Long-range infrared absorption spectroscopy and fast mass spectrometry for rapid online measurements of volatile organic compounds from black tea fermentation

Fermentation is the key process to determine the quality of black tea. Traditional physical and chemical analyses are time consuming, it cannot meet the needs of online monitoring. The existing rapid testing techniques cannot determine the specific volatile organic compounds (VOCs) produced at different stages of fermentation, resulting in poor model transferability; therefore, the current degree of black tea fermentation mainly relies on the sensory judgment of tea makers. This study used proton transfer reaction mass spectrometry (PTR-MS) and fourier transform infrared spectroscopy (FTIR) combined with different injection methods to collect VOCs of the samples, the rule of change of specific VOCs was clarified, and the extreme learning machine (ELM) model was established after principal component analysis (PCA), the prediction accuracy reached 95% and 100%, respectively. Finally, different application scenarios of the two technologies in the actual production of black tea are discussed based on their respective advantages.

Mid-infrared spectroscopic identification of the right-baked rhubarb for ulcerative colitis therapy

Clinical and experimental evidences have confirmed the significant therapeutic effects of rhubarb on ulcerative colitis (UC), but the strong purgative function of rhubarb also aggravates UC symptoms such as bloody diarrhea. Stir-baking to scorch is a traditional Chinese medicinal processing method that can eliminate the adverse purgative function while keep or even enhance the UC therapeutic function of rhubarb. However, the under-baked rhubarb still have the undesirable purgative function, but the over-baked rhubarb may lose the required medicinal functions. Therefore, the determination of the right endpoint is the primary quality concern about the baking process of rhubarb. In this research, typical anthraquinone compounds and mid-infrared (MIR) spectra were recruited to determine the best baking degree of rhubarb for UC therapy. Raw rhubarb slices were baked at 180 °C with rotation to prepare the rhubarbs with different baking degrees. The right-baked rhubarb was defined according to the UC therapeutic responses as well as the traditional color criterion. Referring to the typical anthraquinone compounds in rhubarb slices and extracts, the baking degree of rhubarb may be assessed by the conversion ratio of anthraquinone glycosides to anthraquinone aglycones. MIR spectra showed the gradual decompositions of organic compounds including anthraquinone glycosides and tannins during the baking process. Rhubarbs with different baking degrees can be distinguished clearly by MIR-based principal component analysis. In conclusion, the ratio of anthraquinone glycosides to anthraquinone aglycones may be a reasonable chemical indicator of the right-baked rhubarb. Meanwhile, MIR spectroscopy can identify the right-baked rhubarb simply and rapidly.

Study of the molecular structure of proteins in fermented Maize-Soybean meal-based rations based on FTIR spectroscopy

This research investigates the dynamic alterations that occur in protein molecular structure during the fermentation process of feed. Fourier transform infrared spectroscopy (FTIR), coupled with deconvolution, second derivative and curve-fitting methodologies, was employed to comparatively analyse the protein molecular structures in fermented feed. At the 48-h fermentation mark, the α-helix and β-sheet contents reached their peaks, while the random coil and β-turn contents were at their lowest. Simultaneously, the β-sheet/α-helix ratio was minimized. FTIR spectroscopy emerged as a comprehensive tool, revealing the nuanced changes in molecular structure throughout the fermentation process of corn-soybean meal feed. When integrated with spectral quantitative analysis, it provides a novel perspective for evaluating the nutritional value of fermented feed.

Evaluating the Effect of pH, Temperature and Concentration on Antioxidant and Antibacterial Potential of Spectroscopically, Spectrophotometrically and Microscopically Characterized Mentha Spicata Capped Silver Nanoparticles

The use of traditional plants has been tremendously increased due to their higher biological impact, minimal side effects, and comparatively low cost. Moreover, the emergence of antibacterial resistance is also shifting the scientific community to reconsider herbal remedies which provide relatively safer, cheap and biologically tolerable solutions. The present research was designed to fabricate the Mentha spicata conjugated silver nanoparticles (Me-AgNPs). Furthermore, the assessment of the bactericidal potential of Me-AgNPs against various bacterial strains was another motive behind this study. Fabricated NPs were characterized with the help of the UV-Visible spectrophotometric analysis, Fourier transform infrared spectroscopy (FTIR) and Scanning electron microscopy (SEM). Me-AgNPs showed a significant zone of inhibition (23 ± 0.2 mm) at 8 mg/mL against Staphylococcus aureus and a 4.0 ± 0.2 mm zone of growth inhibition at 2 mg/mL against Aeromonas veronii. The stability of Me-AgNPs was assessed at various pH (4, 7 and 11) and temperatures (25 °C, 4 °C, 37 °C, 75 °C). The significant zones of inhibition (11.3 ± 0.3 mm, 8.3 ± 0.3mm, 14.3 ± 0.3 mm, and 7.6 ± 0.2 mm) were observed at pH 11 against Escherichia coli, Staphylococcus aureus, Bacillus subtilis, and Klebsiella pneumoniae, respectively. Growth inhibition zones (14.0 ± 0.5 mm and 13.0 ± 0.5 mm) were also determined against B. subtilis and S. aureus at 25 °C. DPPH bioassay was conducted to find the antioxidant properties of Me-AgNPs. The highest (38.66 ± 0.2%) free radical scavenging activity was shown by Me-AgNPs at 4 mg/mL. Present study results concluded that biogenic Me-AgNPs have bactericidal as well as anti-oxidative potential. Moreover, these green synthesized Me-AgNPs could maintain their potency and stability at a wide range of pH and temperature.

Two-dimensional correlation infrared spectroscopy elucidated the volatilization process of the microemulsion composed of peppermint essential oil and composite herbal extract

Microemulsion is usually a transparent and isotropic liquid mixture composed of oil phase, water phase, surfactant and cosurfactant. The surfactant-framed nanoscale droplets in the microemulsion can penetrate into the skin surface to reduce its barrier function. This makes microemulsion an ideal preparation for the transdermal drug delivery. The permeability of microemulsion may be further enhanced when botanical essential oils that can dissolve the stratum corneum are used as the oil phase. However, the volatility of essential oils is possible to shorten the retention time of the microemulsion on the skin surface. Therefore, analytical methods are required to understand the volatilization process of the microemulsion composed of essential oils to develop the reasonable topical drug carrier system. In this research, Fourier transform infrared (FTIR) spectroscopy with an attenuated total reflection (ATR) accessory cooperated with two-dimensional correlation spectroscopy (2DCOS) to elucidate the volatilization processes of some microemulsions composed of peppermint essential oil. Principal component analysis (PCA) and moving-window two-dimensional correlation spectroscopy (MW2DCOS) revealed the multiple stages of the volatilization processes of the microemulsions. Synchronous 2D correlation infrared spectra indicated the compositional changes during each stage. It was found that the successive volatilizations of ethanol, water and menthone were the major events during the volatilization process of the microemulsion composed of peppermint essential oil. Ethanol can accelerate the volatilization of water, while the composite herbal extract seemed to not influence the volatilization of the other ingredients. After a 20-min-long volatilization process, the remaining microemulsion still contained considerable peppermint essential oil to affect the skin. The above results showed the feasibility of developing the microemulsion composed of peppermint essential oil for the transdermal drug delivery of composite herbal extract. This research also proved that the combination of ATR-FTIR spectroscopy and 2DCOS was valuable to study the volatilization process of the microemulsion.

Quantitative detection of multicomponent SF6 decomposition products based on Fourier transform infrared spectroscopy combined with SCARS-DNN

Accurate and efficient quantitative analysis of the decomposition products of the insulating medium SF6 in gas-insulated switchgear (GIS) is important for an effective assessment of its internal insulation status. In this work, a quantitative calibration model of Fourier Transform Infrared Spectroscopy (FTIR) combined with SCARS-DNN (Stability Competitive Adaptive Reweighted Sampling-Deep Neural Network) is proposed for the rapid non-destructive detection of SF6 decomposition products. First, the interference of the background gas SF6 on the absorption spectra of the decomposition products is eliminated according to the Lambert-Beer law, while baseline correction and Savitzky-Golay (S-G) smoothing are used to remove baseline drift and noise. Subsequently, a Monte Carlo cross-validation method is used to detect and eliminate the anomalous samples. Then feature selection is performed using uninformative variable elimination (UVE) and stability competitive adaptive reweighted sampling (SCARS), and finally quantitative calibration models of FULL-DNN (full spectral band), UVE-DNN, and SCARS-DNN are developed. For the quantitative detection of SF6 decomposition products, the SCARS-DNN model had the best prediction performance with a maximum reduction of 96.18% in the root mean square error (RMSE) and 96.11% in the mean absolute percentage error (MAPE). Results reveal that the relative errors are basically kept below 1.36% when predicting the three decomposition products, even in the presence of a high level of SF6 interference. Therefore, the SCARS-DNN model is suitable for high-precision quantitative detection of SF6 decomposition gas.

On the Structural and Molecular Properties of PEO and PEO-PPG Functionalized Chitosan Nanoparticles for Drug Delivery

Chitosan nanoparticles (CS-NPs) are currently under investigation for a wide range of applications in nanomedicine. We investigated the structural, morphological, and molecular properties of CS-NPs synthesized via ionic gelation and designed specifically for drug delivery. The CS-NPs were prepared at concentrations ranging from 0.25 to 1.0% w/v. The 1.0% w/v CS-NPs were also functionalized with polyethylene oxide (PEO) alone and with a diblock copolymer of PEO and polypropylene glycol (PPG). The average nanoparticle size determined from TEM imaging is in the 11.3 to 14.8 nm range. The XRD and TEM analyses reveal a semi-crystalline structure with a degree of crystallinity dependent upon the nature of CS-NP functionalization. Functionalizing with PEO had no effect, whereas functionalizing with PEO-PPG resulted in a significant increase in the crystallinity of the 1.0% w/v CS-NPs. Additionally, the CS/TPP concentration (CS:TPP fixed at a 1:1 ratio) did not impact the degree of crystallinity of the CS-NPs. FTIR analysis confirmed the incorporation of TPP with CS and an increase in hydrogen bonding in more crystalline CS-NPs.

Color and Chemical Stability of 3D-Printed and Thermoformed Polyurethane-Based Aligners

The significant rise in the use of clear aligners for orthodontic treatment is attributed to their aesthetic appeal, enhancing patient appearance and self-confidence. The aim of this study is to evaluate the aligners' response to common staining agents (coffee, black tea, Coca-Cola, and Red Bull) in color and chemical stability. Polyurethane-based thermoformed and 3D-printed aligners from four brands were exposed to common beverages to assess color change using a VITA Easyshade compact colorimeter after 24 h, 48 h, 72 h, and 7 days, as well as chemical stability using ATR-FTIR spectroscopy. The brand, beverage, and manufacturing method significantly influence color stability. ATR-FTIR analysis revealed compositional differences, with variations in response to beverage exposure affecting the integrity of polymer bonds. Color change analysis showed coffee as the most potent staining agent, particularly affecting Tera Harz TC85 aligners, while ClearCorrect aligners exhibited the least susceptibility. 3D-printed aligners showed a greater color change compared to thermoformed ones. Aligners with a PETG outer layer are more resistant to stains and chemical alterations than those made of polyurethane. Additionally, 3D-printed polyurethane aligners stain more than thermoformed ones. Therefore, PETG-layered aligners are a more reliable choice for maintaining the aesthetic integrity of aligners.

Evaluation of Transmission Near the Christiansen Wavelength for Dynamic Sand Samples

Many optical applications, including free-space optical communications, lidar, and astronomical measurements, are impacted by the presence of light-scattering particles also known as obscurants. Scattering from particles consisting of sand, dust, dirt, and other substances can significantly degrade optical signals. For many obscurants, the index of refraction is dependent on the wavelength of light, and there exists a Christiansen wavelength (λc) at which scattering is at a minimum. At λc the index of refraction of the scattering particles (ns) matches that of the surrounding medium, in this case air (with refractive index na). This condition makes the scattering particulates almost invisible to the propagating light, minimizing scattering and increasing transmission at λc. Previously, the authors showed a technique for measuring the index of refraction n(λ) and the extinction coefficient k(λ) using spectroscopic ellipsometry for various sand samples. Spectroscopic measurements on static sand samples demonstrated good agreement with the predicted spectral properties and highlighted the presence of a Christiansen feature near 8 µm. However, in outdoor environments, the scattering particles are never stationary but in a constant state of motion. In this work, spectroscopic measurements on dynamic sand samples (sand that is falling through the optical beam path) show two Christiansen features seen previously in predicted and observed static sand measurements. Additionally, we characterize, for the first time, transmission around a Christiansen feature using a tunable laser and show results consistent with other spectroscopic measurements.

Data on the characterization of seaweed, wheat bran, and other food processing byproducts as feasible biosorbents

Traditionally, biosorbents have been used to remove contaminants from polluted water, such as wastewater, landfill leachate, rainwater or drinking water. However, two alternative uses of biosorbents have been proposed relatively recently: the removal of heavy metals from fruit juices by biosorption and the use of saturated biosorbents as animal feed. Because these biosorbents are in contact with food or are used as animal feed, the concentration of contaminants in biosorbents must be known. In addition, the characterization of biosorbents is crucial because biosorbent properties affect both adsorption efficiency and the performance of full-scale biosorbent systems. This article presents data from Fourier transform infrared spectroscopy (FTIR) analysis, and the concentration of toxic metals (determined by ICP-MS) as well as pesticide residues was determined in ten biomass samples, namely, pea skins, straw, seaweed Fucus vesiculosus, wheat bran, rye bran, raspberry seeds, peat, buckwheat husks, highbush blueberry pulp, and blackcurrant pulp. Selected biomass samples were also characterized by scanning electron microscopy (SEM), nitrogen physisorption analysis, and pyrolysis-gas chromatography-mass spectrometry (Py-GC/ MS/FID) analysis.

Expert System for Fourier Transform Infrared Spectra Recognition Based on a Convolutional Neural Network With Multiclass Classification

Fourier transform infrared spectroscopy (FT-IR) is a widely used spectroscopic method for routine analysis of substances and compounds. Spectral interpretation of spectra is a labor-intensive process that provides important information about functional groups or bonds present in compounds and complex substances. In this paper, based on deep learning methods of convolutional neural networks, models were developed to determine the presence of 17 classes of functional groups or 72 classes of coupling oscillations in the FT-IR spectra. Using web scanning, the spectra of 14 361 FT-IR spectra of organic molecules were obtained. Several different variants of model architectures with different sizes of feature maps have been tested. Based on the Shapley additive explanations (SHAP) and gradient-weighted class activation mapping (GradCAM) methods, visualization tools have been developed for visualizing and highlighting the areas of absorption bands manifestation for corresponding functional groups or bonds in the spectrum. To determine 17 and 72 classes, the F1-weighted metric, which is the harmonic mean of the class' precision and class' recall weighted by class' fraction, reached 93 and 88%, respectively, when using data on the position of absorption maxima in the spectrum as an additional source layer. The resulting model can be used to facilitate the routine analysis of spectra for all areas such as organic chemistry, materials science, and biology, as well as to facilitate the preparation of the obtained experimental data for publication.

Use of an uncrewed surface vehicle and near infrared hyperspectral imaging for sampling and analysis of aquatic microplastics

Data on MP in aquatic environments have low resolution in space and time. Scaling up sampling and increasing analysis throughput are the main bottlenecks. We combined two approaches: an uncrewed surface vehicle (USV) and near infrared hyperspectral imaging (NIR-HSI) for sampling and analysis of MP > 300 μm. We collected 35 water samples over 4 d in a coastal area. Samples were analyzed using NIR-HSI and Fourier transform infrared spectroscopy (FTIR). Spiked samples were used to determine recovery. We conclude that using a USV can mitigate issues of traditional trawls like scalability, repeatability, and contamination. NIR-HSI detects more polyethylene but less polypropylene than FTIR analysis and reduces analysis time significantly. Highly variable concentrations were found at both sampling locations, with mean MP concentration of 0.28 and 0.01 MP m-3 for location A and B respectively. USV sampling in tandem with NIR-HSI is an effective analytical pipeline for MP monitoring.

Production of biodiesel from waste fish fat through ultrasound-assisted transesterification using petro-diesel as cosolvent and optimization of process parameters using response surface methodology

Biodiesel is a highly promising and viable alternative to fossil-based diesel that also addresses the urgent need for effective waste management. It can be synthesized by the chemical modification of triglycerides sourced from vegetable origin, animal fat, or algal oil. The transesterification reaction is the preferred method of producing biodiesel. However, the non-miscibility of alcohol and oil layer causes excessive utilization of alcohol, catalyst, and a substantial reacting time and temperature. In the current investigation, transesterification of waste fish oil was performed with petro-diesel as cosolvent, under the influence of ultrasound energy. The combination of both techniques is a unique and efficient way to minimize the mass transfer limitations considerably and hence reduces the parameters of the reaction. It is also a sincere effort to comply with the principles of green chemistry. The optimum reaction conditions were obtained using response surface methodology (RSM) that were as follows: molar ratio of methanol to oil 9.09:1, catalyst concentration of 0.97 wt%, cosolvent concentration of 29.1 wt%, temperature 60.1℃, and a reacting time 30 min. Under these listed conditions, 98.1% biodiesel was achievable, which was in close agreement with the expected result. In addition, the cosolvent removal step from the crude biodiesel was also eliminated as it could be employed as a blended fuel in CI engines.

Probing Effect of 6 MeV Electron Beam Irradiation on Haemoglobin Protein Using Spectroscopic Techniques

In this work, we study the effect of 6 MeV electron beam irradiation on the physicochemical properties of lyophilized Human Haemoglobin A (HbA). Electron beams generated from Race Track Microtron accelerator with energy 6 MeV were used to irradiate HbA at fluences of 5 × 1014 e-/cm2 and 10 × 1014 e-/cm2. Pristine and electron beam irradiated HbA were characterized using UV-visible and Fourier transform infrared spectroscopy (FTIR) spectroscopy. The interfacial tension of the aqueous solutions of HbA are also analysed by pendant drop method. Absorbance intensity, % transmittance and interfacial tension decrease with fluence. The peak position of the Soret band (λsoret = 404 nm) remains unaffected by the fluences. FTIR spectroscopy confirms the changes in the secondary structure of the haemoglobin. In the amide band I, the percentage of α-helix reduced from 8% to 1%, and an increase in β-sheet (19% to 29%) and β helix (6.3% to 15%) is observed. Interfacial tension decreases from 46.0 mN/m and 44.0 mN/m with increase in irradiation dose. These finding provides realistic guideline for biological cells exposure to electron beam radiation doses.

Measurement of the Optical Constants of Sand Samples Using Ellipsometry on Sand-Adhesive Composites

In order to model the propagation of light through a sand cloud, it is critical to have accurate data for the optical constants of the sand particles that comprise it. The same holds true for modeling propagation through particles of any type suspended in a medium. Few methods exist, however, to measure these quantities with high accuracy. In this paper, a characterization method based on spectroscopic ellipsometry (SE) that can be applied to a particulate material is presented. In this method, a polished disc of an adhesive compound is prepared, and its optical constants are measured. Next, a mixture of the adhesive and a sand sample is prepared and processed into a polished disc, and SE is performed. By treating the mixture as a Bruggeman effective medium, the optical constants of the particulate material are extracted. For verification of the proposed method, it is first applied to pure silica powder, demonstrating good agreement between measured optical constants and literature values. It is then applied to Arizona road dust, a standard reference material, as well as real desert sand samples. The resulting optical constant data is input into a rigorous scattering model to predict extinction coefficients for various types of sand. Modeling results are compared to spectroscopic measurements on static sand samples, demonstrating good agreement between predicted and measured spectral properties including the presence of a Christiansen feature near a wavelength of 8 µm.

When it rains it pours: An increased prevalence of intestinal carriage of vancomycin-resistant Enterococcus faecium related to higher use of oral vancomycin in a tertiary care Hungarian clinical centre during the years of the COVID-19 pandemic

OBJECTIVES

This study aims to investigate the association between oral vancomycin consumption and intestinal vancomycin-resistant Enterococcus carriage in the pre- and COVID era in the clinical centre of the University of Szeged, Hungary.

METHODS

This retrospective microbiological examination was carried out using electronically collected data, corresponding to the period between 1 January 2018 and 31 December 2022, at the Department of Medical Microbiology. Data included isolated species and the according antimicrobial susceptibility patterns. Annual consumption data for oral vancomycin consumption were exported from the database of the central pharmacy of the clinical centre. As a strain typing procedure, Fourier transform infrared spectroscopy analysis was used.

RESULTS

There was a significant increase in the number of faecal vancomycin-resistant Enterococcus isolates throughout the study. The prevalence increased significantly during the years of the pandemic. The use of orally administered vancomycin in the clinical centre increased significantly. A strong positive correlation existed between the two phenomena. Several strains with different resistance patterns spread in the clinical centre. Two of these occurred in greater numbers, differing in their high-level aminoglycoside resistance. However, the overall resistance of these strains was stagnating. FTIR analysis revealed that 59 of the 62 strains were also divided into 2 large clusters differing partially in their high-level aminoglycoside resistance.

CONCLUSIONS

During the pandemic, intestinal VRE carriage among clinical centre patients increased significantly, linked to increased oral vancomycin use. Different strains spread, with aminoglycoside resistance being the primary distinction. This highlights the negative impact of the pandemic on VRE carriage.

Multimodal Spectroscopic Studies to Evaluate the Effect of Nod-Factor-Based Fertilizer on the Maize (Zea mays) Stem

Maize (Zea mays) is one of the most cultivated plants in the world. Due to the large area, the scale of its production, and the demand to increase the yield, there is a need for new environmentally friendly fertilizers. One group of such candidates is bacteria-produced nodulation (or nod) factors. Limited research has explored the impact of nodulation, factors on maize within field conditions, with most studies restricted to greenhouse settings and early developmental stages. Additionally, there is a scarcity of investigations that elucidate the metabolic alterations in the maize stem due to nod-factor exposure. It was therefore the aim of this study. Maize stem's metabolites and fibers were analyzed with various imaging analytical techniques: matrix assisted laser desorption ionization-mass spectrometry imaging (MALDI-MSI), Raman spectroscopy, attenuated total reflection Fourier transform infrared spectroscopy (ATR FT-IR), and diffuse reflectance infrared Fourier transform spectroscopy. Moreover, the biochemical analyses were used to evaluate the proteins and soluble carbohydrates concentration and total phenolic content. These techniques were used to evaluate the influence of nod factor-based biofertilizer on the growth of a non-symbiotic plant, maize. The biofertilizer increased the grain yield and the stem mass. Moreover, the spectroscopic and biochemical investigation proved the appreciable biochemical changes in the stems of the maize in biofertilizer-treated plants. Noticeable changes were found in the spatial distribution and the increase in the concentration of flavonoids such as maysin, quercetin, and rutin. Moreover, the concentration of cell wall components (fibers) increased. Furthermore, it was shown that the use of untargeted analyses (such as Raman and ATR FT-IR, spectroscopic imaging, and MALDI-MSI) is useful for the investigation of the biochemical changes in plants.

Microbial degradation of low-density polyethylene, polyethylene terephthalate, and polystyrene by novel isolates from plastic-polluted environment

Biodegradation is an eco-friendly measure to address plastic pollution. This study screened four bacterial isolates that were capable of degrading recalcitrant polymers, i.e., low-density polyethylene, polyethylene terephthalate, and polystyrene. The unique bacterial isolates were obtained from plastic polluted environment. Dermacoccus sp. MR5 (accession no. OP592184) and Corynebacterium sp. MR10 (accession no. OP536169) from Malaysian mangroves and Bacillus sp. BS5 (accession no. OP536168) and Priestia sp. TL1 (accession no. OP536170) from a sanitary landfill. The four isolates showed a gradual increase in the microbial count and the production of laccase and esterase enzymes after 4 weeks of incubation with the polymers (independent experiment set). Bacillus sp. BS5 produced the highest laccase 15.35 ± 0.19 U/mL and showed the highest weight loss i.e., 4.84 ± 0.6% for PS. Fourier transform infrared spectroscopy analysis confirmed the formation of carbonyl and hydroxyl groups as a result of oxidation reactions by enzymes. Liquid chromatography-mass spectrometry analysis showed the oxidation of the polymers to small molecules (alcohol, ethers, and acids) assimilated by the microbes during the degradation. Field emission scanning electron microscopy showed bacterial colonization, biofilm formation, and surface erosion on the polymer surface. The result provided significant insight into enzyme activities and the potential of isolates to target more than one type of polymer for degradation.

Study of mercury resistance and Fourier transform infrared spectroscopy-based metabolic profiling of a potent Bacillus tropicus strain from forest soil

Mercury (Hg) is a highly toxic heavy metal and Hg-resistant indigenous bacterial isolates may offer a green and cost-effective bioremediation strategy to counter Hg contamination. In this study, a potent Hg-resistant bacterium was isolated from the forest soil of a bird sanctuary. Identification using matrix-assisted laser desorption ionization-time of flight mass spectrometry depicted the isolate as a strain of Bacillus tropicus, validated by morphological, biochemical, and molecular studies. The isolate demonstrated biological Hg removal efficiency and capacity of 50.67% and 19.76 mg g-1 , respectively. The plasmid borne resistance determinant, merA, encoding mercuric reductase, was detected in the bacterium endowing it with effective Hg volatilization and resistance capability. A Fourier-transform infrared spectroscopic comparative metabolic profiling revealed the involvement of various functional groups like -COOH, -CH2 , -OH, PO4 - and so on, resulting in differential spectral patterns of the bacterium both in control and Hg-exposed situations. A temporal variance in metabolic signature was also observed during the early and mid-log phase of growth in the presence of Hg. The bacterium described in this study is the first indigenous Hg-resistant strain isolated from the Uttar Dinajpur region, which could be further explored and exploited as a potent bioresource for Hg remediation.

Rapid discrimination of Panax ginseng powder adulterated with various root plants by FT-IR spectroscopy coupled with multivariate analysis

Panax ginseng powder adulterated with other root plants (arrowroot, bellflower, and lance asiabell) was discriminated using Fourier transform infrared (FT-IR) spectroscopy, combined with multivariate analysis. Principal component analysis visually diagnosed the adulteration by showing two distinct clusters based on presence of adulteration. Wavenumber regions (1000 cm-1 and 3300 cm-1) selected from the loading plot associated with the vibration of OH and CH bond in ginsenoside and aromatic compounds. A quantitative model for the content of ginsenosides and specific aromatic compounds as indicators of pure ginseng powder, was developed based on partial least square regression analysis. The performance of the prediction model preprocessed with the Savizky-Golay 1st derivative was improved to R2 of 0.9650, 0.9635, and 0.9591 for Rb1, Rc, and β-Panasinsene, respectively. Therefore, FT-IR technology makes it possible to rapidly authenticate pure ginseng product based on the ginsenoside contents and aroma compound.

Biodegradation of polyethylene in digestive gland homogenates of marine invertebrates

Вiotic factors may be the driving force of plastic fragmentation along with abiotic factors. Since understanding the processes of biodegradation and biological depolymerization of plastic is important, a new methodological approach was proposed in this study to investigate the role of marine invertebrate digestive enzymes in plastic biodegradation. The aim of this study is to evaluate the possibility of enzymatic biodegradation of polyethylene fragments in the digestive gland homogenate of marine invertebrates differing in their feeding type (Strongylocentrotus nudus, Patiria pectinifera, Mizuhopecten yessoensis). Significant changes are found in the functional groups of the polymer after 3 days of incubation in the digestive gland homogenates of the studied marine invertebrates. A significant increase in the calculated CI (carbonyl index) and COI (сarbon-oxygen index) indices compared to the control sample was observed. The results suggest that digestive enzymes of studied organisms may play an important role in the biogeochemical cycling of plastic.

Ante- and Post-Mortem Fracture Identification Protocol Based on Low- and High-Level Fusion Using Fourier Transform Infrared Spectroscopy and Raman Spectroscopy Association

In this study, the application of low-level fusion (LLF) and high-level fusion (HLF) strategies using a combination of Fourier transform infrared spectroscopy (FT-IR) and Raman spectroscopy in the identification of antemortem and postmortem fracture at different postmortem intervals (PMIs) was investigated. On a technical level, the same hard tissue sample can be detected using a mix of FT-IR and Raman techniques. At the method level, two cutting-edge chemometrics approaches (LLF and HLF) combining FT-IR and Raman spectroscopic data are explored. The models were ranked in accordance with their parametric quality as follows: HLF and LLF + HLF models > LLF single model > Raman single model > FT-IR single model. The LLF model performed marginally better than the Raman model, however, when compared to other models, the HLF model performed considerably better. The HLF model achieved the best performance, with both cross-validation accuracy and test data set accuracy of 0.88. The importance of the feature wavelengths in the model construction process was subsequently evaluated by intersection fusion, and it was found that the absorbance bands of amide I, PO43- ν1 ν3, and CH2 in FT-IR and phenylalanine, CO32- ν1- PO43- ν3, and amide III in Raman have outstanding contributions to the construction of antemortem and postmortem fractures identification models. Overall, the combination of FT-IR and Raman with the HLF strategy is a novel and promising approach for developing antemortem and postmortem fracture identification models at different PMIs.

Rapid Classification of Serum from Patients with Paracoccidioidomycosis Using Infrared Spectroscopy, Univariate Statistics, and Linear Discriminant Analysis (LDA)

Paracoccidioidomycosis (PCM) is a systemic mycosis that is diagnosed by visualizing the fungus in clinical samples or by other methods, like serological techniques. However, all PCM diagnostic methods have limitations. The aim of this study was to develop a diagnostic tool for PCM based on Fourier transform infrared (FTIR) spectroscopy. A total of 224 serum samples were included: 132 from PCM patients and 92 constituting the control group (50 from healthy blood donors and 42 from patients with other systemic mycoses). Samples were analyzed by attenuated total reflection (ATR) and a t-test was performed to find differences in the spectra of the two groups. The wavenumbers that had p < 0.05 had their diagnostic potential evaluated using receiver operating characteristic (ROC) curves. The spectral region with the lowest p value was used for variable selection through principal component analysis (PCA). The selected variables were used in a linear discriminant analysis (LDA). In univariate analysis, the ROC curves with the best performance were obtained in the region 1551-1095 cm-1. The wavenumber that had the highest AUC value was 1264 cm-1, achieving a sensitivity of 97.73%, specificity of 76.01%, and accuracy of 94.22%. The total separation of groups was obtained in the PCA performed with a spectral range of 1551-1095 cm-1. LDA performed with the eight wavenumbers with the greatest weight from the group discrimination in the PCA obtained 100% accuracy. The methodology proposed here is simple, fast, and highly accurate, proving its potential to be applied in the diagnosis of PCM. The proposed method is more accurate than the currently known diagnostic methods, which is particularly relevant for a neglected tropical mycosis such as paracoccidioidomycosis.

Rapid diagnosis of rheumatoid arthritis and ankylosing spondylitis based on Fourier transform infrared spectroscopy and deep learning

OBJECTIVE

Rheumatoid arthritis and Ankylosing spondylitis are two common autoimmune inflammatory rheumatic diseases that negatively affect activities of daily living and can lead to structural and functional disability, reduced quality of life. Here, this study utilized Fourier transform infrared (FTIR) spectroscopy on dried serum samples and achieved early diagnosis of rheumatoid arthritis and ankylosing spondylitis based on deep learning models.

METHOD

A total of 243 dried serum samples were collected in this study, including 81 samples each from ankylosing spondylitis, rheumatoid arthritis, and healthy controls. Three multi-scale convolutional modules with different specifications were designed based on the multi-scale convolutional neural network (MSCNN) to effectively fuse the local features to enhance the generalization ability of the model. The FTIR was then combined with the MSCNN model to achieve a non-invasive, fast, and accurate diagnosis of ankylosing spondylitis, rheumatoid arthritis, and healthy controls.

RESULTS

Spectral analysis shows that the curves and waveforms of the three spectral graphs are similar. The main differences are distributed in the spectral regions of 3300-3250 cm-1, 3000-2800 cm-1, 1750-1500 cm-1, and 1500-1300 cm-1, which represent: Amides, fatty acids, cholesterol, proteins with a carboxyl group, amide II, free amino acids, and polysaccharides. Four classification models, namely artificial neural network (ANN), convolutional neural network (CNN), improved AlexNet model, and multi-scale convolutional neural network (MSCNN) were established. Through comparison, it was found that the diagnostic AUC value of the MSCNN model was 0.99, and the accuracy rate was as high as 0.93, which was much higher than the other three models.

CONCLUSION

The study demonstrated the superiority of MSCNN in distinguishing ankylosing spondylitis from rheumatoid arthritis and healthy controls. FTIR may become a rapid, sensitive, and non-invasive means of diagnosing rheumatism.

Advances in far-infrared research: therapeutic mechanisms of disease and application in cancer detection

Far infrared (FIR) irradiation is commonly used as a convenient, non-contact, non-invasive treatment for diseases such as myocardial ischemia, diabetes, and chronic kidney disease. In this review, we focus on reviewing the potential therapeutic mechanisms of FIR and its cutting-edge applications in cancer detection. Firstly, we searched the relevant literature in the last decade for systematic screening and briefly summarized the biophysical properties of FIR. We then focused on the possible mechanisms of FIR in wound healing, cardiovascular diseases, and other chronic diseases. In addition, we review recent applications of FIR in cancer detection, where Fourier transform infrared spectroscopy and infrared thermography provide additional diagnostic methods for the medical diagnosis of cancer. Finally, we conclude and look into the future development of FIR for disease treatment and cancer detection. As a high-frequency non-ionizing wave, FIR has the advantages of safety, convenience, and low cost. We hope that this review can provide biological information reference and relevant data support for those who are interested in FIR and related high-frequency non-ionizing waves, to promote the further application of FIR in the biomedical field.

Estimation of time since deposition of semen stain on different fabric types using ATR-FTIR spectroscopy and chemometrics

Various body fluids such as blood, semen, vaginal secretions, and saliva are frequently encountered at crime scene. In cases of sexual assault, semen stains are one of the most reliable evidence of biological origin. In this study, our objective was to develop a method for estimating the time since deposition of semen stains on five different fabric types using Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) Spectroscopy, with a focus on a time frame of up to 8 weeks. Semen samples from six different volunteers were dripped onto five distinct fabric materials, and ATR-FTIR measurements were obtained at 17 different time points. Principal component analysis (PCA) and partial least squares (PLS) methods were employed to differentiate semen stains on various fabric samples and estimate the age of semen stains. Models constructed using PCA and PLSR achieved high R2 values and low root-mean-square error (RMSE). While the performance varies depending on fabric types, it was observed that age estimation of semen stains can be made within following intervals: 0.39-0.76 days for 0-7 day range, 2.59-3.38 days for the 1-8 week range, and 3.98-8.1 days for the 0-56 day range. This study demonstrates the effectiveness of using ATR-FTIR spectroscopy in combination with chemometrics to estimate the age of human semen stains on various fabric types based on time-dependent spectral changes.

Insights into the LiI Redox Mediation in Aprotic Li-O2 Batteries: Solvation Effects and Singlet Oxygen Evolution

Lithium-oxygen aprotic batteries (aLOBs) are highly promising next-generation secondary batteries due to their high theoretical energy density. However, the practical implementation of these batteries is hindered by parasitic reactions that negatively impact their reversibility and cycle life. One of the challenges lies in the oxidation of Li2O2, which requires large overpotentials if not catalyzed. To address this issue, redox mediators (RMs) have been proposed to reduce the oxygen evolution reaction (OER) overpotentials. In this study, we focus on a lithium iodide RM and investigate its role on the degradation chemistry and the release of singlet oxygen in aLOBs, in different solvent environments. Specifically, we compare the impact of a polar solvent, dimethyl sulfoxide (DMSO), and a low polarity solvent, tetraglyme (G4). We demonstrate a strong interplay between solvation, degradation, and redox mediation in OER by LiI in aLOBs. The results show that LiI in DMSO-based electrolytes leads to extensive degradation and to 1O2 release, affecting the cell performance, while in G4-based electrolytes, the release of 1O2 appears to be suppressed, resulting in better cyclability.

Rapid screening for autoimmune diseases using Fourier transform infrared spectroscopy and deep learning algorithms

Introduce

Ankylosing spondylitis (AS), rheumatoid arthritis (RA), and osteoarthritis (OA) are three rheumatic immune diseases with many common characteristics. If left untreated, they can lead to joint destruction and functional limitation, and in severe cases, they can cause lifelong disability and even death. Studies have shown that early diagnosis and treatment are key to improving patient outcomes. Therefore, a rapid and accurate method for rapid diagnosis of diseases has been established, which is of great clinical significance for realizing early diagnosis of diseases and improving patient prognosis.

Methods

This study was based on Fourier transform infrared spectroscopy (FTIR) combined with a deep learning model to achieve non-invasive, rapid, and accurate differentiation of AS, RA, OA, and healthy control group. In the experiment, 320 serum samples were collected, 80 in each group. AlexNet, ResNet, MSCNN, and MSResNet diagnostic models were established by using a machine learning algorithm.

Result

The range of spectral wave number measured by four sets of Fourier transform infrared spectroscopy is 700-4000 cm-1. Serum spectral characteristic peaks were mainly at 1641 cm-1(amide I), 1542 cm-1(amide II), 3280 cm-1(amide A), 1420 cm-1(proline and tryptophan), 1245 cm-1(amide III), 1078 cm-1(carbohydrate region). And 2940 cm-1 (mainly fatty acids and cholesterol). At the same time, AlexNet, ResNet, MSCNN, and MSResNet diagnostic models are established by using machine learning algorithms. The multi-scale MSResNet classification model combined with residual blocks can use convolution modules of different scales to extract different scale features and use resblocks to solve the problem of network degradation, reduce the interference of spectral measurement noise, and enhance the generalization ability of the network model. By comparing the experimental results of the other three models AlexNet, ResNet, and MSCNN, it is found that the MSResNet model has the best diagnostic performance and the accuracy rate is 0.87.

Conclusion

The results prove the feasibility of serum Fourier transform infrared spectroscopy combined with a deep learning algorithm to distinguish AS, RA, OA, and healthy control group, which can be used as an effective auxiliary diagnostic method for these rheumatic immune diseases.

Corrigendum: Applications of Fourier Transform-Infrared spectroscopy in microbial cell biology and environmental microbiology: advances, challenges, and future perspectives

[This corrects the article DOI: 10.3389/fmicb.2023.1304081.].

Arctangent normalization and principal-component analyses merge method to classify characteristics utilizing time-dependent material data

We propose a technique for classifying paints with time-dependent properties using a new method of merging principal-component analyses (the "PCA-merge" method) that utilizes shifting of the barycenter of the PCA score plot. To understand the molecular structure, elemental concentrations, and the concentrations in the evolved gaseous component of various paints, we performed comprehensive characterizations using Fourier transform infrared spectroscopy, inductively coupled plasma mass spectrometry, and head-space-gas chromatograph/mass spectrometry while drying the paint films for 1-48 h. As various detected intensity- and time-axis variables have different dimensions that cannot be handled equally, we normalized those data as an angle parameter (θ) using arctangent to reduce the influence of high/low intensity data and the various analytical instrument. We could classify the paints into suitable categories by applying multivariate analysis to this arctangent-normalized data set. In addition, we developed a new PCA-merge method to analyze data groups that include different time components. This method merges the PCA data groups of each time-component axis into that of specific-component axes and distinguishes each sample by utilizing the shift in the barycenter of the PCA score plot. The proposed method enables the simultaneous utilization of various data groups that contain information about static and dynamic properties. This provides further insight into the characteristics of the paint materials via shifts in the barycenter of the PCA scores without requiring numerous peak identifications.

Controlled release fertilizer delivery system derived from rice straw cellulose nanofibres: a circular economy based solution for sustainable development

Recently, the development of sustainable and environmentally friendly biomaterials has gained the attention of researchers as potential alternatives to petroleum-based materials. Biomaterials are a promising candidate to mitigate sustainability issues due to their renewability, biodegradability, and cost-effectiveness. Thus, the purpose of this study is to explore a cost-effective biomaterial-based delivery system for delivering fertilizers to plants. To achieve this, rice straw (agro-waste) was selected as a raw material for the extraction of cellulose. The cellulose was extracted through alkali treatment (12% NaOH), followed by TEMPO-based oxidation. The cellulose nanofibers were characterized using Fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy, and transmission electron microscopy. In scanning electron microscopy, a loosening of the fibrillar structure in cellulose nanofibers (CNFs) was observed with a diameter of 17 ± 4 nm. The CNFs were loaded with nitrogen-based fertilizer (ammonium chloride) in 1:1, 1:2, and 2:1 (w/w) proportions. The loading was estimated through surface charge variation; in the case of the 1:1 sample, maximum reductions in surface charge were seen from -42.0 mV to -12.8 mV due to the binding of positive ammonium ions. In the release kinetics study, a controlled release pattern was observed at 1:1, which showed a 58% cumulative release of ammonium ions within 8 days. Thus, the study paves the way for value-added uses of rice straw as an alternative to the current environmentally harmful practices.

Providing potential solutions by using FT-IR spectroscopy for biofluid analysis: Clinical impact of optical screening and diagnostic tests

BACKGROUND

Currently, the potential of FT-IR spectroscopy for rapid diagnosis of many pathologies has been demonstrated by numerous research studies including those targeting COVID-19 detection. However, the number of clinicians aware of this potential and who are willing to use spectroscopy in their clinics and hospitals is still negligible. In addition, lack of awareness creates a huge gap between clinicians and researchers involved in clinical translation of current FT-IR technology hence hindering initiatives to bring basic and applied research together for the direct benefit of patients.

METHODS

Knowledge and medical training on FT-IR on the side of clinicians should be one of the first steps to be able to integrate it into the list of complementary exams which may be requested by health professionals. Countless FT-IR applications could have a life-changing impact on patients' lives, especially screening and diagnostic tests involving biofluids such as blood, saliva and urine which are routinely non-invasively or minimally-invasively.

RESULTS

Blood may be the most difficult to obtain by the invasive method of collection, but much can be evaluated in its components, and areas such as hematology, infectiology, oncology and endocrinology can be directly benefited. Urine with a relatively simple collection method can provide pertinent information from the entire urinary system, including the actual condition of the kidneys. Saliva collection can be simpler for the patient and can provide information on diseases affecting the mouth and digestive system and can be used to diagnose diseases such as oral cancer in its early-stages. An unavoidable second step is the active involvement of industries to design robust and portable instruments for specific purposes, as the medical community requires user-friendly instruments of advanced computational algorithms. A third step resides in the legal situation involving the global use of the technique as a new diagnostic modality.

CONCLUSIONS

It is important to note that decentralized funds for variety of technologies hinders the training of clinical and medical professionals for the use of newly arising technologies and affect the engagement of these professionals with technology developers. As a result of decentralized funding, research efforts are spread out over a range of technologies which take a long time to get validated and translated to the clinic. Partnership over similar groups of technologies and efforts to test the same technologies while overcoming barriers posed to technology validation in different areas around the globe may benefit the clinical/medical, research and industry community globally.

Mitochondrial Common Deletion Level in Adipose Tissue Is Not Associated with Obesity but Is Associated with a Structural Change in Triglycerides as Revealed by FTIR Spectroscopy

OBJECTIVE

Several studies have shown that mitochondrial metabolism may be disrupted if the rate of the specific 4,977 bp deletion of mitochondrial DNA (mtDNA) reaches a threshold. This study aimed to investigate the possible associations between the mtDNA4977 deletion load and obesity-related metabolic abnormalities in the adipose tissue.

METHODS

The study included thirty obese individuals, who underwent bariatric surgery, and twelve control subjects. mtDNA4977 deletion, adenine nucleotides, and lactate levels, which show the bioenergetic status were evaluated in visceral adipose tissues. Fourier transform infrared (FTIR) spectroscopy was used to investigate the structural variations and composition of adipose tissues in the context of deletion load.

RESULTS

There were no differences between the two groups in terms of mtDNA4977 deletion, adenine nucleotides, and lactate levels. The FTIR spectra indicated a few obesity-related alterations in adipose tissues that were not related to the mtDNA deletion load. Also, statistical analysis showed a correlation between the deletion load and a band shift of 1,744 cm-1, which assigns C = O stretching of the carbonyl group of the ester group in triglycerides and other esterified fatty acids, although it is not associated with obesity.

CONCLUSIONS

Our data suggest that the mtDNA4977 deletion in visceral adipose tissues of obese individuals do not have a significant impact on the bioenergetic status. However, the increased accumulation of deletion may be associated with a specific change in the ester bond, indicating structural differences in the lipids. These findings shed light on our understanding of the tissue-specific distribution of mtDNA deletions and obesity-related adipose tissue pathogeneses.

Insight into Organization of Gliadin and Glutenin Extracted from Gluten Modified by Phenolic Acids

The changes in the secondary structure of individual gluten protein fractions (gliadin and glutenin) caused by the supplementation of model dough with eight phenolic acids were analysed. Gliadins and glutenins were extracted from gluten samples obtained from overmixed dough. The changes in the gliadin secondary structure depended on the amount of phenolic acid added to the dough. Higher acid concentrations (0.1% and 0.2%) led to a significant reduction in the amount of α-helices and to the formation of aggregates, non-ordered secondary structures, and antiparallel β-sheets. After the addition of acids at a lower concentration (0.05%), the disaggregation of pseudo-β-sheet structures and the formation of β-turns, hydrogen-bonded β-turns, and antiparallel β-sheets were detected. In the case of glutenin, most of the phenolic acids induced the formation of intermolecular hydrogen bonds between the polypeptide chains, leading to glutenin aggregation. When phenolic acids were added at a concentration of 0.05%, the process of protein folding and regular secondary structure formation was also observed. In this system, antiparallel β-sheets and β-turns were created at the expense of pseudo-β-sheets.

Applications of Fourier Transform-Infrared spectroscopy in microbial cell biology and environmental microbiology: advances, challenges, and future perspectives

Microorganisms play pivotal roles in shaping ecosystems and biogeochemical cycles. Their intricate interactions involve complex biochemical processes. Fourier Transform-Infrared (FT-IR) spectroscopy is a powerful tool for monitoring these interactions, revealing microorganism composition and responses to the environment. This review explores the diversity of applications of FT-IR spectroscopy within the field of microbiology, highlighting its specific utility in microbial cell biology and environmental microbiology. It emphasizes key applications such as microbial identification, process monitoring, cell wall analysis, biofilm examination, stress response assessment, and environmental interaction investigation, showcasing the crucial role of FT-IR in advancing our understanding of microbial systems. Furthermore, we address challenges including sample complexity, data interpretation nuances, and the need for integration with complementary techniques. Future prospects for FT-IR in environmental microbiology include a wide range of transformative applications and advancements. These include the development of comprehensive and standardized FT-IR libraries for precise microbial identification, the integration of advanced analytical techniques, the adoption of high-throughput and single-cell analysis, real-time environmental monitoring using portable FT-IR systems and the incorporation of FT-IR data into ecological modeling for predictive insights into microbial responses to environmental changes. These innovative avenues promise to significantly advance our understanding of microorganisms and their complex interactions within various ecosystems.

Polymer Characterization of Submerged Plastic Litter from Lake Tahoe, United States

Monitoring plastic litter in the environment is critical to understanding the amount, sources, transport, fate, and environmental impact of this pollutant. However, few studies have monitored plastic litter on lakebeds which are potentially important environments for determining the fate and transport of plastic litter in freshwater basins. In this study, a self-contained underwater breathing apparatus was used for litter collection at the lakebed along five transects in Lake Tahoe, United States. Litter was brought to the surface and characterized by litter type. Plastic litter was subsampled, and polymer composition was determined using attenuated total reflection Fourier transform infrared spectroscopy. The average plastic litter from the lakebed for the five dive transects was 83 ± 49 items per kilometer. The top plastic litter categories were other plastic litter (plastic litter that did not fall in another category), followed by food containers, bottles <2 L, plastic bags, and toys. These results are in line with prior studies on submerged litter, and intervention approaches or ongoing education are needed. The six polymers most frequently detected in the subsamples were polyvinyl chloride, polystyrene/expanded polystyrene, polyethylene terephthalate/polyester, polyethylene, polypropylene, and polyamide. These observations reflect global plastic production and microplastic studies from lake surface water and sediments. We found that some litter subcategories were primarily comprised of a single polymer type, therefore, in studies where the polymer type cannot be measured but litter is categorized, these results could provide an estimate of the total polymer composition for select litter categories.

Physiological and transcriptome profiling of Chlorella sorokiniana: A study on azo dye wastewater decolorization

Over decades, synthetic dyes have become increasingly dominated by azo dyes posing a significant environmental risk due to their toxicity. Microalgae-based systems may offer an alternative for treatment of azo dye effluents to conventional physical-chemical methods. Here, microalgae were tested to decolorize industrial azo dye wastewater (ADW). Chlorella sorokiniana showed the highest decolorization efficiency in a preliminary screening test. Subsequently, the optimization of the experimental design resulted in 70% decolorization in a photobioreactor. Tolerance of this strain was evidenced using multiple approaches (growth and chlorophyll content assays, scanning electron microscopy (SEM), and antioxidant level measurements). Raman microspectroscopy was employed for the quantification of ADW-specific compounds accumulated by the microalgal biomass. Finally, RNA-seq revealed the transcriptome profile of C. sorokiniana exposed to ADW for 72 h. Activated DNA repair and primary metabolism provided sufficient energy for microalgal growth to overcome the adverse toxic conditions. Furthermore, several transporter genes, oxidoreductases-, and glycosyltransferases-encoding genes were upregulated to effectively sequestrate and detoxify the ADW. This work demonstrates the potential utilization of C. sorokiniana as a tolerant strain for industrial wastewater treatment, emphasizing the regulation of its molecular mechanisms to cope with unfavorable growth conditions.

Simultaneous SANS/FTIR measurement system incorporating the ATR sampling method

Small-angle neutron scattering (SANS) is widely used as a powerful technique to study the higher-order structure of soft matter. To increase the reliability of SANS profile analysis for complex multi-component systems, combining different types of structural information obtained by other methods is desirable. A simultaneous measurement system combining SANS and Fourier transform infrared (FTIR) spectroscopy meets this objective. It is beneficial for targets where matching the timing of structural changes between experiments is difficult, but the issue is that samples suitable for SANS are too thick for the typical transmission FTIR method. To overcome this problem, a new simultaneous measurement system that employs the attenuated total reflectance (ART) sampling method for FTIR spectroscopy has been developed.

Compositional and spectroscopic analysis of dissolved organic matter samples from Everglades periphyton and water

Periphyton is a ubiquitous niche in aquatic environments and can be a significant source of dissolved organic matter (DOM) production and leaching, especially in such environment as the Everglades, a slow-water flow wetland in Florida, USA. We employed an array of methods, including compositional analysis, 3-dimensional excitation emission matrix (3-D EEM) fluorescence spectroscopy, and attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy, to perform quantitative and qualitative analyses on the DOM produced by periphyton and DOM in surrounding surface water and periphyton overlying water for comparison purposes. Higher dissolved organic carbon (DOC) and total dissolved nitrogen (TDN) contents in periphyton pore water than surface water and periphyton overlying water indicated the remarkable contribution from periphyton-produced DOM. Higher total protein, carbohydrate, and thiol contents in periphyton pore water than in surface water and periphyton overlying water underscored the possibility of periphyton pore water DOM leached from periphyton. These results agreed with 3-D EEM and ATR-FTIR analyses that showed the prevalence of possible microbial source of periphyton pore water DOM as indicated by higher fluorescence index (FI) than surface water and periphyton overlying water. Similarly, the size-fractionated DOM from surface water demonstrated terrestrial sources, and periphyton pore water demonstrated microbial sources regardless of their differences in size based on their FI values. The types of periphyton affect the production and composition of DOM, as evidenced by higher total protein, carbohydrate, and chlorophyll-a (Chl-a) contents in floating mat on the water surface than in epiphyton attached to submerged phytoplankton, probably because the former is photo-synthetically more productive than the latter due to different light availability. This study provided fundamental information on periphyton DOM that is essential for further investigating its role in carbon cycle and its biogeochemistry.

Silicone oils aided fabrication of paraffin wax coated super-hydrophobic sand: A spectroscopic study

To address the global alarm of desertification and boost plant progress in arid and desert environments, super-hydrophobic sand has been suggested and fabricated in numerous researches. In the present work, sand was hydrophobized by coating with a mixture of paraffin wax and silicone oils. The contact angle (CA) of sand with 4.5 w% silicone oils increased from 143.2° to 154.2° with decreasing the chain size of silicone oil, and the further addition of 13.5 w% of paraffin wax produced a super hydrophobic sand with a CA value up to 160° comparing to 154.2° without added paraffin wax. The Fourier Transform Infrared spectra suggested the development of inter molecular forces between silicone oil and sand as well as between paraffin and silicone oil, the driving force of which was the variation in viscosity of silicone oils. The later was higher in the case of lower molecular weight silicone oil. In particular, analyzing the characteristic bands of -(CH2)n-in paraffin wax, i.e. the corresponding bands at 720, 730, 1460 and 1470 cm-1 and the two bands at 1020 and 1095 cm-1 of silicone oil revealed that two roles of paraffin were taking place. While paraffin was placed between sand and silicone oil, it coated the sand particles when lower molecular weight silicone oil was used in the first procedures, whereas it coated the higher molecular weight silicone oil in the second procedures. Molecular dynamic calculation has been performed and confirmed the previous reached conclusions and showed that paraffin molecules were encapsulated in a silicone oil shell. The average adsorption energy of paraffin and silicon oil molecules on sand particles were 29.5 and 38.9 kcal mol-1 respectively.

Application of Infrared and Near-Infrared Microspectroscopy to Microplastic Human Exposure Measurements

Microplastic pollution is a global issue for the environment and human health. The potential for human exposure to microplastic through drinking water, dust, food, and air raises concern, since experimental in vitro and in vivo toxicology studies suggest there is a level of hazard associated with high microplastic concentrations. However, to infer the likelihood of hazards manifesting in the human population, a robust understanding of exposure concentrations is needed. Infrared and near-infrared microspectroscopies have routinely been used to analyze microplastic in different exposure matrices (air, dust, food, and water), with technological advances coupling multivariate and machine learning algorithms to spectral data. This focal point article will highlight the application of infrared and Raman modes of spectroscopy to detect, characterize, and quantify microplastic particles, with a focus on human exposure to microplastic. Methodologies and state-of-the-art approaches will be reported and potential confounding variables and challenges in microplastic analysis discussed. The article provides an up-to-date review of the literature on microplastic exposure measurement using (near) infrared spectroscopies as an analytical tool, highlighting the recent advances in this rapidly advancing field.

Biomolecular alterations detected in multiple sclerosis skin fibroblasts using Fourier transform infrared spectroscopy

Multiple sclerosis (MS) is the leading cause of non-traumatic disability in young adults. New avenues are needed to help predict individuals at risk for developing MS and aid in diagnosis, prognosis, and outcome of therapeutic treatments. Previously, we showed that skin fibroblasts derived from patients with MS have altered signatures of cell stress and bioenergetics, which likely reflects changes in their protein, lipid, and biochemical profiles. Here, we used Fourier transform infrared (FTIR) spectroscopy to determine if the biochemical landscape of MS skin fibroblasts were altered when compared to age- and sex-matched controls (CTRL). More so, we sought to determine if FTIR spectroscopic signatures detected in MS skin fibroblasts are disease specific by comparing them to amyotrophic lateral sclerosis (ALS) skin fibroblasts. Spectral profiling of skin fibroblasts from MS individuals suggests significant alterations in lipid and protein organization and homeostasis, which may be affecting metabolic processes, cellular organization, and oxidation status. Sparse partial least squares-discriminant analysis of spectral profiles show that CTRL skin fibroblasts segregate well from diseased cells and that changes in MS and ALS may be unique. Differential changes in the spectral profile of CTRL, MS, and ALS cells support the development of FTIR spectroscopy to detect biomolecular modifications in patient-derived skin fibroblasts, which may eventually help establish novel peripheral biomarkers.

A Portable Infrared Attenuated Total Reflection Spectrometer for Food Analysis

The analytical performance of a compact infrared attenuated total reflection spectrometer using a pyroelectric detector array has been evaluated and compared to a conventional laboratory Fourier transform infrared system for applications in food analysis. Analytical characteristics including sensitivity, repeatability, linearity of the calibration functions, signal-to-noise ratio, and spectral resolution have been derived for both approaches. Representative analytes of relevance in food industries (i.e., organic solvents, fatty acids, and mycotoxins) have been used for the assessment of the performance of the device and to discuss the potential of this technology in food and feed analysis.

Effect of different waste plastic modifiers on conventional asphalt performance: optimal preparation parameters determination and mechanism analysis

The typical treatment of waste plastics has become a global environmental problem. In light of recent developments, waste plastics used as asphalt modifiers offer an efficient approach to solve this problem. This paper studied the effects of three kinds of waste plastic-modified asphalts (WPMA), with polypropylene (PP), polyethylene (PE) and ethylene-vinyl acetate copolymer (EVA) as their respective modifiers, on the conventional asphalt performance. Furthermore, an orthogonal experimental design (OED) was used to determine the preparation parameters of WPMA. Thereafter, thermogravimetric-differential scanning calorimetry (TG-DSC) and Fourier transform infrared spectroscopy (FTIR) were employed to expound the mechanism of WPMA. It was then subsequently ascertained that the optimum preparation parameters of PP-modified asphalt (PPMA) and PE-modified asphalt (PEMA) were 170 °C, 3000 rpm, and 30 min, while the optimum preparation parameters of EVA-modified asphalt (EVAMA) were 180 °C, 3000 rpm, and 30 min. In addition, WPMA displayed better high-temperature performance and are inherently more suitable for pavement in high-temperature regions. Ultimately, this study will effectively solve the disposal of waste plastic and promote the research and application of WPMA in the future.

Assessing the Effectiveness of Fermented Banana Peel Extracts for the Biosorption and Removal of Cadmium to Mitigate Inflammation and Oxidative Stress

This study identified 11 lactic acid bacteria (LAB) strains that exhibited tolerance to heavy metal cadmium concentrations above 50 ppm for 48 h. Among these strains, T126-1 and T40-1 displayed the highest tolerance, enduring cadmium concentrations up to 500 ppm while still inhibiting bacterial growth by 50%. Moreover, the fermentation of banana peel using LAB significantly enhanced the clearance rate of cadmium (p < 0.05) compared to nonfermented banana peel. Additionally, the LAB-fermented banana peel exhibited higher 1,1-diphenyl-2-picryl-hydrazyl (DPPH) and reduced power values. Strain T40-1 exhibited a significant improvement in its ability to chelate ferrous ions (p < 0.05). Regarding antibiotic resistance, both the T40-1 and TH3 strains demonstrated high resistance with a third-level inhibition rate against ampicillin and tetracycline. Cell viability tests revealed that incubation with the T40-1 and TH3 strains for a duration of 24 h did not result in any cellular damage. Moreover, these LAB strains effectively mitigated oxidative stress markers, such as reactive oxygen species (ROS), glutathione (GSH), and lactate dehydrogenase (LDH), caused by 2 ppm cadmium on cells. Furthermore, the LAB strains were able to reduce the inflammatory response, as evidenced by a decrease in interleukin-8 (IL-8) levels (p < 0.05). The use of Fourier transform infrared (FT-IR) spectroscopy analysis provided valuable insight into the interaction between metal ions and the organic functional groups present on the cell wall of fermented banana peel. In summary, this study highlights the potential of the LAB strains T40-1 and TH3 in terms of their tolerance to the cadmium, ability to enhance cadmium clearance rates, and their beneficial effects on oxidative stress, inflammation, and cell viability.

Physicochemical Characterization of Novel Biomaterial Consisting of Biphasic Calcium Phosphate, Chitosan, Casein and Ethanolic Leaves Extract of Ormocarpum Cochinchinense

Background

Bioceramics are widely used as a biomaterial to promote bone regeneration. Bone defect management requires the placement of bone grafts. Though there are many bone grafts available, these have certain limitations like limited supply and second surgical site morbidity. Phytochemicals in plants are known to have bone regeneration capacity and are used in traditional medicine for bone fracture healing.

Objective

The purpose of the study was to create a novel biomaterial consisting of a composite of biphasic calcium phosphate (BCP), chitosan (CH), casein (CA), and ethanolic leaves extract of Ormocarpum Cochinchinense (OC) fabricated and characterized for physicochemical properties.

Materials and Methods

BCP-CH-CA-OC material was prepared and immersed in Simulated body fluid (SBF) for 21 days. Physical properties were analysed through X-Ray diffraction (XRD), Fourier Transform Spectroscopy (FTIR), and Scanning Electron Microscopy with Energy dispersion spectroscopy (SEM/EDS). Mechanical properties were analysed by compressive strength and diametral tensile strength tests. Using BET (Brunauer-Emmett-Teller) analysis and Nano computed tomography (CT) scan, porosity measurements were made.

Results

XRD did not show any significant change after immersion in SBF, indicating that the material was not under change and is stable. FTIR showed an increase in chitosan content, due to the loss of casein. SEM analysis showed the deposition of crystals and porous structure. EDS showed the deposition of minerals. Nano CT and BET analysis showed clinically significant porosity of 30%.

Conclusion

The mechanical and physical properties of this novel biomaterial could be used in tissue engineering for the repair of bone defects in non-load-bearing areas. The physicochemical properties are at par with other materials used for the purpose of bone grafting. The novel biomaterial has the potential to be used in bone regenerative medicine in non-load-bearing applications.

Predicting adsorption capacity of pharmaceuticals and personal care products on long-term aged microplastics using machine learning

We investigated the adsorption mechanism of 66 coexisting pharmaceuticals and personal care products (PPCPs) on microplastics treated with potassium persulfate, potassium hydroxide, and Fenton reagent for 54, 110, and 500 days. The total adsorption capacity (q_e) of 66 PPCPs on 15 original microplastics was 171.8 - 1043.7 μg/g, far below that of 177 long-term aged microplastics (7114.0 - 13,114.4 μg/g). Around 69.8% of q_e was primarily influenced by the total energy, energy of the highest occupied molecular orbital, and energy gap of PPCPs, calculated using the B3LYP/6-31 G* level. Furthermore, 111 aged microplastics exhibited similar total q_e values. Additionally, we developed predictive models based on attenuated total reflectance Fourier transform infrared spectroscopy to predict the individual and total q_e on 192 microplastics. These models, including the maximal information coefficient and gradient boosting decision tree regression, exhibited high accuracy with R_training² values of 0.9772 and 0.9661, respectively, and p-values below 0.001. Spectroscopic analysis and machine learning models highlighted surface functional group alterations and the importance of the 1528-1700 cm^-1 spectral region and carbon skeleton in the adsorption process. In summary, our findings contribute to understanding the adsorption of PPCPs on microplastics, particularly in the context of long-term aging effects.

D2O assisted FTIR spectroscopic analysis of moisture in edible oil

D₂O-assisted moisture analysis of edible oils was investigated. The acetonitrile extract of the oil samples was split into two parts. The spectrum of one part was taken as is, another was recorded after addition of excess D₂O. Changes in spectral absorption of the H-O-H bending band (1600-1660 cm^-1) was used to calculate moisture in oil samples. To effectively depleting absorption of water in the acetonitrile extract, a 30-fold excess of D₂O is required. The typical OH-containing constituents in oil did not show significant interference on the H/D exchange. Validation experiments by using five oils with five levels of moisture spiked (50-1000 μg/g) suggested that the prediction tracked the spiked amounts well. The results of variance analysis indicate that there is no difference in terms of analytical methods and oil types used (p < 0.001). The D₂O method developed is generally applicable to the accurate analysis of moisture at trace levels (<100 μg/g) in edible oils.

Developing and testing a workflow to identify microplastics using near infrared hyperspectral imaging

The analysis of microplastics (MP) is time-consuming which limits our capacity to monitor and mitigate plastic pollution. Here, near infrared (1000-2500 nm) hyperspectral imaging (NIR-HSI) offers an advantage over other spectroscopic techniques because it can rapidly image large areas relative to other systems. While NIR-HSI can successfully detect MP, accuracy and limitations of the method have not been fully explored. In addition, lack of open databases and analysis pipelines increases the barrier to use. In this work, we developed a spectral database containing preproduction pellets, consumer products and marine plastic debris, imaged using a Hyspex SWIR-320me imager. A SIMCA model identified four polymer types: polypropylene, polyethylene, polyethylene terephthalate and polystyrene (PP, PE, PET, PS) to identify MP in hyperspectral images. We determined the accuracy of size estimates for PS MP > 1000 μm using fluorescence microscopy and tested the impact of photooxidation on detection of plastics by NIR-HSI (PE, PP, PS, PET) and subsequent prediction by the SIMCA model. The model performed well across all polymers as shown by high specificity, sensitivity, and accuracy for internal cross validation (>88%), and sensitivity >80% for external validation. PS MP < 500 μm Feret diameter were not consistently detected by NIR-HSI when compared with fluorescence microscopy. However, estimates for Feret diameter were consistent for PS MP > 1000 μm. Analysis by NIR-HSI showed no spectral changes and SIMCA showed no decreased precision with increased photooxidation across polymer types. Recall varied across polymer type and photooxidation stage with no clear trends. This study shows that NIR-HSI is a rapid method which can accurately identify MP of the four most relevant polymer types, precluding the need to analyze particles one at a time. NIR-HSI can be a key technology for environmental monitoring of plastic debris where rapid analysis of multiple samples is required.

Riverine Microplastic Pollution: Insights from Cagayan de Oro River, Philippines

Rivers are vital water sources for humans and homes for aquatic organisms. Conversely, they are well known as the route of plastics into the ocean. Despite being the world's number one emitter of riverine plastics into the ocean, microplastics (MPs), or plastic particles less than 5 mm, in the Philippines' rivers are relatively unexplored. Water samples were collected from six sampling stations along the river channel of the Cagayan de Oro River, one of the largest rivers in Northern Mindanao, Philippines. The extracted microplastics' abundance, distribution, and characteristics were analyzed using a stereomicroscope and Fourier transform infrared spectroscopy (FTIR). The results showed a mean concentration of 300 items/m³ of MPs dominated by blue-colored (59%), fiber (63%), 0.3-0.5 mm (44%), and polyacetylene (48%) particles. The highest concentration of microplastics was recorded near the mouth of the river, and the lowest was in the middle area. The findings indicated a significant difference in MP concentration at the sampling stations. This study is the first assessment of microplastic in a river in Mindanao. The results of this study will aid in formulating mitigation strategies for reducing riverine plastic emissions.