Surfactant Micelle-Driven High-Efficiency and High-Resolution Length Separation of Carbon Nanotubes for Electronic Applications.

High-efficiency extraction of long single-wall carbon nanotubes (SWCNTs) with excellent optoelectronic properties from SWCNT solution is critical for enabling their application in high-performance optoelectronic devices. Here, a straightforward and high-efficiency method is reported for length separation of SWCNTs by modulating the concentrations of binary surfactants. The results demonstrate that long SWCNTs can spontaneously precipitate for binary-surfactant but not for single-surfactant systems. This effect is attributed to the formation of compound micelles by binary surfactants that squeeze the free space of long SWCNTs due to their large excluded volumes. With this technique, it can readily separate near-pure long (≥500 nm in length, 99% in content) and short (≤500 nm in length, 98% in content) SWCNTs with separation efficiencies of 26% and 64%, respectively, exhibiting markedly greater length resolution and separation efficiency than those of previously reported methods. Thin-film transistors fabricated from extracted semiconducting SWCNTs with lengths >500 nm exhibit significantly improved electrical properties, including a 10.5-fold on-state current and 14.7-fold mobility, compared with those with lengths <500 nm. The present length separation technique is perfectly compatible with various surfactant-based methods for structure separations of SWCNTs and is significant for fabrication of high-performance electronic and optoelectronic devices.

Nurses' preparedness, opinions, barriers, and facilitators in responding to intimate partner violence: A mixed-methods study.

INTRODUCTION: Intimate partner violence (IPV) is associated with multiple adverse health consequences. Nurses (including midwives) are well positioned to identify patients subjected to IPV, and provide care, support, and referrals. However, studies about nursing response to IPV are limited especially in low- and middle-income countries (LMICs). The study aimed to examine nurses' perceived preparedness and opinions toward IPV and to identify barriers and facilitators in responding to IPV. DESIGN: An explanatory sequential mixed-methods study was conducted by collecting quantitative data first and explaining the quantitative findings with qualitative data. METHODS: The study was conducted in two tertiary general hospitals in northeastern (Shenyang city) and southwestern (Chengdu city) China with 1500 and 1800 beds, respectively. A total of 1071 survey respondents (1039 female [97.0%]) and 43 interview participants (34 female [79.1%]) were included in the study. An online survey was administered from September 3 to 23, 2020, using two validated scales from the Physician Readiness to Manage Intimate Partner Violence Survey. In-depth, semistructured interviews were conducted from September 15 to December 23, 2020, guided by the Consolidated Framework for Implementation Research. RESULTS: The survey respondents largely agreed with feeling prepared to manage IPV, e.g., respond to discourses (544 [50.8%] of 1071) and report to police (704 [65.7%] of 1071). The findings of surveyed opinions (i.e., Response competencies; Routine practice; Actual activities; Professionals; Victims; Alcohol/drugs) were mixed and intertwined with social desirability bias. The quantitative and qualitative data were consistent, contradicted, and supplemented. Key qualitative findings were revealed that may explain the quantitative results, including lack of actual preparedness, absence of IPV-related education, training, or practice, and socially desirable responses (especially those pertaining to China's Anti-domestic Violence Law). Commonly reported barriers (e.g., patients' reluctance to disclose; time constraints) and facilitators (e.g., patients' strong need for help; female nurses' gender advantage), as well as previously unreported barriers (e.g., IPV may become a workplace taboo if there are healthcare professionals known as victims/perpetrators of IPV) and facilitators (e.g., nurses' responses can largely meet the first-line support requirements even without formal education or training on IPV) were identified. CONCLUSIONS: Nurses may play a unique and important role in responding to IPV in LMICs where recognition is limited, education and training are absent, policies are lacking, and resources are scarce. Our findings support World Health Organization recommendations for selective screening. CLINICAL RELEVANCE: The study highlights the great potential of nurses for IPV prevention and intervention especially in LMICs. The identified barriers and facilitators are important evidence for developing multifaceted interventions to address IPV in the health sector.

Prostate cancer early diagnosis: circulating microRNA pairs potentially beyond single microRNAs upon 1231 serum samples.

The accuracy of prostate-specific antigen or clinical examination in prostate cancer (PCa) screening is in question, and circulating microRNAs (miRNAs) can be alternatives to PCa diagnosis. However, recent circulating miRNA biomarkers either are identified upon small sample sizes or cannot have robust diagnostic performance in every aspect of performance indicators. These may decrease applicability of potential biomarkers for the early detection of PCa. We reviewed recent studies on blood-derived miRNAs for prostate cancer diagnosis and carried out a large case study to understand whether circulating miRNA pairs, rather than single circulating miRNAs, could contribute to a more robust diagnostic model to significantly improve PCa diagnosis. We used 1231 high-throughput miRNA-profiled serum samples from two cohorts to design and verify a model based on class separability miRNA pairs (cs-miRPs). The pairwise model was composed of five circulating miRNAs coupled to miR-5100 and miR-1290 (i.e. five miRNA pairs, 5-cs-miRPs), reaching approximately 99% diagnostic performance in almost all indicators (sensitivity = 98.96%, specificity = 100%, accuracy = 99.17%, PPV = 100%, NPV = 96.15%) shown by a test set (n = 484: PCa = 384, negative prostate biopsies = 100). The nearly 99% diagnostic performance was also verified by an additional validation set (n = 140: PCa = 40, healthy controls = 100). Overall, the 5-cs-miRP model had 1 false positive and 7 false negatives among the 1231 serum samples and was superior to a recent 2-miRNA model (so far the best for PCa diagnosis) with 18 false positives and 80 false negatives. The present large case study demonstrated that circulating miRNA pairs could potentially bring more benefits to PCa early diagnosis for clinical practice.

Joint Power Control and Resource Allocation with Rate Fairness Consideration for SWIPT-Based Cognitive Two-Way Relay Networks.

This paper investigates the power control and resource allocation problem in a simultaneously wireless information and power transfer (SWIPT)-based cognitive two-way relay network, in which two secondary users exchange information through a power splitting (PS) energy harvesting (EH) cognitive relay node underlay in a primary network. To enhance the secondary networks's transmission ability without detriment to the primary network, we formulate an optimization to maximize the minimum transmission rates of the cognitive users by jointly optimizing power allocation at the sources, the time allocation of transmission frames and power splitting at the relay, under the constraint that the transmission power of the cognitive network is set not to exceed the primary user interference threshold to ensure primary work performance. To efficiently solve this problem, a sub-optimal algorithm named the joint power control and resource allocation (JPCRA) scheme is proposed, in which we decouple the non-convex problem into convex problems and use alternative steps in the optimization algorithm to get final solutions. Numerical results reveal that the proposed scheme enhances transmission fairness and outperforms three traditional schemes.

Extended endocrine therapy in breast cancer: A basket of length-constraint feature selection metaheuristics to balance Type I against Type II errors.

Extended endocrine therapy beyond 5 years is of major concern to ER + breast cancer survivors. However, it might be unsuitable to apply routinely used genomic tests designed for early recurrence risks to distant recurrence within 10 years in extended treatment context. These tests initially aim at high sensitivities with Type I errors much higher than Type II. Having lower positive predictive values (PPVs), these tests can bring many false positives who might not need further treatment options to avoid adversely affecting quality of life. Alternatively, we proposed a top-down approach to the raised issues. We built 149 targeted genes from four genomic tests upon 381 ER-positive node-negative patients with either metastasis free beyond 10 years (n = 202) or metastasis within 10 years (n = 179). By a basket of SVM-wrapped length-constraint feature selection (LCFS), we discovered four genomic SVMs that traded off Type I against Type II errors. Two independent cohorts were used to validate disease outcome predictions. A 36-gene SVM balanced sensitivities with PPVs at good levels: 74% vs 76% on 10-fold cross validation (n = 347) and 75% vs 71% on a test set (n = 34). Neither Oncotype DX RS (cutoff = 18, 31, 60.97) nor PAM50 ROR-S (cutoff = 29, 53, 61.18) could. Independent cohorts showed the 36-gene SVM predicted disease free survival (n = 136, HR = 2.59; 95% CI, 1.4-4.8) and disease specific survival (n = 127, HR = 4.06; 95% CI, 1.63-10.11) better than RS (DFS, HR = 2.15; DSS, HR = 3.86) and ROR-S (DFS, HR = 2.29; DSS, HR = 2.76). The case study demonstrated how we identified a genomic test to balance Type I against Type II errors for risk stratification. The top-down approach centered around the LCFS-metaheuristics basket is a generic methodology for clinical decision-making and quality of life using targeted profiling data where the number of dimensions (p) is smaller than the number of samples (n).

Near Miss Research in the Healthcare System: A Scoping Review.

OBJECTIVES: The aim of this study was to depict a comprehensive description of near miss research and clarify research gaps. BACKGROUND: Learning from near miss can provide early warnings and is critical for proactive and prospective risk management. Because of the lack of structured reviews, there is little knowledge about how near miss management has been managed in the past. METHODS: This review was conducted following the Arksey and O'Malley's methodology and reported by the PRISMA Extension for Scoping Reviews. RESULTS: Sixty-seven research articles were included. The results revealed that the most investigated fields include near miss reporting, near miss characteristics, and good catch project. Poor theoretical investigation, underreporting, and inconsistent outcome indicators are major problems. CONCLUSIONS: Solely understanding causes of near misses cannot guarantee effective learning; we also need to apply appropriate learning theories. Advanced technologies should be applied to solve long-standing underreporting issues. Accurate and consistent indicators should be applied in near miss research and management.

Fixed Point Iteration Based Algorithm for Asynchronous TOA-Based Source Localization.

This paper investigates the problem of source localization using signal time-of-arrival (TOA) measurements in the presence of unknown start transmission time. Most state-of-art methods are based on convex relaxation technologies, which possess global solution for the relaxed optimization problem. However, computational complexity of the convex optimization-based algorithm is usually large, and need CVX toolbox to solve it. Although the two stage weighted least squares (2SWLS) algorithm has very low computational complexity, its estimate performance is susceptible to sensor geometry and threshold phenomenon. A new algorithm that is directly derived from maximum likelihood estimator (MLE) is developed. The newly proposed algorithm is named as fixed point iteration (FPI); it only involves simple calculations, such as addition, multiplication, division, and square-root. Unlike state-of-the-art methods, there is no matrix inversion operation and can avoid the unstable performance incurred by singular matrix. The FPI algorithm can be easily extended to the scenario with sensor position errors. Finally, simulation results demonstrate that the proposed algorithm reaches a good balance between computational complexity and localization accuracy.

A Machine Learning Approach to Improve Ranging Accuracy with AoA and RSSI.

Ranging accuracy is a critical parameter in time-based indoor positioning systems. Indoor environments often have complex structures, which make centimeter-level-accurate ranging a challenging task. This study proposes a new distance measurement method to decrease the ranging error in multipath environment. Our method uses an artificial neural network that utilizes the received signal strength indicator along with a signal's angle of arrival to calculate the line-of-sight distance. This combination results in a significant reduction of the error caused by multipath effects that common RSSI-based methods suffer from. It outperforms traditional ranging methods while the implementation complexity is kept low.

Near-miss organizational learning in nursing within a tertiary hospital: a mixed methods study.

BACKGROUND: Near-miss organizational learning is important for perspective and proactive risk management. Although nursing organizations are the largest component of the healthcare system and act as the final safety barrier, there is little research about the current status of near-miss organizational learning. Thus, we conducted this study to explore near-miss organizational learning in a Chinese nursing organization and offer suggestions for future improvement. METHODS: This was a mixed methods study with an explanatory sequence. It was conducted in a Chinese nursing organization of a tertiary hospital under the guidance of the 4I Framework of Organizational Learning. The quantitative study surveyed 600 nurses by simple random sampling. Then, we applied purposive sampling to recruit 16 nurses across managerial levels from low-, middle- and high-scored nursing units and conducted semi-structured interviews. Descriptive statistics, structured equation modelling and content analysis were applied in the data analysis. The Good Reporting of A Mixed Methods Study (GRAMMS) checklist was used to report this study. RESULTS: Only 33% of participants correctly recognized near-misses, and 4% of participants always reported near-misses. The 4I Framework of Organizational Learning was verified in the surveyed nursing organization (χ2 = 0.775, p = 0.379, RMSEA < 0.01). The current organizational learning behaviour was not conducive to near-miss organizational learning due to poor group-level learning (ßGG = 0.284) and poor learning absorption (ßMisalignment= -0.339). In addition, the researchers developed 13 codes, 9 categories and 5 themes to depict near-miss organizational learning, which were characterized by nurses' unfamiliarity with near-misses, preferences and the dominance of first-order problem-solving behaviour, the suspension of near-miss learning at the group level and poor learning absorption. CONCLUSION: The performance of near-miss organizational learning is unsatisfactory across all levels in surveyed nursing organization, especially with regard to group-level learning and poor learning absorption. Our research findings offer a scientific and comprehensive description of near-miss organizational learning and shed light on how to measure and improve near-miss organizational learning in the future.

Response to the COVID-19 Outbreak in Urban Settings in China.

The COVID-19 outbreak in China was devastating and spread throughout the country before being contained. Stringent physical distancing recommendations and shelter-in-place were first introduced in the hardest-hit provinces, and by March, these recommendations were uniform throughout the country. In the presence of an evolving and deadly pandemic, we sought to investigate the impact of this pandemic on individual well-being and prevention practices among Chinese urban residents. From March 2-11, 2020, 4607 individuals were recruited from 11 provinces with varying numbers of COVID-19 cases using the social networking app WeChat to complete a brief, anonymous, online survey. The analytical sample was restricted to 2551 urban residents. Standardized scales measured generalized anxiety disorder (GAD), the primary outcome. Multiple logistic regression was conducted to identify correlates of GAD alongside assessment of community practices in response to the COVID-19 pandemic. We found that during the COVID-19 pandemic, the recommended public health practices significantly (p < 0.001) increased, including wearing facial mask, practicing physical distancing, handwashing, decreased public spitting, and going outside in urban communities. Overall, 40.3% of participants met screening criteria for GAD and 49.3%, 62.6%, and 55.4% reported that their work, social life, and family life were interrupted by anxious feelings, respectively. Independent correlates of having anxiety symptoms included being a healthcare provider (aOR = 1.58, p < 0.01), living in regions with a higher density of COVID-19 cases (aOR = 2.13, p < 0.01), having completed college (aOR = 1.38, p = 0.03), meeting screening criteria for depression (aOR = 6.03, p < 0.01), and poorer perceived health status (aOR = 1.54, p < 0.01). COVID-19 had a profound impact on the health of urban dwellers throughout China. Not only did they markedly increase their self- and community-protective behaviors, but they also experienced high levels of anxiety associated with a heightened vulnerability like depression, having poor perceived health, and the potential of increased exposure to COVID-19 such as living closer to the epicenter of the pandemic.

Photoluminescence Quantum Yield of Single-Wall Carbon Nanotubes Corrected for the Photon Reabsorption Effect.

Photoluminescence (PL) from single-wall carbon nanotubes (SWCNTs) enables structural identification, but to derive the content rate of the specific chirality species it is necessary to know the quantum yield of each chirality. However, in the PL of SWCNTs, because the Stokes shift is small, the photon reabsorption effect is dominant and the apparent PL spectral shape and emission intensity are greatly modified depending on the concentration. This problem makes quantitative identification of SWCNTs by PL difficult. In this study, the concentration dependence of the PL of SWCNTs separated into a few chiralities was analyzed in detail, including the effect of reabsorption. It is clear that all changes in the PL spectrum occurring in the high concentration range can be explained simply by the reabsorption effect, and additional effects such as Coulomb interactions between SWCNTs can be negligible. Furthermore, a reliable quantum yield was derived from the emission intensity corrected for the reabsorption effect. The PL quantum yield varied with SWCNT chirality and exhibited a clear "family pattern". This is consistent with the theoretical report showing that the chirality-dependent PL quantum yield is dominated mainly by relaxation by optical phonons from E22 to E11.

Early Intervention for Preterm Infants and Their Mothers: A Systematic Review.

This systematic review evaluates the efficacy of various early interventions on maternal emotional outcomes, mother-infant interaction, and subsequent infant outcomes during neonatal intensive care unit admission and postdischarge. Key interventions associated with outcomes in both the neonatal intensive care unit and postdischarge (ie, home) settings are summarized. A comprehensive search of peer-reviewed randomized controlled trials involving early interventions for infants and their mother published between 1993 and 2013 in the electronic databases PubMed, CINAHL, EMBASE, PsychINFO, and Cochrane was undertaken. Methodological quality was assessed using the PEDro scale to evaluate internal and external validity of the study. Twelve randomized controlled trials were included in the review, and all used some form of parenting education. The interventions had limited effects on maternal stress and mother-infant interaction and positive effects on maternal anxiety, depressive symptoms, and maternal coping. There were positive effects on infants' short-term outcomes for length of stay and breast-feeding rate. Positive and clinically meaningful effects of early interventions were seen in some physiological/psychological outcomes of mothers and preterm infants. It is important for nurses to foster close mother-infant contact and increase maternal competence during and after the infant's hospitalization period.

Clinical characteristics and longitudinal chest CT features of healthcare workers hospitalized with coronavirus disease 2019 (COVID-19).

Rationale: The clinical data and corresponding dynamic CT findings were investigated in detail to describe the clinical and imaging profiles of COVID-19 pneumonia disease progression. Methods: Forty HCWs with COVID-19 were included in this study and 30 enrolled for imaging assessment. Disease was divided into four stages based on time from onset: stage 1 (1-6 days), stage 2 (7-13 days), stage 3 (14-22 days), and stage 4 (> 22 days). Clinical wand imaging data were analyzed retrospectively. Results: The cohort included 33 female and 7 male cases, with a median age of 40 years. Six had underlying comorbidities. More than half of the cases were nurses (22, 55%). Each stage included 39, 37, 34 and 32 CTs, respectively. Bilateral lesions, multifocal lesions and lesions with GGO pattern occurred in both lower lobes at all stages. The crazy-paving pattern (20, 54%), air bronchogram (13, 35%), and pleural effusion (2, 5%) were the most common CT features in stage 2. Consolidation score peaked in stage 2 whereas total lesions score peaked in stage 3. Conclusions: COVID-19 pneumonia in HCWs has a potential predilection for younger female workers. Stage 2 of COVID-19 pneumonia may be the key period for controlling progression of the disease, and consolidation scores may be an objective reflection of the severity of lung involvement.

Physical Activity and Factors Affecting Its Maintenance Among Patients With Coronary Heart Disease Not Undergoing Cardiac Rehabilitation in China.

BACKGROUND: The level of physical activity (PA) among patients with coronary heart disease (CHD) living in Chinese communities who do not participate in cardiac rehabilitation programs and the factors contributing to patient maintenance of PA are unclear. OBJECTIVE: This cross-sectional study, guided by the Transtheoretical Model, evaluated (1) the maintenance of PA in Chinese patients with CHD 12 months after hospital discharge and (2) the demographic, clinical, and psychological characteristics associated with maintenance of PA. METHODS: A total of 1162 patients completed 6 questionnaires at 12 months posthospitalization to assess their maintenance of PA, stage of change, symptoms of depression and anxiety, and health-related quality of life and sleep. RESULTS: Only 40% of patients with CHD maintained regular PA 12 months after hospital discharge. Walking was their primary PA. Thirty-seven percent of patients reported no intention of having regular PA. Male sex (odds ratio [OR], 1.69), awareness of PA's cardiac benefit (OR, 4.12), a history of regular PA before the cardiac event (OR, 6.08), history of chronic disease (OR, 1.43), mild depressive symptoms (OR, 1.40), moderate and severe depressive symptoms (OR, 0.41), smoking (OR, 0.54), and years of CHD (OR, 0.96) were related to maintenance of regular PA. Patients with CHD who maintained regular PA had better quality of life and sleep (P < .001) and fewer unplanned clinic visits (P = .001) and cardiac cause readmissions (P = .012) and reported fewer declines in PA capacity (P < .001). CONCLUSIONS: Walking is the most common form of PA 12 months posthospitalization among patients with CHD in China. Patient education and counseling about the cardiac benefits of PA, taking into account stage of change, are important considerations to improve maintenance of PA.

An Efficient NLOS Errors Mitigation Algorithm for TOA-Based Localization.

In time-of-arrival (TOA) localization systems, errors caused by non-line-of-sight (NLOS) signal propagation could significantly degrade the location accuracy. Existing works on NLOS error mitigation commonly assume that NLOS error statistics or the TOA measurement noise variances are known. Such information is generally unavailable in practice. The goal of this paper is to develop an NLOS error mitigation scheme without requiring such information. The core of the proposed algorithm is a constrained least-squares optimization, which is converted into a semidefinite programming (SDP) problem that can be easily solved by using the CVX toolbox. This scheme is then extended for cooperative source localization. Additionally, its performance is better than existing schemes for most of the scenarios, which will be validated via extensive simulation.

Prevalence and Associated Factors of Physical Activity Among Older Adults Living in Nursing Homes: A Cross-Sectional Study.

In many countries, the physical activity level of nursing home residents is low, and the amount of time spent on such behavior has not been quantified in China. In the current study, pedometers were used to measure the physical activity levels of 349 nursing home residents. Daily steps for residents ranged from 5 to 16,773 steps per day, with a median of 1,608 steps per day. Three hundred (85.96%) residents were sedentary, 16 (4.6%) were low active, and 33 (9.5%) were physically active. Factors such as the living conditions of the nursing home, younger age, lower body mass index, higher educational level, marriage, higher pension, and greater family support all led to a higher physical activity level among residents. Regarding sedentary level, male residents were more active than female residents. The physical activity level of nursing home residents in China is lower than the current World Health Organization standard. [Journal of Gerontological Nursing, 46(10), 19-26.].

From patient satisfaction to patient experience: A call to action for nursing in China.

AIM: This commentary presents a preliminary overview of patient experience studies to advocate for advancing research and practice focusing on patient experience in nursing in China. BACKGROUND: There is a growing worldwide focus on evaluation of patient experience. Increasing numbers of national patient experience surveys have been conducted in China; however, nursing seems to be overlooked in this growing trend. EVALUATION: A systematic search and review of studies reporting patient experience in nursing was conducted with China National Knowledge Infrastructure (CNKI) from inception through 11 November 2019. KEY ISSUES: Inappropriate use and expression of patient experience led to confusion and misunderstandings. High-quality studies specifically for patient experience was lacking, especially those adopting quantitative and mixed methods designs. Tools with adequate input from nursing were scant. CONCLUSIONS: Patient experience studies in nursing are still nascent in China in terms of quantity, quality and diversity. IMPLICATIONS FOR NURSING MANAGEMENT: The concept of patient experience should be clearly defined through performing a systematic integrative review. Well-conducted qualitative, quantitative and mixed methods studies are especially needed. Nursing should be more involved in development of tool for measuring patient experience, and an instrument with a clear construct definition, systematically developed and psychometrically validated, constructed by nursing researchers will be valuable.

Identification and characterization of genes with absolute mRNA abundances changes in tumor cells with varied transcriptome sizes.

BACKGROUND: The amount of RNA per cell, namely the transcriptome size, may vary under many biological conditions including tumor. If the transcriptome size of two cells is different, direct comparison of the expression measurements on the same amount of total RNA for two samples can only identify genes with changes in the relative mRNA abundances, i.e., cellular mRNA concentration, rather than genes with changes in the absolute mRNA abundances. RESULTS: Our recently proposed RankCompV2 algorithm identify differentially expressed genes (DEGs) through comparing the relative expression orderings (REOs) of disease samples with that of normal samples. We reasoned that both the mRNA concentration and the absolute abundances of these DEGs must have changes in disease samples. In simulation experiments, this method showed excellent performance for identifying DEGs between normal and disease samples with different transcriptome sizes. Through analyzing data for ten cancer types, we found that a significantly higher proportion of the DEGs with absolute mRNA abundance changes overlapped or directly interacted with known cancer driver genes and anti-cancer drug targets than that of the DEGs only with mRNA concentration changes alone identified by the traditional methods. The DEGs with increased absolute mRNA abundances were enriched in DNA damage-related pathways, while DEGs with decreased absolute mRNA abundances were enriched in immune and metabolism associated pathways. CONCLUSIONS: Both the mRNA concentration and the absolute abundances of the DEGs identified through REOs comparison change in disease samples in comparison with normal samples. In cancers these genes might play more important upstream roles in carcinogenesis.

A prediction model of sleep disturbances among female nurses by using the BP-ANN.

AIM: To describe sleep disturbances and fatigue among female registered nurses in Beijing and to develop a prediction model for sleep disturbances. BACKGROUND: Chinese nurses are required to work rotating shifts on a weekly basis, which could negatively impact their sleep and well-being. METHOD: A total of 647 registered nurses participated in this study. Self-reported sleep-related data and selected physiological data were collected. Back propagation artificial neural networks was used to develop the prediction model by using the risk management and population health framework. RESULTS: Majority of them reported clinically significant poor sleep (69.4%) and fatigue (75.4%). A total of eight predictors were identified for sleep disturbances, and the top four normalized importance predictors are morning fatigue (100%), body mass index (30.5%), gastrointestinal symptoms (17.6%) and drinking caffeinated beverages at work (17.3%). The cross-entropy error was 206.58, and the model accounted for 77.6% of the variance in sleep disturbances. CONCLUSIONS AND IMPLICATIONS FOR NURSING MANAGEMENT: Female registered nurses in China experience clinically significant sleep disturbances. Morning fatigue severity along with seven significant influencing factors may be used to identify shift nurses who face a higher risk of sleep disturbances. The back propagation artificial neural networks model could be used as the foundation for health promotion interventions for registered nurses.

Quantitative or qualitative transcriptional diagnostic signatures? A case study for colorectal cancer.

BACKGROUND: Due to experimental batch effects, the application of a quantitative transcriptional signature for disease diagnoses commonly requires inter-sample data normalization, which would be hardly applicable under common clinical settings. Many cancers might have qualitative differences with the non-cancer states in the gene expression pattern. Therefore, it is reasonable to explore the power of qualitative diagnostic signatures which are robust against experimental batch effects and other random factors. RESULTS: Firstly, using data of technical replicate samples from the MicroArray Quality Control (MAQC) project, we demonstrated that the low-throughput PCR-based technologies also exist large measurement variations for gene expression even when the samples were measured in the same test site. Then, we demonstrated the critical limitation of low stability for classifiers based on quantitative transcriptional signatures in applications to individual samples through a case study using a support vector machine and a naïve Bayesian classifier to discriminate colorectal cancer tissues from normal tissues. To address this problem, we identified a signature consisting of three gene pairs for discriminating colorectal cancer tissues from non-cancer (normal and inflammatory bowel disease) tissues based on within-sample relative expression orderings (REOs) of these gene pairs. The signature was well verified using 22 independent datasets measured by different microarray and RNA_seq platforms, obviating the need of inter-sample data normalization. CONCLUSIONS: Subtle quantitative information of gene expression measurements tends to be unstable under current technical conditions, which will introduce uncertainty to clinical applications of the quantitative transcriptional diagnostic signatures. For diagnosis of disease states with qualitative transcriptional characteristics, the qualitative REO-based signatures could be robustly applied to individual samples measured by different platforms.