Psychosocial Factors Associated With Long-Term Cognitive Impairment Among COVID-19 Survivors: A Cross-Sectional Study.

ABSTRACT: COVID-19 survivors complained of the experience of cognitive impairments, which also called "brain fog" even recovered. The study aimed to describe long-term cognitive change and determine psychosocial factors in COVID-19 survivors. A cross-sectional study was recruited 285 participants from February 2020 to April 2020 in 17 hospitals in Sichuan Province. Cognitive function, variables indicative of the virus infection itself, and psychosocial variables were collected by telephone interview. Univariate logistic regression and Lasso logistic regression models were used for variable selection which plugged into a multiple logistics model. Overall prevalence of moderate or severe cognitive impairment was 6.3%. Logistic regression showed that sex, religion, smoking status, occupation, self-perceived severity of illness, sleep quality, perceived mental distress after COVID-19, perceived discrimination from relatives and friends, and suffered abuse were associated with cognitive impairment. The long-term consequences of cognitive function are related to multiple domains, in which psychosocial factors should be taken into consideration.

Long-term follow-up of brain regional changes and the association with cognitive impairment in quarantined COVID-19 survivors.

OBJECTIVE: This study aimed to evaluate the neuropsychiatric symptoms of quarantined COVID-19 survivors 15 months after discharge and explore its potential association with structural and functional brain changes and inflammation. METHODS: A total of 51 quarantined COVID-19 survivors and 74 healthy controls were included in this study. Cognitive function was assessed using the THINC-integrated tool. Structural brain changes were examined through both surface- and volume-based analyses, and functional changes were assessed using resting-state amplitude low-frequency fluctuation (ALFF). Serum inflammatory markers were measured by a multiplexed flow cytometric assay. RESULTS: COVID-19 survivors exhibited subjective cognitive decline compared to healthy controls, despite no significant differences in objective cognitive tasks. Structural analysis revealed significantly increased gray matter volume and cortical surface area in the left transverse temporal gyrus (Heschl's gyrus) in quarantined COVID-19 survivors. This enlargement was negatively correlated with cognitive impairment. The ALFF analysis showed decreased neural activity in multiple brain regions. Elevated levels of serum inflammatory markers were also found in COVID-19 survivors, including MIP-1a, MIP-1b, TNF-a, and IL-8, which correlated with functional abnormalities. CONCLUSIONS: Our findings indicate a subjective cognitive decline in quarantined COVID-19 survivors 15 months after discharge, which is associated with brain structural alterations in the left Heschl's gyrus. The observed elevation of inflammatory markers suggests a potential mechanism involving inflammation-induced neurogenesis. These results contribute to our understanding of the possible mechanisms underlying long-term neuropsychiatric consequences of COVID-19 and highlight the need for further research to develop targeted interventions.

Oxidative Stress Promotes Liver Cancer Metastasis via RNF25-Mediated E-Cadherin Protein Degradation.

Loss of E-cadherin (ECAD) is required in tumor metastasis. Protein degradation of ECAD in response to oxidative stress is found in metastasis of hepatocellular carcinoma (HCC) and is independent of transcriptional repression as usually known. Mechanistically, protein kinase A (PKA) senses oxidative stress by redox modification in its ß catalytic subunit (PRKACB) at Cys200 and Cys344. The activation of PKA kinase activity subsequently induces RNF25 phosphorylation at Ser450 to initiate RNF25-catalyzed degradation of ECAD. Functionally, RNF25 repression induces ECAD protein expression and inhibits HCC metastasis in vitro and in vivo. Altogether, these results indicate that RNF25 is a critical regulator of ECAD protein turnover, and PKA is a necessary redox sensor to enable this process. This study provides some mechanistic insight into how oxidative stress-induced ECAD degradation promotes tumor metastasis of HCC.

Kiwifruit Peel Extract Improves the Alterations in Lipid Metabolism in High-fat Diet-fed Model Rats.

Previous studies have demonstrated that the kiwifruit peel, which is usually discarded by consumers and factories, has the highest polyphenol content among all parts of the kiwifruit. To maximize the utilization of these waste resources, the aim of this study was to examine the regulatory effects of polyphenols extracted from kiwifruit peel (KPE) on lipid metabolism and investigate their underlying mechanisms. Thirty-two male Sprague‒Dawley rats were divided into four groups: those fed a normal diet, those fed a high-fat (HF) diet, and those fed a HF diet with a low dose of KPE solution (50 mg/kg) or a high dose of KPE (100 mg/kg) by gavage. The findings of the study revealed that KPE effectively reduced body weight gain and the increases in triglycerides and total cholesterol in serum induced by the HF diet (HFD). Additionally, KPE supplementation led to a significant decrease in hepatic fat accumulation, potentially by increasing hepatic oxidation abilities. Hepatic lipidomics demonstrated that KPE influenced various metabolic pathways, including linoleic acid metabolism, steroid biosynthesis, and the biosynthesis of unsaturated fatty acids in HFD-induced rats, which were associated with the downregulation of FATP2, ACC, FAS, GPAT, DGTA1, DGTA2, and PPARγ expression as well as the upregulation of AMPK, PGC-1α, CPT-1, and PPARα expression. These findings suggest that KPE has considerable regulatory effects in rats with dyslipidaemia, which may provide supporting information for the reuse of kiwifruit peel.

The Effect of High-Altitude Hypoxia on Neuropsychiatric Functions.

Liu, Bo, Minlan Yuan, Mei Yang, Hongru Zhu, and Wei Zhang. The effect of high-altitude hypoxia on neuropsychiatric functions. High Alt Med Biol. 25:26-41, 2024. Background: In recent years, there has been a growing popularity in engaging in activities at high altitudes, such as hiking and work. However, these high-altitude environments pose risks of hypoxia, which can lead to various acute or chronic cerebral diseases. These conditions include common neurological diseases such as acute mountain sickness (AMS), high-altitude cerebral edema, and altitude-related cerebrovascular diseases, as well as psychiatric disorders such as anxiety, depression, and psychosis. However, reviews of altitude-related neuropsychiatric conditions and their potential mechanisms are rare. Methods: We conducted searches on PubMed and Google Scholar, exploring existing literature encompassing preclinical and clinical studies. Our aim was to summarize the prevalent neuropsychiatric diseases induced by altitude hypoxia, the potential pathophysiological mechanisms, as well as the available pharmacological and nonpharmacological strategies for prevention and intervention. Results: The development of altitude-related cerebral diseases may arise from various pathogenic processes, including neurovascular alterations associated with hypoxia, cytotoxic responses, activation of reactive oxygen species, and dysregulation of the expression of hypoxia inducible factor-1 and nuclear factor erythroid 2-related factor 2. Furthermore, the interplay between hypoxia-induced neurological and psychiatric changes is believed to play a role in the progression of brain damage. Conclusions: While there is some evidence pointing to pathophysiological changes in hypoxia-induced brain damage, the precise mechanisms responsible for neuropsychiatric alterations remain elusive. Currently, the range of prevention and intervention strategies available is primarily focused on addressing AMS, with a preference for prevention rather than treatment.

Epigenetic regulation in major depression and other stress-related disorders: molecular mechanisms, clinical relevance and therapeutic potential.

Major depressive disorder (MDD) is a chronic, generally episodic and debilitating disease that affects an estimated 300 million people worldwide, but its pathogenesis is poorly understood. The heritability estimate of MDD is 30-40%, suggesting that genetics alone do not account for most of the risk of major depression. Another factor known to associate with MDD involves environmental stressors such as childhood adversity and recent life stress. Recent studies have emerged to show that the biological impact of environmental factors in MDD and other stress-related disorders is mediated by a variety of epigenetic modifications. These epigenetic modification alterations contribute to abnormal neuroendocrine responses, neuroplasticity impairment, neurotransmission and neuroglia dysfunction, which are involved in the pathophysiology of MDD. Furthermore, epigenetic marks have been associated with the diagnosis and treatment of MDD. The evaluation of epigenetic modifications holds promise for further understanding of the heterogeneous etiology and complex phenotypes of MDD, and may identify new therapeutic targets. Here, we review preclinical and clinical epigenetic findings, including DNA methylation, histone modification, noncoding RNA, RNA modification, and chromatin remodeling factor in MDD. In addition, we elaborate on the contribution of these epigenetic mechanisms to the pathological trait variability in depression and discuss how such mechanisms can be exploited for therapeutic purposes.

Explainable machine-learning algorithms to differentiate bipolar disorder from major depressive disorder using self-reported symptoms, vital signs, and blood-based markers.

BACKGROUND AND OBJECTIVE: Caused by shared genetic risk factors and similar neuropsychological symptoms, bipolar disorder (BD) and major depressive disorder (MDD) are at high risk of misdiagnosis, which is associated with ineffective treatment and worsening of outcomes. We aimed to develop a machine learning (ML)-based diagnostic system, based on electronic medical records (EMR) data, to mimic the clinical reasoning of human physicians to differentiate MDD and BD (especially BD depressive episodes) patients about to be admitted to a hospital and, hence, reduce the misdiagnosis of BD as MDD on admission. In addition, we examined to what extent our ML model could be made interpretable by quantifying and visualizing the features that drive the predictions. METHODS: By identifying 16,311 patients admitted to a hospital located in western China between 2009 and 2018 with a recorded main diagnosis of MDD or BD, we established three sub-cohorts with different combinations of features for both the MDD-BD cohort and the MDD-BD depressive episodes cohort, respectively. Four different ML algorithms (logistic regression, extreme gradient boosting (XGBoost), random forest, and support vector machine) and four train-test splits were used to train and validate diagnostic models, and explainable methods (SHAP and Break Down) were utilized to analyze the contribution of each of the features at both population-level and individual-level, including feature importance, feature interaction, and feature effect on prediction decision for a specific subject. RESULTS: The XGBoost algorithm provided the best test performance (AUC: 0.838 (0.810-0.867), PPV: 0.810 and NPV: 0.834) for separating patients with BD from those with MDD. Core predictors included symptoms (mood-up, exciting, bad sleep, loss of interest, talking, mood-down, provoke), along with age, job, myocardial enzyme markers (creatine kinase, hydroxybutyrate dehydrogenase), diabetes-associated marker (glucose), bone function marker (alkaline phosphatase), non-enzymatic antioxidant (uric acid), markers of immune/inflammation (white blood cell count, lymphocyte count, basophil percentage, monocyte count), cardiovascular function marker (low density lipoprotein), renal marker (total protein), liver biochemistry marker (indirect bilirubin), and vital signs like pulse. For separating patients with BD depressive episodes from those with MDD, the test AUC was 0.777 (0.732-0.822), with PPV 0.576 and NPV 0.899. Additional validation in models built with self-reported symptoms removed from the feature set, showed test AUC of 0.701 (0.666-0.736) for differentiating BD and MDD, and AUC of 0.564 (0.515-0.614) for detecting patients in BD depressive episodes from MDD patients. Validation in the datasets without removing the patients with comorbidity showed an AUC of 0.826 (0.806-0.846). CONCLUSION: The diagnostic system accurately identified patients with BD in various clinical scenarios, and differences in patterns of peripheral markers between BD and MDD could enrich our understanding of potential underlying pathophysiological mechanisms of them.

Targeting Mitochondrial Dysfunction in Neurodegenerative Diseases: Expanding the Therapeutic Approaches by Plant-Derived Natural Products.

Mitochondria are the primary source of energy production in neurons, supporting the high energy consumption of the nervous system. Inefficient and dysfunctional mitochondria in the central nervous system have been implicated in neurodegenerative diseases. Therefore, targeting mitochondria offers a new therapeutic opportunity for neurodegenerative diseases. Many recent studies have proposed that plant-derived natural products, as pleiotropic, safe, and readily obtainable sources of new drugs, potentially treat neurodegenerative diseases by targeting mitochondria. In this review, we summarize recent advances in targeting mitochondria in neurotherapeutics by employing plant-derived natural products. We discuss the mechanism of plant-derived natural products according to their mechanism of action on mitochondria in terms of regulating biogenesis, fusion, fission, bioenergetics, oxidative stress, calcium homeostasis, membrane potential, and mitochondrial DNA stability, as well as repairing damaged mitochondria. In addition, we discuss the potential perspectives and challenges in developing plant-derived natural products to target mitochondria, highlighting the clinical value of phytochemicals as feasible candidates for future neurotherapeutics.

Dysfunction of default mode network characterizes generalized anxiety disorder relative to social anxiety disorder and post-traumatic stress disorder.

BACKGROUND: The perseverative cognition of generalized anxiety disorder (GAD) is distinctive compared to other anxiety disorders. However, the disease-specific and shared neuropathophysiological mechanisms of GAD remain unclear. METHODS: We recruited medication-free patients of GAD (N = 33), social anxiety disorder (SAD; N = 36), post-traumatic stress disorder (PTSD; N = 59), and healthy controls (HC; N = 50). All subjects underwent clinical assessments and resting-state functional magnetic resonance imaging. We compared both the amplitude low-frequency fluctuation (ALFF) and seed-based functional connectivity across the whole brain, using the significantly different regions from the ALFF analyses as seed regions, followed by post-hoc tests. RESULTS: We found that ALFF of the left angular gyrus (AG), left inferior parietal lobule (IPL), left precentral gyrus, left middle temporal gyrus, and left cerebellum were higher in GAD compared with SAD, PTSD and HC. This trend was further corroborated by the higher functional connectivity between left AG and bilateral IPL, left inferior temporal gyrus, and left medial prefrontal cortex (mPFC) in GAD. In addition, GAD and SAD both showed abnormally higher left AG-right insula connectivity. Significant correlations were found between anxiety symptom severity and the left AG regional activity and left AG-left mPFC connectivity. LIMITATIONS: We did not compare the differences in neuroimaging between GAD and other anxiety disorders, such as panic disorder. CONCLUSIONS: The default mode network dysfunction may underlie the distinctive perseverative thoughts of GAD relative to other anxiety disorders, and left AG-right insula connectivity may reflect somatic anxiety of anxiety disorder spectrum.

Identifying novel proteins underlying loneliness by integrating GWAS summary data with human brain proteomes.

Enduring loneliness is associated with mental disorders and physical diseases. Although genome-wide association studies (GWAS) have identified risk loci associated with loneliness, how these loci confer the risk remains largely unknown. In the current study, we aimed to investigate key proteins underlying loneliness in the brain by integrating human brain proteomes and transcriptomes with loneliness GWAS to perform a discovery proteome-wide association study (PWAS), followed by a confirmatory PWAS, transcriptome-wide association analysis (TWAS), Mendelian randomization (MR), Steigering filtering analysis and Bayesian colocalization analysis. Moreover, given the fact that loneliness is associated with mental disorders, we explored the shared genetic architecture between loneliness and mental disorders. Totally, we identified 18 genes to be associated with loneliness via their cis-regulated brain protein abundance. Eleven of the 18 genes (61.1%) were replicated in the confirmatory PWAS, and mRNA levels of 4 genes were further validated to be associated with loneliness.MR and genetic colocalization analysis further confirmed that the increased protein abundance of ALDH2 and ICA1L was protective against loneliness, while the increased protein abundance of GPX1 was a risk for developing loneliness. Furthermore, we found genetic correlations, bidirectional causal associations and overlapping phenotype-associated protein profiles between loneliness and mental disorders including major depression and schizophrenia. In summary, our findings provided clues about the brain-related molecular basis underlying loneliness, which warrants further investigation.

Long term neuropsychiatric consequences in COVID-19 survivors: Cognitive impairment and inflammatory underpinnings fifteen months after discharge.

BACKGROUND: Emerging evidence shows that cognitive dysfunction may occur following coronavirus disease 19 (COVID-19) infection which is one of the most common symptoms reported in researches of "Long COVID". Several inflammatory markers are known to be elevated in COVID-19 survivors and the relationship between long-term inflammation changes and cognitive function remains unknown. METHODS: We assessed cognitive function and neuropsychiatric symptoms of 66 COVID-19 survivors and 79 healthy controls (HCs) matched with sex, age, and education level using a digital, gamified cognitive function evaluation tool and questionnaires at 15 months after discharge. Venous blood samples were collected to measure cytokine levels. We performed correlation analyses and multiple linear regression analysis to identify the factors potentially related to cognitive function. RESULTS: The COVID-19 survivors performed less well on the Trails (p = 0.047) than the HCs, but most of them did not report subjective neuropsychiatric symptoms. Intensive care unit experience (ß = -2.247, p < 0.0001) and self-perceived disease severity (ß = -1.522, p = 0.007) were positively correlated, whereas years of education (ß = 0.098, p = 0.013) was negatively associated with the performance on the Trails. Moreover, the abnormally elevated TNF-α levels (r = -0.19, p = 0.040) were negatively correlated with performance on the Trails in COVID-19 group. CONCLUSION: Our findings suggest that COVID-19 survivors show long-term cognitive impairment in executive function, even at 15 months after discharge. Serum TNF-α levels may be an underlying mechanism of long-term cognitive impairment in patients recovering from COVID-19.

Dissecting clinical and biological heterogeneity in clinical states of bipolar disorder: a 10-year retrospective study from China.

Objectives: To dissect clinical and biological heterogeneity in clinical states of bipolar disorder (BD), and investigate if neuropsychological symptomatology, comorbidity, vital signs, and blood laboratory indicators are predictors of distinct BD states. Methods: A retrospective BD cohort was established with data extracted from a Chinese hospital's electronic medical records (EMR) between 2009 and 2018. Subjects were inpatients with a main discharge diagnosis of BD and were assessed for clinical state at hospitalization. We categorized all subjects into manic state, depressive state, and mixed state. Four machine learning classifiers were utilized to classify the subjects. A Shapley additive explanations (SHAP) algorithm was applied to the classifiers to aid in quantifying and visualizing the contributions of each feature that drive patient-specific classifications. Results: A sample of 3,085 records was included (38.54% as manic, 56.69% as depressive, and 4.77% as mixed state). Mixed state showed more severe suicidal ideation and psychomotor abnormalities, while depressive state showed more common anxiety, sleep, and somatic-related symptoms and more comorbid conditions. Higher levels of body temperature, pulse, and systolic and diastolic blood pressures were present during manic episodes. Xgboost achieved the best AUC of 88.54% in manic/depressive states classification; Logistic regression and Random forest achieved the best AUCs of 75.5 and 75% in manic/mixed states and depressive/mixed states classifications, respectively. Myocardial enzymes and the non-enzymatic antioxidant uric acid and bilirubin contributed significantly to distinguish BD clinical states. Conclusion: The observed novel biological associations with BD clinical states confirm that biological heterogeneity contributes to clinical heterogeneity of BD.

Pica in a girl with non-suicidal self-injury: a case report.

Non-suicidal self-injury (NSSI) is on the rise globally, posing a significant societal challenge. Pica, an eating disorder, presents difficulties in treatment due to the absence of effective medications. In this report, we discuss a complex case involving the co-occurrence of pica and non-suicidal self-injury. A 13-year-old girl was admitted to our hospital due to ingesting two batteries. She features a persistent, intense appetite along with sudden and compulsive behaviors such as consuming inedible items or self-inflicted cutting. After receiving a combination of pharmacological treatments (quetiapine, lithium and sertraline), cognitive behavioral therapy (CBT) and modified electroconvulsive therapy (MECT) for 25 days, she was discharged with relief from her clinical symptoms.

Cohort Profile: The China Severe Trauma Cohort (CSTC).

PurposeTo establish a prospective hospital-based cohort, featured by detailed multidimensional data of trauma patients with active follow-ups, which can be a reliable data source for all studies focusing on the effects or underlying mechanistic pathways of environmental and biological factors on multiple interested trauma-related outcomes, particularly the incidence and trajectory of trauma-related psychopathology, in Chinese population.MethodsThe China Severe Trauma Cohort (CSTC) enrolled all traumatized individuals aged 12 to 80 years admitted to the Trauma Center of West China Hospital between 1st March 2020 and 8th July 2022. The bio-sample and detailed questionnaire data were collected at recruitment, and phone/internet follow-ups were scheduled at 1-, 3-, 6-, 12-months after the baseline. Long-term health outcomes are planned to be obtained from administrative databases through data linkage.ResultsA total of 2,500 trauma patients were enrolled (response rate=87.1%) with an average age of 46.01 years, and most of the participants were males(62.6%). The proportions of participants with blood and fecal sample collected at baseline were 93.8% and 66.3%, respectively. Upon 31st August 2022, the follow-up rate was 90.0%, 77.0%, 76.5%, and 89.0% for 1-, 3-, 6-, and 12-months follow-up, respectively. Fall/wrench (47.6%) and traffic accident (26.2%) were the top causes of current trauma. The most common psychopathology at recruitment was sleep disturbance(39.4%), followed by depression(22.6%), anxiety(18.2%), and acute stress reaction(7.8%), all of which showed recovering trajectories during the follow-up period, particularly the first 3 months after baseline.ConclusionsCSTC provides a platform with multidimensional data to study both short-term and long-term trauma-related health consequences, prompting early identification and intervention for individuals with high risk of health decline after trauma exposures.

[Changes and Prediction of Social Functional Disability and Quality of Life in Patients with Major Depressive Disorder over the Course of 1-Year Medication].

Objective: To investigate the changes in social function impairment and quality of life and their predictive factors in patients with major depressive disorder (MDD) over the course of 1-year drug treatment. Methods: A total of 54 MDD patients were enrolled for the study. The 17-item Hamilton Rating Scale for Depression (HAMD-17, hereafter referred to simply as HAMD), Sheehan Disability Scale (SDS), and Quality of Life Enjoyment and Satisfaction Questionnaire-Short Form (Q-LES-Q-SF) were used to evaluate depressive symptoms, social functioning, and quality of life, respectively, at baseline (0), as well as 1 month (1 m), 2 months (2 m), 3 months (3 m), 6 months (6 m), 9 months (9 m), and 12 months (12 m) after medication started. The symptoms and the recovery of social function at different time points was analyzed, and correlation analysis and regression analysis were done to explore the influencing factors of functional recovery. Results: Among the 54 MDD patients, 27 completed the 12-month follow-up, and 2 patients relapsed at 12 m. The total baseline score of SDS (SDS 0) in MDD patients was higher than that in healthy controls ( t=12.161, P<0.001), and the baseline score of Q-LES-Q-SF (Q-LES-Q-SF 0) was lower than that in the controls ( t=12.260, P<0.001). Comparison of the HAMD score, SDS total score and the factor scores, and Q-LES-Q-SF total scores of the MDD patients at different time points showed significant differences, presenting an F value of 65.987, 28.944, 23.589, 27.070 and 28.668, respectively (all P<0.001). HAMD 0 was negatively correlated with age. The HAMD score was positively correlated with SDS score of the same time point and negatively correlated with Q-LES-Q-SF score of the same time point. At 3 m, the change in HAMD score (HAMD 3 m-0) was positively correlated with the change in SDS score (SDS 3 m-0) and negatively correlated with the change in Q-LES-Q-SF score (Q-LES-Q 3 m-0). At 12 m, the change in HAMD score (HAMD 12 m-0) was positively correlated with the change in SDS score (SDS 12 m-0) and negatively correlated with the change in Q-LES-Q-SF score (Q-LES-Q 12 m-0). Regression analysis revealed that SDS 0 and Q-LES-Q 0 could be used to predict SDS 3 m-0, R 2=0.391, while SDS 0 and full-time employment status could be used to predict SDS 12 m-0, R 2=0.640. Q-LES-Q 0 could be used to predict Q-LES-Q 3 m-0, R 2=0.294, while Q-LES-Q 0 and full-time employment status could be used to predict Q-LES-Q 12 m-0, R 2=0.591. Conclusion: Long-term regular medication can improve social dysfunction in patients with MDD and symptom relief is the basis for improvement of social function level and quality of life, while increasing employment saturability to some extent may help improve the long-term social function and quality of life.

Gray Matter Abnormalities in Patients with Chronic Primary Pain: A Coordinate-Based Meta-Analysis.

BACKGROUND: Many structural magnetic resonance imaging (MRI) studies have used voxel-based morphometry (VBM) to identify gray matter abnormalities in patients with chronic primary pain (CPP), but the findings have been inconsistent. OBJECTIVES: To identify (a) gray matter differences between CPP patients or female patients and healthy individuals and (b) the effects of symptom duration and pain scores on gray matter. STUDY DESIGN: We conducted a meta-analysis. METHODS: VBM studies in PubMed, Cochrane Library, and Google Scholar, from November 2005 to June 2020, were thoroughly collected and carefully reviewed. Manual searches were performed using title and citation information. Gray matter VBM study comparing adult patients (18-65 years) with CPP to healthy controls was reviewed, and results, presented in Talairach or Montreal Neurological Institute coordinates, were included. The t value, peak coordinates, and basic clinical information of each study were reported in detail. Anisotropic effect-size signed differential mapping was used for voxel-based meta-analyses. RESULTS: Patients with CPP had decreased gray matter in the left anterior cingulate (z value = 2.950, P < 0.001), right median cingulate (z value = 1.858, P = 0.001), and the insula bilaterally (left: z value = 2.441, P < 0.001; right: z value = 2.113, P < 0.001 ), and increased gray matter in the right striatum (z value = 1.194, P < 0.001). Subgroup meta-analysis showed female patients with CPP also had decreased gray matter in the left anterior cingulate gyrus (z value = 2.622, P < 0.001). Meta-regression analyses revealed that pain symptom duration was positively associated with a large right brain region (z value = 2.110, P < 0.001), a negative association between pain symptom duration and gray matter was found in the right anterior cingulate (z value = 1.969, P < 0.001) and right middle frontal gyrus (z value = 1.849, P < 0.001). LIMITATIONS: Due to the lack of data from male patients, we were unable to perform a male subgroup analysis; therefore, we cannot thoroughly explore the difference in CPP from the perspective of gender. CONCLUSION: We identified gray matter changes in CPP patients and female patients, as well as a close relationship between CPP and mental disorders. With the chronicity of pain leads to changes in relevant brain regions, which makes treatment more challenging and may have synergistic effects with affective disorders. More prospective longitudinal structural MRI studies of CPP examining the associations between those variables and gray matter in a larger population should be conducted. Additional prospective longitudinal structural MRI studies of CPP with larger sample sizes to confirm the relationships between these variables and gray matter are needed as well as gender differences of CPP in brain structure and function.

Transarterial chemoembolization vs. liver resection as initial treatment for hepatocellular carcinoma occurring exclusively in caudate lobe: A retrospective propensity matching analysis.

Treatment of hepatocellular carcinoma (HCC) in the caudate lobe is technically challenging. This retrospective study was designed to evaluate the clinical outcome of both superselective transcatheter arterial chemoembolization (TACE) and liver resection (LR) for HCC occurring exclusively in the caudate lobe. From January 2008 to September 2021, a total of 129 patients were diagnosed with HCC of the caudate lobe. The Cox proportional hazard model was used to analyze the potential clinical factors and established prognostic nomograms with interval validation. Of the total number of patients, 78 received TACE and 51 received LR. The overall survival (OS) rates (TACE vs. LR) at 1, 2, 3, 4, and 5 years were 83.9% vs. 71.0%; 74.2% vs. 61.3%; 58.1% vs. 48.4%; 45.2% vs. 45.2%; and 32.3% vs. 25.0%, respectively. However, subgroup analysis revealed that TACE was superior to LR for treating patients with stage IIb Chinese liver cancer (CNLC-IIb) in the entire cohort (p = 0.002). Interestingly, no difference was found between TACE and LR in the treatment outcomes of CNLC-IIa HCC (p = 0.6). Based on Child-Pugh A and B calculations, TACE tended to lead to a better OS than LR (p = 0.081 and 0.16, respectively). Multivariate analysis showed that Child-Pugh score, CNLC stage, ascites, alpha fetoprotein (AFP), tumor size, and anti-HCV are related to OS. Predictive nomograms for 1, 2, and 3 years were performed. Based on this study, TACE may provide a longer OS than liver resection for patients with CNLC-IIb HCC of the caudate lobe. Because this suggestion is limited by the study design and relatively small sample size, additional randomized controlled trials are needed.

The DRD2 Taq1A polymorphism moderates the effect of PTSD symptom severity on the left hippocampal CA3 volume: a pilot study.

RATIONALE AND OBJECTIVES: The hippocampus, especially the CA1, CA3, and dentate gyrus (DG) subfields, is reported to be associated with post-traumatic stress disorder (PTSD) after trauma. However, neuroimaging studies of the associations between PTSD and hippocampal subfield volumes have failed to yield consistent findings. The aim of this study is to examine whether the dopamine D2 receptor (DRD2) Taq1A polymorphism, which is associated with both hippocampal function and PTSD, moderated the association between PTSD severity and hippocampal CA1, CA3 and DG volumes. METHODS: T1-weighted images were acquired from 142 trauma survivors from the 2008 Wenchuan earthquake using a 3.0-T magnetic resonance imaging system. Hippocampal subfield segmentations were performed with FreeSurfer v6.0. We used the simple moderation model from the PROCESS v3.4 tool for SPSS 23.0 to examine the association between the rs1800497 polymorphism, PTSD severity, and hippocampal CA3 and DG volumes. RESULTS: A significant genotype × PTSD symptom severity interaction was found for the left CA3 volume (ΔF = 5.01, p = 0.008, ΔR2 = 0.05). Post hoc, exploratory analyses deconstructing the interaction revealed that severe PTSD symptomatology were associated with reduced left CA3 volume among TC heterozygotes (t = - 2.86, p = 0.005). CONCLUSIONS: This study suggests that DRD2 Taq1A polymorphism moderates the association between PTSD symptomatology and left CA3 volume, which promotes an etiological understanding of the hippocampal atrophy at the subfield level. This highlights the complex effect of environmental stress, and provides possible mechanism for the relationship between the dopaminergic system and hippocampal function in PTSD.

Dysfunction of Resting-State Functional Connectivity of Amygdala Subregions in Drug-Naïve Patients With Generalized Anxiety Disorder.

Objective: Although previous studies have reported on disrupted amygdala subregional functional connectivity in generalized anxiety disorder (GAD), most of these studies were conducted in GAD patients with comorbidities or with drug treatment. Besides, whether/how the amygdala subregional functional networks were associated with state and trait anxiety is still largely unknown. Methods: Resting-state functional connectivity of amygdala subregions, including basolateral amygdala (BLA) and centromedial amygdala (CMA) as seed, were mapped and compared between 37 drug-naïve, non-comorbidity GAD patients and 31 age- and sex-matched healthy controls (HCs). Relationships between amygdala subregional network dysfunctions and state/trait anxiety were examined using partial correlation analyses. Results: Relative to HCs, GAD patients showed weaker functional connectivity of the left BLA with anterior cingulate/medial prefrontal cortices. Significantly increased functional connectivity of right BLA and CMA with superior temporal gyrus and insula were also identified in GAD patients. Furthermore, these functional connectivities showed correlations with state and trait anxiety scores. Conclusions: These findings revealed abnormal functional coupling of amygdala subregions in GAD patients with regions involved in fear processing and emotion regulation, including anterior cingulate/medial prefrontal cortex and superior temporal gyrus, which provide the unique biological markers for GAD and facilitating the future accurate clinical diagnosis and target treatment.

Supplementation of Kiwifruit Polyphenol Extract Attenuates High Fat Diet Induced Intestinal Barrier Damage and Inflammation via Reshaping Gut Microbiome.

Background: Impaired intestinal integrity and barrier function is associated with various diseases, including inflammatory bowel disease and metabolic syndrome. In recent years, plant-derived polyphenols have attracted much attention on regulating intestinal barrier function. Kiwifruit was recorded as a traditional Chinese medicine which can treat gastrointestinal diseases, but the mechanism was still unclear. In this study we investigated the effects of kiwifruit polyphenol extracts (KPE) on high fat diet induced intestinal permeability and its possible mechanism. Results: Dietary supplementation of KPE with 50 or 100 mg/kg bw could inhibit the increase of intestinal permeability caused by HFD and promote the expression of tight junction protein (Claudin-1, Occludin and ZO-1). From microbial diversity and RT-PCR, KPE administration reshaping gut microbiome, the relative abundance of Lactobacillus and Bifidobacterium were increased, and the relative abundance of Clostridium and Desulfovibrionaceae were decreased. The changes in microbe may influence intestinal inflammatory status. Then the expression of TLRs and cytokines were detected. KPE supplementation showed anti-inflammatory effect, the expression of IL-10 was increased and the expression of TLR-2, TLR-4, TNF-α and IL-1ß were decreased. Correlation analysis indicated that the expression of tight junction protein was negative correlation with TLR-2, TLR-4, TNF-α and IL-1ß expression, but positively correlated with Bacteroidete, Bifidobacterium and IL-10 expression; the expression of Bacteroidete, Lactobacillusand and Bifidobacterium were negative correlation with TLR4, TNF-α, and IL-1ß expression. Conclusion: KPE treatment relieve the intestinal damage caused by HFD, which was related to the regulation of Bacteroidete, Lactobacillusand, and Bifidobacterium expression and inhibit intestinal inflammation. KPE could be a functional component for preventing gut damage and its related disease.