Low-voltage nanodomain writing in He-implanted lithium niobate crystals

A scanning force microscope tip is used to write ferroelectric domains in He-implanted single-crystal lithium niobate and subsequently probe them by piezoresponse force microscopy. Investigation of cross-sections of the samples showed that the buried implanted layer, $\sim 1$\,\textmu m below the surface, is non-ferroelectric and can thus act as a barrier to domain growth. This barrier enabled stable surface domains of $< 1$\,\textmu m size to be written in 500\,\textmu m-thick crystal substrates with voltage pulses of only 10\,V applied to the tip

Sex bias in CNS autoimmune disease mediated by androgen control of autoimmune regulator

Male gender is protective against multiple sclerosis and other T-cell-mediated autoimmune diseases. This protection may be due, in part, to higher androgen levels in males. Androgen binds to the androgen receptor (AR) to regulate gene expression, but how androgen protects against autoimmunity is not well understood. Autoimmune regulator (Aire) prevents autoimmunity by promoting self-antigen expression in medullary thymic epithelial cells, such that developing T cells that recognize these self-antigens within the thymus undergo clonal deletion. Here we show that androgen upregulates Aire-mediated thymic tolerance to protect against autoimmunity. Androgen recruits AR to Aire promoter regions, with consequent enhancement of Aire transcription. In mice and humans, thymic Aire expression is higher in males compared with females. Androgen administration and male gender protect against autoimmunity in a multiple sclerosis mouse model in an Aire-dependent manner. Thus, androgen control of an intrathymic Aire-mediated tolerance mechanism contributes to gender differences in autoimmunity

A Randomized Trial of Nighttime Physician Staffing in an Intensive Care Unit

Background Increasing numbers of intensive care units (ICUs) are adopting the practice of nighttime intensivist staffing despite the lack of experimental evidence of its effectiveness. Methods We conducted a 1-year randomized trial in an academic medical ICU of the effects of nighttime staffing with in-hospital intensivists (intervention) as compared with nighttime coverage by daytime intensivists who were available for consultation by telephone (control). We randomly assigned blocks of 7 consecutive nights to the intervention or the control strategy. The primary outcome was patients’ length of stay in the ICU. Secondary outcomes were patients’ length of stay in the hospital, ICU and in-hospital mortality, discharge disposition, and rates of readmission to the ICU. For length-of-stay outcomes, we performed time-to-event analyses, with data censored at the time of a patient’s death or transfer to another ICU. Results A total of 1598 patients were included in the analyses. The median Acute Physiology and Chronic Health Evaluation (APACHE) III score (in which scores range from 0 to 299, with higher scores indicating more severe illness) was 67 (interquartile range, 47 to 91), the median length of stay in the ICU was 52.7 hours (interquartile range, 29.0 to 113.4), and mortality in the ICU was 18%. Patients who were admitted on intervention days were exposed to nighttime intensivists on more nights than were patients admitted on control days (median, 100% of nights [interquartile range, 67 to 100] vs. median, 0% [interquartile range, 0 to 33]; P\u3c0.001). Nonetheless, intensivist staffing on the night of admission did not have a significant effect on the length of stay in the ICU (rate ratio for the time to ICU discharge, 0.98; 95% confidence interval [CI], 0.88 to 1.09; P=0.72), ICU mortality (relative risk, 1.07; 95% CI, 0.90 to 1.28), or any other end point. Analyses restricted to patients who were admitted at night showed similar results, as did sensitivity analyses that used different definitions of exposure and outcome. Conclusions In an academic medical ICU in the United States, nighttime in-hospital intensivist staffing did not improve patient outcomes. (Funded by University of Pennsylvania Health System and others; ClinicalTrials.gov number, NCT01434823.

Assessing Recent Smoking Status by Measuring Exhaled Carbon Monoxide Levels

The main expectations of applying proteomics technologies to clinical questions are the discovery of disease related biomarkers. Despite technological advancement to increase proteome coverage and depth to meet these expectations the number of generated biomarkers for clinical use is small. One of the reasons is that found potential biomarkers often are false discoveries. Small sample sizes, in combination with patient sample heterogeneity increase the risk of false discoveries. To be able to extract relevant biological information from such data, high demands are put on the experimental design and the use of sensitive and quantitatively accurate technologies. The overall aim of this thesis was to apply quantitative proteomics methods for biomarker discovery in clinical samples. A method for reducing bias by controlling for individual variation in smoking habits is described in paper I. The aim of the method was objective assessment of recent smoking in clinical studies on inflammatory responses. In paper II, the proteome of alveolar macrophages obtained from smoking subjects with and without the inflammatory lung disease chronic obstructive pulmonary disease (COPD) were quantified by two-dimensional gel-electrophoresis (2-DE). A gender focused analysis showed protein level differences within the female group, with down-regulation of lysosomal pathway and up-regulation of oxidative pathway in COPD patients. Paper III, a mass spectrometry based proteomics analysis of tumour samples, contributes to the molecular understanding of vulvar squamous cell carcinoma (VSCC) and we identified a high risk patient subgroup of HPV-negative tumours based on the expression of four proteins, further suggesting that this subgroup is characterized by an altered ubiquitin-proteasome signalling pathway. Paper III describes a data analysis workflow for the extraction of biological information from quantitative mass spectrometry based proteomics data. High patient-to-patient tumour proteome variability was addressed by using pathway profiling on individual tumour data, followed by comparison of pathway association ranks in a multivariate analysis. We show that pathway data on individual tumour level can detect subpopulations of patients and identify pathways of specific importance in pre-defined clinical groups by the use of multivariate statistics. In paper IV, the potentials and limits of quantitative mass spectrometry on clinical samples was evaluated by defining the quantitative accuracy of isobaric labels and label-free quantification. Quantification by isobaric labels in combination with pI pre-fractionation showed a lower limit of quantification (LOQ) than a label-free analysis without pI pre-fractionation, and 6-plex TMT were more sensitive than 8-plex iTRAQ. Precursor mixing measured by isolation interference (MS1 interference) is more linked to the quantitative accuracy of isobaric labels than reporter ion interference (MS2 interference). Based on that we could define recommendations for how much isolation interference that can be accepted; in our data <30% isolation interference had little effect the quantitative accuracy. In conclusion, getting biological knowledge from proteomics studies requires a careful study design, control of possible confounding factors and the use of clinical data to identify disease subtypes. Further, to be able to draw conclusions from the data, the analysis requires accurate quantitative data and robust statistical tools to detect significant protein alterations. Methods around these issues are developed and discussed in this thesis

Models of peer support to remediate post-intensive care syndrome: A report developed by the SCCM Thrive International Peer Support Collaborative

Objective: Patients and caregivers can experience a range of physical, psychological, and cognitive problems following critical care discharge. The use of peer support has been proposed as an innovative support mechanism. Design: We sought to identify technical, safety and procedural aspects of existing operational models of peer support, among the Society of Critical Care Medicine Thrive Peer Support Collaborative. We also sought to categorize key distinctions between these models and elucidate barriers and facilitators to implementation. Subjects: 17 Thrive sites from the USA, UK, and Australia were represented by a range of healthcare professionals. Interventions: Via an iterative process of in-person and email/conference calls, members of the Collaborative, defined the key areas on which peer support models could be defined and compared; collected detailed self-reports from all sites; reviewed the information and identified clusters of models. Barriers and challenges to implementation of peer support models were also documented. Results: Within the Thrive Collaborative, six general models of peer support were identified: Community based, Psychologist-led outpatient, Models based within ICU follow-up clinics, Online, Groups based within ICU and Peer mentor models. The most common barriers to implementation were: recruitment to groups, personnel input and training: sustainability and funding, risk management and measuring success. Conclusion: A number of different models of peer support are currently being developed to help patients and families recover and grow in the post-critical care setting

The Lipid Paradox is present in ST-elevation but not in non-ST-elevation myocardial infarction patients:Insights from the Singapore Myocardial Infarction Registry

Lowering low-density lipoprotein (LDL-C) and triglyceride (TG) levels form the cornerstone approach of cardiovascular risk reduction, and a higher high-density lipoprotein (HDL-C) is thought to be protective. However, in acute myocardial infarction (AMI) patients, higher admission LDL-C and TG levels have been shown to be associated with better clinical outcomes - termed the 'lipid paradox'. We studied the relationship between lipid profile obtained within 72 hours of presentation, and all-cause mortality (during hospitalization, at 30-days and 12-months), and rehospitalization for heart failure and non-fatal AMI at 12-months in ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI) patients treated by percutaneous coronary intervention (PCI). We included 11543 STEMI and 8470 NSTEMI patients who underwent PCI in the Singapore Myocardial Infarction Registry between 2008-2015. NSTEMI patients were older (60.3 years vs 57.7 years, p < 0.001) and more likely to be female (22.4% vs 15.0%, p < 0.001). In NSTEMI, a lower LDL-C was paradoxically associated with worse outcomes for death during hospitalization, within 30-days and within 12-months (all p < 0.001), but adjustment eliminated this paradox. In contrast, the paradox for LDL-C persisted for all primary outcomes after adjustment in STEMI. For NSTEMI patients, a lower HDL-C was associated with a higher risk of death during hospitalization but in STEMI patients a lower HDL-C was paradoxically associated with a lower risk of death during hospitalization. For this endpoint, the interaction term for HDL-C and type of MI was significant even after adjustment. An elevated TG level was not protective after adjustment. These observations may be due to differing characteristics and underlying pathophysiological mechanisms in NSTEMI and STEMI