Background Dietary pattern analysis is a promising approach to understanding the complex relationship between diet and health. While many statistical methods exist, the literature predominantly focuses on classical methods such as dietary quality scores, principal component analysis, factor analysis, clustering analysis, and reduced rank regression. There are some emerging methods that have rarely or never been reviewed or discussed adequately. Methods This paper presents a landscape review of the existing statistical methods used to derive dietary patterns, especially the finite mixture model, treelet transform, data mining, least absolute shrinkage and selection operator and compositional data analysis, in terms of their underlying concepts, advantages and disadvantages, and available software and packages for implementation. Results While all statistical methods for dietary pattern analysis have unique features and serve distinct purposes, emerging methods warrant more attention. However, future research is needed to evaluate these emerging methods’ performance in terms of reproducibility, validity, and ability to predict different outcomes. Conclusion Selection of the most appropriate method mainly depends on the research questions. As an evolving subject, there is always scope for deriving dietary patterns through new analytic methodologies.

We propose a recurrent neural model that generates natural-language questions from documents, conditioned on answers. We show how to train the model using a combination of supervised and reinforcement learning. After teacher forcing for standard maximum likelihood training, we fine-tune the model using policy gradient techniques to maximize several rewards that measure question quality. Most notably, one of these rewards is the performance of a questionanswering system. We motivate question generation as a means to improve the performance of question answering systems. Our model is trained and evaluated on the recent question-answering dataset SQuAD.

Few studies have investigated gender differences in dietary intake. The objective of this cross-sectional study was to examine gender differences in dietary patterns and their association with the prevalence of metabolic syndrome. The food intakes of 3794 subjects enrolled by a two-stage cluster stratified sampling method were collected using a valid semi-quantitative food frequency questionnaire (FFQ). Metabolic syndrome (MetS) was defined according to the International Diabetes Federation (IDF) and its prevalence was 35.70% in the sample (37.67% in men and 24.67% in women). Dietary patterns were identified using factor analysis combined with cluster analysis and multiple group confirmatory factor analysis was used to assess the factorial invariance between gender groups. The dominating dietary pattern for men was the “balanced” dietary pattern (32.65%) and that for women was the “high-salt and energy” dietary pattern (34.42%). For men, the “animal and fried food” dietary pattern was related to higher risk of MetS (odds ratio: 1.27; 95% CI: 1.01–1.60), after adjustment for age, marital status, socioeconomic status and lifestyle factors. For women, the “high-salt and energy” dietary pattern was related to higher risk of MetS (odds ratio: 2.27; 95% CI: 1.24–4.14). We observed gender differences in dietary patterns and their association with the prevalence of MetS. For men, the “animal and fried food” dietary pattern was associated with enhancive likelihood of MetS. For women, it was the “high-salt and energy” dietary pattern.

Background:Several observational studies have investigated the association of insomnia with psychiatric disorders. Such studies yielded mixed results, and whether these associations are causal remains unclear. Thus, we aimed to identify the causal relationships between insomnia and five major psychiatric disorders.Methods:The analysis was implemented with six genome-wide association studies; one for insomnia and five for psychiatric disorders (attention-deficit/hyperactivity disorder, autism spectrum disorder, major depressive disorder, schizophrenia, and bipolar disorder). A heterogeneity in dependent instrument (HEIDI) approach was used to remove the pleiotropic instruments, Mendelian randomization (MR)-Egger regression was adopted to test the validity of the screened instruments, and bidirectional generalized summary data-based MR was performed to estimate the causal relationships between insomnia and these major psychiatric disorders.Results:We observed significant causal effects of insomnia on the risk of autism spectrum disorder and bipolar disorder, with odds ratios of 1.739 (95% confidence interval: 1.217–2.486, p = 0.002) and 1.786 (95% confidence interval: 1.396–2.285, p = 4.02 × 10−6), respectively. There was no convincing evidence of reverse causality for insomnia with these two disorders (p = 0.945 and 0.546, respectively). When insomnia was considered as either the exposure or outcome variable, causal estimates for the remaining three psychiatric disorders were not significant.Conclusions:Our results suggest a causal role of insomnia in autism spectrum disorder and bipolar disorder. Future disease models should include insomnia as a factor for these two disorders to develop effective interventions. More detailed mechanism studies may also be inspired by this causal inference.

ObjectivesThe use of peripherally inserted central catheters (PICCs) are an integral part of caring for hospitalised children. We sought to estimate the incidence of and identify the risk factors for complications associated with PICCs in an advanced registered nurse practitioners (ARNP)-driven programme.DesignRetrospective cohort study.SettingSingle-centre, large quaternary children's hospital.ParticipantsHospitalised children who had PICC inserted from 1 January 2010 to 31 December 2016.InterventionsNone.Measurement and main resultsA total of 2558 PICCs were placed during the study period. Mean age at PICC insertion was 8.7 years, mean dwell time was 17.7 days. The majority of PICCs (97.8%) were placed by ARNP. Most were placed in a single attempt (79.6%). Mean PICC residual external length outside was 2.1±2.7 cm. The rate of central line-associated bloodstream infection (CLABSI), thrombosis and significant bleeding were 1.9%, 1% and 0.2%, respectively. The CLABSI rate in infants and early childhood was higher than those aged ≥5 years (2.8%, 3.1%, respectively vs 1.3%). In a multivariate analysis after adjustment of confounding effects of race and gender, infants (OR= 2.24, CI=1.14 to 4.39, p=0.02) and early childhood cohort (OR=2.37, CI=1.12 to 5.01, p=0.02) were associated with significantly higher odds of developing CLABSI compared with ≥5 years old. In the early childhood cohort, PICCs with longer residual external catheter length (OR=1.30, 95% CI=1.07 to 1.57, p=0.008) and those placed in the operating room (OR=5.49, 95% CI=1.03 to 29.19, p=0.04), were associated with significantly greater risk of developing CLABSI.ConclusionsThe majority of PICCs were successfully placed by ARNPs on the first attempt and had a low incidence of complications. Infants required more attempts for successful PICC placement than older children. The presence of residual external catheter length and placement in the operating room were independent predictors of CLABSI in younger children.

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Activatable fluorescence imaging in the second near‐infrared window (NIR‐II FL, 1000–1700 nm) is of great significance for accurate tumor diagnosis and targeting therapy. However, the clinical translation of most stimulus‐activated nanoprobes is severely restricted by insufficient tumor response and out‐of‐synchronization theranostic process. Herein, an intelligent nanofactory AUC‐GOx/Cel that possesses the “external supply, internal promotion” dual H2O2‐amplification strategy for homologous activated tumor theranostic is designed. This nanofactory is constructed via a two‐step biomineralization method using Au‐doped Ag2S as a carrier for glucose oxidase (GOx) and celastrol, followed by the growing of CuS to “turn off” the NIR‐II FL signal. In the overexpressed H2O2 tumor‐microenvironment, the CuS featuring a responsive‐degradability behavior can effectively release Cu ions, resulting in the “ON” state of NIR‐II FL and Fenton‐like activity. The exposed GOx can realize the intratumoral H2O2 supply (external supply) via the effective conversion of glucose, and mediating tumor‐starvation therapy; the interaction of celastrol and mitochondria can offer a substantial increase in the endogenous H2O2 level (internal promotion), thereby significantly promoting the chemodynamic therapy (CDT) efficacy. Meanwhile, the dual H2O2‐enhancement performance will in turn accelerate the degradation of AUC‐GOx/Cel, and achieve a positive feedback mechanism for self‐reinforcing CDT.