Serum and plasma as a good candidates of body fluids for detection lung cancer by FTIR liquid biopsy.

Using Fourier Transform Infrared spectroscopy (FTIR), it is possible to show chemical composition of materials and / or profile chemical changes occurring in tissues, cells, and body fluids during onset and progression of diseases. For diagnostic application, the use of blood would be the most appropriate in biospectroscopy studies since, (i) it is easily accessible and, (ii) enables frequent analyses of biochemical changes occurring in pathological states. At present, different studies have investigated potential of serum, plasma and sputum being alternative biofluids for lung cancer detection using FTIR.

Differentiation of glioblastoma G4 and two types of meningiomas using FTIR spectra and machine learning.

Brain tumors are among the most dangerous, due to their location in the organ that governs all life processes. Moreover, the high differentiation of these poses a challenge in diagnostics. Therefore, this study focused on the chemical differentiation of glioblastoma G4 (GBM) and two types of meningiomas (atypical - MAtyp and angiomatous - MAng) were done using Fourier Transform InfraRed (FTIR) spectroscopy, combined with statistical, multivariate, machine learning and rate of spectrum changes methods.

Synthesis of spherical and rods-like titanium oxide nanoparticles (TiO NPs) and evaluation of their cytotoxicity towards colon cells in vitro.

Titanium oxide nanoparticles (TiO NPs) are currently used as ingredients in medicines and sunscreens. Unfortunately, recent information about TiO NPs indicates their undesirable biological effect on colon cells. Therefore, the aim of this work was to synthesize and evaluate the physicochemical characterization of spherical (TiO NSs) and rods-like (TiO NRs) NPs, followed by assessment their cytotoxicity.

Correction: Bucki et al. Bactericidal Properties of Rod-, Peanut-, and Star-Shaped Gold Nanoparticles Coated with Ceragenin CSA-131 against Multidrug-Resistant Bacterial Strains. 2021, , 425.

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Urine Analysed by FTIR, Chemometrics and Machine Learning Methods in Determination Spectroscopy Marker of Prostate Cancer in Urine.

Prostate-specific antigen (PSA) is the most commonly used marker of prostate cancer. However, nearly 25% of men with elevated PSA levels do not have cancer and nearly 20% of patients with prostate cancer have normal serum PSA levels. Therefore, in this study, Fourier transform infrared (FTIR) spectroscopy was investigated as a new tool for detection of prostate cancer from urine.

Fourier transform InfraRed spectra analyzed by multivariate and machine learning methods in determination spectroscopy marker of prostate cancer in dried serum.

Prostate cancer represents the second most prevalent form of cancer in males globally. In the diagnosis of prostate cancer, the most commonly utilised biomarker is prostate-specific antigen (PSA). It is unfortunate that approximately 25 % of men with elevated PSA levels do not have cancer, and that approximately 20 % of patients with prostate cancer have normal serum PSA levels.

Determination of platinum-resistance of women with ovarian cancer by FTIR spectroscopy combined with multivariate analyses and machine learning methods.

Patients with high-grade ovarian cancer have a poor prognosis, thus effective treatment remains an unmet medical issue of high importance. Moreover, finding the reason for resistance to cisplatin is a crucial task for the improvement of anti-cancer drugs. In this study, we showed for the first time a chemical difference in a serum collected from platinum-resistance and platinum-sensitive women suffering from ovarian cancer using Fourier Transform InfraRed (FTIR) spectroscopy followed by a data analysis by Principal Component Analysis (PCA), Hierarchical Component Analysis (HCA) and 4 different machine learning algorithms.

FTIR monitoring of the 13-valent pneumococcal conjugate vaccine for lung cancer patients: Changes in amides vibrations correlated with biochemical assays.

Lung cancer is one of the most lethal cancers. Unfortunately, respiratory tract infections are very common in lung cancer patients, delaying appropriate anticancer therapy. To increase therapy efficiency, in this study we examined the effect of 13-Valent Pneumococcal Conjugate Vaccine on the immune response in lung cancer patients, which indirectly affects the success of anticancer therapy.

Chemical composition alterations in rat brain hypothalamus induced by irisin administration using spectroscopic and machine learning techniques.

This study employed Fourier transform infrared (FTIR) spectroscopy to determine the chemical composition of brain tissues and the changes induced by irisin at doses of 50 mg and 100 mg. Brain tissues were collected from control rats and those administered with irisin, and key vibrational peaks were analyzed. In the 50 mg irisin group, all described vibrations decreased compared to control tissues, while the 100 mg group showed a decrease only in lipid vibrations.

Detection of serum alterations in polysubstance use patients by FT-Raman spectroscopy.

Substance use disorders pose significant health risks and treatment challenges due to the diverse interactions between substances and their impact on physical and mental health. The chemical effects of multiple substance use on bodily fluids are not yet fully understood. Therefore, this study aimed to investigate the chemical changes induced by a combination of substances compared to a control group.

Female-age-dependent changes in the lipid fingerprint of the mammalian oocytes.

Study Question: Can oocyte functionality be assessed by observing changes in their intracytoplasmic lipid droplets (LDs) profiles?

Summary Answer: Lipid profile changes can reliably be detected in human oocytes; lipid changes are linked with maternal age and impaired developmental competence in a mouse model.

What Is Known Already: In all cellular components, lipid damage is the earliest manifestation of oxidative stress (OS), which leads to a cascade of negative consequences for organelles and DNA. Lipid damage is marked by the accumulation of LDs.

Determination of spectroscopy marker of atherosclerotic carotid stenosis using FTIR-ATR combined with machine learning and chemometrics analyses.

Atherosclerotic carotid stenosis (ACS) is a recognized risk factor for ischemic stroke. Currently, the gold diagnostic standard is Doppler ultrasound, the results of which do not provide certainty whether a given person should be qualified for surgery or not, because in some patients, carotid artery stenosis, for example at the level of 70 %, does not cause ischemic stroke in others yes. Therefore, there is a need for new methods that will clearly indicate the marker qualifying the patient for surgery.

Raman spectroscopy combined with machine learning and chemometrics analyses as a tool for identification atherosclerotic carotid stenosis from serum.

Atherosclerosis carotid stenosis (ACS) is one of the main causes of stroke. Unfortunately, the highest number of people go to the doctor with an advanced disease or as a result of a stroke, because carotid atherosclerosis does not cause obvious symptoms. Therefore, it is important to find a diagnostic method to detect the disease during routine tests (using blood or serum).

Understanding the Growth of Electrodeposited PtNi Nanoparticle Films Using Correlated Liquid Cell Transmission Electron Microscopy and Synchrotron Radiation.

Electrodeposition is a versatile method for synthesizing nanostructured films, but controlling the morphology of films containing two or more elements requires a detailed understanding of the deposition process. We used liquid cell transmission electron microscopy to follow the electrodeposition of PtNi nanoparticle films on a carbon electrode during cyclic voltammetry. These observations show that the film thickness increases with each cycle, and by the fourth cycle, branched and porous structures could be deposited.

Relationship between amide ratio assessed by Fourier-transform infrared spectroscopy: A biomarker candidate for polycythemia vera disease.

The study utilized Fourier transform infrared (FTIR) spectroscopy coupled with chemometrics to investigate protein composition and structural changes in the blood serum of patients with polycythemia vera (PV). Principal component analysis (PCA) revealed distinct biochemical properties, highlighting elevated absorbance of phospholipids, amides, and lipids in PV patients compared to healthy controls. Ratios of amide I/amide II and amide I/amide III indicated alterations in protein structures.

Investigation of the structural changes in the hippocampus and prefrontal cortex using FTIR spectroscopy in sleep deprived mice.

Sleep is a basic, physiological requirement for living things to survive and is a process that covers one third of our lives. Melatonin is a hormone that plays an important role in the regulation of sleep. Sleep deprivation affect brain structures and functions.

Lipids balance as a spectroscopy marker of diabetes. Analysis of FTIR spectra by 2D correlation and machine learning analyses.

The number of people suffering from type 2 diabetes has rapidly increased. Taking into account, that elevated intracellular lipid concentrations, as well as their metabolism, are correlated with diminished insulin sensitivity, in this study we would like to show lipids spectroscopy markers of diabetes. For this purpose, serum collected from rats (animal model of diabetes) was analyzed using Fourier Transformed Infrared-Attenuated Total Reflection (FTIR-ATR) spectroscopy.

Raman Spectroscopy of Blood Serum for Essential Thrombocythemia Diagnosis: Correlation with Genetic Mutations and Optimization of Laser Wavelengths.

Essential thrombocythemia (ET) is a type of myeloproliferative neoplasm that increases the risk of thrombosis. To diagnose this disease, the analysis of mutations in the Janus Kinase 2 (JAK2), thrombopoietin receptor (MPL), or calreticulin (CALR) gene is recommended. Disease poses diagnostic challenges due to overlapping mutations with other neoplasms and the presence of triple-negative cases.

Modeling Absorption Dynamics of Differently Shaped Gold Glioblastoma and Colon Cells Based on Refractive Index Distribution in Holotomographic Imaging.

Herein, it is demonstrated that the toxic effect of gold nanoparticles (Au NPs) on three different cancer cell lines (U-118 and LN-299 glioblastoma and HCT-116 colon) depends on their absorption dynamics by cells, related to the shapes of the NPs. This hypothesis is confirmed by showing that i) based on refractive index (RI) values, typical for cell components and gold nanoparticles, it is possible to show the absorption dynamics and accumulation locations of the latter ones inside and outside of the cells. Moreover, ii) the saturation of the accumulated Au NPs volume in the cells depends on the nanoparticle shape and is reached in the shortest time for star-shaped Au NPs (AuS NPs) and in the longest time for spherical Au NPs (AuSph NPs) and on the cancer cells, where the longest and the shortest saturation are noticed for HCT-116 and LN-229 cells, respectively.

FT-Raman and FTIR spectroscopy as a tools showing marker of platinum-resistant phenomena in women suffering from ovarian cancer.

Platinum-resistant phenomena in ovarian cancer is very dangerous for women suffering from this disease, because reduces the chances of complete recovery. Unfortunately, until now there are no methods to verify whether a woman with ovarian cancer is platinum-resistant. Importantly, histopathology images also were not shown differences in the ovarian cancer between platinum-resistant and platinum-sensitive tissues.

Quantitative or qualitative biomolecular changes in blood serum composition induced by childhood obesity: A Fourier transform infrared examination.

Childhood obesity (CO) negatively affects one in three children and stands as the fourth most common risk factor of health and well-being. Clarifying the molecular and structural modifications that transpire during the development of obesity is crucial for understanding its progression and devising effective therapies. The study was indeed conducted as part of an ongoing CO treatment trial, where data were collected from children diagnosed with CO before the initiation of non-drug treatment interventions.

FT-Raman spectra in combination with machine learning and multivariate analyses as a diagnostic tool in brain tumors.

Brain tumors are one of the most dangerous, because the position of these are in the organ that governs all life processes. Moreover, a lot of brain tumor types were observed, but only one main diagnostic method was used - histopathology, for which preparation of sample was long. Consequently, a new, quicker diagnostic method is needed.

FT-Raman data analyzed by multivariate and machine learning as a new methods for detection spectroscopy marker of platinum-resistant women suffering from ovarian cancer.

The phenomenon of platinum resistance is a very serious problem in the treatment of ovarian cancer. Unfortunately, no molecular, genetic marker that could be used in assigning women suffering from ovarian cancer to the platinum-resistant or platinum-sensitive group has been discovered so far. Therefore, in this study, for the first time, we used FT-Raman spectroscopy to determine chemical differences and chemical markers presented in serum, which could be used to differentiate platinum-resistant and platinum-sensitive women.

FeO Magnetic Nanoparticles Obtained by the Novel Aerosol-Based Technique for Theranostic Applications.

This work is aimed at presenting a novel aerosol-based technique for the synthesis of magnetite nanoparticles (Fe3O4 NPs) and to assess the potential medical application of their dispersions after being coated with TEA-oleate. Refinement of the processing conditions led to the formation of monodispersed NPs with average sizes of ∼5-6 nm and narrow size distribution ( of ∼3 nm). The NPs were coated with Triethanolammonium oleate (TEA-oleate) to stabilize them in water dispersion.

Detection of primary myelofibrosis in blood serum via Raman spectroscopy assisted by machine learning approaches; correlation with clinical diagnosis.

Primary myelofibrosis (PM) is one of the myeloproliferative neoplasm, where stem cell-derived clonal neoplasms was noticed. Diagnosis of this disease is based on: physical examination, peripheral blood findings, bone marrow morphology, cytogenetics, and molecular markers. However, the molecular marker of PM, which is a mutation in the JAK2V617F gene, was observed also in other myeloproliferative neoplasms such as polycythemia vera and essential thrombocythemia.