Fourier Transform Infrared (FTIR) Spectroscopy to Analyse Human Blood over the Last 20 Years: A Review towards Lab-on-a-Chip Devices

Synthesis and characterization of X (X = Ni or Fe) modified BaTiO3 for effective degradation of Reactive Red 120 dye under UV-A light and its biological activity

For the sustainable advancement of industrial expansion that is environmentally conscious, harmful dyes must be removed from wastewater. Untreated effluents containing colors have the potential to harm the ecosystem and pose major health risks to people, animals, and aquatic life. Here, we have fabricated Ni or Fe modified with BaTiO3 materials and effectively utilized them for Reactive Red 120 (RR 120) dye degradation under UV-A light. The synthesized materials were characterized, and their structural, and photo-physical properties were reported. Phase segregation was not present in the XRD pattern, as evidenced by the absence of secondary phase peaks linked to iron, nickel, or oxides. Low metal ion concentrations may be the cause of this, and the presence of those elements was confirmed by XPS measurements. The Raman spectra of the BaTiO3/Ni and BaTiO3/Fe samples show a widened peak at 500 cm-1, which suggests that Ni or Fe are efficiently loaded onto the BaTiO3. RR 120 dye photodegradation under UV light conditions was effectively catalyzed by BaTiO3/Fe, as evidenced by its superior performance in the UV irradiation technique over both BaTiO3 and BaTiO3/Ni. Compared to bare BaTiO3, both metal-modified materials efficiently degraded the RR 120 dye. Acidic pH facilitated the degradation process, which makes sense given that the heterogeneous photo-Fenton reaction was the mechanism of degradation along with BaTiO3 sensitization. High-acidity sewage can be dangerous and carcinogenic, and conventional biological treatment methods are not appropriate for managing it. In the current investigation, it may be used to treat color effluents with extremely low pH levels. Additionally, the ability of the produced nanocomposites to inhibit the growth of twenty pathogens was examined, along with two fungi, fifteen Gram-negative Bacilli (GNB), one Gram-positive Bacilli (GPB), and two Gram-positive Cocci (GBC).

Assessing the Compatibility of Menatetrenone with Excipients: A Spectroscopic Approach and Implication in Drug Formulation Development

An experiment was conducted to evaluate the compatibility of menatetrenone with selected pharmaceutical excipients. Fourier Transform Infrared Spectroscopy (FTIR) was used to assess drug-excipient compatibility. The present research systematically investigates the FTIR spectrum of each chemical compound separately and their physical blends, analyzing for possible shifts, alterations or novel peak that may indicate chemical interactions. This study aims to utilize spectral data interpretation to detect potential compatibility problems that may occur while design and production of menatetrenone containing dosage forms ensuring their increased stability and effectiveness. The FTIR results demonstrated that all the pharmaceutical excipients were compatible with menatetrenone. In conclusion, the compatibility of pharmaceutical excipients with menatetrenone was successfully assessed using FTIR that will aid in future design of formulations containing menatetrenone as therapeutic moiety.

Analysis of the immune response using FTIR spectroscopy in mothers and their newborns with different vaccination schemes for COVID-19

The SARS-CoV-2 outbreak has provoked more than 6 million deaths worldwide. The scarcity of effective treatments and its virulence converted the vaccines into an essential tool to face it. The most used vaccines were the mRNA, adenovirus vector, and inactivated whole-virus. However, nowadays, infants aged < 6 months are not eligible for any vaccines against COVID-19, and their immunization relies on passive immunity. In this research, we investigated the humoral and cellular immune response generated on newborns of SARS-CoV-2 vaccinated mothers with mRNA or viral vector (VV) vaccine employing Fourier transformed infrared (FTIR) spectroscopy in saliva samples. For this purpose, saliva samples of newborns and their mothers were collected; the population was divided into two groups, VV and mRNA, which were subdivided into three subgroups: before pregnancy (BP), at the first (FTP) and second (STP) trimesters of pregnancy. The samples were analyzed using FTIR spectroscopy, and the bands associated with the humoral and cellular immune responses, such as IgG, IgA, and IFN-γ were analyzed. The integrated areas were calculated and compared to elucidate the quantity of those immunoglobins and the cytokine. Likewise, the correlation of the humoral and cellular immune response between the newborns and their mothers and the correlation between cellular and humoral immune response was also evaluated. The VV vaccine produced a significant humoral and cellular immune response in newborns and their mothers when they received it at the STP compared with the mRNA vaccine, evidencing statistical significance. However, no correlation was observed between newborns and their mothers when the vaccine was applied in this trimester of pregnancy. When administered BP, the mRNA vaccine generated more humoral immunity in newborns and their mothers. Nevertheless, compared with the VV vaccine, it only showed statistical significance in the mothers, highlighting that IgG showed a moderate positive correlation between the newborns and their mothers.

Production, characterization, and potential applications of lipopeptides in food systems: A comprehensive review

Lipopeptides are a class of lipid-peptide-conjugated compounds with differing structural features. This structural diversity is responsible for their diverse range of biological properties, including antimicrobial, antioxidant, and anti-inflammatory activities. Lipopeptides have been attracting the attention of food scientists due to their potential as food additives and preservatives. This review provides a comprehensive overview of lipopeptides, their production, structural characteristics, and functional properties. First, the classes, chemical features, structure-activity relationships, and sources of lipopeptides are summarized. Then, the gene expression and biosynthesis of lipopeptides in microbial cell factories and strategies to optimize lipopeptide production are discussed. In addition, the main methods of purification and characterization of lipopeptides have been described. Finally, some biological activities of the lipopeptides, especially those relevant to food systems along with their mechanism of action, are critically examined.

Green Synthesis of Silver Nanoparticles with Extracts from Kalanchoe fedtschenkoi: Characterization and Bioactivities

In this work, the hexane, chloroform, and methanol extracts from Kalanchoe fedtschenkoi were utilized to green-synthesize silver nanoparticles (Kf1-, Kf2-, and Kf3-AgNPs). The Kf1-, Kf2-, and Kf3-AgNPs were characterized by spectroscopy and microscopy techniques. The antibacterial activity of AgNPs was studied against bacteria strains, utilizing the microdilution assay. The DPPH and H2O2 assays were considered to assess the antioxidant activity of AgNPs. The results revealed that Kf1-, Kf2-, and Kf3-AgNPs exhibit an average diameter of 39.9, 111, and 42 nm, respectively. The calculated ζ-potential of Kf1-, Kf2-, and Kf3-AgNPs were -20.5, -10.6, and -7.9 mV, respectively. The UV-vis analysis of the three samples demonstrated characteristic absorption bands within the range of 350-450 nm, which confirmed the formation of AgNPs. The FTIR analysis of AgNPs exhibited a series of bands from 3500 to 750 cm-1, related to the presence of extracts on their surfaces. SEM observations unveiled that Kf1- and Kf2-AgNPs adopted structural arrangements related to nano-popcorns and nanoflowers, whereas Kf3-AgNPs were spherical in shape. It was determined that treatment with Kf1-, Kf2-, and Kf3-AgNPs was demonstrated to inhibit the growth of E. coli, S. aureus, and P. aeruginosa in a dose-dependent manner (50-300 μg/mL). Within the same range, treatment with Kf1-, Kf2-, and Kf3-AgNPs decreased the generation of DPPH (IC50 57.02-2.09 μg/mL) and H2O2 (IC50 3.15-3.45 μg/mL) radicals. This study highlights the importance of using inorganic nanomaterials to improve the biological performance of plant extracts as an efficient nanotechnological approach.

Green synthesis and characterization of AgNPs, liposomal loaded AgNPs and ZnPcS4 photosensitizer for enhanced photodynamic therapy effects in MCF-7 breast cancer cells

Breast cancer remains a formidable challenge in oncology despite significant advancements in treatment modalities. Conventional therapies such as surgery, chemotherapy, radiation therapy, and hormonal therapy have been the mainstay in managing breast cancer for decades. However, a subset of patient's experiences treatment failure, leading to disease recurrence and progression. Therefore, this study investigates the therapeutic potential of green-synthesized silver nanoparticles (AgNPs) using an African medicinal plant (Dicoma anomala methanol root extract) as a reducing agent for combating breast cancer. AgNPs were synthesized using the bottom-up approach and later modified with liposomes (Lip) loaded with photosensitizer (PS) zinc phthalocyanine tetrasulfonate (Lip@ZnPcS4) using thin film hydration method. The successful formation and Lip modification of AgNPs, alongside ZnPcS4, were confirmed through various analytical techniques including UV-Vis spectroscopy, Fourier-transform infrared spectroscopy (FT-IR), high-resolution transmission electron microscopy (HR-TEM), scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDS). Following a 24 h treatment period, MCF-7 cells were assessed for viability using 3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide (MTT viability assay), cell death analysis using mitochondrial membrane potential (MMP) (ΔΨm), Annexin V-fluorescein isothiocyanate (FITC)-propidium iodide (PI) kit, and caspase- 3, 8 and 9 activities. The experiments were repeated four times (n = 4), and the results were analyzed using SPSS statistical software version 27, with a confidence interval set at 0.95. The synthesized nanoparticles and nanocomplex, including AgNPs, AgNPs-Lip, Lip@ZnPcS4, and AgNPs-Lip@ZnPcS4, exhibited notable cytotoxicity and therapeutic efficacy against MCF-7 breast cancer cells. Notably, the induction of apoptosis, governed by the upregulation of apoptotic proteins i.e., caspase 8 and 9 activities. In addition, caspase 3 was not expressed by MCF-7 cells in both control and experimental groups. Given the challenging prognosis associated with breast cancer, the findings underscore the promise of liposomal nanoformulations in cancer photodynamic therapy (PDT), thus warranting further exploration in clinical settings.

Cell-based vs enzyme-linked immunosorbent assay for detection of anti-Tribbles homolog 2 autoantibodies in Chinese patients with narcolepsy

STUDY OBJECTIVES

Narcolepsy type 1 is attributed to a deficiency in cerebrospinal fluid orexin and is considered linked to autoimmunity. The levels of anti-Tribbles homolog 2 (TRIB2) autoantibodies are elevated in the sera of some patients with narcolepsy with cataplexy. Additionally, injecting mice with serum immunoglobulin from patients with narcolepsy with positive anti-TRIB2 antibodies can induce hypothalamic neuron loss and alterations in sleep patterns. Consequently, we hypothesized the existence of a potential association between anti-TRIB2 antibodies and narcolepsy. To test this possibility, we used cell-based assays (CBAs) and enzyme-linked immunosorbent assays (ELISAs) to detect the presence of anti-TRIB2 antibodies in Chinese patients with narcolepsy.

METHODS

We included 68 patients with narcolepsy type 1, 39 patients with other central disorders of hypersomnolence, and 43 healthy controls. A CBA and a conventional ELISA were used to detect anti-TRIB2 antibody levels in patients' sera.

RESULTS

CBA was used to detect serum anti-TRIB2 antibodies in Chinese patients with narcolepsy, and the results were negative. However, when the ELISA was used, only 2 patients with narcolepsy type 1 had TRIB2 antibody titers higher than the mean titer plus 2 standard deviations of the healthy controls.

CONCLUSIONS

In our study, ELISA identified TRIB2 autoantibodies in sera of patients with narcolepsy where CBA failed to demonstrate them. Contrary to our hypothesis, this intriguing finding deserves further research to elucidate the potential association between TRIB2 and narcolepsy type 1. Exploring the implications of TRIB2 autoantibodies in narcolepsy and disparate outcomes between ELISA and CBA could provide crucial insights.

CITATION

Zhong X, Yuan Y, Zhan Q, et al. Cell-based vs enzyme-linked immunosorbent assay for detection of anti-Tribbles homolog 2 autoantibodies in Chinese patients with narcolepsy. J Clin Sleep Med. 2024;20(6):941-946.

The effect of the anti-coagulant EDTA on the deposition and adhesion of whole blood deposits on non-porous substrates

An investigation into whether the addition of a commonly used anti-coagulant agent like ethylenediaminetetraacetic acid (EDTA) has an impact on the adhesion potential of blood to non-porous substrates was conducted. Two non-porous substrates (aluminum and polypropylene) exhibiting six different surface roughness categories (R1-R6) were used as test substrates upon which either whole blood or blood treated with EDTA was deposited. Samples were exposed to different drying periods (24 hours, 48 hours, and 1 week) before undergoing a tapping agitation experiment in order to evaluate the adhesion to the surface. Clear differences in adhesion potential were observed between whole blood and blood treated with EDTA. Blood treated with EDTA displayed a stronger adhesion strength to aluminum after a drying time of 24 h pre-agitation, while whole blood presented with a stronger adhesion strength at the drying time of 48 h and 1 week. Both EDTA-treated and EDTA-untreated blood was shown to dislodge less easily on polypropylene with the only difference observed on smooth surfaces (0.51-1.50 μm surface roughness). Thus, when conducting transfer studies using smooth hydrophobic substrates like polypropylene or considering the likelihood of transfer given specific case scenarios, differences in adhesion strength of blood due to hydrophobic substrate characteristics and a decreased surface area need to be considered. Overall, whole blood displayed a better adhesion strength to aluminum, emphasizing that indirect transfer probability experiments using EDTA blood on substrates like aluminum should take an increased dislodgment tendency into account in their transfer estimations.

Perspectives of FTIR as Promising Tool for Pathogen Diagnosis, Sanitary and Welfare Monitoring in Animal Experimentation Models: A Review Based on Pertinent Literature

Currently, there is a wide application in the literature of the use of the Fourier Transform Infrared Spectroscopy (FTIR) technique. This basic tool has also proven to be efficient for detecting molecules associated with hosts and pathogens in infections, as well as other molecules present in humans and animals' biological samples. However, there is a crisis in science data reproducibility. This crisis can also be observed in data from experimental animal models (EAMs). When it comes to rodents, a major challenge is to carry out sanitary monitoring, which is currently expensive and requires a large volume of biological samples, generating ethical, legal, and psychological conflicts for professionals and researchers. We carried out a survey of data from the relevant literature on the use of this technique in different diagnostic protocols and combined the data with the aim of presenting the technique as a promising tool for use in EAM. Since FTIR can detect molecules associated with different diseases and has advantages such as the low volume of samples required, low cost, sustainability, and provides diagnostic tests with high specificity and sensitivity, we believe that the technique is highly promising for the sanitary and stress and the detection of molecules of interest of infectious or non-infectious origin.

Isolation, characterization, identification, genomics and analyses of bioaccumulation and biosorption potential of two arsenic-resistant bacteria obtained from natural environments

Arsenic (As) is a significant contaminant whose unrestrained entrance into different ecosystems has created global concern. At the cellular level, As forms unsteady intermediates with genetic materials and perturbs different metabolic processes and proper folding of proteins. This study was the first in this region to explore, isolate, screen systematically, and intensively characterize potent As-tolerant bacterial strains from natural environments near Raiganj town of Uttar Dinajpur, West Bengal. In this study, two potent Gram-negative bacterial strains with high tolerance to the poisonous form of As, i.e., As(III) and As(V), were obtained. Both the isolates were identified using biochemical tests and 16S rRNA gene sequencing. These bacteria oxidized toxic As(III) into less poisonous As(V) and depicted tolerance towards other heavy metals. Comparative metabolic profiling of the isolates in control and As-exposed conditions through Fourier-transform infrared spectroscopy showed metabolic adjustments to cope with As toxicity. The metal removal efficiency of the isolates at different pH showed that one of the isolates, KG1D, could remove As efficiently irrespective of changes in the media pH. In contrast, the efficiency of metal removal by PF14 was largely pH-dependent. The cell mass of both the isolates was also found to favourably adsorb As(III). Whole genome sequence analysis of the isolates depicted the presence of the arsRBC genes of the arsenic operon conferring resistance to As. Owing to their As(III) oxidizing potential, high As bioaccumulation, and tolerance to other heavy metals, these bacteria could be used to bioremediate and reclaim As-contaminated sites.

On-Chip Photonic Detection Techniques for Non-Invasive In Situ Characterizations at the Microfluidic Scale

Microfluidics has emerged as a robust technology for diverse applications, ranging from bio-medical diagnostics to chemical analysis. Among the different characterization techniques that can be used to analyze samples at the microfluidic scale, the coupling of photonic detection techniques and on-chip configurations is particularly advantageous due to its non-invasive nature, which permits sensitive, real-time, high throughput, and rapid analyses, taking advantage of the microfluidic special environments and reduced sample volumes. Putting a special emphasis on integrated detection schemes, this review article explores the most relevant advances in the on-chip implementation of UV-vis, near-infrared, terahertz, and X-ray-based techniques for different characterizations, ranging from punctual spectroscopic or scattering-based measurements to different types of mapping/imaging. The principles of the techniques and their interest are discussed through their application to different systems.

Characterizing amyloid protein conformation with a multi-resonant metasurface based biosensor in the infrared window

Misfolding of amyloid protein will cause neurodegeneration and trigger conformational disease. The lack of an effective detection approach is a brake on unveiling the mechanism of protein misfolding. We theoretically proposed a novel metasurface-based biosensor for characterizing the protein's conformation. The coupling complementary split ring resonator (cSRR) was engineered to manipulate incident waves in the near-infrared (NIR) and mid-infrared (MIR) windows at the same sensing surface. The cSRRs had the advantages of intensifying the electric field and sharpening the resonance profile, resulting in a highly qualified biosensing performance. In the NIR window, the biolayer's refractive index and thickness change were detected by the dual-wavelength, which resolved into an optogeometrical parameter of the amyloid biolayer. In the MIR window, the resonant wave specifically triggered the rotation-vibration transition of amyloid protein molecules with different conformations, which was shown as the unique Amide I and II bands in the fingerprint spectrum. Thus, our proposed biosensor presented sensitive detection of biolayer and specific identification of constituent molecules. It is helpful to interpret the protein's misfolding behavior on the molecular level by associating the biolayer's structure and the constituent molecule's conformational change.

Silver nanoparticles improve the fungicidal properties of Rhazya stricta decne aqueous extract against plant pathogens

One of the most promising, non-toxic, and biocompatible developments for many biological activities is the green synthesis of nanoparticles from plants. In this work, we investigated the antifungal activity of silver nanoparticles (AgNPs) biosynthesized from Rhazya stricta aqueous extract against several plant pathogenic fungi. UV-visible spectroscopy, Zeta potential analysis, Fourier-transform infrared spectroscopy (FTIR), and transmitted electron microscopy (TEM) were used to analyze the biosynthesized AgNPs. Drechslera halodes, Drechslera tetramera, Macrophomina phaseolina, Alternaria alternata, and Curvularia australiensis were tested for their potential antifungal activity. Surface Plasmon Resonance (SPR) of Aq. AgNPs and Alkaline Aq. AgNPs was observed at 405 nm and 415 nm, respectively. FTIR analysis indicated hydroxyl, nitrile, amine, and ketone functional groups. Aq. AgNPs and Alka-line Aq. AgNPs had velocities of - 27.7 mV and - 37.9 mV and sizes of 21-90 nm and 7.2-25.3 nm, respectively, according to zeta potential studies and TEM. The antifungal examination revealed that all species' mycelial development was significantly inhibited, accompanied by severe ultra-structural alterations. Among all treatments, Aq. AgNPs were the most effective fungicide. M. phaseolina was statistically the most resistant, whereas A. alternata was the most vulnerable. To the best of our knowledge, this is the first report on R. stricta's antifungal activity against these species.

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.

Enhancement of Liver Targetability through Statistical Optimization and Surface Modification of Biodegradable Nanocapsules Loaded with Lamivudine

The intention of the current work was to develop and optimize the formulation of biodegradable polymeric nanocapsules for lamivudine (LMV) in order to obtain desired physical characteristics so as to have improved liver targetability. Nanocapsules were prepared in this study as aqueous-core nanocapsules (ACNs) with poly(lactide-co-glycolide) using a modified multiple emulsion technique. LMV was taken as a model drug to investigate the potential of ACNs developed in this work in achieving the liver targetability. Three formulations factors were chosen and 33 factorial design was adopted. The selected formulation factors were optimized statistically so as to have the anticipated characteristics of the ACNs viz. maximum entrapment efficiency, minimum particle size, and less drug release rate constant. The optimized LMV-ACNs were found to have 71.54 ± 1.93% of entrapment efficiency and 288.36 ± 2.53 nm of particle size with zeta potential of -24.7 ± 1.2 mV and 0.095 ± 0.006 h-1 of release rate constant. This optimized formulation was subjected to surface modification by treating with sodium lauryl sulphate (SLS), which increased the zeta potential to a maximum of -41.6 ± 1.3 mV at a 6 mM concentration of SLS. The results of in vivo pharmacokinetics from blood and liver tissues indicated that hepatic bioavailability of LMV was increased from 13.78 ± 3.48 μg/mL ∗ h for LMV solution to 32.94 ± 5.12 μg/mL ∗ h for the optimized LMV-ACNs and to 54.91 ± 6.68 μg/mL ∗ h for the surface-modified LMV-ACNs.

AFM-IR for Nanoscale Chemical Characterization in Life Sciences: Recent Developments and Future Directions

Despite the ubiquitous absorption of mid-infrared (IR) radiation by virtually all molecules that belong to the major biomolecules groups (proteins, lipids, carbohydrates, nucleic acids), the application of conventional IR microscopy to the life sciences remained somewhat limited, due to the restrictions on spatial resolution imposed by the diffraction limit (in the order of several micrometers). This issue is addressed by AFM-IR, a scanning probe-based technique that allows for chemical analysis at the nanoscale with resolutions down to 10 nm and thus has the potential to contribute to the investigation of nano and microscale biological processes. In this perspective, in addition to a concise description of the working principles and operating modes of AFM-IR, we present and evaluate the latest key applications of AFM-IR to the life sciences, summarizing what the technique has to offer to this field. Furthermore, we discuss the most relevant current limitations and point out potential future developments and areas for further application for fruitful interdisciplinary collaboration.

Exosomes derived from rapamycin-treated 4T1 breast cancer cells induced polarization of macrophages to M1 phenotype

M2 macrophages are the most prevalent type in the tumor microenvironment and their polarization to M1 type can be used as a potential cancer immunotherapy. Here, we investigated the role of tumor microenvironment and particularly purified exosomes in M2 to M1 macrophage polarization. Rapamycin treatment on triple-negative breast cancer cells (TNBC) was performed. Tumor cells-derived exosomes (called texosomes) were isolated and characterized using scanning electron microscopy, transmission electron microscopy, dynamic light scattering, high-performance liquid chromatography, Fourier transform infrared, and Western blot assays. M2 mouse peritoneal macrophages were treated with rapamycin or rapamycin-texosome. Then, M1/M2 phenotype-specific marker genes and proteins were measured to assess the degree of M2 to M1 polarization. Finally, nitric oxide (NO) production, phagocytosis, and efferocytosis assays were assessed to verify the functionality of the polarized macrophages. Purified rapamycin-texosomes significantly increased the expression of the M1 markers (Irf5, Nos2, and CD86) and decreased M2 markers (Arg, Ym1, and CD206). In addition, the levels of M1-specific cytokines tumor necrosis factor alpha and interleukin 1β (IL-1β) were increased, whereas the levels of M2 specific cytokines IL-10 and transforming growth factor beta were declined. Furthermore, texosome treatment increased NO concentration and phagocytosis and decreased efferocytosis indicating M1 polarization. These findings suggest rapamycin-texosomes can induce M2 to M1 macrophages polarization as a potential immunotherapy for TNBC.

Application of Fourier Transform InfraRed spectroscopy of machine learning with Support Vector Machine and principal components analysis to detect biochemical changes in dried serum of patients with primary myelofibrosis

Primary myelofibrosis (PM) is a myeloproliferative neoplasm characterized by stem cell-derived clonal neoplasms. Several factors are involved in diagnosing PM, including physical examination, peripheral blood findings, bone marrow morphology, cytogenetics, and molecular markers. Commonly gene mutations are used. Also, these gene mutations exist in other diseases, such as polycythemia vera and essential thrombocythemia. Hence, understanding the molecular mechanism and finding disease-related biomarker characteristics only for PM is crucial for the treatment and survival rate. For this purpose, blood samples of PM (n = 85) vs. healthy controls (n = 45) were collected for biochemical analysis, and, for the first time, Fourier Transform InfraRed (FTIR) spectroscopy measurement of dried PM and healthy patients' blood serum was analyzed. A Support Vector Machine (SVM) model with optimized hyperparameters was constructed using the grid search (GS) method. Then, the FTIR spectra of the biomolecular components of blood serum from PM patients were compared to those from healthy individuals using Principal Components Analysis (PCA). Also, an analysis of the rate of change of FTIR spectra absorption was studied. The results showed that PM patients have higher amounts of phospholipids and proteins and a lower amount of H-O=H vibrations which was visible. The PCA results indicated that it is possible to differentiate between dried blood serum samples collected from PM patients and healthy individuals. The Grid Search Support Vector Machine (GS-SVM) model showed that the prediction accuracy ranged from 0.923 to 1.00 depending on the FTIR range analyzed. Furthermore, it was shown that the ratio between α-helix and β-sheet structures in proteins is 1.5 times higher in PM than in control people. The vibrations associated with the CO bond and the amide III region of proteins showed the highest probability value, indicating that these spectral features were significantly altered in PM patients compared to healthy ones' spectra. The results indicate that the FTIR spectroscope may be used as a technique helpful in PM diagnostics. The study also presents preliminary results from the first prospective clinical validation study.

Prediction of type 1 diabetes with machine learning algorithms based on FTIR spectral data in peripheral blood mononuclear cells

The incidence of autoimmunity is increasing, to ensure timely and comprehensive treatment, there must be a diagnostic method or markers that would be available to the general public. Fourier-transform infrared spectroscopy (FTIR) is a relatively inexpensive and accurate method for determining metabolic fingerprint. The metabolism, molecular composition and function of blood cells vary according to individual physiological and pathological conditions. Thus, by obtaining autoimmune disease-specific metabolic fingerprint markers in peripheral blood mononuclear cells (PBMC) and subsequently using machine learning algorithms, it might be possible to create a tool that will allow the diagnosis of autoimmune diseases. In this preliminary study, it was found that the peak shift at 1545 cm-1 could be considered specific for autoimmune disease type 1 diabetes (T1D), while the shifts at 1070 and 1417 cm-1 could be more attributed to the autoimmune condition per se. The prediction of T1D, despite the small number of participants in the study, showed an inverse AUC = 0.33 ± 0.096, n = 15, indicating a stable trend in the prediction of T1D based on FTIR metabolic fingerprint data in the PBMC.

The Effect of Nanobubbles on Transdermal Applications

In the present work, a new method for dermal delivery using nanobubbles (NBs) is investigated. Oxygen NBs are generated in deionized water and used to produce cosmetic formulations with hyaluronic acid as an active ingredient. Nanobubbles result in the improvement of the effect and penetration of the active ingredient through Strat-M, a synthetic membrane that resembles human skin. Experiments conducted with the Franz Cell device confirm the greater penetration of the active ingredient into Strat-M due to NBs, compared to cosmetic formulations that do not contain NBs. The effect of NBs was further examined by measuring UV-Vis and FTIR spectra. A possible mechanism was outlined, too. It was also found that NBs do not change the pH or the FTIR spectrum of the cosmetic serum indicating non-toxicity.

Effects of Hydrophobic Gold Nanoparticles on Structure and Fluidity of SOPC Lipid Membranes

Gold nanoparticles (AuNPs) are promising candidates in various biomedical applications such as sensors, imaging, and cancer therapy. Understanding the influence of AuNPs on lipid membranes is important to assure their safety in the biological environment and to improve their scope in nanomedicine. In this regard, the present study aimed to analyze the effects of different concentrations (0.5, 1, and 2 wt.%) of dodecanethiol functionalized hydrophobic AuNPs on the structure and fluidity of zwitterionic 1-stearoyl-2-oleoyl-sn-glycerol-3-phosphocholine (SOPC) lipid bilayer membranes using Fourier-transform infrared (FTIR) spectroscopy and fluorescent spectroscopy. The size of AuNPs was found to be 2.2 ± 1.1 nm using transmission electron microscopy. FTIR results have shown that the AuNPs induced a slight shift in methylene stretching bands, while the band positions of carbonyl and phosphate group stretching were unaffected. Temperature-dependent fluorescent anisotropy measurements showed that the incorporation of AuNPs up to 2 wt.% did not affect the lipid order in membranes. Overall, these results indicate that the hydrophobic AuNPs in the studied concentration did not cause any significant alterations in the structure and membrane fluidity, which suggests the suitability of these particles to form liposome-AuNP hybrids for diverse biomedical applications including drug delivery and therapy.

A Review of Machine Learning Methods Recently Applied to FTIR Spectroscopy Data for the Analysis of Human Blood Cells

Machine learning (ML) is a broad term encompassing several methods that allow us to learn from data. These methods may permit large real-world databases to be more rapidly translated to applications to inform patient-provider decision-making. This paper presents a review of articles that discuss the use of Fourier transform infrared (FTIR) spectroscopy and ML for human blood analysis between the years 2019-2023. The literature review was conducted to identify published research of employed ML linked with FTIR for distinction between pathological and healthy human blood cells. The articles' search strategy was implemented and studies meeting the eligibility criteria were evaluated. Relevant data related to the study design, statistical methods, and strengths and limitations were identified. A total of 39 publications in the last 5 years (2019-2023) were identified and evaluated for this review. Diverse methods, statistical packages, and approaches were used across the identified studies. The most common methods included support vector machine (SVM) and principal component analysis (PCA) approaches. Most studies applied internal validation and employed more than one algorithm, while only four studies applied one ML algorithm to the data. A wide variety of approaches, algorithms, statistical software, and validation strategies were employed in the application of ML methods. There is a need to ensure that multiple ML approaches are used, the model selection strategy is clearly defined, and both internal and external validation are necessary to be sure that the discrimination of human blood cells is being made with the highest efficient evidence.

Biological Activities and Chemical Profiles of Kalanchoe fedtschenkoi Extracts

In this study, the leaves of Kalanchoe fedtschenkoi were consecutively macerated with hexane, chloroform, and methanol. These extracts were used to assess the bioactivities of the plant. The antimicrobial activity was tested against a panel of Gram-positive and -negative pathogenic bacterial and fungal strains using the microdilution method. The cytotoxicity of K. fedtschenkoi extracts was investigated using human-derived macrophage THP-1 cells through the MTT assay. Finally, the anti-inflammatory activity of extracts was studied using the same cell line by measuring the secretion of IL-10 and IL-6. The phytoconstituents of hexane and chloroform extracts were evaluated using gas chromatography-mass spectrometry (GC/MS). In addition, high-performance liquid chromatography (HPLC) was used to study the phytochemical content of methanol extract. The total flavonoid content (TFC) of methanol extract is also reported. The chemical composition of K. fedtschenkoi extracts was evaluated using Fourier-transform infrared spectroscopy (FTIR). Results revealed that the chloroform extract inhibited the growth of Pseudomonas aeruginosa at 150 μg/mL. At the same concentration, methanol extract inhibited the growth of methicillin-resistant Staphylococcus aureus (MRSA). Regarding their cytotoxicity, the three extracts were highly cytotoxic against the tested cell line at IC50 < 3 μg/mL. In addition, the chloroform extract significantly stimulated the secretion of IL-10 at 50 μg/mL (p < 0.01). GC/MS analyses revealed that hexane and chloroform extracts contain fatty acids, sterols, vitamin E, and triterpenes. The HPLC analysis demonstrated that methanol extract was constituted by quercetin and kaempferol derivatives. This is the first report in which the bioactivities and chemical profiles of K. fedtschenkoi are assessed for non-polar and polar extracts.

A scalable corneal xenograft platform: simultaneous opportunities for tissue engineering and circular economic sustainability by repurposing slaughterhouse waste

Introduction: Corneal disease is a leading cause of blindness globally that stems from various etiologies. High-throughput platforms that can generate substantial quantities of corneal grafts will be invaluable in addressing the existing global demand for keratoplasty. Slaughterhouses generate substantial quantities of underutilized biological waste that can be repurposed to reduce current environmentally unfriendly practices. Such efforts to support sustainability can simultaneously drive the development of bioartificial keratoprostheses. Methods: Scores of discarded eyes from the prominent Arabian sheep breeds in our surrounding region of the United Arab Emirates (UAE) were repurposed to generate native and acellular corneal keratoprostheses. Acellular corneal scaffolds were created using a whole-eye immersion/agitation-based decellularization technique with a widely available, eco-friendly, and inexpensive 4% zwitterionic biosurfactant solution (Ecover, Malle, Belgium). Conventional approaches like DNA quantification, ECM fibril organization, scaffold dimensions, ocular transparency and transmittance, surface tension measurements, and Fourier-transform infrared (FTIR) spectroscopy were used to examine corneal scaffold composition. Results: Using this high-throughput system, we effectively removed over 95% of the native DNA from native corneas while retaining the innate microarchitecture that supported substantial light transmission (over 70%) after reversing opacity, a well-established hallmark of decellularization and long-term native corneal storage, with glycerol. FTIR data revealed the absence of spectral peaks in the frequency range 2849 cm-1 to 3075 cm-1, indicating the effective removal of the residual biosurfactant post-decellularization. Surface tension studies confirmed the FTIR data by capturing the surfactant's progressive and effectual removal through tension measurements ranging from approximately 35 mN/m for the 4% decellularizing agent to 70 mN/m for elutes highlighting the effective removal of the detergent. Discussion: To our knowledge, this is the first dataset to be generated outlining a platform that can produce dozens of ovine acellular corneal scaffolds that effectively preserve ocular transparency, transmittance, and ECM components using an eco-friendly surfactant. Analogously, decellularization technologies can support corneal regeneration with attributes comparable to native xenografts. Thus, this study presents a simplified, inexpensive, and scalable high-throughput corneal xenograft platform to support tissue engineering, regenerative medicine, and circular economic sustainability.

Salivary ATR-FTIR Spectroscopy Coupled with Support Vector Machine Classification for Screening of Type 2 Diabetes Mellitus

The blood diagnosis of diabetes mellitus (DM) is highly accurate; however, it is an invasive, high-cost, and painful procedure. In this context, the combination of ATR-FTIR spectroscopy and machine learning techniques in other biological samples has been used as an alternative tool to develop a non-invasive, fast, inexpensive, and label-free diagnostic or screening platform for several diseases, including DM. In this study, we used the ATR-FTIR tool associated with linear discriminant analysis (LDA) and a support vector machine (SVM) classifier in order to identify changes in salivary components to be used as alternative biomarkers for the diagnosis of type 2 DM. The band area values of 2962 cm^-1, 1641 cm^-1, and 1073 cm^-1 were higher in type 2 diabetic patients than in non-diabetic subjects. The best classification of salivary infrared spectra was by SVM, showing a sensitivity of 93.3% (42/45), specificity of 74% (17/23), and accuracy of 87% between non-diabetic subjects and uncontrolled type 2 DM patients. The SHAP features of infrared spectra indicate the main salivary vibrational modes of lipids and proteins that are responsible for discriminating DM patients. In summary, these data highlight the potential of ATR-FTIR platforms coupled with machine learning as a reagent-free, non-invasive, and highly sensitive tool for screening and monitoring diabetic patients.

A one-dimensional convolutional neural network based deep learning for high accuracy classification of transformation stages in esophageal squamous cell carcinoma tissue using micro-FTIR

Among the most frequently diagnosed cancers in developing countries, esophageal squamous cell carcinoma (ESCC) ranks among the top six causes of death. It would be beneficial if a rapid, accurate, and automatic ESCC diagnostic method could be developed to reduce the workload of pathologists and improve the effectiveness of cancer treatments. Using micro-FTIR spectroscopy, this study classified the transformation stages of ESCC tissues. Based on 6,352 raw micro-FTIR spectra, a one-dimensional convolutional neural network (1D-CNN) model was constructed to classify-five stages. Based on the established model, more than 93% accuracy was achieved at each stage, and the accuracy of identifying proliferation, low grade neoplasia, and ESCC cancer groups was achieved 99% for the test dataset. In this proof-of-concept study, the developed method can be applied to other diseases in order to promote the use of FTIR spectroscopy in cancer pathology.

Rapid Biomarker-Based Diagnosis of Fibromyalgia Syndrome and Related Rheumatologic Disorders by Portable FT-IR Spectroscopic Techniques

Fibromyalgia syndrome (FM), one of the most common illnesses that cause chronic widespread pain, continues to present significant diagnostic challenges. The objective of this study was to develop a rapid vibrational biomarker-based method for diagnosing fibromyalgia syndrome and related rheumatologic disorders (systemic lupus erythematosus (SLE), osteoarthritis (OA) and rheumatoid arthritis (RA)) through portable FT-IR techniques. Bloodspot samples were collected from patients diagnosed with FM (n = 122) and related rheumatologic disorders (n = 70), including SLE (n = 17), RA (n = 43), and OA (n = 10), and stored in conventional protein saver bloodspot cards. The blood samples were prepared by four different methods (blood aliquots, protein-precipitated extraction, and non-washed and water-washed semi-permeable membrane filtration extractions), and spectral data were collected with a portable FT-IR spectrometer. Pattern recognition analysis, OPLS-DA, was able to identify the signature profile and classify the spectra into corresponding classes (Rcv > 0.93) with excellent sensitivity and specificity. Peptide backbones and aromatic amino acids were predominant for the differentiation and might serve as candidate biomarkers for syndromes such as FM. This research evaluated the feasibility of portable FT-IR combined with chemometrics as an accurate and high-throughput tool for distinct spectral signatures of biomarkers related to the human syndrome (FM), which could allow for real-time and in-clinic diagnostics of FM.

The Convergence of FTIR and EVs: Emergence Strategy for Non-Invasive Cancer Markers Discovery

In conjunction with imaging analysis, pathology-based assessments of biopsied tissue are the gold standard for diagnosing solid tumors. However, the disadvantages of tissue biopsies, such as being invasive, time-consuming, and labor-intensive, have urged the development of an alternate method, liquid biopsy, that involves sampling and clinical assessment of various bodily fluids for cancer diagnosis. Meanwhile, extracellular vesicles (EVs) are circulating biomarkers that carry molecular profiles of their cell or tissue origins and have emerged as one of the most promising biomarkers for cancer. Owing to the biological information that can be obtained through EVs' membrane surface markers and their cargo loaded with biomolecules such as nucleic acids, proteins, and lipids, EVs have become useful in cancer diagnosis and therapeutic applications. Fourier-transform infrared spectroscopy (FTIR) allows rapid, non-destructive, label-free molecular profiling of EVs with minimal sample preparation. Since the heterogeneity of EV subpopulations may result in complicated FTIR spectra that are highly diverse, computational-assisted FTIR spectroscopy is employed in many studies to provide fingerprint spectra of malignant and non-malignant samples, allowing classification with high accuracy, specificity, and sensitivity. In view of this, FTIR-EV approach carries a great potential in cancer detection. The progression of FTIR-based biomarker identification in EV research, the rationale of the integration of a computationally assisted approach, along with the challenges of clinical translation are the focus of this review.

Exploring the binding mechanism and adverse toxic effects of chiral phenothrin to human serum albumin: Based on multi-spectroscopy, biochemical and computational approach

To understand the binding mechanism of a mixture of chiral phenothrin with human serum albumin (HSA), we used multi-spectroscopy, including steady-state fluorescence spectroscopic titration, three-dimensional fluorescence spectroscopy, circular dichroism, and FTIR spectra to explore the precise interactions between the complex. Based on the modified Stern-Volmer equation, the binding constant (K_a) was calculated under three temperatures, which revealed that phenothrin interacts with HSA through a static quenching mechanism. The thermodynamic parameters including enthalpy change (ΔH) and entropy change (ΔS) were determined by fitting the experimental data with van't Hoff equation, which indicates that electrostatic force and hydrogen bonds dominate the interplay in the phenothrin-HSA complex. Circular dichroism and FTIR showed the addition of phenothrin changed the secondary structure of proteins, in which the α-helicity decreased from 52.37% in free HSA to 50.02%. The esterase-like activity was reduced with the increase of phenothrin concentration, which may be attributed to the perturbated senior structure of HSA. Competitive displacement experiments confirmed that phenothrin inserted into the subdomain IIA (site I) of HSA. Several computational approaches such as molecular docking, frontier molecular orbital analysis, and electrostatic potential analysis were utilized to probe into the binding mode of the phenothrin-HSA complex. The binding behaviors of the chiral phenothrin mixture differed during the complexation. In conclusion, both the experimental and theoretical investigations provide useful information for better understanding and reducing the potential deleterious effects of the chiral phenothrin mixture on human long-term physio-pathological status.

A Lower Serum Antioxidant Capacity as a Distinctive Feature for Women with HER2+ Breast Cancer: A Preliminary Study

The overexpression of HER2 in breast cancer (BC) can contribute to redox imbalance, which is related to damage and structural modification in many biomolecules. To the best of our knowledge, this is the first study that has investigated the infrared spectrum wavenumbers obtained by ATR-FTIR and their relationship with the levels of redox status markers such as reduced glutathione, superoxide dismutase (SOD), catalase, Ferric Reducing Antioxidant Power (FRAP), and protein carbonyl among women with HER2+ BC, HER2- BC, and benign breast disease (BBD). The study was conducted with 25 women, 17 of whom were diagnosed with BC (6 HER2+ and 11 HER2-) and 8 with BBD. Our results indicate HER2+ BC cases could be distinguished from HER2- BC and BBD cases by their serum's antioxidant capacity [HER2+ BC vs. HER2- BC (AUC = 0.818; specificity = 81.82%; sensitivity = 66.67%); HER2+ BC vs. BBD (AUC = 0.875; specificity = 75%; sensitivity = 83.33%)]. The changes in biochemical terms that occur in serum as a result of the scarcity of antioxidants are related to a peculiar fingerprint in the infrared spectrum obtained by ATR-FTIR. In the serum of women with BBD, the SOD enzyme level is the highest, and this characteristic allowed us to distinguish them from HER2- BC. Finally, data regarding the serological antioxidant capacity of FRAP and the infrared spectrum by ATR-FTIR will allow us to assess biochemical changes that occur before clinical signs, indicating whether changes in therapy or interventions are necessary.

Two-Channel Detecting Sensor with Signal Cross-Correlation for FTIR Instruments

This paper's purpose was to demonstrate a performance of a novel approach in a low-noise optical sensor for an FTIR spectrometer.

METHODS

Compared to the standard FTIR detection setup, our sensor ensures a higher signal-to-noise ratio (SNR) and lower signal standard deviation by reducing the uncorrelated noise components (e.g., thermal and 1/f noises of the detection module). Its construction is based on two-channel detection modules and a processing unit with implemented cross-correlation signal analyses. Each module was built of LWIR HgCdTe photodiodes and low-noise transimpedance amplifiers.

RESULTS

the experiments demonstrated a decrease in a signal standard deviation of about 1.7 times with a 10 dB-improvement in the SNR.

CONCLUSION

this result indicates our sensor's main benefit, especially in registered "weak" and noisy interferograms.

Characterization, Properties and Antimicrobial Activity of Radiation Induced Phosphorus-Containing PVA Hydrogels

Function modification of polyvinyl alcohol (PVA) having phosphorus-containing heterocyclic compounds is believed to have thermal and biological applications in the area of polymers. The synthesis of phosphorus-containing PVA (P-PVA) was performed using γ-radiation. The chemical structure of the composite polymer is confirmed by spectroscopic techniques of FT-IR, 1H, 13C, and 31P-NMR. Photosensitive properties of polymers were investigated by ultraviolet spectroscopy. Thermal studies are assigned using the Differential Scanning Calorimeter (DSC) and thermogravimetric analysis (TGA). Data display that P-PVA has more thermal stability than PVA. The surface morphology of the prepared hydrogels was performed using scanning electron microscopy (SEM). Quantitative elemental analysis of the P-PVA hydrogel was done through energy-dispersive X-ray spectroscopy (EDX). Antimicrobial activity of the prepared hydrogels using different fungi such as Aspergillus fumigatus, Geotrichum candidum, Candida albicans, and Syncephal-astrum racemosum, in addition to bacteria such as Staphylococcus aureus, Bacillis subtilis (as gram-positive bacteria), Pseudomonas aeruginosa, and Escherichia coli (as gram-negative bacteria), was studied. The phosphorus-contained PVA hydrogels were found to have antimicrobial activity against various fungi and bacteria compared to pure PVA hydrogels.