Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy Research Articles

Design of Silk Fabric Surface with Enhanced Antiseptic Properties through Graft Modification and Iodophor Integration

AbstractTo improve the hydrophobic character of silk and impart iodine complex ion adsorption, the surface of woven silk fabric is enriched by different functional groups through the grafting of N‐vinylpyrrolidone (NVP), ethylene glycol dimethacrylate (EGDMA), and their mixtures (NVP–EGDMA). The dominant fibrous texture of silk enables an efficient graft copolymerization in terms of high grafting yield (>30%) after applying a mild degumming process. The structural and morphological alterations in the silk surface are evidenced with attenuated total reflectance‐fourier transform infrared spectroscopy (ATR‐FTIR), X‐ray diffraction (XRD), and scanning electron microscopy (SEM) techniques. The imparted hydrophilicity property of the samples is revealed by contact angle–wetting time measurements. The usability of the graft‐modified samples as an iodophor polymeric substrate is then examined by treatment with I2/KI solutions, and the results are monitored using UV–vis spectroscopy. It is obtained that the NVP–EGDMA mixture‐grafted sample exhibits satisfactorily high iodine adsorption compared to untreated and NVP‐grafted silk samples, such as 0.05 g per 1 g fabric with high antibacterial activity against various pathogens, including methicillin‐resistant Staphylococcus aureus (MRSA) responsible for hospital‐acquired infections. This finding evidences its potential as an alternative antiseptic tissue for biomedical applications.

Chitosan-supported calcium hydroxide hybrid material as new, efficient, and recyclable catalyst for biodiesel production

In this work, a novel supported catalyst was prepared starting from calcium chloride and chitosan flakes using a very mild approach in an aqueous medium without final calcination at high temperatures. The as-prepared catalyst was fully characterized by thermogravimetric analysis (TGA), attenuated total reflectance Fourier transform infrared (ATR-FTIR), and X-ray photoelectron (XPS) spectroscopies, transmission and scanning electron microscopies (TEM, SEM), Energy Dispersive X-ray Spectroscopy (EDS), demonstrating that it consists of calcium hydroxide particles of about 200 nm supported on chitosan micrometric structures. The most crucial parameters in the transesterification process were investigated. A methanol/oil ratio of 6:1, a reaction time of 6 h, and a temperature of 60 °C were found to lead to complete conversion. A reaction on a gram scale using waste oil as a starting material was also tested, and excellent results were achieved. Moreover, the catalyst proved to be very robust, since even after the 10th recycle, the conversion rate remained at around 90 %. Spectroscopic analyses showed minimal leaching of material without modification of chemical composition. The kinetic behavior (activation energy, Ea) of the catalyst was also studied, which resulted in similar outcomes to Ca-based systems present in the literature, but without the need for costly preparations and with superior recycling resistance. An Ea value of 63.25 kJ·mol−1 was found, which agrees with data reported in the literature.

Advancements towards the development artificial intelligence for sensory analysis: Integrating pattern recognition and signal processing in ATR-FTIR analysis of spirits

Spirits have been gaining acceptance by international consumers due to its distinct organoleptic profile, which provide each beverage with a characteristic sensation of the product (taste, smell, and color). However, it is important to establish differences by an analytical technique supported by artificial intelligence to demonstrate with mathematical solutions rather of being subjective such as human senses. To reduce the uncertainty associated to the sensory analysis, the present study shows as strategy the recognition of patterns of ATR-FTIR spectra of a variety of distilled beverages: Tequila 100% agave (n = 20), Mezcal (n = 20), Raicilla (n = 20), Aguardiente (n = 20), and Vodka (n = 20). All ATR-FTIR spectra present seven characteristic bands associated with methanol, ethanol, isoamyl alcohol, butanol, ethyl acetate, acetaldehyde, and furfural in beverages. Based on the analysis of the peak signals obtained from the Attenuated Total Reflection Fourier Transform Infrared (ATR-FTIR) spectra, the implementation of an Artificial Neural Network was proposed with the objective to classify each alcoholic beverage in its corresponding groups. Results showed that the artificial intelligence algorithm proposed permits to correct classify 100% of the samples being a great alternative strategy being innovative, fast, and of low-cost strengthening food quality analyses by machine learning decision-making.

ATR-FTIR spectroscopy and Machine learning for sustainable wood sourcing and species Identification: Applications to wood forensics

Wood forensics, a vital tool in addressing global concerns surrounding illegal logging and the authenticity of wood products, plays a pivotal role in promoting sustainable forestry practices. The integration of Attenuated Total Reflectance Fourier-Transform Infrared (ATR-FTIR) spectroscopy and machine learning presents a potent approach to streamline identification processes and enhance responsible wood sourcing. ATR-FTIR facilitates the detailed characterization of wood components by analyzing spectral data, revealing unique chemical signatures associated with different wood species. This study focuses on Eucalyptus, Dalbergia, and Populus wood species in India, revealing common peaks related to cellulose, flavones, hemicellulose, and lignin constituents. Isolation Forest (iForest) identifies outliers, subsequently removed for supervised modelling, while Principal Component Analysis (PCA) reduces dimensionality effectively. Tree-based supervised machine learning algorithms, including Decision Tree, Extra Tree, Random Forest, and CatBoost classifiers, enhances the accuracy of wood species discrimination by deciphering complex patterns within ATR-FTIR spectra. Further, evaluation through various performance metrics supports the comparative analysis. The outcomes of this study hold significant value for law enforcement agencies in combating illegal logging and timber trade, and potential applications in quality control for timber industries. This research substantiates its real-world applicability, marking a noteworthy advancement in the evolving field of wood forensics.

Detection of meloxicam residues in milk using ATR- FTIR spectroscopy coupled with chemometrics

Meloxicam (MELX), a non-steroidal anti-inflammatory drug (NSAID), is frequently administered to cattle, poses a risk to human health when it is found in milk. Regulatory bodies of EU, Canada, China and India have prescribed maximum residue limits for MELX in milk as 15, 35 and 15 and 10 μg/kg, respectively. This study explores the use of attenuated total reflectance- Fourier transform infrared (ATR-FTIR) spectroscopy in conjunction with chemometric techniques to detect MELX residues in milk. Samples of pure milk and milk samples spiked with MELX at different concentrations ranging from 1 to 50 μg/kg were analysed. ATR-FTIR measurements were taken in the wavenumber range of 4000–400 cm−1 for all the samples. Principal component analysis (PCA) was applied in the regions of 2940–2840 and 1765–1730 cm−1 to differentiate clusters of milk sample with those of MELX and milk spiked with MELX samples. The coefficient of determination (R2) values for calibration and validation sets in wavenumber regions of 2940–2840 and 1765–1730 cm−1 were >0.92 and > 0.94, respectively for the developed partial least squares regression (PLSR) models. All the samples showed 100% classification efficiency using the soft independent modeling of class analogy (SIMCA) technique. The study concluded that the presence of MELX residues can be detected in milk even at 1 μg/kg level using ATR-FTIR and chemometrics. Results obtained from developed FTIR based chemometric method were in agreement with those obtained from LC-MS/MS method and have the potential for application in screening milk samples for the presence of MELX.

Novel sulfonated calixarenes derived crosslinker for reinforcing and toughening collagen: Relevance between structure and properties

AbstractCollagen is widely used in the development of new functional materials due to its high structural stability, good biocompatibility, and excellent hydrophilicity, but the collagen protein denatures easily, which makes its thermal stability and mechanical strength difficult to reach some of the parameters required in the application. To solve this, protein crosslinking is an effective way to better use collagen. In this paper, we compared the thermal stability and morphological stability of three kinds of sulfonated calixarenes crosslinked collagen before and after the treatment. The results showed that sulfonated calixarenes could significantly improve the thermal stability and morphological stability of dermal collagen. The reinforcing and toughening mechanism of the sulfonated calixarenes was revealed by scanning electron microscopy (SEM), infrared spectroscopy (FT‐IR), attenuated total reflection‐Fourier transform infrared spectroscopy (ATR‐FTIR), ultraviolet–visible–near‐infrared (UV–vis–NIR) spectrometer, X‐ray diffraction detection (XRD), atomic force microscopy (AFM), and circular dichroism (CD) detection. The results showed that sulfonated calixarenes were evenly distributed in collagen fibers and formed hydrogen bonds or electrovalent bonds with amino groups, peptide groups, or amide groups in collagen to improve the thermal stability of the collagen. Three kinds of sulfonated calixarenes enter collagen fiber to support the collagen, increase the three‐dimensional weave angle of collagen, and improve the physical and mechanical properties of collagen, thereby toughening and enhancing the collagen. Based on the above studies, the reinforcing and toughening mechanism of the sulfonated calixarenes crosslinked collagen was established. Confirmed the existence of hydrogen bonds between the three sulfonated calixarenes and collagen, and the nonchemical bond energy of the system was proportional to the molecular size of sulfonated calixarenes.

Surface properties of schwertmannite with different sulfate contents and its effect on Cr(VI) adsorption

Sulfate is a critical component of schwertmannite. However, the sulfate content of schwertmannite decreases with the increase in AMD-polluted river pH value, and its impact on the surface properties and Cr(VI) adsorption of schwertmannite remains unclear. To address this issue, different methods, including batch adsorption, N2 physisorption, scanning electron microscopy (SEM), potentiometric titration, X-ray photoelectron spectroscopy (XPS), attenuated total reflectance–Fourier transform infrared spectroscopy (ATR-FTIR) in combination with two-dimensional correlation spectroscopy (2D-COS) analysis, and surface complexation modeling (SCM) were employed. Our results showed that sulfate existed as both non-protonated bidentate-binuclear complexes and non-protonated outer-sphere complexes in schwertmannite. The surface morphology and particle size of schwertmannite were unaffected by the sulfate content. However, a decrease in sulfate content resulted in a drop in the negative charge on the surface of schwertmannite, which is conducive to particle aggregation. An increase in pH, on the other hand, raised the negative charge and encouraged the dispersion of the particles. And then, reducing the sulfate content of schwertmannite led to a decrease in acid-base buffer and Cr(VI) adsorption capacity of schwertmannite. The adsorption process of Cr(VI) by schwertmannite can be divided into two stages. In the first stage, Cr(VI) was adsorbed primarily through anion exchange reactions with the sulfate; however, the contribution of surface complexation gradually increased as the initial sulfate content decreased because of a reduced likelihood of anion exchange and an increase in the specific surface area of schwertmannite. Additionally, the behavior of sulfate and Cr(VI) in this stage could be predicted based on the initial sulfate content of schwertmannite. In the second stage, surface complexation with hydroxyl sites became the predominant mechanism of adsorption, which still exhibited great potential at higher Cr(VI) concentrations. Finally, the aforementioned hypothesis was used to establish a CD-MUSIC model, and the fitting results demonstrated that the density and Cr(VI) adsorption capacity of the sulfate site dropped as the sulfate content decreased, while the hydroxyl site was less impacted. The findings have provided insights into further understanding the properties of schwertmannite and its adsorption of Cr(VI).

Impact of different smoke flavors on the quality of hermetically sealed green chili paste (Nam Prik Num)

This research examines how various smoke flavors such as powdered smoke, teak, and longan wood affect the quality of hermetically sealed green chili paste (Nam Prik Num). Teak and longan wood smoking produced a darker green color than the control and smoke powder samples. The smoky aroma had no impact on yield, pH, water release, or chemical composition. However, it did influence moisture content, lightness (L*), redness (a*), yellowness (b*), and water activity (aw) compared to control and smoke-flavored samples. The attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR) showed structural changes, control with C-H groups at 2924 cm−1, and smoking introduced –COOR at 1744 cm−1, signifying flavor-induced alterations. The heightened peak hinted at a distinctive smoke aroma, deepening our understanding of molecular transformations. Sample smoke flavor compounds studied using a solid-phase microextraction-gas chromatography-mass spectrometry (SPME-GC-MS), included hydrocarbons, alcohol, aldehydes, ketones, esters, acids, and sulfide compounds, with sulfide compounds, alcohol, hydrocarbon, and alcohol compounds as the predominant volatiles. Nam Prik Num with smoke powder scored higher in appearance, color, aroma, taste, and texture than the control. Flavoring with smoke powder is more effective than charcoal grilling for adding smoky taste to Nam Prik Num.

Rapid assessment of the blood-feeding histories of wild-caught malaria mosquitoes using mid-infrared spectroscopy and machine learning

BackgroundThe degree to which Anopheles mosquitoes prefer biting humans over other vertebrate hosts, i.e. the human blood index (HBI), is a crucial parameter for assessing malaria transmission risk. However, existing techniques for identifying mosquito blood meals are demanding in terms of time and effort, involve costly reagents, and are prone to inaccuracies due to factors such as cross-reactivity with other antigens or partially digested blood meals in the mosquito gut. This study demonstrates the first field application of mid-infrared spectroscopy and machine learning (MIRS-ML), to rapidly assess the blood-feeding histories of malaria vectors, with direct comparison to PCR assays.Methods and resultsFemale Anopheles funestus mosquitoes (N = 1854) were collected from rural Tanzania and desiccated then scanned with an attenuated total reflectance Fourier-transform Infrared (ATR-FTIR) spectrometer. Blood meals were confirmed by PCR, establishing the ‘ground truth’ for machine learning algorithms. Logistic regression and multi-layer perceptron classifiers were employed to identify blood meal sources, achieving accuracies of 88%–90%, respectively, as well as HBI estimates aligning well with the PCR-based standard HBI.ConclusionsThis research provides evidence of MIRS-ML effectiveness in classifying blood meals in wild Anopheles funestus, as a potential complementary surveillance tool in settings where conventional molecular techniques are impractical. The cost-effectiveness, simplicity, and scalability of MIRS-ML, along with its generalizability, outweigh minor gaps in HBI estimation. Since this approach has already been demonstrated for measuring other entomological and parasitological indicators of malaria, the validation in this study broadens its range of use cases, positioning it as an integrated system for estimating pathogen transmission risk and evaluating the impact of interventions.

Microplastic concentrations and risk assessment in water, sediment and invertebrates from Simon's Town, South Africa

Plastic pollution is an ever-increasing threat globally and poor waste management in South Africa has caused an increase in plastic leakage into the environment. Plastic waste in the environment are categorized according to size and plastic particles smaller than 5 mm in size are regarded as microplastics (MPs), and little to no research has been done on MPs pollution within the marine coastal environment and rocky shores in South Africa. Sampling was done in February 2020 at a rocky shore within Simon's Town Marina, Cape Town. MPs were extracted from collected water (n = 5), sediment (n = 5) and biota (n ≤ 30) samples. The extracted MPs were further classified based on shape, colour, size and an attenuated total reflectance Fourier-transform infrared (ATR-FTIR) instrument was utilized for polymer type identification The risks posed by MPs because of concentration at which they occurred and chemical composition were assessed in all the sample types. As expected, MPs were higher in sediment (38 ± 2 MP/kg) than in water (0.37 ± 0.06 MP/L) as the area has low water energy, allowing MP particles to settle within the sediment. Filter-feeding organisms had the lowest average MP particle concentrations (0.28 ± 0.04 MP/g) but displayed the highest variation of MP particle colours due to the non-selective feeding strategy, where other feeding strategies ingested mostly black/grey particles. The dominant MP size was between 100 μm and 500 μm in size for all samples combined, with the most abundant MP polymer type being nylon (27.27 %), polyethylene terephthalate (PET) (18.18 %) and natural MP particles such as cotton (18.18 %). The risk assessment indicated that polymer type poses a greater risk of MP pollution than MP concentrations.

Evaluation of the Quality Changes in Three Commercial Pastourma Samples during Refrigerated Storage Using Physicochemical, Microbiological, and Image Analyses Combined with Chemometrics.

Despite the inherent stability of dried and cured products, such as pastourma, appropriate refrigeration remains essential for preserving their optimal characteristics. This study explored quality and safety characteristics in lamb, beef, and buffalo pastourma during 16-day refrigeration storage after package opening. The comprehensive approach employed Attenuated Total Reflection-Fourier-Transform Infrared (ATR-FTIR) spectroscopy, colorimetry, and image analysis, alongside physicochemical and microbiological analyses, to shed light on these alterations. The findings reveal a reduction in textural uniformity and color vibrancy (fading reds and yellows) across all samples during storage, with lamb pastourma exhibiting the most pronounced effects. Notably, image analysis emerged as a powerful tool, enabling the accurate classification of samples based on storage duration. Additionally, significant variations were observed in moisture content, hue angle, firmness, and TBARS levels, highlighting their influence on pastourma quality. The study documented a gradual decrease in lactic acid bacteria and aerobic plate count populations over time. ATR-FTIR spectra's interpretation revealed the presence of lipids, proteins, carbohydrates, and water. Protein secondary structures, demonstrably influenced by the meat type used, exhibited significant changes during storage, potentially impacting the functional and textural properties of pastourma. Overall, the findings contribute to a deeper understanding of pastourma spoilage during storage, paving the way for the development of improved preservation and storage strategies.

An Insight into Viscosity and Conductivity in the Formulation of Co-axial Electrospun Carica papaya Leaf Extract

Objective: This research aimed to investigate the application of the coaxial electrospun method for the production of natural extracts (papaya leaf extract) fibre films. This was achieved through utilising different polymers and with a focus on the conductivity and the viscosity of polymer solutions as critical parameters to generate successful fibres. Significance: Electrospinning is a promising trending manufacturing method for incorporating thermolabile herbal extracts using coaxial electrospun features. However, the complexity of the electrospinning process and the feasibility of the product required precise scrutiny. Methods: The electrospinning solution parameters (conductivity and viscosity) were evaluated by employing various ratios of Eudragit L100 (EL100) and Eudragit L100-55 (EL100-55) pre-spinning polymeric blend solutions. The electrospinning process and ambient parameters were optimised. Following that, the in-silico physicochemical properties of phytochemical marker, rutin, were illustrated using SwissADME web tool. Both freeze-dried Carica papaya leaf extract and its produced films were characterised using Scanning Electron Microscopy (SEM), Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR), polarised light microscopy, and X-Ray Powder Diffraction (XRPD). Results: The optimal values of conductivity (≈40-44 × 10−4 S/m) and viscosity (≈32-42 × 10−3 Pa·s) were determined for producing evenly distributed and small fibre diameters in SEM images. These parameters significance was highlighted in acquiring and maintaining adequate tangential stress for fibre elongation, which would consequently affect the morphology and diameter of the fibres formed. Conclusion: In conclusion, the solution, process, and ambient parameters are significant in developing natural extracts into films via electrospinning technology, and this includes the promising Carica papaya leaf extract films produced by coaxial electrospinning.

New methods for the identification of malachite pigments with varying particle sizes used in ancient Chinese murals by spectroscopic techniques

This study attempts to propose a simple, low-interventive and higher accuracy identification method for malachite pigments with varying particle sizes based on attenuated total reflection-Fourier transform infrared (ATR-FTIR), and evaluate the accuracy of ATR-FTIR and ultraviolet–visible near-infrared (UV-VIS-NIR) spectroscopy for identifying particle sizes. The micro-morphology, particle size, colour difference, and spectral characteristics of the malachite samples were determined using scanning electron microscopy (SEM), laser particle size analysis, colourimetry, UV-VIS-NIR and ATR-FTIR spectrometry. The principal component analysis (PCA) and mathematical models based on nonlinear curve fitting using UV-VIS-NIR and FTIR spectral data were developed and evaluated for the particle size identification of various malachite samples (pure malachite samples, fresh and aged malachite-rabbit glue samples). SEM morphological results showed that the malachite pigments with smaller particle sizes appear to have irregular flakes with a few loose agglomerated granules attached to the surface. The weight-specific surface area also increased gradually as the pigment particle size decreased. The colour difference results revealed that smaller malachite particle size gradually shifted toward the red–blue regions in CIE L*a*b* colour space. In addition, more intense reflectance and IR spectral absorbance peaks were observed in the case of the smaller particle size. The above proposed methods of particle size identification proved to be highly feasible and effective in predicting pigment particle size, which were confirmed by the PCA identification results and the mathematical model. Also, ATR-FTIR spectroscopy could provide more accurate predictions than UV-VIS-NIR spectroscopy, by keeping prediction errors below 5.5 μm.

Attenuated Total Reflectance–Fourier Transform Infrared (ATR-FTIR) Spectroscopy Combined With Deep Learning for Classification of Idiopathic Recurrent Spontaneous Miscarriage (IRSM)

Idiopathic recurrent spontaneous miscarriage (IRSM) is characterized by the repeated losses of two or more clinically detected pregnancies before 24 week of gestation with the cause remaining unknown. We aim to ascertain whether attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy with deep learning (DL) can accurately distinguish IRSM from controls. Endometrial tissue (internal lining of the uterine cavity) was collected from 20 women with IRSM and 20 controls during window of implantation. ATR-FTIR spectroscopy was used to acquire spectra (400–4000 cm−1) from three random locations across each specimen and averaged. Multivariate analysis was used to assess group differentiation. Furthermore, DL classifiers were implemented to predict IRSM. Hierarchical cluster analysis (HCA) demonstrated distinct clustering of the two groups. The principal component analysis (PCA) loading plot indicated contributions from amide I, II and III bands, symmetric methyl (CH3) bending of proteins, lipids, nucleic acids, asymmetric stretching of CH2 due to lipids, collagen, and glucose in discriminating between IRSM and controls. Supervised orthogonal projections to latent structures discriminant analysis (OPLS-DA) exhibited optimized discrimination between the groups. Convolutional neural network (CNN) and variational autoencoder-artificial neural network (VAE-ANN) classifiers exhibited good performance and showed classification accuracy of 94% and 94% and F1 scores (mean of recall and precision) of 95% and 93%, respectively. The optimal area under the receiver operating characteristic curve (AUC) value of both CNN and VAE-ANN was 0.94. ATR-FTIR spectroscopy combined with DL approach is promising for understanding complex disease pathophysiology and enabling early prediction.

Honey differentiation with FTIR-ATR spectroscopy – Comparison with physicochemical parameters of a Polish honey sample set

The varietal discrimination of honey is important because its bioactive properties, as well as specific characteristics, depend on the botanical origin. The present study aimed to verify the discriminatory power of Fourier-transform infrared spectroscopy (FT-IR) for differentiating Polish honeys and compare the results with the discrimination power of a model built on the basis of selected physicochemical parameters. For this purpose, buckwheat, rape, acacia, heather, goldenrod, and coniferous honeydew honeys were collected from trustworthy apiaries in different regions of Poland. The samples were further authenticated using pollen analysis and tested by means of FT-IR and the attenuated total reflection (ATR) technique. Basic psychochemical parameters were also assessed. The obtained data were analyzed by means of principal component analysis (PCA) and linear discriminant analysis (LDA). The obtained models were validated with a leave-one-out cross-validation (LOOCV) procedure. PCA analysis confirmed the usefulness of the ATR FT-IR method as a honey differentiation tool. The LDA for the FT-IR model allowed to correctly classify 26 out of 32 samples (81.3% accuracy), which was only slightly lower than for data the model based on the physiochemical characteristics (27 out of 32 samples and 84.4% accuracy), revealing a certain potential of FT-IR as fast evaluation method.

Synthesis, structural characterization, computational studies, and antifungal activity of isoniazid derivative

In this work, the isoniazid derivative N',N'''-((1E,1′E)-1,4-phenylenebis(methaneylylidene))di(isonicotinohydrazide) (BISHDZHI) was synthesized and characterized by Nuclear Magnetic Resonance (NMR), Attenuated Total Reflectance Fourier Transform Infrared spectroscopy (ATR-FTIR), Fourier Transform Raman (FT-Raman), and Ultraviolet-Visible (UV–Vis) spectroscopy, and its potential against fungal strains of Candida ssp. was evaluated by in vitro assays. The NMR spectrum confirmed the molecular structure of BISHDZHI. Quantum chemistry computational calculations allowed to obtain the potential energy surface, optimized molecular structure, and to identify all the bands of the Raman, infrared and UV spectra. The data calculated for isoniazid derivative BISHDZHI using the Functional Density Theory (DFT) are in accordance with the experimental values. Our in vitro studies showed that the BISHDZHI compound in association with Fluconazole possesses antifungal action against Candida tropicalis strain, with a reduction of the IC50 24 times to the host. In silico study of ADMET suggested that BISHDZHI has excellent oral bioavailability and metabolic stability, which allows therapeutic action without severe risk to the host. In addition, the molecular docking showed a high interaction potential between the Candida Albicans target. While the molecular dynamics simulations suggested that the BISHDZHI ligand occasioned a minor change in the structure target, indicating more excellent stability than the drug fluconazole.

BSA nanoclusters-based sensor for detection of dopamine in schizophrenia from biofluids

Objective To develop nontoxic and stable fluorescent emission B-Cu nanoclusters (NCs) for the specific detection of dopamine at low concentrations in cerebrospinal fluid (CSF). Significance Fluorescent gold and copper NCs conjugated with proteins, such as bovine serum albumin (BSA), offer photostability and healthcare potential. This study focused on fabricating B-Cu NCs that exhibited superior characteristics for sensitive dopamine detection. Methods The study employed various instrumental techniques including attenuated total reflectance Fourier-transform infrared spectroscopy (ATR-FTIR), scanning electron microscopy (SEM), spectrofluorometry, and transmission electron microscopy (TEM) to characterize the formulated B-Cu NCs. The NCs were synthesized, resulting in particle size ∼300 nm. The highest observed fluorescence was recorded at 24542.81 relative fluorescence units (RFU). Results The introduction of dopamine at concentrations of 0.1, 0.2, 0.3, and 0.4 ng/mL led to decreased fluorescence in both B-Au and B-Cu NCs due to an electron transport system. This reduction in fluorescence allowed dopamine concentration analysis in phosphate buffer and biological fluids such as blood plasma and CSF. B-Cu NCs showed potential as a biosensing system for point-of-care (POC) applications, specifically for diagnosing schizophrenia. Conclusion The study successfully synthesized stable and nontoxic B-Cu NCs with enhanced fluorescent emission properties. These NCs exhibited the capacity to detect dopamine at low concentrations in CSF. The study’s findings hold promise for future applications, particularly in the development of a B-Cu NCs-based biosensing system for convenient POC detection of schizophrenia by both patients and clinicians. The potential impact of this technology on healthcare and biomedical fields is substantial.

Application of modified porcine xenograft by collagen coating in the veterinary field: pre-clinical and clinical evaluations.

This study aimed to identify a collagen-coating method that does not affect the physicochemical properties of bone graft material. Based on this, we developed a collagen-coated porcine xenograft and applied it to dogs to validate its effectiveness. Xenografts and collagen were derived from porcine, and the collagen coating was performed through N-ethyl-N'-(3- (dimethylamino)propyl) carbodiimide/N-hydroxysuccinimide (EDC/NHS) activation. The physicochemical characteristics of the developed bone graft material were verified through field emission scanning electron microscope (FE-SEM), brunauer emmett teller (BET), attenuated total reflectance-fourier transform infrared (ATR-FTIR), and water absorption test. Subsequently, the biocompatibility and bone healing effects were assessed using a rat calvarial defect model. The physicochemical test results confirmed that collagen coating increased bone graft materials' surface roughness and fluid absorption but did not affect their porous structure. In vivo evaluations revealed that collagen coating had no adverse impact on the bone healing effect of bone graft materials. After confirming the biocompatibility and effectiveness, we applied the bone graft materials in two orthopedic cases and one dental case. Notably, successful fracture healing was observed in both orthopedic cases. In the dental case, successful bone regeneration was achieved without any loss of alveolar bone. This study demonstrated that porcine bone graft material promotes bone healing in dogs with its hemostatic and cohesive effects resulting from the collagen coating. Bone graft materials with enhanced biocompatibility through collagen coating are expected to be widely used in veterinary clinical practice.

Synthesis and Characterisation of 4D-Printed NVCL-co-DEGDA Resin Using Stereolithography 3D Printing

The design and manufacturing of objects in various industries have been fundamentally altered by the introduction of D-dimensional (3D) and four-dimensional (4D) printing technologies. Four-dimensional printing, a relatively new technique, has emerged as a result of the ongoing development and advancements in 3D printing. In this study, a stimulus-responsive material, N-Vinylcaprolactam-co-DEGDA (NVCL-co-DEGDA) resin, was synthesised by Stereolithography (SLA) 3D printing technique. The N-Vinylcaprolactam-co-DEGDA resins were initiated by the Diphenyl (2,4,6-trimethylbenzoyl) phosphine oxide (TPO) photoinitiator. A range of Di(ethylene glycol) diacrylate (DEGDA) concentrations in the NVCL-co-DEGDA resin was explored, ranging from 5 wt% to 40 wt%. The structural properties of the 3D printed objects were investigated by conducting Attenuated Total Reflectance–Fourier Transform Infrared Spectroscopy (ATR-FTIR). Additionally, the 3D printed samples underwent further characterisation through differential scanning calorimetry (DSC) and swelling analysis. The results revealed an inverse relationship between DEGDA concentration and Tg values, indicating that higher concentrations of DEGDA resulted in lower Tg values. Additionally, the pulsatile swelling studies demonstrated that increasing DEGDA concentration prolonged the time required to reach the maximum swelling ratio. These findings highlight the influence of DEGDA concentration on both the thermal properties and swelling behaviour of 3D printed samples.

On the way to increase osseointegration potential: Sequential SI-ATRP as promising tool for PEEK-based implant nano-engineering

In the search of the ideal bone implant material, surface initiated atom transfer radical polymerization (SI-ATRP) techniques were successfully employed to modify the polyetheretherketone (PEEK) surface with complex architecture nanolayers featuring hydrophilic poly(2-(dimethylamino)ethyl methacrylate) (PDMAEMA) or poly(2-hydroxyethyl methacrylate) (PHEMA) branches. As a result, polymer layers with height up to over 300 nm were synthesized to decrease the water contact angle from 92.8° to 23.0°. In-depth analysis of layer topography, structure and elemental composition realized with atomic force microscopy (AFM), attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR), time-of-flight secondary ions mass spectroscopy (TOF-SIMS) and X-ray photon spectroscopy (XPS) confirmed successful surface modification. Additionally, to demonstrate the applicability of proposed PEEK functionalization, the biomineralization assay in simulated body fluid (SBF) solution was conducted. The high density of hydroxyl and amine groups in branched polymer brushes structure enhanced the rate of hydroxyapatites (HAp) formation substantially. Compared to untreated PEEK, modification with polymer brushes resulted in the creation of cauliflower-like structures with high specific surface area and Ca/P ratio equal to 1.83–1.87 for PEEK grafted with brushes composed of PHEMA backbone segment and PDMAEMA or PHEMA as block polymer branches (PEEK-g-PHEMA-g-PDMAEMA or PEEK-g-PHEMA-g-PHEMA) after 2 weeks. Finally, the process of the hydroxyapatite formation and increase of the layer thickness in a range of 14 days to 6 weeks of immersion in SBF was thoroughly visualized by scanning electron microscopy (SEM).