Effects of childhood trauma on the symptom-level relation between depression, anxiety, stress, and problematic smartphone use: A network analysis.

BACKGROUND: Childhood trauma experience is closely associated with depression, anxiety, stress, and problematic smartphone use (PSU). However, few studies have explored the complex symptom-level relations between these variables among people with and without trauma experiences, leaving a gap in treating and alleviating these mental disorders among individuals with childhood trauma. METHODS: The current study used a convenience sampling method and recruited 2708 participants who completed Childhood Trauma Questionnaire-Short Form (CTQ-SF), Depression Anxiety and Stress Scales (DASS-21), and Mobile Phone Addiction Tendency Scale (MPATS), dividing them into trauma (n = 1454, Mean age = 19.67) and no-trauma (n = 1254, Mean age = 19.57) groups according to the cut-off scores of CTQ-SF. Symptom network analysis and network comparison test were conducted to construct and compare the network models between trauma and no-trauma groups. RESULTS: The findings indicate that the trauma group and females exhibit greater average levels of DASS-21 and PSU symptoms compared to the no-trauma group and males, respectively. Additionally, the edge between "Stress" and "Anxiety" is the strongest across trauma and no-trauma groups. "Social comfort" is a bridge symptom of the trauma group network and the results of bridge symptoms in the no-trauma group are not stable. LIMITATIONS: This study did not categorize all individuals according to specific types of trauma experiences and it is a cross-sectional design. The prevalences calculated in this study may not be generalizable. CONCLUSIONS: Interventions targeting different bridge symptoms in the trauma and no-trauma network models may help reduce the severity of symptoms.

Enhancing X-Ray Sensitization with Multifunctional Nanoparticles.

In the progression of X-ray-based radiotherapy for the treatment of cancer, the incorporation of nanoparticles (NPs) has a transformative impact. This study investigates the potential of NPs, particularly those comprised of high atomic number elements, as radiosensitizers. This aims to optimize localized radiation doses within tumors, thereby maximizing therapeutic efficacy while preserving surrounding tissues. The multifaceted applications of NPs in radiotherapy encompass collaborative interactions with chemotherapeutic, immunotherapeutic, and targeted pharmaceuticals, along with contributions to photodynamic/photothermal therapy, imaging enhancement, and the integration of artificial intelligence technology. Despite promising preclinical outcomes, the paper acknowledges challenges in the clinical translation of these findings. The conclusion maintains an optimistic stance, emphasizing ongoing trials and technological advancements that bolster personalized treatment approaches. The paper advocates for continuous research and clinical validation, envisioning the integration of NPs as a revolutionary paradigm in cancer therapy, ultimately enhancing patient outcomes.

Identification of ferroptosis-associated genes and potential pharmacological targets in sepsis-induced myopathy.

Background: The role of Ferroptosis in the course of sepsis-induced myopathy is yet unclear. The objective of our work is to identify key genes connected with Ferroptosis in sepsis-induced myopathy and investigate possible pharmaceutical targets related to this process. This research aims to provide new insights into the management of sepsis-induced myopathy. Methods: We got the GSE13205 dataset from the Gene Expression Omnibus (GEO) and extracted Ferroptosis-associated genes from the FerrDb database. After conducting a functional annotation analysis of these genes, we created a protein-protein interaction network using Cytoscape software to identify important genes. Subsequently, we employed CMap to investigate prospective pharmaceuticals that could target these crucial genes. Results: A total of 61 genes that are expressed differently (DEGs) have been found concerning Ferroptosis. These genes are involved in a wide range of biological functions, including reacting to signals from outside the cell and the availability of nutrients, programmed cell death, controlling apoptosis, and responding to peptides, chemical stressors, and hormones. The KEGG pathway study revealed that these pathways are involved in Ferroptosis, autophagy, P53 signaling, PI3K-Akt signaling, mTOR signaling, HIF-1 signaling, endocrine resistance, and different tumorigenic processes. In addition, we created a network that shows the simultaneous expression of important genes and determined the top 10 medications that have the potential to treat sepsis-induced myopathy. Conclusion: The bioinformatics research undertaken sheds insight into the probable role of Ferroptosis-associated genes in sepsis-induced myopathy. The identified critical genes show potential as therapeutic targets for treating sepsis-induced myopathy, offering opportunities for the development of tailored medicines.

Mapping network connection and direction among symptoms of depression and anxiety in patients with chronic gastritis.

Regarding neurophysiological and developmental findings, anxiety and depression are usual comorbidities of gastritis patients. However, research related to anxiety and depression among chronic gastritis patients was conducted on the disease level while ignoring symptoms. Hence, we rendered the network approach to reveal the symptoms of anxiety and depression among chronic gastritis patients. Three hundred and sixty-nine chronic gastritis patients (female = 139, Mage = 55.87 years) were asked to complete the Self-Rating Anxiety Scale and Self-Rating Depression Scale. Three symptom networks and one directed acyclic graph (DAG) network were formed. First, in the anxiety network of chronic gastritis patients, dizziness was the most influential symptom. In the depression network of chronic gastritis patients, depressed affect and psychomotor retardation were the influential symptoms. Second, panic, easy fatiguability, weakness, palpitation, depressed affect, tachycardia, fatigue, and psychomotor agitation bridged the anxiety-depression network of chronic gastritis patients. Third, DAG networks showed that anxiousness and hopelessness could trigger other symptoms in the anxiety-depression networks of chronic gastritis patients. The current study provided insightful information on patients with chronic gastritis by examining the structures of symptoms.

Injectable Double Crosslinked Hydrogel-Polypropylene Composite Mesh for Repairing Full-Thickness Abdominal Wall Defects.

Abdominal wall defects are common clinical diseases, and mesh repair is the standard treatment method. The most commonly used polypropylene (PP) mesh in clinical practice has the advantages of good mechanical properties, stable performance, and effective tissue integration effect. However, direct contact between abdominal viscera and PP mesh can lead to severe abdominal adhesions. To prevent this, the development of a hydrogel-PP composite mesh with anti-adhesive properties may be an effective measure. Herein, biofunctional hydrogel loaded with rosmarinic acid is developed by modifying chitosan and Pluronic F127, which possesses suitable physical and chemical properties and commendable in vitro biocompatibility. In the repair of full-thickness abdominal wall defects in rats, hydrogels are injected onto the surface of PP mesh and applied to intraperitoneal repair. The results indicate that the use of hydrogel-PP composite mesh can alleviate abdominal adhesions resulting from traditional PP mesh implantation by decreasing local inflammatory response, reducing oxidative stress, and regulating the fibrinolytic system. Combined with the tissue integration ability of PP mesh, hydrogel-PP composite mesh has great potential for repairing full-thickness abdominal wall defects.

The unique role of meaning in life in the relationships between trait awe, subjective well-being, and prosocial tendency: A network analysis.

Although individuals with higher trait awe (the tendency to experience awe) are known to be happier and more prosocial, there is limited understanding of the mechanisms underlying these complex relationships. This study uses network analysis to explore dimension-level relationships between trait awe, meaning in life, subjective well-being (SWB), and prosocial tendency in a joint network and to explore the bridging role of meaning in life in the network. A total of 538 adults (53.2% females; Mage = 19.86 ± 1.51) completed the survey. The network revealed unique and intricate connections between the dimensions of trait awe, meaning in life (i.e., the presence of and the search for meaning, abbreviated as POM and SFM), subjective happiness and life satisfaction (SWB), and prosocial tendency (i.e., willingness to donate money and volunteer time). Trait awe exhibited direct links to subjective happiness, life satisfaction, and prosocial tendency to donate money. Moreover, through POM and SFM, trait awe also exhibited indirect links to each dimension of SWB and prosocial tendency. Within the global network, POM was further identified as acting as a bridge node with the highest bridge strength and closeness, indicating that POM could efficiently transmit influences within the entire network. These findings highlight the distinct contributions of meaning in life to understanding the relationships between trait awe, SWB, and prosocial tendency, and provide valuable insights for improving SWB and fostering prosocial tendencies.

The impact of long-term online learning on social anxiety and problematic smartphone use symptoms among secondary school students with different levels of fear of missing out: Evidence from a symptom network and longitudinal panel network analysis.

Background: The advancement of communication technology and the impact of the COVID-19 pandemic have led to an increased reliance on online education. However, the effects of the long-term use of smart devices for online learning on students' social anxiety and problematic smartphone use (PSU) and the role of fear of missing out (FoMO) in this process have yet to be fully explored. Methods: This study analysed longitudinal data from 2,356 high school students (female = 1,137 (48.26%), mean age = 13.84, SD age = 1.37) in China, divided into high- and low-FoMO groups based on their scores on the FoMO scale, to examine the impact of four months of online learning on social anxiety and PSU. The Social Anxiety Scale (SAS) and Mobile Phone Addiction Index (MPAI) were used to assess social anxiety and PSU symptoms. Results: The undirected symptom networks revealed more bridge symptoms among the students in the high-FoMO group, although their overall symptom scores decreased. The results of the directed cross-lagged panel networks showed that "productivity loss" predicted other symptoms in the low-FoMO group but that "afraid of negative evaluation" was the predictor in the high-FoMO group. Meanwhile, "withdrawal/escape" and "productivity loss" were the symptoms that were most affected by other symptoms in the high-FoMO and low-FoMO groups, respectively. Conclusions: The current study therefore sheds light on the changes in social anxiety and PSU symptoms among secondary school students during long-term online learning, as well as the moderating role of FoMO.

First Report of Leek Yellow Stripe Virus Infecting Allium cepa in China.

Onion (Allium cepa), a member of the genus Allium, is widely cultivated throughout the world including China (Zhang et al. 2022). In July 2022, stunted onion (A. cepa 'Weiwang') plants showing typical symptoms of yellow stripe and leaves distortion (Fig. S1) were observed in a vegetable garden in Hohhot, Inner Mongolia, China. The garden is approximately 0.24 ha with around 20,000 onion plants, out of which 140 plants were symptomatic. Diagnosis of the symptomatic plants using negative stain electron microscopy revealed the association of long flexuous virus particles measuring about 11 to 12 nm × 820 to 1000 nm (Fig. S2), which was suggestive of the presence of potyvirus (Chen et al. 2002). Subsequently, the pathogen was identified as the leek yellow stripe virus through RT-PCR combined with Sanger sequencing as described below. The total RNA of each sample was extracted using the MiniBEST plant RNA extraction kit (TaKaRa, Dalian, China), serving as template for synthesis of cDNA using the ABScriptIII RT master mix (ABclonal Biotechnology, Wuhan, China). We then amplified a fragment at the 3' terminus of LYSV using a M5 Hiper superluminal mix (Mei5 Biotechnology, Beijing, China) with the primer pair LYSV-F / LYSV-R (Santosa and Ertunc 2020) which flank the partial NIb gene, the complete coat protein gene and partial 3' untranslated region of LYSV. A unique PCR product of about 1 kb was seen for 10 out of the 140 samples. Five out of the 10 PCR products were randomly selected and cloned using a Zero Background pTOPO-TA cloning kit (Aidlab Technologies, Beijing, China) and E. coli JM109 competent cells were then transformed. Positive colonies were screened by PCR detection of the insert fragments using the primers LYSV-F/-R, and the inserts were sequenced at BGI Genomics (Beijing) using the M13(-21) Forward and M13 Reverse primers. All the obtained sequences were 1032 nt in length, and shared nucleotide sequence identities of 99.2% to 100% (two out of the five sequences were identical to each other). The query sequences were submitted to BLASTn to retrieve homologous sequences from NCBI GenBank databases, and the results showed that the four sequences were homologous to LYSV, suggesting the occurrence of LYSV on onions in Inner Mongolia, China. The sequences were then deposited in GenBank under accession numbers of OQ969953-56, named LYSV isolate Hohhot-1, -2, -3, and -4. In comparison with other published LYSV isolates, the LYSV Hohhot-1, -2, -3, and -4 had the highest nucleotide sequence identity of 87.23%, 86.97%, 87.33%, and 87.23% with LYSV G66 (GenBank accession no. MN059493), respectively, which infects garlic in China. Phylogeny analysis was performed based on 41 complete sequences of the CP gene of LYSV, including the four in this work and another 37 from GenBank of which six isolates were discovered in onions in Turkey (MN070124, MN070126, MN070130, MN070131, MN864794 and MN864795) and the others 31 isolates were from garlics or leeks in 15 different countries (Argentina, Australia, Brazil, China, Ethiopia, Germany, India, Iran, Japan, Mexico, Netherlands, New Zealand, Serbia, South Korea, and Spain), while the CP gene of onion yellow dwarf virus (AJ510223) was employed as an outgroup reference. The tree was reconstructed using the neighbor-joining method of MEGA11 with a bootstrap value of 1,000 replicates. On the tree (Fig. S3), the LYSV Hohhot-1, -2, -3, and -4 were closely related to each other and were distinct from other LYSV isolates including the six isolates in onions in Turkey, suggesting a specific genetic variation of the LYSV isolates in Hohhot. According to Santosa et al. (2023), LYSV Hohhot-1, -2, -3, and -4 were within the S-type lineage. This was the first record of LYSV infecting onions in China, expanding the natural host range of LYSV in China, which offered important information for the management of onion diseases.

A novel ratiometric electrochemical aptasensor based on M-shaped functional DNA complexes for simultaneous detection of trace lead and mercury ions in series aquatic edible vegetables.

Simultaneous quantification of multiple heavy metal ions (HMIs) is essential due to enhanced toxicity induced by synergistic effects. The currently available detection methods suffer from drawbacks such as costly devices, poor anti-interference, and specificity. In this work, a ratiometric electrochemical aptasensor for simultaneous detection of trace lead (Pb2+) and mercury ions (Hg2+) was developed. Here, a metal-organic framework, UiO-66-CNTs, with inherent and stable electrochemical signal was used for loading complementary strands (CSs) and internal reference. Guanine-rich and thymine-rich oligonucleotides, labelled with carbon dots (CDs), acted as aptamers (Apts) and hybridized with CSs to form M-shaped DNA complexes. Pb2+ and Hg2+ could be recognized and captured by Apts to form Pb2+-G-quadruplex and T-Hg2+-T complexes, leading to the destruction of M-shaped DNA complexes and changes in CDs' signal. The current ratios, ICDs/IUiO-66-CNTs, were applied to quantify Pb2+ and Hg2+. Benefiting from the anti-interference ability of the ratiometric strategy and the specificity of Apts, the proposed method enabled detection Pb2+ and Hg2+ through simple instrumentation, with detection limits of 2.0 ng mL-1 and 0.5 ng mL-1. Moreover, it was applied to assess Pb2+ and Hg2+ contamination in series of aquatic edible vegetables. The experimental results were consistent with inductively coupled plasma-mass spectrometry (ICP-MS), demonstrating its potential in practical applications.

Mapping network connection and direction between anxiety and depression symptoms across the early, middle, and late adolescents: Insights from a large Chinese sample.

Depression and anxiety are two mental disorders prevailing among adolescents. However, issues regarding the trajectory of depression and anxiety are still controversial on both the disease and symptom dimensions. The novel method of network analysis was used to provide insight into the symptom dimension. 20,544 adolescents (female = 10,743, 52.3%) aged between 14 and 24 years (age mean ± sd = 16.9 ± 2.94) were divided into three subgroups according to age so that the course of depression and anxiety could be traced. Network analysis and the Bayesian network model were used in the current study. The results indicated that uncontrollable worry - excessive worry was the most significant edge for all adolescents, whereas concentration - motor had the highest edge weights for early adolescents, and anhedonia - energy was the most critical pairwise symptom for middle and late adolescents. Irritability can bridge anxiety and depression in the early and middle stages of adolescence, while suicide plays a bridging role in the early and late stages of adolescence. Restlessness and guilt can bridge anxiety and depression in middle- and late-stage adolescents, and feeling afraid plays a unique role in middle-stage adolescents. Except for sad mood, which can trigger middle adolescents' anxiety and depression, the other three subgroups were mainly triggered by nervousness. In addition, all results in our current study were shown to be stable and accurate. In treatment, targeting central and triggering symptoms at different stages of adolescence may be critical to alleviating the comorbidity of anxiety and depression.

Ultrasound-Induced Cascade Amplification in a Mechanoluminescent Nanotransducer for Enhanced Sono-Optogenetic Deep Brain Stimulation.

Remote and genetically targeted neuromodulation in the deep brain is important for understanding and treatment of neurological diseases. Ultrasound-triggered mechanoluminescent technology offers a promising approach for achieving remote and genetically targeted brain modulation. However, its application has thus far been limited to shallow brain depths due to challenges related to low sonochemical reaction efficiency and restricted photon yields. Here we report a cascaded mechanoluminescent nanotransducer to achieve efficient light emission upon ultrasound stimulation. As a result, blue light was generated under ultrasound stimulation with a subsecond response latency. Leveraging the high energy transfer efficiency of focused ultrasound in brain tissue and the high sensitivity to ultrasound of these mechanoluminescent nanotransducers, we are able to show efficient photon delivery and activation of ChR2-expressing neurons in both the superficial motor cortex and deep ventral tegmental area after intracranial injection. Our liposome nanotransducers enable minimally invasive deep brain stimulation for behavioral control in animals via a flexible, mechanoluminescent sono-optogenetic system.

Ultrasound programmable hydrogen-bonded organic frameworks for sono-chemogenetics.

The precise control of mechanochemical activation within deep tissues via non-invasive ultrasound holds profound implications for advancing our understanding of fundamental biomedical sciences and revolutionizing disease treatments. However, a theory-guided mechanoresponsive materials system with well-defined ultrasound activation has yet to be explored. Here we present the concept of using porous hydrogen-bonded organic frameworks (HOFs) as toolkits for focused ultrasound programmably triggered drug activation to control specific cellular events in the deep brain, through on-demand scission of the supramolecular interactions. A theoretical model is developed to visualize the mechanochemical scission and ultrasound mechanics, providing valuable guidelines for the rational design of mechanoresponsive materials at the molecular level to achieve programmable and spatiotemporal activation control. To demonstrate the practicality of this approach, we encapsulate designer drug clozapine N-oxide (CNO) into the optimal HOF nanoparticles for FUS gated release to activate engineered G-protein-coupled receptors in the mice and rat ventral tegmental area (VTA), and hence achieved targeted neural circuits modulation even at depth 9 mm with a latency of seconds. This work demonstrates the capability of ultrasound to precisely control molecular interaction and develops ultrasound programmable HOFs to minimally invasive and spatiotemporally control cellular events, thereby facilitating the establishment of precise molecular therapeutic possibilities. We anticipate that this research could serve as a source of inspiration for precise and non-invasive molecular manipulation techniques, potentially applicable in programming molecular robots to achieve sophisticated control over cellular events in deep tissues.

Brain tumor image segmentation based on improved FPN.

PURPOSE: Automatic segmentation of brain tumors by deep learning algorithm is one of the research hotspots in the field of medical image segmentation. An improved FPN network for brain tumor segmentation is proposed to improve the segmentation effect of brain tumor. MATERIALS AND METHODS: Aiming at the problem that the traditional full convolutional neural network (FCN) has weak processing ability, which leads to the loss of details in tumor segmentation, this paper proposes a brain tumor image segmentation method based on the improved feature pyramid networks (FPN) convolutional neural network. In order to improve the segmentation effect of brain tumors, we improved the model, introduced the FPN structure into the U-Net structure, captured the context multi-scale information by using the different scale information in the U-Net model and the multi receptive field high-level features in the FPN convolutional neural network, and improved the adaptability of the model to different scale features. RESULTS: Performance evaluation indicators show that the proposed improved FPN model has 99.1% accuracy, 92% DICE rating and 86% Jaccard index. The performance of the proposed method outperforms other segmentation models in each metric. In addition, the schematic diagram of the segmentation results shows that the segmentation results of our algorithm are closer to the ground truth, showing more brain tumour details, while the segmentation results of other algorithms are smoother. CONCLUSIONS: The experimental results show that this method can effectively segment brain tumor regions and has certain generalization, and the segmentation effect is better than other networks. It has positive significance for clinical diagnosis of brain tumors.

The impact of romantic relationships on deception detection: Exploring the gender differences and the mediating role of mentalizing.

In evolution, romantic relationships serve as the foundation for breeding and producing offspring. The ability to detect deception in these relationships can safeguard the investment and cultivation of descendants, leading to greater chances of survival and reproduction. However, barely any research has been carried out within this domain. The current study investigated the preliminary relationship between romantic relationships, mentalizing ability, and deception detection ability through an empirical experiment. Participants were primed by their romantic experiences and neutral experiences, and then went through a Reading the Mind in the Eyes (RTM) task and the deception detecting task for real person crime-type videos. Results showed that romantic relationships can improve participants' emotion recognition ability toward negative emotions, and females performed better in the deception detection task than males did. Most importantly, romantic relationships can improve participants' deception detection ability through the mediator of mentalizing ability. Though gender difference was not statistically significant in the RTM task, the results lay a solid foundation for further investigation into females' mentalizing ability and disclose the evolutionary meaning of romantic relationships.

Ultra-Bright Heptamethine Dye Clusters Based on a Self-Adaptive Co-Assembly Strategy for NIR-IIb Biomedical Imaging.

Despite the wide range of applications of bright NIR-II polymethine scaffolds in biomedical imaging, their solvatochromism and aggregation-caused quenching (ACQ) effects in aqueous solutions limit their inherent brightness using traditional encapsulation methods, and effective hydrophilization strategies are still scarce. Here, a new set of Flav dyes is synthesized and PEGylated, followed by manufacturing DSPE@FlavP2000 nanoparticles using a self-adaptive co-assembly strategy to overcome these limitations. FlavP2000 can autonomously adjust its conformation when co-assembled with DSPE-PEG2000 , resulting in high-efficiency luminescence (≈44.9% fluorescence of Flav in DMSO). DSPE@FlavP2000 enables NIR-IIb (>1500 nm) angiography with high signal-to-noise ratios. Notably, this co-assembly can occur in situ between FlavP2000 with proteins in the living body based on a novel mechanism of brightness activation induced by disassembly (BAD), achieving consistent brightness as DSPE@FlavP2000 in blood or serum. The self-adaptive co-assembly strategy can be enhanced by incorporating an IPA moiety, which dynamically binds to albumin to prolong the dye's blood circulation time. Thus, the "enhanced" BAD is successfully applied to long-term vascular imaging and sciatic nerve imaging. Both the self-adaptive co-assembly strategy and BAD phenomenon improve the selectivity and availability of the hydrophilization methods, paving the way for efficient biological applications of polymethine dyes.

Effects of Neuroticism on Differences in Symptom Structure of Life Satisfaction and Depression-Anxiety among College Students: A Network Analysis.

Object: Numerous studies show that depression and anxiety have an adverse effect on life satisfaction among college students. Moreover, neuroticism affects depression, anxiety, and life satisfaction. Comparing the low-neuroticism and high-neuroticism groups, the current study used network analysis to examine the relationship between depression, anxiety, and life satisfaction among college students. Methods: A sample consisted of 1233 college students from China who completed the Big Five Inventory-2 (BFI-2), Self-rating Anxiety Scale (SAS), Self-rating Depression Scale (SDS), and Satisfaction With Life Scale (SWLS).All students were divided into two groups according to levels of neuroticism. Depression-anxiety symptom networks and flow networks were formed. Results: "Insomnia" (SAS19) and "Sleep disturbance" (SDS4) are bridge symptoms of groups with varying neuroticism. In addition, compared to the group with low levels of neuroticism, the group with high levels of neuroticism showed more depression symptoms in bridge symptoms and greater global strength. Many depression-anxiety symptoms are negatively associated with life satisfaction, and "Emptiness" (SDS18) is an important symptom in the high-neuroticism group's flow network. Conclusion: This study contributes to our understanding of the connection between depression, anxiety, neuroticism, and life satisfaction. In addition, the current study identified the essential symptoms to target in depression and anxiety intervention and life satisfaction enhancement among college students.

Mapping network connection of comorbidity of depression and anxiety symptoms among firefighters exposed to traumatic events: Insights from a network analysis.

OBJECTIVE: Firefighters are prone to mental disorders such as anxiety and depression because they are frequently exposed to trauma, including injury and death. Network analysis is an approach used to depict a holistic view of mental disorders, which is a symptom-oriented method, and argues that the mental structure is likely to arise from the interaction among observable symptoms. Hence, the present study aims to reveal the characteristics of depressive and anxiety symptoms for Chinese firefighters via a network approach. METHOD: We recruited 715 male firefighters (Mage = 26.29, SDage = 5.93) and asked them to complete the Self-rating Anxiety Scale and Self-rating Depression Scale to measure their levels of anxiety and depression. RESULTS: Faintness had the highest symptom strength in the anxiety network, while irritability had the highest symptom strength in the depression network. The strongest edge (i.e., the connection among symptoms) in the anxiety network was apprehension-restlessness, and in the depression network was confusion-psychomotor retardation. In the bridge network, which contained both anxiety and depression, the strongest edge was confusion-psychomotor retardation, and the highest centrality symptoms (Z score above 1) were panic, easy fatiguability, palpitations, crying spells, and tachycardia. Bayesian network analysis revealed that fear was the most influential trigger symptom in the anxiety-depression network structure of firefighters. CONCLUSIONS: Clinicians could focus on treating the related bridge and trigger symptoms, such as panic, easy fatiguability, palpitations, crying spells, tachycardia, and fear, to alleviate the comorbidity of anxiety and depression in firefighters. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The Impact of Long-Term Online Learning on Internet Addiction Symptoms among Depressed Secondary School Students: Insights from a Cross-Panel Network Analysis.

BACKGROUND: The COVID-19 pandemic and the shift to online learning have increased the risk of Internet addiction (IA) among adolescents, especially those who are depressed. This study aims to identify the core symptoms of IA among depressed adolescents using a cross-lagged panel network framework, offering a fresh perspective on understanding the interconnectedness of IA symptoms. METHODS: Participants completed the Internet addiction test and the Patient Health Questionnaire-9. A total of 2415 students were initially included, and after matching, only 342 students (a cutoff score of 8) were retained for the final data analysis. A cross-lagged panel network analysis was conducted to examine the autoregressive and cross-lagged trajectories of IA symptoms over time. RESULTS: The incidence rate of depression rose remarkably from 14.16% (N = 342) to 17.64% (N = 426) after the four-month online learning. The symptom of "Anticipation" exhibited the highest out-expected influence within the IA network, followed by "Stay online longer" and "Job performance or productivity suffer". Regarding the symptom network of depression, "Job performance or productivity suffer" had the highest in-expected influence, followed by "Life boring and empty", "Snap or act annoyed if bothered", "Check email/SNS before doing things", and "School grades suffer". No significant differences were found in global network strength and network structure between waves 1 and 2. CONCLUSION: These findings prove the negative effects of online learning on secondary students' mental health and have important implications for developing more effective interventions and policies to mitigate IA levels among depressed adolescents undergoing online learning.

Centrality depression-anxiety symptoms linked to suicidal ideation among depressed college students--A network approach.

The long-term effects of the COVID-19 pandemic have caused severe mental health problems among college students, which can eventually cause suicidal ideation. Therefore, through network analysis, this study aims to explore the new characteristics of the depression-anxiety symptom network that arose during the long-term lockdown of the COVID-19 pandemic and to identify the most influential symptoms linked to suicidal ideation. We used a Patient Health Questionnaire (PHQ-9) score above 10 as the cutoff and screened 622 participants with an inclination toward depressive disorders from 7976 college students, and then divided the sample into suicidal and nonsuicidal groups based on the presence or absence of suicidal ideation. The General Anxiety Disorder scale (GAD-7) was also used. Network analysis was used to identify the network structure of anxiety-depression and which symptoms were directly related to suicidal ideation in the network. The prevalence of depression and anxiety among Chinese college students in the late stage of the COVID-19 pandemic was 7.8% and 17.8%, respectively. The most central symptoms in the nonsuicidal group were "excessive worry," "uncontrollable worry," and "nervousness," and in the suicidal group they were "excessive worry," "motor function," and "irritability." The network of the suicidal group was denser than that of the nonsuicidal group. The most influential symptom directly related to suicidal ideation was "guilt." The most influential central symptom of depression-anxiety comorbidity characteristics of Chinese adolescents showed a tendency to shift from depression-oriented (i.e., sad mood) to anxiety-oriented (i.e., excessive worry) with the continuation of the COVID-19 pandemic. Treatments or interventions focused on these critical symptoms could be useful in preventing college students from suicide risk.

Fear facilitates utilitarian moral judgments: Evidence from a moral judgment task.

Previous research on moral judgment (MJ) has focused on understanding the cognitive processes and emotional factors that influence different types of moral judgment tasks, such as personal and impersonal dilemmas. However, few studies have distinguished between the emotions related to cognition and the complex emotions specifically caused by MJ tasks. This gap in knowledge is important to address to have a better understanding of how emotions influence moral judgment. The aim of this study was to investigate the influence of fear and the role of moral emotions on MJ. Data were collected from 145 participants through jsPsych and analyzed using mixed-model analysis of variance (ANOVA) and correlation analysis. The study found that individuals who were triggered by the fear increased the number of utilitarian moral judgments in personal moral scenarios and lengthened the cognitive process, but not in impersonal moral dilemmas. Hence, we speculate that fear may play a cognitive role in personal moral dilemmas and an emotional role in impersonal moral dilemmas. Another finding is that the complex moral emotions arising from the moral decision-making process may affect the effectiveness of fear and potentially influence moral judgments. However, this study adopts a cautious attitude toward these discoveries, and further verification of this hypothesis should be conducted in the future.