detecting adulterations, three chemometric approaches were compared: (1) classification models (linear discriminant analysis-LDA, adaptive regression splines-MARS, support vector machine-SVM, and artificial neural networks-ANNs); (2) regression models (multiple linear regression-MLR, MARS, SVM, ANNs, and PLS); and (3) a combined model of orthogonal partial least squares discriminant analysis (OPLS-DA). With the LDA model, the highest accuracy of 99.5% in classifying the samples, followed by ANN > SVM > MARS, was achieved. Among the regression models, the ANN model showed the highest correlation between observed and predicted values (R = 0.996), while other models showed goodness of fit as following MARS > SVM > MLR. Comparing OPLS-DA and PLS methods, higher values of R2X(cum) = 0.986 and Q2 = 0.973 were observed with the PLS model than OPLS-DA. This study demonstrates the usefulness of the DSC technique and importance of an appropriate chemometric model for predicting the adulteration of cold-pressed flaxseed oil with refined rapeseed oil.

DSC Phase Transition Profiles Analyzed by Control Charts to Determine Markers for the Authenticity and Deterioration of Flaxseed Oil during Storage.

An approach of implementing X-bar and R control charts as a statistical control tool to monitor the changes in the melting profile of fresh and stored flaxseed oils by differential scanning calorimetry (DSC) was used. Phase transition melting profiles were collected after 0, 2, 4, and 6 months of storing flaxseed oils, originating from five different cultivars. Four peaks at around -36, -30, -25, and -12 °C were identified using the deconvolution analysis procedure, which enabled the data to be collected at peak temperature (T), peak height (h), the peak area (A), and the percentages of the area (P A), as well as the ratio calculated from these parameters. Control charts obtained for the second peak of the melting profile showed a significant decrease of peak height (h2) from 0.50 to 0.39 W/g and the percentage of the area (P A2) from 50 to 38%, within the storage time (p ≤ 0.05); thus, they were considered to be indicators of oil deterioration. Strong negative correlations of the unstable parameters of DSC with chemical indicators of the oils' oxidative stability (PV, p-AV, TOTOX) were found. For DSC parameters, related to the first peak (h1, A1) and the third peak (h3, A3), changes were statistically not significant within storage (p > 0.05); thus, they can be used as markers of flaxseed oil authenticity. The study demonstrated that X-bar and R control charts could effectively monitor changes in the specific peaks and calculated ratios from the DSC melting profile of fresh and stored flaxseed oils, serving as reliable indicators of oil deterioration.

Combined electric and magnetic field therapy for bone repair and regeneration: an investigation in a 3-mm and an augmented 17-mm tibia osteotomy model in sheep.

BACKGROUND: Therapies using electromagnetic field technology show evidence of enhanced bone regeneration at the fracture site, potentially preventing delayed or nonunions. METHODS: Combined electric and magnetic field (CEMF) treatment was evaluated in two standardized sheep tibia osteotomy models: a 3-mm non-critical size gap model and a 17-mm critical size defect model augmented with autologous bone grafts, both stabilized with locking compression plates. CEMF treatment was delivered across the fracture gap twice daily for 90 min, starting 4 days postoperatively (post-OP) until sacrifice (9 or 12 weeks post-OP, respectively). Control groups received no CEMF treatment. Bone healing was evaluated radiographically, morphometrically (micro-CT), biomechanically and histologically. RESULTS: In the 3-mm gap model, the CEMF group (n = 6) exhibited higher callus mineral density compared to the Control group (n = 6), two-fold higher biomechanical torsional rigidity and a histologically more advanced callus maturity (no statistically significant differences). In the 17-mm graft model, differences between the Control (n = 6) and CEMF group (n = 6) were more pronounced. The CEMF group showed a radiologically more advanced callus, a higher callus volume (p = 0.003) and a 2.6 × higher biomechanical torsional rigidity (p = 0.024), combined with a histologically more advanced callus maturity and healing. CONCLUSIONS: This study showed that CEMF therapy notably enhanced bone healing resulting in better new bone structure, callus morphology and superior biomechanical properties. This technology could transform a standard inert orthopedic implant into an active device stimulating bone tissue for accelerated healing and regeneration.

Predictive modelling of TBARS changes in the intramuscular lipid fraction of raw ground pork enriched with plant extracts.

The aim of the study was to develop and compare the predictive models of lipid oxidation in minced raw pork meat enriched with selected plant extracts (allspice, basil, bay leaf, black seed, cardamom, caraway, cloves, garlic, nutmeg, onion, oregano, rosemary and thyme) by investigation TBARS values changes during storage at different temperatures. Meat samples with extract addition were stored under various temperatures (4, 8, 12, 16, and 20°C). TBARS values changes in samples stored at 12°C were used as external validation dataset. Lipid oxidation was evaluated by the TBARS content. Lipid oxidation increased with storage time and temperature. The dependence of lipid oxidation on temperature was adequately modelled by the Arrhenius and log-logistic equation with high R2 coefficients (0.98-0.99). Kinetic models and artificial neural networks (ANNs) were used to build the predictive models. The obtained result demonstrates that both kinetic Arrhenius (R 2 = 0.83) and log-logistic (R 2 = 0.84) models as well as ANN (R 2 = 0.99) model can predict TBARS changes in raw ground pork meat during storage.

Chemometric Analysis of Fatty Acid Composition of Raw Chicken, Beef, and Pork Meat with Plant Extract Addition during Refrigerated Storage.

During the shelf-life, meat undergoes a number of processes that negatively affect the quality of the product, including fatty acid composition. The application of various plant extracts in meat could affect the changes of fatty acids during storage. Thus, the aim of this study was to investigate the effect of various spice and herb extracts on fatty acid composition in raw pork, beef, and chicken meat when stored at 4 °C for 13 days. Based on multivariate statistical analysis, two datasets were extracted from each type of meat. One dataset included samples with allspice, bay leaf, black seed, cardamom, caraway, clove, and nutmeg with the high share of total MUFA (monounsaturated fatty acids) in chicken and pork meat and high MUFA and PUFA (polyunsaturated fatty acids) contribution in beef meat after storage. The second dataset included basil, garlic, onion, oregano, rosemary, and thyme with high PUFA share in chicken and pork meat and high SFA (saturated fatty acids) contribution in beef meat. From the regression analysis, a significant effect of time on fatty acid composition in meat was reported. Generally, the rates of fatty acid changes were dependent on the plant extract incorporated into the meat. The most visible effect of plant extracts was obtained in chicken meat. In chicken meat with plant extracts, the rates of SFA and PUFA changes with time were slower compared to the control sample. In summary, the fatty acid composition of intramuscular fat varied during storage, and the addition of plant extracts significantly affected the rate of these changes, which was dependent on the meat matrix.

Prediction of Thiol Group Changes in Minced Raw and Cooked Chicken Meat with Plant Extracts-Kinetic and Neural Network Approaches.

The aim of the study was to develop predictive models of thiol group (SH) level changes in minced raw and heat-treated chicken meat enriched with selected plant extracts (allspice, basil, bay leaf, black seed, cardamom, caraway, cloves, garlic, nutmeg, onion, oregano, rosemary, and thyme) during storage at different temperatures. Meat samples with extract addition were stored under various temperatures (4, 8, 12, 16, and 20 °C). SH changes were measured spectrophotometrically using Ellman's reagent. Samples stored at 12 °C were used as the external validation dataset. SH content decreased with storage time and temperature. The dependence of SH changes on temperature was adequately modeled by the Arrhenius equation with average high R2 coefficients for raw meat (R2 = 0.951) and heat-treated meat (R2 = 0.968). Kinetic models and artificial neural networks (ANNs) were used to build the predictive models of thiol group decay during meat storage. The obtained results demonstrate that both kinetic Arrhenius (R2 = 0.853 and 0.872 for raw and cooked meat, respectively) and ANN (R2 = 0.803) models can predict thiol group changes in raw and cooked ground chicken meat during storage.

Predictive Modeling of Thiol Changes in Raw Ground Pork as Affected by 13 Plant Extracts-Application of Arrhenius, Log-logistic and Artificial Neural Network Models.

In this study, predictive models of protein oxidation, expressed as the content of thiol groups (SH), in raw ground pork were established and their accuracy was compared. The SH changes were monitored during, maximum, 11 days of storage at five temperature levels: 4, 8, 12, 16, and 20 °C. The effect of 13 plant extracts, including spices such as allspice, black seed, cardamom, caraway, cloves, garlic, nutmeg, and onion, and herbs such as basil, bay leaf, oregano, rosemary, and thyme, on protein oxidation in pork was studied. The zero-order function was used to described SH changes with time. The effect of temperature was assessed by using Arrhenius and log-logistic equations. Artificial neural network (ANN) models were also developed. The results obtained showed very good acceptability of the models for the monitoring and prediction of protein oxidation in raw pork samples. High average R2 coefficients equal to 0.948, 0.957, and 0.944 were obtained for Arhhenius, log-logistic and ANN models, respectively. Multiple linear regression (MLR) was used to assess the influence of plant extracts on protein oxidation and showed oregano as the most potent antioxidant among the tested ones in raw ground pork.

Predictive Modeling of Changes in TBARS in the Intramuscular Lipid Fraction of Raw Ground Beef Enriched with Plant Extracts.

The aim of the study was to develop and compare the predictive models of lipid oxidation in minced raw beef meat enriched with selected plant extracts (allspice, basil, bay leaf, black seed, cardamom, caraway, cloves, garlic, nutmeg, onion, oregano, rosemary and thyme) expressed as value changes of TBARS (thiobarbituric acid reactive substances) in various time/temperature conditions. Meat samples were stored at the temperatures of 4, 8, 12, 16 and 20 °C. The value changes of TBARS in samples stored at 12 °C were used as the external validation dataset. Lipid oxidation increased significantly with storage time and temperature. The rate of this increase varied depending on the addition of the plant extract and was the most pronounced in the control sample. The dependence of lipid oxidation on temperature was adequately modeled by the Arrhenius and log-logistic equation with high average R2 coefficients (≥0.98) calculated for all extracts. Kinetic models and artificial neural networks (ANNs) were used to build the predictive models. The obtained result demonstrates that both kinetic Arrhenius (R2 = 0.972) and log-logistic (R2 = 0.938) models as well as ANN (R2 = 0.935) models can predict changes in TBARS in raw ground beef meat during storage.

Comprehensive Thermal Characteristics of Different Cultivars of Flaxseed Oil (Linum usittatissimum L.).

The aim of this study was to describe the thermal properties of selected cultivars of flaxseed oil by the use of the differential scanning calorimetry (DSC) technique. The crystallization and melting profiles were analyzed depending on different scanning rates (1, 2, 5 °C/min) as well as oxidative induction time (OIT) isothermally at 120 °C and 140 °C, and oxidation onset temperatures (Ton) at 2 and 5 °C/min were measured. The crystallization was manifested as a single peak, differing for a cooling rate of 1 and 2 °C/min. The melting curves were more complex with differences among the cultivars for a heating rate of 1 and 2 °C/min, while for 5 °C/min, the profiles did not differ, which could be utilized in analytics for profiling in order to assess the authenticity of the flaxseed oil. Moreover, it was observed that flaxseed oil was highly susceptible to thermal oxidation, and its stability decreased with increasing temperature and decreasing heating rate. Significant negative linear correlations were found between unsaturated fatty acid content (C18:2, C18:3 n-3) and DSC parameters (OIT, Ton). Principal component analysis (PCA) also established a strong correlation between total oxidation value (TOTOX), peroxide value (PV) and all DSC parameters of thermo-oxidative stability.

Physical Properties, Chemical Analysis, and Evaluation of Antimicrobial Response of New Polylactide/Alginate/Copper Composite Materials.

In recent years, due to an expansion of antibiotic-resistant microorganisms, there has been growing interest in biodegradable and antibacterial polymers that can be used in selected biomedical applications. The present work describes the synthesis of antimicrobial polylactide-copper alginate (PLA-ALG-Cu2+) composite fibers and their characterization. The composites were prepared by immersing PLA fibers in aqueous solution of sodium alginate, followed by ionic cross-linking of alginate chains within the polylactide fibers with Cu(II) ions to yield PLA-ALG-Cu2+ composite fibers. The composites, so prepared, were characterized by scanning electron microscopy (SEM), UV/VIS transmittance and attenuated total reflection Fourier-transform infrared spectroscopy ATR-FTIR, and by determination of their specific surface area (SSA), total/average pore volumes (through application of the 5-point Brunauer-Emmett-Teller method (BET)), and ability to block UV radiation (determination of the ultraviolet protection factor (UPF) of samples). The composites were also subjected to in vitro antimicrobial activity evaluation tests against colonies of Gram-negative (E. coli) and Gram-positive (S. aureus) bacteria and antifungal susceptibility tests against Aspergillus niger and Chaetomium globosum fungal mold species. All the results obtained in this work showed that the obtained composites were promising materials to be used as an antimicrobial wound dressing.

The Power of Human Protective Modifiers: PLS3 and CORO1C Unravel Impaired Endocytosis in Spinal Muscular Atrophy and Rescue SMA Phenotype.

Homozygous loss of SMN1 causes spinal muscular atrophy (SMA), the most common and devastating childhood genetic motor-neuron disease. The copy gene SMN2 produces only ∼10% functional SMN protein, insufficient to counteract development of SMA. In contrast, the human genetic modifier plastin 3 (PLS3), an actin-binding and -bundling protein, fully protects against SMA in SMN1-deleted individuals carrying 3-4 SMN2 copies. Here, we demonstrate that the combinatorial effect of suboptimal SMN antisense oligonucleotide treatment and PLS3 overexpression-a situation resembling the human condition in asymptomatic SMN1-deleted individuals-rescues survival (from 14 to >250 days) and motoric abilities in a severe SMA mouse model. Because PLS3 knockout in yeast impairs endocytosis, we hypothesized that disturbed endocytosis might be a key cellular mechanism underlying impaired neurotransmission and neuromuscular junction maintenance in SMA. Indeed, SMN deficit dramatically reduced endocytosis, which was restored to normal levels by PLS3 overexpression. Upon low-frequency electro-stimulation, endocytotic FM1-43 (SynaptoGreen) uptake in the presynaptic terminal of neuromuscular junctions was restored to control levels in SMA-PLS3 mice. Moreover, proteomics and biochemical analysis revealed CORO1C, another F-actin binding protein, whose direct binding to PLS3 is dependent on calcium. Similar to PLS3 overexpression, CORO1C overexpression restored fluid-phase endocytosis in SMN-knockdown cells by elevating F-actin amounts and rescued the axonal truncation and branching phenotype in Smn-depleted zebrafish. Our findings emphasize the power of genetic modifiers to unravel the cellular pathomechanisms underlying SMA and the power of combinatorial therapy based on splice correction of SMN2 and endocytosis improvement to efficiently treat SMA.

Flavoromics approach in monitoring changes in volatile compounds of virgin rapeseed oil caused by seed roasting.

Two varieties of rapeseed (one high oleic - containing 76% of oleic acid, and the other - containing 62% of oleic acid) were used to produce virgin (pressed) oil. The rapeseeds were roasted at different temperature/time combinations (at 140-180°C, and for 5-15min); subsequently, oil was pressed from the roasted seeds. The roasting improved the flavour and contributed to a substantial increase in the amount of a potent antioxidant-canolol. The changes in volatile compounds related to roasting conditions were monitored using comprehensive gas chromatography-mass spectrometry (GC×GC-ToFMS), and the key odorants for the non-roasted and roasted seeds oils were determined by gas chromatography-olfactometry (GC-O). The most important compounds determining the flavour of oils obtained from the roasted seeds were dimethyl sulphide, dimethyltrisulfide, 2,3-diethyl-5-methylpyrazine, 2,3-butenedione, octanal, 3-isopropyl-2-methoxypyrazine and phenylacetaldehyde. For the oils obtained from the non-roasted seeds, the dominant compounds were dimethylsulfide, hexanal and octanal. Based on GC×GC-ToFMS and principal component analysis (PCA) of the data, several compounds were identified that were associated with roasting at the highest temperatures regardless of the rapeseed variety: these were, among others, methyl ketones (2-hexanone, 2-heptanone and 2-octanone).

Investigational therapies for the treatment of spinal muscular atrophy.

INTRODUCTION: Currently, there is no cure available for the hereditary neurodegenerative disease proximal spinal muscular atrophy (SMA), which is the number one genetic killer in early childhood. However, growing knowledge of SMA pathophysiology has opened new avenues for potential therapeutic interventions. AREAS COVERED: This review summarizes a variety of investigational therapeutic approaches for SMA. Focusing on the current state-of-the-art applications, the authors discuss the outcome of the first clinical interventions and compare the first results from the newest strategies. The achievements of the investigational drugs highlighted in this article were deduced from original articles, pharmaceutical company press releases and clinical trial results. EXPERT OPINION: Nearly two decades after the discovery of the disease causing gene survival motor neuron 1, many therapeutic options for SMA have been developed, some of which made it to clinical trials but could not prove their promising experimental results. Recently, big research efforts from academia, government and the pharmaceutical industry have led to the development of highly promising compounds that are currently in clinical trials, and which could lead to feasible treatment options in the future.

Identification of the botanical origin of raw spirits produced from rye, potato, and corn based on volatile compounds analysis using a SPME-MS method.

Determination of the botanical origin of raw spirit used for alcoholic beverage production is of great importance for rectifying units, control laboratories, and proper product labeling. Raw spirit samples (138) produced from rye, corn, and potato were analyzed using a solid phase microextraction-mass spectrometry (SPME-MS) method, which involved volatiles preconcentration by SPME with subsequent volatile fraction characterization by MS without particular compounds separation by GC. Obtained data were treated using principal component analysis and linear discriminant analysis (LDA) to test the possibility of sample classification. SPME sampling conditions allowed rapid extraction in 2 min at 50 °C using a carboxen/divinylbenzene/polydimethylsiloxane fiber, followed by rapid MS analysis. Use of LDA made possible the classification of raw spirits based on the material they were produced from. The classification ability of the developed SPME-MS method was 100%, whereas its prediction ability was 96%.