BACKGROUND:Liver biopsy assessment by pathologists remains the gold standard for diagnosing metabolic dysfunction-associated steatotic liver disease (MASLD). Current automated image analysis tools for patient risk stratification are often proprietary or not applicable to whole slide images (WSIs). Here, we introduce "Liver-Quant," an open-source Python package for quantifying steatosis and fibrosis in liver WSIs. METHOD:Liver-Quant leverages colour and morphological features to measure Steatosis Proportionate Area (SPA) and Collagen Proportionate Area (CPA). We evaluated the method using an internal dataset of 414 WSIs from adult patients (Leeds Teaching Hospitals NHS Trust, 2016-2022) and an external public dataset (109 WSIs). Semi-quantitative scores were extracted from pathological reports. The Spearman rank coefficient (ρ) assessed correlations between computed SPA/CPA and pathologist scores. RESULTS:Steatosis quantification showed a substantial correlation (ρ = 0.92), while fibrosis quantification yielded a moderate correlation (ρ = 0.51). We further investigated the impact of three staining dyes (Van Gieson (VG), Picro Sirius Red (PSR), and Masson's Trichrome (MTC)) on fibrosis quantification (n = 18). Stain normalisation yielded excellent agreement in CPA measurements across all three stains. Without normalisation, PSR achieved the strongest correlation with human scores (ρ = 0.9) followed by VG (ρ = 0.8) and MTC (ρ = 0.59). Finally, we explored the impact of apparent magnification on SPA and CPA. High-resolution images (0.25 or 0.50 μm per pixel (MPP)) were necessary for accurate SPA measurement, while lower resolution (10 MPP) sufficed for CPA measurements. CONCLUSIONS:Liver-Quant offers an open-source solution for rapid and precise MASLD quantification in WSIs applicable to multiple histological stains.

Whole slide imaging (WSI) of pathology glass slides with high-resolution scanners has enabled the large-scale application of artificial intelligence (AI) in pathology, to support the detection and diagnosis of disease, potentially increasing efficiency and accuracy in tissue diagnosis. Despite the promise of AI, it has limitations. 'Brittleness' or sensitivity to variation in inputs necessitates that large amounts of data are used for training. AI is often trained on data from different scanners but not usually by replicating the same slide across scanners. The utilisation of multiple WSI instruments to produce digital replicas of the same glass slides will make more comprehensive datasets and may improve the robustness and generalisability of AI algorithms as well as reduce the overall data requirements of AI training. To this end, the National Pathology Imagine Cooperative (NPIC) has built the AI FORGE (Facilitating Opportunities for Robust Generalisable data Emulation), a unique multi-scanner facility embedded in a clinical site in the NHS to (a) compare scanner performance and (b) replicate digital pathology image datasets across WSI systems. The NPIC AI FORGE currently comprises 15 scanners from 9 manufacturers. It can generate approximately 4000 WSI images per day (approximately 7Tb of image data). This paper describes the process followed to plan and build such a facility.

Human visual attention allows prior knowledge or expectations to influence visual processing, allocating limited computational resources to only that part of the image that are likely to behaviourally important. Here, we present an image recognition system based on biological vision that guides attention to more informative locations within a larger parent image, using a sequence of saccade-like motions. We demonstrate that at the end of the saccade sequence the system has an improved classification ability compared to the convolutional neural network (CNN) that represents the feedforward part of the model. Feedback activations highlight salient image features supporting the explainability of the classification. Our attention model deviates substantially from more common feedforward attention mechanisms, which linearly reweight part of the input. This model uses several passes of feedforward and backward activation, which interact non-linearly. We apply our feedback architecture to histopathology patch images, demonstrating a 3.5% improvement in accuracy (p<0.001) when retrospectively processing 59,057 9-class patches from 689 colorectal cancer WSIs. In the saccade implementation, overall agreement between expert-labelled patches and model prediction reached 93.23% for tumour tissue, surpassing inter-pathologist agreement. Our method is adaptable to other areas of science which rely on the analysis of extremely large-scale images.

Abstract Checkpoint inhibitors (CPI), ameliorate the anti-tumour response by blocking inhibitory immune checkpoint receptors, and have revolutionised the treatment of advanced cancers. However, the prediction of treatment response is suboptimal, and there remains a strong reliance on tumour mutation burden (TMB). Studies to date are limited to whole exome sequencing (WES), with no data yet reported on the utility of whole genome sequencing (WGS) in a pan-cancer cohort. Here we report a pan-cancer cohort of 318 tumour/normal genomes from the Genomics England 100,000 Genomes Project cohort treated with CPIs. Pan-cancer biomarkers previously reported from WES such as clonal TMB, total neoantigen burden and TMB had continued utility in predicting treatment response. Clonal TMB remained the strongest univariate predictor of positive treatment outcome, followed by infiltrating T cell fraction, and tobacco/UV mutational signatures. using whole genome assay, we additionally detected novel signatures associated with poor outcomes, including markers reflecting chemotherapy-induced mutations. Patients treated with chemotherapy prior to CPI displayed reduced survival irrespective of tumour type and had more subclonal mutations. Structural variants (SVs) were also predictive of poor therapeutic response and were enriched with non-coding intronic breakpoints, generating significantly fewer neoantigens than expected by chance. Global genomic features such as telomere length were associated with poor survival following CPI treatment, particularly in renal and bladder cancers. Together, these validated and novel biomarkers showed collective utility when combined to predict CPI outcomes. Our results highlight the value of WGS in detecting biomarkers of treatment resistance and highlight the promise of WGS for use in clinical practice.

Digital pathology Whole Slide Images (WSIs) are large images (∼30 GB/slide uncompressed) of high resolution (0.25 microns per pixel), presenting a significant data storage challenge for hospitals wishing to adopt digital pathology. Lossy compression has been adopted by scanner manufacturers to address this issue - we compare lossy Joint Photographic Experts Group (JPEG) compression for WSIs and investigate the Vector Quantised Variational Autoencoder 2 variant (VQVAE2) as a possible alternative to reduce file size while encoding useful features in the compressed representation. We trained three VQVAE2 models on a Camelyon 2016 subset to the Compression Ratio (CR) of 19.2:1 (CR1), 9.6:1 (CR2) and 4.8:1 (CR3) and tested on a Camelyon 2016 (DS1) subset; University of California (DS2) and Internal Validation Set (DS3). We then compared compression performance to ImageMagick JPEG and JPEG 2000 implementations. Both JPEG and JPEG 2000 compression outperformed the VQVAE2 implementation within the Peak Signal to Noise Ratio (PSNR) and Structural Similarity (SSIM) metrics. The trained VQVAE2 models could visually reproduce WSI tissue structure, but used colours from the original training data within the reconstructions on other datasets.

Checkpoint inhibitors (CPI), ameliorate the anti-tumour response by blocking inhibitory immune checkpoint receptors, and have revolutionised the treatment of advanced cancers. However, the prediction of treatment response is suboptimal, and there remains a strong reliance on tumour mutation burden (TMB). Studies to date are limited to whole exome sequencing (WES), with no data yet reported on the utility of whole genome sequencing (WGS) in a pan-cancer cohort. Here we report a pan-cancer cohort of 318 tumour/normal genomes from the Genomics England 100,000 Genomes Project cohort treated with CPIs. Pan-cancer biomarkers previously reported from WES such as clonal TMB, total neoantigen burden and TMB had continued utility in predicting treatment response. Clonal TMB remained the strongest univariate predictor of positive treatment outcome, followed by infiltrating T cell fraction, and tobacco/UV mutational signatures. using whole genome assay, we additionally detected novel signatures associated with poor outcomes, including markers reflecting chemotherapy-induced mutations. Patients treated with chemotherapy prior to CPI displayed reduced survival irrespective of tumour type and had more subclonal mutations. Structural variants (SVs) were also predictive of poor therapeutic response and were enriched with non-coding intronic breakpoints, generating significantly fewer neoantigens than expected by chance. Global genomic features such as telomere length were associated with poor survival following CPI treatment, particularly in renal and bladder cancers. Together, these validated and novel biomarkers showed collective utility when combined to predict CPI outcomes. Our results highlight the value of WGS in detecting biomarkers of treatment resistance and highlight the promise of WGS for use in clinical practice.

The Covid-19 pandemic instigated a rapid shift to remote learning in schools of architecture in the United Kingdom. Through the largest survey of its kind of architectural students and tutors in the UK, this research compares experiences in the physical design studio and its remote equivalent. The context of the pandemic provided a unique opportunity to survey a range of cohorts, at different stages in their architectural education to compare these two modes of studio delivery. The findings show a fall in student satisfaction after the move to remote learning in every metric assessed. Peer interaction and support were particularly effected. More formal teaching interactions, such as reviews, crits and tutorials, also suffered but to a lesser extent. For teaching staff, some small improvements in the working environment were observed as well as organisational factors. However, these small gains were outweighed by the negative changes. The research suggests that despite the replication of teaching activities digitally, the situated learning of design education and the facilitation of informal learning scenarios are critical components of design education. This research contributes to the ongoing characterisation of architectural education's signature pedagogy and suggests that for effective remote learning, design studio education must be reconceptualised, and alternative pedagogies embraced. This can direct educators looking to develop remote design studio learning as well as highlighting areas in which the traditional model of architectural education may be enhanced.

Digital slide images produced from routine diagnostic histopathological preparations suffer from variation arising at every step of the processing pipeline. Typically, pathologists compensate for such variation using expert knowledge and experience, which is difficult to replicate in automated solutions. The extent to which inconsistencies affect image analysis is explored in this work, examining in detail, the results from a previously published algorithm automating the generation of tumor:stroma ratio (TSR) in colorectal clinical trial datasets. One dataset consisting of 2,211 cases and 106,268 expert-labelled images is used to identify quality issues, by visually inspecting cases where algorithm-pathologist agreement is lowest. Twelve categories are identified and used to analyze pathologist-algorithm agreement in relation to these categories. Of the 2,211 cases, 701 were found to be free from any image quality issues. Algorithm performance was then assessed, comparing pathologist agreement with image quality classification. It was found that agreement was lowest on poorly differentiated tissue, with a mean TSR difference of 0.25 (sd = 0.24). Removing images that contained quality issues increased accuracy from 80% to 83%, at the expense of reducing the dataset to 33,736 images (32%). Training the algorithm on the optimized dataset, prior to testing on all images saw a decrease in accuracy of 4%, indicating that the optimized dataset did not contain enough variation to generate a fully representative model. The results provide an in-depth perspective on image quality, highlighting the importance of the effects on downstream image analysis.

Pathology departments must rise to new staffing challenges caused by the coronavirus disease-19 pandemic and may need to work more flexibly for the foreseeable future. In light of this, many pathologists and departments are considering the merits of remote or home reporting of digital cases. While some individuals have experience of this, little work has been done to determine optimum conditions for home reporting, including technical and training considerations. In this publication produced in response to the pandemic, we provide information regarding risk assessment of home reporting of digital slides, summarize available information on specifications for home reporting computing equipment, and share access to a novel point-of-use quality assurance tool for assessing the suitability of home reporting screens for digital slide diagnosis. We hope this study provides a useful starting point and some practical guidance in a difficult time. This study forms the basis of the guidance issued by the Royal College of Pathologists, available at: https://www.rcpath.org/uploads/assets/626ead77-d7dd-42e1-949988e43dc84c97/RCPath-guidance-for-remote-digital-pathology.pdf.

The conversion of industrial crops to energy has received significant attention recently as a means to reduce carbon emissions and meeting the renewable energy targets. Samples of whole crop maize (Zea mays L.) were pre-treated in tap water using a novel microbubble-enhanced dielectric barrier discharge (DBD) plasma reactor that generates highly reactive species in situ and distribute them using microbubbles. The pre-treated maize was then used as feedstock in batch and continuously-fed mesophilic continuously-stirred anaerobic digesters (AD). Half of the pre-treated samples were washed in deionized water prior to feeding to assess the effect of possible inhibitory by-products generated during pre-treatment. In batch AD experiments, DBD-plasma pre-treated and washed maize produced 18% greater biogas production in comparison to untreated raw samples, and unwashed samples produced 29% lower biogas than the untreated samples. These results suggest the production of inhibitors to the AD process, but biogas production can be enhanced by removing these inhibiting compounds. Continuously-fed AD reactors exhibited no noticeable change in biogas output between raw and plasma-treated maize. For AD reactors operating in batch, or with a relatively long residence time and fed with high lignocellulose feedstocks, plasmamicrobubble pre-treatment could enhance biogas output and process efficiency. (C) 2020 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

Reactive species produced by atmospheric-pressure plasma (APP) are useful in many applications including disinfection, pretreatment, catalysis, detection and chemical synthesis. Most highly reactive species produced by plasma, such as ·OH, 1O2 and $$ {\text{O}}_{2}^{ \cdot - } $$, are short-lived; therefore, in situ generation is essential to transfer plasma products to the liquid phase efficiently. A novel microfluidic device that generates a dielectric barrier discharge (DBD) plasma at the gas–liquid interface and disperses the reactive species generated using microbubbles of ca. 200 µm in diameter has been developed and tested. As the bubble size affects the mass transfer performance of the device, the effect of operating parameters and plasma discharge on generated bubbles size has been studied. The mass transfer performance of the device was evaluated by transferring the reactive species generated to an aqueous solution containing dye and measuring percentage degradation of the dye. Monodisperse microbubbles (polydispersity index between 2 and 7%) were generated under all examined conditions, but for gas flow rate exceeding a critical value, a secondary break-up event occurred after bubble formation leading to multiple monodisperse bubble populations. The generated microbubble size increased by up to ~ 8% when the device was operated with the gas plasma in the dispersed phase compared to the case without the plasma due to thermal expansion of the feed gas. At the optimal operating conditions, initial dye concentration was reduced by ~ 60% in a single pass with a residence time of 5–10 s. This microfluidic chip has the potential to play a significant role in lab-on-a-chip devices where highly reactive species are essential for the process.

Most cancer patients receive chemotherapy at some stage of their treatment which makes improving the efficacy of cytotoxic drugs an ongoing and important goal. Despite large numbers of potent anti-cancer agents being developed, a major obstacle to clinical translation remains the inability to deliver therapeutic doses to a tumor without causing intolerable side effects. To address this problem, there has been intense interest in nanoformulations and targeted delivery to improve cancer outcomes. The aim of this work was to demonstrate how vascular endothelial growth factor receptor 2 (VEGFR2)-targeted, ultrasound-triggered delivery with therapeutic microbubbles (thMBs) could improve the therapeutic range of cytotoxic drugs. Methods: Using a microfluidic microbubble production platform, we generated thMBs comprising VEGFR2-targeted microbubbles with attached liposomal payloads for localised ultrasound-triggered delivery of irinotecan and SN38 in mouse models of colorectal cancer. Intravenous injection into tumor-bearing mice was used to examine targeting efficiency and tumor pharmacodynamics. High-frequency ultrasound and bioluminescent imaging were used to visualise microbubbles in real-time. Tandem mass spectrometry (LC-MS/MS) was used to quantitate intratumoral drug delivery and tissue biodistribution. Finally, 89Zr PET radiotracing was used to compare biodistribution and tumor accumulation of ultrasound-triggered SN38 thMBs with VEGFR2-targeted SN38 liposomes alone. Results: ThMBs specifically bound VEGFR2 in vitro and significantly improved tumor responses to low dose irinotecan and SN38 in human colorectal cancer xenografts. An ultrasound trigger was essential to achieve the selective effects of thMBs as without it, thMBs failed to extend intratumoral drug delivery or demonstrate enhanced tumor responses. Sensitive LC-MS/MS quantification of drugs and their metabolites demonstrated that thMBs extended drug exposure in tumors but limited exposure in healthy tissues, not exposed to ultrasound, by persistent encapsulation of drug prior to elimination. 89Zr PET radiotracing showed that the percentage injected dose in tumors achieved with thMBs was twice that of VEGFR2-targeted SN38 liposomes alone. Conclusions: thMBs provide a generic platform for the targeted, ultrasound-triggered delivery of cytotoxic drugs by enhancing tumor responses to low dose drug delivery via combined effects on circulation, tumor drug accumulation and exposure and altered metabolism in normal tissues.

The emerging field of atmospheric pressure plasmas (APPS) for treatment of various solutions and suspensions has led to a variety of plasma reactors and power sources. This article reports on the design, characterisation and modelling of a novel plasma-microbubble reactor that forms a dielectric barrier discharge (DBD) at the gas-liquid interface to facilitate the transfer of short-lived highly reactive species from the gas plasma into the liquid phase. The use of microbubbles enabled efficient dispersion of long-lived reactive species in the liquid and UVC-induced oxidation reactions are triggered by the plasma radiation at the gas-liquid interface. A numerical model was developed to understand the dynamics of the reactor, and the model was validated using experimental measurements. Fluid velocities in the riser region of the reactor were found to be an order of magnitude higher for smaller bubbles ((5) over tilde mu m diameter) than for larger bubbles ((2) over tilde 500 mu m diameter); hence provided well-mixed conditions for treatment. In addition to other reactive oxygen species (ROS) and reactive nitrogen species (RNS), a dissolved ozone concentration of 3 mu M was recoded after a 15-min operation of the reactor, demonstrating the suitability of this design for various applications. (C) 2019 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

Nucleotomy is a common surgical procedure and is also performed in ex vivo mechanical testing to model decreased nucleus pulposus (NP) pressurization that occurs with degeneration. Here, we implement novel and noninvasive methods using magnetic resonance imaging (MRI) to study internal 3D annulus fibrosus (AF) deformations after partial nucleotomy and during axial compression by evaluating changes in internal AF deformation at reference loads (50 N) and physiological compressive loads (similar to 10% strain). One particular advantage of this methodology is that the full 3D disc deformation state, inclusive of both in-plane and out-of-plane deformations, can be quantified through the use of a high-resolution volumetric MR scan sequence and advanced image registration. Intact grade II L3-L4 cadaveric human discs before and after nucleotomy were subjected to identical mechanical testing and imaging protocols. Internal disc deformation fields were calculated by registering MR images captured in each loading state (reference and compressed) and each condition (intact and nucleotomy). Comparisons were drawn between the resulting three deformation states (intact at compressed load, nucleotomy at reference load, nucleotomy at compressed load) with regard to the magnitude of internal strain and direction of internal displacements. Under compressed load, internal AF axial strains averaged -18.5% when intact and -22.5% after nucleotomy. Deformation orientations were significantly altered by nucleotomy and load magnitude. For example, deformations of intact discs oriented in-plane, whereas deformations after nucleotomy oriented axially. For intact discs, in-plane components of displacements under compressive loads oriented radially outward and circumferentially. After nucleotomy, in-plane displacements were oriented radially inward under reference load and were not significantly different from the intact state at compressed loads. Re-establishment of outward displacements after nucleotomy indicates increased axial loading restores the characteristics of internal pressurization. Results may have implications for the recurrence of pain, design of novel therapeutics, or progression of disc degeneration.

In this study we examine both the effect of changing the applied voltage waveform shape and the modulation on-time on the amount of ozone dissolved within a liquid in a dielectric barrier discharges (DBD) bubble reactor. In this device, the discharge forms at the gas–liquid interface allowing for effective transfer of the plasma effluent into the liquid. To produce different voltage waveforms, a multilevel inverter power supply capable of generating arbitrary waveforms without switching-on and switching-off transients has been used. Of the four waveforms used in the study (sinusoidal, sawtooth, square and short-pulse), the square waveform was found to be the most efficient at producing the highest ozone concentration for a fixed peak voltage and average power. To determine the effect of the modulation on-time, the number of cycles during the on-time were increased from 1 up to 1000, adjusting the off-time accordingly to maintain the same duty cycle. Shorter on-time periods were found to be more efficient. Experimental and computational results indicate that the time between subsequent discharges is critical for increased ozone generation efficacy, as this needs to be long enough for ozone produced in one discharge event to diffuse away from the discharge region before the next discharge event occurs, thereby avoiding its partial destruction in the plasma. This insight provides a valuable criterion for the optimization of DBD reactors used in novel biomedical, agricultural and environmental applications.

Final effluent from wastewater treatment plants may contain bacteria that can pose a range of environmental and health threats. A microbubble-gas plasma reactor capable of producing a number of both reactive oxygen species and reactive nitrogen species has been developed for inactivating bacteria in final effluents. At the optimum operating conditions, greater than 5-log reductions in E. coli. viability was achieved in pure water after 30 min of operation with an energy consumption of 68 kJ/L. Addition of humic acid reduced the E. coli. inactivation rate. At the highest concentration of humic acid tested (0.0015% w/w), E. coli. inactivation was reduced by (similar to)50% compared to that achieved in pure water for a 30-minute treatment time. Longer treatment times may be required for waste streams having a high organic content, but the disinfection levels achieved with a low power consumption demonstrate the potential of this approach for industrial use.

Understanding the production mechanisms of ozone and other reactive species in atmospheric pressure dielectric barrier discharges (DBDs) has become increasingly important for the optimization and commercial success of these plasma devices in emerging applications, such as plasma medicine, plasma agriculture, and plasma catalysis. In many of these applications, input power modulation is exploited as a means to maintain a low gas temperature. Although the chemical pathways leading to ozone production/destruction and their strong temperature dependence are relatively well understood, the effect of the on-time duration on the performance of these modulated DBDs remains largely unexplored. In this study, we use electrical and optical diagnostics, as well as computational methods, to assess the performance of a modulated DBD device. The well-established Lissajous method for measuring the power delivered to the discharge is not suitable for modulated DBDs because the transients generated at the beginning of each pulse become increasingly important in short on-time modulated plasmas. It is shown that for the same input power and modulation duty-cycle, shorter on-time pulses result in significantly enhanced ozone production, despite their operation at slightly higher temperatures. The key underpinning mechanism that causes this counter-intuitive observation is the more efficient net generation rate of ozone during the plasma on-time due to the lower accumulation of NO2 in the discharge volume.