Quantitative analysis of the effect of tubulin isotype expression on sensitivity of cancer cell lines to a set of novel colchicine derivatives

<p>Abstract</p> <p>Background</p> <p>A maximum entropy approach is proposed to predict the cytotoxic effects of a panel of colchicine derivatives in several human cancer cell lines. Data was obtained from cytotoxicity assays performed with 21 drug molecules from the same family of colchicine compounds and correlate these results with independent tubulin isoform expression measurements for several cancer cell lines. The maximum entropy method is then used in conjunction with computed relative binding energy values for each of the drug molecules against tubulin isotypes to which these compounds bind with different affinities.</p> <p>Results</p> <p>We have found by using our analysis that <it>αβ</it>I and <it>αβ</it>III tubulin isoforms are the most important isoforms in establishing predictive response of cancer cell sensitivity to colchicine derivatives. However, since <it>αβ</it>I tubulin is widely distributed in the human body, targeting it would lead to severe adverse side effects. Consequently, we have identified tubulin isotype <it>αβ</it>III as the most important molecular target for inhibition of microtubule polymerization and hence cancer cell cytotoxicity. Tubulin isotypes <it>αβ</it>I and <it>αβ</it>II are concluded to be secondary targets.</p> <p>Conclusions</p> <p>The benefit of being able to correlate expression levels of specific tubulin isotypes and the resultant cell death effect is that it will enable us to better understand the origin of drug resistance and hence design optimal structures for the elimination of cancer cells. The conclusion of the study described herein identifies tubulin isotype <it>αβ</it>III as a target for optimized chemotherapy drug design.</p

Data from: Exploring emergency department 4-hour target performance and cancelled elective operations: a regression analysis of routinely collected and openly reported NHS trust data.

Objective: To quantify the effect of intra-hospital patient flow on Emergency Department (ED) performance targets and indicate if the expectations set by the NHS England five year forward review are realistic in returning emergency services to previous performance levels. Design: Linear regression analysis of routinely reported trust activity and performance data using a series of cross-sectional studies. Setting: NHS trusts in England submitting routine nationally reported measures to NHS England. Participants: 142 acute non-specialist trusts operating in England between 2012 and 2016. Main outcome measures: The primary outcome measures were: proportion of four-hour waiting time breaches and cancelled elective operations. Methods: Univariate and multivariate linear regression models were used to show relationships between the outcome measures, and various measures of trust activity including: empty day-beds, empty night-beds, day-to-night bed ratio, ED conversion ratio and delayed transfers of care. Results: Univariate regression results using the outcome of four-hour breaches showed clear relationships with: empty night-beds and ED conversion ratio between 2012-2016. The day-to-night bed ratio showed an increasing ability to explain variation in performance between 2015-2016. Delayed transfers of care showed little evidence of an association. Multivariate model results indicated that the ability of patient flow variables to explain four-hour target performance had reduced between 2012-2016 (19% to 12%), and had increased in explaining cancelled elective operations (7% to 17%). Conclusions: The flow of patients through trusts is shown to influence ED performance, however performance has become less explainable by intra-trust patient flow between 2012 and 2016. Some commonly stated explanatory factors such as delayed transfers of care showed limited evidence of being related. The results indicate some of the measures proposed by NHS England to reduce pressure on EDs may not have the desired impact on returning services to previous performance levels

An evidence-based approach to quality improvement for COVIDoximetry@Home

Robust data-driven insights are critical for the design, adaptation, and improvement of clinical and operational management policies governing care pathways and resource models. However, understanding the requirements for data and analysis can be challenging when faced with disruptive innovations that offer new or reconfigured services such as COVIDOximetry@Home(NHS England and NHS Improvement, 2020), and when such change impacts multiple providers in an Integrated Care System (ICS). In this report we outline measurement, monitoring and analysis of COVIDOximetry@Homeusing evidence-based practice as the underpinning foundation for PDSA quality improvement[1]. Many operational and clinical decisions should be considered, and it is the purpose of the data and analytics to offer decision makers with insights necessary to design, assessment and implement of policies for better care. ▪Clinical: predict patient outcomes; understand the efficacy of interventions at different COVID patient disease stages and associated clinical care settings▪Operational: understand how clinical services respond to workload and resources for planning, optimisation, and reconfiguration; identification and validation of processes▪Compliance: understand the degree to which services are operating according to procedures and practices▪Programme Evaluation: deliver evidence as part of programme evaluation and for sustainability investment decisionsWhilst the COVID-19 Virtual Wards Data Provision Notice (NHS Digital 2020-1) mandates the “data to be collected for the evaluation of the Virtual Wards pilot”, our work puts data into the context of digital systems, and ongoing clinical and operational quality improvement. We describe the COVID19 Virtual Ward concept and clinical setting, and then elaborate the clinical, operation, compliance, and evaluation requirements. Finally, we summarise a system view from an exemplar ICS, outlining the relation between structure and data

Exploring emergency department 4-hour target performance and cancelled elective operations: a regression analysis of routinely collected and openly reported NHS trust data

Objective: to quantify the effect of intrahospital patient flow on emergency department (ED) performance targets and indicate if the expectations set by the National Health Service (NHS) England 5-year forward review are realistic in returning emergency services to previous performance levels.Design: linear regression analysis of routinely reported trust activity and performance data using a series of cross-sectional studies.Setting: NHS trusts in England submitting routine nationally reported measures to NHS England.Participants: 142 acute non-specialist trusts operating in England between 2012 and 2016.Main outcome measures: the primary outcome measures were proportion of 4-hour waiting time breaches and cancelled elective operations.Methods: nivariate and multivariate linear regression models were used to show relationships between the outcome measures and various measures of trust activity including empty day beds, empty night beds, day bed to night bed ratio, ED conversion ratio and delayed transfers of care.Results: univariate regression results using the outcome of 4-hour breaches showed clear relationships with empty night beds and ED conversion ratio between 2012 and 2016. The day bed to night bed ratio showed an increasing ability to explain variation in performance between 2015 and 2016. Delayed transfers of care showed little evidence of an association. Multivariate model results indicated that the ability of patient flow variables to explain 4-hour target performance had reduced between 2012 and 2016 (19% to 12%), and had increased in explaining cancelled elective operations (7% to 17%).Conclusions: the flow of patients through trusts is shown to influence ED performance; however, performance has become less explainable by intratrust patient flow between 2012 and 2016. Some commonly stated explanatory factors such as delayed transfers of care showed limited evidence of being related. The results indicate some of the measures proposed by NHS England to reduce pressure on EDs may not have the desired impact on returning services to previous performance levels

Independent evaluation of the piloting of the implementation of MymHealth [myCOPD, myHeart and myDiabetes] by Dorset Clinical Commissioning Group

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The removal of the carboxy-terminal region of tubulin favors its vinblastine-induced aggregation into spiral-like structures

Vinblastine induces brain tubulin to assemble into spirals. This process is stimulated by microtubule-associated proteins (MAPs) which copolymerize with brain microtubules assembled in vitro. When the carboxy terminal of tubulin is removed by subtilisin digestion, vinblastine readily induces the aggregation of tubulin into spiral-like or circular structures, even in the absence of MAPs. These results suggest that in the absence of MAPs, the carboxy-terminal domain of tubulin may inhibit vinblastine-induced polymerization of tubulin into spiral-like structures.Peer reviewe

NHS England routinely reported measures 2011-2016

NHS England routinely and openly publish reports of various measures which are collected across NHS services in England. The reports are made available here: https://www.england.nhs.uk/statistics/ . The statistics reported are grouped into &lsquo;statistical work areas&rsquo;, published separately, and are recorded over different time intervals (i.e. monthly, quarterly, yearly) which makes combined analysis time consuming. As part of a study into acute hospital pressure, various &lsquo;statistical work areas&rsquo; were combined into one file to complete analysis between calendar years 2011-2016. Contains public sector information licensed under the Open Government Licence v3.0.</span