Search

Discoid lupus erythematosus (DLE) is the most common form of cutaneous lupus1. It can cause permanent scarring. The pathophysiology of is not fully understood. Plasmacytoid dendritic cells are found in close association with apoptotic keratinocytes inferring close cellular signalling. Matrix Associated Laser Desorption Ionisation (MALDI) combined with Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT-ICR-MS) is an exquisitely sensitive combination to examine disease processes at the cellular and molecular level. Active areas of discoid lupus erythematosus were compared with normal perilesional skin using MALDI combined with FT-ICR-MS. A unique set of biomarkers, including epidermal lipids is identified in active discoid lupus. These were assigned as sphingomyelins, phospholipids and ceramides. Additionally, increased levels of proteins from the keratin, and small proline rich family, and aromatic amino acids (tryptophan, phenylalanine, and tyrosine) in the epidermis are observed. These techniques, applied to punch biopsies of the skin, have shown a distinctive lipid profile of active discoid lupus. This profile may indicate specific lipid signalling pathways. Lipid rich microdomains (known as lipid rafts) are involved in cell signalling and lipid abnormalities have been described with systemic lupus erythematosus which correlate with disease activity. [ABSTRACT FROM AUTHOR]

Prostate cancer (PCa) is a significant healthcare problem worldwide. Current diagnosis and treatment methods are limited by a lack of precise in vivo tissue analysis methods. Real‐time cancer identification and grading could dramatically improve current protocols. Here, we report the testing of a thin optical probe using Raman spectroscopy (RS) and classification methods to detect and grade PCa accurately in real‐time. We present the first clinical trial on fresh ex vivo biopsy cores from an 84 patient cohort. Findings from 2395 spectra measured on 599 biopsy cores show high accuracy for diagnosing and grading PCa. We can detect clinically significant PCa from benign and clinically insignificant PCa with 90% sensitivity and 80.2% specificity. We also demonstrate the ability to differentiate cancer grades with 90% sensitivity and specificity ≥82.8%. This work demonstrates the utility of RS for real‐time PCa detection and grading during routine transrectal biopsy appointments. [ABSTRACT FROM AUTHOR]

Objective: Stress can play a role in the onset and exacerbation of psoriasis. Psychological interventions to reduce stress have been shown to improve psychological and psoriasis-related outcomes. This pilot randomised study investigated the feasibility of a brief interaction with a Paro robot to reduce stress and improve skin parameters, after a stressor, in patients with psoriasis. Methods: Around 25 patients with psoriasis participated in a laboratory stress task, before being randomised to either interact with a Paro robot or sit quietly (control condition) for 30 min. Raman spectroscopy and trans-epidermal water loss were measured at baseline, after the stressor and after the intervention as indexes of acute skin changes. Psychological variables, including self-reported stress and affect, were also measured at the three time-points. Results: No statistically significant differences between the two conditions were found for any of the outcomes measured. However, effect sizes suggest significance could be possible with a larger sample size. Changes in the psychological and Raman spectroscopy outcomes across the experimental session were found, indicating the feasibility of the procedures. Conclusion: This pilot study showed that a brief interaction with a Paro robot was a feasible intervention for patients with psoriasis, but future trials should broaden the inclusion criteria to try to increase recruitment rates. Studying people who are highly stressed, depressed or who are stress-responders may increase the power of the intervention to show effects using a longer-term intervention. [ABSTRACT FROM AUTHOR]

Bone strength in human cortical bone is determined by the composition and structure of both the mineral and collagen matrices and influenced by factors such as age, gender, health, lifestyle and genetic factors. Age-related changes in the bone matrix are known to result in loss of mechanical strength and increased fragility. In this study we show how Raman spectroscopy, with its exquisite sensitivity to the molecular structure of bone, reveals new insights into age- and sex-related differences. Raman analysis of 18 samples of cortical hip bone obtained from people aged between 47–82 years with osteoarthritis (OA) found subtle changes in the lipid and collagen secondary structure, and the carbonate (CO32−) and phosphate (PO43−) mineral ratios in the bone matrix. Significant differences were observed between older and younger bones, and between older female and older male bones; no significant differences were observed between younger male and female bones. Older female bones presented the lowest mineral to matrix ratios (MMR) and highest CO32−/PO43− ratios, and relative to lipid/collagen –CH2 deformation modes at 1450 cm−1 they had lowest overall mineral content, higher collagen cross linking and lipid content but lower levels of α-helix collagen structures than older male and younger male and female bones. These observations provided further insight on bone composition changes observed in the bone volume fraction (BV/TV) for the older female bones from microCT measurements on the same samples, while tissue mineral density (TMD) measurements had shown no significant differences between the samples. [ABSTRACT FROM AUTHOR]

In an era where phytoplankton-based technologies are expanding, optimization for rapid cellular growth detection and detailed biochemical characterization is key to enhancing productivity. Hence, the complex analysis and development of highly sensitive and rapid in-vivo methods for precise real-time molecular monitoring of phytoplankton cells is imperative. Herein, a multi-block spectroscopic based methodology for the identification and characterization of molecular changes occurring across different growth phases in the chlorophyte species, Tetraselmis suecica , is presented. Confocal Raman microscopy with near-infrared (NIR) excitation spectra and concurrent excitation-emission fluorescence matrix (EEM) measurements were taken at different intervals across a twenty-day cell growth cycle period encompassing three distinct growth phases (exponential, stationary and decline). Three different data fusion strategies were explored: low-level, mid-level and a mixed level with subsequent multi-block model building using the Common Components and Specific Weights Analysis (CCSWA) algorithm. Various pre-processing sequences in regard to the raw data and single-block exploratory methods were evaluated for all three strategies and selected based on the optimum computed salience contribution towards the multi-block global components within each model. A detailed characterization of the biochemical changes happening within cellular growth phases of the chlorophyte species was constructed. Additionally, the study establishes a novel paradigm for data manipulation within a multi-block framework for complex spectroscopic data of biological cells, such as phytoplankton. [Display omitted] • Multiblock analysis applied to spectroscopic data of growth phases in a chlorophyte. • Optimization of pre-processing and integration of Raman and EEM data blocks. • Changes in pigments across phytoplankton growth phases were identified. • Novel application of EEM-PARAFAC for phytoplankton characterization. • Biochemical and pigment changes across growth phases in a chlorophyte identified in- situ. [ABSTRACT FROM AUTHOR]