Coupling and regulation mechanisms of the flavin-dependent halogenase PyrH observed by infrared difference spectroscopy.

Flavin-dependent halogenases are central enzymes in the production of halogenated secondary metabolites in various organisms and they constitute highly promising biocatalysts for regioselective halogenation. The mechanism of these monooxygenases includes formation of hypohalous acid from a reaction of fully reduced flavin with oxygen and halide. The hypohalous acid then diffuses via a tunnel to the substrate-binding site for halogenation of tryptophan and other substrates. Oxidized flavin needs to be reduced for regeneration of the enzyme, which can be performed in vitro by a photoreduction with blue light. Here, we employed this photoreduction to study characteristic structural changes associated with the transition from oxidized to fully reduced flavin in PyrH from Streptomyces rugosporus as a model for tryptophan-5-halogenases. The effect of the presence of bromide and chloride or the absence of any halides on the UV-vis spectrum of the enzyme demonstrated a halide-dependent structure of the flavin-binding pocket. Light-induced FTIR difference spectroscopy was applied and the signals assigned by selective isotope labeling of the protein moiety. The identified structural changes in α-helix and ß-sheet elements were strongly dependent on the presence of bromide, chloride, the substrate tryptophan, and the product 5-chloro-tryptophan, respectively. We identified a clear allosteric coupling in solution at ambient conditions between cofactor-binding site and substrate-binding site that is active in both directions, despite their separation by a tunnel. We suggest that this coupling constitutes a fine-tuned mechanism for the promotion of the enzymatic reaction of flavin-dependent halogenases in dependence of halide and substrate availability.

Cross-α/ß polymorphism of PSMα3 fibrils.

The formation of ordered cross-ß amyloid protein aggregates is associated with a variety of human disorders. While conventional infrared methods serve as sensitive reporters of the presence of these amyloids, the recently discovered amyloid secondary structure of cross-α fibrils presents new questions and challenges. Herein, we report results using Fourier transform infrared spectroscopy and two-dimensional infrared spectroscopy to monitor the aggregation of one such cross-α-forming peptide, phenol soluble modulin alpha 3 (PSMα3). Phenol soluble modulins (PSMs) are involved in the formation and stabilization of Staphylococcus aureus biofilms, making sensitive methods of detecting and characterizing these fibrils a pressing need. Our experimental data coupled with spectroscopic simulations reveals the simultaneous presence of cross-α and cross-ß polymorphs within samples of PSMα3 fibrils. We also report a new spectroscopic feature indicative of cross-α fibrils.

Investigating the mechanism of photoisomerization in jellyfish rhodopsin with the counterion at an atypical position.

The position of the counterion in animal rhodopsins plays a crucial role in maintaining visible light sensitivity and facilitating the photoisomerization of their retinal chromophore. The counterion displacement is thought to be closely related to the evolution of rhodopsins, with different positions found in invertebrates and vertebrates. Interestingly, box jellyfish rhodopsin (JelRh) acquired the counterion in transmembrane 2 independently. This is a unique feature, as in most animal rhodopsins, the counterion is found in a different location. In this study, we used Fourier Transform Infrared spectroscopy to examine the structural changes that occur in the early photointermediate state of JelRh. We aimed to determine whether the photochemistry of JelRh is similar to that of other animal rhodopsins by comparing its spectra to those of vertebrate bovine rhodopsin (BovRh) and invertebrate squid rhodopsin (SquRh). We observed that the N-D stretching band of the retinal Schiff base was similar to that of BovRh, indicating the interaction between the Schiff base and the counterion is similar in both rhodopsins, despite their different counterion positions. Furthermore, we found that the chemical structure of the retinal in JelRh is similar to that in BovRh, including the changes in the hydrogen-out-of-plane band that indicates a retinal distortion. Overall, the protein conformational changes induced by the photoisomerization of JelRh yielded spectra that resemble an intermediate between BovRh and SquRh, suggesting a unique spectral property of JelRh, and making it the only animal rhodopsin with a counterion in TM2 and an ability to activate Gs protein.

Infrared Spectroscopy for Rapid Triage of Cancer Using Blood Derivatives: A Reality Check.

Infrared (IR) spectroscopy of serum/plasma represents an alluring molecular diagnostic tool, especially for cancer, as it can provide a molecular fingerprint of clinical samples based on vibrational modes of chemical bonds. However, despite the superior performance, the routine adoption of this technique for clinical settings has remained elusive. This is due to the potential confounding factors that are often overlooked and pose a significant barrier to clinical translation. In this Perspective, we summarize the concerns associated with various confounding factors, such as fluid sampling, optical effects, hemolysis, abnormal cardiovascular and/or hepatic functions, infections, alcoholism, diet style, age, and gender of a patient or normal control cohort, and improper selection of numerical methods that ultimately would lead to improper spectral diagnosis. We also propose some precautionary measures to overcome the challenges associated with these confounding factors.

Development and validation of a quick, automated, and reproducible ATR FT-IR spectroscopy machine-learning model for Klebsiella pneumoniae typing.

The reliability of Fourier-transform infrared (FT-IR) spectroscopy for Klebsiella pneumoniae typing and outbreak control has been previously assessed, but issues remain in standardization and reproducibility. We developed and validated a reproducible FT-IR with attenuated total reflectance (ATR) workflow for the identification of K. pneumoniae lineages. We used 293 isolates representing multidrug-resistant K. pneumoniae lineages causing outbreaks worldwide (2002-2021) to train a random forest classification (RF) model based on capsular (KL)-type discrimination. This model was validated with 280 contemporaneous isolates (2021-2022), using wzi sequencing and whole-genome sequencing as references. Repeatability and reproducibility were tested in different culture media and instruments throughout time. Our RF model allowed the classification of 33 capsular (KL)-types and up to 36 clinically relevant K. pneumoniae lineages based on the discrimination of specific KL- and O-type combinations. We obtained high rates of accuracy (89%), sensitivity (88%), and specificity (92%), including from cultures obtained directly from the clinical sample, allowing to obtain typing information the same day bacteria are identified. The workflow was reproducible in different instruments throughout time (>98% correct predictions). Direct colony application, spectral acquisition, and automated KL prediction through Clover MS Data analysis software allow a short time-to-result (5 min/isolate). We demonstrated that FT-IR ATR spectroscopy provides meaningful, reproducible, and accurate information at a very early stage (as soon as bacterial identification) to support infection control and public health surveillance. The high robustness together with automated and flexible workflows for data analysis provide opportunities to consolidate real-time applications at a global level. IMPORTANCE We created and validated an automated and simple workflow for the identification of clinically relevant Klebsiella pneumoniae lineages by FT-IR spectroscopy and machine-learning, a method that can be extremely useful to provide quick and reliable typing information to support real-time decisions of outbreak management and infection control. This method and workflow is of interest to support clinical microbiology diagnostics and to aid public health surveillance.

Exploring the decolorization efficiency and biodegradation mechanisms of different functional textile azo dyes by Streptomyces albidoflavus 3MGH.

Efficiently mitigating and managing environmental pollution caused by the improper disposal of dyes and effluents from the textile industry is of great importance. This study evaluated the effectiveness of Streptomyces albidoflavus 3MGH in decolorizing and degrading three different azo dyes, namely Reactive Orange 122 (RO 122), Direct Blue 15 (DB 15), and Direct Black 38 (DB 38). Various analytical techniques, such as Fourier Transform Infrared (FTIR) spectroscopy, High-Performance Liquid Chromatography (HPLC), and Gas Chromatography-Mass Spectrometry (GC-MS) were used to analyze the degraded byproducts of the dyes. S. albidoflavus 3MGH demonstrated a strong capability to decolorize RO 122, DB 15, and DB 38, achieving up to 60.74%, 61.38%, and 53.43% decolorization within 5 days at a concentration of 0.3 g/L, respectively. The optimal conditions for the maximum decolorization of these azo dyes were found to be a temperature of 35 °C, a pH of 6, sucrose as a carbon source, and beef extract as a nitrogen source. Additionally, after optimization of the decolorization process, treatment with S. albidoflavus 3MGH resulted in significant reductions of 94.4%, 86.3%, and 68.2% in the total organic carbon of RO 122, DB 15, and DB 38, respectively. After the treatment process, we found the specific activity of the laccase enzyme, one of the mediating enzymes of the degradation mechanism, to be 5.96 U/mg. FT-IR spectroscopy analysis of the degraded metabolites showed specific changes and shifts in peaks compared to the control samples. GC-MS analysis revealed the presence of metabolites such as benzene, biphenyl, and naphthalene derivatives. Overall, this study demonstrated the potential of S. albidoflavus 3MGH for the effective decolorization and degradation of different azo dyes. The findings were validated through various analytical techniques, shedding light on the biodegradation mechanism employed by this strain.

Nanosecond time-resolved infrared spectroscopy for the study of electron transfer in photosystem I.

Microsecond time-resolved step-scan FTIR difference spectroscopy was used to study photosystem I (PSI) from Thermosynechococcus vestitus BP-1 (T. vestitus, formerly known as T. elongatus) at 77 K. In addition, photoaccumulated (P700+-P700) FTIR difference spectra were obtained at both 77 and 293 K. The FTIR difference spectra are presented here for the first time. To extend upon these FTIR studies nanosecond time-resolved infrared difference spectroscopy was also used to study PSI from T. vestitus at 296 K. Nanosecond infrared spectroscopy has never been used to study PSI samples at physiological temperatures, and here it is shown that such an approach has great value as it allows a direct probe of electron transfer down both branches in PSI. In PSI at 296 K, the infrared flash-induced absorption changes indicate electron transfer down the B- and A-branches is characterized by time constants of 33 and 364 ns, respectively, in good agreement with visible spectroscopy studies. These time constants are associated with forward electron transfer from A1- to FX on the B- and A-branches, respectively. At several infrared wavelengths flash-induced absorption changes at 296 K recover in tens to hundreds of milliseconds. The dominant decay phase is characterized by a lifetime of 128 ms. These millisecond changes are assigned to radical pair recombination reactions, with the changes being associated primarily with P700+ rereduction. This conclusion follows from the observation that the millisecond infrared spectrum is very similar to the photoaccumulated (P700+-P700) FTIR difference spectrum.

Study of Monoclonal Antibody Aggregation at the Air-Liquid Interface under Flow by ATR-FTIR Spectroscopic Imaging.

Throughout bioprocessing, transportation, and storage, therapeutic monoclonal antibodies (mAbs) experience stress conditions that may cause protein unfolding and/or chemical modifications. Such structural changes may lead to the formation of aggregates, which reduce mAb potency and may cause harmful immunogenic responses in patients. Therefore, aggregates need to be detected and removed or ideally prevented from forming. Air-liquid interfaces, which arise during various stages of bioprocessing, are one of the stress factors causing mAb aggregation. In this study, the behavior of an immunoglobulin G (IgG) at the air-liquid interface was investigated under flow using macro attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopic imaging. This chemically specific imaging technique allows observation of adsorption of IgG to the air-liquid interface and detection of associated secondary structural changes. Chemical images revealed that IgG rapidly accumulated around an injected air bubble under flow at 45 °C; however, no such increase was observed at 25 °C. Analysis of the second derivative spectra of IgG at the air-liquid interface revealed changes in the protein secondary structure associated with increased intermolecular ß-sheet content, indicative of aggregated IgG. The addition of 0.01% w/v polysorbate 80 (PS80) reduced the amount of IgG at the air-liquid interface in a static setup at 30 °C; however, this protective effect was lost at 45 °C. These results suggest that the presence of air-liquid interfaces under flow may be detrimental to mAb stability at elevated temperatures and demonstrate the power of ATR-FTIR spectroscopic imaging for studying the structural integrity of mAbs under bioprocessing conditions.

Screening of malaria infections in human blood samples with varying parasite densities and anaemic conditions using AI-Powered mid-infrared spectroscopy.

BACKGROUND: Effective testing for malaria, including the detection of infections at very low densities, is vital for the successful elimination of the disease. Unfortunately, existing methods are either inexpensive but poorly sensitive or sensitive but costly. Recent studies have shown that mid-infrared spectroscopy coupled with machine learning (MIRs-ML) has potential for rapidly detecting malaria infections but requires further evaluation on diverse samples representative of natural infections in endemic areas. The aim of this study was, therefore, to demonstrate a simple AI-powered, reagent-free, and user-friendly approach that uses mid-infrared spectra from dried blood spots to accurately detect malaria infections across varying parasite densities and anaemic conditions. METHODS: Plasmodium falciparum strains NF54 and FCR3 were cultured and mixed with blood from 70 malaria-free individuals to create various malaria parasitaemia and anaemic conditions. Blood dilutions produced three haematocrit ratios (50%, 25%, 12.5%) and five parasitaemia levels (6%, 0.1%, 0.002%, 0.00003%, 0%). Dried blood spots were prepared on Whatman™ filter papers and scanned using attenuated total reflection-Fourier Transform Infrared (ATR-FTIR) for machine-learning analysis. Three classifiers were trained on an 80%/20% split of 4655 spectra: (I) high contrast (6% parasitaemia vs. negative), (II) low contrast (0.00003% vs. negative) and (III) all concentrations (all positive levels vs. negative). The classifiers were validated with unseen datasets to detect malaria at various parasitaemia levels and anaemic conditions. Additionally, these classifiers were tested on samples from a population survey in malaria-endemic villages of southeastern Tanzania. RESULTS: The AI classifiers attained over 90% accuracy in detecting malaria infections as low as one parasite per microlitre of blood, a sensitivity unattainable by conventional RDTs and microscopy. These laboratory-developed classifiers seamlessly transitioned to field applicability, achieving over 80% accuracy in predicting natural P. falciparum infections in blood samples collected during the field survey. Crucially, the performance remained unaffected by various levels of anaemia, a common complication in malaria patients. CONCLUSION: These findings suggest that the AI-driven mid-infrared spectroscopy approach holds promise as a simplified, sensitive and cost-effective method for malaria screening, consistently performing well despite variations in parasite densities and anaemic conditions. The technique simply involves scanning dried blood spots with a desktop mid-infrared scanner and analysing the spectra using pre-trained AI classifiers, making it readily adaptable to field conditions in low-resource settings. In this study, the approach was successfully adapted to field use, effectively predicting natural malaria infections in blood samples from a population-level survey in Tanzania. With additional field trials and validation, this technique could significantly enhance malaria surveillance and contribute to accelerating malaria elimination efforts.

Evaluating Fourier-transform infrared spectroscopy with IR Biotyper as a faster and simpler method for investigating the sources of an outbreak of legionellosis.

Fourier-transform infrared (FTIR) spectroscopy using the IR Biotyper and core genome single nucleotide polymorphism (cgSNP) analysis were performed on 12 Legionella isolates associated with an outbreak at a spa house in Kanagawa Prefecture, Japan, and 3 non-outbreak isolates. The discriminative power of FTIR spectroscopy for 48-h incubation conditions of L. pneumophila in this outbreak was lower than cgSNP-based typing but higher than serogroup typing. FTIR spectroscopy could screen outbreak isolates from a group of genetically related isolates and may be useful as an initial typing method in Legionella outbreak investigations.

Identifying hypothermia death in a mouse model by ATR-FTIR.

The identification of hypothermia death (HD) is difficult for cadavers, especially the distinction from death due to alternative causes. A large number of studies have shown that brown adipose tissue (BAT) plays critical roles in thermoregulation of mammals. In this study, BAT of mice was used for the discrimination of HD using attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR). A modified mouse HD model conducted by Feeney DM was used in this study to obtain infrared spectra of BAT. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to establish discrimination models. The PLS-DA and OPLS-DA models exhibit prominent discriminative efficiency, and the accuracy of HD identification using fingerprint regions and ratios of absorption intensity is near 100% in both the calibration and validation sets. Our preliminary study suggests that BAT may be an extremely effective target tissue for identification of cadavers of HD, and ATR-FTIR spectra combined with chemometrics have also shown potential for cadaver identification in forensic practice in a fast and accurate manner.

Identification of sudden cardiac death from human blood using ATR-FTIR spectroscopy and machine learning.

OBJECTIVE: The aim of this study is to identify a rapid, sensitive, and non-destructive auxiliary approach for postmortem diagnosis of SCD, addressing the challenges faced in forensic practice. METHODS: ATR-FTIR spectroscopy was employed to collect spectral features of blood samples from different cases, combined with pathological changes. Mixed datasets were analyzed using ANN, KNN, RF, and SVM algorithms. Evaluation metrics such as accuracy, precision, recall, F1-score and confusion matrix were used to select the optimal algorithm and construct the postmortem diagnosis model for SCD. RESULTS: A total of 77 cases were collected, including 43 cases in the SCD group and 34 cases in the non-SCD group. A total of 693 spectrogram were obtained. Compared to other algorithms, the SVM algorithm demonstrated the highest accuracy, reaching 95.83% based on spectral biomarkers. Furthermore, by combing spectral biomarkers with age, gender, and cardiac histopathological changes, the accuracy of the SVM model could get 100%. CONCLUSION: Integrating artificial intelligence technology, pathology, and physical chemistry analysis of blood components can serve as an effective auxiliary method for postmortem diagnosis of SCD.

Sex and blood group determination from hair using ATR-FTIR spectroscopy and chemometrics.

Examination of hair with its intact root is commonly used for DNA profiling of the donor. However, its use for gathering other types of information is less explored. Using attenuated total reflectance-Fourier transform infrared spectroscopy, the present study aims to explore other relevant aspects in a non-destructive manner for forensics. Determining the sex and blood group of human hair samples were the major goals of the study. Sex determination was accomplished by analyzing the differential vibrational intensities and stretching of various chemical groups associated with hair and its proteins. Statistical inference of spectral data was performed using chemometric algorithms such as PCA and PLS-DA. The PLS-DA model determined sex with 100% accuracy and blood grouping with an average accuracy of 95%. The present study is the first of its kind to determine sex and blood grouping from human scalp hair shafts, as far as the author knows. By acting as a preliminary screening test, this study could have significant implications for forensic analysis of crime scene samples. Human and synthetic hair were used in validation studies, resulting in 100% accuracy, specificity, and sensitivity, with 0% false positives and false negatives. The technique ATR FTIR spectroscopy could complement the currently used methods of hair analysis such as physical examination and mitochondrial or genomic DNA analysis.

Serum-based ATR-FTIR spectroscopy combined with multivariate analysis for the diagnosis of pre-diabetes and diabetes.

Diabetes mellitus (DM) is a metabolic disease with an increasing prevalence that is causing worldwide concern. The pre-diabetes stage is the only reversible stage in the patho-physiological process towards DM. Due to the limitations of traditional methods, the diagnosis and detection of DM and pre-diabetes are complicated, expensive, and time-consuming. Therefore, it would be of great benefit to develop a simple, rapid and inexpensive diagnostic test. Herein, the infrared (IR) spectra of serum samples from 111 DM patients, 111 pre-diabetes patients and 333 healthy volunteers were collected using attenuated total reflection Fourier-transform IR (ATR-FTIR) spectroscopy and this was combined with the multivariate analysis of principal component analysis linear discriminant analysis (PCA-LDA) to develop a discriminant model to verify the diagnostic potential of this approach. The study found that the accuracy of the test model established by ATR-FTIR spectroscopy combined with PCA-LDA was 97%, and the sensitivity and specificity were 100% and 100% in the control group, 94% and 98% in the pre-diabetes group, and 91% and 98% in the DM group, respectively. This indicates that this method can effectively diagnose DM and pre-diabetes, which has far-reaching clinical significance.

Attenuated total reflection Fourier-transform infrared spectroscopy for the prediction of hormone concentrations in plants.

Plant hormones are important in the control of physiological and developmental processes including seed germination, senescence, flowering, stomatal aperture, and ultimately the overall growth and yield of plants. Many currently available methods to quantify such growth regulators quickly and accurately require extensive sample purification using complex analytic techniques. Herein we used ultra-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) to create and validate the prediction of hormone concentrations made using attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectral profiles of both freeze-dried ground leaf tissue and extracted xylem sap of Japanese knotweed (Reynoutria japonica) plants grown under different environmental conditions. In addition to these predictions made with partial least squares regression, further analysis of spectral data was performed using chemometric techniques, including principal component analysis, linear discriminant analysis, and support vector machines (SVM). Plants grown in different environments had sufficiently different biochemical profiles, including plant hormonal compounds, to allow successful differentiation by ATR-FTIR spectroscopy coupled with SVM. ATR-FTIR spectral biomarkers highlighted a range of biomolecules responsible for the differing spectral signatures between growth environments, such as triacylglycerol, proteins and amino acids, tannins, pectin, polysaccharides such as starch and cellulose, DNA and RNA. Using partial least squares regression, we show the potential for accurate prediction of plant hormone concentrations from ATR-FTIR spectral profiles, calibrated with hormonal data quantified by UHPLC-HRMS. The application of ATR-FTIR spectroscopy and chemometrics offers accurate prediction of hormone concentrations in plant samples, with advantages over existing approaches.

Fast cancer imaging in pancreatic biopsies using infrared imaging.

Pancreatic cancer, particularly Pancreatic ductal adenocarcinoma, remains a highly lethal form of cancer with limited early diagnosis and treatment options. Infrared (IR) spectroscopy, combined with machine learning, has demonstrated great potential in detecting various cancers. This study explores the translation of a diagnostic model from Fourier Transform Infrared to Quantum Cascade Laser (QCL) microscopy for pancreatic cancer classification. Furthermore, QCL microscopy offers faster measurements with selected frequencies, improving clinical feasibility. Thus, the goals of the study include establishing a QCL-based model for pancreatic cancer classification and creating a fast surgical margin detection model using reduced spectral information. The research involves preprocessing QCL data, training Random Forest (RF) classifiers, and optimizing the selection of spectral features for the models. Results demonstrate successful translation of the diagnostic model to QCL microscopy, achieving high predictive power (AUC = 98%) in detecting cancerous tissues. Moreover, a model for rapid surgical margin recognition, based on only a few spectral frequencies, is developed with promising differentiation between benign and cancerous regions. The findings highlight the potential of QCL microscopy for efficient pancreatic cancer diagnosis and surgical margin detection within clinical timeframes of minutes per surgical resection tissue.

A novel approach using ATR-FTIR spectroscopy and chemometric analysis to distinguish male and female human hair samples.

This article presents an attempt to discriminate between human male and female hair samples using a single strand of scalp hair. The methodology involves the non-destructive application of ATR-FTIR spectroscopy coupled with chemometric analysis. A total of 96 hair samples, evenly distributed between 48 male and 48 female volunteers from India, were collected. Spectral analysis revealed subtle differences between the two groups, and reliance on visual interpretation might introduce biasness. To avoid subjective biases, chemometric techniques such as principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA) were employed for enhanced data visualization and separation. PCA results revealed that the first 10 principal components accounted for 93% of the total variance, with three significant PCs. The PLS-DA model demonstrated a remarkable sensitivity and specificity in sex discrimination from hair samples, establishing its efficacy as a robust classification tool. Furthermore, the proposed model exhibited 100% accuracy in predicting unknown samples, underscoring its potential applicability in real-world scenarios. These outcomes affirm the viability of our approach for non-invasive classification of human male and female hair based on single-strand scalp hair analysis.

Characterization and antibacterial evaluation of Eco-friendly silver nanoparticles synthesized by halophilic Streptomyces rochei SSCM102 isolated from mangrove sediment.

BACKGROUND: Antimicrobial resistance has surged due to widespread antimicrobial drug use, prompting interest in biosynthesizing nanoparticles from marine-derived actinomycetes extracellular metabolites, valued for their diverse bioactive compounds. This approach holds promise for addressing the urgent need for novel antimicrobial agents. The current study aimed to characterize novel bioactive compounds from unexplored biodiversity hotspots, halophilic Streptomyces sp. isolated from mangrove sediment in the Pichavaram region, India. METHODS AND RESULTS: Streptomyces rochei SSCM102 was conclusively identified through morphological and molecular characterization. Synthesis of silver nanoparticles (AgNPs) from Streptomyces rochei SSCM102 was characterized using various techniques, including UV-Vis, XRD, SEM, EDX, and FT-IR. The UV-Vis spectrum of the reduced AgNPs exhibited a prominent peak at 380 nm, confirming the AgNPs. The UV-Vis spectrum confirmed the synthesis of AgNP, and SEM analysis revealed a cubic morphology with sizes ranging from 11 to 21 nm. The FTIR spectrum demonstrated a shift in frequency widths between 626 cm-1 and 3432 cm-1. The EDX analysis substantiated the presence of metallic silver, evident from a strong band at 1.44 keV. The synthesized AgNPs exhibited antibacterial efficacy against human pathogens Escherichia coli (64 ± 0.32 µg/ml), Klebsiella pneumoniae (32 ± 0.16 µg/ml), and Pseudomonas aeruginosa (16 ± 0.08 µg/ml) by MIC and MBC values of 128 ± 0.64 (µg/ml), 64 ± 0.32 (µg/ml) and 32 ± 0.16 (µg/ml), respectively. Additionally, at a concentration of 400 µg/ml, the AgNPs displayed a 72% inhibition of DPPH radicals, indicating notable antioxidant capacity. The LC50 value of 130 µg/mL indicates that the green-synthesized AgNPs have lower toxicity by Brine Shrimp Larvae assay. CONCLUSION: The study's novel approach to synthesizing eco-friendly silver nanoparticles using Halophilic Streptomyces rochei SSCM102 contributes significantly to the field of biomedical research and drug development. By demonstrating potent antibacterial properties and aligning with sustainability goals, these nanoparticles offer promising avenues for novel antibacterial therapies.

Advancements in medical research: Exploring Fourier Transform Infrared (FTIR) spectroscopy for tissue, cell, and hair sample analysis.

BACKGROUND: Fourier Transform Infrared (FTIR) spectroscopy has emerged as a powerful analytical tool in medical research, offering non-invasive and precise examination of the molecular composition of biological samples. The primary objective of this review is to underscore the benefits of FTIR spectroscopy in medicinal research, emphasizing its ability to delineate molecular fingerprints and assist in the identification of biochemical structures and key peaks in biological samples. METHODS: This review comprehensively explores the diverse applications of FTIR spectroscopy in medical investigations, with a specific focus on its utility in analyzing tissue, cells, and hair samples. Various sources, including Google Scholar, PubMed, WorledCat and Scopus, were utilized to conduct this comprehensive literature review. RESULTS: Recent advancements showcase the versatility of FTIR spectroscopy in elucidating cellular and molecular processes, facilitating disease diagnostics, and enabling treatment monitoring. Notably, FTIR spectroscopy has found significant utility in clinical assessment, particularly in screening counterfeit medicines, owing to its user-friendly operation and minimal sample preparation requirements. Furthermore, customs officials can leverage this technique for preliminary analysis of suspicious samples. CONCLUSION: This review aims to bridge a gap in the literature and serve as a valuable resource for future research endeavors in FTIR spectroscopy within the medical domain. Additionally, it presents fundamental concepts of FTIR spectroscopy and spectral data interpretation, highlighting its utility as a tool for molecular analysis using Mid-Infrared (MIR) radiation.

Development and evaluation of the in vitro schistosomicidal activity of solid dispersions based on 2-(-5-bromo-1-H-indole-3-yl-methylene)-N-(naphthalene-1-ylhydrazine-carbothiamide.

Among all the neglected diseases, schistosomiasis is considered the second most important parasitic infection after malaria. Praziquantel is the most widely used drug for this disease, but its exclusive use may result in the development of drug-resistant schistosomiasis. To increase the control of the disease, new drugs have been developed as alternative treatments, among them 2-(-5-bromo-1-h-indole-3-yl-methylene)-N-(naphthalene-1-ylhydrazine-carbothiamide (LQIT/LT-50), which showed promising schistosomicidal activity in nonclinical studies. However, LQIT/LT-50 presents low solubility in water, resulting in reduced bioavailability. To overcome this solubility problem, the present study aimed to develop LQIT/LT-50 solid dispersions for the treatment of schistosomiasis. Solid dispersions were prepared through the solvent method using Soluplus©, polyethylene glycol (PEG) or polyvinylpyrrolidone (PVP K-30) as hydrophilic carriers. The formulations with the best results in the compatibility tests, aqueous solubility and preliminary stability studies have undergone solubility tests and physicochemical characterizations by Fourier-transform infrared spectroscopy (FTIR), x-ray diffractometry (XRD), exploratory differential calorimetry (DSC), thermogravimetry (TG) and Raman spectroscopy. Finally, the schistosomicidal activity was evaluated in vitro. The phycochemical analyzes showed that when using PVP K-30, there was an interaction between the PVP K-30 and LQIT/LT-50, proving the successful development of the solid dispersion. Furthermore, an increase in the solubility of the new system was observed (LQIT/LT-50:PVP K-30) in addition to the improvement in the in vitro shistosomidal activity at 1:4 (w/w) molar ratio (i.e., 20% drug loading) when compared to LQIT/LT-50 alone. The development of the LQIT/LT-50:PVP K-30 1:4 solid dispersion is encouraging for the future development of new pharmaceutical solid formulations, aiming the schistosomicidal treatment.