Knowledge discovery for friction stir welding via data driven approaches: Part 2 – multiobjective modelling using fuzzy rule based systems

In this final part of this extensive study, a new systematic data-driven fuzzy modelling approach has been developed, taking into account both the modelling accuracy and its interpretability (transparency) as attributes. For the first time, a data-driven modelling framework has been proposed designed and implemented in order to model the intricate FSW behaviours relating to AA5083 aluminium alloy, consisting of the grain size, mechanical properties, as well as internal process properties. As a result, ‘Pareto-optimal’ predictive models have been successfully elicited which, through validations on real data for the aluminium alloy AA5083, have been shown to be accurate, transparent and generic despite the conservative number of data points used for model training and testing. Compared with analytically based methods, the proposed data-driven modelling approach provides a more effective way to construct prediction models for FSW when there is an apparent lack of fundamental process knowledge

Haemophagocytic lymphohistiocytosis: An uncommon clinical presentation of tuberculosis

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UNCLES: Method for the identification of genes differentially consistently co-expressed in a specific subset of datasets

Background: Collective analysis of the increasingly emerging gene expression datasets are required. The recently proposed binarisation of consensus partition matrices (Bi-CoPaM) method can combine clustering results from multiple datasets to identify the subsets of genes which are consistently co-expressed in all of the provided datasets in a tuneable manner. However, results validation and parameter setting are issues that complicate the design of such methods. Moreover, although it is a common practice to test methods by application to synthetic datasets, the mathematical models used to synthesise such datasets are usually based on approximations which may not always be sufficiently representative of real datasets. Results: Here, we propose an unsupervised method for the unification of clustering results from multiple datasets using external specifications (UNCLES). This method has the ability to identify the subsets of genes consistently co-expressed in a subset of datasets while being poorly co-expressed in another subset of datasets, and to identify the subsets of genes consistently co-expressed in all given datasets. We also propose the M-N scatter plots validation technique and adopt it to set the parameters of UNCLES, such as the number of clusters, automatically. Additionally, we propose an approach for the synthesis of gene expression datasets using real data profiles in a way which combines the ground-truth-knowledge of synthetic data and the realistic expression values of real data, and therefore overcomes the problem of faithfulness of synthetic expression data modelling. By application to those datasets, we validate UNCLES while comparing it with other conventional clustering methods, and of particular relevance, biclustering methods. We further validate UNCLES by application to a set of 14 real genome-wide yeast datasets as it produces focused clusters that conform well to known biological facts. Furthermore, in-silico-based hypotheses regarding the function of a few previously unknown genes in those focused clusters are drawn. Conclusions: The UNCLES method, the M-N scatter plots technique, and the expression data synthesis approach will have wide application for the comprehensive analysis of genomic and other sources of multiple complex biological datasets. Moreover, the derived in-silico-based biological hypotheses represent subjects for future functional studies.The National Institute for Health Research (NIHR) under its Programme Grants for Applied Research Programme (Grant Reference Number RP-PG-0310-1004)

Combined immunohistochemistry of β-catenin, cytokeratin 7, and cytokeratin 20 is useful in discriminating primary lung adenocarcinomas from metastatic colorectal cancer

BACKGROUND: It is important to discriminate between primary and secondary lung cancer. However, often, the discriminating diagnosis of primary lung acinar adenocarcinoma and lung metastasis of colorectal cancer based on morphological and pathological findings is difficult. The purpose of this study was to evaluate the clinical usefulness of immunohistochemistry of β-catenin, cytokeratin (CK) 7, and CK20 for the discriminating diagnosis of lung cancer. METHODS: We performed immunohistochemistry of β-catenin, CK7, and CK20 in 19 lung metastasis of colorectal cancer samples, 10 corresponding primary colorectal cancer samples and 11 primary lung acinar adenocarcinoma samples and compared the levels of accuracy of the discriminating diagnosis by using antibodies against these antigens. RESULTS: Positive staining of β-catenin was observed in all the lung metastasis of colorectal cancer samples as well as in the primary colorectal cancer samples but in none of the primary lung acinar adenocarcinoma samples. Positive staining of CK7 was observed in 90.9% of the primary lung acinar adenocarcinoma samples and in 5.3% of the lung metastasis of colorectal cancer samples, but in none of the primary colorectal cancer samples. Positive staining of CK20 was observed in all the primary colorectal cancer samples and in 84.2% of the lung metastasis of colorectal cancer samples, but in none of the primary lung acinar adenocarcinoma samples. CONCLUSION: Combined immunohistochemistry of β-catenin, CK7, and CK20 is useful for making a discriminating diagnosis between lung metastasis of colorectal cancer and primary lung acinar adenocarcinoma. This method will enable accurate diagnosis of a lung tumor and will be useful for selecting appropriate therapeutic strategies, including chemotherapeutic agents and operation methods

Molecular Analysis of Precursor Lesions in Familial Pancreatic Cancer

PMCID: PMC3553106This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

A rare case of a retroperitoneal enterogenous cyst with in-situ adenocarcinoma

<p>Abstract</p> <p>Background</p> <p>Retroperitoneal enterogenous cysts are uncommon and adenocarcinoma within such cysts is a rare complication.</p> <p>Case presentation</p> <p>We present the third described case of a retroperitoneal enterogenous cyst with adenocarcinomatous changes and only the second reported case whereby the cyst was not arising from any anatomical structure.</p> <p>Conclusion</p> <p>This case demonstrates the difficulties in making a diagnosis as well as the importance of a multi-disciplinary approach, and raises further questions regarding post-operative treatment with chemotherapy.</p

Challenges of self-reported medical conditions and electronic medical records among members of a large military cohort

<p>Abstract</p> <p>Background</p> <p>Self-reported medical history data are frequently used in epidemiological studies. Self-reported diagnoses may differ from medical record diagnoses due to poor patient-clinician communication, self-diagnosis in the absence of a satisfactory explanation for symptoms, or the "health literacy" of the patient.</p> <p>Methods</p> <p>The US Department of Defense military health system offers a unique opportunity to evaluate electronic medical records with near complete ascertainment while on active duty. This study compared 38 self-reported medical conditions to electronic medical record data in a large population-based US military cohort. The objective of this study was to better understand challenges and strengths in self-reporting of medical conditions.</p> <p>Results</p> <p>Using positive and negative agreement statistics for less-prevalent conditions, near-perfect negative agreement and moderate positive agreement were found for the 38 diagnoses.</p> <p>Conclusion</p> <p>This report highlights the challenges of using self-reported medical data and electronic medical records data, but illustrates that agreement between the two data sources increases with increased surveillance period of medical records. Self-reported medical data may be sufficient for ruling out history of a particular condition whereas prevalence studies may be best served by using an objective measure of medical conditions found in electronic healthcare records. Defining medical conditions from multiple sources in large, long-term prospective cohorts will reinforce the value of the study, particularly during the initial years when prevalence for many conditions may still be low.</p

A Therapeutic Antibody against West Nile Virus Neutralizes Infection by Blocking Fusion within Endosomes

Defining the precise cellular mechanisms of neutralization by potently inhibitory antibodies is important for understanding how the immune system successfully limits viral infections. We recently described a potently inhibitory monoclonal antibody (MAb E16) against the envelope (E) protein of West Nile virus (WNV) that neutralizes infection even after virus has spread to the central nervous system. Herein, we define its mechanism of inhibition. E16 blocks infection primarily at a post-attachment step as antibody-opsonized WNV enters permissive cells but cannot escape from endocytic compartments. These cellular experiments suggest that E16 blocks the acid-catalyzed fusion step that is required for nucleocapsid entry into the cytoplasm. Indeed, E16 directly inhibits fusion of WNV with liposomes. Additionally, low-pH exposure of E16–WNV complexes in the absence of target membranes did not fully inactivate infectious virus, further suggesting that E16 prevents a structural transition required for fusion. Thus, a strongly neutralizing anti–WNV MAb with therapeutic potential is potently inhibitory because it blocks viral fusion and thereby promotes clearance by delivering virus to the lysosome for destruction

Household out-of-pocket medical expenditures and national health insurance in Taiwan: income and regional inequality

BACKGROUND: Unequal geographical distribution of medical care resources and insufficient healthcare coverage have been two long-standing problems with Taiwan's public health system. The implementation of National Health Insurance (NHI) attempted to mitigate the inequality in health care use. This study examines the degree to which Taiwan's National Health Insurance (NHI) has reduced out-of-pocket medical expenditures in households in different regions and varying levels of income. METHODS: Data used in this study were drawn from the 1994 and 1996 Surveys of Family Income and Expenditure. We pooled the data from 1994 and 1996 and included a year dummy variable (NHI), equal to 1 if the household data came from 1996 in order to assess the impact of NHI on household out-of-pocket medical care expenditures shortly after its implementation in 1995. RESULTS: An individual who was older, female, married, unemployed, better educated, richer, head of a larger family household, or living in the central and eastern areas was more likely to have greater household out-of-pocket medical expenditures. NHI was found to have effectively reduced household out-of-pocket medical expenditures by 23.08%, particularly for more affluent households. With the implementation of NHI, lower and middle income quintiles had smaller decreases in out-of-pocket medical expenditure. NHI was also found to have reduced household out-of-pocket medical expenditures more for households in eastern Taiwan. CONCLUSION: Although NHI was established to create free medical care for all, further effort is needed to reduce the medical costs for certain disadvantaged groups, particularly the poor and aborigines, if equality is to be achieved