Evaluating the effectiveness of whole blood plasma versus protein precipitates in ovarian cancer detection through infrared spectroscopy

Early diagnosis of ovarian cancer remains challenging due to the absence of effective screening tests. The success of treatment and 5 year survival rates are significantly reliant on identifying the disease at a non-advanced stage, which highlights the urgent need for novel early detection and diagnostic approaches. Blood-based spectroscopic techniques, combined with chemometrics, have the potential to be used as tools for screening and diagnostic purposes in this context. In this study, we utilised attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy to analyse blood plasma samples from benign (n = 15) and ovarian cancer (n = 15) cases. We conducted multivariate discrimination models to compare the results in terms of sensitivity, specificity, and diagnostic accuracy when using either plasmatic protein precipitates or whole plasma to distinguish between benign and ovarian cancer. Notably, diagnostic accuracy values of 96% (sensitivity and specificity of 96%) and 92% (sensitivity and specificity of 88% and 96%, respectively) were achieved for the protein precipitates and whole plasma datasets respectively using genetic algorithms with linear and quadratic discriminant analysis. Furthermore, this methodology demonstrated its capability to categorise samples within the ovarian cancer class, distinguishing between early stage (FIGO I) and advanced stage (FIGO II-III), with excellent accuracy exceeding 97% for protein precipitate dataset. These findings highlight the utilisation of a specific class of biomolecules in a proteomic-like approach based on infrared spectroscopy and chemometrics for detecting ovarian cancer using blood plasma samples.

Application of spectrochemical analysis with chemometrics to profile biochemical alterations in nanoplastic-exposed HepG2 cells

Humans are routinely exposed to nanoplastics (NPs) in various ways, and this exposure presents a significant health risk. Nevertheless, there remain gaps in our knowledge, particularly in the mechanisms of toxicity of NPs with different surface charges at very low environmental concentrations. Herein, a spectrochemical approach was used to profile the cytotoxicity of NPs with different surface charges in HepG2 cells. It was found that all three NPs can cause some biomolecular alterations in cells, affecting cellular lipids, proteins, amino acids, and genetic material. Of these, PS and PS-COOH led to a non-linear dose-response, which may be related to a biphasic dose-response, whereas PS-NH2 led to a linear dose-response with a gradual increase in toxicity with increasing exposure concentration. In addition, the spectroscopic results showed that surface modifications led to cellular biochemical changes and caused adverse biological effects, with PS-NH2 exhibiting higher toxicity compared to PS or PS-COOH along with an inhibition of cell proliferation. Surprisingly PS-COOH, although considered the least toxic NP, appears to cause DNA damage. Overall, the toxic effects of different surface-modified NPs in cells were detected for the first time by applying spectrochemical techniques, and these findings provide important data towards understanding the emerging widespread environmental pollution of NPs and their effects on humans.

Monitoring and modelling the dynamics of the cellular glycolysis pathway: A review and future perspectives

BACKGROUND

The dynamics of the cellular glycolysis pathway underpin cellular function and dysfunction, and therefore ultimately health, disease, diagnostic and therapeutic strategies. Evolving our understanding of this fundamental process and its dynamics remains critical.

SCOPE OF REVIEW

This paper reviews the medical relevance of glycolytic pathway in depth and explores the current state of the art for monitoring and modelling the dynamics of the process. The future perspectives of label free, vibrational microspectroscopic techniques to overcome the limitations of the current approaches are considered.

MAJOR CONCLUSIONS

Vibrational microspectroscopic techniques can potentially operate in the niche area of limitations of other omics technologies for non-destructive, real-time, in vivo label-free monitoring of glycolysis dynamics at a cellular and subcellular level.

In situ identification of environmental microorganisms with Raman spectroscopy

Microorganisms in natural environments are crucial in maintaining the material and energy cycle and the ecological balance of the environment. However, it is challenging to delineate environmental microbes' actual metabolic pathways and intraspecific heterogeneity because most microorganisms cannot be cultivated. Raman spectroscopy is a culture-independent technique that can collect molecular vibration profiles from cells. It can reveal the physiological and biochemical information at the single-cell level rapidly and non-destructively in situ. The first part of this review introduces the principles, advantages, progress, and analytical methods of Raman spectroscopy applied in environmental microbiology. The second part summarizes the applications of Raman spectroscopy combined with stable isotope probing (SIP), fluorescence in situ hybridization (FISH), Raman-activated cell sorting and genomic sequencing, and machine learning in microbiological studies. Finally, this review discusses expectations of Raman spectroscopy and future advances to be made in identifying microorganisms, especially for uncultured microorganisms.

Density functional study of trans,trans,trans-[Pt(N3)2(OH)2(Py)2] on molecular structure and vibrational spectroscopy

This study records the selection of the best combination of geometric optimization and frequency calculation methods of the trans,trans,trans-[Pt(N₃)₂(OH)₂(py)₂](FM-190) by using different density functional calculation methods and basis sets. The results show that the CAM-B3LYP/SDD method has the best fit to the experimental data for geometric optimization, while the LSDA/SDD method has better performance in frequency calculation, and the infrared vibration peak is assigned. In addition, the calculated HOMO and LUMO show the energy gap and the internal charge transfer of this complex. The hyperconjugation of the pyridine ring have been explained by NBO analysis.

New targeted approaches for epigenetic age predictions

Background

Age-associated DNA methylation changes provide a promising biomarker for the aging process. While genome-wide DNA methylation profiles enable robust age-predictors by integration of many age-associated CG dinucleotides (CpGs), there are various alternative approaches for targeted measurements at specific CpGs that better support standardized and cost-effective high-throughput analysis.

Results

In this study, we utilized 4647 Illumina BeadChip profiles of blood to select CpG sites that facilitate reliable age-predictions based on pyrosequencing. We demonstrate that the precision of DNA methylation measurements can be further increased with droplet digital PCR (ddPCR). In comparison, bisulfite barcoded amplicon sequencing (BBA-seq) gave slightly lower correlation between chronological age and DNA methylation at individual CpGs, while the age-predictions were overall relatively accurate. Furthermore, BBA-seq data revealed that the correlation of methylation levels with age at neighboring CpG sites follows a bell-shaped curve, often associated with a CTCF binding site. We demonstrate that within individual BBA-seq reads the DNA methylation at neighboring CpGs is not coherently modified, but reveals a stochastic pattern. Based on this, we have developed a new approach for epigenetic age predictions based on the binary sequel of methylated and non-methylated sites in individual reads, which reflects heterogeneity in epigenetic aging within a sample.

Conclusion

Targeted DNA methylation analysis at few age-associated CpGs by pyrosequencing, BBA-seq, and particularly ddPCR enables high precision of epigenetic age-predictions. Furthermore, we demonstrate that the stochastic evolution of age-associated DNA methylation patterns in BBA-seq data enables epigenetic clocks for individual DNA strands.

Establishing spectrochemical changes in the natural history of oesophageal adenocarcinoma from tissue Raman mapping analysis

Raman spectroscopy is a fast and sensitive technique able to identify molecular changes in biological specimens. Herein, we report on three cases where Raman microspectroscopy was used to distinguish normal vs. oesophageal adenocarcinoma (OAC) (case 1) and Barrett’s oesophagus vs. OAC (cases 2 and 3) in a non-destructive and highly accurate fashion. Normal and OAC tissues were discriminated using principal component analysis plus linear discriminant analysis (PCA-LDA) with 97% accuracy (94% sensitivity and 100% specificity) (case 1); Barrett’s oesophagus vs. OAC tissues were discriminated with accuracies ranging from 98 to 100% (97–100% sensitivity and 100% specificity). Spectral markers responsible for class differentiation were obtained through the difference-between-mean spectrum for each group and the PCA loadings, where C–O–C skeletal mode in β-glucose (900 cm⁻¹), lipids (967 cm⁻¹), phosphodioxy (1296 cm⁻¹), deoxyribose (1456 cm⁻¹) and collagen (1445, 1665 cm⁻¹) were associated with normal and OAC tissue differences. Phenylalanine (1003 cm⁻¹), proline/collagen (1066, 1445 cm⁻¹), phospholipids (1130 cm⁻¹), CH₂ angular deformation (1295 cm⁻¹), disaccharides (1462 cm⁻¹) and proteins (amide I, 1672/5 cm⁻¹) were associated with Barrett’s oesophagus and OAC tissue differences. These findings show the potential of using Raman microspectroscopy imaging for fast and accurate diagnoses of oesophageal pathologies and establishing subtle molecular changes predisposing to adenocarcinoma in a clinical setting.

Graphical abstract

Feature engineering applied to intraoperative in vivo Raman spectroscopy sheds light on molecular processes in brain cancer: a retrospective study of 65 patients

Raman spectroscopy is a promising tool for neurosurgical guidance and cancer research. Quantitative analysis of the Raman signal from living tissues is, however, limited. Their molecular composition is convoluted and influenced by clinical factors, and access to data is limited. To ensure acceptance of this technology by clinicians and cancer scientists, we need to adapt the analytical methods to more closely model the Raman-generating process. Our objective is to use feature engineering to develop a new representation for spectral data specifically tailored for brain diagnosis that improves interpretability of the Raman signal while retaining enough information to accurately predict tissue content. The method consists of band fitting of Raman bands which consistently appear in the brain Raman literature, and the generation of new features representing the pairwise interaction between bands and the interaction between bands and patient age. Our technique was applied to a dataset of 547 in situ Raman spectra from 65 patients undergoing glioma resection. It showed superior predictive capacities to a principal component analysis dimensionality reduction. After analysis through a Bayesian framework, we were able to identify the oncogenic processes that characterize glioma: increased nucleic acid content, overexpression of type IV collagen and shift in the primary metabolic engine. Our results demonstrate how this mathematical transformation of the Raman signal allows the first biological, statistically robust analysis of in vivo Raman spectra from brain tissue.

Fourier Transform Infrared Spectroscopy as a Cancer Screening and Diagnostic Tool: A Review and Prospects

Infrared spectroscopy has long been used to characterize chemical compounds, but the applicability of this technique to the analysis of biological materials containing highly complex chemical components is arguable. However, recent advances in the development of infrared spectroscopy have significantly enhanced the capacity of this technique in analyzing various types of biological specimens. Consequently, there is an increased number of studies investigating the application of infrared spectroscopy in screening and diagnosis of various diseases. The lack of highly sensitive and specific methods for early detection of cancer has warranted the search for novel approaches. Being more simple, rapid, accurate, inexpensive, non-destructive and suitable for automation compared to existing screening, diagnosis, management and monitoring methods, Fourier transform infrared spectroscopy can potentially improve clinical decision-making and patient outcomes by detecting biochemical changes in cancer patients at the molecular level. Besides the commonly analyzed blood and tissue samples, extracellular vesicle-based method has been gaining popularity as a non-invasive approach. Therefore, infrared spectroscopic analysis of extracellular vesicles could be a useful technique in the future for biomedical applications. In this review, we discuss the potential clinical applications of Fourier transform infrared spectroscopic analysis using various types of biological materials for cancer. Additionally, the rationale and advantages of using extracellular vesicles in the spectroscopic analysis for cancer diagnostics are discussed. Furthermore, we highlight the challenges and future directions of clinical translation of the technique for cancer.

Vibrational Spectroscopy Fingerprinting in Medicine: from Molecular to Clinical Practice

In the last two decades, Fourier Transform Infrared (FTIR) and Raman spectroscopies turn out to be valuable tools, capable of providing fingerprint-type information on the composition and structural conformation of specific molecular species. Vibrational spectroscopy's multiple features, namely highly sensitive to changes at the molecular level, noninvasive, nondestructive, reagent-free, and waste-free analysis, illustrate the potential in biomedical field. In light of this, the current work features recent data and major trends in spectroscopic analyses going from in vivo measurements up to ex vivo extracted and processed materials. The ability to offer insights into the structural variations underpinning pathogenesis of diseases could provide a platform for disease diagnosis and therapy effectiveness evaluation as a future standard clinical tool.

Biomedical optical spectroscopy for the early diagnosis of gastrointestinal neoplasms

Gastrointestinal cancer is a leading contributor to cancer-related morbidity and mortality worldwide. Early diagnosis currently plays a key role in the prognosis of patients with gastrointestinal cancer. Despite the advances in endoscopy over the last decades, missing lesions, undersampling and incorrect sampling in biopsies, as well as invasion still result in a poor diagnostic rate of early gastrointestinal cancers. Accordingly, there is a pressing need to develop non-invasive methods for the early detection of gastrointestinal cancers. Biomedical optical spectroscopy, including infrared spectroscopy, Raman spectroscopy, diffuse scattering spectroscopy and autofluorescence, is capable of providing structural and chemical information about biological specimens with the advantages of non-destruction, non-invasion and reagent-free and waste-free analysis and has thus been widely investigated for the diagnosis of oesophageal, gastric and colorectal cancers. This review will introduce the advances of biomedical optical spectroscopy techniques, highlight their applications for the early detection of gastrointestinal cancers and discuss their limitations.

Airway remodeling: Systems biology approach, from bench to bedside

Airway Remodeling, a patho-physiologic process, is considered as a key feature of chronic airway diseases. In recent years, our understanding of the complex diseases has increased significantly by the use of combined approaches, including systems biology, which may contribute to the development of personalized and predictive medicine approaches. Integrative analysis, along with the cooperation of clinicians, computer scientists, research scientists, and bench scientists, has become an important part of the experimental design and therapeutic strategies in the era of omics. The airway remodeling process is the result of the dysregulation of several signaling pathways that modulate the airway regeneration; therefore, high-throughput experiments and systems biology approach can help to understand this process better. The study reviews related literature and is consistent with the existing clinical evidence.

FTIR Spectroscopic and Molecular Analysis during Differentiation of Pluripotent Stem Cells to Pancreatic Cells

Some of the greatest challenges in stem cells (SCs) biology and regenerative medicine are differentiation control of SCs and ensuring the purity of differentiated cells. In this work, we differentiated mouse pluripotent stem cells (mPSCs) toward pancreatic cells characterizing this differentiation process by molecular and spectroscopic technics. Both mPSCs and Differentiated Pancreatic Cells (DPCs) were subjected to a genetic, phenotypic, and biochemical analysis by real-time quantitative PCR (RT-qPCR), immunocytochemistry, and Fourier Transform Infrared (FTIR) spectroscopy. Cultured mPCSs expressed pluripotent genes and proteins (Nanog and SOX2). DPCs expressed endodermal genes (SOX17 and Pdx1) at day 11, an inductor gene of embryonic pancreas development (Pdx1) at day 17 and pancreas genes and proteins (Insulin and Glucagon) at day 21 of differentiation. Likewise, FTIR spectra of mPSCs and DPCs at different maturation stages (11, 17, and 21 days) were obtained and showed absorption bands related with different types of biomolecules. These FTIR spectra exhibited significant spectral changes agreeing with the differentiation process, particularly in proteins and nucleic acids bands. In conclusion, the obtained DPCs passed through the chronological stages of embryonic pancreas development and FTIR spectra provide a new biophysical parameter based on molecular markers indicating the differentiation process of mPSCs to specialized cells.

ATR-FTIR and multivariate analysis as a screening tool for cervical cancer in women from northeast Brazil: a biospectroscopic approach

Cervical cancer is the fourth most frequent cancer in women worldwide and the third in Brazil.