CD, or not CD, that is the question: a digital interobserver agreement study in coeliac disease.

OBJECTIVE: Coeliac disease (CD) diagnosis generally depends on histological examination of duodenal biopsies. We present the first study analysing the concordance in examination of duodenal biopsies using digitised whole-slide images (WSIs). We further investigate whether the inclusion of immunoglobulin A tissue transglutaminase (IgA tTG) and haemoglobin (Hb) data improves the interobserver agreement of diagnosis. DESIGN: We undertook a large study of the concordance in histological examination of duodenal biopsies using digitised WSIs in an entirely virtual reporting setting. Our study was organised in two phases: in phase 1, 13 pathologists independently classified 100 duodenal biopsies (40 normal; 40 CD; 20 indeterminate enteropathy) in the absence of any clinical or laboratory data. In phase 2, the same pathologists examined the (re-anonymised) WSIs with the inclusion of IgA tTG and Hb data. RESULTS: We found the mean probability of two observers agreeing in the absence of additional data to be 0.73 (±0.08) with a corresponding Cohen's kappa of 0.59 (±0.11). We further showed that the inclusion of additional data increased the concordance to 0.80 (±0.06) with a Cohen's kappa coefficient of 0.67 (±0.09). CONCLUSION: We showed that the addition of serological data significantly improves the quality of CD diagnosis. However, the limited interobserver agreement in CD diagnosis using digitised WSIs, even after the inclusion of IgA tTG and Hb data, indicates the importance of interpreting duodenal biopsy in the appropriate clinical context. It further highlights the unmet need for an objective means of reproducible duodenal biopsy diagnosis, such as the automated analysis of WSIs using artificial intelligence.

Digital pathology for reporting histopathology samples, including cancer screening samples - definitive evidence from a multisite study.

AIMS: To conduct a definitive multicentre comparison of digital pathology (DP) with light microscopy (LM) for reporting histopathology slides including breast and bowel cancer screening samples. METHODS: A total of 2024 cases (608 breast, 607 GI, 609 skin, 200 renal) were studied, including 207 breast and 250 bowel cancer screening samples. Cases were examined by four pathologists (16 study pathologists across the four speciality groups), using both LM and DP, with the order randomly assigned and 6 weeks between viewings. Reports were compared for clinical management concordance (CMC), meaning identical diagnoses plus differences which do not affect patient management. Percentage CMCs were computed using logistic regression models with crossed random-effects terms for case and pathologist. The obtained percentage CMCs were referenced to 98.3% calculated from previous studies. RESULTS: For all cases LM versus DP comparisons showed the CMC rates were 99.95% [95% confidence interval (CI) = 99.90-99.97] and 98.96 (95% CI = 98.42-99.32) for cancer screening samples. In speciality groups CMC for LM versus DP showed: breast 99.40% (99.06-99.62) overall and 96.27% (94.63-97.43) for cancer screening samples; [gastrointestinal (GI) = 99.96% (99.89-99.99)] overall and 99.93% (99.68-99.98) for bowel cancer screening samples; skin 99.99% (99.92-100.0); renal 99.99% (99.57-100.0). Analysis of clinically significant differences revealed discrepancies in areas where interobserver variability is known to be high, in reads performed with both modalities and without apparent trends to either. CONCLUSIONS: Comparing LM and DP CMC, overall rates exceed the reference 98.3%, providing compelling evidence that pathologists provide equivalent results for both routine and cancer screening samples irrespective of the modality used.

Development and validation of artificial intelligence-based prescreening of large-bowel biopsies taken in the UK and Portugal: a retrospective cohort study.

BACKGROUND: Histopathological examination is a crucial step in the diagnosis and treatment of many major diseases. Aiming to facilitate diagnostic decision making and improve the workload of pathologists, we developed an artificial intelligence (AI)-based prescreening tool that analyses whole-slide images (WSIs) of large-bowel biopsies to identify typical, non-neoplastic, and neoplastic biopsies. METHODS: This retrospective cohort study was conducted with an internal development cohort of slides acquired from a hospital in the UK and three external validation cohorts of WSIs acquired from two hospitals in the UK and one clinical laboratory in Portugal. To learn the differential histological patterns from digitised WSIs of large-bowel biopsy slides, our proposed weakly supervised deep-learning model (Colorectal AI Model for Abnormality Detection [CAIMAN]) used slide-level diagnostic labels and no detailed cell or region-level annotations. The method was developed with an internal development cohort of 5054 biopsy slides from 2080 patients that were labelled with corresponding diagnostic categories assigned by pathologists. The three external validation cohorts, with a total of 1536 slides, were used for independent validation of CAIMAN. Each WSI was classified into one of three classes (ie, typical, atypical non-neoplastic, and atypical neoplastic). Prediction scores of image tiles were aggregated into three prediction scores for the whole slide, one for its likelihood of being typical, one for its likelihood of being non-neoplastic, and one for its likelihood of being neoplastic. The assessment of the external validation cohorts was conducted by the trained and frozen CAIMAN model. To evaluate model performance, we calculated area under the convex hull of the receiver operating characteristic curve (AUROC), area under the precision-recall curve, and specificity compared with our previously published iterative draw and rank sampling (IDaRS) algorithm. We also generated heat maps and saliency maps to analyse and visualise the relationship between the WSI diagnostic labels and spatial features of the tissue microenvironment. The main outcome of this study was the ability of CAIMAN to accurately identify typical and atypical WSIs of colon biopsies, which could potentially facilitate automatic removing of typical biopsies from the diagnostic workload in clinics. FINDINGS: A randomly selected subset of all large bowel biopsies was obtained between Jan 1, 2012, and Dec 31, 2017. The AI training, validation, and assessments were done between Jan 1, 2021, and Sept 30, 2022. WSIs with diagnostic labels were collected between Jan 1 and Sept 30, 2022. Our analysis showed no statistically significant differences across prediction scores from CAIMAN for typical and atypical classes based on anatomical sites of the biopsy. At 0·99 sensitivity, CAIMAN (specificity 0·5592) was more accurate than an IDaRS-based weakly supervised WSI-classification pipeline (0·4629) in identifying typical and atypical biopsies on cross-validation in the internal development cohort (p<0·0001). At 0·99 sensitivity, CAIMAN was also more accurate than IDaRS for two external validation cohorts (p<0·0001), but not for a third external validation cohort (p=0·10). CAIMAN provided higher specificity than IDaRS at some high-sensitivity thresholds (0·7763 vs 0·6222 for 0·95 sensitivity, 0·7126 vs 0·5407 for 0·97 sensitivity, and 0·5615 vs 0·3970 for 0·99 sensitivity on one of the external validation cohorts) and showed high classification performance in distinguishing between neoplastic biopsies (AUROC 0·9928, 95% CI 0·9927-0·9929), inflammatory biopsies (0·9658, 0·9655-0·9661), and atypical biopsies (0·9789, 0·9786-0·9792). On the three external validation cohorts, CAIMAN had AUROC values of 0·9431 (95% CI 0·9165-0·9697), 0·9576 (0·9568-0·9584), and 0·9636 (0·9615-0·9657) for the detection of atypical biopsies. Saliency maps supported the representation of disease heterogeneity in model predictions and its association with relevant histological features. INTERPRETATION: CAIMAN, with its high sensitivity in detecting atypical large-bowel biopsies, might be a promising improvement in clinical workflow efficiency and diagnostic decision making in prescreening of typical colorectal biopsies. FUNDING: The Pathology Image Data Lake for Analytics, Knowledge and Education Centre of Excellence; the UK Government's Industrial Strategy Challenge Fund; and Innovate UK on behalf of UK Research and Innovation.

Complex interactions among temperature, microplastics and cyanobacteria may facilitate cyanobacteria proliferation and microplastic deposition.

Cyanobacterial blooms are a global concern prone to causing environmental and economic damages and are tightly linked to anthropogenic nutrient inputs. Likewise, microplastic pollution has also become globally ubiquitous inevitably co-occurring with blooms. However, little is known on how microplastics influence cyanobacterial physiologically and how potential physiological changes can affect their buoyancy, ultimately impacting their fate, and transport, including deposition during bloom events. Interactions of environmental relevant concentrations of high-density polyethylene microplastics (MPs) (0-0.4 mg/mL) and temperatures (2.5-32.5 °C) were evaluated to assess the effects of MPs on interactions of cyanobacteria Anabaena variabilis's growth, total organic carbon concentrations, extracellular polymeric substances (EPS) production, and MP deposition. Microplastics both stimulated and inhibited A. variabilis growth depending on the concentration. Lower MPs concentrations (0.1-0.2 mg/L) increased A. variabilis growth while higher MP concentrations (>0.3 mg/mL) impeded it across all temperatures studied. Carbon sources leached from MPs may have been a contributing factor to the increased growth at lower MPs concentration, while higher MPs concentration potentially shaded A. variabilis inhibiting its growth. Shading may have induced stress which corresponded with an observed increase in EPS production by A. variabilis when exposed to MP. Extracellular polymeric substances generation activated under adverse circumstances (MPs 0.4 mg/mL) enhanced MP deposition. Overall, our findings indicate that MPs play an important role in cyanobacterial blooms, and that these blooms may enhance MPs deposition.

IoT-based Edge Computing (IoTEC) for Improved Environmental Monitoring.

This research considered several applications of a coupled Internet of Things sensor network with Edge Computing (IoTEC) for improved environmental monitoring. Two pilot applications, covering environmental monitoring of vapor intrusion and system performance of wastewater-based algae cultivation, were designed to compare data latency, energy consumption, and economic cost between the IoTEC approach and the conventional sensor monitoring method. The results show that the IoTEC monitoring approach, compared with conventional IoT sensor networks, could significantly reduce data latency by 13%, and the amount of data transmission decreased by an average of 50%. In addition, the IoTEC method can increase the duration of power supply by 130%. Collectively, these improvements could lead to a compelling cost reduction of 55% - 82% per year for monitoring vapor intrusion at five houses, with more houses leading to more significant savings. Additionally, our results demonstrate the feasibility of deploying machine learning tools at edge servers for more advanced data processing and analysis.

Screening of normal endoscopic large bowel biopsies with interpretable graph learning: a retrospective study.

OBJECTIVE: To develop an interpretable artificial intelligence algorithm to rule out normal large bowel endoscopic biopsies, saving pathologist resources and helping with early diagnosis. DESIGN: A graph neural network was developed incorporating pathologist domain knowledge to classify 6591 whole-slides images (WSIs) of endoscopic large bowel biopsies from 3291 patients (approximately 54% female, 46% male) as normal or abnormal (non-neoplastic and neoplastic) using clinically driven interpretable features. One UK National Health Service (NHS) site was used for model training and internal validation. External validation was conducted on data from two other NHS sites and one Portuguese site. RESULTS: Model training and internal validation were performed on 5054 WSIs of 2080 patients resulting in an area under the curve-receiver operating characteristic (AUC-ROC) of 0.98 (SD=0.004) and AUC-precision-recall (PR) of 0.98 (SD=0.003). The performance of the model, named Interpretable Gland-Graphs using a Neural Aggregator (IGUANA), was consistent in testing over 1537 WSIs of 1211 patients from three independent external datasets with mean AUC-ROC=0.97 (SD=0.007) and AUC-PR=0.97 (SD=0.005). At a high sensitivity threshold of 99%, the proposed model can reduce the number of normal slides to be reviewed by a pathologist by approximately 55%. IGUANA also provides an explainable output highlighting potential abnormalities in a WSI in the form of a heatmap as well as numerical values associating the model prediction with various histological features. CONCLUSION: The model achieved consistently high accuracy showing its potential in optimising increasingly scarce pathologist resources. Explainable predictions can guide pathologists in their diagnostic decision-making and help boost their confidence in the algorithm, paving the way for its future clinical adoption.

Assessment of Mitochondrial Function and Oxygen Consumption Measured During Ex Vivo Normothermic Machine Perfusion of Injured Pig Kidneys Helps to Monitor Organ Viability.

Donor kidney assessment may improve organ utilisation. Normothermic Machine Perfusion (NMP) has the potential to facilitate this advance. The mechanism of action is not yet determined and we aimed to assess mitochondrial function during NMP. Anaesthetised pigs (n = 6) had one kidney clamped for 60 min. The healthy contralateral kidney was removed and underwent NMP for 8 h (healthy control (HC), n = 6). Following 60 min warm ischaemia the injured kidney underwent HMP for 24 h, followed by NMP for 8 h (n = 6). Mitochondria were extracted from fresh tissue for analysis. Injured kidneys were analysed as two separate groups (IMa, n = 3 and IMb, n = 3). Renal resistance was higher (0.39ï, ± 0.29 vs. 1.65ï, ± 0.85; p = 0.01) and flow was lower (55ï, ± 28 vs. 7ï, ± 4; p = 0.03) during HMP in IMb than IMa. NMP blood flow was higher in IMa versus IMb (2-way ANOVA; p < 0.001) After 60 min NMP, O2 consumption was significantly lower in IMb versus IMa (p ≤ 0.002). State-3 respiration was significantly different between the groups (37ï, ± 19 vs. 24ï, ± 14 vs. 10ï, ± 8; nmolO2/min/mg; p = 0.049). Lactate levels were significantly lower in IMa versus IMb (p = 0.028). Mitochondrial respiration levels during NMP may be suggestive of kidney viability. Oxygen consumption, renal blood flow and lactate can differentiate severity of kidney injury during NMP.

Semantic annotation for computational pathology: multidisciplinary experience and best practice recommendations.

Recent advances in whole-slide imaging (WSI) technology have led to the development of a myriad of computer vision and artificial intelligence-based diagnostic, prognostic, and predictive algorithms. Computational Pathology (CPath) offers an integrated solution to utilise information embedded in pathology WSIs beyond what can be obtained through visual assessment. For automated analysis of WSIs and validation of machine learning (ML) models, annotations at the slide, tissue, and cellular levels are required. The annotation of important visual constructs in pathology images is an important component of CPath projects. Improper annotations can result in algorithms that are hard to interpret and can potentially produce inaccurate and inconsistent results. Despite the crucial role of annotations in CPath projects, there are no well-defined guidelines or best practices on how annotations should be carried out. In this paper, we address this shortcoming by presenting the experience and best practices acquired during the execution of a large-scale annotation exercise involving a multidisciplinary team of pathologists, ML experts, and researchers as part of the Pathology image data Lake for Analytics, Knowledge and Education (PathLAKE) consortium. We present a real-world case study along with examples of different types of annotations, diagnostic algorithm, annotation data dictionary, and annotation constructs. The analyses reported in this work highlight best practice recommendations that can be used as annotation guidelines over the lifecycle of a CPath project.

Extracellular polymeric substances in green alga facilitate microplastic deposition.

Microplastics (MPs) are globally ubiquitous in sediments and surface waters. Interactions between biota and MPs are complex and influence their fate and effects in the environment. Once MPs enter aquatic systems, they are colonized by biofilms that may form from the excretion of extracellular polymeric substances (EPS) from microalgae. Biofilm accumulation may change the density of the MPs, contributing to their transport to the sediments. Furthermore, benthic plantivores may consume biofilm laden MPs allowing them to enter the food web. Thus, it is crucial to understand the role algae plays in the vertical transport of MPs in the aquatic environment. In this study, Chlamydomonas was cultured with MPs at different concentrations (0-0.4 mg/mL), and temperatures ranging from 2.5 to 32.5 °C to understand the deposition dynamics and impacts of MPs on EPS production and algal density. Temperatures ranging up to 25 °C increased algal density and MPs deposition. However, at 32.5 °C, algal density and MPs deposition declined. The quantity of MPs also affected algal cell density and EPS production. MPs concentration from 0 to 0.4 mg/mL increased EPS production at all temperatures. Similarly, an increase in algal cell density and MPs deposition occurred when MPs concentration was raised to 0.3 mg/mL. Algal cultures exposed to 0.3-0.4 mg/mL of MPs had a decrease in algal cell density, with no corresponding decline in EPS production. At certain conditions, MPs can facilitate biofilm formation by stimulating EPS production, which can increase cell density thereby expediting MPs transport to the sediment.

Pathophysiological Implications of Urinary Peptides in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is known to be associated with protein alterations and extracellular fibrous deposition. We investigated the urinary proteomic profiles of HCC patients in this prospective cross sectional multicentre study. 195 patients were recruited from the UK (Coventry) and Germany (Hannover) between 1 January 2013 and 30 June 2019. Out of these, 57 were HCC patients with a background of liver cirrhosis (LC) and 138 were non-HCC controls; 72 patients with LC, 57 with non-cirrhotic liver disease and 9 with normal liver function. Analysis of the urine samples was performed by capillary electrophoresis (CE) coupled to mass spectrometry (MS). Peptide sequences were obtained and 31 specific peptide markers for HCC were identified and further integrated into a multivariate classification model. The peptide model demonstrated 79.5% sensitivity and 85.1% specificity (95% CI: 0.81-0.93, p < 0.0001) for HCC and 4.1-fold increased risk of death (95% CI: 1.7-9.8, p = 0.0005). Proteases potentially involved in HCC progression were mapped to the N- and C-terminal sequence motifs of the CE-MS peptide markers. In silico protease prediction revealed that kallikrein-6 (KLK6) elicits increased activity, whilst Meprin A subunit α (MEP1A) has reduced activity in HCC compared to the controls. Tissue expression of KLK6 and MEP1A was subsequently verified by immunohistochemistry.

HLA Antibody Incompatible Renal Transplantation: Long-term Outcomes Similar to Deceased Donor Transplantation.

BACKGROUND: HLA incompatible renal transplantation still remains one of best therapeutic options for a subgroup of patients who are highly sensitized and difficult to match but not much is known about its long-term graft and patient survival. METHODS: One hundred thirty-four HLA incompatible renal transplantation patients from 2003 to 2018 with a median follow of 6.93 y were analyzed retrospectively to estimate patient and graft survivals. Outcomes were compared with groups defined by baseline crossmatch status and the type and timings of rejection episodes. RESULTS: The overall patient survival was 95%, 90%, and 81%; and graft survival was 95%, 85%, and 70% at 1, 5, and 10 y, respectively. This was similar to the first-time deceased donor transplant cohort. The graft survival for pretreatment cytotoxic-dependent crossmatch (CDC) positive crossmatch group was significantly low at 83%, 64%, and 40% at 1, 5, and 10 y, respectively, compared with other groups (Bead/CDC, P = 0.007; CDC/Flow, P = 0.001; and microbead assay/flow cytometry crossmatch, P = 0.837), although those with a low CDC titer (<1 in 2) have comparable outcomes to the CDC negative group. Female patients in general fared worse in both patient and graft survival outcomes in each of the 3 groups based on pretreatment crossmatch, although this did not reach statistical significance. Antibody-mediated rejection was the most frequent type of rejection with significant decline in graft survival by 10 y when compared with no rejection (P < 0.001). Rejection that occurred or continued to occur after the first 2 wk of transplantation caused a significant reduction in graft survivals (P < 0.001), whereas good outcomes were seen in those with a single early rejection episode. CONCLUSIONS: One-, 5-, and 10-y HLA incompatible graft and patient survival is comparable to deceased donor transplantation and can be further improved by excluding high-CDC titer cases. Antibody-positive female patients show worse long-term survival. Resolution of early rejection is associated with good long-term graft survival.

Fibrotic Phenotype of Peritumour Mesenteric Adipose Tissue in Human Colon Cancer: A Potential Hallmark of Metastatic Properties.

The impact of tumour associated stroma on cancer metastasis is an emerging field. However, cancer associated genes in peritumoral adipose tissue (pAT) in human colon cancer have not been explored. The aim of this study was to identify differentially expressed genes (DEGs) associated with cancer pathways in mesenteric pAT compared with adjacent adipose tissue. In total, nine patients with colon cancer pathological stage T2/T4 were employed in this study. DEGs were identified in 6 patients employing Nanostring PanCancer Pathway Panel and pathway enrichment analyses were performed. Differential expression of the 5 most up-regulated and 2 down regulated genes was validated with qRT-PCR. Results showed collagen type I alpha 1 chain (COL1A1) p = 0.007; secreted frizzled related protein (SFRP2) p = 0.057; fibroblast growth factor 7 (FGF7) not significant (ns); phospholipase A2, group IIA (PLA2G2A) ns; nerve growth factor receptor (NGFR) ns; lymphoid enhancer binding factor 1 (LEF1) p = 0.03; cadherin 1, Type 1, E-cadherin (epithelial) (CDH1) 0.09. Results have highlighted down-regulation of the Wingless/Integrated (Wnt) pathway in mesenteric pAT compared to distal adipose tissue. Highly upregulated genes in mesenteric pAT were involved in extracellular matrix (ECM)-receptor interactions and focal adhesion. Highly down regulated genes were involved in the cell cycle. Immunohistochemistry revealed differential distribution of COL1A1 showing maximum levels in tumour tissue and gradually decreasing in distant adipose tissue. COL1A1 and down regulation of Wnt pathway may have a role in local invasion and distant metastasis. COL1A1 may represent a stromal prognostic biomarker and therapeutic target in colon cancer.

Removal efficiency of micro- and nanoplastics (180 nm-125 µm) during drinking water treatment.

This study investigated the removal efficiency of micro- and nanoplastics (180 nm-125 µm) during drinking water treatment, particularly coagulation/flocculation combined with sedimentation (CFS) and granular filtration under ordinary working conditions at water treatment plants (WTPs). It also studied the interactions between biofilms and microplastics and the consequential impact on treatment efficiency. Generally, CFS was not sufficient to remove micro- and nanoplastics. The sedimentation rate of clean plastics was lower than 2.0% for all different sizes of plastic particles with coagulant Al2(SO4)3. Even with the addition of coagulant aid (PolyDADMAC), the highest removal was only 13.6% for 45-53 µm of particles. In contrast, granular filtration was much more effective at filtering out micro- and nanoplastics, from 86.9% to nearly complete removal (99.9% for particles larger than 100 µm). However, there existed a critical size (10-20 µm) where a significant lower removal (86.9%) was observed. Biofilms were easily formed on microplastics. In addition, biofilm formation significantly increased the removal efficiency of CFS treatment from <2.0% to 16.5%. This work provides new knowledge to better understand the fate and transport of emerging micro- and nanoplastic pollutants during drinking water treatment, which is of increasing concern due to the potential human exposure to micro- and nanoplastics in drinking water.

Microplastic ingestion by quagga mussels, Dreissena bugensis, and its effects on physiological processes.

The impacts of microplastic particulates in benthic freshwater organisms have been largely unexplored despite abundant plastic accumulation in the sediments of these systems. We investigated the uptake of plastic particles by benthic filter feeding quagga mussels (Dreissena bugensis) and associated toxicity exhibited through impacts on mortality, filtration rate, reproduction and oxygen consumption. Matrix Assisted Laser Desorption/Ionization Imaging Mass Spectrometry (MALDI-IMS) technology was used to assess the microplastic inclusion. For this purpose, quagga mussels were exposed to four treatments ranging from 0.0 to 0.8 g/L of a high density fluorescent red polyethylene powder in the size range of 10-45 µm for 24-h, and the targeted endpoints were quantified. Identification of several micrograms of microplastics in the digestive tract suggests rapid clearance from the water column by filtering. At the higher concentrations, about 95% of the microplastics ingested remained in the mussels after 24-h. Microplastics were found in the gills which correlated with decreasing filtration rate at higher microplastic concentrations. Despite large-scale ingestion, plastic exposure did not affect survivorship, reproduction rates, or oxygen consumption in the period examined. MALDI-IMS identified unique mass spectra that correlated with microplastic inclusion. This research suggests that microplastics can impair feeding through decreased filtration rates of filter feeding organisms, potentially resulting in a reduction of overall fitness over time and that MALDI-IMS may have the potential to identify microplastics and changes in tissue at the borders of plastic inclusion.

Identification of Optimal Calcium and Temperature Conditions for Quagga Mussel Filtration Rates as a Potential Predictor of Invasion.

Quagga mussels (Dreissena rostriformis burgensis) are a highly invasive aquatic species to North America, capable of filtering large volumes of water and causing severe ecological and economic impacts. Their range has been expanding since they first invaded the Great Lakes in the 1980s. To predict their spread, it is crucial to understand environmental parameters, which facilitate their range expansion. Two factors likely to influence their distribution include calcium and temperature, because the former is vital for shell development and the latter for metabolic activity. When these factors are optimal for mussels' fitness, the filtration rate has the potential to be maximized if other environmental conditions are also favorable, thus enabling mussels to exploit their growth potential. Deviations from optimal conditions likely result in filtration-rate decline. We identify calcium concentrations and temperatures that maximize the mussel filtration rate for 2 phytoplankton species: Ankistrodesmus facaltus, a common food source for quagga mussels, and a less palatable Microcystis icthyoblabe. In laboratory experiments, filtration rates were measured through cell counts after 24 h of filtration when exposed to a range of temperatures between 2 and 30 °C, and calcium concentrations between 0 and 180 mg/L. Response surface methodology was used to identify a maximum filtration rate, which occurred at 22 mL/mg/h at 137 mg/L of calcium carbonate and 26 °C when fed Ankistrodesmus. To establish a quagga mussel population in a new water source, optimum conditions are required; thus, this information can be used to rank the relative susceptibility of water bodies to invasion by quagga mussels. Environ Toxicol Chem 2020;39:410-418. © 2019 SETAC.

Fibroblast growth factor 7 signalling is disrupted in colorectal cancer and is a potential marker of field cancerisation.

BACKGROUND: Field cancerisation proposes that there are pre-malignant genetic mutations in the macroscopically normal mucosal tissue around colorectal cancer. This study aims to evaluate fibroblast growth factor 7 (FGF7) tissue expression in the mucosal field around colorectal cancer. METHODS: Gene and protein expression of FGF7, its receptor, FGFR2 and its downstream targets; FRS2α, Erk 1/2 and Akt was measured from mucosal samples in 34 control subjects and 17 cancer patients. Serial samples from tumour, adjacent to tumour and at the resection margin were utilised. RESULTS: FGF7 gene expression was significantly higher in tumour (2.3-fold), adjacent mucosa (3.2-fold) and resection margin (2.8-fold) of cancer patients compared with control subjects (P<0.01 respectively). However, FGFR2 was down regulated (3.5-fold) in the tumour tissue (P<0.001). Protein expression of FRS2α and Akt was significantly lower in tumour tissue compared with the resection margin in cancer patients (P<0.05 respectively). No differences in protein expression of Erk 1/2 were detected. CONCLUSIONS: FGF7 was elevated in the mucosal field of cancer patients supporting its potential as a biomarker of field cancerisation. Changes in FRS2α, Akt and Erk 1/2 expression in the tumour tissue indicate that with malignant transformation, FGF7 loses its ability to regulate cellular differentiation.

The utility of 18F-fluorodeoxyglucose positron emission tomography with computed tomography in Mycobacterium chimaera endocarditis: a case series.

BACKGROUND: Infective endocarditis secondary to Mycobacterium chimaera can present with classical constitutional symptoms of infective endocarditis but can be blood culture negative and without vegetations on transthoracic or transoesophageal echocardiogram. Patients with prosthetic valves are at particularly high risk. CASE SUMMARY: We present two patients who were diagnosed with infective endocarditis secondary to M. chimaera infection. They presented similarly with pyrexia of unknown origin and night sweats. Both patients had previously undergone aortic valve replacement; one with a tissue valve and the other with a metallic valve. New cardiac murmurs were evident on auscultation, but clinical examination showed no peripheral stigmata of endocarditis. Transoesophageal echo and transthoracic echo were both unremarkable, as were serial blood cultures. FDG PET CT scan was the key investigation, which showed increased uptake in the spleen beside other areas. Histopathology and mycobacterial cultures confirmed the diagnosis of M. chimaera infection in both cases. The first patient completed medical therapy and is now fit and well. However, the second patient unfortunately developed disseminated infection causing death. DISCUSSION: The management of M. chimaera infective endocarditis is challenging, often with delayed diagnosis and poor outcomes. In the context of negative blood cultures and inconclusive echocardiograms where there remains a high index of suspicion for endocarditis, FDG PET CT scanning can be a crucial diagnostic importance and should be considered early in patients with prosthetic valves.

Mixotrophic Microalgae Biofilm: A Novel Algae Cultivation Strategy for Improved Productivity and Cost-efficiency of Biofuel Feedstock Production.

In this work, we studied a novel algae cultivation strategy, mixotrophic microalgae biofilm, to improve the productivity and cost-efficiency of algal biofuel production. In contrast to previous methods, this improved approach can achieve high productivity at low cost by harnessing the benefits of mixotrophic growth's high efficiency, i.e., capable of subsisting on inorganic and organic carbons thus unaffected by limited light, and microalgae biofilm's low harvesting cost. Our results, as one of the first studies of this type, proved that microalgae biofilms under mixotrophic condition exhibited significantly higher productivity and quality of biofuel feedstock: 2-3 times higher of biomass yield, 2-10 times higher of lipid accumulation, and 40-60% lower of ash content when compared to microalgae biofilms under autotrophic condition. In addition, we investigated the impact of cell-surface properties (hydrophobicity and roughness) on the growth activities of microalgae biofilms and found that the productivity of mixotrophic biofilms was significantly correlated with the surface hydrophobicity. Finally, our work demonstrated the applicability of integrating this novel cultivation method with wastewater for maximum efficiency. This study opens a new possibility to solve the long-lasting challenges of algal biofuel feedstock production, i.e., low productivity and high cost of algal cultivation.

An assessment of candidate genes to assist prognosis in gastric cancer.

BACKGROUND: Gastric cancer (GC) is the fourth commonest cancer worldwide, with the second highest mortality rate. Its poor mortality is linked to delayed presentation. There is a drive towards non-invasive biomarker screening and monitoring of many different types of cancer, although with limited success so far. We aimed to determine if any genes from a 32-gene panel could be used to determine GC prognosis. METHODS: We carried out a retrospective study on the expression of 32 genes, selected for their proven or potential links to GC, on historic formalin fixed paraffin-embedded (FFPE) GC specimens from our unit. Gene expression was measured using quantitative nuclease protection assays (qNPA) technology. Following statistical analysis of the results, immunohistochemical staining for eight genes, both discriminating and non-discriminating, was conducted in seven age and sex matched non-metastatic: metastatic GC pairings. The stained samples were reviewed by two blinded consultant histopathologists. RESULTS: Multivariate Cox analysis of the gene expression data revealed metastatic status, age, sex and five genes appeared to influence GC survival. Genes negatively influencing survival included BCAS1, P53 and HSP90AA1 (relative risks 2.20, 3.73 and 7.53 respectively). Genes conveying survival benefit included CASP3 and TERT (relative risks 0.10 and 0.24 respectively). Immunohistochemical staining of seven age and sex matched non-metastatic: metastatic pairs revealed no association between gene expression and protein expression. CONCLUSIONS: Our study found several genes whose expression may affect GC prognosis. However, immunohistochemical analysis revealed no association between gene expression and protein expression. It remains to be determined whether gene expression or protein expression are reliable means of assessing GC prognosis.

Glyoxalase 1 copy number variation in patients with well differentiated gastro-entero-pancreatic neuroendocrine tumours (GEP-NET).

BACKGROUND: The glyoxalase-1 gene (GLO1) is a hotspot for copy-number variation (CNV) in human genomes. Increased GLO1 copy-number is associated with multidrug resistance in tumour chemotherapy, but prevalence of GLO1 CNV in gastro-entero-pancreatic neuroendocrine tumours (GEP-NET) is unknown. METHODS: GLO1 copy-number variation was measured in 39 patients with GEP-NET (midgut NET, n = 25; pancreatic NET, n = 14) after curative or debulking surgical treatment. Primary tumour tissue, surrounding healthy tissue and, where applicable, additional metastatic tumour tissue were analysed, using real time qPCR. Progression and survival following surgical treatment were monitored over 4.2 ± 0.5 years. RESULTS: In the pooled GEP-NET cohort, GLO1 copy-number in healthy tissue was 2.0 in all samples but significantly increased in primary tumour tissue in 43% of patients with pancreatic NET and in 72% of patients with midgut NET, mainly driven by significantly higher GLO1 copy-number in midgut NET. In tissue from additional metastases resection (18 midgut NET and one pancreatic NET), GLO1 copy number was also increased, compared with healthy tissue; but was not significantly different compared with primary tumour tissue. During mean 3 - 5 years follow-up, 8 patients died and 16 patients showed radiological progression. In midgut NET, a high GLO1 copy-number was associated with earlier progression. In NETs with increased GLO1 copy number, there was increased Glo1 protein expression compared to non-malignant tissue. CONCLUSIONS: GLO1 copy-number was increased in a large percentage of patients with GEP-NET and correlated positively with increased Glo1 protein in tumour tissue. Analysis of GLO1 copy-number variation particularly in patients with midgut NET could be a novel prognostic marker for tumour progression.