Double-Clad Antiresonant Hollow-Core Fiber and Its Comparison with Other Fibers for Multiphoton Micro-Endoscopy.

Label-free and multiphoton micro-endoscopy can transform clinical histopathology by providing an in situ tool for diagnostic imaging and surgical treatment in diseases such as cancer. Key to a multiphoton imaging-based micro-endoscopic device is the optical fiber, for distortion-free and efficient delivery of ultra-short laser pulses to the sample and effective signal collection. In this work, we study a new hollow-core (air-filled) double-clad anti-resonant fiber (DC-ARF) as a high-performance candidate for multiphoton micro-endoscopy. We compare the fiber characteristics of the DC-ARF with a single-clad anti-resonant fiber (SC-ARF) and a solid core fiber (SCF). In this work, while the DC-ARF and the SC-ARF enable low-loss (<0.2 dBm-1), close to dispersion-free excitation pulse delivery (<10% pulse width increase at 900 nm per 1 m fiber) without any induced non-linearities, the SCF resulted in spectral broadening and pulse-stretching (>2000% of pulse width increase at 900 nm per 1 m fiber). An ideal optical fiber endoscope needs to be several meters long and should enable both excitation and collection through the fiber. Therefore, we performed multiphoton imaging on endoscopy-compatible 1 m and 3 m lengths of fiber in the back-scattered geometry, wherein the signals were collected either directly (non-descanned detection) or through the fiber (descanned detection). Second harmonic images were collected from barium titanate crystals as well as from biological samples (mouse tail tendon). In non-descanned detection conditions, the ARFs outperformed the SCF by up to 10 times in terms of signal-to-noise ratio of images. Significantly, only the DC-ARF, due to its high numerical aperture (NA) of 0.45 and wide-collection bandwidth (>1 µm), could provide images in the de-scanned detection configuration desirable for endoscopy. Thus, our systematic characterization and comparison of different optical fibers under different image collection configurations, confirms and establishes the utility of DC-ARFs for high-performing label-free multiphoton imaging-based micro-endoscopy.

Holistic vibrational spectromics assessment of human cartilage for osteoarthritis diagnosis.

Osteoarthritis (OA) is the most common degenerative joint disease, presented as wearing down of articular cartilage and resulting in pain and limited mobility for 1 in 10 adults in the UK [Osteoarthr. Cartil.28(6), 792 (2020)10.1016/j.joca.2020.03.004]. There is an unmet need for patient friendly paradigms for clinical assessment that do not use ionizing radiation (CT), exogenous contrast enhancing dyes (MRI), and biopsy. Hence, techniques that use non-destructive, near- and shortwave infrared light (NIR, SWIR) may be ideal for providing label-free, deep tissue interrogation. This study demonstrates multimodal "spectromics", low-level abstraction data fusion of non-destructive NIR Raman scattering spectroscopy and NIR-SWIR absorption spectroscopy, providing an enhanced, interpretable "fingerprint" for diagnosis of OA in human cartilage. This is proposed as method level innovation applicable to both arthro- or endoscopic (minimally invasive) or potential exoscopic (non-invasive) optical approaches. Samples were excised from femoral heads post hip arthroplasty from OA patients (n = 13) and age-matched control (osteoporosis) patients (n = 14). Under multivariate statistical analysis and supervised machine learning, tissue was classified to high precision: 100% segregation of tissue classes (using 10 principal components), and a classification accuracy of 95% (control) and 80% (OA), using the combined vibrational data. There was a marked performance improvement (5 to 6-fold for multivariate analysis) using the spectromics fingerprint compared to results obtained from solely Raman or NIR-SWIR data. Furthermore, clinically relevant tissue components were identified through discriminatory spectral features - spectromics biomarkers - allowing interpretable feedback from the enhanced fingerprint. In summary, spectromics provides comprehensive information for early OA detection and disease stratification, imperative for effective intervention in treating the degenerative onset disease for an aging demographic. This novel and elegant approach for data fusion is compatible with various NIR-SWIR optical devices that will allow deep non-destructive penetration.

Classification of osteoarthritic and healthy cartilage using deep learning with Raman spectra.

Raman spectroscopy is a rapid method for analysing the molecular composition of biological material. However, noise contamination in the spectral data necessitates careful pre-processing prior to analysis. Here we propose an end-to-end Convolutional Neural Network to automatically learn an optimal combination of pre-processing strategies, for the classification of Raman spectra of superficial and deep layers of cartilage harvested from 45 Osteoarthritis and 19 Osteoporosis (Healthy controls) patients. Using 6-fold cross-validation, the Multi-Convolutional Neural Network achieves comparable or improved classification accuracy against the best-performing Convolutional Neural Network applied to either the raw or pre-processed spectra. We utilised Integrated Gradients to identify the contributing features (Raman signatures) in the network decision process, showing they are biologically relevant. Using these features, we compared Artificial Neural Networks, Decision Trees and Support Vector Machines for the feature selection task. Results show that training on fewer than 3 and 300 features, respectively, for the disease classification and layer assignment task provide performance comparable to the best-performing CNN-based network applied to the full dataset. Our approach, incorporating multi-channel input and Integrated Gradients, can potentially facilitate the clinical translation of Raman spectroscopy-based diagnosis without the need for laborious manual pre-processing and feature selection.

Longitudinal urinary neopterin is associated with hearing threshold change over time in independent older adults.

Low-grade chronic inflammation is associated with many age-related conditions. Non-invasive methods to monitor low-grade chronic inflammation may improve the management of older people at risk of poorer outcomes. This longitudinal cohort study has determined baseline inflammation using neopterin volatility in monthly urine samples of 45 independent older adults (aged 65-75 years). Measurement of neopterin, an inflammatory metabolite, enabled stratification of individuals into risk categories based on how often in a 12-month period their neopterin level was raised. Hearing was measured (pure-tone audiometry) at baseline, 1 year and 3 years of the study. Results show that those in the highest risk category (neopterin raised greater than 50% of the time) saw greater deterioration, particularly in high-frequency, hearing. A one-way Welch's ANOVA showed a significant difference between the risk categories for change in high-frequency hearing (W (3, 19.6) = 9.164, p = 0.0005). Despite the study size and duration individuals in the highest risk category were more than twice as likely to have an additional age-related morbidity than those in the lowest risk category. We conclude that volatility of neopterin in urine may enable stratification of those at greatest risk of progression of hearing loss.

Correlative geochemical imaging of Desmophyllum dianthus reveals biomineralisation strategy as a key coral vital effect.

The chemical and isotopic composition of stony coral skeletons form an important archive of past climate. However, these reconstructions are largely based on empirical relationships often complicated by "vital effects" arising from uncertain physiological processes of the coral holobiont. The skeletons of deep-sea corals, such as Desmophyllum dianthus, are characterised by micron-scale or larger geochemical heterogeneity associated with: (1) centres of calcification (COCs) where nucleation of new skeleton begins, and (2) fibres that thicken the skeleton. These features are difficult to sample cleanly using traditional techniques, resulting in uncertainty surrounding both the causes of geochemical differences and their influence on environmental signals. Here we combine optical, and in-situ chemical and isotopic, imaging tools across a range of spatial resolutions (~ 100 nm to 10 s of µm) in a correlative multimodal imaging (CMI) approach to isolate the microstructural geochemistry of each component. This reveals COCs are characterised by higher organic content, Mg, Li and Sr and lower U, B and δ11B compared to fibres, reflecting the contrasting biomineralisation mechanisms employed to construct each feature. CMI is rarely applied in Environmental/Earth Sciences, but here we illustrate the power of this approach to unpick the "vital effects" in D. dianthus, and by extension, other scleractinian corals.

Markers of adipose tissue fibrogenesis associate with clinically significant liver fibrosis and are unchanged by synbiotic treatment in patients with NAFLD.

BACKGROUND AND AIMS: Subcutaneous adipose tissue (SAT) dysfunction contributes to NAFLD pathogenesis and may be influenced by the gut microbiota. Whether transcript profiles of SAT are associated with liver fibrosis and are influenced by synbiotic treatment (that changes the gut microbiome) is unknown. We investigated: (a) whether the presence of clinically significant, ≥F2 liver fibrosis associated with adipose tissue (AT) dysfunction, differential gene expression in SAT, and/or a marker of tissue fibrosis (Composite collagen gene expression (CCGE)); and (b) whether synbiotic treatment modified markers of AT dysfunction and the SAT transcriptome. METHODS: Sixty-two patients with NAFLD (60 % men) were studied before and after 12 months of treatment with synbiotic or placebo and provided SAT samples. Vibration-controlled transient elastography (VCTE)-validated thresholds were used to assess liver fibrosis. RNA-sequencing and histological analysis of SAT were performed to determine differential gene expression, CCGE and the presence of collagen fibres. Regression modelling and receiver operator characteristic curve analysis were used to test associations with, and risk prediction for, ≥F2 liver fibrosis. RESULTS: Patients with ≥F2 liver fibrosis (n = 24) had altered markers of AT dysfunction and a SAT gene expression signature characterised by enrichment of inflammatory and extracellular matrix-associated genes, compared to those with

Mechanisms of SARS-CoV-2 Inactivation Using UVC Laser Radiation.

Severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) has had a tremendous impact on humanity. Prevention of transmission by disinfection of surfaces and aerosols through a chemical-free method is highly desirable. Ultraviolet C (UVC) light is uniquely positioned to achieve inactivation of pathogens. We report the inactivation of SARS-CoV-2 virus by UVC radiation and explore its mechanisms. A dose of 50 mJ/cm2 using a UVC laser at 266 nm achieved an inactivation efficiency of 99.89%, while infectious virions were undetectable at 75 mJ/cm2 indicating >99.99% inactivation. Infection by SARS-CoV-2 involves viral entry mediated by the spike glycoprotein (S), and viral reproduction, reliant on translation of its genome. We demonstrate that UVC radiation damages ribonucleic acid (RNA) and provide in-depth characterization of UVC-induced damage of the S protein. We find that UVC severely impacts SARS-CoV- 2 spike protein's ability to bind human angiotensin-converting enzyme 2 (hACE2) and this correlates with loss of native protein conformation and aromatic amino acid integrity. This report has important implications for the design and development of rapid and effective disinfection systems against the SARS-CoV-2 virus and other pathogens.

Development of hydrogel-based standards and phantoms for non-linear imaging at depth.

Significance: Rapid advances in medical imaging technology, particularly the development of optical systems with non-linear imaging modalities, are boosting deep tissue imaging. The development of reliable standards and phantoms is critical for validation and optimization of these cutting-edge imaging techniques. Aim: We aim to design and fabricate flexible, multi-layered hydrogel-based optical standards and evaluate advanced optical imaging techniques at depth. Approach: Standards were made using a robust double-network hydrogel matrix consisting of agarose and polyacrylamide. The materials generated ranged from single layers to more complex constructs consisting of up to seven layers, with modality-specific markers embedded between the layers. Results: These standards proved useful in the determination of the axial scaling factor for light microscopy and allowed for depth evaluation for different imaging modalities (conventional one-photon excitation fluorescence imaging, two-photon excitation fluorescence imaging, second harmonic generation imaging, and coherent anti-Stokes Raman scattering) achieving actual depths of 1550, 1550, 1240, and 1240 µm, respectively. Once fabricated, the phantoms were found to be stable for many months. Conclusions: The ability to image at depth, the phantom's robustness and flexible layered structure, and the ready incorporation of "optical markers" make these ideal depth standards for the validation of a variety of imaging modalities.