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The vitamin K (VK) levels vary greatly among different populations and in different regions. Currently, there is a lack of reference intervals for VK levels in healthy individuals, The aim of this study is to establish and validate the reference intervals of serum vitamin K1 (VK1) and vitamin K2 (VK2, specifically including menaquinone-4 (MK4) and menaquinone-7 (MK7)) levels in some healthy populations in Beijing. Serum VK1, MK4, and MK7 were firstly measured by high-performance liquid chromatography and mass spectrometry in 434 subjects. The reference intervals for three indicators were established by calculating the data of 2.5 and 97.5 percentiles. Finally, preliminary clinical validation was conducted on 60 apparent healthy individuals undergoing physical examination. In the young, middle-aged, and elderly groups, the reference intervals of VK1 were 0.180 ng/mL ∼ 1.494 ng/mL, 0.247 ng/mL ∼ 1.446 ng/mL, and 0.167 ng/mL ∼ 1.445 ng/mL, respectively. The reference intervals of MK4 were 0.009 ng/mL ∼ 0.115 ng/mL, 0.002 ng/mL ∼ 0.103 ng/mL, and 0.003 ng/mL ∼ 0.106 ng/mL, respectively. The reference intervals of MK7 were 0.169 ng/mL ∼ 0.881 ng/mL, 0.238 ng/mL ∼ 0.936 ng/mL, and 0.213 ng/mL ∼ 1.012 ng/mL, respectively. The reference intervals had been validated by the samples of healthy individuals for physical examination. In conclusion, the reference intervals of VK established in this study with different age groups have certain clinical applicability, providing data support for further multicentre studies.
Glucagon-like peptide-1 receptor agonists (GLP-1RAs) are widely used due to their profound efficacy in glycemic control and weight management. Real-world observations have revealed potential neuropsychiatric adverse events (AEs) associated with GLP-1RAs. This study aimed to comprehensively investigate and characterize these neuropsychiatric AEs with GLP-1RAs.
Methods
We analyzed GLP-1RA adverse reaction reports using the FDA Adverse Event Reporting System database. Disproportionality analysis using reporting odds ratio (ROR) identified eight categories of neuropsychiatric AEs associated with GLP-1RAs. We conducted descriptive and time-to-onset (TTO) analyses and explored neuropsychiatric AE signals among individual GLP-1RAs for weight loss and diabetes mellitus (DM) indications.
Results
We identified 25,110 cases of GLP-1RA-related neuropsychiatric AEs. GLP-1RAs showed an association with headache (ROR 1.74, 95% confidence interval [CI] 1.65–1.84), migraine (ROR 1.28, 95%CI 1.06–1.55), and olfactory and sensory nerve abnormalities (ROR 2.44, 95%CI 1.83–3.25; ROR 1.69, 95%CI 1.54–1.85). Semaglutide showed a moderate suicide-related AEs signal in the weight loss population (ROR 2.55, 95%CI 1.97–3.31). The median TTO was 16 days (interquartile range: 3–66 days).
Conclusions
In this study, we identified eight potential neuropsychiatric adverse events (AEs) associated with GLP-1RAs and, for the first time, detected positive signals for migraine, olfactory abnormalities, and sensory abnormalities. We also observed positive suicide-related signals of semaglutide, in weight loss population. This study provides a reliable basis for further investigation of GLP-1RA-related neuropsychiatric AEs. However, as an exploratory study, our findings require confirmation through large-scale prospective studies.
Aiming at the problems of many path inflection points, unsmooth paths, and poor local obstacle avoidance in path planning of inspection robots in static-dynamic scenes under complex geological conditions in coal mine roadways, a hybrid path planning method based on the improved A* algorithm and dynamic window approach (DWA) algorithm is proposed. First, the inspection robot platform and system model are constructed. An improved heuristic function that incorporates target weight information is proposed based on the A* global path planning algorithm. Additionally, redundant nodes are eliminated, and the path is smoothed using the Floyd algorithm and B-spline curves. Second, the global path planning A* algorithm and the local path planning DWA algorithm are fused. The dynamic path planning is carried out by setting the key node information of the global path extracted from the improved A* algorithm as the local target point of the DWA algorithm. On this basis, a grid map is established to simulate and analyze the proposed path planning algorithm. Finally, the autonomous path planning and walking experiment of inspection robot in simulated roadway environment are carried out. The results show that the hybrid path planning method based on improved A* algorithm and DWA algorithm proposed in this paper is more efficient and safer, which can meet the motion requirements of inspection robot in coal mine roadway.
The school–vacation cycle may have impacts on the psychological states of adolescents. However, little evidence illustrates how transition from school to vacation impacts students’ psychological states (e.g. depression and anxiety).
Aims
To explore the changing patterns of depression and anxiety symptoms among adolescent students within a school–vacation transition and to provide insights for prevention or intervention targets.
Method
Social demographic data and depression and anxiety symptoms were measured from 1380 adolescent students during the school year (age: 13.8 ± 0.88) and 1100 students during the summer vacation (age: 14.2 ± 0.93) in China. Multilevel mixed-effect models were used to examine the changes in depression and anxiety levels and the associated influencing factors. Network analysis was used to explore the symptom network structures of depression and anxiety during school and vacation.
Results
Depression and anxiety symptoms significantly decreased during the vacation compared to the school period. Being female, higher age and with lower mother's educational level were identified as longitudinal risk factors. Interaction effects were found between group (school versus vacation) and the father's educational level as well as grade. Network analyses demonstrated that the anxiety symptoms, including ‘Nervous’, ‘Control worry’ and ‘Relax’ were the most central symptoms at both times. Psychomotor disturbance, including ‘Restless’, ‘Nervous’ and ‘Motor’, bridged depression and anxiety symptoms. The central and bridge symptoms showed variation across the school vacation.
Conclusions
The school–vacation transition had an impact on students’ depression and anxiety symptoms. Prevention and intervention strategies for adolescents’ depression and anxiety during school and vacation periods should be differentially developed.
Differential item functioning (DIF) analysis is an important step in establishing the validity of measurements. Most traditional methods for DIF analysis use an item-by-item strategy via anchor items that are assumed DIF-free. If anchor items are flawed, these methods will yield misleading results due to biased scales. In this article, based on the fact that the item’s relative change of difficulty difference (RCD) does not depend on the mean ability of individual groups, a new DIF detection method (RCD-DIF) is proposed by comparing the observed differences against those with simulated data that are known DIF-free. The RCD-DIF method consists of a D-QQ (quantile quantile) plot that permits the identification of internal references points (similar to anchor items), a RCD-QQ plot that facilitates visual examination of DIF, and a RCD graphical test that synchronizes DIF analysis at the test level with that at the item level via confidence intervals on individual items. The RCD procedure visually reveals the overall pattern of DIF in the test and the size of DIF for each item and is expected to work properly even when the majority of the items possess DIF and the DIF pattern is unbalanced. Results of two simulation studies indicate that the RCD graphical test has Type I error rate comparable to those of existing methods but with greater power.
A social network comprises both actors and the social connections among them. Such connections reflect the dependence among social actors, which is essential for individuals’ mental health and social development. In this article, we propose a mediation model with a social network as a mediator to investigate the potential mediation role of a social network. In the model, the dependence among actors is accounted for by a few mutually orthogonal latent dimensions which form a social space. The individuals’ positions in such a latent social space are directly involved in the mediation process between an independent and dependent variable. After showing that all the latent dimensions are equivalent in terms of their relationship to the social network and the meaning of each dimension is arbitrary, we propose to measure the whole mediation effect of a network. Although individuals’ positions in the latent space are not unique, we rigorously articulate that the proposed network mediation effect is still well defined. We use a Bayesian estimation method to estimate the model and evaluate its performance through an extensive simulation study under representative conditions. The usefulness of the network mediation model is demonstrated through an application to a college friendship network.
A multifunctional optical diagnostic system, which includes an interferometer, a refractometer and a multi-frame shadowgraph, has been developed at the Shenguang-II upgrade laser facility to characterize underdense plasmas in experiments of the double-cone ignition scheme of inertial confinement fusion. The system employs a 266 nm laser as the probe to minimize the refraction effect and allows for flexible switching among three modes of the interferometer, refractometer and multi-frame shadowgraph. The multifunctional module comprises a pair of beam splitters that attenuate the laser, shield stray light and configure the multi-frame and interferometric modules. By adjusting the distance and angle between the beam splitters, the system can be easily adjusted and switched between the modes. Diagnostic results demonstrate that the interferometer can reconstruct electron density below 1019 cm–3, while the refractometer can diagnose density approximately up to 1020 cm–3. The multi-frame shadowgraph is used to qualitatively characterize the temporal evolution of plasmas in the cases in which the interferometer and refractometer become ineffective.
Cognitive impairment, a major determinant of poor functioning in schizophrenia, had limited responses to existing antipsychotic drugs. The limited efficacy could be due to regional differences in the dysregulation of the dopamine system. This study investigated striatal and peripheral dopaminergic makers in schizophrenia and their relationship with cognitive impairment.
Methods
Thirty-three patients with schizophrenia and 36 age- and sex-matched healthy controls (HC) participated. We evaluated their cognitive performance, examined the availability of striatal dopamine transporter (DAT) using single-photon emission computed tomography with 99mTc-TRODAT, and measured plasma levels of dopaminergic precursors (phenylalanine and tyrosine) and three branched-chain amino acids (BCAA) that compete with precursors for brain uptake via ultra-performance liquid chromatography.
Results
Schizophrenia patients exhibited lower cognitive performance, decreased striatal DAT availability, and reduced levels of phenylalanine, tyrosine, leucine, and isoleucine, and the ratio of phenylalanine plus tyrosine to BCAA. Within the patient group, lower DAT availability in the left caudate nucleus (CN) or putamen was positively associated with attention deficits. Meanwhile, lower tyrosine levels and the ratio of phenylalanine plus tyrosine to BCAA were positively related to executive dysfunction. Among all participants, DAT availability in the right CN or putamen was positively related to memory function, and plasma phenylalanine level was positively associated with executive function.
Conclusions
This study supports the role of dopamine system abnormalities in cognitive impairment in schizophrenia. The distinct associations between different dopaminergic alterations and specific cognitive domain impairments suggest the potential need for multifaceted treatment approaches to target these impairments.
In contemporary neuroimaging studies, it has been observed that patients with major depressive disorder (MDD) exhibit aberrant spontaneous neural activity, commonly quantified through the amplitude of low-frequency fluctuations (ALFF). However, the substantial individual heterogeneity among patients poses a challenge to reaching a unified conclusion.
Methods
To address this variability, our study adopts a novel framework to parse individualized ALFF abnormalities. We hypothesize that individualized ALFF abnormalities can be portrayed as a unique linear combination of shared differential factors. Our study involved two large multi-center datasets, comprising 2424 patients with MDD and 2183 healthy controls. In patients, individualized ALFF abnormalities were derived through normative modeling and further deconstructed into differential factors using non-negative matrix factorization.
Results
Two positive and two negative factors were identified. These factors were closely linked to clinical characteristics and explained group-level ALFF abnormalities in the two datasets. Moreover, these factors exhibited distinct associations with the distribution of neurotransmitter receptors/transporters, transcriptional profiles of inflammation-related genes, and connectome-informed epicenters, underscoring their neurobiological relevance. Additionally, factor compositions facilitated the identification of four distinct depressive subtypes, each characterized by unique abnormal ALFF patterns and clinical features. Importantly, these findings were successfully replicated in another dataset with different acquisition equipment, protocols, preprocessing strategies, and medication statuses, validating their robustness and generalizability.
Conclusions
This research identifies shared differential factors underlying individual spontaneous neural activity abnormalities in MDD and contributes novel insights into the heterogeneity of spontaneous neural activity abnormalities in MDD.
Developing a model to describe the shock-accelerated cylindrical fluid layer with arbitrary Atwood numbers is essential for uncovering the effect of Atwood numbers on the perturbation growth. The recent model (J. Fluid Mech., vol. 969, 2023, p. A6) reveals several contributions to the instability evolution of a shock-accelerated cylindrical fluid layer but its applicability is limited to cases with an absolute value of Atwood numbers close to $1$, due to the employment of the thin-shell correction and interface coupling effect of the fluid layer in vacuum. By employing the linear stability analysis on a cylindrical fluid layer in which two interfaces separate three arbitrary-density fluids, the present work generalizes the thin-shell correction and interface coupling effect, and thus, extends the recent model to cases with arbitrary Atwood numbers. The accuracy of this extended model in describing the instability evolution of the shock-accelerated fluid layer before reshock is confirmed via direct numerical simulations. In the verification simulations, three fluid-layer configurations are considered, where the outer and intermediate fluids remain fixed and the density of the inner fluid is reduced. Moreover, the mechanisms underlying the effect of the Atwood number at the inner interface on the perturbation growth are mainly elucidated by employing the model to analyse each contribution. As the Atwood number decreases, the dominant contribution of the Richtmyer–Meshkov instability is enhanced due to the stronger waves reverberated inside the layer, leading to weakened perturbation growth at initial in-phase interfaces and enhanced perturbation growth at initial anti-phase interfaces.
With the over-use of tetracycline (TC) and its ultimate accumulation in aquatic systems, the demand for TC removal from contaminated water is increasing due to its severe threat to public health. Clay minerals have attracted great attention as low-cost adsorbents for controlling water pollution. The objective of the present study was to measure the adsorption behavior and mechanisms of TC on allophane, a nanosized clay mineral with a hollow spherical structure; to highlight the advantage of the allophane nanostructure, a further objective was to compare allophane with halloysite and montmorillonite, which have nanostructures that differ from allophane. Structural features and surface physicochemical properties were characterized by transmission electron microscopy (TEM), Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), zeta potential, N2-physisorption, and acid–base titration. The adsorption data showed that TC adsorption followed the pseudo-second order and Langmuir models. The adsorption was pH dependent, as all three clay minerals performed better under neutral to weakly alkaline conditions and maintained high adsorption performance in the presence of co-existing Na+/K+/Ca2+/Mg2+ cations. Regeneration of the adsorbent was excellent, with efficiencies exceeding 75% after five recycles. By comparison, allophane always exhibited the greatest adsorption capacity, up to 796 mg g–1 at ~pH 9. The TC adsorption on allophane and halloysite was dominated by inner-sphere complexation, together with a small amount of electrostatic adsorption, while that on montmorillonite involved mainly interlayer cation exchange. The findings provide insights into the effects of nanostructures of clay minerals on their TC adsorption performance and highlight the huge potential of allophane as an efficient and inexpensive adsorbent for TC removal.
The influence of the SNP rs174575 (C/G) within the fatty acid desaturase 2 gene on the levels of long-chain PUFA was determined through statistical meta-analysis. Six databases were searched to retrieve the relevant literature. Original data were analysed using Stata 17·0, encompassing summary statistics, tests for heterogeneity, assessment of publication bias, subgroup analysis and sensitivity analysis. A total of ten studies were identified and grouped into twelve trials. Our results showed that individuals who carried the minor G allele of rs174575 had significantly higher dihomo-γ-linolenic acid levels (P = 0·005) and lower arachidonic acid levels (P = 0·033) than individuals who were homozygous for the major allele. The subgroup analysis revealed that the G-allele carriers of rs174575 were significantly positively correlated with linoleic acid (P = 0·002) and dihomo-γ-linolenic acid (P < 0·001) and negatively correlated with arachidonic acid (P = 0·004) in the European populations group. This particular SNP showed a potential association with higher concentrations of dihomo-γ-linolenic acid (P = 0·050) and lower concentrations of arachidonic acid (P = 0·030) within the breast milk group. This meta-analysis has been registered in the PROSPERO database (ID: CRD42023470562).
In this paper, a capsule endoscopy system with a sensing function is proposed for medical devices. A single-arm spiral antenna is designed for data transmission and is combined with the voltage controlled oscillator to achieve sensing capabilities. The designed antenna operates at a 900 MHz industrial scientific medical band. By establishing a three-layer cylindrical model of the stomach, it was concluded that the antenna in the stomach has a high peak gain of −1.1 dBi. Additionally, the antenna achieved a −10 dB impedance bandwidth of 5%. The capsule endoscopy was experimentally measured in both actual stomach and simulated environments. The maximum working distance of the capsule endoscope was measured to be 6.8 m. Additionally, the proposed capsule endoscope was tested for its sensing function using solutions with different dielectric constants. Finally, it was confirmed through link analysis that it has good communication capabilities. The results and analysis confirm that the proposed capsule endoscope can be used for examining gastric diseases.
This study presents observations of coherent modes (CMs) in a spherical tokamak using a microwave interferometer near the midplane. The CMs within the 30–60 kHz frequency range were observed during electron cyclotron resonance heating only, and the frequency of the CMs increased proportionally with the square root of the electron temperature near $R = 0.7m$. Generally, these modes displayed bursting and chirping signatures with strong density rise and fall. Their appearance indicated an increase in the intensity of hard x rays, suggesting a deterioration in energetic electron confinement. Furthermore, the effect of CMs on the intensity of energetic electron-driven whistler waves was observed. They decreased when CMs were present and gradually increased with the decrease in CM intensity. The CMs may influence the intensity of whistler waves by affecting the energetic electron confinement.
Aphis gossypii is one of the most economically important agricultural pests that cause serious crop losses worldwide, and the indiscriminate chemical application causes resistance development in A. gossypii, a major obstacle to successful control. In this study, we selected the up-regulated expression gene AgJHAMT, which was enriched into juvenile hormone pathway though transcriptome sequencing analysis of the cotton aphids that fed on transgenic cotton lines expressing dsAgCYP6CY3 (the TG cotton). The AgJHAMT gene was overexpressed in cotton aphids which fed on the TG cotton, and its expression profile during the nymphs was clarified. Then, silencing AgJHAMT could advance the developmental period of cotton aphids by 0.5 days compared with control groups. The T and t values of cotton aphids in the dsJHAMT treatment group (6.88 ± 0.15, 1.65 ± 0.06) were significantly shorter than that of the sprayed H2O control group (7.6 ± 0.14, 1.97 ± 0.09) (P < 0.05), respectively. The fast growth caused by AgJHAMT silencing was rescued by applying the JH analogue, methoprene. Overall, these findings clarified the function of AgJHAMT in the developmental period of A. gossypii. This study contributes to further clarify the molecular mechanisms of delaying the growth and development of cotton aphids by the transgenic cotton lines expressing dsAgCYP6CY3.
One species-general life history (LH) principle posits that challenging childhood environments are coupled with a fast or faster LH strategy and associated behaviors, while secure and stable childhood environments foster behaviors conducive to a slow or slower LH strategy. This coupling between environments and LH strategies is based on the assumption that individuals’ internal traits and states are independent of their external surroundings. In reality, individuals respond to external environmental conditions in alignment with their intrinsic vitality, encompassing both physical and mental states. The present study investigated attachment as an internal mental state, examining its role in mediating and moderating the association between external environmental adversity and fast LH strategies. A sample of 1169 adolescents (51% girls) from 9 countries was tracked over 10 years, starting from age 8. The results confirm both mediation and moderation and, for moderation, secure attachment nullified and insecure attachment maintained the environment-LH coupling. These findings suggest that attachment could act as an internal regulator, disrupting the contingent coupling between environmental adversity and a faster pace of life, consequently decelerating human LH.
Thanks to its real-time computation efficiency, deep reinforcement learning (DRL) has been widely applied in motion planning for mobile robots. In DRL-based methods, a DRL model computes an action for a robot based on the states of its surrounding obstacles, including other robots that may communicate with it. These methods always assume that the environment is attack-free and the obtained obstacles’ states are reliable. However, in the real world, a robot may suffer from obstacle localization attacks (OLAs), such as sensor attacks, communication attacks, and remote-control attacks, which cause the robot to retrieve inaccurate positions of the surrounding obstacles. In this paper, we propose a robust motion planning method ObsGAN-DRL, integrating a generative adversarial network (GAN) into DRL models to mitigate OLAs in the environment. First, ObsGAN-DRL learns a generator based on the GAN model to compute the approximation of obstacles’ accurate positions in benign and attack scenarios. Therefore, no detectors are required for ObsGAN-DRL. Second, by using the approximation positions of the surrounding obstacles, ObsGAN-DRL can leverage the state-of-the-art DRL methods to compute collision-free motion commands (e.g., velocity) efficiently. Comprehensive experiments show that ObsGAN-DRL can mitigate OLAs effectively and guarantee safety. We also demonstrate the generalization of ObsGAN-DRL.
Vessel trajectories from the Automatic Identification System (AIS) play an important role in maritime traffic management, but a drawback is the huge amount of memory occupation which thus results in a low speed of data acquisition in maritime applications due to a large number of scattered data. This paper proposes a novel online vessel trajectory compression method based on the Improved Open Window (IOPW) algorithm. The proposed method compresses vessel trajectory instantly according to vessel coordinates along with a timestamp driven by the AIS data. In particular, we adopt the weighted Euclidean distance (WED), fusing the perpendicular Euclidean distance (PED) and synchronous Euclidean distance (SED) in IOPW to improve the robustness. The realistic AIS-based vessel trajectories are used to illustrate the proposed model by comparing it with five traditional trajectory compression methods. The experimental results reveal that the proposed method could effectively maintain the important trajectory features and significantly reduce the rate of distance loss during the online compression of vessel trajectories.
Various psychosocial and psychological interventions have been developed to reduce schizophrenia relapse prevention. A better understanding of these active interventions is important for clinical practice and for meaningful allocation of resources. However, no bibliometric analysis of this area has been conducted. Studies were retrieved from the Web of Science Core Collection database. The publication outputs and cooperation of institutions were visualized with Origin 2021. Global cooperation was visualized using ArcGIS Pro3.0. VOSviewer was used to generate visualizations of network of authors and keywords. The number of annual publications generally showed a fluctuating upward trend over the past 20 years. Germany published the most relevant articles (361, 26.76%). The Technical University of Munich was the most productive institution (70, 9.86%). Leucht Stefan published the most articles (46, 6.48%) and had the highest number of citations (4,375 citations). Schizophrenia Research published the most studies (39, 5.49%). Keywords were roughly classified into three clusters: cognitive behavioral therapy (CBT), family interventions and family psychoeducation and other factors related to interventions. The findings provided the current status of research on psychosocial and psychological interventions for schizophrenia relapse prevention from a bibliometric perspective. Recent research has mainly focused on CBT, family interventions and family psychoeducation.