Blockade of catecholamine-induced growth by adrenergic and dopaminergic receptor antagonists in Escherichia coli O157:H7, Salmonella enterica and Yersinia enterocolitica

BACKGROUND: The ability of catecholamines to stimulate bacterial growth was first demonstrated just over a decade ago. Little is still known however, concerning the nature of the putative bacterial adrenergic and/or dopaminergic receptor(s) to which catecholamines (norepinephrine, epinephrine and dopamine) may bind and exert their effects, or even whether the binding properties of such a receptor are similar between different species. RESULTS: Use of specific catecholamine receptor antagonists revealed that only α, and not β, adrenergic antagonists were capable of blocking norepinephrine and epinephrine-induced growth, while antagonism of dopamine-mediated growth was achieved with the use of a dopaminergic antagonist. Both adrenergic and dopaminergic antagonists were highly specific in their mechanism of action, which did not involve blockade of catecholamine-facilitated iron-acquisition. Use of radiolabeled norepinephrine suggested that the adrenergic antagonists could be acting by inhibiting catecholamine uptake. CONCLUSION: The present data demonstrates that the ability of a specific pathogen to respond to a particular hormone is dependent upon the host anatomical region in which the pathogen causes disease as well as the neuroanatomical specificity to which production of the particular hormone is restricted; and that both are anatomically coincidental to each other. As such, the present report suggests that pathogens with a high degree of exclusivity to the gastrointestinal tract have evolved response systems to neuroendocrine hormones such as norepinephrine and dopamine, but not epinephrine, which are found with the enteric nervous system

The incidence of mental deficiency in a community and a study of the natural history of mental deficiency in the hospital group catering for that community

Abstract Not Provided

The diagnostic accuracy of a single CEA blood test in detecting colorectal cancer recurrence: Results from the FACS trial

Objective: To evaluate the diagnostic accuracy of a single CEA (carcinoembryonic antigen) blood test in detecting colorectal cancer recurrence. Background: Patients who have undergone curative resection for primary colorectal cancer are typically followed up with scheduled CEA testing for 5 years. Decisions to investigate further (usually by CT imaging) are based on single test results, reflecting international guidelines. Methods: A secondary analysis was undertaken of data from the FACS trial (two arms included CEA testing). The composite reference standard applied included CT-CAP imaging, clinical assessment and colonoscopy. Accuracy in detecting recurrence was evaluated in terms of sensitivity, specificity, likelihood ratios, predictive values, time-dependent area under the ROC curves, and operational performance when used prospectively in clinical practice are reported. Results: Of 582 patients, 104 (17.9%) developed recurrence during the 5 year follow-up period. Applying the recommended threshold of 5µg/L achieves at best 50.0% sensitivity (95% CI: 40.1-59.9%); in prospective use in clinical practice it would lead to 56 missed recurrences (53.8%; 95% CI: 44.2-64.4%) and 89 false alarms (56.7% of 157 patients referred for investigation). Applying a lower threshold of 2.5µg/L would reduce the number of missed recurrences to 36.5% (95% CI: 26.5-46.5%) but would increase the false alarms to 84.2% (924/1097 referred). Some patients are more prone to false alarms than others – at the 5µg/L threshold, the 89 episodes of unnecessary investigation were clustered in 29 individuals. Conclusion: Our results demonstrated very low sensitivity for CEA, bringing to question whether it could ever be used as an independent triage test. It is not feasible to improve the diagnostic performance of a single test result by reducing the recommended action threshold because of the workload and false alarms generated. Current national and international guidelines merit re-evaluation and options to improve performance, such as making clinical decisions on the basis of CEA trend, should be further assessed

Toward a comprehensive system for constructing compartmental epidemic models

Compartmental models are valuable tools for investigating infectious diseases. Researchers building such models typically begin with a simple structure where compartments correspond to individuals with different epidemiological statuses, e.g., the classic SIR model which splits the population into susceptible, infected, and recovered compartments. However, as more information about a specific pathogen is discovered, or as a means to investigate the effects of heterogeneities, it becomes useful to stratify models further -- for example by age, geographic location, or pathogen strain. The operation of constructing stratified compartmental models from a pair of simpler models resembles the Cartesian product used in graph theory, but several key differences complicate matters. In this article we give explicit mathematical definitions for several so-called ``model products'' and provide examples where each is suitable. We also provide examples of model stratification where no existing model product will generate the desired result

The use of tumour markers CEA, CA-195 and CA-242 in evaluating the response to chemotherapy in patients with advanced colorectal cancer.

Tumour markers CEA, CA-195 and CA-242 were measured in 33 patients undergoing chemotherapy for advanced colorectal cancer. The aim was to determine whether they could be used to accurately monitor the course of the disease, and reduce the need for imaging. Treatment with a 5-fluorouracil based regimen resulted in a partial response in nine patients (27%), whereas the remainder either had disease stabilisation or suffered from progression. Before treatment the CEA was elevated in 85% of patients and the CA-195 and CA-242 in 78%. All three markers were elevated in 70% and at least one elevated in 93%. CA-195 and CA-242 appeared to be co-expressed, by contrast with the CEA. When compared to the results of serial CT scanning the CEA correlated best with the course of the disease, the positive predictive value being 54% for a partial response, 77% for minor and partial responses combined and 100% for progressive disease. The corresponding values for CA-195 were 46%, 62% and 100% respectively and for CA-242, 50%, 67% and 100% respectively. Thus, although falling levels of markers overestimate the number of responses demonstrated by imaging, rising tumour markers invariably herald progressive disease. This was often evident up to 16 weeks before progression was observed on scanning. CEA is the most useful of the three markers in the monitoring of patients being treated for advanced colorectal cancer, but other markers may prove valuable if the CEA is normal. The use of tumour markers should reduce the need for regular scanning

Protein dynamics with off-lattice Monte Carlo moves

A Monte Carlo method for dynamics simulation of all-atom protein models is introduced, to reach long times not accessible to conventional molecular dynamics. The considered degrees of freedom are the dihedrals at C$_\alpha$-atoms. Two Monte Carlo moves are used: single rotations about torsion axes, and cooperative rotations in windows of amide planes, changing the conformation globally and locally, respectively. For local moves Jacobians are used to obtain an unbiased distribution of dihedrals. A molecular dynamics energy function adapted to the protein model is employed. A polypeptide is folded into native-like structures by local but not by global moves.Comment: 10 pages, 4 Postscript figures, uses epsf.sty and a4.sty; scheduled tentatively for Phys.Rev.E issue of 1 March 199

Comprehensive Imaging Characterization of Colorectal Liver Metastases

Colorectal liver metastases (CRLM) have heterogenous histopathological and immunohistochemical phenotypes, which are associated with variable responses to treatment and outcomes. However, this information is usually only available after resection, and therefore of limited value in treatment planning. Improved techniques for in vivo disease assessment, which can characterise the variable tumour biology, would support further personalization of management strategies. Advanced imaging of CRLM including multiparametric MRI and functional imaging techniques have the potential to provide clinically-actionable phenotypic characterisation. This includes assessment of the tumour-liver interface, internal tumour components and treatment response. Advanced analysis techniques, including radiomics and machine learning now have a growing role in assessment of imaging, providing high-dimensional imaging feature extraction which can be linked to clinical relevant tumour phenotypes, such as a the Consensus Molecular Subtypes (CMS). In this review, we outline how imaging techniques could reproducibly characterize the histopathological features of CRLM, with several matched imaging and histology examples to illustrate these features, and discuss the oncological relevance of these features. Finally, we discuss the future challenges and opportunities of CRLM imaging, with a focus on the potential value of advanced analytics including radiomics and artificial intelligence, to help inform future research in this rapidly moving field

Comparison of phenomics and cfDNA in a large breast screening population: the Breast Screening and Monitoring Study (BSMS)

To assess their roles in breast cancer diagnostics, we aimed to compare plasma cell-free DNA (cfDNA) levels with the circulating metabolome in a large breast screening cohort of women recalled for mammography, including healthy women and women with mammographically detected breast diseases, ductal carcinoma in situ and invasive breast cancer: the Breast Screening and Monitoring Study (BSMS). In 999 women, plasma was analyzed by nuclear magnetic resonance (NMR) and Ultra-Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS) and then processed to isolate and quantify total cfDNA. NMR and UPLC-MS results were compared with data for 186 healthy women derived from the AIRWAVE cohort. Results showed no significant differences between groups for all metabolites, whereas invasive cancers had significantly higher plasma cfDNA levels than all other groups. When stratified the supervised OPLS-DA analysis and total cfDNA concentration showed high discrimination accuracy between invasive cancers and the disease/medication-free subjects. Furthermore, comparison of OPLS-DA data for invasive breast cancers with the AIRWAVE cohort showed similar discrimination between breast cancers and healthy controls. This is the first report of agreement between metabolomics and plasma cfDNA levels for discriminating breast cancer from healthy subjects in a true screening population. It also emphasizes the importance of sample standardization. Follow on studies will involve analysis of candidate features in a larger validation series as well as comparing results with serial plasma samples taken at the next routine screening mammography appointment. The findings here help establish the role of plasma analysis in the diagnosis of breast cancer in a large real-world cohort