Prognostic relevance of a T-type calcium channels gene signature in solid tumours: A correlation ready for clinical validation

BackgroundT-type calcium channels (TTCCs) mediate calcium influx across the cell membrane. TTCCs regulate numerous physiological processes including cardiac pacemaking and neuronal activity. In addition, they have been implicated in the proliferation, migration and differentiation of tumour tissues. Although the signalling events downstream of TTCC-mediated calcium influx are not fully elucidated, it is clear that variations in the expression of TTCCs promote tumour formation and hinder response to treatment.MethodsWe examined the expression of TTCC genes (all three subtypes; CACNA-1G, CACNA-1H and CACNA-1I) and their prognostic value in three major solid tumours (i.e. gastric, lung and ovarian cancers) via a publicly accessible database.ResultsIn gastric cancer, expression of all the CACNA genes was associated with overall survival (OS) among stage I-IV patients (all pConclusionsAlterations in CACNA gene expression are linked to tumour prognosis. Gastric cancer represents the most promising setting for further evaluation

Covariant Description of Flavor Conversion in the LHC Era

A simple covariant formalism to describe flavor and CP violation in the left-handed quark sector in a model independent way is provided. The introduction of a covariant basis, which makes the standard model approximate symmetry structure manifest, leads to a physical and transparent picture of flavor conversion processes. Our method is particularly useful to derive robust bounds on models with arbitrary mechanisms of alignment. Known constraints on flavor violation in the K and D systems are reproduced in a straightforward manner. Assumptions-free limits, based on top flavor violation at the LHC, are then obtained. In the absence of signal, with 100 fb^{-1} of data, the LHC will exclude weakly coupled (strongly coupled) new physics up to a scale of 0.6 TeV (7.6 TeV), while at present no general constraint can be set related to Delta t=1 processes. LHC data will constrain Delta F=2 contributions via same-sign tops signal, with a model independent exclusion region of 0.08 TeV (1.0 TeV). However, in this case, stronger bounds are found from the study of CP violation in D-bar D mixing with a scale of 0.57 TeV (7.2 TeV). In addition, we apply our analysis to models of supersymmetry and warped extra dimension. The minimal flavor violation framework is also discussed, where the formalism allows to distinguish between the linear and generic non-linear limits within this class of models.Comment: 24 pages, 6 figures. Some corrections and clarifications; references added. Matches published versio

Hierarchical Regression for Multiple Comparisons in a Case-Control Study of Occupational Risks for Lung Cancer

BACKGROUND Occupational studies often involve multiple comparisons and therefore suffer from false positive findings. Semi-Bayes adjustment methods have sometimes been used to address this issue. Hierarchical regression is a more general approach, including Semi-Bayes adjustment as a special case, that aims at improving the validity of standard maximum-likelihood estimates in the presence of multiple comparisons by incorporating similarities between the exposures of interest in a second-stage model. METHODOLOGY/PRINCIPAL FINDINGS We re-analysed data from an occupational case-control study of lung cancer, applying hierarchical regression. In the second-stage model, we included the exposure to three known lung carcinogens (asbestos, chromium and silica) for each occupation, under the assumption that occupations entailing similar carcinogenic exposures are associated with similar risks of lung cancer. Hierarchical regression estimates had smaller confidence intervals than maximum-likelihood estimates. The shrinkage toward the null was stronger for extreme, less stable estimates (e.g., "specialised farmers": maximum-likelihood OR: 3.44, 95%CI 0.90-13.17; hierarchical regression OR: 1.53, 95%CI 0.63-3.68). Unlike Semi-Bayes adjustment toward the global mean, hierarchical regression did not shrink all the ORs towards the null (e.g., "Metal smelting, converting and refining furnacemen": maximum-likelihood OR: 1.07, Semi-Bayes OR: 1.06, hierarchical regression OR: 1.26). CONCLUSIONS/SIGNIFICANCE Hierarchical regression could be a valuable tool in occupational studies in which disease risk is estimated for a large amount of occupations when we have information available on the key carcinogenic exposures involved in each occupation. With the constant progress in exposure assessment methods in occupational settings and the availability of Job Exposure Matrices, it should become easier to apply this approach

Social sciences research in neglected tropical diseases 2: A bibliographic analysis

The official published version of the article can be found at the link below.Background There are strong arguments for social science and interdisciplinary research in the neglected tropical diseases. These diseases represent a rich and dynamic interplay between vector, host, and pathogen which occurs within social, physical and biological contexts. The overwhelming sense, however, is that neglected tropical diseases research is a biomedical endeavour largely excluding the social sciences. The purpose of this review is to provide a baseline for discussing the quantum and nature of the science that is being conducted, and the extent to which the social sciences are a part of that. Methods A bibliographic analysis was conducted of neglected tropical diseases related research papers published over the past 10 years in biomedical and social sciences. The analysis had textual and bibliometric facets, and focussed on chikungunya, dengue, visceral leishmaniasis, and onchocerciasis. Results There is substantial variation in the number of publications associated with each disease. The proportion of the research that is social science based appears remarkably consistent (<4%). A textual analysis, however, reveals a degree of misclassification by the abstracting service where a surprising proportion of the "social sciences" research was pure clinical research. Much of the social sciences research also tends to be "hand maiden" research focused on the implementation of biomedical solutions. Conclusion There is little evidence that scientists pay any attention to the complex social, cultural, biological, and environmental dynamic involved in human pathogenesis. There is little investigator driven social science and a poor presence of interdisciplinary science. The research needs more sophisticated funders and priority setters who are not beguiled by uncritical biomedical promises

Modification of second cancer risk after malignant melanoma by parental history of cancer

The Swedish Family-Cancer Database was used to quantify the incidence of second tumours in melanoma patients with a parental history of cancer. Patients with parents affected by melanoma showed a 32.3-fold risk of second primary melanomas, which was greater than a multiplicative interaction

Geographical heterogeneity of clinical and serological phenotypes of systemic sclerosis observed at tertiary referral centres. The experience of the Italian SIR-SPRING registry and review of the world literature

Introduction: Systemic sclerosis (SSc) is characterized by a complex etiopathogenesis encompassing both host genetic and environmental -infectious/toxic- factors responsible for altered fibrogenesis and diffuse microangiopathy. A wide spectrum of clinical phenotypes may be observed in patients' populations from different geographical areas. We investigated the prevalence of specific clinical and serological phenotypes in patients with definite SSc enrolled at tertiary referral centres in different Italian geographical macro-areas. The observed findings were compared with those reported in the world literature.Materials and methods: The clinical features of 1538 patients (161 M, 10.5%; mean age 59.8 +/- 26.9 yrs.; mean disease duration 8.9 +/- 7.7 yrs) with definite SSc recruited in 38 tertiary referral centres of the SPRING (Systemic sclerosis Progression INvestiGation Group) registry promoted by Italian Society of Rheumatology (SIR) were obtained and clustered according to Italian geographical macroareas.Results: Patients living in Southern Italy were characterized by more severe clinical and/or serological SSc phenotypes compared to those in Northern and Central Italy; namely, they show increased percentages of diffuse cutaneous SSc, digital ulcers, sicca syndrome, muscle involvement, arthritis, cardiopulmonary symptoms, interstitial lung involvement at HRCT, as well increased prevalence of serum anti-Scl70 autoantibodies. In the same SSc population immunusppressive drugs were frequently employed. The review of the literature underlined the geographical heterogeneity of SSc phenotypes, even if the observed findings are scarcely comparable due to the variability of methodological approaches.Conclusion: The phenotypical differences among SSc patients' subgroups from Italian macro-areas might be correlated to genetic/environmental co-factors, and possibly to a not equally distributed national network of information and healthcare facilities

Tumor location and patient characteristics of colon and rectal adenocarcinomas in relation to survival and TNM classes

<p>Abstract</p> <p>Background</p> <p>Old age at diagnosis is associated with poor survival in colorectal cancer (CRC) for unknown reasons. Recent data show that colonoscopy is efficient in preventing left-sided cancers only. We examine the association of Tumor Node Metastasis (TNM) classes with diagnostic age and patient characteristics.</p> <p>Methods</p> <p>The Swedish Family-Cancer Database has data on TNM classes on 6,105 CRC adenocarcinoma patients. Ordinal logistic regression analysis was performed to model tumor characteristics according to age at diagnosis, tumor localization, gender, socioeconomic status, medical region and family history. The results were compared to results from survival analysis.</p> <p>Results</p> <p>The only parameters systematically associated with TNM classes were age and tumor localization. Young age at diagnosis was a risk factor for aggressive CRC, according to stage, N and M with odds ratios (ORs) ranging from 1.80 to 1.93 for diagnosis before age 50 years compared to diagnosis at 80+ years. All tumor characteristics, particularly T, were worse for colon compared to rectal tumors. Right-sided tumors showed worse characteristics for all classifiers but M. The survival analysis on patients diagnosed since 2000 showed a hazard ratio of 0.55 for diagnosis before age 50 years compared to diagnosis at over 80 years and a modestly better prognosis for left-sided compared to right-sided tumors.</p> <p>Conclusions</p> <p>The results showed systematically more aggressive tumors in young compared to old patients. The poorer survival of old patients in colon cancer was not related to the available tumor characteristics. However, these partially agreed with the limited colonoscopic success with right-sided tumors.</p

Impacts of climate change on plant diseases – opinions and trends

There has been a remarkable scientific output on the topic of how climate change is likely to affect plant diseases in the coming decades. This review addresses the need for review of this burgeoning literature by summarizing opinions of previous reviews and trends in recent studies on the impacts of climate change on plant health. Sudden Oak Death is used as an introductory case study: Californian forests could become even more susceptible to this emerging plant disease, if spring precipitations will be accompanied by warmer temperatures, although climate shifts may also affect the current synchronicity between host cambium activity and pathogen colonization rate. A summary of observed and predicted climate changes, as well as of direct effects of climate change on pathosystems, is provided. Prediction and management of climate change effects on plant health are complicated by indirect effects and the interactions with global change drivers. Uncertainty in models of plant disease development under climate change calls for a diversity of management strategies, from more participatory approaches to interdisciplinary science. Involvement of stakeholders and scientists from outside plant pathology shows the importance of trade-offs, for example in the land-sharing vs. sparing debate. Further research is needed on climate change and plant health in mountain, boreal, Mediterranean and tropical regions, with multiple climate change factors and scenarios (including our responses to it, e.g. the assisted migration of plants), in relation to endophytes, viruses and mycorrhiza, using long-term and large-scale datasets and considering various plant disease control methods

Neural hypernetwork approach for pulmonary embolism diagnosis

Background Hypernetworks are based on topological simplicial complexes and generalize the concept of two-body relation to many-body relation. Furthermore, Hypernetworks provide a significant generalization of network theory, enabling the integration of relational structure, logic and analytic dynamics. A pulmonary embolism is a blockage of the main artery of the lung or one of its branches, frequently fatal. Results Our study uses data on 28 diagnostic features of 1427 people considered to be at risk of pulmonary embolism enrolled in the Department of Internal and Subintensive Medicine of an Italian National Hospital “Ospedali Riuniti di Ancona”. Patients arrived in the department after a first screening executed by the emergency room. The resulting neural hypernetwork correctly recognized 94 % of those developing pulmonary embolism. This is better than previous results obtained with other methods (statistical selection of features, partial least squares regression, topological data analysis in a metric space). Conclusion In this work we successfully derived a new integrative approach for the analysis of partial and incomplete datasets that is based on Q-analysis with machine learning. The new approach, called Neural Hypernetwork, has been applied to a case study of pulmonary embolism diagnosis. The novelty of this method is that it does not use clinical parameters extracted by imaging analysis