Feeling sleepy? stop driving-awareness of fall asleep crashes.

STUDY OBJECTIVES: To examine whether drivers are aware of sleepiness and associated symptoms, and how subjective reports predict driving impairment and physiological drowsiness. METHODS: Sixteen shift workers (19-65 years; 9 women) drove an instrumented vehicle for 2 hours on a closed-loop track after a night of sleep and a night of work. Subjective sleepiness/symptoms were rated every 15 minutes. Severe and moderate driving impairment was defined by emergency brake maneuvers and lane deviations, respectively. Physiological drowsiness was defined by eye closures (Johns drowsiness scores) and EEG-based microsleep events. RESULTS: All subjective ratings increased post night-shift (p < 0.001). No severe drive events occurred without noticeable symptoms beforehand. All subjective sleepiness ratings, and specific symptoms, predicted a severe (emergency brake) driving event occurring in the next 15 minutes (OR: 1.76-2.4, AUC > 0.81, p < 0.009), except "head dropping down". Karolinska Sleepiness Scale (KSS), ocular symptoms, difficulty keeping to center of the road, and nodding off to sleep, were associated with a lane deviation in the next 15 minutes (OR: 1.17-1.24, p<0.029), although accuracy was only "fair" (AUC 0.59-0.65). All sleepiness ratings predicted severe ocular-based drowsiness (OR: 1.30-2.81, p < 0.001), with very good-to-excellent accuracy (AUC > 0.8), while moderate ocular-based drowsiness was predicted with fair-to-good accuracy (AUC > 0.62). KSS, likelihood of falling asleep, ocular symptoms, and "nodding off" predicted microsleep events, with fair-to-good accuracy (AUC 0.65-0.73). CONCLUSIONS: Drivers are aware of sleepiness, and many self-reported sleepiness symptoms predicted subsequent driving impairment/physiological drowsiness. Drivers should self-assess a wide range of sleepiness symptoms and stop driving when these occur to reduce the escalating risk of road crashes due to drowsiness.

Association between lung function and future risks of diabetes, asthma, myocardial infarction, hypertension and all-cause mortality.

BACKGROUND: While forced expiratory volume in 1 s (FEV1) is a hallmark of disease progression in chronic obstructive lung diseases, little is known about the relationship between baseline FEV1 and future risks of other medical conditions. OBJECTIVE: The aim of this study was to investigate the association between baseline FEV1 and future risks of diabetes, asthma, myocardial infarction, hypertension and all-cause mortality. METHODS: We used data from the National Health and Nutrition Examination Survey and its Epidemiological Follow-Up Study. Our data provided longitudinal follow-up of the original cohort for up to 12 years. We used two competing risks approaches, the cause-specific hazard model and the Fine-Gray sub-distribution hazard model, to measure the associations between baseline FEV1 and future risks of the outcomes of interest. All models were adjusted for major confounding factors. RESULTS: The final sample included 3020 participants (mean±sd baseline age 44.64±13.44 years). In the cause-specific hazard model, for every per cent increase in the baseline per cent predicted FEV1, the hazard of the event reduced by 2.5% (HR 0.975; 95% CI 0.958-0.994) for diabetes, 4.3% (HR 0.957; 95% CI 0.932-0.983) for asthma and 1.8% (HR 0.982; 95% CI 0.971-0.992) for all-cause mortality. There was no statistically significant association between baseline per cent predicted FEV1 and future risks of myocardial infarction (HR 0.987; 95% CI 0.970-1.004) and hypertension (HR 0.998; 95% CI 0.992-1.005). Consistent results were observed for the Fine-Gray sub-distribution hazard model. CONCLUSION: Our data suggest that lower per cent predicted FEV1 values at baseline were significantly associated with higher future risks of diabetes, asthma and all-cause mortality.

High-efficiency generation of narrowband soft x rays from carbon nanotube foams irradiated by relativistic femtosecond lasers.

A number of applications require x rays of both high flux and narrow bandwidth. In this work, we experimentally demonstrate the high-efficiency generation of narrowband soft x rays from carbon nanotube foams irradiated by a femtosecond laser pulse at an intensity of 1019W/cm2. The building blocks of the foam, single-walled carbon nanotube bundles with diameters smaller than the laser skin length can be volumetrically heated and fully ionized on a femtosecond time scale. The three-dimensional network structure of the foam permits deep penetration and drastic absorption of the laser pulse, and results in bright line emissions without prominent Stark broadening. A single-shot yield of 3×1014photons in the carbon Lyα line at 3.37 nm was measured with a bandwidth of 0.013 nm.

Association of Cancer Stem Cell Radio-Resistance Under Ultra-High Dose Rate FLASH Irradiation With Lysosome-Mediated Autophagy.

Cancer stem cell (CSC) is thought to be the major cause of radio-resistance and relapse post radiotherapy (RT). Recently ultra-high dose rate "FLASH-RT" evokes great interest for its decreasing normal tissue damages while maintaining tumor responses compared with conventional dose rate RT. However, the killing effect and mechanism of FLASH irradiation (FLASH-IR) on CSC and normal cancer cell are still unclear. Presently the radiation induced death profile of CSC and normal cancer cell were studied. Cells were irradiated with FLASH-IR (∼109 Gy/s) at the dose of 6-9 Gy via laser-accelerated nanosecond particles. Then the ratio of apoptosis, pyroptosis and necrosis were determined. The results showed that FLASH-IR can induce apoptosis, pyroptosis and necrosis in both CSC and normal cancer cell with different ratios. And CSC was more resistant to radiation than normal cancer cell under FLASH-IR. Further experiments tracing lysosome and autophagy showed that CSCs had higher levels of lysosome and autophagy. Taken together, our results suggested that the radio-resistance of CSC may associate with the increase of lysosome-mediated autophagy, and the decrease of apoptosis, necrosis and pyroptosis. To our limited knowledge, this is the first report shedding light on the killing effects and death pathways of CSC and normal cancer cell under FLASH-IR. By clarifying the death pathways of CSC and normal cancer cell under FLASH-IR, it may help us improve the understanding of the radio-resistance of CSC and thus help to optimize the future clinical FLASH treatment plan.

Ultra-High Dose Rate FLASH Irradiation Induced Radio-Resistance of Normal Fibroblast Cells Can Be Enhanced by Hypoxia and Mitochondrial Dysfunction Resulting From Loss of Cytochrome C.

Ultra-high dose rate FLASH irradiation (FLASH-IR) has got extensive attention since it may provide better protection on normal tissues while maintain tumor killing effect compared with conventional dose rate irradiation. The FLASH-IR induced protection effect on normal tissues is exhibited as radio-resistance of the irradiated normal cells, and is suggested to be related to oxygen depletion. However, the detailed cell death profile and pathways are still unclear. Presently normal mouse embryonic fibroblast cells were FLASH irradiated (∼109 Gy/s) at the dose of ∼10-40 Gy in hypoxic and normoxic condition, with ultra-fast laser-generated particles. The early apoptosis, late apoptosis and necrosis of cells were detected and analyzed at 6, 12, and 24 h post FLASH-IR. The results showed that FLASH-IR induced significant early apoptosis, late apoptosis and necrosis in normal fibroblast cells, and the apoptosis level increased with time, in either hypoxic or normoxic conditions. In addition, the proportion of early apoptosis, late apoptosis and necrosis were significantly lower in hypoxia than that of normoxia, indicating that radio-resistance of normal fibroblast cells under FLASH-IR can be enhanced by hypoxia. To further investigate the apoptosis related profile and potential pathways, mitochondria dysfunction cells resulting from loss of cytochrome c (cyt c-/-) were also irradiated. The results showed that compared with irradiated normal cells (cyt c+/+), the late apoptosis and necrosis but not early apoptosis proportions of irradiated cyt c-/- cells were significant decreased in both hypoxia and normoxia, indicating mitochondrial dysfunction increased radio-resistance of FLASH irradiated cells. Taken together, to our limited knowledge, this is the first report shedding light on the death profile and pathway of normal and cyt c-/- cells under FLASH-IR in hypoxic and normoxic circumstances, which might help us improve the understanding of the FLASH-IR induced protection effect in normal cells, and thus might potentially help to optimize the future clinical FLASH treatment.

Influence of Hostility on 24-Hour Diastolic Blood Pressure Load in Hypertension Patients with Depressive Disorders.

BACKGROUND Hostility in hypertension patients combined with depressive disorders indicates a worse outcome for hypertension management. This study was designed to explore the influence of hostility on 24-h diastolic blood pressure in hypertension patients who also had depressive disorders. MATERIAL AND METHODS A total of 130 people with primary hypertension and depressive disorders were collected through unstructured psychiatric interview by a professional psychiatrist and ambulatory blood pressure monitor in this cross-sectional study. During the study, dynamic blood pressure was examined for 24 h by ambulatory blood pressure monitoring. Patients were divided into 3 groups according to the hostility level. Hostility was defined by hostile factors of the Symptom Checklist 90. The association between hostility and 24-h dynamic blood pressure was analyzed by multivariable logistic regression. RESULTS 30.8% (40 of 130) patients had a high level of 24-h dynamic blood pressure load (>30%), in which 14.6% was for male and 16.2% for female respectively. In male, the proportion of high 24 h DBP load (>30%) in highest hostility group was greater than that of low hostility group and median hostility group significantly (p=0.03). No significant differences were revealed among 3 groups in female. The age-adjusted odds-ratio (OR) 95% confidence interval of diastolic blood pressure across the categories of hostility were: in males, 1.44 (0.60, 3.47) (1 for reference), and in females, 5.86 (0.58, 59.06) (P for trend=0.04). CONCLUSIONS Our results showed that hostility may be a risk factor for increased 24-h diastolic blood pressure in hypertension patients who also have depressive disorders, especially in males. The clinical meaning of the study is that hypertension management should contain psychological interventions for better effects.

Use of Smartphone Apps for Improving Physical Function Capacity in Cardiac Patient Rehabilitation: Systematic Review.

BACKGROUND: Cardiac rehabilitation (CR) is an evidence-based approach for preventing secondary cardiac events. Smartphone apps are starting to be used in CR to give patients real-time feedback on their health, connect them remotely with their medical team, and allow them to perform their rehabilitation at home. The use of smartphone apps is becoming omnipresent and has real potential in impacting patients in need of CR. OBJECTIVE: This paper provides critical examinations and summaries of existing research studies with an in-depth analysis of not only the individual studies but also the larger patterns that have emerged with smartphone apps in CR as well as their significance for practice change. METHODS: A systematic review was conducted through broad database searches that focused on evaluating randomized controlled trials, in compliance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) expectations. A total of 43 articles were evaluated, and 6 were chosen for this review. The dates of the articles ranged from 2014-2020, and the studies focused on the population of cardiac outpatients who needed CR after suffering a cardiac event, with interventions using a smartphone that incorporated the CR standards of the American Heart Association. The outcomes measured were directed at focusing on improved exercise function capacity, valued at a significance level of P<.05, for improved 6-minute walk test (6MWT) and peak oxygen uptake (PVO2) results. RESULTS: In the evaluated articles, the results were inconsistent for significant positive effects of CR smartphone apps on cardiac patients' physical function capacity in terms of the 6MWT and PVO2 when using a smartphone app to aid in CR. CONCLUSIONS: Because evidence in the literature suggests nonhomogeneous results for successful use of smartphone apps in CR, it is crucial to investigate the potential reasons for this inconsistency. An important observation from this systematic review is that smartphone apps used in CR have better clinical outcomes related to physical function capacity if the app automatically records information or provides real-time feedback to participants about their progress, compared to apps that only educate and encourage use while requiring the participant to manually log their CR activities. Additional factors to consider during these studies include the starting health of the patients, the sample sizes, and the specific components of CR that the smartphone apps are using. Overall, more clinical trials are needed that implement smartphone apps with these factors in mind, while placing stronger emphasis on using biosensing capabilities that can automatically log results and send them to providers on a real-time dashboard.

A Physical Activity Mobile Game for Hematopoietic Stem Cell Transplant Patients: App Design, Development, and Evaluation.

BACKGROUND: Physical activity mobile apps may encourage patients with cancer to increase exercise uptake, consequently decreasing cancer-related fatigue. While many fitness apps are currently available for download, most are not suitable for patients with cancer due to the unique barriers these patients face, such as fatigue, pain, and nausea. OBJECTIVE: The aim of this study is to design, develop, and perform alpha testing of a physical activity mobile health game for hematopoietic stem cell transplant (HSCT) patients. The ultimate future goal of this project is to motivate HSCT patients to increase physical activity and provide them with a safe and fun way to exercise. METHODS: A mobile health game called Walking Warrior was designed as a puzzle game where tiles are moved and matched. Walking Warrior interfaces with an open-source step counter and communicates with a central online MySQL database to record game play and walking performance. The game came to fruition after following an iterative process model with several prototypes. Game developers and bone marrow transplant nurses were recruited to perform an expert usability evaluation of the Walking Warrior prototype by completing a heuristic questionnaire and providing qualitative suggestions for improvement. Experts also made qualitative recommendations for improvements on speed, movement of tiles, appearance, and accuracy of the step counter. We recruited 5 additional usability evaluators who searched for and compared 4 open-source step counter programs, then qualitatively compared them for accuracy, robustness, cheat proofing, ease of use, and battery drain issues. Patient recruitment is planned at a later stage in this project. This paper only describes software design, development, and evaluation, rather than behavioral evaluation (ie, impact on physical activity), which is the long-term goal of this project. RESULTS: Internal consistency and the instrument's reliability evaluation results from 1 clinical expert and 4 technical experts were deemed excellent (Cronbach α=.933). A hierarchical cluster analysis of the questionnaire item responses for similarity/dissimilarity among the experts indicated that the two expert groups were not clustered into two separate groups in the dendrogram. This indicates that the item responses were not affected by profession. Factor analyses indicate that responses from the 40-item questionnaire were classified into five primary factors. The associated descriptive statistics for each of these categories were as follows (on a scale of 1 to 5): clarity and ease (median 4; mean 3.7, SD 0.45), appropriateness (median 4; mean 3.7, SD 0.49), game quality (median 3.5; mean 3.3, SD 0.42), motivation to walk (median 3; mean 3.1, SD 0.58), and mental effort (median 3.5; mean 3.1, SD 1.27). CONCLUSIONS: The evaluation from experts and clinicians provided qualitative information to further improve game design and development. Findings from the expert usability evaluation suggest the game's assets of clarity, ease of use, appropriateness, quality, motivation to walk, and mental effort were all favorable. This mobile game could ultimately help patients increase physical activity as an aid to recovery.

Type I Diabetes Self-management With Game-Based Interventions for Pediatric and Adolescent Patients.

Type 1 diabetes is a disease with a peak diagnosis between the ages of 10 and 14 and carries with it required intensive lifestyle changes. Disease self-management is essential for adequate metabolic control to prevent acute and long-term complications. Yet common methods of diabetes self-management education, such as lectures or pamphlets, lead to low knowledge, engagement, and clinical outcomes. Game-based learning has led to increased motivation, engagement, and productivity overall with substantial increases in self-management of chronic diseases in children. The purpose of this article is to review and synthesize literature on the impact on self-management knowledge, behavior, and engagement of the game-based interventions of serious games and gamification for children and adolescents with type 1 diabetes. Nine studies were reviewed. Results showed statistically significant differences in knowledge, behavior, and engagement in response to the game-based interventions. Knowledge outcomes were found most significant in serious game interventions, while behavioral outcomes were predominantly found in gamification/serious game combination interventions. Findings also reveal there was inconsistent use of theories for game development and moderate to low quality of evidence across studies. While the nine studies reviewed strongly demonstrate the potential of game-based tools to significantly improve type 1 diabetes self-management care, further studies with expanded and more rigorous study parameters are recommended before an outright change in practice may be applied. The potential impact of the clinical nurse leader in the use and research of game-based interventions is also discussed.

Detection of driver manual distraction via image-based hand and ear recognition.

Driving distraction is a leading cause of fatal car accidents, and almost nine people are killed in the US each day because of distracting activities. Therefore, reducing the number of distraction-affected traffic accidents remains an imperative issue. A novel algorithm for detection of drivers' manual distraction was proposed in this manuscript. The detection algorithm consists of two modules. The first module predicts the bounding boxes of the driver's right hand and right ear from RGB images. The second module takes the bounding boxes as input and predicts the type of distraction. 106,677 frames extracted from videos, which were collected from twenty participants in a driving simulator, were used for training (50%) and testing (50%). For distraction classification, the results indicated that the proposed framework could detect normal driving, using the touchscreen, and talking with a phone with F1-score 0.84, 0.69, 0.82, respectively. For overall distraction detection, it achieved F1-score of 0.74. The whole framework ran at 28 frames per second. The algorithm achieved comparable overall accuracy with similar research, and was more efficient than other methods. A demo video for the algorithm can be found at https://youtu.be/NKclK1bHRd4.

Computer- and Robot-Assisted Therapies to Aid Social and Intellectual Functioning of Children with Autism Spectrum Disorder.

BACKGROUND AND OBJECTIVES: Children with autism spectrum disorder (ASD) experience challenges with social interactions, a core feature of the disorder. Social skills therapy has been shown to be helpful. Over the past several years, computer-assisted and robot-assisted therapies have been infiltrating the social skills teaching environment. Rapid progress in the field of technology, especially in the robotics area, offers tremendous possibilities for innovation and treatment or even education for individuals with ASD. This paper's purpose is to drive awareness of these innovative interventions in order to support the social lives of children with ASD. The aims of the paper are identifying (1) the types of Information Technology platforms that are being evaluated in computer and robot-assisted therapies for children with ASD; (2) the various disciplines or professions studying and utilizing these computer and robot-assisted social skill therapies; (3) the outcomes being evaluated in each trial; and (4) if results demonstrate benefits to children with autism. MATERIALS AND METHODS: PubMed, CINAHL, Science Direct, and Web of Science databases were searched for clinical trials published over the past five years. Search terms incorporated the subject intersection of autism, and computer or robot-assisted therapy. Results were mined for pediatric populations only and study designs establishing controlled comparisons. RESULTS: Eighteen unique international studies were identified that utilize robot interventions (11 studies) and serious computer game interventions (seven studies). Most demonstrated promising results in improving outcomes for children with ASD. Study implications reveal a rapidly evolving assistive technology for ASD social skills therapy. CONCLUSIONS: These interventions show considerable promise, but more effectiveness and cost effectiveness research of high quality should be carried out with larger numbers of children. Also, further studies are necessary to evaluate these technologies' effectiveness amongst adults with ASD and within unique subsets of the higher functioning autism population.

Reproducibility of biomarker identifications from mass spectrometry proteomic data in cancer studies.

Reproducibility of disease signatures and clinical biomarkers in multi-omics disease analysis has been a key challenge due to a multitude of factors. The heterogeneity of the limited sample, various biological factors such as environmental confounders, and the inherent experimental and technical noises, compounded with the inadequacy of statistical tools, can lead to the misinterpretation of results, and subsequently very different biology. In this paper, we investigate the biomarker reproducibility issues, potentially caused by differences of statistical methods with varied distribution assumptions or marker selection criteria using Mass Spectrometry proteomic ovarian tumor data. We examine the relationship between effect sizes, p values, Cauchy p values, False Discovery Rate p values, and the rank fractions of identified proteins out of thousands in the limited heterogeneous sample. We compared the markers identified from statistical single features selection approaches with machine learning wrapper methods. The results reveal marked differences when selecting the protein markers from varied methods with potential selection biases and false discoveries, which may be due to the small effects, different distribution assumptions, and p value type criteria versus prediction accuracies. The alternative solutions and other related issues are discussed in supporting the reproducibility of findings for clinical actionable outcomes.

Effectiveness of a telephone-delivered psycho-behavioural intervention on depression in elderly with chronic heart failure: rationale and design of a randomized controlled trial.

BACKGROUND: Depression is common among chronic heart failure (CHF) patients, and it is associated with significant re-hospitalization and mortality as well as lower quality of life. While psychotherapy is efficacious treatment for depression, the effect for depression among CHF is uncertain. And barriers preclude widely utility of psychotherapy among the elderly. Telephone-delivered psycho-behavioural intervention specifically focuses on depression among the elderly with CHF, and could be a promising alternative to conventional treatment. The present study was designed to prospectively investigate the effect of a telephone-delivered psycho-behavioural intervention on depression in the elderly with chronic heart failure (CHF). METHOD/DESIGN: In this prospective, multicentre, parallel, randomized, and controlled trial, 236 participants with depression associated with CHF (New York Heart Association classes II and III) will be enrolled. The study will consist of a 12-week intensive intervention and a 24-week maintenance intervention. Eligible participants will be randomized to either the intervention arm or the control arm. During the intensive phase, participants will receive either a guided telephone psycho-behavioural intervention or regular telephone contacts from the counsellors weekly. During the maintenance phase, participants will receive either psychological behavioural support or regular telephone contacts monthly from counsellors. Depressive symptoms, cardiac outcome and quality of life will be assessed at baseline and weeks 1, 2, 4, 8, 12, 24 and 36. Participants will undergo echocardiography and the plasma concentrations of N-terminal pro-brain natriuretic peptide (NT-proBNP) tested at baseline, weeks 12 and 36. The primary outcome is the response rate of depression, from baseline to week 12. The second outcomes include the change in cardiac function, quality of life and severity of depressive symptoms during the trial. DISCUSSION: To our knowledge, this study is the first prospective randomized trial to test the effective of the telephone-delivered psycho-behavioural intervention on depression in the elderly with CHF. The findings are expected to provide a new and evidence-based approach for depression among the elderly with CHF. TRIAL REGISTRATION: The trial was registered at www.clinicaltrials.gov (identification number: NCT03233451 ) on 28 July 2017 and updated on 18 August 2017.

Amido surface-functionalized magnetic molecularly imprinted polymers for the efficient extraction of Sibiskoside from Sibiraea angustata.

A general method for efficient and selective extraction of a target compound from complex natural products remains elusive, despite decades of research. By introducing a functional amido group on the surface of dispersity-enhanced magnetic nanoparticles, a nanoparticle receptor to selectively recognize Sibiskoside (a monoterpene) from the aerial portion of Sibiraea angustata by hydrogen bond interaction was synthesized. The superparamagnetic Fe3O4 nanoparticles were successively modified with tetraethyl orthosilicate (TEOS), amino and amido functional groups, and 4-vinylbenzoic acid (VBZA) was used as the functional monomer. A thin layer of poly (VBZA) imprinted with Sibiskoside was immobilized on the surface of magnetic carriers. Attributing to the amido group introduced into the magnetic particles, the template could attract and bind to the surface and promote the formation of a hydrogen bond system between the carrier, template molecules and functional monomer. High-density molecular recognition sites grew on the surface of magnetic substrate. The adsorption reached equilibrium at approximately 150 min, while fast adsorption occurred during the first 60 min. The maximum adsorption capacity has been found to be 13.75 mg g-1 according to calculation with the Langmuir isotherm. The selectivity coefficients of Molecular imprinting polypers (MIPs) for Sibiskoside with respect to Andrographolide, Loganin, Gastrodin, geraniol-1-O-[α-l-rhamnopyranosyl-(1 → 6)-1-ß-d-glucopyranoside] (GRG), Sibiscolacton and Sibiraic acid were 2.26, 1.43, 1.701.56, 1.05, 0.73 and, respectively. The results indicated that the MIPs possessed good specific adsorption capacity and selectivity toward Sibiskoside and had the potential to be a candidate for the separation and purification of monoterpenes from Sibiraea angustata, which is of great significance to obesity management.

Creation and Evaluation of a Preoperative Education Website for Hip and Knee Replacement Patients-A Pilot Study.

The use of websites to provide patient education is becoming more common. The benefits of a properly executed and effective preoperative patient educational intervention have been shown to result in improved psychological and physical well-being for patients undergoing surgery. The purpose of this pilot study was to determine the usability, utility, and feasibility of a website we created to increase engagement and improve the quality of the preoperative education patients receive in preparation for hip and knee arthroplasty. Eighty patients who met the inclusion criteria were recruited, aged between 40 to 65, among those 52.5% were female, 71.25% were placed for knee replacement, 28.75% for hip replacement. Forty patients were randomly assigned to paper education cohort, 40 to the paper and website education cohort. However, only 19 from each cohort participated in the survey questionnaire. The outcome of interest included qualitative data for patient knowledge, satisfaction, utilities, and usability, which were assessed based on the Perceived Health Website Usability Questionnaire online survey. The paper-based survey contains ten questions using a 7-point Likert scale while the web-based survey contains fourteen questions using the same 7-point Likert scale. Descriptive statistics and independent samples t-tests were used for comparative analysis of usual paper education and website education cohorts; whereby Microsoft Excel data analytics tool was used to compute the results. The Alpha level was set to 0.05 for the statistical results. The result of the study showed no statistically significant differences in both cohorts at the 0.05 level. We hypothesized that both information delivery methods were effective in increasing knowledge and engaging patients to their preoperative educations. According to the survey result for the nursing staff, they believed that the use of the website improved nursing workflow, efficiency, and patient education.

Prediction of drowsiness events in night shift workers during morning driving.

The morning commute home is an especially vulnerable time for workers engaged in night shift work due to the heightened risk of experiencing drowsy driving. One strategy to manage this risk is to monitor the driver's state in real time using an in vehicle monitoring system and to alert drivers when they are becoming sleepy. The primary objective of this study is to build and evaluate predictive models for drowsiness events occurring in morning drives using a variety of physiological and performance data gathered under a real driving scenario. We used data collected from 16 night shift workers who drove an instrumented vehicle for approximately two hours on a test track on two occasions: after a night shift and after a night of rest. Drowsiness was defined by two outcome events: performance degradation (Lane-Crossing models) and electroencephalogram (EEG) characterized sleep episodes (Microsleep Models). For each outcome, we assessed the accuracy of sets of predictors, including or not including a driver factor, eyelid measures, and driving performance measures. We also compared the predictions using different time intervals relative to the events (e.g., 1-min prior to the event through 10-min prior). By examining the Area Under the receiver operating characteristic Curve (AUC), accuracy, sensitivity, and specificity of the predictive models, the results showed that the inclusion of an individual driver factor improved AUC and prediction accuracy for both outcomes. Eyelid measures improved the prediction for the Lane-Crossing models, but not for Microsleep models. Prediction performance was not changed by adding driving performance predictors or by increasing the time to the event for either outcome. The best models for both measures of drowsiness were those considering driver individual differences and eyelid measures, suggesting that these indicators should be strongly considered when predicting drowsiness events. The results of this paper can benefit the development of real-time drowsiness detection and help to manage drowsiness to avoid related motor-vehicle crashes and loss.

[Molecular imprinting technology and its application in terpenoids].

Molecular imprinting technology is widely used in the separation and analysis of compounds such as flavonoids, alkaloids and polyphenols, due to its high selectivity and specific recognition and so on. However, no much of attention has been paid to the terpenoids. This paper is aimed to not only review the effects of common synthetic elements such as functional monomers, cross-linking agents and porogens on the polymer properties, but also highlight the application of terpene molecular imprinting in solid phase extraction, sensor, membrane separation and chromatographic separation by means of statistical analysis of literature. Furthermore, the shortcomings and improvement directions are discussed.We believed that this paper could provide references for better applications of molecular imprinting techniques to the analysis of terpenoid compounds.

Dynamic modeling and network approaches for omics time course data: overview of computational approaches and applications.

Inferring networks and dynamics of genes, proteins, cells and other biological entities from high-throughput biological omics data is a central and challenging issue in computational and systems biology. This is essential for understanding the complexity of human health, disease susceptibility and pathogenesis for Predictive, Preventive, Personalized and Participatory (P4) system and precision medicine. The delineation of the possible interactions of all genes/proteins in a genome/proteome is a task for which conventional experimental techniques are ill suited. Urgently needed are rapid and inexpensive computational and statistical methods that can identify interacting candidate disease genes or drug targets out of thousands that can be further investigated or validated by experimentations. Moreover, identifying biological dynamic systems, and simultaneously estimating the important kinetic structural and functional parameters, which may not be experimentally accessible could be important directions for drug-disease-gene network studies. In this article, we present an overview and comparison of recent developments of dynamic modeling and network approaches for time-course omics data, and their applications to various biological systems, health conditions and disease statuses. Moreover, various data reduction and analytical schemes ranging from mathematical to computational to statistical methods are compared including their merits, drawbacks and limitations. The most recent software, associated web resources and other potentials for the compared methods are also presented and discussed in detail.

Shared polymorphisms and modifiable behavior factors for myocardial infarction and high cholesterol in a retrospective population study.

Genetic and environmental (behavior, clinical, and demographic) factors are associated with increased risks of both myocardial infarction (MI) and high cholesterol (HC). It is known that HC is major risk factor that may cause MI. However, whether there are common single nucleotide polymorphism (SNPs) associated with both MI and HC is not firmly established, and whether there are modulate and modified effects (interactions of genetic and known environmental factors) on either HC or MI, and whether these joint effects improve the predictions of MI, is understudied.The purpose of this study is to identify novel shared SNPs and modifiable environmental factors on MI and HC. We assess whether SNPs from a metabolic pathway related to MI may relate to HC; whether there are moderate effects among SNPs, lifestyle (smoke and drinking), HC, and MI after controlling other factors [gender, body mass index (BMI), and hypertension (HTN)]; and evaluate prediction power of the joint and modulate genetic and environmental factors influencing the MI and HC.This is a retrospective study with residents of Erie and Niagara counties in New York with a history of MI or with no history of MI. The data set includes environmental variables (demographic, clinical, lifestyle). Thirty-one tagSNPs from a metabolic pathway related to MI are genotyped. Generalized linear models (GLMs) with imputation-based analysis are conducted for examining the common effects of tagSNPs and environmental exposures and their interactions on having a history of HC or MI.MI, BMI, and HTN are significant risk factors for HC. HC shows the strongest effect on risk of MI in addition to HTN; gender and smoking status while drinking status shows protective effect on MI. rs16944 (gene IL-1ß) and rs17222772 (gene ALOX) increase the risks of HC, while rs17231896 (gene CETP) has protective effects on HC either with or without the clinical, behavioral, demographic factors with different effect sizes that may indicate the existence of moderate or modifiable effects. Further analysis with the inclusions of gene-gene and gene-environmental interactions shows interactions between rs17231896 (CETP) and rs17222772 (ALOX); rs17231896 (CETP) and gender. rs17237890 (CETP) and rs2070744 (NOS3) are found to be significantly associated with risks of MI adjusted by both SNPs and environmental factors. After multiple testing adjustments, these effects diminished as expected. In addition, an interaction between drinking and smoking status is significant. Overall, the prediction power in successfully classifying MI status is increased to 80% with inclusions of all significant tagSNPs and environmental factors and their interactions compared with environmental factors only (72%).Having a history of either HC or MI has significant effects on each other in both directions, in addition to HTN and gender. Genes/SNPs identified from this analysis that are associated with HC may be potentially linked to MI, which could be further examined and validated through haplotype-pairs analysis with appropriate population stratification corrections, and function/pathway regulation analysis to eliminate the limitations of the current analysis.

Computational dynamic approaches for temporal omics data with applications to systems medicine.

Modeling and predicting biological dynamic systems and simultaneously estimating the kinetic structural and functional parameters are extremely important in systems and computational biology. This is key for understanding the complexity of the human health, drug response, disease susceptibility and pathogenesis for systems medicine. Temporal omics data used to measure the dynamic biological systems are essentials to discover complex biological interactions and clinical mechanism and causations. However, the delineation of the possible associations and causalities of genes, proteins, metabolites, cells and other biological entities from high throughput time course omics data is challenging for which conventional experimental techniques are not suited in the big omics era. In this paper, we present various recently developed dynamic trajectory and causal network approaches for temporal omics data, which are extremely useful for those researchers who want to start working in this challenging research area. Moreover, applications to various biological systems, health conditions and disease status, and examples that summarize the state-of-the art performances depending on different specific mining tasks are presented. We critically discuss the merits, drawbacks and limitations of the approaches, and the associated main challenges for the years ahead. The most recent computing tools and software to analyze specific problem type, associated platform resources, and other potentials for the dynamic trajectory and interaction methods are also presented and discussed in detail.