Bioprocess monitoring applications of an innovative ATR-FTIR spectroscopy platform.

Pharmaceutical manufacturing is reliant upon bioprocessing approaches to generate the range of therapeutic products that are available today. The high cost of production, susceptibility to process failure, and requirement to achieve consistent, high-quality product means that process monitoring is paramount during manufacturing. Process analytic technologies (PAT) are key to ensuring high quality product is produced at all stages of development.

A spectroscopic liquid biopsy for the earlier detection of multiple cancer types.

Background: A rapid, low-cost blood test that can be applied to reliably detect multiple different cancer types would be transformational.

Methods: In this large-scale discovery study (n = 2092 patients) we applied the Dxcover® Cancer Liquid Biopsy to examine eight different cancers. The test uses Fourier transform infrared (FTIR) spectroscopy and machine-learning algorithms to detect cancer.

A scoping review of clinical practice guidelines for the diagnosis of primary spontaneous pneumothorax.

Introduction/background: Primary spontaneous pneumothorax (PSP) is characterised by the onset of pneumothorax with no evidence of trauma or associated co-morbidities. Several clinical practice guidelines (CPGs) have been published regarding the management of PSP. Inconsistency in imaging protocols across clinics globally may indicate variability in the recommendations within these guidelines.

Clinical validation of a spectroscopic liquid biopsy for earlier detection of brain cancer.

Background: Diagnostic delays impact the quality of life and survival of patients with brain tumors. Earlier and expeditious diagnoses in these patients are crucial to reduce the morbidities and mortalities associated with brain tumors. A simple, rapid blood test that can be administered easily in a primary care setting to efficiently identify symptomatic patients who are most likely to have a brain tumor would enable quicker referral to brain imaging for those who need it most.

Identification of biomarkers for the diagnosis and targets for therapy in patients with clear cell ovarian cancer: a systematic literature review.

Clear cell ovarian cancer (CCOC) is a rare type of epithelial cancer often resistant to platinum-based chemotherapy. Biomarkers for the diagnosis of CCOC, and targets for immunotherapy, both have the potential to improve outcomes for patients. Our review aims to determine whether any antigens already identified in the literature could fulfil this remit.

Rapid Spectroscopic Liquid Biopsy for the Universal Detection of Brain Tumours.

Background: To support the early detection and diagnosis of brain tumours we have developed a rapid, cost-effective and easy to use spectroscopic liquid biopsy based on the absorbance of infrared radiation. We have previously reported highly sensitive results of our approach which can discriminate patients with a recent brain tumour diagnosis and asymptomatic controls. Other liquid biopsy approaches (e.

Early diagnosis of brain tumours using a novel spectroscopic liquid biopsy.

Early diagnosis of brain tumours is challenging and a major unmet need. Patients with brain tumours most often present with non-specific symptoms more commonly associated with less serious diagnoses, making it difficult to determine which patients to prioritize for brain imaging. Delays in diagnosis affect timely access to treatment, with potential impacts on quality of life and survival.

Early economic evaluation to guide the development of a spectroscopic liquid biopsy for the detection of brain cancer.

Objectives: An early economic evaluation to inform the translation into clinical practice of a spectroscopic liquid biopsy for the detection of brain cancer. Two specific aims are (1) to update an existing economic model with results from a prospective study of diagnostic accuracy and (2) to explore the potential of brain tumor-type predictions to affect patient outcomes and healthcare costs.

Methods: A cost-effectiveness analysis from a UK NHS perspective of the use of spectroscopic liquid biopsy in primary and secondary care settings, as well as a cost-consequence analysis of the addition of tumor-type predictions was conducted.

Interrogation of Status in Gliomas by Fourier Transform Infrared Spectroscopy.

Mutations in the isocitrate dehydrogenase 1 () gene are found in a high proportion of diffuse gliomas. The presence of the mutation is a valuable diagnostic, prognostic and predictive biomarker for the management of patients with glial tumours. Techniques involving vibrational spectroscopy, e.

Stratifying Brain Tumour Histological Sub-Types: The Application of ATR-FTIR Serum Spectroscopy in Secondary Care.

Patients living with brain tumours have the highest average years of life lost of any cancer, ultimately reducing average life expectancy by 20 years. Diagnosis depends on brain imaging and most often confirmatory tissue biopsy for histology. The majority of patients experience non-specific symptoms, such as headache, and may be reviewed in primary care on multiple occasions before diagnosis is made.

Rapid analysis of disease state in liquid human serum combining infrared spectroscopy and "digital drying".

In recent years, the diagnosis of brain tumors has been investigated with attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy on dried human serum samples to eliminate spectral interferences of the water component, with promising results. This research evaluates ATR-FTIR on both liquid and air-dried samples to investigate "digital drying" as an alternative approach for the analysis of spectra obtained from liquid samples. Digital drying approaches, consisting of water subtraction and least-squares method, have demonstrated a greater random forest (RF) classification performance than the air-dried spectra approach when discriminating cancer vs control samples, reaching sensitivity values higher than 93.

Biofluid diagnostics by FTIR spectroscopy: A platform technology for cancer detection.

Fourier Transform Infrared Spectroscopy (FTIR) has been largely employed by scientific researchers to improve diagnosis and treatment of cancer, using various biofluids and tissues. The technology has proved to be easy to use, rapid and cost-effective for analysis on human blood serum to discriminate between cancer versus healthy control samples. The high sensitivity and specificity achievable during samples classification aided by machine learning algorithms, offers an opportunity to transform cancer referral pathways, as it has been demonstrated in a unique and recent prospective clinical validation study on brain tumours.

Developing infrared spectroscopic detection for stratifying brain tumour patients: glioblastoma multiforme vs. lymphoma.

Over a third of brain tumour patients visit their general practitioner more than five times prior to diagnosis in the UK, leading to 62% of patients being diagnosed as emergency presentations. Unfortunately, symptoms are non-specific to brain tumours, and the majority of these patients complain of headaches on multiple occasions before being referred to a neurologist. As there are currently no methods in place for the early detection of brain cancer, the affected patients' average life expectancy is reduced by 20 years.

Development of high-throughput ATR-FTIR technology for rapid triage of brain cancer.

Non-specific symptoms, as well as the lack of a cost-effective test to triage patients in primary care, has resulted in increased time-to-diagnosis and a poor prognosis for brain cancer patients. A rapid, cost-effective, triage test could significantly improve this patient pathway. A blood test using attenuated total reflection (ATR)-Fourier transform infrared (FTIR) spectroscopy for the detection of brain cancer, alongside machine learning technology, is advancing towards clinical translation.

Optimised spectral pre-processing for discrimination of biofluids via ATR-FTIR spectroscopy.

Pre-processing is an essential step in the analysis of spectral data. Mid-IR spectroscopy of biological samples is often subject to instrumental and sample specific variances which may often conceal valuable biological information. Whilst pre-processing can effectively reduce this unwanted variance, the plethora of possible processing steps has resulted in a lack of consensus in the field, often meaning that analysis outputs are not comparable.

Health economic evaluation of a serum-based blood test for brain tumour diagnosis: exploration of two clinical scenarios.

Objectives: To determine the potential costs and health benefits of a serum-based spectroscopic triage tool for brain tumours, which could be developed to reduce diagnostic delays in the current clinical pathway.

Design: A model-based health pre-trial economic assessment. Decision tree models were constructed based on simplified diagnostic pathways.

Biofluid spectroscopic disease diagnostics: A review on the processes and spectral impact of drying.

The complex patterns observed from evaporated liquid drops have been examined extensively over the last 20 years. Complete understanding of drop deposition is vital in many medical processes, and one which is essential to the translation of biofluid spectroscopic disease diagnostics. The promising use of spectroscopy in disease diagnosis has been hindered by the complicated patterns left by dried biological fluids which may inhibit the clinical translation of this technology.

Feature driven classification of Raman spectra for real-time spectral brain tumour diagnosis using sound.

Spectroscopic diagnostics have been shown to be an effective tool for the analysis and discrimination of disease states from human tissue. Furthermore, Raman spectroscopic probes are of particular interest as they allow for in vivo spectroscopic diagnostics, for tasks such as the identification of tumour margins during surgery. In this study, we investigate a feature-driven approach to the classification of metastatic brain cancer, glioblastoma (GB) and non-cancer from tissue samples, and we provide a real-time feedback method for endoscopic diagnostics using sound.

Effects of 4-nonylphenol on spermatogenesis and induction of testicular apoptosis through oxidative stress-related pathways.

This study tested the hypothesis that prepubertal exposure to 4-nonylphenol (NP) affects reproductive function in male rats. Twenty-four rats at five-weeks-old were randomly divided into four groups and treated with NP at varying concentrations (0, 5, 20, and 60mg/kg/2d) for thirty days by intra-peritoneal injection. 60mg/kg NP induced spermatogenic degeneration and pronounced deficits in epididymal sperm count, motility and function, whereas potentially stimulatory effects were observed at 5 NPmg/kg.

4-Nonylphenol induces disruption of spermatogenesis associated with oxidative stress-related apoptosis by targeting p53-Bcl-2/Bax-Fas/FasL signaling.

4-Nonylphenol (NP) is a ubiquitous environmental chemical with estrogenic activity. Our aim was to test the hypothesis that pubertal exposure to NP leads to testicular dysfunction. Herein, 24 7-week-old rats were randomly divided into four groups and treated with NP (0, 25, 50, or 100 mg/kg body weight every 2 days for 20 consecutive days) by intraperitoneal injection.

Spectrochemical analysis of sycamore (Acer pseudoplatanus) leaves for environmental health monitoring.

Terrestrial plants are ideal sentinels of environmental pollution, due to their sedentary nature, abundance and sensitivity to atmospheric changes. However, reliable and sensitive biomarkers of exposure have hitherto been difficult to characterise. Biospectroscopy offers a novel approach to the derivation of biomarkers in the form of discrete molecular alterations detectable within a biochemical fingerprint.

Using Raman spectroscopy to characterize biological materials.

Raman spectroscopy can be used to measure the chemical composition of a sample, which can in turn be used to extract biological information. Many materials have characteristic Raman spectra, which means that Raman spectroscopy has proven to be an effective analytical approach in geology, semiconductor, materials and polymer science fields. The application of Raman spectroscopy and microscopy within biology is rapidly increasing because it can provide chemical and compositional information, but it does not typically suffer from interference from water molecules.

Gold nanoparticles as a substrate in bio-analytical near-infrared surface-enhanced Raman spectroscopy.

As biospectroscopy techniques continue to be developed for screening or diagnosis within a point-of-care setting, an important development for this field will be high-throughput optimization. For many of these techniques, it is therefore necessary to adapt and develop parameters to generate a robust yet simple approach delivering high-quality spectra from biological samples. Specifically, this is important for surface-enhanced Raman spectroscopy (SERS) wherein there are multiple variables that can be optimised to achieve an enhancement of the Raman signal from a sample.

A comprehensive transcriptome analysis of silique development and dehiscence in Arabidopsis and Brassica integrating genotypic, interspecies and developmental comparisons.

Asynchronous flowering of Brassica napus (canola) leads to seeds and siliques at varying stages of maturity as harvest approaches. This range of maturation can result in premature silique dehiscence (pod shattering), resulting in yield losses, which may be worsened by environmental stresses. Therefore, a goal for canola crop improvement is to reduce shattering in order to maximize yield.

Using Fourier transform IR spectroscopy to analyze biological materials.

IR spectroscopy is an excellent method for biological analyses. It enables the nonperturbative, label-free extraction of biochemical information and images toward diagnosis and the assessment of cell functionality. Although not strictly microscopy in the conventional sense, it allows the construction of images of tissue or cell architecture by the passing of spectral data through a variety of computational algorithms.