Microscopic FTIR studies of lung cancer cells in pleural fluid

Rapid serotype-independent differential detection of biofilm-positive and biofilm-negative Salmonella using Fourier transform infrared biotyping

Foodborne illnesses caused by Salmonella represent a global one health challenge, with biofilm-forming strains exhibiting enhanced public health risks due to their ability to persist due to resistance to antimicrobial agents, disinfectants, and environmental stresses. While food-safety and public health investigation primarily focus on Salmonella identification and source tracing, they often overlook the biofilm-forming capacity of isolates, limiting their predictive value for risks posed by biofilm producing Salmonella. This study assessed fourier transform infrared (FTIR) biotyping for rapid serotype-independent differentiatial detection of biofilm-positive (BFP) from biofilm-negative (BFN) Salmonella. A total of 270 Salmonella strains representing 12 common serotypes were classified using three conventional biofilm assays (congo red and coomassie brilliant blue agar test, calcofluor test, and tube test) into true BFP (n = 80), true BFN (n = 64), and uncertain (n = 59) biofilm producers. Biofilm production for each group was also assessed with a microtiter plate assay. FTIR biotyping was applied to a subset of 115 strains (61 BFP, 54 BFN). Using spectral windows of 1180-1050 cm-1 and 1400-1200 cm-1, FTIR biotyping accurately differentiated BFP from BFN strains with 93.4 % sensitivity, 83.3 % specificity, and 88.6 % overall accuracy. FTIR biotyping differentiated 59 strains with uncertain biofilm status into BFN (n = 45) and BFP (n = 14). FTIR biotyping provides a rapid, sensitive and specific method for detection of biofilm-forming Salmonella strains. Incorporating FTIR biotyping for biofilm detection in current Salmonella surveillance and source-tracing protocols can enhance food safety risk assessments and improve Salmonella outbreak prevention.

Full fingerprint hyperspectral imaging of prostate cancer tissue microarrays within clinical timeframes using quantum cascade laser microscopy

One of the major limitations for clinical applications of infrared spectroscopic imaging modalities is the acquisition time required to obtain reasonable images of tissues with high spatial resolution and good signal-to-noise ratio (SNR). The time to acquire a reasonable signal to noise spectroscopic scan of a standard microscope slide region of tissue can take many hours. As a trade-off, systems can allow for discrete wavenumber acquisitions, sacrificing potentially vital chemical bands in order to reach specific acquisition targets. Recent instrumentation developments now allow for the full fingerprint imaging of entire microscope slides in under 30 minutes, enabling rapid, high quality spectroscopic imaging of tissues within clinical timeframes without sacrificing frequency bands. Here we compare the data from a novel QCL microscope to an FTIR microscope covering multiple aspects of spectroscopic imaging of a large, clinically relevant, prostate cancer tissue cohort (N = 1281). Comparisons of hyperspectral data acquisition quality in both achieved signal to noise and image contrast alongside the capacity for unsupervised and supervised modelling of tissue constituents are reported. We conclude that it is now possible to collect full fingerprint spectra and derive clinically relevant data in a timeframe suitable for translation into the pathology laboratory without the need to resort to discrete frequency imaging with subsequent loss of information.

Structural diversity of Alzheimer-related protein aggregations revealed using photothermal ratio-metric micro-spectroscopy

The crucial link between pathological protein aggregations and lipids in Alzheimer's disease pathogenesis is increasingly recognized, yet its spatial dynamics remain challenging for labeling-based microscopy. Here, we demonstrate photothermal ratio-metric infrared spectro-microscopy (PRISM) to investigate the in situ structural and molecular compositions of pathological features in brain tissues at submicron resolution. By identifying the vibrational spectroscopic signatures of protein secondary structures and lipids, PRISM tracks the structural dynamics of pathological proteins, including amyloid and hyperphosphorylated Tau (pTau). Amyloid-associated lipid features in major brain regions were observed, notably the enrichment of lipid-dissociated plaques in the hippocampus. Spectroscopic profiling of pTau revealed significant heterogeneity in phosphorylation levels and a distinct lipid-pTau relationship that contrasts with the anticipated lipid-plaque correlation. Beyond in vitro studies, our findings provide direct visualization evidence of aggregate-lipid interactions across the brain, offering new insights into mechanistic and therapeutic research of neurodegenerative diseases.

Exploring the antiviral activities of the FDA-approved drug sulfadoxine and its derivatives against Chikungunya virus

BACKGROUND

Currently, there is no antiviral licensed to treat chikungunya fever, a disease caused by the infection with Alphavirus chikungunya (CHIKV). Treatment is based on analgesic and anti-inflammatory drugs to relieve symptoms. Our study aimed to evaluate the antiviral activity of sulfadoxine (SFX), an FDA-approved drug, and its derivatives complexed with silver(I) (AgSFX), salicylaldehyde Schiff base (SFX-SL), and with both Ag and SL (AgSFX-SL) against CHIKV.

METHODS

The anti-CHIKV activity of SFX and its derivatives was investigated using BHK-21 cells infected with CHIKV-nanoluc, a marker virus-carrying nanoluciferase reporter. Dose-response and time of drug-addition assays were performed in order to assess the antiviral effects of the compounds, as well as in silico data and ATR-FTIR analysis for insights on their mechanisms of action.

RESULTS

The SFX inhibited 34% of CHIKV replication, while AgSFX, SFX-SL, and AgSFX-SL enhanced anti-CHIKV activity to 84%, 89%, and 95%, respectively. AgSFX, SFX-SL, and AgSFX-SL significantly decreased viral entry and post-entry to host cells, and the latter also protected cells against infection. Additionally, molecular docking calculations and ATR-FTIR analysis demonstrated interactions of SFX-SL, AgSFX, and AgSFX-SL with CHIKV.

CONCLUSIONS

Collectively, our findings suggest that the addition of metal ions and/or Schiff base to SFX improved its antiviral activity against CHIKV.

Antilisterial effect of alkyl polyglycosides biosurfactant and modes of action

Several outbreaks of Listeria monocytogenes originated mainly from contaminated contact surfaces. Thus, this study investigated the antilisterial effect of natural surfactants in terms of their use as a 2-in-1 sanitizing washer on a food contact surface and evaluated their modes of action. The antilisterial activity of alkyl polyglycosides (APGs), namely capryl glucoside (CA), coco glucoside (CG), and decyl glucoside (DG), was evaluated based on the minimum inhibitory concentration (MIC) and the minimum bactericidal concentration (MBC) using broth dilution assay. The results showed that CG had the strongest antilisterial activity. Therefore, CG was selected for further investigation. The time-kill assay showed a lethal effect of 0.5 % (w/w) CG by inactivating 4 Log reduction (99.99 %) of L. monocytogenes within 3 s. Furthermore, 1 % (w/w) CG with slight mechanical force in washing (by shaking) was efficient for sanitizing a stainless-steel coupon surface based on its ability to cause a total reduction of deposited L. monocytogenes (99.9 %) within 10 min. Scanning electron microscopy and applying Fourier-transform infrared spectroscopy revealed that CG chemically disrupted the cell wall and plasma membrane of L. monocytogenes within 5 min after a gentle wash. The results showed it had potent antimicrobial activity and was bactericidal against L. monocytogenes. Overall, our results supported the use of CG as a natural antibacterial surfactant to alter the chemical sanitizer and the possibility of its practical use in the food industry and for household use.

IR-EcoSpectra: Exploring sustainable ex situ and in situ FTIR applications for green chemical and pharmaceutical analysis

In various industries, particularly in the chemical and pharmaceutical fields, Fourier transform infrared spectroscopy (FTIR) spectroscopy provides a unique capacity to detect and characterise complex chemicals while minimising environmental damage by minimal waste generation and reducing the need for extensive sample preparation or use of harmful reagents. This review showcases the versatility of ex situ and in situ FTIR applications for substance identification, analysis, and dynamic monitoring. Ex situ FTIR spectroscopy's accuracy in identifying impurities, monitoring crystallisation processes, and regulating medication release patterns improves product quality, safety, and efficacy. Furthermore, its quantification capabilities enable more effective drug development, dosage procedures, and quality control practices, all of which are consistent with green analytical principles. On the other hand, in situ FTIR spectroscopy appears to be a novel tool for the real-time investigation of molecular changes during reactions and processes, allowing for the monitoring of drug release kinetics, crystallisation dynamics, and surface contacts, as well as providing vital insights into material behaviour. The combination of ex situ FTIR precision and in situ FTIR dynamic capabilities gives a comprehensive analytical framework for developing green practices, quality control, and innovation in the chemical and pharmaceutical industries. This review presents the wide range of applications of ex situ and in situ FTIR spectroscopy in chemical, pharmaceutical and medical fields as an analytical green chemistry tool. However, further study is required to fully realise FTIR's potential and develop new applications that improve sustainability in these areas.

Turning Portunus pelagicus Shells into Biocompatible Scaffolds for Bone Regeneration

Bone tissue engineering (BTE) provides an alternative for addressing bone defects by integrating cells, a scaffold, and bioactive growth factors to stimulate tissue regeneration and repair, resulting in effective bioengineered tissue. This study focuses on repurposing chitosan from blue swimming crab (Portunus pelagicus) shell waste as a composite scaffold combined with HAP and COL I to improve biocompatibility, porosity, swelling, and mechanical properties. The composite scaffold demonstrated nearly 60% porosity with diameters ranging from 100-200 μm with an interconnected network that structurally mimics the extracellular matrix. The swelling ratio of the scaffold was measured at 208.43 ± 14.05%, 248.93 ± 4.32%, 280.01 ± 1.26%, 305.44 ± 20.71%, and 310.03 ± 17.94% at 1, 3, 6, 12, and 24 h, respectively. Thus, the Portunus pelagicus scaffold showed significantly lower degradation ratios of 5.64 ± 1.89%, 14.34 ± 8.59%, 19.57 ± 14.23%, and 29.13 ± 9.87% for 1 to 4 weeks, respectively. The scaffold supports osteoblast attachment and proliferation for 7 days. Waste from Portunus pelagicus shells has emerged as a prospective source of chitosan with potential application in tissue engineering.

Attenuated Total Reflection Fourier-Transform Infrared Spectral Discrimination in Human Tissue of Oesophageal Transformation to Adenocarcinoma

This study presents ATR-FTIR (attenuated total reflectance Fourier-transform infrared) spectral analysis of ex vivo oesophageal tissue including all classifications to oesophageal adenocarcinoma (OAC). The article adds further validation to previous human tissue studies identifying the potential for ATR-FTIR spectroscopy in differentiating among all classes of oesophageal transformation to OAC. Tissue spectral analysis used principal component analysis quadratic discriminant analysis (PCA-QDA), successive projection algorithm quadratic discriminant analysis (SPA-QDA), and genetic algorithm quadratic discriminant analysis (GA-QDA) algorithms for variable selection and classification. The variables selected by SPA-QDA and GA-QDA discriminated tissue samples from Barrett's oesophagus (BO) to OAC with 100% accuracy on the basis of unique spectral "fingerprints" of their biochemical composition. Accuracy test results including sensitivity and specificity were determined. The best results were obtained with PCA-QDA, where tissues ranging from normal to OAC were correctly classified with 90.9% overall accuracy (71.4-100% sensitivity and 89.5-100% specificity), including the discrimination between normal and inflammatory tissue, which failed in SPA-QDA and GA-QDA. All the models revealed excellent results for distinguishing among BO, low-grade dysplasia (LGD), high-grade dysplasia (HGD), and OAC tissues (100% sensitivities and specificities). This study highlights the need for further work identifying potential biochemical markers using ATR-FTIR in tissue that could be utilised as an adjunct to histopathological diagnosis for early detection of neoplastic changes in susceptible epithelium.

Bioactivation of an orthodontic wire using multifunctional nanomaterials to prevent plaque accumulation

Controlling the growth of biofilm on orthodontic material has become a difficult challenge in modern dentistry. The antibacterial efficacy of currently used orthodontic material becomes limited due to the higher affinity of oral microbial flora for plaque formation on the material surface. Thus it is crutial to device an efficient strategy to prevent plaque buildup caused by pathogenic microbiota. In this work, we have fabricated a bioactive orthodontic wire using titanium nanoparticles (TiO₂NPs) and silver nanoparticles (AgNPs). AgNPs were synthesized from the extracts of Ocimum sanctum, Ocimum tenuiflorum, Solanum surattense, and Syzygium aromaticum, while the TiO₂NPs were synthesized by the Sol-Gel method. The nanoparticles were characterized by various biophysical techniques. The surface of the dental wire was molded by functionalizing these AgNPs followed by an additional coating of TiO₂NPs. Functionalized dental wires were found to counteract the formation of tenacious intraoral biofilm, and showed an enhanced anti-bacterial effect against Multi-Drug Resistant (MDR) bacteria isolated from patients with various dental ailments. Data revealed that such surface coating counteracts the bacterial pathogens by inducing the leakage of Ag ions which eventually disrupts the cell membrane as confirmed from TEM micrographs. The results offer a significant opportunity for innovations in developing nanoparticle-based formulations to modify or fabricate an effective orthodontic material.

Breast cancer early detection by using Fourier-transform infrared spectroscopy combined with different classification algorithms

Early detection of breast cancer is of great value in improving the prognosis. The current detection methods of breast cancer have their own limitations. In this study, we investigated the feasibility of Fourier Transform Infrared (FT-IR) spectroscopy combined with different classification algorithms for the early detection of breast cancer in a large sample of 526 patients, including 308 invasive breast cancer, 101 ductal carcinoma in situ, and 117 healthy controls. The serum was measured with FT-IR spectroscopy. Kennard-Stone (KS) algorithm was used to divide the data into the training set and testing set. Support vector machine (SVM) model and back propagation neural network (BPNN) model were used to distinguish ductal carcinoma in situ, invasive breast cancer from healthy controls. The accuracies of the SVM model and BPNN model were 92.9% and 94.2%. To determine the effect of different material absorption bands on early detection, the band was divided into four parts including 900-1425 cm^-1, 1475-1710 cm^-1, 2800-3000 cm^-1, and 3090-3700 cm^-1, to be modeled and detected respectively. The final results showed that the ranges 900-1425 cm^-1 and 1475-1710 cm^-1 had superior classification accuracies. The region 900-1425 cm^-1 corresponded to the lipids, proteins, sugar, and nucleic acids, and the region 1475-1710 cm^-1 corresponded to the proteins. The biochemical substances in other bands also contributed some unique potential to the classification, so the classification accuracy was the best in the full band. The study indicates that serum FT-IR spectroscopy combined with SVM and BPNN models is an effective tool for the early detection of breast cancer.

Rapid diagnosis of malignant pleural mesothelioma and its discrimination from lung cancer and benign exudative effusions using blood serum

Malignant pleural mesothelioma (MPM), an aggressive cancer associated with exposure to fibrous minerals, can only be diagnosed in the advanced stage because its early symptoms are also connected with other respiratory diseases. Hence, understanding the molecular mechanism and the discrimination of MPM from other lung diseases at an early stage is important to apply effective treatment strategies and for the increase in survival rate. This study aims to develop a new approach for characterization and diagnosis of MPM among lung diseases from serum by Fourier transform infrared spectroscopy (FTIR) coupled with multivariate analysis. The detailed spectral characterization studies indicated the changes in lipid biosynthesis and nucleic acids levels in the malignant serum samples. Furthermore, the results showed that healthy, benign exudative effusion, lung cancer, and MPM groups were successfully separated from each other by applying principal component analysis (PCA), support vector machine (SVM), and especially linear discriminant analysis (LDA) to infrared spectra.

Artificial neural network in the discrimination of lung cancer based on infrared spectroscopy

Given the increasing prevalence of lung cancer worldwide, an auxiliary diagnostic method is needed alongside the microscopic examination of biopsy samples, which is dependent on the skills and experience of pathologists. Thus, this study aimed to advance lung cancer diagnosis by developing five (5) artificial neural network (NN) models that can discriminate malignant from benign samples based on infrared spectral data of lung tumors (n = 122; 56 malignant, 66 benign). NNs were benchmarked with classical machine learning (CML) models. Stratified 10-fold cross-validation was performed to evaluate the NN models, and the performance metrics-area under the curve (AUC), accuracy (ACC) positive predictive value (PPV), negative predictive value (NPV), specificity rate (SR), and recall rate (RR)-were averaged for comparison. All NNs were able to outperform the CML models, however, support vector machine is relatively comparable to NNs. Among the NNs, CNN performed best with an AUC of 92.28% ± 7.36%, ACC of 98.45% ± 1.72%, PPV of 96.62% ± 2.30%, NPV of 90.50% ± 11.92%, SR of 96.01% ± 3.09%, and RR of 89.21% ± 12.93%. In conclusion, NNs can be potentially used as a computational tool in lung cancer diagnosis based on infrared spectroscopy of lung tissues.

Lung Cancer: Spectral and Numerical Differentiation among Benign and Malignant Pleural Effusions Based on the Surface-Enhanced Raman Spectroscopy

We present here that the surface-enhanced Raman spectroscopy (SERS) technique in conjunction with the partial least squares analysis is as a potential tool for the differentiation of pleural effusion in the course of the cancerous disease and a tool for faster diagnosis of lung cancer. Pleural effusion occurs mainly in cancer patients due to the spread of the tumor, usually caused by lung cancer. Furthermore, it can also be initiated by non-neoplastic diseases, such as chronic inflammatory infection (the most common reason for histopathological examination of the exudate). The correlation between pleural effusion induced by tumor and non-cancerous diseases were found using surface-enhanced Raman spectroscopy combined with principal component regression (PCR) and partial least squares (PLS) multivariate analysis method. The PCR predicts 96% variance for the division of neoplastic and non-neoplastic samples in 13 principal components while PLS 95% in only 10 factors. Similarly, when analyzing the SERS data to differentiate the type of tumor (squamous cell vs. adenocarcinoma), PLS gives more satisfactory results. This is evidenced by the calculated values of the root mean square errors of calibration and prediction but also the coefficients of calibration determination and prediction (R2C = 0.9570 and R2C = 0.7968), which are more robust and rugged compared to those calculated for PCR. In addition, the relationship between cancerous and non-cancerous samples in the dependence on the gender of the studied patients is presented.

Protective role of AKBA against benzo(a)pyrene-induced lung carcinogenesis by modulating biotransformation enzymes and oxidative stress

The present study was designed to explore the chemopreventive potential of 3-acetyl-11-keto-β-boswellic acid (AKBA) during the initiation and promotion stage of lung carcinogenesis induced by benzo(a)pyrene (BaP) in female Sprague Dawley rats. BaP was administered at a dose level of 50 mg/kg b.wt. twice a week orally in olive oil for 4 weeks. AKBA administration was started 4 weeks before BaP treatment and continued for another 8 weeks at a dose level of 50 mg/kg b.wt. orally in olive oil three times a week. BaP treatment showed significantly increased in the activities of Phase I biotransformation enzymes (Cytochrome P₄₅₀ , b₅ , and aryl hydrocarbon hydrolase) and inhibited the activity of Phase II enzyme (glutathione-S-transferase). Also, a significant elevation in oxidative stress biomarkers lipid peroxidation, reactive oxygen species, and protein carbonyl content concentration. Further, an appreciable decrease was observed in the activities of endogenous antioxidant enzymes superoxide dismutase, CAT, GPx, GR, and a decline in nonenzymatic GSH levels. As a result of BaP induced oxidative stress, alteration in erythrocytes morphology was observed. Fourier transform infrared spectroscopy spectrum of lung tissue showed structural changes due to BaP exposure. Moreover, levels of tumor biomarkers such as total sialic acid, carcinoembryonic antigen, and alkaline phosphatase were significantly elevated following BaP treatment which was substantiated by alterations noticed in the histoarchitecture of lung tissue. Interestingly, AKBA administration to BaP treated rats appreciably alleviated the changes inflicted by BaP on various biochemical indices and histoarchitecture of lungs. Therefore, the study clearly revealed that AKBA by containing oxidative stress shall prove to be quite effective in providing chemoprevention against BaP induced lung carcinogenesis.

Insight into metastatic oral cancer tissue from novel analyses using FTIR spectroscopy and aperture IR-SNOM

A novel machine learning algorithm is shown to accurately discriminate between oral squamous cell carcinoma (OSCC) nodal metastases and surrounding lymphoid tissue on the basis of a single metric, the ratio of Fourier transform infrared (FTIR) absorption intensities at 1252 cm-1 and 1285 cm-1. The metric yields discriminating sensitivities, specificities and precision of 98.8 ± 0.1%, 99.89 ± 0.01% and 99.78 ± 0.02% respectively, and an area under receiver operator characteristic (AUC) of 0.9935 ± 0.0006. The delineation of the OSCC and lymphoid tissue revealed by the image formed from the metric is in better agreement with an immunohistochemistry (IHC) stained image than are either of the FTIR images obtained at the individual wavenumbers. Scanning near-field optical microscopy (SNOM) images of the tissue obtained at a number of key wavenumbers, with high spatial resolution, show variations in the chemical structure of the tissue with a feature size down to ∼4 μm. The image formed from the ratio of the SNOM images obtained at 1252 cm-1 and 1285 cm-1 shows more contrast than the SNOM images obtained at these or a number of other individual wavenumbers. The discrimination between the two tissue types is dominated by the contribution from the 1252 cm-1 signal, which is representative of nucleic acids, and this shows the OSCC tissue to be accompanied by two wide arcs of tissue which are particularly low in nucleic acids. Haematoxylin and eosin (H&E) staining shows the tumour core in this specimen to be ∼40 μm wide and the SNOM topography shows that the core centre is raised by ∼1 μm compared to the surrounding tissue. Line profiles of the SNOM signal intensity taken through the highly keratinised core show that the increase in height correlates with an increase in the protein signal. SNOM line profiles show that the nucleic acids signal decreases at the centre of the tumour core between two peaks of higher intensity. All these nucleic acid features are ∼25 μm wide, roughly the width of two cancer cells.

FTIR based approach to study EnaC mechanosensory functions

The pulmonary epithelial sodium ion channel (ENaC) is gaining importance for its sodium gating and mechanosensitive roles. The mechano functional studies on ENaC suggest direct molecular interactions between the ENaC protein with cytoskeleton microtubules and other extracellular matrix components. Also, in few mechanotransduction studies, ENaC was shown to respond both to membrane stretch as well as cell volume changes. However, the conformational characteristic of ENaC during sodium and mechano gating are yet to be fully elucidated. Thus obtaining ENaC protein conformational spectrum based on Fourier Transform Infrared Radiation (FTIR) spectroscopy in solution will be useful in predicting the nature of conformational changes occurring during any cell volume changes in an epithelial cell. The conformational spectrum looks promising in studying the disease biology of cystic fibrosis (CF) and CF like conditions that arise due to abnormal ion conductance membrane proteins and subsequent frequent fluid retentions. This review article presents the basics of epithelial ENaC protein as a gated mechanosensor and FTIR for developing fluid dynamics of ENaC protein. This can be applied to develop an ENaC based quantum mechanosensor for the prognosis as well as diagnosis of cystic fibrosis (CF) and allied lung diseases.

Arecanut-induced fibrosis display dual phases of reorganising glycans and amides in skin extracellular matrix

The habit of chewing arecanut leads to fibrosis in the oral tissues, which can lead to cancer. Despite high mortality, fibrosis has limited clinical success owing to organ-specific variations, genetic predispositions, and slow progression. Fibrosis is a progressive condition that is unresponsive to medications in the severe phase. To understand underlying macromolecular changes we studied the extracellular matrix's (ECM) key molecular modifications in the early and late phase of arecanut-induced fibrosis in skin. To study the fibrosis, we topically applied arecanut extract on the mice skin. We observed that the matrix changes observe early and late phases based on ECM characteristics including the matrix proteins and the glycans. A spike in the levels of proteoglycans and β-sheet structures are noted in the early phase. A significant drop in the proteoglycans and strengthening of amide covalent interactions is observed in the late phase. Although, almost no physical changes are noticeable only in the early phase; the late phase observes thick collagen bundling and a 4-fold stiffening of the skin tissue. The study indicates that the temporal interplay of proteins and glycans determine the matrix's severity state while opening avenues to research directed towards the phase-specific clinical discovery.

Raman spectroscopy of human skin for kidney failure detection

The object of this paper is in vivo study of skin spectral-characteristics in patients with kidney failure by conventional Raman spectroscopy in near infrared region. The experimental dataset was subjected to discriminant analysis with the projection on latent structures (PLS-DA). Application of Raman spectroscopy to investigate the forearm skin in 85 adult patients with kidney failure (90 spectra) and 40 healthy adult volunteers (80 spectra) has yielded the accuracy of 0.96, sensitivity of 0.94 and specificity of 0.99 in terms of identifying the target subjects with kidney failure. The autofluorescence analysis in the near infrared region identified the patients with kidney failure among healthy volunteers of the same age group with specificity, sensitivity, and accuracy of 0.91, 0.84, and 0.88, respectively. When classifying subjects by the presence of kidney failure using the PLS-DA method, the most informative Raman spectral bands are 1315 to 1330, 1450 to 1460, 1700 to 1800 cm^-1 . In general, the performed study demonstrates that for in vivo skin analysis, the conventional Raman spectroscopy can provide the basis for cost-effective and accurate detection of kidney failure and associated metabolic changes in the skin.

Differential regulation and the underlying mechanisms of clay minerals to Escherichia coli under the stress of polymyxin B: Comparing halloysite with kaolinite

The reuse of polymyxin B (PMB) has attracted extensive attention. Although the resistance mechanism to PMB is clear, there are few reports on the regulation mechanisms and effects of clay minerals on bacteria induced by PMB. The focus of this study is to investigate the multidrug resistance, cell morphology and physiological modification of Escherichia coli (E. coli) exposed to PMB in the presence and absence of clay minerals. To be specific, E. coli was cultured serially for 15 days in the increasing concentration of PMB, with or without halloysite or kaolinite. The potential influence mechanisms of halloysite and kaolinite on E. coli was analyzed by proteomics, antibiotic resistance testing, confocal laser scanning microscopy, scanning electron microscopy and Fourier transform infrared. The results showed that kaolinite could obviously promote the growth of bacteria. Moreover, compared with halloysite, kaolinite could stimulate the overexpression of PMB resistance-related proteins ArnA, ArnB and EptA in E. coli exposed to PMB, and promote the synthesis of peptidoglycan and activate glycolysis pathway to produce energy. In contrast, halloysite was able to regulate the production of low molecular weight thiols by E. coli to prevent bacteria from producing excessive reactive oxygen species, activate the oxidative phosphorylation pathway to supply energy for bacterial life activities, and reduce multidrug resistance of E. coli in a variety of ways. These findings are essential for exploring the impacts of clay minerals on the emergence and spread of multi-drug resistant strains in the environment.

Investigation of molecular mechanisms of experimental compounds in murine models of chronic allergic airways disease using synchrotron Fourier-transform infrared microspectroscopy

The ovalbumin-induced (OVA) chronic allergic airways murine model is a well-established model for investigating pre-clinical therapies for chronic allergic airways diseases, such as asthma. Here, we examined the effects of several experimental compounds with potential anti-asthmatic effects including resveratrol (RV), relaxin (RLN), l-sulforaphane (LSF), valproic acid (VPA), and trichostatin A (TSA) using both a prevention and reversal model of chronic allergic airways disease. We undertook a novel analytical approach using focal plane array (FPA) and synchrotron Fourier-transform infrared (S-FTIR) microspectroscopic techniques to provide new insights into the mechanisms of action of these experimental compounds. Apart from the typical biological effects, S-FTIR microspectroscopy was able to detect changes in nucleic acids and protein acetylation. Further, we validated the reduction in collagen deposition induced by each experimental compound evaluated. Although this has previously been observed with conventional histological methods, the S-FTIR technique has the advantage of allowing identification of the type of collagen present. More generally, our findings highlight the potential utility of S-FTIR and FPA-FTIR imaging techniques in enabling a better mechanistic understanding of novel asthma therapeutics.

Differentiating Between Malignant Mesothelioma and Other Pleural Lesions Using Fourier Transform Infrared Spectroscopy

Histopathology, despite being the gold standard as a diagnostic tool, does not always provide a correct diagnosis for different pleural lesions. Although great progress was made in this field, the problem to differentiate between reactive and malignant pleural lesions still stimulates the search for additional diagnostic tools. Our research using vibrational spectroscopy and principal component analysis (PCA) statistical modeling represents a potentially useful tool to approach the problem. The objective method this paper explores is based on the correlation between different types of pleural lesions and their vibrational spectra. Obtained tissue spectra recorded by infrared spectroscopy allowed us to categorize spectra in different groups using a created PCA statistical model. The PCA model was built using tissues of known pathology as the model group. The validation samples were then used to confirm the functionality of our PCA model. Student's t-test was also used for comparing samples in paired groups. The PCA model was able to clearly differentiate the spectra of mesothelioma, metastasis and reactive changes (inflammation), and place them in discrete groups. Thus, we showed that Fourier transform infrared spectroscopy combined with PCA can differentiate pleural lesions with high sensitivity and specificity. This new approach could contribute in objectively differentiating specific pleural lesions, thus helping pathologists to better diagnose difficult pleural samples but also could shed additional light into the biology of malignant pleural mesothelioma.

The use of Fourier-transform infrared spectroscopy to characterize connective tissue components in skeletal muscle of Atlantic cod (Gadus morhua L.)

In the present study, Fourier-transform infrared spectroscopy (FTIR) is investigated as a method to measure connective tissue components that are important for the quality of Atlantic cod filets (Gadus morhua L.). The Atlantic cod used in this study originated from a feeding trial, which found that fish fed a high starch diet contained relative more collagen type I, while fish fed a low starch (LS) diet contained relative more glycosaminoglycans (GAGs) in the connective tissue. FTIR spectra of pure commercial collagen type I and GAGs were acquired to identify spectral markers and compare them with FTIR spectra and images from connective tissue. Using principal component analysis, high and LS diets were separated due to collagen type I in the spectral region 1800 to 800 cm-1 . The spatial distribution of collagen type I and GAGs were further investigated by FTIR imaging in combination with immunohistochemistry. Pixel-wise correlation images were calculated between preprocessed connective tissue images and preprocessed pure components spectra of collagen type I and GAGs, respectively. For collagen, the FTIR images reveal a collagen distribution that closely resembles the collagen distribution as imaged by immunohistochemistry. For GAGs, the concentration is very low. Still, the FTIR images detect the most GAGs rich regions.

Fourier transform infrared spectroscopy based spectral biomarkers of metastasized breast cancer progression

Breast cancer is a global health issue and the second leading cause of cancer death in women. Breast cancer tends to migrate to bone and causes bone metastases which is ultimately the cause of death. Here, we report the use of FTIR to identify spectral biomarkers of cancer progression on 3D in vitro model of breast cancer bone metastasis. Our results indicate that the following spectral biomarkers can monitor cancer progression, for example, lipids (CH2 asymmetric/CH2 symmetric stretch), Amide I/Amide II, and RNA/DNA. Principal component analysis also confirmed the involvement of protein, lipids and nucleic acids in cancer progression on sequential culture. The collective observations from this study suggest successful application of FTIR as a non-invasive and accurate method to identify biochemical changes in cancer cells during the progression of breast cancer bone metastasis.

Optical probing of gastrocnemius in patients with peripheral artery disease characterizes myopathic biochemical alterations and correlates with stage of disease

Peripheral artery disease (PAD) is a condition caused by atherosclerotic blockages in the arteries supplying the lower limbs and is characterized by ischemia of the leg, progressive myopathy, and increased risk of limb loss. The affected leg muscles undergo significant changes of their biochemistry and metabolism including variations in the levels of many key proteins, lipids, and nucleotides. The mechanisms behind these changes are poorly understood. The objective of this study was to correlate the severity of the PAD disease stage and associated hemodynamic limitation (determined by the ankle brachial index, ABI) in the legs of the patients with alterations in the biochemistry of chronically ischemic leg muscle as determined by ATR‐Fourier transform infrared micro‐spectroscopy. Muscle (gastrocnemius) biopsies were collected from 13 subjects including four control patients (ABI≥0.9), five claudicating patients (0.4 ≤ ABI<0.9), and four critical limb ischemia (CLI) patients (ABI<0.4). Slide mounted specimens were analyzed by ATR‐Fourier transform infrared micro‐spectroscopy. An analysis of variance and a partial least squares regression model were used to identify significant differences in spectral peaks and correlate them with the ABI. The spectra revealed significant differences (P < 0.05) across control, claudicating, and CLI patients in the fingerprint and functional group regions. Infrared microspectroscopic probing of ischemic muscle biopsies demonstrates that PAD produces significant and unique changes to muscle biochemistry in comparison to control specimens. These distinctive biochemical profiles correlate with disease progression and may provide insight and direction for new targets in the diagnosis and therapy of muscle degeneration in PAD.

Effect of Drying Methods on Protein and DNA Conformation Changes in Lactobacillus rhamnosus GG Cells by Fourier Transform Infrared Spectroscopy

Microencapsulation protects cells against environmental stress encountered during the production of probiotics, which are used as live microbial food ingredients. Freeze-drying and spray-drying are used in the preparation of powdered microencapsulated probiotics. This study examines the ability of Fourier transform infrared (FTIR) spectroscopy to detect differences in cells exposed to freeze-drying and spray-drying of encapsulated Lactobacillus rhamnosus GG cells. The FTIR analysis clearly demonstrated there were more significant molecular changes in lipid, fatty acid content, protein, and DNA conformation of nonencapsulated compared to encapsulated bacterial cells. The technique was also able to differentiate between spray-dried and freeze-dried cells. The results also revealed the extent of protection from a protein-carbohydrate-based encapsulant matrix on the cells depending on the type drying process. The extent of this protection to the dehydration stress was shown to be less in spray-dried cells than in freeze-dried cells. This suggests that FTIR could be used as a rapid, noninvasive, and real-time measurement technique to detect detrimental drying effects on cells.

Application of ATR-FTIR Spectroscopy to Compare the Cell Materials of Wood Decay Fungi with Wood Mould Fungi

Wood fungi create vast damage among standing trees and all types of wood materials. The objectives of this study are to (a) characterize the cell materials of two major wood decay fungi (Basidiomycota), namely, Trametes versicolor and Postia placenta, and (b) compare the cell materials of decay fungi with four wood mould fungi (Ascomycota), namely, Aureobasidium pullulans, Alternaria alternata, Cladosporium cladosporioides, and Ulocladium atrum. Fourier transform infrared (FTIR) spectroscopy is used to characterize the microbial cellular materials. The results showed that the IR bands for the fatty acid at ∼2900 cm−1 were different for the two-decay-fungi genre. Postia placenta shows more absorbance peaks at the fatty acid region. Band ratio indices for amide I and amide II from protein amino acids were higher for the mould fungi (Ascomycota) than the decay fungi (Basidiomycota). Similarly, the band ratio index calculated for the protein end methyl group was found to be higher for the mould fungi than the decay fungi. Mould fungi along with the decay fungi demonstrated a positive correlation (R2=0.75) between amide I and amide II indices. The three-component multivariate, principal component analysis showed a strong correlation of amide and protein band indices.

The combination of artificial neural networks and synchrotron radiation-based infrared micro-spectroscopy for a study on the protein composition of human glial tumors

Protein-related changes associated with the development of human brain gliomas are of increasing interest in modern neuro-oncology.

Novel sensor technologies towards environmental health monitoring in urban environments: a case study in the Niger Delta (Nigeria)

The Niger Delta (Nigeria) is an exemplar of a legacy of environmental pollution. Limited knowledge on spatial and temporal pollutant distributions in the region highlights the need for biomonitoring approaches to study impacts on sentinel organisms. This study evaluated whether infrared (IR) spectroscopy and multivariate analysis could detect alterations in biomolecules in samples in differing exposure scenarios, i.e., spatial and temporal using African catfish (Heterobranchus bidorsalis) or water spinach (Ipomea aquatica). Significant spectral differences between tissues isolated from African catfish based on site or season were observed; in a region where fish appeared not to be present, water spinach was used as a surrogate sentinel organism. Using one-way ANOVA, the spectral categories were significant (P < 0.0001). The applicability of IR spectroscopy to detect subtle changes in target biological molecules within sentinel organisms along with its low-cost yet high-throughput potential suggests that biospectroscopy permits real-time evaluation of environmental exposure effects.

FTIR spectroscopic comparison of serum from lung cancer patients and healthy persons

The incidence and mortality of lung cancer remains so high that it is very urgent to develop an effective method for early detection of lung cancer. Serum can reflect physiological and pathological changes of human body, so FTIR spectroscopy was used to compare lung cancer patients' and healthy persons' serum in this study. The A1080/A1170 ratio might be potentially useful for distinguishing lung cancer patients' serum from healthy persons' serum. Moreover, the result of curve fitting indicated that the ratios of α-helix/antiparallel β-sheet were lower for lung cancer patients' serum than those for healthy persons' serum. These results indicated that IR spectra of serum might be potentially useful for detecting lung cancer.

Apoptotic pathways of U937 leukemic monocytes investigated by infrared microspectroscopy and flow cytometry

Infrared microspectroscopy and flow cytometry were used to study apoptosis in starved and CCCP-treated U937 monocyte cells.

Fourier transform infrared for noninvasive optical diagnosis of oral, oropharyngeal, and laryngeal cancer

The 5-year survival rate for advanced head and neck cancers is 50%. There is currently no noninvasive method or effective screening procedure available to diagnose head and neck cancer at the earliest stages when it is still highly curable. This study aims to show how Fourier transform infrared (FTIR) spectroscopy could be used as a sensitive, noninvasive, low cost technique to diagnose head and neck cancer at an earlier stage and, thus, increase the likelihood of survival. Sputum samples were collected from 16 cases with oral or oropharyngeal cancer, 8 cases with laryngeal cancer patients and 15 normal controls. Cell pellets were produced from each of these samples and used to generate FTIR spectra within the 'biochemical fingerprint' wavenumber region of 1800 to 950 cm(-1). Discrimination between cancer and normal sputum was achieved using infrared wavenumbers 1650 cm(-1), 1550 cm(-1), and 1042 cm(-1) determined by robust feature selection. These 3 wavenumbers were used to develop potential models to discriminate both oropharyngeal and laryngeal cancer from normal control. In cancer cases, the absorbance levels for 1550 cm(-1) were increased relative to controls, whereas 1042 cm(-1) absorbance was decreased suggesting changes to protein and glycoprotein structure within sputa cells. This preliminary study shows potential for how FTIR could be developed into a simplistic diagnostic tool that could easily be implemented by a nonspecialist to diagnose and monitor head and neck cancer. The method could especially provide a means for detecting laryngeal cancer hidden from noninvasive observation.

Novel biospectroscopy sensor technologies towards environmental health monitoring in urban environments

Biospectroscopy is an emerging inter-disciplinary field that exploits the application of sensor technologies [e.g., Fourier-transform infrared spectroscopy, Raman spectroscopy] to lend novel insights into biological questions. Methods involved are relatively non-destructive so samples can subsequently be analysed by more conventional approaches, facilitating deeper mechanistic insights. Fingerprint spectra are derived and these consist of wavenumber-absorbance intensities; within a typical biological experiment, a complex dataset is quickly generated. Biological samples range from biofluids to cytology to tissues derived from human or sentinel sources, and analyses can be carried out ex vivo or in situ in living tissue. A reference range of a designated normal state can be derived; anything outside this is potentially atypical and discriminating chemical entities identified. Computational approaches allow one to minimize within-category confounding factors. Because of ease of sample preparation, low-cost and high-throughput capability, biospectroscopy approaches herald a new greener means of environmental health monitoring in urban environments.

Detection of cancer using advanced computerized analysis of infrared spectra of peripheral blood

We have developed a novel approach for detection of cancer based on biochemical analysis of peripheral blood plasma using Fourier transform infrared spectroscopy. This approach has proven to be quick, safe, minimal invasive, and effective. Our approach recognizes any signs of solid tumor presence, regardless of location in the body or cancer type by measuring a spectrum that gives information regarding the total molecular composition and structure of the peripheral blood samples. The analysis includes clinically relevant preprocessing and feature extraction with principal component analysis, and uses Fisher's linear discriminant analysis to classify between cancer patients and healthy controls. We evaluated our method with leave-one-out cross validation and were able to establish sensitivity of 93.33%, specificity of 87.8%, and overall accuracy of 90.7%. Using our method for cancer detection should result in fewer unnecessary invasive procedures and yield fast detection of solid tumors.

Identification of colitis and cancer in colon biopsies by Fourier Transform Infrared spectroscopy and chemometrics

Cancer is a disease that does great harms to the health of human beings. FT-IR spectroscopy could identify variability at the molecular level in biological specimens. It is a rapid and noninvasive method, which could be used intraoperatively to modify surgical procedures. The aim of this paper is to identify and separate cancer from colitis in endoscopic colon biopsies through the use of FT-IR spectroscopy. A total of 88 endoscopic colon samples, including 41 cases of colitis and 47 cases of colon cancer, were obtained. Specimens were placed on an ATR accessory linked to FT-IR spectrometer with a MCT detector for greater stability and sensitivity. Later, specimens were sent for the histological examination as the reference in the spectral analysis. 41 colitis and 47 cancer specimens were compared. Spectra preprocessed with smoothing and normalization were used for discrimination analysis. PCA was processed to simplify the spectrum data set. Naive Bayes classifier model was constructed for diagnostic classification. Leave-one-out cross-validation method was utilized to assess the discrimination results. The sensitivity of FT-IR detection for cancer achieves 97.6%. The results showed that colon cancer could be distinguished from colitis with high accuracy using FT-IR spectroscopy and chemometrics.

Application of second derivative spectroscopy for increasing molecular specificity of Fourier transform infrared spectroscopic imaging of articular cartilage

OBJECTIVE

Fourier transform infrared (FT-IR) spectroscopic imaging is a promising method that enables the analysis of spatial distribution of biochemical components within histological sections. However, analysis of FT-IR spectroscopic data is complicated since absorption peaks often overlap with each other. Second derivative spectroscopy is a technique which enhances the separation of overlapping peaks. The objective of this study was to evaluate the specificity of the second derivative peaks for the main tissue components of articular cartilage (AC), i.e., collagen and proteoglycans (PGs).

MATERIALS AND METHODS

Histological bovine AC sections were measured before and after enzymatic removal of PGs. Both formalin-fixed sections (n = 10) and cryosections (n = 6) were investigated. Relative changes in the second derivative peak heights caused by the removal of PGs were calculated for both sample groups.

RESULTS

The results showed that numerous peaks, e.g., peaks located at 1202 cm(-1) and 1336 cm(-1), altered less than 5% in the experiment. These peaks were assumed to be specific for collagen. In contrast, two peaks located at 1064 cm(-1) and 1376 cm(-1) were seen to alter notably, approximately 50% or more. These peaks were regarded to be specific for PGs. The changes were greater in cryosections than formalin-fixed sections.

CONCLUSIONS

The results of this study suggest that the second derivative spectroscopy offers a practical and more specific method than routinely used absorption spectrum analysis methods to obtain compositional information on AC with FT-IR spectroscopic imaging.

Identification of fungal phytopathogens using Fourier transform infrared-attenuated total reflection spectroscopy and advanced statistical methods

The early diagnosis of phytopathogens is of a great importance; it could save large economical losses due to crops damaged by fungal diseases, and prevent unnecessary soil fumigation or the use of fungicides and bactericides and thus prevent considerable environmental pollution. In this study, 18 isolates of three different fungi genera were investigated; six isolates of Colletotrichum coccodes, six isolates of Verticillium dahliae and six isolates of Fusarium oxysporum. Our main goal was to differentiate these fungi samples on the level of isolates, based on their infrared absorption spectra obtained using the Fourier transform infrared-attenuated total reflection (FTIR-ATR) sampling technique. Advanced statistical and mathematical methods: principal component analysis (PCA), linear discriminant analysis (LDA), and k-means were applied to the spectra after manipulation. Our results showed significant spectral differences between the various fungi genera examined. The use of k-means enabled classification between the genera with a 94.5% accuracy, whereas the use of PCA [3 principal components (PCs)] and LDA has achieved a 99.7% success rate. However, on the level of isolates, the best differentiation results were obtained using PCA (9 PCs) and LDA for the lower wavenumber region (800-1775  cm(-1)), with identification success rates of 87%, 85.5%, and 94.5% for Colletotrichum, Fusarium, and Verticillium strains, respectively.

Detection and quantification of poliovirus infection using FTIR spectroscopy and cell culture

Background

In a globalized word, prevention of infectious diseases is a major challenge. Rapid detection of viable virus particles in water and other environmental samples is essential to public health risk assessment, homeland security and environmental protection. Current virus detection methods, especially assessing viral infectivity, are complex and time-consuming, making point-of-care detection a challenge. Faster, more sensitive, highly specific methods are needed to quantify potentially hazardous viral pathogens and to determine if suspected materials contain viable viral particles. Fourier transform infrared (FTIR) spectroscopy combined with cellular-based sensing, may offer a precise way to detect specific viruses. This approach utilizes infrared light to monitor changes in molecular components of cells by tracking changes in absorbance patterns produced following virus infection. In this work poliovirus (PV1) was used to evaluate the utility of FTIR spectroscopy with cell culture for rapid detection of infective virus particles.

Results

Buffalo green monkey kidney (BGMK) cells infected with different virus titers were studied at 1 - 12 hours post-infection (h.p.i.). A partial least squares (PLS) regression method was used to analyze and model cellular responses to different infection titers and times post-infection. The model performs best at 8 h.p.i., resulting in an estimated root mean square error of cross validation (RMSECV) of 17 plaque forming units (PFU)/ml when using low titers of infection of 10 and 100 PFU/ml. Higher titers, from 10³ to 10⁶ PFU/ml, could also be reliably detected.

Conclusions

This approach to poliovirus detection and quantification using FTIR spectroscopy and cell culture could potentially be extended to compare biochemical cell responses to infection with different viruses. This virus detection method could feasibly be adapted to an automated scheme for use in areas such as water safety monitoring and medical diagnostics.

Infrared spectral signatures of CDCP1-induced effects in colon carcinoma cells

Metastasis is the major cause of death by cancer. Indeed, metastatic colonies can reactivate and become life threatening, sometimes months or years after the initial diagnosis and surgery of the primary tumor. Therefore, there is a crucial need to develop methods for diagnosis of tumor cells that exhibit high metastatic potential. Here, we addressed the capability of vibrational spectroscopy for investigating the effects induced by CDCP1 expression in colon carcinoma cells. This transmembrane protein has been suggested to play a key role in metastasis by its pleiotropic function. We focused on a cellular model constituted by the cell lines SW480 and SW620 derived respectively from the primary tumor and a lymph node metastasis of the same patient. Induced CDCP1 expression in SW480 led to marked changes in cell morphology. Whereas SW480 form a cell layer, the SW480/CDCP1 cells exhibited reduced cell-to-cell contact. On collagen I, SW480 was more spread and filopodia were observed. In contrast, SW480/CDCP1 cells exhibited lower spreading with no formation of filopodia. Synchrotron Fourier transform infrared microspectroscopy experiments were performed on this cellular model. High quality spectroscopic information at sub-cellular resolution, provided by the use of the synchrotron source in infrared microspectroscopy, was recorded on numerous individual cells. Multivariate analysis of spectra recorded using principal component analysis indicated a highest intensity increase of the 970 and 1080 cm(-1) bands, and a modest intensity increase of the 1240 cm(-1) band in the SW480/CDCP1 cells. These bands were correlated with an increased content of phosphorylated proteins as confirmed by in situ labelling using a monoclonal antibody directed against phosphorylated tyrosines. Altogether, these results demonstrate that the vibrational technique used in this study exhibits the capability to characterize spectral signatures of CDCP1-induced effects in colon carcinoma cells. This study may open new avenues for rapid diagnosis of cells with a metastatic potential.

Determination of total phenolic content and antioxidant capacity of onion (Allium cepa) and shallot (Allium oschaninii) using infrared spectroscopy

Total phenolic content (TPC) and total antioxidant capacity (TAC) of four onion varieties (red, white, yellow and sweet) and shallot from selected locations (Washington, Idaho, Oregon, Texas and Georgia) were determined using Fourier transform infrared (FT-IR) spectroscopy (4000-400cm^-1). The Folin-Ciocalteu (F-C) assay was used to quantify TPC and three assays were used to determine TAC, including 2,2-diphenyl-picrylhydrazyl (DPPH) assay, Trolox equivalent antioxidant capacity (TEAC) assay and ferric reducing antioxidant power (FRAP) assay. Partial least squares regression (PLSR) with cross-validation (leave-one-out) was conducted on onion and shallot extracts (n=200) and their corresponding F-C, DPPH, TEAC and FRAP values were employed to obtain four independent calibration models for predicting TPC and TAC for the extracts. Spectra from an extra 19 independent extracts were used as an external validation set for prediction. A correlation of r>0.95 was obtained between FT-IR predicted and reference values (by F-C, DPPH, TEAC and FRAP assay) with standard errors of calibration (SEC) and standard errors of cross-validation (SECV) less than 2.85, 0.35 and 0.45μmolTrolox/g FW of extracts for TEAC, FRAP and DPPH assay, respectively; and 0.36mggallic acid/g FW of extracts for the F-C assay. In addition, cluster analysis (principal component analysis (PCA)) and discriminant function analysis (DFA) could differentiate varieties of onions and shallot based upon infrared spectral features. Loading plots for the various chemometrics models indicated that hydroxyl and phenolic functional groups were most closely correlated with antioxidant capacity. The use of mid-infrared spectroscopy to predict the total antioxidant capacity of vegetables provides a rapid and precise alternative to traditional wet chemistry analysis.

Evaluation of FTIR spectroscopy as a diagnostic tool for lung cancer using sputum

Background

Survival time for lung cancer is poor with over 90% of patients dying within five years of diagnosis primarily due to detection at late stage. The main objective of this study was to evaluate Fourier transform infrared spectroscopy (FTIR) as a high throughput and cost effective method for identifying biochemical changes in sputum as biomarkers for detection of lung cancer.

Methods

Sputum was collected from 25 lung cancer patients in the Medlung observational study and 25 healthy controls. FTIR spectra were generated from sputum cell pellets using infrared wavenumbers within the 1800 to 950 cm^-1 "fingerprint" region.

Results

A panel of 92 infrared wavenumbers had absorbances significantly different between cancer and normal sputum spectra and were associated with putative changes in protein, nucleic acid and glycogen levels in tumours. Five prominent significant wavenumbers at 964 cm^-1, 1024 cm^-1, 1411 cm^-1, 1577 cm^-1 and 1656 cm^-1 separated cancer spectra from normal spectra into two distinct groups using multivariate analysis (group 1: 100% cancer cases; group 2: 92% normal cases). Principal components analysis revealed that these wavenumbers were also able to distinguish lung cancer patients who had previously been diagnosed with breast cancer. No patterns of spectra groupings were associated with inflammation or other diseases of the airways.

Conclusions

Our results suggest that FTIR applied to sputum might have high sensitivity and specificity in diagnosing lung cancer with potential as a non-invasive, cost-effective and high-throughput method for screening.

Trial Registration

ClinicalTrials.gov: NCT00899262

Infrared spectroscopy characterization of normal and lung cancer cells originated from epithelium

The vibrational spectral differences of normal and lung cancer cells were studied for the development of effective cancer cell screening by means of attenuated total reflection infrared spectroscopy. The phosphate monoester symmetric stretching ν_s(PO₃^2-) band intensity at ~970 cm^-1 and the phosphodiester symmetric stretching ν_s(PO₂^-) band intensity at ~1,085 cm^-1 in nucleic acids and phospholipids appeared to be significantly strengthened in lung cancer cells with respect to the other vibrational bands compared to normal cells. This finding suggests that more extensive phosphorylation occur in cancer cells. These results demonstrate that lung cancer cells may be prescreened using infrared spectroscopy tools.