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. A physical model of Au NPs absorption dynamics is proposed, where the diameter and shape of the Au NPs are used as parameters. The obtained theoretical data are consistent with experimental data in 85-98%.

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. In this paper, FT-Raman spectra of brain tissues were analyzed by Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA), four different machine learning (ML) algorithms to show possibility of differentiating between glioblastoma G4 and meningiomas, as well as two different types of meningiomas (atypical and angiomatous). Obtained results showed that in meningiomas additional peak around 1503 cm-1 and higher level of amides was noticed in comparison with glioblastoma G4. In the case of meningiomas differentiation, in angiomatous meningiomas tissues lower level of lipids and polysaccharides were visible than in atypical meningiomas. Moreover, PCA analyses showed higher distinction between glioblastoma G4 and meningiomas in the FT-Raman range between 800 cm-1 and 1800 cm-1 and between two types of meningiomas in the range between 2700 cm-1 and 3000 cm-1. Decision trees showed, that the most important peaks to differentiate glioblastoma and meningiomas were at 1151 cm-1 and 2836 cm-1 while for angiomatous and atypical meningiomas - 1514 cm-1 and 2875 cm-1. Furthermore, the accuracy of obtained results for glioblastoma G4 and meningiomas was 88 %, while for meningiomas - 92 %. Consequently, obtained data showed possibility of using FT-Raman spectroscopy in diagnosis of different types of brain tumors.

Lipid droplets in mammalian eggs are utilized during embryonic diapause.

Embryonic diapause (ED) is a temporary arrest of an embryo at the blastocyst stage when it waits for the uterine receptivity signal to implant. ED used by over 100 species may also occur in normally "nondiapausing" mammals when the uterine receptivity signal is blocked or delayed. A large number of lipid droplets (LDs) are stored throughout the preimplantation embryo development, but the amount of lipids varies greatly across different mammalian species. Yet, the role of LDs in the mammalian egg and embryo remains unknown. Here, using a mouse model, we provide evidence that LDs play a crucial role in maintaining ED. By mechanical removal of LDs from zygotes, we demonstrated that delipidated embryos are unable to survive during ED. LDs are not essential for normal prompt implantation, without ED. We further demonstrated that with the progression of ED, the amount of intracellular lipid reduces, and composition changes. This decrease in lipid is caused by a switch from carbohydrate metabolism to lipid catabolism in diapausing blastocysts, which also exhibit increased release of exosomes reflecting elevated embryonic signaling to the mother. We have also shown that presence of LDs in the oocytes of various mammals positively corelates with their species-specific length of diapause. Our results reveal the functional role of LDs in embryonic development. These results can help to develop diagnostic techniques and treatment of recurrent implantation failure and will likely ignite further studies in developmental biology and reproductive medicine fields.

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. Therefore, there is a need to find methods that provide a marker unique to PM and allow for higher accuracy of PM diagnosis and consequently the treatment of the disease. Continuing, in this study, we used Raman spectroscopy, Principal Components Analysis (PCA), and Partial Least Squares (PLS) analysis as helpful diagnostic tools for PM. Consequently, we used serum collected from PM patients, which were classified using clinical parameters of PM such as the dynamic international prognostic scoring system (DIPSS) for primary myelofibrosis plus score, the JAK2V617F mutation, spleen size, bone marrow reticulin fibrosis degree and use of hydroxyurea drug features. Raman spectra showed higher amounts of C-H, C-C and C-C/C-N and amide II and lower amounts of amide I and vibrations of CH3 groups in PM patients than in healthy ones. Furthermore, shifts of amides II and I vibrations in PM patients were noticed. Machine learning methods were used to analyze Raman regions: (i) 800 cm-1 and 1800 cm-1, (ii) 1600 cm-1-1700 cm-1, and (iii) 2700 cm-1-3000 cm-1 showed 100 % accuracy, sensitivity, and specificity. Differences in the spectral dynamic showed that differences in the amide II and amide I regions were the most significant in distinguishing between PM and healthy subjects. Importantly, until now, the efficacy of Raman spectroscopy has not been established in clinical diagnostics of PM disease using the correlation between Raman spectra and PM clinical prognostic scoring. Continuing, our results showed the correlation between Raman signals and bone marrow fibrosis, as well as JAKV617F. Consequently, the results revealed that Raman spectroscopy has a high potential for use in medical laboratory diagnostics to quantify multiple biomarkers simultaneously, especially in the selected Raman regions.

Correlation between human colon cancer specific antigens and Raman spectra. Attempting to use Raman spectroscopy in the determination of tumor markers for colon cancer.

Colorectal cancer is the second most common cause of cancer-related deaths worldwide. To follow up on the progression of the disease, tumor markers are commonly used. Here, we report serum analysis based on Raman spectroscopy to provide a rapid cancer diagnosis with tumor markers and two new cell adhesion molecules measured using the ELISA method. Raman spectra showed higher Raman intensities at 1447 cm-1 1560 cm-1, 1665 cm-1, and 1769 cm-1, which originated from CH2 proteins and lipids, amide II and amide I, and CO lipids vibrations. Furthermore, the correlation test showed, that only the CEA colon cancer marker correlated with the Raman spectra. Importantly, machine learning methods showed, that the accuracy of the Raman method in the detection of colon cancer was around 95 %. Obtained results suggest, that Raman shifts at 1302 cm-1 and 1306 cm-1 can be used as spectroscopy markers of colon cancer.

Increased levels of nerve growth factor accompany oxidative load in recurrent pregnancy loss. Machine learning applied to FT-Raman spectra study.

The presented article is focused on developing and validating an efficient, credible, minimally invasive technique based on spectral signatures of blood serum samples in patients with diagnosed recurrent pregnancy loss (RPL) versus healthy individuals who were followed at the Gynecology department. A total of 120 participants, RPL disease (n = 60) and healthy individuals (n = 60), participated in the study. First, we investigated the effect of circulating nerve growth factor (NGF) in RPL and healthy groups. To show NGF's effect, we measured the level of oxidative loads such as Total Antioxidant Level (TAS), Total Oxidant Level (TOS), and Oxidative Stress Index (OSI) with Beckman Coulter AU system and biochemical assays. We find a correlation between oxidative load and NGF level. Oxidative load mainly causes structural changes in the blood. Therefore, we obtained Raman measurements of the participant's serum. Then we selected two Raman regions, 800 and 1800 cm-1, and between 2700 cm-1 and 3000 cm-1, to see chemical changes. We noted that Raman spectra obtained for RPL and healthy women differed. The findings confirm that the imbalance between reactive oxygen species and antioxidants has important implications for the pathogenesis of RPL and that NGF levels accompany the level of oxidative load in the RPL state. Biomolecular structure and composition were determined using Raman spectroscopy and machine learning methods, and the correlation of these parameters was studied alongside machine learning technologies to advance toward clinical translation. Here we determined and validated the development of instrumentation for the Analysis of RPL patients' serum that can differentiate from control individuals with an accuracy of 100% using the Raman region corresponding to structural changes. Furthermore, this study found a correlation between traditional biochemical parameters and Raman data. This suggests that Raman spectroscopy is a sensitive tool for detecting biochemical changes in serum caused by RPL or other diseases.

Blood serum lipid profiling may improve the management of recurrent miscarriage: a combination of machine learning of mid-infrared spectra and biochemical assays.

The present article is focused on developing and validating an efficient, credible, minimally invasive technique based on spectral signatures of blood samples of women with recurrent miscarriage vs. those of healthy individuals who were followed in the Department of Obstetrics and Gynecology for 2 years. For this purpose, blood samples from a total of 120 participants, including healthy women (n=60) and women with diagnosed recurrent miscarriage (n=60), were obtained. The lipid profile (high-density lipoprotein, low-density lipoprotein, triglyceride, and total cholesterol levels) and lipid peroxidation (malondialdehyde and glutathione levels) were evaluated with a Beckman Coulter analyzer system for chemical analysis. Biomolecular structure and composition were determined using an attenuated total reflectance sampling methodology with Fourier transform infrared spectroscopy alongside machine learning technology to advance toward clinical translation. Here, we developed and validated instrumentation for the analysis of recurrent miscarriage patient serum that was able to differentiate recurrent miscarriage and control patients with an accuracy of 100% using a Fourier transform infrared region corresponding to lipids. We found that predictors of lipid profile abnormalities in maternal serum could significantly improve this patient pathway. The study also presents preliminary results from the first prospective clinical validation study of its kind.

Application of Spectroscopic Methods for the Identification of Superoxide Dismutases in Cyanobacteria.

Superoxide dismutases (SODs) belong to the group of metalloenzymes that remove superoxide anion radicals and they have been identified in three domains of life: Bacteria, Archaea and Eucarya. SODs in Synechocystis sp. PCC 6803, Gloeobacter violaceus CCALA 979, and Geitlerinema sp. ZHR1A were investigated. We hypothesized that iron (FeSOD) and/or manganese (MnSOD) dominate as active forms in these cyanobacteria. Activity staining and three different spectroscopic methods of SOD activity bands excised from the gels were used to identify a suitable metal in the separated samples. FeSODs or enzymes belonging to the Fe-MnSOD superfamily were detected. The spectroscopic analyses showed that only Fe is present in the SOD activity bands. We found FeSOD in Synechocystis sp. PCC 6803 while two forms in G. violaceus and Geitlerinema sp. ZHR1A: FeSOD1 and FeSOD2 were present. However, no active Cu/ZnSODs were identified in G. violaceus and Geitlerinema sp. ZHR1A. We have shown that selected spectroscopic techniques can be complementary to the commonly used method of staining for SOD activity in a gel. Furthermore, the occurrence of active SODs in the cyanobacteria studied is also discussed in the context of SOD evolution in oxyphotrophs.

Development of novel spectroscopic and machine learning methods for the measurement of periodic changes in COVID-19 antibody level.

In this research, blood samples of 47 patients infected by COVID were analyzed. The samples were taken on the 1st, 3rd and 6th month after the detection of COVID infection. Total antibody levels were measured against the SARS-CoV-2 N antigen and surrogate virus neutralization by serological methods. To differentiate COVID patients with different antibody levels, Fourier Transform InfraRed (FTIR) and Raman spectroscopy methods were used. The spectroscopy data were analyzed by multivariate analysis, machine learning and neural network methods. It was shown, that analysis of serum using the above-mentioned spectroscopy methods allows to differentiate antibody levels between 1 and 6 months via spectral biomarkers of amides II and I. Moreover, multivariate analysis showed, that using Raman spectroscopy in the range between 1317 cm-1 and 1432 cm-1, 2840 cm-1 and 2956 cm-1 it is possible to distinguish patients after 1, 3, and 6 months from COVID with a sensitivity close to 100%.

Changes in Chemical Composition and Accumulation of Cryoprotectants as the Adaptation of Anholocyclic Aphid Cinara tujafilina to Overwintering.

One of the consequences of climate change is the expansion of insects' ranges. Colonization of new habitats forces insects to adapt to new conditions, such as low temperatures in winter. Cinara tujafilina is a thermophilic anholocyclic aphid species, which reproduce exclusively parthenogenetic throughout the year, including winter. On the areas where the populations of C. tujafilina had expanded, it demonstrated its adaptation for surviving colder winters. Based on analyses of changes in body chemical composition using Fourier transform infrared (FTIR) and changes in cryoprotectant content using high performance liquid chromatography (HPLC), we showed how aphid C. tujafilina adapted to overwintering as an active stage. In the FTIR spectrum of the winter type of C. tujafilina, higher peak values originating from the carbohydrates, proteins and lipids, were observed. Glucose, trehalose, mannitol, myo-inositol and glycerol were identified in the aphid body in winter as main putative cryoprotectants to increase the insects' tolerance to cold. The complex sugar-polyol cryoprotectant system facilitates aphids' survival in unfavorable low temperatures.

Treating honey bees with an extremely low frequency electromagnetic field and pesticides: Impact on the rate of disappearance of azoxystrobin and λ-cyhalothrin and the structure of some functional groups of the probabilistic molecules.

The purpose of these laboratory tests was to assess the impact of 50 Hz EMF (electromagnetic field) on the disappearance of azoxystrobin (active ingredient (AI) of Amistar 250 SC) and λ-cyhalothrin (AI of Karate Zeon 050 CS) in the body of honey bees (Apis mellifera) and the structure of some functional groups of the probabilistic molecules in their organisms. Amistar 250 SC (an azoxystrobin-based fungicide; ABF) and Karate Zeon 050 CS (a λ-cyhalothrin-based insecticide; CBI) are plant protection products (PPPs) applied to bee-pollinated-crops. Chromatographic methods were used to assess the rate of AI disappearance. EMF affected the rate of disappearance of azoxystrobin and λ-cyhalothrin in bees within 6 h of intoxication. When these substances were used separately their disappearance in the presence of EMF slowed from 12.6% to 10.5% h-1 and from 9.2% to 4.8% h-1, respectively, and accelerated when used in a mixture, from 14.1% to 14.7% h-1 and from 9.3% to 11.5% h-1 respectively. Fourier Transform Infrared (FTIR) spectroscopy was used to analyze changes in the functional groups of the probabilistic molecules of the tested bees. To obtain the information about the spectra variations we used the Principal Component Analysis. It has been shown, that EMF statistically significantly interferes with amide I and II, symmetric PO32- group from DNA, RNA and phospholipids vibrations. It also increased the number of changes of functional groups of the probabilistic molecules caused by ABF, but at the same time limited the changes in the functional groups studied in bees treated with CBI and a mixture containing both of them. In addition, exposure to EMF in bees treated with fungicide or insecticide, separately, and with both preparations caused differences (p < 0.05) in the secondary structure of proteins compared to controls. The obtained results indicate that EMF may affect the rate of metabolism and the detoxification process of pesticides in bees, depending on the AI of PPPs, applied individually or together. However, further detailed research is required to explain the mechanism of EMF as a detoxification modulator.

Fancy-Shaped Gold-Platinum Nanocauliflowers for Improved Proton Irradiation Effect on Colon Cancer Cells.

Enhancing the effectiveness of colorectal cancer treatment is highly desirable. Radiation-based anticancer therapy-such as proton therapy (PT)-can be used to shrink tumors before subsequent surgical intervention; therefore, improving the effectiveness of this treatment is crucial. The addition of noble metal nanoparticles (NPs), acting as radiosensitizers, increases the PT therapeutic effect. Thus, in this paper, the effect of novel, gold-platinum nanocauliflowers (AuPt NCs) on PT efficiency is determined. For this purpose, crystalline, 66-nm fancy shaped, bimetallic AuPt NCs were synthesized using green chemistry method. Then, physicochemical characterization of the obtained AuPt NCs by transmission electron microscopy (TEM), selected area electron diffraction (SAED), energy dispersive X-ray spectroscopy (EDS), and UV-Vis spectra measurements was carried out. Fully characterized AuPt NCs were placed into a cell culture of colon cancer cell lines (HCT116, SW480, and SW620) and a normal colon cell line (FHC) and subsequently subjected to proton irradiation with a total dose of 15 Gy. The 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium (MTS) test, performed after 18-h incubation of the irradiated cell culture with AuPt NCs, showed a significant reduction in cancer cell viability compared to normal cells. Thus, the radio-enhancing features of AuPt NCs indicate their potential application for the improvement in effectiveness of anticancer proton therapy.

Simultaneous FTIR and Raman Spectroscopy in Endometrial Atypical Hyperplasia and Cancer.

Currently, endometrial carcinoma (EC) is the most common genital cancer in high-income countries. Some types of endometrial hyperplasia (EH) may be progressing to this malignancy. The diagnosis of EC and EH is based on time consuming histopathology evaluation, which is subjective and causes discrepancies in reassessment. Therefore, there is a need to create methods of objective evaluation allowing the diagnosis of early changes. The study aimed to simultaneously asses Fourier Transform Infrared (FTIR) and Raman spectroscopy combined with multidimensional analysis to identify the tissues of endometrial cancer, atypical hyperplasia and the normal control group, and differentiate them. The results of FTIR and Raman spectroscopy revealed quantitative and qualitative changes in the nucleic acid and protein in the groups of cancer and atypical hyperplasia, in comparison with the control group. Changes in the lipid region were also observed in Raman spectra. Pearson correlation coefficient demonstrated a statistically significant correlation between Raman spectra for the cancer and atypical hyperplasia groups (0.747, p < 0.05) and for atypical hyperplasia and the controls (0.507, p < 0.05), while FTIR spectra demonstrated a statistically significant positive correlation for the same group as in Raman data and for the control and cancer groups (0.966, p < 0.05). To summarize, the method of spectroscopy enables differentiation of atypical hyperplasia and endometrial cancer tissues from the physiological endometrial tissue.

Gold Nanopeanuts as Prospective Support for Cisplatin in Glioblastoma Nano-Chemo-Radiotherapy.

Herein, we propose newly designed and synthesized gold nanopeanuts (Au NPes) as supports for cisplatin (cPt) immobilization, dedicated to combined glioblastoma nano-chemo-radiotherapy. Au NPes offer a large active surface, which can be used for drugs immobilization. Transmission electron microscopy (TEM) revealed that the size of the synthesized Au NPes along the longitudinal axis is ~60 nm, while along the transverse axis ~20 nm. Raman, thermogravimetric analysis (TGA) and differential scanning calorimetry (DCS) measurements showed, that the created nanosystem is stable up to a temperature of 110 °C. MTT assay revealed, that the highest cell mortality was observed for cell lines subjected to nano-chemo-radiotherapy (20-55%). Hence, Au NPes with immobilized cPt (cPt@AuNPes) are a promising nanosystem to improve the therapeutic efficiency of combined nano-chemo-radiotherapy.

Similarities in the General Chemical Composition of Colon Cancer Cells and Their Microvesicles Investigated by Spectroscopic Methods-Potential Clinical Relevance.

Colon cancer constitutes 33% of all cancer cases in humans and the majority of patients with metastatic colon cancer still have poor prognosis. An important role in cancer development is the communication between cancer and normal cells. This may occur, among others, through extracellular vesicles (including microvesicles) (MVs), which are being released by both types of cells. MVs may regulate a diverse range of biological processes and are considered as useful cancer biomarkers. Herein, we show that similarity in the general chemical composition between colon cancer cells and their corresponding tumor-derived microvesicles (TMVs) does exist. These results have been confirmed by spectroscopic methods for four colon cancer cell lines: HCT116, LoVo, SW480, and SW620 differing in their aggressiveness/metastatic potential. Our results show that Raman and Fourier Transform InfraRed (FTIR) analysis of the cell lines and their corresponding TMVs did not differ significantly in the characterization of their chemical composition. However, hierarchical cluster analysis of the data obtained by both of the methods revealed that only Raman spectroscopy provides results that are in line with the molecular classification of colon cancer, thus having potential clinical relevance.

The Spectroscopic Similarity between Breast Cancer Tissues and Lymph Nodes Obtained from Patients with and without Recurrence: A Preliminary Study.

Lymph nodes (LNs) play a very important role in the spread of cancer cells. Moreover, it was noticed that the morphology and chemical composition of the LNs change in the course of cancer development. Therefore, finding and monitoring similarities between these characteristics of the LNs and tumor tissues are essential to improve diagnostics and therapy of this dreadful disease. In the present study, we used Raman and Fourier transform infrared (FTIR) spectroscopies to compare the chemical composition of the breast cancer tissues and LNs collected from women without (I group-4 patients) and with (II group-4 patients) recurrence. It was shown that the similarity of the chemical composition of the breast tissues and LNs is typical for the II group of the patients. The average Raman spectrum of the breast cancer tissues from the I group was not characterized by vibrations in the 800-1000 cm-1 region originating from collagen and carbohydrates, which are typical for tumor-affected breast tissues. At the same time, this spectrum contains peaks at 1029 cm-1, corresponding to PO2- from DNA, RNA and phospholipids, and 1520 cm-1, which have been observed in normal breast tissues before. It was shown that Raman bands of the average LN spectrum of the II group associated with proteins and carbohydrates are more intensive than those of the breast tissues spectrum. The intensity of the Raman spectra collected from the samples of the II group is almost three times higher compared to the I group. The vibrations of carbohydrates and amide III are much more intensive in the II group's case. The Raman spectra of the breast cancer tissues and LNs of the II group's samples do not contain bands (e.g., 1520 cm-1) found in the Raman spectra of the normal breast tissues elsewhere. FTIR spectra of the LNs of the I group's women showed a lower level of vibrations corresponding to functional group building nucleic acid, collagen, carbohydrates, and proteins in comparison with the breast cancer tissues. Pearson's correlation test showed positive and more significant interplay between the nature of the breast tissues and LN spectra obtained for the II group of patients than that in the I group's spectra. Moreover, principal component analysis (PCA) showed that it is possible to distinguish Raman and FTIR spectra of the breast cancer tissues and LNs collected from women without recurrence of the disease.

Control of Arms of Au Stars Size and its Dependent Cytotoxicity and Photosensitizer Effects in Photothermal Anticancer Therapy.

Gold nanostars (AuS NPs) are a very attractive nanomaterial, which is characterized by high effective transduction of the electromagnetic radiation into heat energy. Therefore, AuS NPs can be used as photosensitizers in photothermal therapy (PTT). However, understanding the photothermal conversion efficiency in nanostars is very important to select the most appropriate shape and size of AuS NPs. Therefore, in this article, the synthesis of AuS NPs with different lengths of star arms for potential application in PTT was investigated. Moreover, the formation mechanism of these AuS NPs depending on the reducer concentration is proposed. Transmission electron microscopy (TEM) with selected area diffraction (SEAD) and X-ray diffraction (X-Ray) showed that all the obtained AuS NPs are crystalline and have cores with similar values of the diagonal (parameter d), from 140 nm to 146 nm. However, the widths of the star arm edges (parameter c) and the lengths of the arms (parameter a) vary between 3.75 nm and 193 nm for AuS1 NPs to 6.25 nm and 356 nm for AuS4 NPs. Ultraviolet-visible (UV-Vis) spectra revealed that, with increasing edge widths and lengths of the star arms, the surface plasmon resonance (SPR) peak is shifted to the higher wavelengths, from 640 nm for AuS1 NPs to 770 nm for AuS4 NPs. Moreover, the increase of temperature in the AuS NPs solutions as well as the values of calculated photothermal efficiency grew with the elongation of the star arms. The potential application of AuS NPs in the PTT showed that the highest decrease of viability, around 75%, of cells cultured with AuS NPs and irradiated by lasers was noticed for AuS4 NPs with the longest arms, while the smallest changes were visible for gold nanostars with the shortest arms. The present study shows that photothermal properties of AuS NPs depend on edge widths and lengths of the star arms and the values of photothermal efficiency are higher with the increase of the arm lengths, which is correlated with the reducer concentration.

FTIR and Raman Spectroscopy-Based Biochemical Profiling Reflects Genomic Diversity of Clinical Candida Isolates That May Be Useful for Diagnosis and Targeted Therapy of Candidiasis.

Despite the fact that Candida albicans is documented to be the main cause of human candidiasis, non-C. albicans Candida (NCAC) species, such as Candida glabrata and Candida tropicalis, are also suggested to be implicated in the etiopathogenesis of opportunistic fungal infections. As biology, epidemiology, pathogenicity, and antifungal resistance of NCAC species may be affected as a result of genomic diversity and plasticity, rapid and unambiguous identification of Candida species in clinical samples is essential for proper diagnosis and therapy. In the present study, 25 clinical isolates of C. albicans, C. glabrata, and C. tropicalis species were characterized in terms of their karyotype patterns, DNA content, and biochemical features. Fourier transform infrared (FTIR) spectra- and Raman spectra-based molecular fingerprints corresponded to the diversity of chromosomal traits and DNA levels that provided correct species identification. Moreover, Raman spectroscopy was documented to be useful for the evaluation of ergosterol content that may be associated with azole resistance. Taken together, we found that vibrational spectroscopy-based biochemical profiling reflects the variability of chromosome patterns and DNA content of clinical Candida species isolates and may facilitate the diagnosis and targeted therapy of candidiasis.

Predicting Ewing Sarcoma Treatment Outcome Using Infrared Spectroscopy and Machine Learning.

BACKGROUND: Improved outcome prediction is vital for the delivery of risk-adjusted, appropriate and effective care to paediatric patients with Ewing sarcoma-the second most common paediatric malignant bone tumour. Fourier transform infrared (FTIR) spectroscopy of tissues allows the bulk biochemical content of a biological sample to be probed and makes possible the study and diagnosis of disease. METHODS: In this retrospective study, FTIR spectra of sections of biopsy-obtained bone tissue were recorded. Twenty-seven patients (between 5 and 20 years of age) with newly diagnosed Ewing sarcoma of bone were included in this study. The prognostic value of FTIR spectra obtained from Ewing sarcoma (ES) tumours before and after neoadjuvant chemotherapy were analysed in combination with various data-reduction and machine learning approaches. RESULTS: Random forest and linear discriminant analysis supervised learning models were able to correctly predict patient mortality in 92% of cases using leave-one-out cross-validation. The best performing model for predicting patient relapse was a linear Support Vector Machine trained on the observed spectral changes as a result of chemotherapy treatment, which achieved 92% accuracy. CONCLUSION: FTIR spectra of tumour biopsy samples may predict treatment outcome in paediatric Ewing sarcoma patients with greater than 92% accuracy.

Identification of birch pollen species using FTIR spectroscopy.

In this study, the morphology and chemical composition of pollen grains of six birch species (Betula utilis Doorenbos, B. dahurica, B. maximowicziana, B. pendula, B. pubescens and B. humilis) were examined to verify which of these features allow distinguishing them in a more unambiguous way. For this purpose, scanning electron microscopy and light microscopy, as well as Fourier transform infrared (FTIR) spectroscopy and curve-fitting analysis of amide I profile, were performed. The microscopy images show that the pollen grains of B. pubescens, B. pendula and B. humilis are similar in diameter and significantly smaller than those of others species, with the largest diameter observed for B. utilis Doorenbos. However, the results obtained from FTIR spectroscopy indicate that the chemical compositions of B. pubescens and B. pendula are similar, but B. humilis is outlaying. Summarizing, it is not possible to unambiguously state, which feature or which technique is the best for differentiating between the six chosen birch species. However, the study showed that both techniques have potential for identification of birch pollen species.