Search Results (581)

Background: The development of naturally derived pharmaceutical excipients has attracted increasing interest as alternatives to conventional synthetic materials. Methods: In this study, starch–beeswax composites were prepared using native rice starch (RS) and spray-dried rice starch (SDRS) through melt levigation (ML) and emulsification (EM) techniques at starch-to-beeswax ratios of 9:1, 8:2, and 7:3. The physicochemical properties, surface hydrophobicity, morphology, tabletability, and lubrication performance of the resulting composites were evaluated and compared with magnesium stearate (MGS) and hydrogenated vegetable oil (HVO). Results: Co-processing with beeswax markedly increased the water contact angle from 35.4° and 59.7° for RS and SDRS, respectively, to values ranging from 94.5° to 125.1°, indicating successful modification of surface hydrophobicity. SEM analysis demonstrated changes in particle morphology and surface appearance following co-processing, while FT-IR confirmed the coexistence of characteristic starch- and beeswax-associated spectral features without evidence of detectable covalent modification. Co-processed formulations generally maintained or improved tabletability relative to their corresponding starch bases, with SDRS-based composites producing substantially harder tablets than RS-based formulations. The composites also reduced tablet ejection force and improved tablet mechanical properties compared with lubricant-free formulations. Among all samples, SDRS-EM-73 exhibited the best overall performance, reducing ejection force from 386.5 N for the lubricant-free control to 89.2 N, a value comparable to HVO (93.0 N), while producing tablets with high hardness (60.9 N), low friability (0.16%), and acceptable disintegration time (44.8 s). Conclusions: These findings demonstrate that co-processed starch–beeswax composites, particularly SDRS-EM-73, show considerable potential as naturally derived excipients for tablet manufacturing and may serve as sustainable alternatives to conventional tablet lubricants. Full article

There is currently a need for high-value applications of vinegar residue, a major byproduct generated during vinegar production, in order to benefit the environment and economic development. Melanoidins exist in vinegar residue as brown and bioactive macromolecules which are produced during the vinegar brewing process. However, the physicochemical characteristics and potential immunomodulatory activity of melanoidins from vinegar residue (VRM) have yet to be clarified. In this study, VRM exhibited structural heterogeneity, with a molecular weight of 9005.42 Da. Carbohydrates were the dominant component, accounting for 57.86 ± 3.36% (w/w), and xylose was the primary monosaccharide, with molar ratios of 53.15%. In addition, microstructural observations showed clear edges and a relatively smooth surface in VRM samples. Spectral analysis with FTIR showed that VRM has broad-spectrum ultraviolet absorption capacity and contains hydroxyl groups and unsaturated structures. Meanwhile, VRM exhibited higher antioxidant capacity than vinegar melanoidins according to ABTS and FRAP. Furthermore, the effects of VRM on immunomodulation were investigated in macrophages. VRM significantly induced phagocytic capacity and the secretion of NO, TNF-α, and IL-6. VRM at 800 ug/mL effectively exerted an immunomodulatory effect, which was associated with the TLR4-mediated NF-κB pathway. These findings demonstrate that VRM has a polysaccharide skeleton cross-linked with proteins and polyphenols, and possesses antioxidant and immunomodulatory properties. It will provide a novel and functional product for the efficient utilization of vinegar residue. Full article

Walnut kernels are highly valued for their mineral, vitamin, protein, lipid, and polyphenol content. To understand their nutritional value, quality, and potential for human consumption and industrial use, the chemical composition of different genotypes must be analyzed. The kernel composition of 41 walnut genotypes (31 Romanian, 8 Moldovan, and 2 American) from the Research Institute for Fruit Growing Pitesti germplasm collection in Romania was analyzed. The following parameters were analyzed: moisture, ash, sugars, lipids, polyphenols, tannins, flavonoids, carotenoids, and anthocyanins. The Moldovan genotypes exhibited the highest average kernel moisture and ash content, outperforming the Romanian average, while the individual American cultivars sat between them. Regarding sugar content, ‘Hartley’ cv. recorded the highest individual level, followed by the Romanian and Moldovan averages, whereas ‘Chandler’ cv. displayed lower values. For lipids and polyphenolic fractions, ‘Chandler’ cv. prominently surpassed both regional averages, while ‘Hartley’ cv. recorded values well below them, though both American cultivars excelled individually in anthocyanin accumulation. ATR-FTIR spectroscopy combined with second-derivative Savitzky–Golay preprocessing further supported the observed compositional variability. The most discriminative spectral regions were 3050–2800 cm⁻¹ and 1800–900 cm⁻¹, which are mainly associated with functional groups related to lipids, proteins, and carbohydrates. Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) identified distinct compositional groups, with lipid-related spectral features representing the main source of variability among the samples. These results emphasize the significant biochemical diversity among walnut genotypes and support the selection of cultivars with valuable nutritional and technological properties. Full article

Background: Biotrauma from invasive mechanical ventilation (IMV) and extracorporeal membrane oxygenation (ECMO) drives systemic inflammation, metabolic dysregulation, and organ dysfunction in critically ill patients. Therefore, this study aimed to identify clinical and metabolomic features associated with ICU mortality in patients receiving IMV or ECMO, as these remain incompletely characterized. Methods: The retrospective analysis included 30 ICU patients on IMV and 22 on ECMO. Metabolomic and proteomic profiling were performed using ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC-HRMS), and serum spectral analysis by Fourier-transform infrared spectroscopy (FTIRS). Significant variables were incorporated into multivariate logistic regression models, ranked by AIC, AUC, and statistical significance. Model performance was evaluated using stratified 5-fold cross-validation. Final models were adjusted for relevant demographic and clinical covariates. Results: The IMV cohort showed discriminatory FTIRS wavenumbers across all preprocessings, and 155 metabolites plus 14 proteins were significantly altered, with unadjusted models achieving mean AUCs above 0.9. The ECMO cohort showed discriminatory FTIRS wavenumbers in one preprocessing, and 15 metabolites plus 3 proteins were highlighted. FTIRS, metabolomic, and proteomic models reached mean AUCs of 0.967, 0.867, and 0.783, respectively, with lower stability during cross-validation. Adjustment for demographic and clinical covariates reduced model robustness. Conclusions: Stronger and more reproducible molecular signatures related to ICU mortality were observed in the IMV cohort, whereas the ECMO cohort showed reduced model stability, likely reflecting increased biological heterogeneity and small sample size. These findings support the utility of integrated omics for characterizing critical illness and outcome stratification, while reinforcing the need for validation in larger and independent cohorts. Full article

This study investigates the design, fabrication, and manufacturing/mechanical characterization of 3D-printed polylactic acid (PLA) cylindrical filter supports developed as substrates for subsequent hydrochar functionalization. Filters with an outer diameter of 30 mm, a height of 20 mm, and a wall thickness of 3 mm were manufactured by material extrusion additive manufacturing and internally filled with gyroid architectures generated in Bambu Studio at three density levels, namely 10%, 15%, and 20%. The printed filters were first evaluated in terms of weight and compressive response. The main focus of the work was the manufacturing consistency and mechanical response of the gyroid supports, while hydrochar deposition was considered as an initial functionalization screening step. The results showed that increasing gyroid density led to higher maximum compressive stress, while mass-normalized analysis revealed a trade-off between absolute mechanical resistance and material efficiency. Surface-treatment screening trials were then carried out on flat PLA specimens to evaluate whether algae-derived hydrochar could be retained on PLA after alkaline activation. Visual and SEM observations showed partial and heterogeneous hydrochar-related surface coverage, with localized agglomerates and partial masking of the original printing lines, but without the formation of a homogeneous coating. EDX analysis of selected agglomerates revealed C and O together with Na, Cl, K, and Ca, supporting the presence of hydrochar-related/mineral-containing deposits on the treated PLA surface, although K may also be associated with residual species from the KOH activation step. FTIR analysis did not reveal clear hydrochar-related spectral features, indicating that FTIR alone was not sufficient to demonstrate effective homogeneous surface functionalization and supporting the interpretation of heterogeneous surface retention. Overall, the study provides a first manufacturing-oriented basis for PLA gyroid filter supports intended for hydrochar deposition and highlights the need for improved surface activation strategies before subsequent functional validation. Full article

A comprehensive evaluation of allogeneic human bone-derived gelatin (hBG) was conducted as a promising material for regenerative medicine and 3D bioprinting. Comparative analysis with a commercial animal-derived gelatin product (hereinafter CDH) revealed a similar FTIR spectral profile, confirming the retention of key functional groups. Rheological analysis under steady shear showed that hBG is a pseudoplastic fluid with a concentration-dependent viscosity. However, a complete characterization of bioinks requires oscillatory measurements (G′, G″, and gelation point), which are planned in future studies. In vitro experiments on spheroid models (chondroblasts) demonstrated biocompatibility, an absence of cytotoxicity, and support for cell viability in 5% and 10% (hBG-5/10) matrices. Owing to its origin, the material allows for the modeling of “human-in-human” conditions, which makes it a promising precursor for the development of bioinks and matrices in regenerative medicine and tissue engineering. However, definitive positioning of the material as a bioink requires additional oscillatory rheological studies (determination of G′, G″, thixotropy, and gelation point), which were not performed in the present work. Full article

The development of transparent multifunctional coatings capable of combining optical properties with mechanical durability remains a significant challenge in advanced materials engineering. In this study, novel hybrid coatings based on a poly(vinyl butyral)/epoxy resin (PVB/epoxy) matrix reinforced with tungsten disulfide (WS₂) nanostructures were developed and examined for potential application in camouflage protection of glass surfaces. Camouflage aims to reduce the detectability of an object by minimizing the optical contrast between the object and its surrounding environment. For transparent substrates such as glass, this objective is particularly demanding because the transparency must be preserved while reducing unwanted surface reflection and optical signatures over relevant spectral ranges. For this purpose, in this research two types of nanostructures were investigated: fullerene-like nanoparticles (IF-WS₂) and inorganic nanotubes (INT-WS₂). The coatings were fabricated via ultrasonically assisted solution dispersion followed by casting over the glass plates and Teflon molds, and solvent evaporation. Structural, thermal, optical, and mechanical properties were systematically evaluated using SEM, FTIR, DSC, UV-Vis-NIR spectroscopy, gloss measurements, hardness testing, and cavitation wear resistance analysis. The incorporation of WS₂ nanostructures led to improved mechanical performance, with increased hardness and enhanced resistance to cavitation-induced wear. Optical characterization showed moderate reductions in reflectance and controlled transmittance in the visible and near-infrared regions, while overall transparency was maintained. The results indicate that WS₂ nanostructures contribute to both light scattering and absorption, leading to reduced specular reflection and improved optical masking potential. The findings demonstrate that hybrid PVB/epoxy/WS₂ coatings offer a promising approach for designing transparent, mechanically resistant coatings with tunable optical properties, with potential applications in protective glass systems and advanced functional surfaces. Full article

The continuous search for new chemical structures more active and less toxic than those currently in practice is justified on the basis of the use of proven pharmacophoric building blocks (benzimidazole heterocycle, sulfonyl group and amidoxime framework in our case). The aim of the work was to synthesize new O-alkylsulfonyl-β-(benzimidazol-1-yl)propioamidoximes and to test them for in vitro biological activities to identify potentially effective agents. Novel O-alkylsulfonylamidoximes were synthesized in hydrochloride and base forms by the reaction of β-(benzimidazol-1-yl)propioamidoxime with alkylsulfonyl chlorides AlkSO₂Cl (Alk = CH₃, n-C₃H₇, i-C₃H₇, n-C₄H₉) in a mixture of water:acetone in hydrochloride and base forms. Hydrochlorides and bases of the O-alkylsulfonyl-β-(benzimidazol-1-yl)propioamidoximes were obtained in moderate to high yields. The structures of the synthesized compounds were established by physicochemical and spectral (elemental analysis, FT-IR, NMR and X-ray diffraction) methods. The obtained derivatives were tested for antimicrobial, antifungal and antidiabetic activity. Biological screening found effective samples of amidoximes with antimicrobial and antifungal activities that were near or exceeded the activity of the reference drugs gentamicin and nystatin; in addition, two samples with antidiabetic activity higher than acarbose were found. The results of the present study open new possibilities for the novel β-aminopropioamidoxime class as active antimicrobial and antifungal agents, as well as antidiabetic ones. Full article

Citrus peel, a major by-product of citrus processing, is a rich source of pectin and other bioactive compounds. In this study, pectin extracted from seven citrus species was comprehensively characterized for its structural, spectral, thermal, physicochemical, techno-functional, antioxidant, and anti-amylase properties. The extracted pectin (~50% methyl esterification) contained residual cellulose, hemicellulose, lignin, and proteins, with Fourier-transform infrared (FTIR) and ultraviolet-visible (UV-Vis) confirming typical galacturonic acid-based structures. Fluorescence analysis revealed emission shifts (420–500 nm) compared to standard pectin. Thermal analysis indicated multi-stage degradation, with major transitions linked to moisture loss, polysaccharide depolymerization, and lignin oxidation. X-ray diffraction (XRD) confirmed a predominantly amorphous structure with minor cellulose domains. The pectin solution showed negative zeta potential, shear-thinning behavior, and high conductivity. Functionally, it exhibited strong swelling, hygroscopicity, and water/oil holding capacity, but low foaming ability. Biologically, it demonstrated moderate antioxidant activity and α-amylase inhibition. These findings highlight citrus pectin as a promising sustainable ingredient for food and pharmaceutical applications, with future work needed to enhance its solubility and bioactivity. Full article

Malignant pleural mesothelioma (MPM) is an aggressive pleural tumor associated with asbestos exposure. Poor clinical outcome of MPM is often driven by late-stage diagnosis due to non-specific clinical presentation, similarity to pleural lesions (e.g., inflammatory changes, metastatic adenocarcinoma), and limitations of current diagnostic methods. We employed Fourier transform infrared (FTIR) spectroscopy combined with convolutional neural networks (CNNs) to analyze formalin-fixed paraffin-embedded (FFPE) pleural tissue samples from patients with MPM, metastatic adenocarcinoma, pleural inflammation, and normal (healthy) pleura. Glycan analysis of FFPE normal pleura and MPM was performed using ultra-high-performance liquid chromatography (UPLC) and mass spectrometry (MS). Our FTIR-spectral analysis uncovered a strong spectral fingerprint of MPM that was especially apparent in the region typical for C-O and C-C stretches as well as local symmetry region typical for deformation vibrations of CH₂ and C-OH groups, all appearing in carbohydrates. Our orthogonal validation of these findings through a targeted glycomics approach using UPLC confirmed that the MPM N-glycome exhibits a distinct fingerprint that distinguishes it from normal pleural tissue. Through utilization of MS for identifying the exact structures of differentially expressed N-glycan peaks, we also identified two high-mannose N-glycan structures that show a specific biomarker potential for MPM and need to be examined in future studies. Full article

Estimating the post-feeding developmental time of necrophagous larvae remains challenging because body size and behavior provide limited resolution after larvae cease feeding. This study integrated behavioral observation, attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR), chemometric regression modeling, transcriptomic analysis, and reverse transcription quantitative polymerase chain reaction (RT-qPCR) validation to characterize post-feeding development in Sarcophaga peregrina (Robineau-Desvoidy) under 25 °C. The post-feeding stage began at 84.83 ± 1.34 h after larviposition and lasted 38.21 ± 2.29 h. ATR-FTIR spectra from 0, 10, 20, 30, and 40 h post-feeding larvae showed temporal changes in the 1800–900 cm⁻¹ fingerprint region, mainly involving bands associated with proteins, lipids, polysaccharides, and chitin. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and variable importance in projection (VIP) analyses identified discriminative spectral regions, while regression models further evaluated time-estimation performance. Among the models, partial least squares regression (PLS-R) showed the most balanced predictive ability, with the coefficient of determination in prediction (R²P) = 0.920 and the root mean square error of prediction (RMSEP) = 4.00 h in the prediction set. Transcriptomic analysis identified 4641 differentially expressed genes, and RT-qPCR confirmed temporal expression patterns of selected candidate genes. These molecular changes were mainly associated with cuticle/chitin remodeling, protein metabolism, and energy metabolism. Overall, ATR-FTIR combined with chemometric modeling provides a complementary biochemical approach for estimating post-feeding developmental time in S. peregrina under controlled 25 °C conditions, although validation at other temperatures is required before broader application. Full article

Early detection of diabetes mellitus (DM) is essential for preventing disease progression and improving clinical outcomes. However, developing robust machine learning (ML) models for diabetes diagnosis is often constrained by limited data availability, privacy regulations, and challenges with data sharing. This study investigates a privacy-preserving synthetic data augmentation framework for classifying diabetic and non-diabetic blood serum samples using Fourier Transform Infrared (FTIR) spectroscopy. Two deep generative approaches, Autoencoders (AEs) and Generative Adversarial Networks (GANs), were evaluated for their ability to generate realistic synthetic FTIR spectra while preserving the statistical and biochemical characteristics of the original dataset. Synthetic datasets generated by the AE and GAN models were assessed using six ML classifiers: Support Vector Machine (SVM), Random Forest (RF), K-Nearest Neighbors (KNN), Gradient Boosting (GB), Logistic Regression (LoR), and Decision Tree (DT). Model performance was evaluated using accuracy, precision, recall, F1-score, Receiver Operating Characteristic (ROC) curves, and Area Under the Curve (AUC). Results showed that AE-generated spectra retained stronger discriminative characteristics and were more easily distinguished from the original spectra, whereas GAN-generated spectra exhibited lower classifier separability, suggesting closer alignment with the original data distribution and greater realism for privacy-oriented data augmentation. Correlation analysis demonstrated high spectral fidelity for both approaches. Compared with the original spectra, AE-generated spectra achieved r = 0.9990 and R² = 0.9999, whereas GAN-generated spectra achieved r = 0.9982 and R² = 0.9965. The most prominent diabetes related spectral variations were observed in the carbohydrate (1000–1200 cm⁻¹), Amide I (~1650 cm⁻¹), and lipid-associated (3000–3500 cm⁻¹) regions. To explore the transferability of the proposed framework, a preliminary experimental feasibility study was conducted using independently acquired whole blood FTIR spectra. The generated spectra showed strong agreement with the measured whole blood spectra, demonstrating the potential applicability of the framework under alternative sampling conditions. Because the experimental cohort included only one diabetic volunteer, this analysis was intended solely as a proof-of-concept assessment of spectral feasibility and methodological transferability, rather than as a validation of diabetes classification performance. Overall, the findings demonstrate that synthetic data generation can effectively augment limited FTIR datasets while preserving privacy and key spectral characteristics. The proposed framework provides a promising foundation for privacy-aware biomedical data augmentation and future development of robust FTIR diabetes screening systems. The results should be interpreted as methodological evidence of feasibility and synthetic data utility rather than as evidence of clinical diagnostic readiness, as the serum dataset remains modest in size and the independent whole-blood experiment was intentionally exploring. Full article

Background: Rejection remains a major barrier to long-term kidney allograft survival, and pre-transplant risk stratification remains incomplete. This study evaluated whether pre-transplant serum Fourier-transform infrared (FTIR) spectra, analyzed using machine learning methods, could identify kidney transplant recipients at increased risk of subsequent biopsy-proven rejection. Methods: In this retrospective single-center study, 80 pre-transplant serum samples collected on the day of transplantation were initially evaluated; after spectral quality control, 79 samples were retained for analysis. FTIR spectra were acquired in transmission mode and analyzed in the 600–1900 cm⁻¹ and 2800–3400 cm⁻¹ regions. Multiple preprocessing strategies were assessed, including Rubber Band baseline correction, vector normalization, and first- and second-derivative transformation, with and without normalization. Naïve Bayes classifiers with Leave-One-Out Cross-Validation and Fast Correlation-Based Filter feature selection were applied. Results: Exploratory analysis showed broad overlap between groups, indicating a subtle multivariate spectral signal. In the initial exploratory workflow, classifier performance depended strongly on preprocessing and feature selection. Because non-nested feature selection may produce optimistic estimates, the main supervised analysis was repeated using FCBF nested within each LOOCV training fold. The best-performing nested model was obtained using second derivative transformation followed by normalization in the combined 600–1900 and 2800–3400 cm⁻¹ regions, achieving an AUC of 0.837, accuracy of 0.747, sensitivity of 0.675, specificity of 0.821, balanced accuracy of 0.748, and F1-score of 0.730. Permutation testing with 1000 label-randomized repetitions supported performance above chance expectation, with no permuted model reaching the observed AUC (empirical p = 0.000999). Conclusions: Pre-transplant serum FTIR spectroscopy combined with leakage-aware nested machine learning analysis identified an internally validated spectral signal associated with subsequent biopsy-proven rejection. These findings support FTIR as a promising complementary and hypothesis-generating approach for pre-transplant biochemical risk phenotyping, requiring external multicenter validation before clinical application. Full article

Sodium hypochlorite (NaOCl) remains the gold standard irrigant in endodontics due to its proteolytic and antimicrobial properties, whereas hydrogen peroxide (HP) is widely used for internal bleaching because of its oxidative capacity. Both agents have been associated with chemical and structural alterations in dentin; however, the impact of their sequential application on the organic–mineral balance has not been fully elucidated. Objective: To evaluate whether the isolated and sequential application of 5.25% NaOCl and 37.5% HP induces chemical alterations in dentin by analyzing changes in the organic matrix and mineral phase using Fourier-transform infrared spectroscopy (FTIR) and Energy-dispersive X-ray spectroscopy (EDX). Methods: Twenty-four independent dentin sections (n = 6 per group) from six human third molars were distributed using a tooth-balanced allocation into four groups: Control, NaOCl (5.25%, 15 min), HP (37.5%, 30 min), and sequential NaOCl+HP. FTIR assessed organic (amide I, II, III, CH₂) and inorganic (phosphate, carbonate) components through baseline-corrected integrated areas, Full Width at Half Maximum (FWHM), and molecular ratios. Surface elemental composition and the calculated Ca/P atomic ratio were determined by EDX. Multiple sub-measurements per specimen were averaged before statistical analysis. Data were analyzed using Kruskal–Wallis and Mann–Whitney U tests with Bonferroni correction (p < 0.05). Results: FTIR revealed treatment-dependent modifications. NaOCl reduced absorbance in organic-associated bands, indicating collagen degradation, whereas HP altered the mineral phase. The NaOCl+HP group exhibited increased numerical values for integrated band areas, with differences detected in carbonate, phosphate, and amide III bands (p < 0.05), reflecting structural disorganization and modified spectral signal rather than tissue preservation. No differences were detected across the calculated infrared ratios (p > 0.05). EDX showed decreased absolute atomic percentages of Ca, P, and O in the NaOCl+HP group (p < 0.05), indicating structural demineralization, while its stoichiometric Ca/P ratio remained at 1.56. Isolated HP shifted the mineral stoichiometry to the highest numerical Ca/P ratio (1.69; range 1.58–1.80). Fluorine decreased across all treated groups (p < 0.001). Conclusions: Sequential NaOCl and HP application triggers distinct chemical alterations compared to individual treatments, inducing severe structural disorganization of the organic network and absolute mineral depletion of Ca and P. This multi-agent sequence alters dentin stoichiometry, which may compromise the biomechanical integrity of the tissue. Full article

Background: Simultaneous pancreas–kidney (SPK) transplantation can restore renal function and insulin independence, but non-technical pancreas graft dysfunction remains difficult to anticipate. Methods: We conducted an exploratory single-centre retrospective biomarker-modelling study to determine whether day-zero recipient serum Fourier-transform infrared (FTIR) spectra are associated with subsequent loss of insulin independence after SPK transplantation. Results: Among 104 screened recipients, 51 met predefined sample-availability, spectral-quality, data-linkage and endpoint-adjudication criteria; 30 maintained pancreas graft function and 21 developed dysfunction. Cases dominated by early technical surgical failure were excluded. Clinical-only, FTIR-only and FTIR–clinical Naïve Bayes models were evaluated using leave-one-out cross-validation with Fast Correlation-Based Filter feature selection. In locked-feature internal validation, the best FTIR-only model used second-derivative spectra with vector normalization and nine selected wavenumbers, achieving AUC 0.997 (95% CI 0.985–1.000) and accuracy 0.961 (95% CI 0.902–1.000). A fixed-feature permutation analysis exceeded label-randomized performance (empirical p = 0.001). The secondary Group 1 versus Group 3 analysis suggested discrimination of pancreas dysfunction despite preserved kidney function (AUC 0.992; accuracy 0.930). Conclusions: Given the small cohort, high-dimensional input, non-nested feature selection, selection-bias risk and absence of external validation, serum FTIR should be considered a candidate risk-enrichment platform requiring prospective multicentre validation. Full article