Severity and Vaccine Effectiveness in Patients With the Omicron Variant of COVID-19 in Suzhou: A Retrospective Single-Center Study.

Background The Omicron variant of the coronavirus disease 2019 (COVID-19) virus has spread rapidly worldwide, even in areas with high vaccination rates. Consequently, it has further exacerbated the current global pandemic. In this study, we aimed to characterize the clinical severity of patients with the COVID-19 variant Omicron and analyze vaccine effectiveness in predicting clinical severity. Methodology A total of 142 patients who contracted the COVID-19 virus in the Omicron era were retrospectively studied, and differences in their clinical severity were analyzed. They were stratified as follows: unvaccinated vs. vaccinated, unvaccinated vs. one to two vaccine doses vs. three vaccine doses, and cycle threshold (CT) values ≤ 28 vs. CT > 28. Results Of the 142 patients, 27 were asymptomatic, 83 had mild disease, and 32 had moderate disease. The median age was 32 years for asymptomatic patients vs. 31 years for those with mild disease vs. 59 years for those with moderate disease (P＜0.05), and the direct medical hospitalization costs were ¥4901 for asymptomatic patients vs. ¥5259 for those with mild disease vs. ¥8378 for those with moderate disease (P＜0.05). Of the 142 patients, 112 (78.8%) were vaccinated, 11 (7.7%) had one vaccine dose, 63 (44.4%) had two vaccine doses, and 38 (26.7%) received three vaccine doses. The median direct medical cost in the vaccinated group was significantly lower than that in the unvaccinated group (¥5470.5 vs. ¥7535.5, P＜0.05). For ORF1ab and N genes, hospital stay length and direct medical cost significantly decreased in the group with CT values > 28 compared with those in the group with CT values ≤ 28 (P＜0.05). Multiple regression analysis showed that being ≥ 60 years old could be a predictor of moderate disease severity in patients, and three vaccine doses could be effective against moderate COVID-19. Conclusion Mild infection is the main clinical manifestation of the Omicron variant. Vaccination can significantly decrease direct Omicron-associated medical costs. Although vaccination cannot provide protection against severe disease caused by this variant, three vaccine doses are highly effective in preventing moderate COVID-19.

A systematic review of interpersonal psychotherapy for postpartum depression.

BACKGROUND: The current study endeavored to systematically integrate and quantitatively evaluate the effectiveness of interpersonal psychological interventions for postpartum depression patients. METHODS: Four electronic databases Pubmed, Embase, Cochrane and Web of Science were employed for literature retrieval, and the search time was from the inception of the database to May 30, 2022. Literature screening and data extraction were performed independently by two researchers. RESULTS: A total of 528 studies were screened, and 9 of them were finally included. There were 1012 subjects, 518 of them were assigned in experimental group and 494 in control. Evidence from interpersonal psychological interventions indicated that the data on postpartum depression, satisfaction with family, and social support in both groups after intervention included: depression score [MD = -2.80, 95%CI (-3.86 to -1.74), P < 0.05], satisfaction score [MD = 8.41, 95%CI (1.49 to -15.33), P < 0.05], and social support score [MD = 1.83, 95%CI (-2.10 to -5.76)] of postpartum depression patients. P values < 0.05 indicated substantial improvement as compared to control. LIMITATIONS: During the research process, it is impossible for the experimental group and the researchers to use double-blind trials simultaneously, which may present a Hawthorne effect, but this can be avoided by general psychological intervention for the control. CONCLUSIONS: Interpersonal psychotherapy could improve depression in patients with postpartum depression, but the appropriate intervention time was between 4 and 8 weeks, and it also improved satisfaction with family of patients, and the longer the intervention, the higher the satisfaction with the family.

The trends of psychosomatic symptoms and perceived stress among healthcare workers during the COVID-19 pandemic in China: Four cross-sectional nationwide surveys, 2020-2023.

An unseen wave of vast infection was detected in China in December 2022, and healthcare workers faced inevitable challenges and heavy stress. We aimed to present a dynamic mental health map and, most importantly, provide a timely report of the current situation in healthcare workers. The current study conducted four national cross-sectional online surveys from February and March 2020, Apr 2022, and Jan 2023. The Psychosomatic Symptom Scale (PSSS) and Perceived Stress Scale-10 (PSS-10) were used to assess psychosomatic symptoms and perceived stress. Fourteen thousand nine hundred forty-five participants (8578 healthcare workers and 6367 others) participated in the surveys. The prevalence of psychosomatic syndrome, reflected by PSSS, was 19.3% (Wave1), 22.9% (Wave2), 36.4% (Wave3), and 60.7% (Wave4) among healthcare workers, compared to 24.0% (Wave1), 35.7% (Wave2), 34.2% (Wave3) and 50.5% (Wave4) among the others. In addition, healthcare workers exhibited lower PSSS total scores at the beginning but higher in later waves. Despite their infection status, they now suffer from more severe psychosomatic symptoms than the rest of society. Our findings suggest that healthcare workers in China have now experienced severe psychosomatic symptoms and tremendous stress. Therefore, there is an urgent need to utilize social support for them.

The dynamic changes of psychosomatic symptoms in three waves of COVID-19 outbreak and fatigue caused by enduring pandemic in China.

BACKGROUND: Two years have passed since the 2019 novel coronavirus disease (COVID-19) was first reported. The persistent pandemic might lead to severe psychosomatic problems and fatigue. In addition, the recent rapid rising COVID-19 cases in China have become a trending issue. Therefore, this study aimed to investigate the dynamic changes in psychosomatic problems at the initial and current stages of the pandemic. METHODS: Three waves of cross-sectional online survey were conducted during the initial COVID outbreak in China. The psychosomatic symptom scale (PSSS), perceived stress scale (PSS), and pandemic fatigue scale (PFS) were used to assess the psychosomatic problems, stress, and fatigue. RESULTS: 4317, 1096, and 2172 participants completed the first, second, and third surveys. The prevalence of psychosomatic disorder was 22 %, 28 %, and 39 %, respectively. The network structure of PSSS symptoms has not significantly changed as the pandemic progresses. However, the global strength of the PSSS networks, indicating the overall connectivity, in the third wave was significantly higher than in the first wave (s = 0.54, P = 0.007). The most central symptoms in the first and third wave networks were depressed mood and tiredness. The PFS score was higher in the people concerned with indirect impact than those concerned with health (P < 0.001). PFS has positive relationships with PSSS and PSS score (R = 0.41, P < 0.001 and R = 0.35, P < 0.001, respectively). CONCLUSIONS: The persistence of the pandemic caused critical psychosomatic issues, stress, and indirect burden over time, leading to inevitable fatigue. People endured needing immediate attention to prevent or reduce psychosomatic disorders.

Predicting the diagnosis of various mental disorders in a mixed cohort using blood-based multi-protein model: a machine learning approach.

The lack of objective diagnostic methods for mental disorders challenges the reliability of diagnosis. The study aimed to develop an easily accessible and useable objective method for diagnosing major depressive disorder (MDD), schizophrenia (SZ), bipolar disorder (BPD), and panic disorder (PD) using serum multi-protein. Serum levels of brain-derived neurotrophic factor (BDNF), VGF (non-acronymic), bicaudal C homolog 1 (BICC1), C-reactive protein (CRP), and cortisol, which are generally recognized to be involved in different pathogenesis of various mental disorders, were measured in patients with MDD (n = 50), SZ (n = 50), BPD (n = 55), and PD along with 50 healthy controls (HC). Linear discriminant analysis (LDA) was employed to construct a multi-classification model to classify these mental disorders. Both leave-one-out cross-validation (LOOCV) and fivefold cross-validation were applied to validate the accuracy and stability of the LDA model. All five serum proteins were included in the LDA model, and it was found to display a high overall accuracy of 96.9% when classifying MDD, SZ, BPD, PD, and HC groups. Multi-classification accuracy of the LDA model for LOOCV and fivefold cross-validation (within-study replication) reached 96.9 and 96.5%, respectively, demonstrating the feasibility of the blood-based multi-protein LDA model for classifying common mental disorders in a mixed cohort. The results suggest that combining multiple proteins associated with different pathogeneses of mental disorders using LDA may be a novel and relatively objective method for classifying mental disorders. Clinicians should consider combining multiple serum proteins to diagnose mental disorders objectively.

Internet-based cognitive behavioural therapy combined with attentional bias modification training in generalized anxiety disorder: a randomized, controlled multi-session experiment.

BACKGROUND: Although attentional bias modification training (ABM) and cognitive behavioural therapy (CBT) are two effective methods to decrease the symptoms of generalized anxiety disorders (GAD), to date, no randomized controlled trials have yet evaluated the effectiveness of an intervention combining internet-based cognitive behavioural therapy (ICBT) and ABM for adults with GAD. AIMS: This study aimed to investigate the effectiveness of an intervention combining ICBT and ABM for adults with GAD. METHOD: Sixty-three participants diagnosed with GAD were randomly assigned to the treatment group (ICBT with ABM; 31 participants) or the control group (ICBT with ABM placebo; 32 participants), and received 8 weeks of treatment and three evaluations. The CBT, ABM and ABM-placebo training were conducted via the internet. The evaluations were conducted at baseline, 8 weeks later, and 1 month later, respectively. RESULTS: Both the treatment and control groups reported significantly reduced anxiety symptoms and attentional bias, with no clear superiority of either intervention. However, the treatment group showed a greater reduction in negative automatic thoughts than the control group after treatment and at 1-month follow-up (η2 = 0.123). CONCLUSION: The results suggest that although not differing in therapeutic efficacy, the intervention combining ICBT and ABM is superior to the intervention combining ICBT and ABM-placebo in the reduction of negative automatic thoughts. ABM may be a useful augmentation of ICBT on reducing anxiety symptoms.

Adiponectin. rs266729 Polymorphism and Nicotine Dependence Interaction: Genetic Investigations on the Anxiety Susceptibility.

BACKGROUND AND AIMS: Nicotine dependence (ND)-induced anxiety might be modulated by genetic polymorphisms. The gene-by-environment interaction can be fitted into the diathesis-stress and differential susceptibility models. Nevertheless, knowledge of the interaction between adiponectin (ADPN) polymorphisms and ND on the incident mental disorder is currently scarce. This study aims to understand the role of ADPN rs266729 on anxiety in patients with ND while elucidating the psychology model and the various reactions across genotypes. METHODS: We included 315 Chinese males with confirmed ND, measured using the Fagerstrom test for nicotine dependence (FTND). Anxiety was assessed using the Self-rating Anxiety Scale. Genomic DNA was extracted and genotyped from peripheral blood. Hierarchical regression models were used to test the interactions. RESULTS: There was a significant interaction between ADPN rs266729 and ND (ß = -0.19, p < 0.05). The CC homozygote was more likely to be affected by ND-induced anxiety (ß = 0.14, t = 4.43, p < 0.01). Re-parameterized regression models revealed that the interaction between ADPN rs266729 and ND could fit the strong differential susceptibility model (R2 = 0.05, p < 0.001). CONCLUSIONS: ADPN rs266729 was correlated with susceptibility to anxiety symptoms among male adults with ND and could fit the differential susceptibility model. The CC homozygote of rs266729 was a plasticity factor that increased anxiety symptoms in individuals with ND.

Case report: Cases of narcolepsy misdiagnosed as other psychiatric disorders.

Narcolepsy is characterized by uncontrollable excessive daytime sleepiness, paroxysmal cataplexy, sleep paralysis, and hallucinations. It is often misdiagnosed as psychiatric disorders such as depression and schizophrenia, resulting from the overlap in symptoms and a lack of understanding of narcolepsy. In the present study, three cases of narcolepsy misdiagnosed as depression, dissociative disorder, and schizophrenia are presented to emphasize the high occurrence of the misdiagnosis of narcolepsy in clinical practice. The main reasons for this dilemma are attributed to the lack of adequate sleep, medicine, education, as well as specialized professional technicians. A multi-disciplinary team composed of psychiatrists and sleep specialists should be established to deal with this problem.

Development and validation of a nomogram based on lymphocyte subsets to distinguish bipolar depression from major depressive disorder.

Objective: Bipolar depression (BD) and major depressive disorder (MDD) are both common affective disorders. The common depression episodes make it difficult to distinguish between them, even for experienced clinicians. Failure to properly diagnose them in a timely manner leads to inappropriate treatment strategies. Therefore, it is important to distinguish between BD and MDD. The aim of this study was to develop and validate a nomogram model that distinguishes BD from MDD based on the characteristics of lymphocyte subsets. Materials and methods: A prospective cross-sectional study was performed. Blood samples were obtained from participants who met the inclusion criteria. The least absolute shrinkage and selection operator (LASSO) regression model was used for factor selection. A differential diagnosis nomogram for BD and MDD was developed using multivariable logistic regression and the area under the curve (AUC) with 95% confidence interval (CI) was calculated, as well as the internal validation using a bootstrap algorithm with 1,000 repetitions. Calibration curve and decision curve analysis (DCA) were used to evaluate the calibration and clinical utility of the nomogram, respectively. Results: A total of 166 participants who were diagnosed with BD (83 cases) or MDD (83 cases), as well as 101 healthy controls (HCs) between June 2018 and January 2022 were enrolled in this study. CD19+ B cells, CD3+ T cells, CD3-CD16/56+ NK cells, and total lymphocyte counts were strong predictors of the diagnosis of BD and MDD and were included in the differential diagnosis nomogram. The AUC of the nomogram and internal validation were 0.922 (95%; CI, 0.879-0.965), and 0.911 (95% CI, 0.838-0.844), respectively. The calibration curve used to discriminate BD from MDD showed optimal agreement between the nomogram and the actual diagnosis. The results of DCA showed that the net clinical benefit was significant. Conclusion: This is an easy-to-use, repeatable, and economical nomogram for differential diagnosis that can help clinicians in the individual diagnosis of BD and MDD patients, reduce the risk of misdiagnosis, facilitate the formulation of appropriate treatment strategies and intervention plans.

ERK1/2-dependent BDNF synthesis and signaling is required for the antidepressant effect of microglia stimulation.

Depressed mice have lower numbers of microglia in the dentate gyrus (DG). Reversal of this decline by a single low dose of lipopolysaccharide (LPS) may have antidepressant effects, but there is little information on the molecular mechanisms underlying this effect. It is known that impairment of brain-derived neurotrophic factor (BDNF) signaling is involved in the development of depression. Here, we used a combination of neutralizing antibodies, mutant mice, and pharmacological approaches to test the role of BDNF-tyrosine kinase receptor B (TrkB) signaling in the DG in the effect of microglial stimulation. Our results suggest that inhibition of BDNF signaling by infusion of an anti-BDNF antibody, the BDNF receptor antagonist K252a, or knock-in of the mutant BDNF Val68Met allele abolished the antidepressant effect of LPS in chronically stressed mice. Increased BDNF synthesis in DG, mediated by extracellular signal-regulated kinase1/2 (ERK1/2) signaling but not protein kinase B (Akt)-mammalian target of rapamycin (mTOR) signaling, was essential for the antidepressant effect of microglial stimulation. These results suggest that increased BDNF synthesis through activation of ERK1/2 caused by a single LPS injection and subsequent TrkB signaling are required for the antidepressant effect of hippocampal microglial stimulation.

Aberrated Multidimensional EEG Characteristics in Patients with Generalized Anxiety Disorder: A Machine-Learning Based Analysis Framework.

Although increasing evidences support the notion that psychiatric disorders are associated with abnormal communication between brain regions, scattered studies have investigated brain electrophysiological disconnectivity of patients with generalized anxiety disorder (GAD). To this end, this study intends to develop an analysis framework for automatic GAD detection through incorporating multidimensional EEG feature extraction and machine learning techniques. Specifically, resting-state EEG signals with a duration of 10 min were obtained from 45 patients with GAD and 36 healthy controls (HC). Then, an analysis framework of multidimensional EEG characteristics (including univariate power spectral density (PSD) and fuzzy entropy (FE), and multivariate functional connectivity (FC), which can decode the EEG information from three different dimensions) were introduced for extracting aberrated multidimensional EEG features via statistical inter-group comparisons. These aberrated features were subsequently fused and fed into three previously validated machine learning methods to evaluate classification performance for automatic patient detection. We showed that patients exhibited a significant increase in beta rhythm and decrease in alpha1 rhythm of PSD, together with the reduced long-range FC between frontal and other brain areas in all frequency bands. Moreover, these aberrated features contributed to a very good classification performance with 97.83 ± 0.40% of accuracy, 97.55 ± 0.31% of sensitivity, 97.78 ± 0.36% of specificity, and 97.95 ± 0.17% of F1. These findings corroborate previous hypothesis of disconnectivity in psychiatric disorders and further shed light on distribution patterns of aberrant spatio-spectral EEG characteristics, which may lead to potential application of automatic diagnosis of GAD.

Combining S100B and Cytokines as Neuro-Inflammatory Biomarkers for Diagnosing Generalized Anxiety Disorder: A Proof-of-Concept Study Based on Machine Learning.

Introduction: S100 calcium-binding protein B (S100B) is a neurotrophic factor that regulates neuronal growth and plasticity by activating astrocytes and microglia through the production of cytokines involved in Generalized Anxiety Disorder (GAD). However, few studies have combined S100B and cytokines to explore their role as neuro-inflammatory biomarkers in GAD. Methods: Serum S100B and cytokines (IL-1ß, IL-2, IL-4, and IL-10) of 108 untreated GAD cases and 123 healthy controls (HC) were determined by enzyme-linked immunosorbent assay (ELISA), while Hamilton Anxiety Rating Scale (HAMA) scores and Hamilton Depression Rating Scale (HAMD) scores were measured to evaluate anxiety and depression severity. This was used to help physicians identify persons having GAD. Machine learning techniques were applied for feature ordering of cytokines and S100B and the classification of persons with GAD and HC. Results: The serum S100B, IL-1ß, and IL-2 levels of GAD cases were significantly lower than HC (P < 0.001), and the IL-4 level in persons with GAD was significantly higher than HC (P < 0.001). At the same time, IL-10 had no significant difference between the two groups (P = 0.215). The feature ranking distinguishing GAD from HC using machine learning ranked the features in the following order: IL-2, IL-1ß, IL-4, S100B, and IL-10. The accuracy of S100B combined with IL-1ß, IL-2, IL-4, and IL-10 in distinguishing persons with GAD from HC was 94.47 ± 2.06% using an integrated back propagation neural network based on a bagging algorithm (BPNN-Bagging). Conclusion: The serum S-100B, IL-1ß, and IL-2 levels in persons with GAD were down-regulated while IL-4 was up-regulated. The combination of S100B and cytokines had a good diagnosis value in determining GAD with an accuracy of 94.47%. Machine learning was a very effective method to study neuro-inflammatory biomarkers interacting with each other and mediated by plenty of factors.

Correlates of Adherence of Multimodal Non-pharmacological Interventions in Older Adults With Mild Cognitive Impairment: A Cross-Sectional Study.

Background: Non-pharmacological interventions are promising for delaying cognitive decline in older adults with mild cognitive impairment (MCI). Although some studies have demonstrated adherence rates and factors influencing participation in single modality non-pharmacological interventions, little is known about the level and correlates of adherence to multimodal non-pharmacological interventions (MNPIs) in older adults with MCI. Objective: This study aimed to explore the adherence level and the correlates of adherence to MNPIs in older adults with MCI. Methods: A cross-sectional design was employed. Community-dwelling older adults aged 60 years and over were recruited from senior community centers and healthcare centers in Huzhou from March 2019 to December 2020. Data were collected by a general information questionnaire and the adherence scale of cognitive dysfunction management (AS-CDM) in older adults with MCI. Hierarchical regression analyses were applied to explore the correlates of adherence to MNPIs. Results: A total of 216 completed questionnaires were finally analyzed. Of these, 68.52% were female, and 45.4% of the participants had no less than 6 years of education. The overall mean score for adherence was 117.58 (SD = 10.51) out of 160, equivalent to 73.49 in the hundred-mark system, indicating a medium-level adherence to MNPIs in older adults with MCI. Of the five dimensions of adherence (AS-CDM), self-efficacy scored the highest, and the lowest was perceived barriers. The univariate analysis showed that the factors associated with the adherence to MNPIs were: regular physical exercise, meat-vegetable balance, absence of multimorbidity, high level of education, living alone, and living in urban (p < 0.05). In the hierarchical regression analysis, the final model explained 18.8% of variance in overall adherence (p < 0.01), which high school (Beta = 0.161, p < 0.05), college and above more (Beta = 0.171, p < 0.05), meat-vegetarian balance (Beta = 0.228, p < 0.05), regular physical exercise (Beta = 0.234, p < 0.05), and presence of multimorbidity (Beta = -0.128, p < 0.05) significantly contributed to adherence. In addition, nearly 80% of older adults with MCI preferred MNPIs. Conclusion: Early assessment and management of adherence to MNPIs were essential in older adults with MCI. Furthermore, the findings shed light on several critical areas of intervention to improve adherence to MNPIs in older adults with MCI. Clinical Trial Registration: http://www.chictr.org.cn/showproj.aspx?proj=35363, ChiCTR1900020950 (Registered on January 23, 2019).

Methodology of Measuring Motoric Cognitive Risk Syndrome-Focusing on Slow Gait Speed: Protocol for a Systematic Review.

Introduction: Older adults with motoric cognitive risk (MCR) syndrome are at high risk of developing dementia. Although the definition of MCR is well recognized and consensus, previous studies did not reach an agreement on diagnostic criteria and measurement methods/tools for slow gait speed, which is one of four components of MCR diagnosis. The substantial heterogeneity in the methodology of slow gait speed diagnosis for MCR limits comparability and meta-analysis of studies. Objective: The study aims to conduct systematic and standardized integration for diagnostic criteria and methods of slow gait speed diagnosis for MCR based on previous evidence that may improve comparability between future studies. Methods: A systematic literature review will be undertaken by searching the following electronic databases (until February 1, 2022): PUBMED, EMBASE, The Cochrane Library, Web of Science. Additional studies will be identified by checking the reference lists of included studies or relevant reviews, manually searching the internet search engine Google Scholar, and searching the authors' personal files, if necessary. Two researchers will perform data extraction independently, and discrepancies will be resolved by discussion, which will include a third researcher if requires. The paper selection will perform in duplicate. Finally, a narrative account will synthesize the findings to answer the objectives of this review. Discussion: This is the first study on systematic and standardized integration for diagnostic criteria and measurement methods/tools for slow gait speed in diagnosing MCR. The findings of this study will be convenient for medical staff to examine the intended use and applicability of each instrument/tool for evaluating the gait speed, and provide insight into developing uniform guidelines for MCR. Systematic Review Registration: PROSPERO registration number: CRD42021232671.

Higher baseline serum adiponectin predicts better treatment remission in patients with generalized anxiety disorder treated with escitalopram.

BACKGROUND: Generalized anxiety disorder (GAD) is partly attibuted to the dysregulation of nuero-inflammation which can be mediated by adiponectin. We conducted this study was to explore the characteristics of peripheral adiponectin and its role in predicting treatment outcome in patients with generalized anxiety disorder (GAD) treated by escitalopram or venlafaxine. METHODS: A total of 70 untreated GAD inpatients who met the diagnosis criteria of the Diagnostic and Statistical Manual of Mental Disorders IV (DSM-IV) were enrolled and randomly selected for treatment with escitalopram (n=36) or venlafaxine (n=34) for 8 weeks. The serum adiponectin level of GAD and healthy controls (HCs) was measured by enzyme-linked immunosorbent assay (ELISA) before treatment. Hamilton Anxiety Rating Scale (HAM-A) assessment was conducted at baseline and at 1, 2, 4, and 8 weeks after treatment respectively. Serum adiponectin levels were compared between GAD patients and HCs, as well as between remission and nonremission cases; the correlation between baseline adiponectin level and HAM-A reduction rate were also analyzed. RESULTS: The serum adiponectin levels were higher in GAD patients compared to HCs (t=2.304; P=0.023), the serum adiponectin levels were higher in remission cases compared to nonremission cases (t=2.255, P=0.027), and the receiver operating characteristic (ROC) area in predicting treatment remission was 0.652±0.066 (P=0.029). The correlation between baseline adiponectin level and HAM-A reduction rate of GAD cases treated with escitalopram and venlafaxine in the endpoint was 0.362 (P=0.030) and -0.026 (P=0.883), respectively, and the ROC area of baseline adiponectin level in predicting treatment remission was 0.72±0.086 (P=0.024) and 0.473±0.102 (P=0.469), respectively. CONCLUSIONS: Peripheral adiponectin is upregulated in GAD, and it seems higher baseline adiponectin level predicts a better treatment remission treated by escitalopram but not with venlafaxine, which suggests adiponectin maybe a potential key biomarker in Chinese GAD.

The effects of a multi-disciplinary team on sleep quality assessment in mild-to-moderate Alzheimer's disease patients with sleep disorders.

BACKGROUND AND AIMS: Sleep disturbances are a severe problem among patients with Alzheimer's disease (AD). By evaluating sleep quality in mild-to-moderate AD patients, this study aimed to assess the effects of multi-disciplinary team (MDT) in reducing the incidence of adverse reactions of AD patients. The reduction in the incidence of adverse reactions to predict multi-disciplinary team (MDT) treatment effects. METHODS AND RESULTS: This study included 60 mild-to-moderate AD patients with sleep problems when hospitalized in Huzhou Third Municipal Hospital. The patients were randomly distributed into two groups, routine and MDT treatments. The cognitive functions, sleep conditions, and psycho-behavioral symptoms were compared between both the groups. Cognitive function declined significantly between pretherapy and follow-up in the routine treatment group (MMSE: t = -7.961, P < 0.001; MoCA: t = -4.672, P < 0.001). There was a significant decline in drowsiness in the MDT group compared to that in the routine treatment group (χ2 = 4.320, P = 0.038). Sleep quality improved significantly during the follow-up in the MDT treatment group (t = 6.098, P < 0.001). The results of the Hamilton Depression Scale (HAMD) and Hamilton Anxiety Scale (HAMA) among family caregivers (FCGs) demonstrated that MDT treatment could alleviate caregivers' depression (t = -2.867, P = 0.042), and routine treatment can worsen their anxiety (t = 3.258, P = 0.003). CONCLUSION: The MDT treatment method as an effective and meaningful therapy can help mitigate the suffering of patients with AD and FCGs.

Tolerance-inducing effect and properties of innate immune stimulation on chronic stress-induced behavioral abnormalities in mice.

Over-activation of the innate immune system constitutes a risk factor for the development of nervous system disorders but may reduce the severity of these disorders by inducing tolerance effect. Here, we studied the tolerance-inducing effect and properties of innate immune stimulation on chronic social defeat stress (CSDS)-induced behavioral abnormalities in mice. A single injection of the innate immune enhancer lipopolysaccharide (LPS) one day before stress exposure prevented CSDS-induced impairment in social interaction and increased immobility time in the tail suspension test and forced swimming test. This effect was observed at varying doses (100, 500, and 1000 µg/kg) and peaked at 100 µg/kg. A single LPS injection (100 µg/kg) either one or five but not ten days before stress exposure prevented CSDS-induced behavioral abnormalities. A second LPS injection ten days after the first LPS injection, or a 2 × or 4 × LPS injections ten days before stress exposure also induced tolerance against stress-induced behavioral abnormalities. Our results furthermore showed that a single LPS injection one day before stress exposure skewed the neuroinflammatory response in the hippocampus and prefrontal cortex of CSDS-exposed mice toward an anti-inflammatory phenotype. Inhibiting the central innate immune response by pretreatment with minocycline or PLX3397 abrogated the tolerance-inducing effect of LPS preconditioning on CSDS-induced behavioral abnormalities and neuroinflammatory responses in the brain. These results provide evidence for a prophylactic effect of innate immune stimulation on stress-induced behavioral abnormalities via changes in microglial activation, which may help develop novel strategies for the prevention of stress-induced psychological disorders.

Aberrant amplitude low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) in generalized anxiety disorder (GAD) and their roles in predicting treatment remission.

BACKGROUND: Generalized anxiety disorder (GAD) is a common affective disorder characterized by comprehensive anxiety with dysregulation of brain activity which can be reflected by functional magnetic resonance imaging (f-MRI). We aimed to examine abnormal aberrant amplitude low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) in GAD and evaluate their ability to predict treatment remission. METHODS: Using resting-state fMRI (Rs-fMRI), we examined ALFF and ReHo in 30 GAD patients and 30 healthy control (HC) participants. Using on DEPASF4.3 Advanced Edition, voxel-based two-sample t-test analysis was performed on the ALFF and ReHo maps to compare GAD to HC groups, and to compare remitters (n=9) and non-remitters (n=21). Pearson's correlation analysis was used to explore the relationship between baseline Hamilton Anxiety Rating Scale (HAM-A) scores/illness duration and mean ALFF/ReHo values. The severity of GAD symptoms was rated with HAM-A. Remission was defined as HAM-A ≤7 by week 8. RESULTS: Compared to the HC group, GAD patients showed lower ALFF in the right postcentral and right precentral gyrus; lower ReHo in the right precentral, right postcentral, and left precentral gyrus; and higher ReHo in the left posterior cingulate cortex. ALFF values for left postcentral gyrus was negatively correlated with baseline HAM-A, while that of the middle frontal gyrus was positively correlated with baseline HAM-A scores. ReHo value of the left postcentral gyrus was negatively correlated with baseline HAM-A, while that of the right middle frontal gyrus was positively correlated with baseline HAM-A scores. ALFF of the right frontal_superior_orbital and right frontal-medial-orbital cortex was positively correlated with illness duration. ReHo of the left supplementary motor area cortex was negatively correlated with illness duration. Remitters showed higher ALFF in the left hippocampus and higher ReHo value in the right postcentral cortex compared to nonremitters. CONCLUSIONS: These results suggest that altered regional brain activity and local synchronization may be related to the pathophysiology of GAD and have certain value in predicting remission in treatment.

Can virtual reality improve traditional anatomy education programmes? A mixed-methods study on the use of a 3D skull model.

BACKGROUND: Realistic, portable, and scalable lectures, cadaveric models, 2D atlases and computer simulations are being combined more frequently for teaching anatomy, which result in major increases in user satisfaction. However, although digital simulations may be more portable, interesting, or motivating than traditional teaching tools, whether they are superior in terms of student learning remain unclear. This paper presents a study in which the educational effectiveness of a virtual reality (VR) skull model is compared with that of cadaveric skulls and atlases. The aim of this study was to compare the results of teaching with VR to results of teaching with traditional teaching methods by administering objective questionnaires and perception surveys. METHODS: A mixed-methods study with 73 medical students was conducted with three different groups, namely, the VR group (N = 25), cadaver group (N = 25) and atlas group (N = 23). Anatomical structures were taught through an introductory lecture and model-based learning. All students completed the pre- and post-intervention tests, which comprised a theory test and an identification test. The theory test consisted of 18 multiple-choice questions, and the identification test consisted of 25 fill-in-the-blank questions. RESULTS: The participants in all three groups had significantly higher total scores on the post-intervention test than on the pre-intervention test; the post-intervention test score in the VR group was not statistically significantly higher than the post-intervention test score of the other groups (VR: 30 [IQR: 22-33.5], cadaver: 26 [IQR: 20-31.5], atlas: 28[IQR: 20-33]; p > 0.05). The participants in the VR and cadaver groups provided more positive feedback on their learning models than the atlas group (VR: 26 [IQR: 19-30], cadaver: 25 [IQR: 19.5-29.5], atlas: 12 [IQR: 9-20]; p < 0.001). CONCLUSIONS: The skull virtual learning resource (VLR) was equally efficient as the cadaver skull and atlas in teaching anatomy structures. Such a model can aid individuals in understanding complex anatomical structures with a higher level of motivation and tolerable adverse effects.

The association of catechol-O-methyltransferase (COMT) rs4680 polymorphisms and generalized anxiety disorder in the Chinese Han population.

The catechol-O-methyltransferase (COMT) Val158Met polymorphism has been reported to be implicated in generalized anxiety disorder (GAD) as well as the treatment response to antidepressants in patients with GAD, but the findings are inconsistent. In this study, we explore the association among COMT, GAD, and the antidepressant response in the Chinese Han population. One hundred and two patients with GAD and 120 healthy controls (HC) were recruited. All the patients were treated with escitalopram or venlafaxine for 8 weeks. The Hamilton Rating Scale for Anxiety (HAMA) was used to assess the treatment response. All the participants were genotyped for the COMT Val158Met polymorphism using the polymerase chain reaction method. No significant differences in the frequency of the COMT rs4680 polymorphism were found between the GAD and HC groups, or between patients with different genders. Further, we found no significant correlation between the COMT rs4680 polymorphism, gender, and the antidepressant treatment outcomes after eight weeks in the GAD patients. This study indicated that the COMT rs4680 genotype might not be related to GAD or to the genders of the GAD patients, nor did it have any effect on the antidepressant therapeutic response in the GAD patients. Even so, our research will be helpful by providing guidance and direction for future, more in depth, research.