The Effect of Anesthetic Drugs During Craniotomy on Patient Outcomes

Glioblastoma remains an aggressive, highly malignant brain cancer with poor prognosis despite treatment options including surgery, radiotherapy, and chemotherapy. The objective of this retrospective chart review study was to evaluate if there is a correlation between the type and dose of anesthetic drugs administered during craniotomy surgery for glioblastoma and the time to first postoperative tumor progression and mortality. Based on preliminary data in mice, it was hypothesized that the use of propofol during surgery is associated with slower tumor progression and lower mortality, when compared with other anesthetic drugs. In the observed time frame, 133 patients were diagnosed with glioblastoma and underwent a total of 161 craniotomy surgeries (23 awake, 138 asleep) at Henry Ford Hospital. Propofol was utilized in 97.5% of these surgeries. Other anesthetics such as isoflurane (53.4%), dexmedetomidine (37.7%), sevoflurane (31.0%), desflurane (14.3%), and nitrous oxide (4.9%) were used less frequently. Data analysis regarding time to progression and mortality after use of each anesthetic remains in progress. This study will guide the administration of anesthetic drugs during surgery to treat glioblastoma, with potential to improve the poor prognosis for these patients

Pulmonary giant cells and their significance for the diagnosis of asphyxiation

This study was performed to prove whether the detection of polynuclear giant cells in lungs is useful for the diagnosis of asphyxiation due to throttling or strangulation. Therefore, lung specimens of 54 individuals with different natural and unnatural causes of death were investigated. In most lungs examined numerous alveolar macrophages with 1-2 nuclei were found. Polynuclear giant cells, which were arbitrarily defined as alveolar macrophages containing 3 or more nuclei, were observed in all groups investigated except in the cases of hypoxia due to covering the head with plastic bags. Apparent differences between the other groups in particular an increased number in cases of throttling or strangulation, could not be observed. Immunohistochemical investigations confirmed the hypothesis that the observed polynuclear giant cells were derived from alveolar macrophages. The immunohistochemical analysis of the proliferation marker antigen Ki 67 revealed no positive reaction in the nuclei of polynuclear giant cells indicating that these cells had not developed shortly before death by endomitosis as an adaptative change following reduction in oxygen supply. The results provide evidence that the detection of pulmonary polynuclear giant cells cannot be used as a practical indicator for death by asphyxiation due to throttling or strangulation

Simplified Models for Dark Matter and Missing Energy Searches at the LHC

The study of collision events with missing energy as searches for the dark matter (DM) component of the Universe are an essential part of the extensive program looking for new physics at the LHC. Given the unknown nature of DM, the interpretation of such searches should be made broad and inclusive. This report reviews the usage of simplified models in the interpretation of missing energy searches. We begin with a brief discussion of the utility and limitation of the effective field theory approach to this problem. The bulk of the report is then devoted to several different simplified models and their signatures, including s-channel and t-channel processes. A common feature of simplified models for DM is the presence of additional particles that mediate the interactions between the Standard Model and the particle that makes up DM. We consider these in detail and emphasize the importance of their inclusion as final states in any coherent interpretation. We also review some of the experimental progress in the field, new signatures, and other aspects of the searches themselves. We conclude with comments and recommendations regarding the use of simplified models in Run-II of the LHC.Comment: v2. references added, version submitted to journal. v1. 47 pages, 13 plot

Impact of sensor and measurement timing errors on model-based insulin sensitivity

peer reviewe

Climate change adaptation, flood risks and policy coherence in integrated water resources management in England

Integrated water resources management (IWRM) assumes coherence between cognate aspects of water governance at the river basin scale, for example water quality, energy production and agriculture objectives. But critics argue that IWRM is often less ‘integrated’ in practice, raising concerns over inter-sectoral coherence between implementing institutions. One increasingly significant aspect of IWRM is adaptation to climate change-related risks, including threats from flooding, which are particularly salient in England. Although multiple institutional mechanisms exist for flood risk management (FRM), their coherence remains a critical question for national adaptation. This paper therefore (1) maps the multi-level institutional frameworks determining both IWRM and FRM in England; (2) examines their interaction via various inter-institutional coordinating mechanisms; and (3) assesses the degree of coherence. The analysis suggests that cognate EU strategic objectives for flood risk assessment demonstrate relatively high vertical and horizontal coherence with river basin planning. However, there is less coherence with flood risk requirements for land-use planning and national flood protection objectives. Overall, this complex governance arrangement actually demonstrates de-coherence over time due to ongoing institutional fragmentation. Recommendations for increasing IWRM coherence in England or re-coherence based on greater spatial planning and coordination of water-use and land-use strategies are proposed

Validation of a model-based virtual trials method for tight glycemic control in intensive care

peer reviewedBACKGROUND: In-silico virtual patients and trials offer significant advantages in cost, time and safety for designing effective tight glycemic control (TGC) protocols. However, no such method has fully validated the independence of virtual patients (or resulting clinical trial predictions) from the data used to create them. This study uses matched cohorts from a TGC clinical trial to validate virtual patients and in-silico virtual trial models and methods. METHODS: Data from a 211 patient subset of the Glucontrol trial in Liege, Belgium. Glucontrol-A (N = 142) targeted 4.4-6.1 mmol/L and Glucontrol-B (N = 69) targeted 7.8-10.0 mmol/L. Cohorts were matched by APACHE II score, initial BG, age, weight, BMI and sex (p > 0.25). Virtual patients are created by fitting a clinically validated model to clinical data, yielding time varying insulin sensitivity profiles (SI(t)) that drives in-silico patients.Model fit and intra-patient (forward) prediction errors are used to validate individual in-silico virtual patients. Self-validation (tests A protocol on Group-A virtual patients; and B protocol on B virtual patients) and cross-validation (tests A protocol on Group-B virtual patients; and B protocol on A virtual patients) are used in comparison to clinical data to assess ability to predict clinical trial results. RESULTS: Model fit errors were small (<0.25%) for all patients, indicating model fitness. Median forward prediction errors were: 4.3, 2.8 and 3.5% for Group-A, Group-B and Overall (A+B), indicating individual virtual patients were accurate representations of real patients. SI and its variability were similar between cohorts indicating they were metabolically similar.Self and cross validation results were within 1-10% of the clinical data for both Group-A and Group-B. Self-validation indicated clinically insignificant errors due to model and/or clinical compliance. Cross-validation clearly showed that virtual patients enabled by identified patient-specific SI(t) profiles can accurately predict the performance of independent and different TGC protocols. CONCLUSIONS: This study fully validates these virtual patients and in silico virtual trial methods, and clearly shows they can accurately simulate, in advance, the clinical results of a TGC protocol, enabling rapid in silico protocol design and optimization. These outcomes provide the first rigorous validation of a virtual in-silico patient and virtual trials methodology

Association of multi-criteria derived air toxics hazard score with lung cancer incidence in a major metropolitan area

BackgroundLung cancer remains a major health problem world-wide. Environmental exposure to lung cancer carcinogens can affect lung cancer incidence. We investigated the association between lung cancer incidence and an air toxics hazard score of environmental carcinogen exposures derived previously under the exposome concept.MethodsLung cancer cases diagnosed in Philadelphia and the surrounding counties between 2008 and 2017 were identified from the Pennsylvania Cancer Registry. Age-adjusted incidence rates at the ZIP code level were calculated based on the residential address at diagnosis. The air toxics hazard score, an aggregate measure for lung cancer carcinogen exposures, was derived using the criteria of toxicity, persistence, and occurrence. Areas with high incidence or hazard score were identified. Spatial autoregressive models were fitted to evaluate the association, with and without adjusting for confounders. Stratified analysis by smoking prevalence was performed to examine potential interactions.ResultsWe observed significantly higher age-adjusted incidence rates in ZIP codes that had higher air toxics hazard score values after controlling for demographic variables, smoking prevalence, and proximity to major highways. Analyzes stratified by smoking prevalence suggested that exposure to environmental lung carcinogens had a larger effect on cancer incidence in locations with higher smoking prevalence.ConclusionThe positive association between the multi-criteria derived air toxics hazard score and lung cancer incidence provides the initial evidence to validate the hazard score as an aggregate measure of carcinogenic exposures in the environment. The hazard score can be used to supplement the existing risk factors in identifying high risk individuals. Communities with higher incidence/hazard score may benefit from greater awareness of lung cancer risk factors and targeted screening programs

Pilot proof of concept clinical trials of Stochastic Targeted (STAR) glycemic control

ABSTRACT: INTRODUCTION: Tight glycemic control (TGC) has shown benefits but has been difficult to achieve consistently. STAR (Stochastic TARgeted) is a flexible, model-based TGC approach directly accounting for intra- and inter- patient variability with a stochastically derived maximum 5% risk of blood glucose (BG) /=3 days. Written informed consent was obtained for all patients, and approval was granted by the NZ Upper South A Regional Ethics Committee. RESULTS: A total of 402 measurements were taken over 660 hours (~14/day), because nurses showed a preference for 2-hourly measurements. Median [interquartile range, (IQR)] cohort BG was 5.9 mmol/L [5.2-6.8]. Overall, 63.2%, 75.9%, and 89.8% of measurements were in the 4.0-6.5, 4.0-7.0, and 4.0-8.0 mmol/L bands. There were no hypoglycemic events (BG < 2.2 mmol/L), and the minimum BG was 3.5 mmol/L with 4.5% < 4.4 mmol/L. Per patient, the median [IQR] hours of TGC was 92 h [29-113] using 53 [19-62] measurements (median, ~13/day). Median [IQR] results: BG, 5.9 mmol/L [5.8-6.3]; carbohydrate nutrition, 6.8 g/h [5.5-8.7] (~70% goal feed median); insulin, 2.5 U/h [0.1-5.1]. All patients achieved BG < 6.1 mmol/L. These results match or exceed SPRINT and clinical workload is reduced more than 20%. CONCLUSIONS: STAR TGC modulating insulin and nutrition inputs provided very tight control with minimal variability by managing intra- and inter- patient variability. Performance and safety exceed that of SPRINT, which reduced mortality and cost in the Christchurch ICU. The use of glucometers did not appear to impact the quality of TGC. Finally, clinical workload was self-managed and reduced 20% compared with SPRINT

Physical modelling of water, fauna and flora: knowledge gaps, avenues for future research and infrastructural needs

peer reviewedPhysical modelling is a key tool for generating understanding of the complex interactions between aquatic organisms and hydraulics, which is important for management of aquatic environments under environmental change and our ability to exploit ecosystem services. Many aspects of this field remain poorly understood and the use of physical models within eco-hydraulics requires advancement in methodological application and substantive understanding. This paper presents a review of the emergent themes from a workshop tasked with identifying the future infrastructure requirements of the next generation of eco-hydraulics researchers. The identified themes are: abiotic factors, adaptation, complexity and feedback, variation, and scale and scaling. The paper examines these themes and identifies how progress on each of them is key to existing and future eðorts to progress our knowledge of eco-hydraulic interactions. Examples are drawn from studies on biofilms, plants, and sessile and mobile fauna in shallow water fluvial and marine environments. Examples of research gaps and directions for educational, infrastructural and technological advance are also presented.PISCES work package of HYDRALAB FP