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In this paper, a nonlinear backstepping controller is proposed to manage the performance of a full-variable permanent magnet synchronous generator wind turbine. This nonlinear controller achieves a rotational speed objective for the generator and is validated through Lyapunov-based stability analysis. Additionally, this objective is accomplished without a measurement for wind speed that influences the wind torque. The proposed scheme is compared to a typical linear controller through simulation results. Simulation tests are performed to compare the response time and average error of each controller in both a drastic and realistic dynamic wind environment. These results demonstrate that the proposed controller is far more robust to wind turbulence than traditional control schemes. The simulation results of this study indicate a 1000% increase in response time and 3000% decrease in average controller error. [ABSTRACT FROM AUTHOR]

In this paper, a nonlinear controller is proposed to manage the rotational speed of a full-variable Squirrel Cage Induction Generator wind turbine. This control scheme improves upon tractional vector controllers by removing the need for a rotor flux observer. Additionally, the proposed controller manages the performance through turbulent wind conditions by accounting for unmeasurable wind torque dynamics. This model-based approach utilizes a current-based control in place of traditional voltage-mode control and is validated using a Lyapunov-based stability analysis. The proposed scheme is compared to a linear vector controller through simulation results. These results demonstrate that the proposed controller is far more robust to wind turbulence than traditional control schemes. [ABSTRACT FROM AUTHOR]

Purpose: Novel particle engineering approach was used in this study to generate high dose inhalable effervescent particles with synergistic effects against Pseudomonas aeruginosa biofilms. Methods: Spray dried co-amorphous salt of ciprofloxacin (CFX) and tartaric acid (TA) was prepared and coated with external layer of sodium bicarbonate and silica coated silver nanobeads. Design of experiments (DOE) was used to optimize physicochemical properties of particles for enhanced lung deposition. Results: Generated particles were co-amorphous CFX/TA showing that CFX lost its zwitterionic form and exhibiting distinct properties to CFX/HCl as assessed by FTIR and thermal analysis. Particles exhibited mass mean aerodynamic diameter (MMAD) of 3.3 μm, emitted dose of 78% and fine particle dose of 85%. Particles were further evaluated via antimicrobial assessment of minimum inhibitory concentrations (MIC) and minimum biofilm eradication concentration (MBEC). MIC and MBEC results showed that the hybrid particles were around 3–5 times more effective when compared to CFX signifying that synergistic effect was achieved. Diffusing wave spectroscopy results showed that the silver containing particles had a disruptive effect on rheological properties as opposed to silver free particles. Conclusions: Overall, these results showed the potential to use particle engineering to generate particles that are highly disruptive of bacterial biofilms. [ABSTRACT FROM AUTHOR]

Polyamide 6 is a widely used engineering plastic; however, its thermomechanical properties are not well understood, particularly at medium and high strain rates. In this research, the thermomechanical properties of Polyamide 6 were extensively characterized. Differential Scanning Calorimetry was performed to investigate the glass transition temperature and crystallinity. Frequency sweep Dynamic Mechanical Analysis was carried out through the secondary- and glass-transitions, and the temperature dependent storage moduli obtained from different sweep frequencies were used to construct a master curve. Quasi-static tensile tests at two loading speeds were conducted with digital image correlation for full-field strain mapping. Compression properties were measured at strain rates between 0.001 and 6000 s−1 at room temperature, and temperatures between −60 and 200 °C at 0.01 s−1. The mechanical response is highly rate- and temperature-dependent; at large strains and elevated rates, apparent softening occurs owing to heat generation, which was quantified using an infrared camera. [Display omitted] • Polyamide 6 characterised from −60 to 200 °C and 0.001–6000 s−1 in compression. • Tensile tests performed with digital image correlation. • High speed infrared camera measured temperature rise in compression. • Time-temperature equivalence gives insights into rate dependence. [ABSTRACT FROM AUTHOR]

Polyamide 6 and its composites are widely used in engineering applications that are exposed to high strain rate deformation. This paper investigates the thermomechanical properties of two polyamide 6 composites, both reinforced with 30 wt% short glass fibres, and one of which additionally contains an impact modifier, to provide an understanding of the mechanical response over a wide range of strain rates and temperatures. Compression experiments were performed at rates between 2 and 3000 s−1, with high speed optical and infrared cameras to aid interpretation of the rate-dependent failure arising from the formation of adiabatic shear bands. Further high strain rate experiments were performed with ultra-fast X-ray phase-contrast imaging to provide in-situ internal damage evaluation. These data will improve the utilization of these composites and aid in development of advanced thermomechanical models. [ABSTRACT FROM AUTHOR]

Computational pathology is a rapidly expanding area for research due to the current global transformation of histopathology through the adoption of digital workflows. Survival prediction of breast cancer patients is an important task that currently depends on histopathology assessment of cancer morphological features, immunohistochemical biomarker expression and patient clinical findings. To facilitate the manual process of survival risk prediction, we developed a computational pathology framework for survival prediction using digitally scanned haematoxylin and eosin-stained tissue microarray images of clinically aggressive triple negative breast cancer. Our results show that the model can produce an average concordance index of 0.616. Our model predictions are analysed for independent prognostic significance in univariate analysis (hazard ratio = 3.12, 95% confidence interval [1.69,5.75], p < 0.005) and multivariate analysis using clinicopathological data (hazard ratio = 2.68, 95% confidence interval [1.44,4.99], p < 0.005). Through qualitative analysis of heatmaps generated from our model, an expert pathologist is able to associate tissue features highlighted in the attention heatmaps of high-risk predictions with morphological features associated with more aggressive behaviour such as low levels of tumour infiltrating lymphocytes, stroma rich tissues and high-grade invasive carcinoma, providing explainability of our method for triple negative breast cancer. [ABSTRACT FROM AUTHOR]

Persons who have hypermethylation of one allele of MLH1 in somatic cells throughout the body (a germ-line epimutation) have a predisposition for the development of cancer in a pattern typical of hereditary nonpolyposis colorectal cancer. By studying the families of two such persons, we found evidence that the epimutation was transmitted from a mother to her son but was erased in his spermatozoa. The affected maternal allele was inherited by three other siblings from these two families, but in those offspring the allele had reverted to the normal active state. These findings demonstrate a novel pattern of inheritance of cancer susceptibility and are consistent with transgenerational epigenetic inheritance. [ABSTRACT FROM AUTHOR]

Genetic alterations in tumor cells often lead to the emergence of growth-stimulatory autocrine and paracrine signals, involving overexpression of secreted peptide growth factors, cytokines, and hormones. Increased levels of these soluble proteins may be exploited for cancer diagnosis and management or as points of therapeutic intervention. Here, we combined the use of controlled vocabulary terms and sequence-based algorithms to predict genes encoding secreted proteins from among ≈12,500 sequences represented on oligonucleotide microarrays. Expression of these genes was queried in 150 carcinomas from 10 anatomic sites of origin and compared with 46 normal tissues derived from the corresponding sites of tumor origin and other body tissues and organs. Of 74 different genes identified as overexpressed in cancer tissues, several encode proteins with demonstrated clinical diagnostic application, such as α-fetoprotein in liver carcinoma, and kallikreins 6 and 10 in ovarian cancer, or therapeutic utility, such as gastrin-releasing peptide/bombesin in lung carcinomas. We show that several of the other candidate genes encode proteins with high levels of tumor-associated expression by immunohistochemistry on tissue microarrays and further demonstrate significantly elevated levels of another novel candidate protein, macrophage inhibitory cytokine 1, a distant member of the tranforming growth factor-β superfamily, in the serum of patients with metastatic prostate, breast, and colorectal carcinomas. Our results suggest that the combination of annotation/protein sequence analysis, transcript profiling, immunohistochemistry, and immunoassay is a powerful approach for delineating candidate biomarkers with potential clinical significance and may be broadly applicable to other human diseases. [ABSTRACT FROM AUTHOR]

• A Whole Slide Images-based survival model is proposed which doesn't need ROI annotations. • The proposed model is more adaptive and flexible than recent WSI-based survival learning approaches. • The proposed approach has better interpretability in locating important patterns that contribute to accurate cancer survival predictions. Traditional image-based survival prediction models rely on discriminative patch labeling which make those methods not scalable to extend to large datasets. Recent studies have shown Multiple Instance Learning (MIL) framework is useful for histopathological images when no annotations are available in classification task. Different to the current image-based survival models that limit to key patches or clusters derived from Whole Slide Images (WSIs), we propose Deep Attention Multiple Instance Survival Learning (DeepAttnMISL) by introducing both siamese MI-FCN and attention-based MIL pooling to efficiently learn imaging features from the WSI and then aggregate WSI-level information to patient-level. Attention-based aggregation is more flexible and adaptive than aggregation techniques in recent survival models. We evaluated our methods on two large cancer whole slide images datasets and our results suggest that the proposed approach is more effective and suitable for large datasets and has better interpretability in locating important patterns and features that contribute to accurate cancer survival predictions. The proposed framework can also be used to assess individual patient's risk and thus assisting in delivering personalized medicine. Image, graphical abstract [ABSTRACT FROM AUTHOR]

Electrospinning has been applied to produce ceramic fibers using sol gel-based spinning solutions consisting of ceramic precursors, a solvent, and a polymer to control the viscosity of the solution. However, the addition of polymers to the spinning solution makes the process more complex, increases the processing time, and results in porous mechanically weak ceramic fibers. Herein, we develop a coelectrospinning technique, where a nonspinnable sol (<10 mPa s) consisting of only the ceramic precursor(s) and solvent(s) is encapsulated inside a polymeric shell, forming core-shell precursor fibers that are further calcined into ceramic fibers with reduced porosity, decreased surface defects, uniform crystal packing, and controlled diameters. We demonstrate the versatility of this method by applying it to a series of nonspinnable sols and creating high-quality ceramic fibers containing TiO 2 , ZrO 2 , SiO 2 , and Al 2 O 3 . The polycrystalline TiO 2 fibers possess excellent flexibility and a high Young's modulus reaching 54.3 MPa, solving the extreme brittleness problem of the previously reported TiO 2 fibers. The single-component ZrO 2 fibers exhibit a Young's modulus and toughness of 130.5 MPa and 11.9 KJ/m 3 , respectively, significantly superior to the counterparts prepared by conventional sol-gel electrospinning. We also report the creation of ceramic fibers in micro- and nanospring morphologies and examine the formation mechanisms using thermomechanical simulations. The fiber assemblies constructed by the helical fibers exhibit a density-normalized toughness of 3.5-5 times that of the straight fibers due to improved fracture strain. This work expands the selection of the electrospinning solution and enables the development of ceramic fibers with more attractive properties.

Polymeric materials are widely used in industries ranging from automotive to biomedical. Their mechanical properties play a crucial role in their application and function and arise from the nanoscale structures and interactions of their constitutive polymer molecules. Polymeric materials behave viscoelastically, i.e., their mechanical responses depend on the time scale of the measurements; quantifying these time-dependent rheological properties at the nanoscale is relevant to develop, for example, accurate models and simulations of those materials, which are needed for advanced industrial applications. In this paper, an atomic force microscopy (AFM) method based on the photothermal actuation of an AFM cantilever is developed to quantify the nanoscale loss tangent, storage modulus, and loss modulus of polymeric materials. The method is then validated on styrene-butadiene rubber (SBR), demonstrating the method's ability to quantify nanoscale viscoelasticity over a continuous frequency range up to 5 orders of magnitude (0.2-20,200 Hz). Furthermore, this method is combined with AFM viscoelastic mapping obtained with amplitude modulation-frequency modulation (AM-FM) AFM, enabling the extension of viscoelastic quantification over an even broader frequency range and demonstrating that the novel technique synergizes with preexisting AFM techniques for quantitative measurement of viscoelastic properties. The method presented here introduces a way to characterize the viscoelasticity of polymeric materials and soft and biological matter in general at the nanoscale for any application., Competing Interests: The authors declare no competing financial interest., (© 2024 The Authors. Published by American Chemical Society.)

Background: Precise prognosis prediction in patients with colorectal cancer (ie, forecasting survival) is pivotal for individualised treatment and care. Histopathological tissue slides of colorectal cancer specimens contain rich prognostically relevant information. However, existing studies do not have multicentre external validation with real-world sample processing protocols, and algorithms are not yet widely used in clinical routine., Methods: In this retrospective, multicentre study, we collected tissue samples from four groups of patients with resected colorectal cancer from Australia, Germany, and the USA. We developed and externally validated a deep learning-based prognostic-stratification system for automatic prediction of overall and cancer-specific survival in patients with resected colorectal cancer. We used the model-predicted risk scores to stratify patients into different risk groups and compared survival outcomes between these groups. Additionally, we evaluated the prognostic value of these risk groups after adjusting for established prognostic variables., Findings: We trained and validated our model on a total of 4428 patients. We found that patients could be divided into high-risk and low-risk groups on the basis of the deep learning-based risk score. On the internal test set, the group with a high-risk score had a worse prognosis than the group with a low-risk score, as reflected by a hazard ratio (HR) of 4·50 (95% CI 3·33-6·09) for overall survival and 8·35 (5·06-13·78) for disease-specific survival (DSS). We found consistent performance across three large external test sets. In a test set of 1395 patients, the high-risk group had a lower DSS than the low-risk group, with an HR of 3·08 (2·44-3·89). In two additional test sets, the HRs for DSS were 2·23 (1·23-4·04) and 3·07 (1·78-5·3). We showed that the prognostic value of the deep learning-based risk score is independent of established clinical risk factors., Interpretation: Our findings indicate that attention-based self-supervised deep learning can robustly offer a prognosis on clinical outcomes in patients with colorectal cancer, generalising across different populations and serving as a potentially new prognostic tool in clinical decision making for colorectal cancer management. We release all source codes and trained models under an open-source licence, allowing other researchers to reuse and build upon our work., Funding: The German Federal Ministry of Health, the Max-Eder-Programme of German Cancer Aid, the German Federal Ministry of Education and Research, the German Academic Exchange Service, and the EU., Competing Interests: Declaration of interests JNK has received consulting fees from Owkin; DoMore Diagnostics; Panakeia; and Histofy; furthermore, JNK holds shares and holds a leadership role in StratifAI and has received honoraria for lectures by Bayer, Eisai, Merck Sharp & Dohme (MSD), Bristol-Myers Squibb (BMS), Roche, Pfizer, and Fresenius and has participated on a Data Safety Monitoring Board or Advisory Board for Bayer, Eisai, MSD, BMS, Roche, and Pfizer. PQ and NPW declare research funding from Roche and PQ consulting and speaker services for Roche. JJ declares consulting fees from WHO (Development of Digital Health Solution) and CARE International, Papua New Guinea (Development of Survey Instruments). SF declares grants and contracts from Bundesministerium für Bildung und Forschung, Deutsche Forschungsgemeinschaft, and German Cancer Aid, and payment or honoraria from BMS, MSD, European Society for Medical Oncology, and Deutsche Gesellschaft für Pathologie. DT holds shares in StratifAI. WM is a shareholder of Gemeinschaftspraxis Pathologie Starnberg, a private pathology practice in Germany. All other authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Deep learning (DL) can accelerate the prediction of prognostic biomarkers from routine pathology slides in colorectal cancer (CRC). However, current approaches rely on convolutional neural networks (CNNs) and have mostly been validated on small patient cohorts. Here, we develop a new transformer-based pipeline for end-to-end biomarker prediction from pathology slides by combining a pre-trained transformer encoder with a transformer network for patch aggregation. Our transformer-based approach substantially improves the performance, generalizability, data efficiency, and interpretability as compared with current state-of-the-art algorithms. After training and evaluating on a large multicenter cohort of over 13,000 patients from 16 colorectal cancer cohorts, we achieve a sensitivity of 0.99 with a negative predictive value of over 0.99 for prediction of microsatellite instability (MSI) on surgical resection specimens. We demonstrate that resection specimen-only training reaches clinical-grade performance on endoscopic biopsy tissue, solving a long-standing diagnostic problem., Competing Interests: Declaration of interests J.N.K. reports consulting services for Owkin, France, Panakeia, UK, and DoMore Diagnostics, Norway and has received honoraria for lectures by M.S.D., Eisai, and Fresenius. N.W. has received fees for advisory board activities with BMS, Astellas, GSK, and Amgen, not related to this study. N.W. has received fees for advisory board activities with BMS, Astellas, and Amgen, not related to this study. P.Q. has received fees for advisory board activities with Roche and AMGEN and research funding from Roche through an Innovate UK National Pathology Imaging Consortium grant. H.I.G. has received fees for advisory board activities by AstraZeneca and BMS, not related to this study. M.S.T. is a scientific advisor to Mindpeak and Sonrai Analytics, and has received honoraria recently from BMS, MSD, Roche, Sanofi, and Incyte. He has received grant support from Phillips, Roche, MSD, and Akoya. None of these disclosures are related to this work. D.N.C. has participated in advisory boards for MSD and has received research funding on behalf of the TransSCOT consortium from HalioDx for analyses independent of this study. V.H.K. has served as an invited speaker on behalf of Indica Labs and has received project-based research funding from The Image Analysis Group and Roche outside of the submitted work. No other potential disclosures are reported by any of the authors., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background & Aims: Dysbiosis of gut microbiota is linked to the development of colorectal cancer (CRC). However, microbiota-based stratification of CRC tissue and how this relates to clinicomolecular characteristics and prognosis remains to be clarified., Methods: Tumor and normal mucosa from 423 patients with stage I to IV CRC were profiled by bacterial 16S rRNA gene sequencing. Tumors were characterized for microsatellite instability (MSI), CpG island methylator phenotype (CIMP), APC, BRAF, KRAS, PIK3CA, FBXW7, SMAD4, and TP53 mutations, subsets for chromosome instability (CIN), mutation signatures, and consensus molecular subtypes (CMS). Microbial clusters were validated in an independent cohort of 293 stage II/III tumors., Results: Tumors reproducibly stratified into 3 oncomicrobial community subtypes (OCSs) with distinguishing features: OCS1 (Fusobacterium/oral pathogens, proteolytic, 21%), right-sided, high-grade, MSI-high, CIMP-positive, CMS1, BRAF V600E, and FBXW7 mutated; OCS2 (Firmicutes/Bacteroidetes, saccharolytic, 44%), and OCS3 (Escherichia/Pseudescherichia/Shigella, fatty acid β-oxidation, 35%) both left-sided and exhibiting CIN. OCS1 was associated with MSI-related mutation signatures (SBS15, SBS20, ID2, and ID7) and OCS2 and OCS3 with SBS18 related to damage by reactive oxygen species. Among stage II/III patients, OCS1 and OCS3 both had poorer overall survival compared with OCS2 for microsatellite stable tumors (multivariate hazard ratio [HR], 1.85; 95% confidence interval [CI], 1.15-2.99; P = .012; and HR, 1.52; 95% CI 1.01-2.29; P = .044, respectively) and left-sided tumors (multivariate HR, 2.66; 95% CI, 1.45-4.86; P = .002; and HR, 1.76; 95% CI, 1.03-3.02; P = .039, respectively)., Conclusions: OCS classification stratified CRCs into 3 distinct subgroups with different clinicomolecular features and outcomes. Our findings provide a framework for a microbiota-based stratification of CRC to refine prognostication and to inform the development of microbiota-targeted interventions., (Copyright © 2023 AGA Institute. All rights reserved.)

Achieving the long-term stability of perovskite solar cells is arguably the most important challenge required to enable widespread commercialization. Understanding the perovskite crystallization process and its direct impact on device stability is critical to achieving this goal. The commonly employed dimethyl-formamide/dimethyl-sulfoxide solvent preparation method results in a poor crystal quality and microstructure of the polycrystalline perovskite films. In this work, we introduce a high-temperature dimethyl-sulfoxide-free processing method that utilizes dimethylammonium chloride as an additive to control the perovskite intermediate precursor phases. By controlling the crystallization sequence, we tune the grain size, texturing, orientation (corner-up versus face-up) and crystallinity of the formamidinium (FA)/caesium (FA) y Cs 1-y Pb(I x Br 1-x ) 3 perovskite system. A population of encapsulated devices showed improved operational stability, with a median T80 lifetime (the time over which the device power conversion efficiency decreases to 80% of its initial value) for the steady-state power conversion efficiency of 1,190 hours, and a champion device showed a T80 of 1,410 hours, under simulated sunlight at 65 °C in air, under open-circuit conditions. This work highlights the importance of material quality in achieving the long-term operational stability of perovskite optoelectronic devices., (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)

Purpose: Advanced-stage mucinous ovarian carcinoma (MOC) has poor chemotherapy response and prognosis and lacks biomarkers to aid stage I adjuvant treatment. Differentiating primary MOC from gastrointestinal (GI) metastases to the ovary is also challenging due to phenotypic similarities. Clinicopathologic and gene-expression data were analyzed to identify prognostic and diagnostic features., Experimental Design: Discovery analyses selected 19 genes with prognostic/diagnostic potential. Validation was performed through the Ovarian Tumor Tissue Analysis consortium and GI cancer biobanks comprising 604 patients with MOC (n = 333), mucinous borderline ovarian tumors (MBOT, n = 151), and upper GI (n = 65) and lower GI tumors (n = 55)., Results: Infiltrative pattern of invasion was associated with decreased overall survival (OS) within 2 years from diagnosis, compared with expansile pattern in stage I MOC [hazard ratio (HR), 2.77; 95% confidence interval (CI), 1.04-7.41, P = 0.042]. Increased expression of THBS2 and TAGLN was associated with shorter OS in MOC patients (HR, 1.25; 95% CI, 1.04-1.51, P = 0.016) and (HR, 1.21; 95% CI, 1.01-1.45, P = 0.043), respectively. ERBB2 (HER2) amplification or high mRNA expression was evident in 64 of 243 (26%) of MOCs, but only 8 of 243 (3%) were also infiltrative (4/39, 10%) or stage III/IV (4/31, 13%)., Conclusions: An infiltrative growth pattern infers poor prognosis within 2 years from diagnosis and may help select stage I patients for adjuvant therapy. High expression of THBS2 and TAGLN in MOC confers an adverse prognosis and is upregulated in the infiltrative subtype, which warrants further investigation. Anti-HER2 therapy should be investigated in a subset of patients. MOC samples clustered with upper GI, yet markers to differentiate these entities remain elusive, suggesting similar underlying biology and shared treatment strategies., (©2022 The Authors; Published by the American Association for Cancer Research.)

Mucinous colorectal adenocarcinoma (CRC) is conventionally defined by extracellular mucin comprising >50% of the tumour area, while tumours with ≤50% mucin are designated as having a mucinous component. However, these definitions are largely arbitrary and comparisons of clinico-molecular features and outcomes by proportion of mucinous component are limited. A cohort of 1643 patients with stage II/III cancer was examined for tumour mucinous component, DNA mismatch repair (MMR) status, BRAF mutation and tumour infiltrating lymphocytes (TILs). Tumours with ≤50% mucinous component exhibited similar characteristics as mucinous tumours, including association with female gender, proximal location, high grade, TIL-high, defective MMR (dMMR) and BRAF mutation. Proportion of mucinous component did not stratify disease-free survival (DFS). In univariate analysis dMMR status, but not histological grade, stratified survival for mucinous and mucinous component tumours; however, in multivariate analysis dMMR status was not an independent predictor. BRAF mutation prognostic value depended on mucinous differentiation and MMR status, with poor prognosis limited to non-mucinous pMMR tumours (HR 2.61, 95% CI 1.69-4.03; p < 0.001). TIL status was a strong independent predictor of DFS in mucinous/mucinous component tumours (HR 0.40, 95% CI 0.23-0.67; p < 0.001), and a superior predictor of prognosis compared with histological grade, MMR and BRAF mutation. Mucinous component and mucinous stage II/III CRCs exhibit clinico-molecular resemblances, with histological grade and BRAF mutation lacking prognostic value. Prognosis for these tumours was instead strongly associated with TIL status, with the most favourable outcomes in TIL-high dMMR tumours, whilst TIL-low tumours had poor outcomes irrespective of MMR status.

Purpose: MLH1 is a major tumor suppressor gene involved in the pathogenesis of Lynch syndrome and various sporadic cancers. Despite their potential pathogenic importance, genomic regions capable of regulating MLH1 expression over long distances have yet to be identified. Experimental Design: Here, we use chromosome conformation capture (3C) to screen a 650-kb region flanking the MLH1 locus to identify interactions between the MLH1 promoter and distal regions in MLH1 -expressing and nonexpressing cells. Putative enhancers were functionally validated using luciferase reporter assays, chromatin immunoprecipitation, and CRISPR-Cas9-mediated deletion of endogenous regions. To evaluate whether germline variants in the enhancer might contribute to impaired MLH1 expression in patients with suspected Lynch syndrome, we also screened germline DNA from a cohort of 74 patients with no known coding mutations or epimutations at the MLH1 promoter. Results: A 1.8-kb DNA fragment, 35 kb upstream of the MLH1 transcription start site enhances MLH1 gene expression in colorectal cells. The enhancer was bound by CTCF and CRISPR-Cas9-mediated deletion of a core binding region impairs endogenous MLH1 expression. A total of 5.4% of suspected Lynch syndrome patients have a rare single-nucleotide variant (G > A; rs143969848; 2.5% in gnomAD European, non-Finnish) within a highly conserved CTCF-binding motif, which disrupts enhancer activity in SW620 colorectal carcinoma cells. Conclusions: A CTCF-bound region within the MLH1 -35 enhancer regulates MLH1 expression in colorectal cells and is worthy of scrutiny in future genetic screening strategies for suspected Lynch syndrome associated with loss of MLH1 expression. Clin Cancer Res; 24(18); 4602-11. ©2018 AACR ., (©2018 American Association for Cancer Research.)

Background: Molecular indicators of colorectal cancer prognosis have been assessed in several studies, but most analyses have been restricted to a handful of markers. We aimed to identify prognostic biomarkers for colorectal cancer by sequencing panels of multiple driver genes., Methods: In stage II or III colorectal cancers from the QUASAR 2 open-label randomised phase 3 clinical trial and an Australian community-based series, we used targeted next-generation sequencing of 82 and 113 genes, respectively, including the main colorectal cancer drivers. We investigated molecular pathways of tumorigenesis, and analysed individual driver gene mutations, combinations of mutations, or global measures such as microsatellite instability (MSI) and mutation burden (total number of non-synonymous mutations and coding indels) for associations with relapse-free survival in univariable and multivariable models, principally Cox proportional hazards models., Findings: In QUASAR 2 (511 tumours), TP53, KRAS, BRAF, and GNAS mutations were independently associated with shorter relapse-free survival (p<0·035 in all cases), and total somatic mutation burden with longer survival (hazard ratio [HR] 0·81 [95% CI 0·68-0·96]; p=0·014). MSI was not independently associated with survival (HR 1·12 [95% CI 0·57-2·19]; p=0·75). We successfully validated these associations in the Australian sample set (296 tumours). In a combined analysis of both the QUASAR 2 and the Australian sample sets, mutation burden was also associated with longer survival (HR 0·84 [95% CI 0·74-0·94]; p=0·004) after exclusion of MSI-positive and POLE mutant tumours. In an extended analysis of 1732 QUASAR 2 and Australian colorectal cancers for which KRAS, BRAF, and MSI status were available, KRAS and BRAF mutations were specifically associated with poor prognosis in MSI-negative cancers. MSI-positive cancers with KRAS or BRAF mutations had better prognosis than MSI-negative cancers that were wild-type for KRAS or BRAF. Mutations in the genes NF1 and NRAS from the MAPK pathway co-occurred, and mutations in the DNA damage-response genes TP53 and ATM were mutually exclusive. We compared a prognostic model based on the gold standard of clinicopathological variables and MSI with our new model incorporating clinicopathological variables, mutation burden, and driver mutations in KRAS, BRAF, and TP53. In both QUASAR 2 and the Australian cohort, our new model was significantly better (p=0·00004 and p=0·0057, respectively, based on a likelihood ratio test)., Interpretation: Multigene panels identified two previously unreported prognostic associations in colorectal cancer involving TP53 mutation and total mutation burden, and confirmed associations with KRAS and BRAF. Even a modest-sized gene panel can provide important information for use in clinical practice and outperform MSI-based prognostic models., Funding: UK Technology Strategy Board, National Institute for Health Research Oxford Biomedical Research Centre, Cancer Australia Project, Cancer Council Victoria, Ludwig Institute for Cancer Research, Victorian Government., (Copyright © 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

The Wnt signalling receptor receptor tyrosine kinase-like orphan receptor 2 (ROR2) is implicated in numerous human cancers. However, there have been conflicting reports regarding ROR2 expression, some studies showing upregulation and others downregulation of ROR2 in the same cancer type. The majority of these studies used immunohistochemistry (IHC) to detect ROR2 protein, without validation of the used antibodies. There appears to be currently no consensus on the antibody best suited for ROR2 detection or how ROR2 expression changes in various cancer types. We examined three commercially available ROR2 antibodies and found that only one bound specifically to ROR2. Another antibody cross-reacted with other proteins, and the third failed to detect ROR2 at all. ROR2 detection by IHC on 107 patient samples using the ROR2 specific antibody showed that the majority of colorectal cancers show loss of ROR2 protein. We found no association between ROR2 staining and poor patient survival, as had been previously reported. These results question the previously reported association between ROR2 and poor patient survival in colorectal cancer. Future studies should use fully validated antibodies when detecting ROR2 protein, as non-specific staining can lead to irrelevant observations and misinterpretations.

Rationale and Objectives: Diagnostic imaging is under-represented in medical curricula globally. Adaptive tutorials, online intelligent tutoring systems that provide a personalized learning experience, have the potential to bridge this gap. However, there is limited evidence of their effectiveness for learning about diagnostic imaging., Materials and Methods: We performed a randomized mixed methods crossover trial to determine the impact of adaptive tutorials on perceived engagement and understanding of the appropriate use and interpretation of common diagnostic imaging investigations. Although concurrently engaged in disparate blocks of study, 99 volunteer medical students (from years 1-4 of the 6-year program) were randomly allocated to one of two groups. In the first arm of the trial on chest X-rays, one group received access to an adaptive tutorial, whereas the other received links to an existing peer-reviewed Web resource. These two groups crossed over in the second arm of the trial, which focused on computed tomography scans of the head, chest, and abdomen. At the conclusion of each arm of the trial, both groups completed an examination-style assessment, comprising questions both related and unrelated to the topics covered by the relevant adaptive tutorial. Online questionnaires were used to evaluate student perceptions of both learning resources., Results: In both arms of the trial, the group using adaptive tutorials obtained significantly higher assessment scores than controls. This was because of higher assessment scores by senior students in the adaptive tutorial group when answering questions related to topics covered in those tutorials. Furthermore, students indicated significantly better engagement with adaptive tutorials than the Web resource and rated the tutorials as a significantly more valuable tool for learning., Conclusions: Medical students overwhelmingly accept adaptive tutorials for diagnostic imaging. The tutorials significantly improve the understanding of diagnostic imaging by senior students., (Crown Copyright © 2015. Published by Elsevier Inc. All rights reserved.)

Background: The tumour suppressor gene 'mutated in colorectal cancer' (MCC) is silenced through promoter methylation in colorectal cancer and has been implicated as a regulator of the nuclear factor kappa B (NFκB) pathway. Therefore, we aimed to determine whether MCC modulates NFκB activation in colorectal cancer., Materials and Methods: NFκB activation was assessed using luciferase reporter assays in colorectal cancer cells in vitro. MCC methylation was analysed in primary tumour specimens from patients with inflammatory bowel disease., Results: Re-expression of MCC reduced NFκB-dependent transcription in tumour necrosis factor alpha (TNFα)- or lipopolysaccharide (LPS)-stimulated cells. Conversely, knockdown of MCC resulted in accumulation of the inhibitor of kappa B alpha (IκBα) protein, encoded by NFKBIA, a first response gene specifically and rapidly regulated by NFκB pathway activation. The MCC gene is methylated in up to 6/16 of inflammatory bowel disease-associated tissue specimens, and myosin-10 and valosin-containing protein were identified as MCC-interacting proteins., Conclusion: These findings suggest that MCC modulates NFκB pathway signalling indirectly in colorectal cancer cells.

Lynch syndrome is an autosomal dominant cancer susceptibility syndrome characterized by the early development of microsatellite unstable colorectal, endometrial and other cancers. Lynch syndrome is caused by germline heterozygous loss-of-function sequence mutations within the mismatch repair genes MLH1, MSH2, MSH6 or PMS2. Some individuals with Lynch syndrome have constitutional epimutations, characterized by promoter methylation and transcriptional inactivation of a single allele in normal somatic tissues, while others lack identifiable pathogenic changes in the germline. We hypothesized that analysis of the relative levels of allelic expression of MLH1 would assist in the identification of cryptic pathogenic defects of MLH1 in five presumed Lynch syndrome cases whose tumours demonstrated MLH1 loss, but whose causative mutation remained unidentified. We exploited the common benign c.655A>G SNP (rs1799977) within MLH1 exon 8 to distinguish between the two genetic alleles in heterozygous individuals and to study their transcriptional activity, using quantitative pyrosequencing assays. In one of the five patients we detected loss of expression of one allele and deletion of the other allele in the tumour, prompting renewed germline screening. A novel intronic splice mutation was subsequently identified, which resulted in loss of an entire exon from the transcript. This pyrosequencing assay also proved useful in demonstrating the gradual reversal of a constitutional MLH1 epimutation during lymphoblastoid cell culture, suggesting this defect may not be stably maintained in immortalized cells. Our findings illustrate that the study of allelic behaviour can complement conventional molecular analyses by providing new insight into the genetic or epigenetic mechanisms underlying disease.

Purpose: Macrophage inhibitory cytokine-1 (MIC-1) is a divergent member of the tumor growth factor beta (TGF-beta) superfamily. Several observations suggest that it plays a role in colorectal carcinoma (CRC). In particular, MIC-1 is markedly up-regulated in colorectal cancers as well as in premalignant adenomas. This study examines the relationship of serum MIC-1 levels and genotypes to clinical and pathologic features of colonic neoplasia., Experimental Design: We confirmed the presence of MIC-1 in CRC tissue and the cell line CaCo-2. The normal range for serum MIC-1 levels was defined in 260 healthy blood donors, and the differences between normal subjects and 193 patients having adenomatous polyps or CRC were then determined. In a separate cohort of 224 patients, we evaluated the relationship of MIC-1 serum level and genotype to standard tumor parameters and outcome measures., Results: MIC-1 was expressed in CRC tissue and the cancer cell line CaCo-2. There was a progressive increase in serum MIC-1 levels between normal individuals [mean (M) = 495 pg/ml, SD = 210), those with adenomatous polyps (M = 681 pg/ml, SD = 410), and those with CRC (M = 783 pg/ml, SD = 491)]. Serum MIC-1 level was correlated with the extent of disease so that the levels were higher in patients with higher Tumor-Node-Metastasis stage. There were significant differences in time to relapse and overall survival between subjects with different MIC-1 levels and genotypes., Conclusions: This study identifies a strong association between MIC-1 serum levels and neoplastic progression within the large bowel. We suggest that the measurement of serum MIC-1 levels and determination of MIC-1 genotype may have clinical use in the management of patients with CRC.