Biased allosteric activation of ketone body receptor HCAR2 suppresses inflammation.

Hydroxycarboxylic acid receptor 2 (HCAR2), modulated by endogenous ketone body ß-hydroxybutyrate and exogenous niacin, is a promising therapeutic target for inflammation-related diseases. HCAR2 mediates distinct pathophysiological events by activating Gi/o protein or ß-arrestin effectors. Here, we characterize compound 9n as a Gi-biased allosteric modulator (BAM) of HCAR2 and exhibit anti-inflammatory efficacy in RAW264.7 macrophages via a specific HCAR2-Gi pathway. Furthermore, four structures of HCAR2-Gi complex bound to orthosteric agonists (niacin or monomethyl fumarate), compound 9n, and niacin together with compound 9n simultaneously reveal a common orthosteric site and a unique allosteric site. Combined with functional studies, we decipher the action framework of biased allosteric modulation of compound 9n on the orthosteric site. Moreover, co-administration of compound 9n with orthosteric agonists could enhance anti-inflammatory effects in the mouse model of colitis. Together, our study provides insight to understand the molecular pharmacology of the BAM and facilitates exploring the therapeutic potential of the BAM with orthosteric drugs.

scATAC-Ref: a reference of scATAC-seq with known cell labels in multiple species.

Chromatin accessibility profiles at single cell resolution can reveal cell type-specific regulatory programs, help dissect highly specialized cell functions and trace cell origin and evolution. Accurate cell type assignment is critical for effectively gaining biological and pathological insights, but is difficult in scATAC-seq. Hence, by extensively reviewing the literature, we designed scATAC-Ref (https://bio.liclab.net/scATAC-Ref/), a manually curated scATAC-seq database aimed at providing a comprehensive, high-quality source of chromatin accessibility profiles with known cell labels across broad cell types. Currently, scATAC-Ref comprises 1 694 372 cells with known cell labels, across various biological conditions, >400 cell/tissue types and five species. We used uniform system environment and software parameters to perform comprehensive downstream analysis on these chromatin accessibility profiles with known labels, including gene activity score, TF enrichment score, differential chromatin accessibility regions, pathway/GO term enrichment analysis and co-accessibility interactions. The scATAC-Ref also provided a user-friendly interface to query, browse and visualize cell types of interest, thereby providing a valuable resource for exploring epigenetic regulation in different tissues and cell types.

Resetting of the 24-nt siRNA landscape in rice zygotes.

The zygote, a totipotent stem cell, is crucial to the life cycle of sexually reproducing organisms. It is produced by the fusion of two differentiated cells-the egg and sperm, which in plants have radically different siRNA transcriptomes from each other and from multicellular embryos. Owing to technical challenges, the epigenetic changes that accompany the transition from differentiated gametes to totipotent zygote are poorly understood. Because siRNAs serve as both regulators and outputs of the epigenome, we characterized small RNA transcriptomes of zygotes from rice. Zygote small RNAs exhibit extensive maternal carryover and an apparent lack of paternal contribution, indicated by absence of sperm signature siRNAs. Zygote formation is accompanied by widespread redistribution of 24-nt siRNAs relative to gametes, such that ∼70% of the zygote siRNA loci do not overlap any egg cell siRNA loci. Newly detected siRNA loci in zygote are gene-proximal and not associated with centromeric heterochromatin, similar to canonical siRNAs, in sharp contrast to gametic siRNA loci that are gene-distal and heterochromatic. In addition, zygote but not egg siRNA loci are associated with high DNA methylation in the mature embryo. Thus, the zygote begins transitioning before the first embryonic division to an siRNA profile that is associated with future RdDM in embryogenesis. These findings indicate that, in addition to changes in gene expression, the transition to totipotency in the plant zygote is accompanied by resetting of the epigenetic reprogramming that occurred during gamete formation.

Encapsulation engineering of porous crystalline frameworks for delayed luminescence and circularly polarized luminescence.

Delayed luminescence (DF), including phosphorescence and thermally activated delayed fluorescence (TADF), and circularly polarized luminescence (CPL) exhibit common and broad application prospects in optoelectronic displays, biological imaging, and encryption. Thus, the combination of delayed luminescence and circularly polarized luminescence is attracting increasing attention. The encapsulation of guest emitters in various host matrices to form host-guest systems has been demonstrated to be an appealing strategy to further enhance and/or modulate their delayed luminescence and circularly polarized luminescence. Compared with conventional liquid crystals, polymers, and supramolecular matrices, porous crystalline frameworks (PCFs) including metal-organic frameworks (MOFs), covalent-organic frameworks (COFs), zeolites and hydrogen-bonded organic frameworks (HOFs) can not only overcome shortcomings such as flexibility and disorder but also achieve the ordered encapsulation of guests and long-term stability of chiral structures, providing new promising host platforms for the development of DF and CPL. In this review, we provide a comprehensive and critical summary of the recent progress in host-guest photochemistry via the encapsulation engineering of guest emitters in PCFs, particularly focusing on delayed luminescence and circularly polarized luminescence. Initially, the general principle of phosphorescence, TADF and CPL, the combination of DF and CPL, and energy transfer processes between host and guests are introduced. Subsequently, we comprehensively discuss the critical factors affecting the encapsulation engineering of guest emitters in PCFs, such as pore structures, the confinement effect, charge and energy transfer between the host and guest, conformational dynamics, and aggregation model of guest emitters. Thereafter, we summarize the effective methods for the preparation of host-guest systems, especially single-crystal-to-single-crystal (SC-SC) transformation and epitaxial growth, which are distinct from conventional methods based on amorphous materials. Then, the recent advancements in host-guest systems based on PCFs for delayed luminescence and circularly polarized luminescence are highlighted. Finally, we present our personal insights into the challenges and future opportunities in this promising field.

Evaluation of disease severity and prediction of severe cases in children hospitalized with influenza A (H1N1) infection during the post-COVID-19 era: a multicenter retrospective study.

BACKGROUND: The rebound of influenza A (H1N1) infection in post-COVID-19 era recently attracted enormous attention due the rapidly increased number of pediatric hospitalizations and the changed characteristics compared to classical H1N1 infection in pre-COVID-19 era. This study aimed to evaluate the clinical characteristics and severity of children hospitalized with H1N1 infection during post-COVID-19 period, and to construct a novel prediction model for severe H1N1 infection. METHODS: A total of 757 pediatric H1N1 inpatients from nine tertiary public hospitals in Yunnan and Shanghai, China, were retrospectively included, of which 431 patients diagnosed between February 2023 and July 2023 were divided into post-COVID-19 group, while the remaining 326 patients diagnosed between November 2018 and April 2019 were divided into pre-COVID-19 group. A 1:1 propensity-score matching (PSM) was adopted to balance demographic differences between pre- and post-COVID-19 groups, and then compared the severity across these two groups based on clinical and laboratory indicators. Additionally, a subgroup analysis in the original post-COVID-19 group (without PSM) was performed to investigate the independent risk factors for severe H1N1 infection in post-COIVD-19 era. Specifically, Least Absolute Shrinkage and Selection Operator (LASSO) regression was applied to select candidate predictors, and logistic regression was used to further identify independent risk factors, thus establishing a prediction model. Receiver operating characteristic (ROC) curve and calibration curve were utilized to assess discriminative capability and accuracy of the model, while decision curve analysis (DCA) was used to determine the clinical usefulness of the model. RESULTS: After PSM, the post-COVID-19 group showed longer fever duration, higher fever peak, more frequent cough and seizures, as well as higher levels of C-reactive protein (CRP), interleukin 6 (IL-6), IL-10, creatine kinase-MB (CK-MB) and fibrinogen, higher mechanical ventilation rate, longer length of hospital stay (LOS), as well as higher proportion of severe H1N1 infection (all P < 0.05), compared to the pre-COVID-19 group. Moreover, age, BMI, fever duration, leucocyte count, lymphocyte proportion, proportion of CD3+ T cells, tumor necrosis factor α (TNF-α), and IL-10 were confirmed to be independently associated with severe H1N1 infection in post-COVID-19 era. A prediction model integrating these above eight variables was established, and this model had good discrimination, accuracy, and clinical practicability. CONCLUSIONS: Pediatric H1N1 infection during post-COVID-19 era showed a higher overall disease severity than the classical H1N1 infection in pre-COVID-19 period. Meanwhile, cough and seizures were more prominent in children with H1N1 infection during post-COVID-19 era. Clinicians should be aware of these changes in such patients in clinical work. Furthermore, a simple and practical prediction model was constructed and internally validated here, which showed a good performance for predicting severe H1N1 infection in post-COVID-19 era.

Analysis of Risk Factors for Severe Acute Pancreatitis in the Early Period (<24 h) After Admission.

BACKGROUND: Severe acute pancreatitis (SAP) has high mortality. Early identification of high-risk factors that may progress to SAP and active intervention measures may improve the prognosis of SAP patients. OBJECTIVE: Clinical data within 24 h after admission were retrospectively analyzed to provide an evidence for early screening of high-risk factors in patients with SAP. METHODS: A review of clinical data of acute pancreatitis patients from January 1, 2018, to December 31, 2022, was conducted. We compared the clinical data of SAP and non-SAP patients, and a multivariable logistic regression model was used to identify the independent predictors of SAP. The receiver operating characteristic (ROC) curve of SAP was drawn for continuous numerical variables to calculate the optimal clinical cutoff value of each variable, and the predictive value of each variable was compared by the area under the ROC curve. RESULTS: Based on the multivariate logistic regression analysis of Age (odds ratio (OR), 1.032;95% confident interval (CI),1.018-1.046, p < 0.001), body mass index (BMI) (OR, 1.181; 95% CI,1.083-1.288, p < 0.001), Non-HTGAP (nonhypertriglyceridemic acute pancreatitis) (OR, 2.098; 95% CI,1.276-3.45, p = 0.003), white blood cell count (WBC) (OR,1.072; 95% CI,1.034-1.111, p < 0.001), procalcitonin (PCT) (OR, 1.060; 95% CI, 1.027-1.095, p < 0.001), serum calcium (Ca) (OR,0.121; 95% CI, 0.050-0.292, p < 0.001), computed tomography severity index (CTSI) ≥4 (OR,12.942;95% CI,7.267-23.049, p < 0.001) were identified as independent risk factors for SAP. The area under the ROC curve (AUC) and optimal CUT-OFF values of continuous numerical variables for predicting SAP were Age (0.6079,51.5), BMI (0.6,23.25), WBC (0.6701,14.565), PCT (0.7086, 0.5175), Ca (0.7787,1.965), respectively. CONCLUSION: Age, BMI, non-HTGAP, WBC, PCT, serum Ca and CTSI≥4 have good predictive value for SAP.

PV Panel Model Parameter Estimation by Using Particle Swarm Optimization and Artificial Neural Network.

Photovoltaic (PV) panels are one of the popular green energy resources and PV panel parameter estimations are one of the popular research topics in PV panel technology. The PV panel parameters could be used for PV panel health monitoring and fault diagnosis. Recently, a PV panel parameters estimation method based in neural network and numerical current predictor methods has been developed. However, in order to further improve the estimation accuracies, a new approach of PV panel parameter estimation is proposed in this paper. The output current and voltage dynamic responses of a PV panel are measured, and the time series of the I-V vectors will be used as input to an artificial neural network (ANN)-based PV model parameter range classifier (MPRC). The MPRC is trained using an I-V dataset with large variations in PV model parameters. The results of MPRC are used to preset the initial particles' population for a particle swarm optimization (PSO) algorithm. The PSO algorithm is used to estimate the PV panel parameters and the results could be used for PV panel health monitoring and the derivation of maximum power point tracking (MMPT). Simulations results based on an experimental I-V dataset and an I-V dataset generated by simulation show that the proposed algorithms can achieve up to 3.5% accuracy and the speed of convergence was significantly improved as compared to a purely PSO approach.

The effect of fine particulate matter (PM2.5) pollution on health inequality: an intergenerational perspective.

Air pollution poses a serious challenge to public health and simultaneously exacerbating regional & intergenerational health inequality. This research introduces PM2.5 pollution into the intergenerational health transmission model, and estimates its impact on health inequality in China using Ordered Logit Regression (OLR) and Multi-scale Geographically Weighted Regression (MGWR) model. The results indicate that PM2.5 pollution exacerbate the intergenerational health inequality, and its impacts show inconsistency across family income levels, parental health insurance status, and area of residence. Specifically, it is more difficult for offspring in low-income families to escape from the influence of unhealthy family to become upwardly mobile. Additionally, this health inequality is more significant in households in which at least one parent does not have health insurance. Moreover, the intergenerational solidification caused by PM2.5 pollution is higher in the east and lower in the west. Both the PM2.5 level and solidification effect are high in Beijing-Tianjin-Hebei region, Yangtze River Delta region and central areas of China, which is the focus of air pollution management. These findings suggest that more emphasis should be placed on family-based health promotion. In areas with high PM2.5 pollution levels, resources, subsidies and air pollution protection should be provided for less healthy families with lower incomes and no health insurance.

Triply Interlocked [2]catenanes: Rational Synthesis, Reversible Conversion Studies and Unprecedented Application in Photothermal Responsive Elastomer.

Triply interlocked [2]catenane complexes featuring two identical, mechanically interlocked units are extraordinarily rare chemical compounds, whose properties and applications remain open to detailed studies. Herein, we introduce the rational design of a new ligand precursor, L1, suitable for the synthesis of six triply interlocked [2]catenanes by coordination-driven self-assembly. The interlocked compounds can be reversibly converted into the corresponding simple triangular prism metallacage by addition of H2O or DMF solvents to their CH3OH solutions, thereby demonstrating the importance of π···π stacking and hydrogen bonding interactions in the formation of triply interlocked [2]catenanes. Moreover, extensive studies have been conducted to assess the remarkable photothermal conversion performance. Complex 6a, exhibiting outstanding photothermal conversion performance (conversion efficiency in solution : 31.82%), is used to prepare novel photoresponsive elastomer in combination with thermally activated liquid crystal elastomer. The resultant material displays robust response to near-infrared (NIR) laser and the capability of completely reforming the shape and reversible actuation, paving the way for the application of half-sandwich organometallic units in photo-responsive smart materials.

Engineered Superhydrophilic/Superaerophobic Catalyst: Two-Dimensional Co(OH)2-CeO2 Nanosheets Supported on Three-Dimensional Co Dendrites for Overall Water Splitting.

Efficient electrocatalysts require not only a tunable electronic structure but also great active site accessibility and favorable mass transfer. Here, a two-dimensional/three-dimensional (2D/3D) hierarchical electrocatalyst consisting of Co(OH)2-CeO2 nanosheet-decorated Co dendrites is proposed, named as Co(OH)2-CeO2/Co. Based on the strong electronic interaction of the Co(OH)2-CeO2 heterojunction, the electronic structure of the Co site is optimized, which facilitates the adsorption of intermediates and the dissociation of H2O. Moreover, the open 2D/3D structure formed by introducing the Co substrate further reduces the accumulation of heterogeneous nanosheets and promotes the radial diffusion of the electrolyte, significantly improving the utilization of active sites and shortening the electron transfer pathway. In addition, the superhydrophilic/superaerophobic interface achieved by constructing the hierarchical micro-nanostructure is beneficial to electrolyte infiltration and bubble desorption, thus ensuring favorable mass transfer. Therefore, Co(OH)2-CeO2/Co exhibits an excellent overall water-splitting activity in alkaline solution.

A Meta-Analysis on the Impact of Prenatal and Early Childhood Antimicrobial Use on Autism Spectrum Disorders.

OBJECTIVE: To investigate the impact of prenatal and early childhood antimicrobial use on autism spectrum disorders (ASD). DATA SOURCES: We searched PubMed and Embase databases for relevant studies from inception to August 2022. STUDY SELECTION AND DATA EXTRACTION: Peer-reviewed, observational studies were all acceptable. Raw data were extracted into a predefined worksheet and quality analysis was performed using the Newcastle-Ottawa Scale. DATA SYNTHESIS: Nineteen studies were identified in the meta-analysis. Prenatal antimicrobial exposure was not associated with ASD (P = 0.06 > 0.05), whereas early childhood antimicrobial exposure was associated with an increased odds ratio of ASD (OR = 1.17, 95% CI = [1.08-1.27], P value < 0.001). The sibling-matched analysis, with a very limited sample size, suggested that neither prenatal (P = 0.47 > 0.05) nor early childhood (P = 0.13 > 0.05) antimicrobial exposure was associated with ASD. Medical professionals may need to take the possible association into consideration when prescribing an antimicrobial in children. CONCLUSIONS: Early childhood antimicrobial exposure could increase the incidence of ASD. In future studies, it would be necessary to control for confounding factors, such as genetic factors, parenteral age at birth, or low birthweight, to further validate the association.

Supportive care needs in Australian melanoma patients and caregivers: results from a quantitative cross-sectional survey.

PURPOSE: This study aimed to investigate the supportive care needs of Australian melanoma patients and their caregivers to form the basis for improving services. METHODS: General and melanoma-related supportive care needs in melanoma patients were measured using the SCNS-SF34 and SCNS-M12 respectively, whereas caregivers completed the SCNS-P&C. Patients also completed the MCQ-28 and FCRI-9, with all participants completing the QLQ-C30, DASS-21, and questions measuring utilisation and preference for supportive health services. Multivariable stepwise logistic regression was used to identify variables associated with unmet needs in melanoma patients. RESULTS: A total of 56 early-stage patients, 100 advanced-stage patients, and 37 caregivers participated. At least three-quarters ([Formula: see text] 75%) of each participant group reported at least one unmet need. Of the ten most reported unmet needs in each participant group, at least six ([Formula: see text] 60%) were related to psychological and emotional well-being, with access to a psychologist the most desired service (> 25%). Fear of cancer recurrence was equally prevalent in both patient groups at a level indicative of need for intervention. Advanced-stage patients reported significantly (p < 0.05) more unmet psychological, physical and daily living, and sexuality needs, and significantly (p < 0.05) worse functioning than early-stage patients. CONCLUSION: Australian melanoma patients and caregivers report substantial unmet supportive care needs, particularly regarding their psychological and emotional well-being. Psychological and emotional well-being services, such as access to a clinical psychologist or implementation of patient-reported outcome measures, should be incorporated into routine melanoma care to address unmet patient and caregiver needs and improve well-being.

Using HVS Dual-Pathway and Contrast Sensitivity to Blindly Assess Image Quality.

Blind image quality assessment (BIQA) aims to evaluate image quality in a way that closely matches human perception. To achieve this goal, the strengths of deep learning and the characteristics of the human visual system (HVS) can be combined. In this paper, inspired by the ventral pathway and the dorsal pathway of the HVS, a dual-pathway convolutional neural network is proposed for BIQA tasks. The proposed method consists of two pathways: the "what" pathway, which mimics the ventral pathway of the HVS to extract the content features of distorted images, and the "where" pathway, which mimics the dorsal pathway of the HVS to extract the global shape features of distorted images. Then, the features from the two pathways are fused and mapped to an image quality score. Additionally, gradient images weighted by contrast sensitivity are used as the input to the "where" pathway, allowing it to extract global shape features that are more sensitive to human perception. Moreover, a dual-pathway multi-scale feature fusion module is designed to fuse the multi-scale features of the two pathways, enabling the model to capture both global features and local details, thus improving the overall performance of the model. Experiments conducted on six databases show that the proposed method achieves state-of-the-art performance.

PV Panel Model Parameter Estimation by Using Neural Network.

Photovoltaic (PV) panels have been widely used as one of the solutions for green energy sources. Performance monitoring, fault diagnosis, and Control of Operation at Maximum Power Point (MPP) of PV panels became one of the popular research topics in the past. Model parameters could reflect the health conditions of a PV panel, and model parameter estimation can be applied to PV panel fault diagnosis. In this paper, we will propose a new algorithm for PV panel model parameters estimation by using a Neural Network (ANN) with a Numerical Current Prediction (NCP) layer. Output voltage and current signals (VI) after load perturbation are observed. An ANN is trained to estimate the PV panel model parameters, which is then fined tuned by the NCP to improve the accuracy to about 6%. During the testing stage, VI signals are input into the proposed ANN-NCP system. PV panel model parameters can then be estimated by the proposed algorithms, and the estimated model parameters can be then used for fault detection, health monitoring, and tracking operating points for MPP conditions.

Analysis of a maritime transport chain with information asymmetry and disruption risk.

Maritime transport chain is facing huge information asymmetry after the outbreak of major emergencies, such as COVID-19 epidemic. The previous literature has proved that information investing and information sharing are two effective tactics to relieve information asymmetry between supply chain nodes, and help them improve the performance of the supply chain. This paper assumes random demand disruption is the main cause of the information asymmetry in a maritime transportation chain. To explore how the random demand disruption and channel competition jointly impact operational decisions in a dual-channel maritime transport chain composed of one port, two carriers and shippers, we construct a game-theoretical basic model, and proposed two strategies, i.e., information investing and information sharing. Several significant managerial insights are derived. First, we find that inaccurate disruption information leads to inaccurate decisions and huge losses; Second, investing in precise information benefits the port only if the chain members are optimistic about the market, and improves the revenue of the carrier who invested in information if the investment cost is reasonable; Third, accepting information sharing benefits the port only when the precise disruption and the distortion of information are relatively large, as well as the misappropriate rate is relatively small; and only when the port is pessimistic about the market or the channel competition is weak, sharing information may hurt the carrier who invested in information. Finally, the strength of the channel competition will enhance the impact of information inaccuracy on the maritime transport chain.

Anthocyanins identification and transcriptional regulation of anthocyanin biosynthesis in purple Brassica napus.

KEY MESSAGE: The main anthocyanin components were identified, and the transcriptional regulation pattern of anthocyanin related genes in leaves and stem bark was elucidated in a purple B. napus. Brassica napus is one of the most important oil crops planted worldwide, and developing varieties of dual-purpose for oil and vegetable is beneficial to improve economic benefits. Anthocyanins are a class of secondary metabolites that not only make plants present beautiful colors, but have a variety of important physiological functions and biological activities. Therefore, increasing the accumulation of anthocyanin in vegetative organs can improve vegetable value of rapeseed. However, anthocyanin enriched varieties in vegetative organs are rare, and there are few studies on category identification and accumulation mechanism of anthocyanin, which limits the utilization of anthocyanins in B. napus. In this study, 157 anthocyanin biosynthesis related genes (ABGs) were identified in B. napus genome by homology comparison and collinearity analysis of genes related to anthocyanin synthesis and regulation in Arabidopsis. Moreover, five anthocyanins were identified in the stem bark and leaves of the purple B. napus PR01 by high performance liquid chromatography-mass spectrometry (HPLC-MS), and the expression characteristics of ABGs in the leaves and stem bark of PR01 were analyzed and compared with the green cultivar ZS11 by RNA-Seq. Combining further weighted gene co-expression network analysis (WGCNA), the up-regulation of transcript factors BnaA07. PAP2 and BnaC06. PAP2 were identified as the key to the up-regulation of most of anthocyanin synthesis genes that promoted anthocyanin accumulation in PR01. This study is helpful to understand the transcriptional regulation of anthocyanin biosynthesis in B. napus and provides the theoretical basis for breeding novel varieties of dual-purpose for oil and vegetable.

Realization of Single-Phase White-Light-Emitting Materials with Time-Evolution Ultralong Room-Temperature Phosphorescence by Coordination Assemblies.

Two Cd-based supramolecular coordination polymers, [Cd3(CzIP)3(DMF)2] (1) and [Cd2(CzIP)2(DMF)4] (2), were synthesized by using 5-(carbazol-9-yl) isophthalate (CzIP) as ligands. These two compounds exhibit multiple luminescence emissions; apart from fluorescence, time- and temperature-dependent ultralong phosphorescence (RTP) were also achieved under room conditions. Significantly, compound 1 has a long-lived afterglow of 0.93 s at 545 nm under ambient conditions. Compound 2 shows nearly pure white-light emission with CIE coordinates of (0.33, 0.33) via the dual emission of fluorescence and phosphorescence. It has come to our attention that it is the first example of a luminescent coordination polymer with single-phase white-light emission and color-evolution RTP. In addition, the long-lived RTP materials can be used in time-dependent anticounterfeiting and white-light-emitting diodes. Experimental and singlet and triplet state calculations indicate that both C-H···π interaction and inter- and intramolecular charge transfer interactions could be beneficial to the emission of ultralong RTP.

Relationships Between Multiple Dimensions of Insight and Neurocognition, Metacognition, and Social Cognition: A Meta-Analysis.

ABSTRACT: Insight is a complex and multidimensional concept, and has a complex relationship with cognition. A meta-analysis of 102 studies of 9396 patients was conducted to determine the magnitude of the relationship between insight and neurocognition, higher-order cognition in multiple mental disorders. Insight has been found moderately related to higher-order cognition, but only weakly related to neurocognition. The different relationship has been found between the dimensions of insight and higher-order cognition. Almost none of the correlational coefficients of insight and cognitive domains were found to differ significantly among the different diagnostic groups. In conclusion, insight may be essentially related to higher-order cognition, but not to neurocognition. The orientation and expression of different dimensions of insight might be different, and the relationship of insight and cognition might not be explained by specific diagnosis.

Association between obsession, compulsion, depression and insight in obsessive-compulsive disorder: a meta-analysis.

BACKGROUND: Previous studies examining potential relationships of impaired insight with severity obsessive-compulsive (O-C) symptoms and depressive symptoms in patients diagnosed with obsessive-compulsive disorder (OCD) have produced mixed results. Here, we examined differences in these clinical characteristics and their changes after treatment in adult patients with OCD who have poor insight (OCD-PI) versus in those who have good insight (OCD-GI). METHODS: Fifty-nine full-text articles were screened for eligibility with 20 studies ultimately being included in the present meta-analysis. RESULTS: The OCD-PI and OCD-GI groups differed from each other with respect to O-C symptom (p < 0.001, g > 0.7) and depressive symptom (p < 0.001, g = 0.614) severity. Significant and moderate correlations were observed between insight and treatment outcomes (O-C symptoms, r = 0.33; depressive symptoms, r = 0.47). Exploratory meta-regression showed that methodological factors influenced the magnitudes of inter-group O-C symptom differences. CONCLUSIONS: The current meta-analysis indicates that poorer insight is associated with more severe O-C and depression, and less improvement of symptoms in patients with OCD. Insight impairment may be a critical and core OCD-related deficit.

Subjective and objective risk perceptions and the willingness to pay for agricultural insurance: evidence from an in-the-field choice experiment in rural China.

We conducted in-the-field choice experiments in China to investigate farmers' willingness to pay for crop insurance and to determine how objective and subjective beliefs affect Willingness to Pay (WTP). We deploy three variants of the choice experiment using a priming mechanism on objective and subjective beliefs plus a control. We find that the cuing frame matters in that there are differences in WTP within five attributes and across variants. In terms of practical policy, our results suggest that farmers' frame of reference toward objective and subjective risks can affect insurance demand.