miR-153 promotes neural differentiation by activating the cell adhesion/Ca2+ signaling pathway and targeting ion channel activity in HT-22 cells by bioinformatic analysis.

MicroRNAs have been studied extensively in neurodegenerative diseases. In a previous study, miR-153 promoted neural differentiation and projection formation in mouse hippocampal HT-22 cells. However, the pathways and molecular mechanism underlying miR-153-induced neural differentiation remain unclear. To explore the molecular mechanism of miR-153 on neural differentiation, we performed RNA sequencing on miR-153-overexpressed HT-22 cells. Based on RNA sequencing, differentially expressed genes (DEGs) and pathways in miR-153-overexpressed cells were identified. The Database for Annotation, Visualization and Integrated Discovery and Gene Set Enrichment Analysis were used to perform functional annotation and enrichment analysis of DEGs. Targetscan predicted the targets of miR-153. The Search Tool for the Retrieval of Interacting Genes and Cytoscape, were used to construct protein-protein interaction networks and identify hub genes. Q-PCR was used to detect mRNA expression of the identified genes. The expression profiles of the identified genes were compared between embryonic days 9.5 (E9.5) and E11.5 in the embryotic mouse brain of the GDS3442 dataset. Cell Counting Kit-8 assay was used to determine cell proliferation and cellular susceptibility to amyloid ß-protein (Aß) toxicity in miR-153-overexpressed cells. The results indicated that miR-153 increased cell adhesion/Ca2+ (Cdh5, Nrcam, and P2rx4) and Bdnf/Ntrk2 neurotrophic signaling pathway, and decreased ion channel activity (Kcnc3, Kcna4, Clcn5, and Scn5a). The changes in the expression of the identified genes in miR-153-overexpressed cells were consistent with the expression profile of GDS3442 during neural differentiation. In addition, miR-153 overexpression decreased cellular susceptibility to Aß toxicity in HT-22 cells. In conclusion, miR-153 overexpression may promote neural differentiation by inducing cell adhesion and the Bdnf/Ntrk2 pathway, and regulating electrophysiological maturity by targeting ion channels. MiR-153 may play an important role in neural differentiation; the findings provide a useful therapeutic direction for neurodegenerative diseases.

Cultural Dimensions Moderate the Association between Loneliness and Mental Health during Adolescence and Younger Adulthood: A Systematic Review and Meta-Analysis.

Cultural factors, such as country or continent, influence the relationship between loneliness and mental health. However, less is known about how cultural dimensions moderate this relationship during adolescence and younger adulthood, even if these dimensions manifest as country or continent differences. This study aims to examine the potential influence of Hofstede's cultural dimensions on this relationship using a three-level meta-analysis approach. A total of 292 studies with 291,946 participants aged 10 to 24 were included in this study. The results indicate that cultural dimensions, such as individualism vs. collectivism, indulgence vs. restraint, power distance, and long-term vs. short-term orientation, moderated the associations between loneliness and social anxiety, stress, Internet overuse, and negative affect. The association between loneliness and mental health was not moderated by cultural dimensions, such as masculinity and uncertainty avoidance. These findings suggest that culture's influence on the association between loneliness and mental health is based on a domain-specific mechanism.

A resting-state EEG dataset for sleep deprivation.

To investigate the impact of sleep deprivation (SD) on mood, alertness, and resting-state electroencephalogram (EEG), we present an eyes-open resting-state EEG dataset. The dataset comprises EEG recordings and cognitive data from 71 participants undergoing two testing sessions: one involving SD and the other normal sleep. In each session, participants engaged in eyes-open resting-state EEG. The Psychomotor Vigilance Task (PVT) was employed for alertness measurement. Emotional and sleepiness were measured using Positive and Negative Affect Scale (PANAS) and Stanford Sleepiness Scale (SSS). Additionally, to examine the influence of individual sleep quality and traits on SD, Pittsburgh Sleep Quality Index (PSQI) and Buss-Perry Aggression Questionnaire (BPAQ) were utilized. This dataset's sharing may contribute to open EEG measurements in the field of SD.

Differences in attentional function between experienced mindfulness meditators and non-meditators.

Introduction: Attentional enhancement has often been identified as the central cognitive mechanism underlying the benefits of mindfulness meditation. However, the extent to which this enhancement is observable in the neural processes underlying long-term meditation is unclear. This current study aimed to examine differences in attentional performance between meditators and controls (non-meditators) using a visual oddball task with concurrent electroencephalography (EEG) recordings. Methods: Thirty-four participants were recruited, including 16 meditators and 18 healthy controls, who were non-meditators. The participants completed a visual oddball task, using visual stimuli, and EEG recording. Results: Self-reports revealed that meditators had higher mindful attention scores than did the control group. The behavioral results showed that the meditators demonstrated faster reaction times than the non-meditators did. Neural findings indicated a higher P2 amplitude in the meditators than in the controls. The meditators demonstrated a significantly higher P3 in the target trials than in the distractor trials, which was not observed in the controls. Additionally, the time-frequency analysis demonstrated that the delta and theta powers in the meditators were significantly higher than those in the controls. Conclusions: The study suggests the meditators exhibited greater attentional performance than the controls did, as revealed by EEG and behavioral measures. This study extends previous research on the effects of mindfulness meditation on attention and adds to our understanding of the effects of long-term mindfulness meditation.

Attachment and sleep quality in adults: A multilevel meta-analysis of actor and partner effect.

Within the context of sleep, attachment is hypothesized to play a central role in regulating bedtime affect and arousal. While previous studies have suggested a link between attachment and sleep quality, a meta-analysis specifically examining this association in adults has been lacking. To address this gap, we conducted a series of multilevel meta-analyses of 28 studies on this topic. Our results indicated a correlation between attachment anxiety and an individual's own sleep quality (r = -0.16, p < 0.001), as well as their partner's sleep quality (r = -0.10, p < 0.05). There was also a negative correlation between attachment avoidance and an individual's sleep quality (r = -0.15, p < 0.001) as well as their partner's sleep quality (r = -0.16, p < 0.01). Additionally, the relationships were moderated by several variables, including age, sleep measurement, and gender. Further analysis indicated that attachment anxiety was associated with poorer subjective sleep quality (PSQI) (r = -0.23, p < 0.001), longer sleep latency (r = -0.10, p < 0.05), increased wakefulness after sleep onset (r = -0.09, p < 0.05), and greater daytime sleepiness (r = -0.20, p < 0.01). Attachment avoidance was associated with poorer self-reported sleep quality (PSQI) (r = -0.16, p < 0.001), longer time to fall asleep (r = -0.15, p < 0.05), and increased daytime sleepiness (r = -0.15, p < 0.05). In summary, the findings of the current study supported the association between attachment insecurity and poorer sleep quality in both individuals and their partners. These findings hold important implications for future interventions aimed at improving sleep quality by addressing attachment-related concerns.

Volume of the Dentate Gyrus/CA4 Hippocampal subfield mediates the interplay between sleep quality and depressive symptoms / El volumen del subcampo del giro dentado/hipocampo CA4 media la interacción entre la calidad del sueño y los síntomas depresivos

Background: Emerging evidence increasingly suggests that poor sleep quality is associated with depressive symptoms. The hippocampus might play a crucial role in the interplay between sleep disturbance and depressive symptomatology, e.g., hippocampal atrophy is typically seen in both insomnia disorder and depression. Thus, examining the role of hippocampal volume in the interplay between poor sleep quality and depressive symptoms in large healthy populations is vital. Methods: We investigated the association between self-reported sleep quality, depressive symptoms, and hippocampal total and subfields’ volumes in 1603 healthy young adults from the Behavioral Brain Research Project. Mediation analysis explored the mediating role of hippocampal volumes between sleep quality and depressive symptoms. Results: Self-reported sleep quality and depressive symptoms were positively correlated. In addition, it negatively related to three hippocampal subfields but not total hippocampal volume. In particular, hippocampal subfield DG and CA4 volumes mediated the interrelationship between poor sleep quality and depressive symptoms. Conclusions: Our findings improved the current understanding of the relationship between sleep disturbance, depressive symptomatology, and hippocampal subfields in healthy populations. Considering the crucial role of DG in hippocampal neurogenesis, our results suggest that poor sleep quality may contribute to depression through a reduction of DG volume leading to impaired neurogenesis which is crucial for the regulation of mood.(AU)

Latent profile of the insomnia severity index: A longitudinal study.

STUDY OBJECTIVES: To identify the distinct classification of insomnia symptoms and to explore their association with sleep problems and depression. METHODS: Latent profile analysis was used to examine patterns of insomnia symptoms in two samples. Discovery and replication samples comprised 1043 (Mean age at baseline = 18.95 ± 0.93 years, 62.2% females) and 729 (Mean age at baseline = 18.71 ± 1.02 years, 66.4% females) college students, respectively. Participants completed measures of sleep problems (insomnia symptoms, sleep quality, susceptibility to insomnia, perceived consequences of insomnia, dream recall frequency, and percentage of recurring nightmares) and other psychological variables (rumination and depression). Binary logistic regression was used to analyze the effects of different types of insomnia symptoms at baseline on sleep problems and depression two years later. RESULTS: Four classes of insomnia symptoms were identified, and classified as "non-insomnia" (class 1, 45.7%), "mild subjective symptoms but severe subjective feelings" (class 2, 23.9%), "severe subjective symptoms but mild subjective feelings" (class 3, 22.0%), and "high insomnia risk" (class 4, 8.4%), respectively. Compared with the group classified as non-insomnia group, other classifications significantly predicted insomnia two years later, only class 4 significantly predicted depression, and class 3 significantly predicted susceptibility to insomnia, after adjusting gender, insomnia, depression, and susceptibility to insomnia at baseline. CONCLUSIONS: The findings highlighted the importance of identifying the patterns of insomnia symptoms, and the need for tailored intervention to improve sleep problems. Additionally, when screening for insomnia symptoms, simplified screening using Insomnia Severity Index (ISI) dimensions or items should be considered.

Volume of the Dentate Gyrus/CA4 Hippocampal subfield mediates the interplay between sleep quality and depressive symptoms.

Background: Emerging evidence increasingly suggests that poor sleep quality is associated with depressive symptoms. The hippocampus might play a crucial role in the interplay between sleep disturbance and depressive symptomatology, e.g., hippocampal atrophy is typically seen in both insomnia disorder and depression. Thus, examining the role of hippocampal volume in the interplay between poor sleep quality and depressive symptoms in large healthy populations is vital. Methods: We investigated the association between self-reported sleep quality, depressive symptoms, and hippocampal total and subfields' volumes in 1603 healthy young adults from the Behavioral Brain Research Project. Mediation analysis explored the mediating role of hippocampal volumes between sleep quality and depressive symptoms. Results: Self-reported sleep quality and depressive symptoms were positively correlated. In addition, it negatively related to three hippocampal subfields but not total hippocampal volume. In particular, hippocampal subfield DG and CA4 volumes mediated the interrelationship between poor sleep quality and depressive symptoms. Conclusions: Our findings improved the current understanding of the relationship between sleep disturbance, depressive symptomatology, and hippocampal subfields in healthy populations. Considering the crucial role of DG in hippocampal neurogenesis, our results suggest that poor sleep quality may contribute to depression through a reduction of DG volume leading to impaired neurogenesis which is crucial for the regulation of mood.

Elevated BMI impacts brain-state dynamics within the sensorimotor-to-transmodal hierarchy.

OBJECTIVE: Overweight and obesity, as commonly indicated by a higher BMI, are associated with functional alterations in the brain, which may potentially result in cognitive decline and emotional illness. However, the manner in which these detrimental impacts manifest in the brain's dynamic characteristics remains largely unknown. METHODS: Based on two independent resting-state functional magnetic resonance imaging data sets (Behavioral-Brain Research Project of Chinese Personality, n = 1923; Human Connectome Project, n = 998), the current study employed a Hidden Markov model to identify the spatiotemporal features of brain activity states. Subsequently, the study examined the changes in brain-state dynamics and the corresponding functional outcomes that arise with an increase in BMI. RESULTS: Elevated BMI tends to shift the brain's activity states toward a greater emphasis on a specific set of states, i.e., the metastate, that are relevant to the joint activities of sensorimotor systems, making it harder to transfer to the metastate of transmodal systems. These findings were reconfirmed in a longitudinal sample (Behavioral-Brain Research Project of Chinese Personality, n = 34) that exhibited a significant increase in BMI at follow-up. Importantly, the alternation of brain-state dynamics specifically mediated the relationships between BMI and adverse functional outcomes, including cognitive decline and symptoms of mental illness. CONCLUSIONS: The altered brain-state dynamics within the sensorimotor-to-transmodal hierarchy provide new insights into obesity-related brain dysfunctions and mental health issues.

Single-cell sequencing reveals lung cell fate evolution initiated by smoking to explore gene predictions of correlative diseases.

Continuous smoking leads to adaptive regulation and physiological changes in lung tissue and cells, and is an inductive factor for many diseases, making smokers face the risk of malignant and nonmalignant diseases. The impact of research in this area is getting more and more in-depth, but the stimulant effect, mechanism of action and response mechanism of the main cells in the lungs caused by smoke components have not yet been fully elucidated, and the early diagnosis and identification of various diseases induced by smoke toxins have not yet formed a systematic relationship method. In this study, single-cell transcriptome data were generated from three lung samples of smokers and nonsmokers through scRNA-seq technology, revealing the influence of smoking on lung tissue and cells and the changes in immune response. The results show that: through UMAP cell clustering, 16 intermediate cell states of 23 cell clusters of the four main cell types in the lung are revealed, the differences of the main cell groups between smokers and nonsmokers are explained, and the human lung cells are clarified. Components and their marker genes, screen for new marker genes that can be used in the evolution of intermediate-state cells, and at the same time, the analysis of lung cell subgroups reveals the changes in the intermediate state of cells under smoke stimulation, forming a subtype intermediate state cell map. Pseudo-time ordering analysis, to determine the pattern of dynamic processes experienced by cells, differential expression analysis of different branch cells, to clarify the expression rules of cells at different positions, to clarify the evolution process of the intermediate state of cells, and to clarify the response of lung tissue and cells to smoke components mechanism. The development of this study provides new diagnosis and treatment ideas for early disease detection, identification, disease prevention and treatment of patients with smoking-related diseases, and lays a theoretical foundation based on cell and molecular regulation.

Resting-State EEG Reveals Abnormal Microstate Characteristics of Depression with Insomnia.

Previous research revealed various aspects of resting-state EEG for depression and insomnia. However, the EEG characteristics of depressed subjects with insomnia are rarely studied, especially EEG microstates that capture the dynamic activities of the large-scale brain network. To fill these research gaps, the present study collected resting-state EEG data from 32 subclinical depression subjects with insomnia (SDI), 31 subclinical depression subjects without insomnia (SD), and 32 healthy controls (HCs). Four topographic maps were generated from clean EEG data after clustering and rearrangement. Temporal characteristics were obtained for statistical analysis, including cross-group variance analysis (ANOVA) and intra-group correlation analysis. In our study, the global clustering of all individuals in the EEG microstate analysis revealed the four previously discovered categories of microstates (A, B, C, and D). The occurrence of microstate B was lower in SDI than in SD and HC subjects. The correlation analysis showed that the total Pittsburgh Sleep Quality Index (PSQI) score negatively correlated with the occurrence of microstate C in SDI (r = - 0.415, p < 0.05). Conversely, there was a positive correlation between Self-rating Depression Scale (SDS) scores and the duration of microstate C in SD (r = 0.359, p < 0.05). These results indicate that microstates reflect altered large-scale brain network dynamics in subclinical populations. Abnormalities in the visual network corresponding to microstate B are an electrophysiological characteristic of subclinical individuals with symptoms of depressive insomnia. Further investigation is needed for microstate changes related to high arousal and emotional problems in people suffering from depression and insomnia.

Identifying the insomnia-related psychological issues associated with hyperarousal: A network perspective.

Hyperarousal, recognized as a fundamental characteristic of insomnia for decades, has yielded limited evidence concerning its direct psychological associations. This study aimed to explore the psychological factors linked to hyperarousal within the framework of interrelated variables. Two independent samples, comprising n = 917 and n = 652 young adults, were included in the study. Employing the first dataset as a discovery sample and the second dataset as a replication sample, network analyses were conducted using 26 variables derived from 17 scales. The objective was to estimate the direct and indirect associations between psychological issues, including hyperarousal and insomnia. Additionally, linear regression analysis was employed to assess the convergence of findings obtained from the network analysis. Network analyses in both samples converged to reveal direct associations between insomnia severity and several psychological factors, including negative sleep beliefs, physical fatigue, insomnia response to stress, hyperarousal, self-reported depression, and mental fatigue. Notably, the nodes with relative importance within the network include trait anxiety, depressive rumination, hyperarousal, perfectionism sub-dimension of concern over mistakes, and private self-consciousness. Hyperarousal is one of the key factors linking insomnia with a variety of psychological issues, including emotion-related factors (rumination, perveived stress), sleep-related factors (dysfunctional sleep beliefs and attitudes, insomnia response to stress, fatigue, chronotype), and self-related factors (self-consciousness, perfectionism). The results suggest that forthcoming strategies for enhancing the treatment efficacy of insomnia could consider supplementary interventions that specifically address hyperarousal, other factors directly linked to insomnia, or the hub nodes within the network.

Response inhibition impairment related to altered frontal-striatal functional connectivity in insomnia disorder: A pilot and non-clinical study.

BACKGROUND: It is not clear whether and how insomnia disorder (ID) impairs response inhibition ability. Fronto-striatal functional connectivity (FC) plays a critical role in response inhibition and is found be abnormal in patients with ID. In this study, we examined whether insomnia symptoms impair response inhibition in a large non-clinical sample and whether impaired response inhibition is related to abnormal fronto-striatal FC. METHODS: One hundred and fifteen young ID patients and 160 age and sex-matched healthy controls (HC) underwent resting-state functional magnetic response imaging scans and performed the stop-signal task (SST). Performance of SST, Gray Matter Volumes (GMVs), and connections of brain regions related to fronto-striatal circuits was compared between groups. Further examined the association between response inhibition impairment and fronto-striatal FC. RESULTS: The behavioral results showed that patients with ID had significantly longer stop-signal reaction time (SSRT) compared with the HC, reflecting the impaired response inhibition among IDs. Brain imaging results showed IDs had decreased GMVs of the Right Superior Frontal (SFG) and left Supplementary Motor area (SMA). Seed-based FC results showed that compared to HC, the ID showed decreased FC between left SMA and left Paracentral lobule, left SMA and right SMA, and right SFG and right Orbital Middle Frontal gyrus, and increased FC between right SFG and right putamen. Meanwhile, the FC between right SFG and putamen was positively correlated with SSRT in IDs. CONCLUSIONS: The current study found significantly impaired response inhibition among ID and this impairment may be related to abnormal fronto-striatal FC in ID.

Functional Connectome Hierarchy in Schizotypy and Its Associations With Expression of Schizophrenia-Related Genes.

BACKGROUND AND HYPOTHESIS: Schizotypy has been conceptualized as a continuum of symptoms with marked genetic, neurobiological, and sensory-cognitive overlaps to schizophrenia. Hierarchical organization represents a general organizing principle for both the cortical connectome supporting sensation-to-cognition continuum and gene expression variability across the cortex. However, a mapping of connectome hierarchy to schizotypy remains to be established. Importantly, the underlying changes of the cortical connectome hierarchy that mechanistically link gene expressions to schizotypy are unclear. STUDY DESIGN: The present study applied novel connectome gradient on resting-state fMRI data from 1013 healthy young adults to investigate schizotypy-associated sensorimotor-to-transmodal connectome hierarchy and assessed its similarity with the connectome hierarchy of schizophrenia. Furthermore, normative and differential postmortem gene expression data were utilized to examine transcriptional profiles linked to schizotypy-associated connectome hierarchy. STUDY RESULTS: We found that schizotypy was associated with a compressed functional connectome hierarchy. Moreover, the pattern of schizotypy-related hierarchy exhibited a positive correlation with the connectome hierarchy observed in schizophrenia. This pattern was closely colocated with the expression of schizophrenia-related genes, with the correlated genes being enriched in transsynaptic, receptor signaling and calcium ion binding. CONCLUSIONS: The compressed connectome hierarchy suggests diminished functional system differentiation, providing a novel and holistic system-level basis for various sensory-cognition deficits in schizotypy. Importantly, its linkage with schizophrenia-altered hierarchy and schizophrenia-related gene expression yields new insights into the neurobiological continuum of psychosis. It also provides mechanistic insight into how gene variation may drive alterations in functional hierarchy, mediating biological vulnerability of schizotypy to schizophrenia.

Covariance patterns between sleep health domains and distributed intrinsic functional connectivity.

Sleep health is both conceptually and operationally a composite concept containing multiple domains of sleep. In line with this, high dependence and interaction across different domains of sleep health encourage a transition in sleep health research from categorical to dimensional approaches that integrate neuroscience and sleep health. Here, we seek to identify the covariance patterns between multiple sleep health domains and distributed intrinsic functional connectivity by applying a multivariate approach (partial least squares). This multivariate analysis reveals a composite sleep health dimension co-varying with connectivity patterns involving the attentional and thalamic networks and which appear relevant at the neuromolecular level. These findings are further replicated and generalized to several unseen independent datasets. Critically, the identified sleep-health related connectome shows diagnostic potential for insomnia disorder. These results together delineate a potential brain connectome biomarker for sleep health with high potential for clinical translation.

Functional Connectivity Between Default Mode and Ventral Attention Networks Mediates the Effects of Chronotype on Daily Physical Activity.

Daily physical activity (dPA) is closely related to circadian rhythm and chronotype. The functional connectivity (FC) within or between the default mode (DMN) and ventral attention network (vAN) were associated with dPA and chronotype. DMN-vAN FC was investigated for its role in chronotype and dPA. 153 participants completed the reduced version of the Morningness-Eveningness Questionnaire (rMEQ), dPA was measured via actigraphy (5-day), and then resting-state fMRI scans were performed. rMEQ scores and steps recorded by the actigraphic devices (with each hour as the time window to calculate steps for five consecutive days per hour, subsequently yielding the maximum number of steps and its corresponding time, ie, SM and SMT) represent chronotype and dPA respectively. The results found that the rMEQ scores were significantly negatively correlated with SMT. The positive correlation between the rMEQ scores and the DMN-vAN FC was significant. There were also significant positive correlations between SMT and DMN-vAN FC. Further analysis revealed that DMN-vAN mediates the relationship between chronotype and SMT. The FC of DMN-vAN may be the underlying neural mechanism through which chronotype influences dPA. These findings could support the development of reasonable activity schedules or specific intervention programs to improve physical health.

Spatio-temporal evolution and trend prediction of urban ecosystem service value based on CLUE-S and GM (1,1) compound model.

Ecosystem service value (ESV) is a significant indicator related to regional ecological well-being. Evaluating ESV premised on continuous time series land benefit data can provide an accurate reference for regional ecological civilization construction and sustainable development. Taking Shijiazhuang, the capital city of Hebei Province as an example, the study analyzed land use changes based on the land use data of the continuous time series from 2000 to 2020 and introduced a socio-economic adjustment factor and biomass factor adjustment factor to construct a dynamic assessment model of ecosystem service value. The spatiotemporal changes of the ecosystem service value in Shijiazhuang City were evaluated, and the dynamic prediction of the ecosystem service value was made using the CLUE-S model and the GM (1,1) model. (1) The changes in the overall ESV and spatial pattern in Shijiazhuang are strongly linked to the change in land use, and the contribution of cultivated land, woodland, and grassland to ecosystem service value exceeds 90%. (2) Between 2000 and 2020, the value of ecosystem services illustrated a dynamic change and gradually declined, with the total amount falling from 28.003 to 19.513 billion yuan. Among individual ecosystem services, the value of regulation services suffered the most serious loss. (3) CLUE-S and GM (1,1) perform well in the prediction of ESV. The prediction outcomes illustrate that the ecosystem service value of Shijiazhuang will continue to decline by 2025, and the ecosystem value will drop to 16.771 billion yuan. This research may offer a reference for the dynamic assessment of ESV of the continuous sequence and help to promote regional ecological protection and sustainable development.

Coagulation markers as independent predictors of prostate cancer aggressiveness: a retrospective cohort study.

Coagulation system activation is commonly observed in tumor patients, including prostate cancer (PCa), with coagulation markers proposed as potential prognostic indicators for cancer severity. However, the correlation between these markers and clinicopathological features in PCa remains unclear. Thus, this study investigates the association between comprehensive coagulation markers and clinicopathological characteristics in PCa patients. A retrospective evaluation of 162 PCa patients diagnosed and categorized into low-intermediate-risk or high-risk groups based on clinical and pathological features was conducted. Coagulation markers, including fibrinogen (FIB), D-dimer (DD), activated partial thromboplastin time (APTT), prothrombin time (PT), prothrombin activity (PTA), thrombin time (TT), platelet count (PLT), and international normalized ratio (INR), were assessed. Univariate and multivariate logistic regression analyses were performed to determine associations with clinicopathological features. FIB and DD were confirmed as independent factors associated with high-risk PCa. Furthermore, FIB and DD levels showed significant positive correlations with clinical parameters, including PSA levels, ISUP grade, T stage, N stage, and M stage. Our findings suggest that FIB and DD hold promise as independent prognostic biomarkers for risk stratification in PCa. These coagulation markers may aid in assessing PCa severity and guiding personalized treatment strategies.

Enhanced rich club connectivity in mild or moderate depression after nonpharmacological treatment: A preliminary study.

INTRODUCTION: It has been suggested that the rich club organization in major depressive disorder (MDD) was altered. However, it remained unclear whether the rich club organization could be served as a biomarker that predicted the improvement of clinical symptoms in MDD. METHODS: The current study included 29 mild or moderate patients with MDD, who were grouped into a treatment group (receiving cognitive behavioral therapy or real-time fMRI feedback treatment) and a no-treatment group. Resting-state MRI scans were obtained for all participants. Graph theory was employed to investigate the treatment-related changes in network properties and rich club organization. RESULTS: We found that patients in the treatment group had decreased depressive symptom scores and enhanced rich club connectivity following the nonpharmacological treatment. Moreover, the changes in rich club connectivity were significantly correlated with the changes in depressive symptom scores. In addition, the nonpharmacological treatment on patients with MDD increased functional connectivity mainly among the salience network, default mode network, frontoparietal network, and subcortical network. Patients in the no-treatment group did not show significant changes in depressive symptom scores and rich club organization. CONCLUSIONS: Those results suggested that the remission of depressive symptoms after nonpharmacological treatment in MDD patients was associated with the increased efficiency of global information processing.

The Impact of Sleep Deprivation on Brain Networks in Response to Social Evaluation Tasks.

Sleep loss may lead to negative bias during social interaction. In the current study, we conducted a revised social evaluation task experiment to investigate how sleep deprivation influences the self-referential and cognitive processes of social feedback. The experiment consisted of a first impression task and a social feedback task. Seventy-eight participants completed the first impression task and were divided into normal and poor sleep groups. The results of an independent samples t-test showed that participants who slept worse were less likely to socialize with others but did not evaluate others as less attractive. Afterward, 22 of the participants from the first impression task were recruited to complete the social feedback task during functional magnetic resonance imaging (fMRI) on the mornings following two different sleep conditions at night: one night of normal sleep and one night of sleep deprivation. The results of this within-subject design study showed that participants who experienced the latter condition showed increased activation within the default mode network (i.e. superior parietal lobule, precuneus, inferior parietal lobule, inferior temporal gyrus, and medial frontal gyrus) and anterior cingulate cortex (ACC) and stronger negative insula functional connectivity (FC) with the precuneus to negative feedback than positive feedback. The altered activation and behavioral pattern may indicate a negative bias for social cues. However, stronger negative coupling may indicate stronger cognitive control, which may protect against potential damage to self-concept. Our study suggested that sleep impairs most social functions, but may protect against impairment of important ones, such as self-concept.