Optimal Choice of Sample Substrate and Laser Wavelength for Raman Spectroscopic Analysis of Biological Specimen

Raman spectroscopy is an optical technique based on the inelastic scattering of monochromatic light that can be used to identify the biomolecular composition of biological cells and tissues. It can be used as both an aid for understanding the etiology of disease and for accurate clinical diagnostics when combined with multivariate statistical algorithms. This method is nondestructive,potentially non-invasive and can be applied in vitro or in vivo directly or via a fiber optic probe. However, there exists a high degree of variability across experimental protocols, some of which result in large background signals that can often overpower the weak Raman signals being emitted. These protocols need to be standardised before the technique can provide reliable and reproducible experimental results in an everyday clinical environment. The objective of this study is to investigate the impact of different experimental parameters involved in the analysis of biological specimen. We investigate the Raman signals generated from healthy human cheek cells using different source laser wavelengths; 473 nm, 532 nm, 660 nm, 785 nm and 830 nm, and different sample substrates; Raman-grade calcium fluoride, IR polished calcium fluoride, magnesium fluoride, aluminium (100 nm and 1500 nm thin films on glass), glass, fused silica, potassium bromide, sodium chloride and zinc selenide, whilst maintaining all other experimental parameters constant throughout the study insofar as possible

Methodologies and considerations for bladder cancer detection with Raman based urine cytology

Bladder cancer has the highest recurrence rate of any cancer. The American Urological Association recommends cystoscopic surveillance every 3–6 months for 3 years, and at least once a year thereafter, particularly for high-risk patients; however, cystoscopy is invasive, expensive, and is not without insignificant morbidity for the patient. Urine cytology is often used as an adjunct to cystoscopy; however, it has a low sensitivity in detecting low grade bladder cancers. Recent studies have investigated the application of Raman micro-spectroscopy for the detection of bladder cancer via urine cytology, and it has been demonstrated to significantly improve the diagnostic sensitivity of urine cytology for low grade bladder cancer under ideal experimental conditions. In this paper we attempt to move Raman micro-spectroscopy a step closer to the clinic by systematically examining the potential of this technology to classify low and high grade bladder cancer cell lines under the stringent clinical conditions that can be expected in the standard pathology laboratory, in terms of consumables, protocols, and instrumentation. We show that the use of glass slides, traditional fixing agents, lengthy exposure to urine, red blood cell lysing agents, as well as common cell deposition methods, do not significantly impact on the diagnostic potential of Raman based urine cytology. This study suggests that urine samples prepared with the ThinPrep (R) UroCyte (TM) method and analysed with micro-Raman spectroscopy could provide a useful alternative to cystoscopy for long term bladder cancer surveillance

Self-perceived disease activity was the strongest predictor of COVID-19 pandemic-related concerns in young people with autoimmune rheumatic diseases, irrespective of their gender, with females reporting higher concerns

OBJECTIVE: We report the results of a pilot young patient survey that targeted patients with JSLE and JDM, exploring well-being, resilience and general concern about the coronavirus disease 2019 (COVID-19) pandemic as well as self-assessment of disease activity. METHODS: The survey was completed anonymously by patients who had been approached via the automatically generated hospital database between June and December 2020. In addition to disease characteristics, geographic location, education and employment level, we explored young patients’ resilience, mood and feelings, mental well-being, self-assessed disease activity and general COVID-19 concerns using validated tools and visual analogue scales. RESULTS: This pilot study found that self-perceived disease activity was the strongest predictor of COVID-19 concern, irrespective of gender, employment and education status or well-being and resilience. Generalized concerns regarding the COVID-19 pandemic were significantly higher in females, although their self-reported DASs were comparable to male respondents. CONCLUSION: Our findings highlight a gender bias in the generalized concern related to the COVID-19 pandemic, irrespective of the examined potential confounders. This suggests the need for further research around young patient self-reported outcomes outside hospital visits, especially in the context of gender differences and potential challenges of future pandemics

Marital status and gender differences as key determinants of COVID-19 impact on well-being, job satisfaction and resilience in health care workers and staff working in academia in the UK during the first wave of the pandemic

BACKGROUND: The COVID-19 pandemic is an unprecedented global public health crisis that continues to exert immense pressure on healthcare and related professional staff and services. The impact on staff wellbeing is likely to be influenced by a combination of modifiable and non-modifiable factors. OBJECTIVES: The aim of this study is to evaluate the effect of the COVID-19 pandemic on the self-reported wellbeing, resilience, and job satisfaction of National Health Service (NHS) and university staff working in the field of healthcare and medical research. METHODS: We conducted a cross sectional survey of NHS and UK university staff throughout the COVID-19 pandemic between May-November 2020. The anonymous and voluntary survey was disseminated through social media platforms, and via e-mail to members of professional and medical bodies. The data was analysed using descriptive and regression (R) statistics. RESULTS: The enjoyment of work and satisfaction outside of work was significantly negatively impacted by the COVID-19 pandemic for all of staff groups independent of other variables. Furthermore, married women reporting significantly lower well-being than married men (P=0.028). Additionally, the well-being of single females was significantly lower than both married women and men (P=0.017 and P<0.0001, respectively). Gender differences were also found in satisfaction outside of work, with women reporting higher satisfaction than men before the COVID-19 pandemic (P=0.0002). CONCLUSION: Our study confirms that the enjoyment of work and general satisfaction of staff members has been significantly affected by the first wave of the COVID-19 pandemic. Interestingly, being married appears to be a protective factor for wellbeing and resilience but the effect may be reversed for life satisfaction outside work. Our survey highlights the critical need for further research to examine gender differences using a wider range of methods

Bostonia: 1993-1994, no. 2-3

Founded in 1900, Bostonia magazine is Boston University's main alumni publication, which covers alumni and student life, as well as university activities, events, and programs

Development and validation of a multivariable risk factor questionnaire to detect oesophageal cancer in 2-week wait patients

INTRODUCTION: Oesophageal cancer is associated with poor health outcomes. Upper GI (UGI) endoscopy is the gold standard for diagnosis but is associated with patient discomfort and low yield for cancer. We used a machine learning approach to create a model which predicted oesophageal cancer based on questionnaire responses. METHODS: We used data from 2 separate prospective cross-sectional studies: the Saliva to Predict rIsk of disease using Transcriptomics and epigenetics (SPIT) study and predicting RIsk of diSease using detailed Questionnaires (RISQ) study. We recruited patients from National Health Service (NHS) suspected cancer pathways as well as patients with known cancer. We identified patient characteristics and questionnaire responses which were most associated with the development of oesophageal cancer. Using the SPIT dataset, we trained seven different machine learning models, selecting the best area under the receiver operator curve (AUC) to create our final model. We further applied a cost function to maximise cancer detection. We then independently validated the model using the RISQ dataset. RESULTS: 807 patients were included in model training and testing, split in a 70:30 ratio. 294 patients were included in model validation. The best model during training was regularised logistic regression using 17 features (median AUC: 0.81, interquartile range (IQR): 0.69-0.85). For testing and validation datasets, the model achieved an AUC of 0.71 (95% CI: 0.61-0.81) and 0.92 (95% CI: 0.88-0.96) respectively. At a set cut off, our model achieved a sensitivity of 97.6% and specificity of 59.1%. We additionally piloted the model in 12 patients with gastric cancer; 9/12 (75%) of patients were correctly classified. CONCLUSIONS: We have developed and validated a risk stratification tool using a questionnaire approach. This could aid prioritising patients at high risk of having oesophageal cancer for endoscopy. Our tool could help address endoscopic backlogs caused by the COVID-19 pandemic

Optimal choice of sample substrate and laser wavelength for Raman spectroscopic analysis of biological specimen

Raman spectroscopy is an optical technique based on the inelastic scattering of monochromatic light that can be used to identify the biomolecular composition of biological cells and tissues. It can be used as both an aid for understanding the etiology of disease and for accurate clinical diagnostics when combined with multivariate statistical algorithms. This method is non-destructive, potentially non-invasive and can be applied in vitro or in vivo directly or via a fiber optic probe. However, there exists a high degree of variability across experimental protocols, some of which result in large background signals that can often overpower the weak Raman signals being emitted. These protocols need to be standardised before the technique can provide reliable and reproducible experimental results in an everyday clinical environment. The objective of this study is to investigate the impact of different experimental parameters involved in the analysis of biological specimen. We investigate the Raman signals generated from healthy human cheek cells using different source laser wavelengths; 473 nm, 532 nm, 660 nm, 785 nm and 830 nm, and different sample substrates; Raman-grade calcium fluoride, IR polished calcium fluoride, magnesium fluoride, aluminium (100 nm and 1500 nm thin films on glass), glass, fused silica, potassium bromide, sodium chloride and zinc selenide, whilst maintaining all other experimental parameters constant throughout the study insofar as possible

Applications of Raman spectroscopy to the urinary bladder for cancer diagnostics

Biomolecular changes associated with cancer progression can be identified using Raman spectroscopy, allowing for this technique to be utilized as a non-invasive tool for the diagnosis of bladder cancer. Applications of Raman spectroscopy for diagnostics in real-time have consistently produced higher sensitivities and specificities than current clinical methods. This technique can be applied in vivo during bladder visualization (cystoscopic) procedures as an “optical biopsy” or in vitro to cells obtained from urine cytology specimens. This review follows the evolution of studies in this field from the first in vitro experiment to the most recent in vivo application, identifies how diagnostic algorithms are developed, and provides molecular information associated with the etiology of the biochemical continuum of disease progression. Future prospects for the application of Raman spectroscopy in bladder cancer diagnostics are also discussed