Fundamentals and applications of Raman-based techniques for the design and development of active biomedical materials

Raman spectroscopy is an analytical method based on light–matter interactions that can interrogate the vibrational modes of matter and provide representative molecular fingerprints. Mediated by its label-free, non-invasive nature, and high molecular specificity, Raman-based techniques have become ubiquitous tools for in situ characterization of materials. This review comprehensively describes the theoretical and practical background of Raman spectroscopy and its advanced variants. The numerous facets of material characterization that Raman scattering can reveal, including biomolecular identification, solid-to-solid phase transitions, and spatial mapping of biomolecular species in bioactive materials, are highlighted. The review illustrates the potential of these techniques in the context of active biomedical material design and development by highlighting representative studies from the literature. These studies cover the use of Raman spectroscopy for the characterization of both natural and synthetic biomaterials, including engineered tissue constructs, biopolymer systems, ceramics, and nanoparticle formulations, among others. To increase the accessibility and adoption of these techniques, the present review also provides the reader with practical recommendations on the integration of Raman techniques into the experimental laboratory toolbox. Finally, perspectives on how recent developments in plasmon- and coherently-enhanced Raman spectroscopy can propel Raman from underutilized to critical for biomaterial development are provided

Towards enhanced optical sensor performance:SEIRA and SERS with plasmonic nanostars

We report the preparation and characterization of plasmonic chip-based systems comprising self-assembled gold nanostars at silicon substrates that enable concomitantly enhanced Raman (surface enhanced Raman spectroscopy; SERS) and mid-infrared (surface enhanced infrared reflection or absorption spectroscopy; SEIRA) spectral signatures. The high-aspect-ratio structure of gold nanostars provides an increased number of hot spots at their surface, which results in an electric field enhancement around the nanomaterial. Gold nanostars were immobilized at a silicon substrate via a thin gold layer, and α-ω-dimercapto polyethylene glycol (SH-PEG-SH) linkers. The Raman and IR spectra of crystal violet (CV) revealed a noticeable enhancement of the analyte vibrational signal intensity in SERS and SEIRA studies resulting from the presence of the nanostars. Enhancement factors of 2.5 × 10 3 and 2.3 × 10 3 were calculated in SERS considering the CV bands at 1374.9 cm -1 and 1181 cm -1 , respectively; for SEIRA, an enhancement factor of 5.36 was achieved considering the CV band at 1585 cm -1

Monte Carlo simulation of signals in digital diaphanoscopy of the maxillary sinuses

Digital diaphanoscopy method has potential to separate normal and pathological conditions of the maxillary sinuses. The entirety of all the features of the investigated area (the presence or absence of pathology, its etiology and morphological features) affects the resulting images of the maxillary sinuses by the digital diaphanoscopy. In this work, the MonteCarlo numerical simulation method was used to determine the patterns of propagation of light radiation in biological tissue. A biologically heterogeneous environment, represented by structures of the skull and maxillary sinuses, as well as pathological changes in them was modelled in the TracePro software

Optical Diagnostics of the Maxillary Sinuses by Digital Diaphanoscopy Technology

The work is devoted to the development of a scientific and technical basis for instrument implementation of a digital diaphanoscopy technology for the diagnosis of maxillary sinus inflammatory diseases taking into account the anatomical features of patients (differences in skin structure, skull bone thickness, and sinus size), the optical properties of exercised tissues, and the age and gender characteristics of patients. The technology is based on visualization and analysis of scattering patterns of low-intensity radiation as it passes through the maxillary sinuses. The article presents the experimental data obtained using the digital diaphanoscopy method and the results of numerical simulation of the optical radiation passage through the study area. The experimental setup has been modernized through the installation of a a device for controlling the LED applicator brightness. The approach proposed may have considerable promise for creating diagnostic criteria for various pathological changes and can be used to assess the differences in the optical and anatomical features of males and females

Array-based DNA methylation profiling of primary lymphomas of the central nervous system

<p>Abstract</p> <p>Background</p> <p>Although primary lymphomas of the central nervous system (PCNSL) and extracerebral diffuse large B-cell lymphoma (DLBCL) cannot be distinguished histologically, it is still a matter of debate whether PCNSL differ from systemic DLBCL with respect to their molecular features and pathogenesis. Analysis of the DNA methylation pattern might provide further data distinguishing these entities at a molecular level.</p> <p>Methods</p> <p>Using an array-based technology we have assessed the DNA methylation status of 1,505 individual CpG loci in five PCNSL and compared the results to DNA methylation profiles of 49 DLBCL and ten hematopoietic controls.</p> <p>Results</p> <p>We identified 194 genes differentially methylated between PCNSL and normal controls. Interestingly, Polycomb target genes and genes with promoters showing a high CpG content were significantly enriched in the group of genes hypermethylated in PCNSL. However, PCNSL and systemic DLBCL did not differ in their methylation pattern.</p> <p>Conclusions</p> <p>Based on the data presented here, PCNSL and DLBCL do not differ in their DNA methylation pattern. Thus, DNA methylation analysis does not support a separation of PCNSL and DLBCL into individual entities. However, PCNSL and DLBCL differ in their DNA methylation pattern from non- malignant controls.</p

Acquisition of biologically relevant gene expression data by Affymetrix microarray analysis of archival formalin-fixed paraffin-embedded tumours

Robust protocols for microarray gene expression profiling of archival formalin-fixed paraffin-embedded tissue (FFPET) are needed to facilitate research when availability of fresh-frozen tissue is limited. Recent reports attest to the feasibility of this approach, but the clinical value of these data is poorly understood. We employed state-of-the-art RNA extraction and Affymetrix microarray technology to examine 34 archival FFPET primary extremity soft tissue sarcomas. Nineteen arrays met stringent QC criteria and were used to model prognostic signatures for metastatic recurrence. Arrays from two paired frozen and FFPET samples were compared: although FFPET sensitivity was low (∼50%), high specificity (95%) and positive predictive value (92%) suggest that transcript detection is reliable. Good agreement between arrays and real time (RT)–PCR was confirmed, especially for abundant transcripts, and RT–PCR validated the regulation pattern for 19 of 24 candidate genes (overall R(2)=0.4662). RT–PCR and immunohistochemistry on independent cases validated prognostic significance for several genes including RECQL4, FRRS1, CFH and MET – whose combined expression carried greater prognostic value than tumour grade – and cmet and TRKB proteins. These molecules warrant further evaluation in larger series. Reliable clinically relevant data can be obtained from archival FFPET, but protocol amendments are needed to improve the sensitivity and broad application of this approach

A Tissue Biomarker Panel Predicting Systemic Progression after PSA Recurrence Post-Definitive Prostate Cancer Therapy

Many men develop a rising PSA after initial therapy for prostate cancer. While some of these men will develop a local or metastatic recurrence that warrants further therapy, others will have no evidence of disease progression. We hypothesized that an expression biomarker panel can predict which men with a rising PSA would benefit from further therapy.A case-control design was used to test the association of gene expression with outcome. Systemic (SYS) progression cases were men post-prostatectomy who developed systemic progression within 5 years after PSA recurrence. PSA progression controls were matched men post-prostatectomy with PSA recurrence but no evidence of clinical progression within 5 years. Using expression arrays optimized for paraffin-embedded tissue RNA, 1021 cancer-related genes were evaluated-including 570 genes implicated in prostate cancer progression. Genes from 8 previously reported marker panels were included. A systemic progression model containing 17 genes was developed. This model generated an AUC of 0.88 (95% CI: 0.84-0.92). Similar AUCs were generated using 3 previously reported panels. In secondary analyses, the model predicted the endpoints of prostate cancer death (in SYS cases) and systemic progression beyond 5 years (in PSA controls) with hazard ratios 2.5 and 4.7, respectively (log-rank p-values of 0.0007 and 0.0005). Genes mapped to 8q24 were significantly enriched in the model.Specific gene expression patterns are significantly associated with systemic progression after PSA recurrence. The measurement of gene expression pattern may be useful for determining which men may benefit from additional therapy after PSA recurrence

Targeted genome engineering via zinc finger nucleases

With the development of next-generation sequencing technology, ever-expanding databases of genetic information from various organisms are available to researchers. However, our ability to study the biological meaning of genetic information and to apply our genetic knowledge to produce genetically modified crops and animals is limited, largely due to the lack of molecular tools to manipulate genomes. Recently, targeted cleavage of the genome using engineered DNA scissors called zinc finger nucleases (ZFNs) has successfully supported the precise manipulation of genetic information in various cells, animals, and plants. In this review, we will discuss the development and applications of ZFN technology for genome engineering and highlight recent reports on its use in plants

Batch effect correction for genome-wide methylation data with Illumina Infinium platform

<p>Abstract</p> <p>Background</p> <p>Genome-wide methylation profiling has led to more comprehensive insights into gene regulation mechanisms and potential therapeutic targets. Illumina Human Methylation BeadChip is one of the most commonly used genome-wide methylation platforms. Similar to other microarray experiments, methylation data is susceptible to various technical artifacts, particularly batch effects. To date, little attention has been given to issues related to normalization and batch effect correction for this kind of data.</p> <p>Methods</p> <p>We evaluated three common normalization approaches and investigated their performance in batch effect removal using three datasets with different degrees of batch effects generated from HumanMethylation27 platform: quantile normalization at average β value (QNβ); two step quantile normalization at probe signals implemented in "lumi" package of R (lumi); and quantile normalization of A and B signal separately (ABnorm). Subsequent Empirical Bayes (EB) batch adjustment was also evaluated.</p> <p>Results</p> <p>Each normalization could remove a portion of batch effects and their effectiveness differed depending on the severity of batch effects in a dataset. For the dataset with minor batch effects (Dataset 1), normalization alone appeared adequate and "lumi" showed the best performance. However, all methods left substantial batch effects intact in the datasets with obvious batch effects and further correction was necessary. Without any correction, 50 and 66 percent of CpGs were associated with batch effects in Dataset 2 and 3, respectively. After QNβ, lumi or ABnorm, the number of CpGs associated with batch effects were reduced to 24, 32, and 26 percent for Dataset 2; and 37, 46, and 35 percent for Dataset 3, respectively. Additional EB correction effectively removed such remaining non-biological effects. More importantly, the two-step procedure almost tripled the numbers of CpGs associated with the outcome of interest for the two datasets.</p> <p>Conclusion</p> <p>Genome-wide methylation data from Infinium Methylation BeadChip can be susceptible to batch effects with profound impacts on downstream analyses and conclusions. Normalization can reduce part but not all batch effects. EB correction along with normalization is recommended for effective batch effect removal.</p

Identification of Type 1 Diabetes-Associated DNA Methylation Variable Positions That Precede Disease Diagnosis

Monozygotic (MZ) twin pair discordance for childhood-onset Type 1 Diabetes (T1D) is similar to 50%, implicating roles for genetic and non-genetic factors in the aetiology of this complex autoimmune disease. Although significant progress has been made in elucidating the genetics of T1D in recent years, the non-genetic component has remained poorly defined. We hypothesized that epigenetic variation could underlie some of the non-genetic component of T1D aetiology and, thus, performed an epigenome-wide association study (EWAS) for this disease. We generated genome-wide DNA methylation profiles of purified CD14(+) monocytes (an immune effector cell type relevant to T1D pathogenesis) from 15 T1D-discordant MZ twin pairs. This identified 132 different CpG sites at which the direction of the intra-MZ pair DNA methylation difference significantly correlated with the diabetic state, i.e. T1D-associated methylation variable positions (T1D-MVPs). We confirmed these T1D-MVPs display statistically significant intra-MZ pair DNA methylation differences in the expected direction in an independent set of T1D-discordant MZ pairs (P = 0.035). Then, to establish the temporal origins of the T1D-MVPs, we generated two further genome-wide datasets and established that, when compared with controls, T1D-MVPs are enriched in singletons both before (P = 0.001) and at (P = 0.015) disease diagnosis, and also in singletons positive for diabetes-associated autoantibodies but disease-free even after 12 years follow-up (P = 0.0023). Combined, these results suggest that T1D-MVPs arise very early in the etiological process that leads to overt T1D. Our EWAS of T1D represents an important contribution toward understanding the etiological role of epigenetic variation in type 1 diabetes, and it is also the first systematic analysis of the temporal origins of disease-associated epigenetic variation for any human complex disease