Innovating for improved healthcare: Sociotechnical and innovation systems perspectives and lessons from the NHS

Healthcare systems with limited resources face rising demand pressures. Healthcare decision-makers increasingly recognise the potential of innovation to help respond to this challenge and to support high-quality care. However, comprehensive and actionable evidence on how to realise this potential is lacking. We adopt sociotechnical systems and innovation systems theoretical perspectives to examine conditions that can support and sustain innovating healthcare systems. We use primary data focussing on England (with 670 contributions over time) and triangulate findings against globally-relevant literature. We discuss the complexity of factors influencing an innovating healthcare system’s ability to support the development and uptake of innovations and share practical learning about changes in policy, culture, and behaviour that could support system improvement. Three themes are examined in detail: skills, capabilities, and leadership; motivations and accountabilities; and collaboration and coordination. We also contribute to advancing applications of sociotechnical systems thinking to major societal transformation challenges

Performance of the CMS Cathode Strip Chambers with Cosmic Rays

The Cathode Strip Chambers (CSCs) constitute the primary muon tracking device in the CMS endcaps. Their performance has been evaluated using data taken during a cosmic ray run in fall 2008. Measured noise levels are low, with the number of noisy channels well below 1%. Coordinate resolution was measured for all types of chambers, and fall in the range 47 microns to 243 microns. The efficiencies for local charged track triggers, for hit and for segments reconstruction were measured, and are above 99%. The timing resolution per layer is approximately 5 ns

Inhibition of NOX1/4 with GKT137831: a potential novel treatment to attenuate neuroglial cell inflammation in the retina

BACKGROUND: Inflammation and the excess production of reactive oxygen species (ROS) contribute significantly to the pathogenesis of ischemic retinopathies such as diabetic retinopathy and retinopathy of prematurity. We hypothesized that GKT137831, a dual inhibitor of NADPH oxidases (NOX) 1 and NOX4, reduces inflammation in the ischemic retina by dampening the pro-inflammatory phenotype of retinal immune cells as well as macroglial Müller cells and neurons. METHODS: Ischemic retinopathy was induced in Sprague-Dawley rats by exposure to 80 % O(2) cycled with 21 % O(2) for 3 h per day from postnatal day (P) 0 to P11, followed by room air (P12 to P18). GKT137831 was administered P12 to P18 (60 mg/kg, subcutaneous) and comparisons were to room air controls. Retinal inflammation was examined by measuring leukocyte adherence to the retinal vasculature, ionized calcium-binding adaptor protein-1-positive microglia/macrophages, and the mRNA and protein levels of key inflammatory factors involved in retinal disease. Damage to Müller cells was evaluated by quantitating glial fibrillary acidic protein-positive cells and vascular leakage with an albumin ELISA. To verify the anti-inflammatory actions of GKT137831 on glia and neurons involved in ischemic retinopathy, primary cultures of rat retinal microglia, Müller cells, and ganglion cells were exposed to the in vitro counterpart of ischemia, hypoxia (0.5 %), and treated with GKT137831 for up to 72 h. ROS levels were evaluated with dihydroethidium and the protein and gene expression of inflammatory factors with quantitative PCR, ELISA, and a protein cytokine array. RESULTS: In the ischemic retina, GKT137831 reduced the increased leukocyte adherence to the vasculature, the pro-inflammatory phenotype of microglia and macroglia, the increased gene and protein expression of vascular endothelial growth factor, monocyte chemoattractant protein-1, and leukocyte adhesion molecules as well as vascular leakage. In all cultured cell types, GKT137831 reduced the hypoxia-induced increase in ROS levels and protein expression of various inflammatory mediators. CONCLUSIONS: NOX1/4 enzyme inhibition with GKT137831 has potent anti-inflammatory effects in the retina, indicating its potential as a treatment for a variety of vision-threatening retinopathies

Beyond reduction of atherosclerosis: PON2 provides apoptosis resistance and stabilizes tumor cells

Major contributors to atherosclerosis are oxidative damage and endoplasmic reticulum (ER) stress-induced apoptosis; both of which can be diminished by the anti-oxidative protein paraoxonase-2 (PON2). ER stress is also relevant to cancer and associated with anti-cancer treatment resistance. Hence, we addressed, for the first time, whether PON2 contributes to tumorigenesis and apoptotic escape. Intriguingly, we found that several human tumors upregulated PON2 and such overexpression provided resistance to different chemotherapeutics (imatinib, doxorubicine, staurosporine, or actinomycin) in cell culture models. This was reversed after PON2 knock-down. Remarkably, just deficiency of PON2 caused apoptosis of selective tumor cells per se, demonstrating a previously unanticipated oncogenic function. We found a dual mechanistic role. During ER stress, high PON2 levels lowered redox-triggered induction of pro-apoptotic CHOP particularly via the JNK pathway, which prevented mitochondrial cell death signaling. Apart from CHOP, PON2 also diminished intrinsic apoptosis as it prevented mitochondrial superoxide formation, cardiolipin peroxidation, cytochrome c release, and caspase activation. Ligand-stimulated apoptosis by TRAIL or TNFα remained unchanged. Finally, PON2 knock-down caused vast reactive oxygen species formation and stimulated JNK-triggered CHOP expression, but inhibition of JNK signaling did not prevent cell death, demonstrating the pleiotropic, dominating anti-oxidative effect of PON2. Therefore, targeting redox balance is powerful to induce selective tumor cell death and proposes PON2 as new putative anti-tumor candidate

Alignment of the CMS silicon tracker during commissioning with cosmic rays

The CMS silicon tracker, consisting of 1440 silicon pixel and 15 148 silicon strip detector modules, has been aligned using more than three million cosmic ray charged particles, with additional information from optical surveys. The positions of the modules were determined with respect to cosmic ray trajectories to an average precision of 3-4 microns RMS in the barrel and 3-14 microns RMS in the endcap in the most sensitive coordinate. The results have been validated by several studies, including laser beam cross-checks, track fit self-consistency, track residuals in overlapping module regions, and track parameter resolution, and are compared with predictions obtained from simulation. Correlated systematic effects have been investigated. The track parameter resolutions obtained with this alignment are close to the design performance

Aligning the CMS Muon Chambers with the Muon Alignment System during an Extended Cosmic Ray Run

Peer reviewe

Alignment of the CMS muon system with cosmic-ray and beam-halo muons

This is the Pre-print version of the Article. The official published version of the Paper can be accessed from the link below - Copyright @ 2010 IOPThe CMS muon system has been aligned using cosmic-ray muons collected in 2008 and beam-halo muons from the 2008 LHC circulating beam tests. After alignment, the resolution of the most sensitive coordinate is 80 microns for the relative positions of superlayers in the same barrel chamber and 270 microns for the relative positions of endcap chambers in the same ring structure. The resolution on the position of the central barrel chambers relative to the tracker is comprised between two extreme estimates, 200 and 700 microns, provided by two complementary studies. With minor modifications, the alignment procedures can be applied using muons from LHC collisions, leading to additional significant improvements.This work is supported by FMSR (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES (Croatia); RPF (Cyprus); Academy of Sciences and NICPB (Estonia); Academy of Finland, ME, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); OTKA and NKTH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); NRF (Korea); LAS (Lithuania); CINVESTAV, CONACYT, SEP, and UASLP-FAI (Mexico); PAEC (Pakistan); SCSR (Poland); FCT (Portugal); JINR(Armenia, Belarus, Georgia, Ukraine, Uzbekistan); MST and MAE (Russia); MSTDS (Serbia); MICINN and CPAN (Spain); Swiss Funding Agencies (Switzerland); NSC (Taipei); TUBITAK and TAEK (Turkey); STFC (United Kingdom); DOE and NSF (USA)

CMS Data Processing Workflows during an Extended Cosmic Ray Run

Peer reviewe

Alignment of the CMS muon system with cosmic-ray and beam-halo muons

This is the Pre-print version of the Article. The official published version of the Paper can be accessed from the link below - Copyright @ 2010 IOPThe CMS muon system has been aligned using cosmic-ray muons collected in 2008 and beam-halo muons from the 2008 LHC circulating beam tests. After alignment, the resolution of the most sensitive coordinate is 80 microns for the relative positions of superlayers in the same barrel chamber and 270 microns for the relative positions of endcap chambers in the same ring structure. The resolution on the position of the central barrel chambers relative to the tracker is comprised between two extreme estimates, 200 and 700 microns, provided by two complementary studies. With minor modifications, the alignment procedures can be applied using muons from LHC collisions, leading to additional significant improvements.This work is supported by FMSR (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES (Croatia); RPF (Cyprus); Academy of Sciences and NICPB (Estonia); Academy of Finland, ME, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); OTKA and NKTH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); NRF (Korea); LAS (Lithuania); CINVESTAV, CONACYT, SEP, and UASLP-FAI (Mexico); PAEC (Pakistan); SCSR (Poland); FCT (Portugal); JINR(Armenia, Belarus, Georgia, Ukraine, Uzbekistan); MST and MAE (Russia); MSTDS (Serbia); MICINN and CPAN (Spain); Swiss Funding Agencies (Switzerland); NSC (Taipei); TUBITAK and TAEK (Turkey); STFC (United Kingdom); DOE and NSF (USA)

Commissioning of the CMS high-level trigger with cosmic rays

This is the Pre-print version of the Article. The official published version of the paper can be accessed from the link below - Copyright @ 2010 IOPThe CMS High-Level Trigger (HLT) is responsible for ensuring that data samples with potentially interesting events are recorded with high efficiency and good quality. This paper gives an overview of the HLT and focuses on its commissioning using cosmic rays. The selection of triggers that were deployed is presented and the online grouping of triggered events into streams and primary datasets is discussed. Tools for online and offline data quality monitoring for the HLT are described, and the operational performance of the muon HLT algorithms is reviewed. The average time taken for the HLT selection and its dependence on detector and operating conditions are presented. The HLT performed reliably and helped provide a large dataset. This dataset has proven to be invaluable for understanding the performance of the trigger and the CMS experiment as a whole.This work is supported by FMSR (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES (Croatia); RPF (Cyprus); Academy of Sciences and NICPB (Estonia); Academy of Finland, ME, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); OTKA and NKTH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); NRF (Korea); LAS (Lithuania); CINVESTAV, CONACYT, SEP, and UASLP-FAI (Mexico); PAEC (Pakistan); SCSR (Poland); FCT (Portugal); JINR (Armenia, Belarus, Georgia, Ukraine, Uzbekistan); MST and MAE (Russia); MSTDS (Serbia); MICINN and CPAN (Spain); Swiss Funding Agencies (Switzerland); NSC (Taipei); TUBITAK and TAEK (Turkey); STFC (United Kingdom); DOE and NSF (USA)