Associations of obesity with chronic inflammatory airway diseases and mortality in adults: a population-based investigation.

BACKGROUND: The association between obesity and respiratory diseases has been confirmed. However, few studies have reported the relationship between obesity and the risk and mortality of chronic inflammatory airway disease (CIAD). The aim of this study was to reveal the association between obesity and the risk of CIAD, and mortality in patients with CIAD. METHODS: The study was conducted using data from the National Health and Nutrition Examination Survey (NHANES) 2013 to 2018 among adults aged 20 years and above. All participants were grouped according to body mass index (BMI) and waist circumference (WC) levels to study the relationship between obesity and CIAD. Multivariate logistic regression analysis was utilized to examine the connection between CIAD and obesity in a cross-sectional study. The association between obesity and all-cause mortality in individuals with CIAD was examined using multiple cox regression models and smooth curve fitting in a prospective cohort study. RESULTS: When stratified based on BMI in comparison to the normal weight group, the ORs with 95%CIs of CIAD for underweight and obesity were 1.39 (1.01-1.93) and 1.42 (1.27-1.58), respectively. The OR with 95%CI of CIAD for obesity was 1.20 (1.09-1.31) when stratified according to WC. Additionally, underweight was associated with a higher mortality (HR = 2.44, 95% CI = 1.31-4.55), whereas overweight (HR = 0.58,95% CI = 0.39-0.87) and obesity (HR = 0.59,95% CI = 0.4-0.87) were associated with a lower mortality (P for trend < 0.05). There was a non-linear association between BMI and all-cause mortality (P for non-linear = 0.001). An analysis of a segmentation regression model between BMI and all-cause mortality revealed a BMI turning point value of 32.4 kg/m2. The mortality of CIAD patients was lowest when BMI was 32.4 kg/m2. When BMI ≤ 32.4 kg/m2, BMI was inversely associated with all-cause mortality in patients with CIAD (HR: 0.92, 95%CI:0.88-0.97). However, when BMI > 32.4 kg/m2, there was no association between BMI and all-cause mortality (HR:1.02, 95%CI:0.97-1.06). CONCLUSION: Compared to normal weight, underweight and obesity were associated with the increased risk of CIAD. Underweight was associated with increased all-cause mortality, while overweight was associated with reduced all-cause mortality. There was a non-linear association between BMI and all-cause mortality in patients with CIAD. The all-cause mortality was lowest when BMI was 32.4 kg/m2.

Aberrant modular segregation of brain networks in female patients with bulimia nervosa.

OBJECTIVE: Bulimia nervosa (BN) is an eating disorder associated with the dysfunction of intrinsic brain networks. However, whether the network disruptions in BN patients manifest as dysconnectivity or imbalances of network modular segregation remains unclear. METHOD: We collected data from 41 women with BN and 41 matched healthy control (HC) women. We performed graph theory analysis based on resting-state functional magnetic resonance imaging (RS-fMRI) data; then, we computed the participation coefficient (PC) among brain modules to characterize the modular segregation for the BN and HC groups. The number of intra- and inter-modular connections was calculated to explain the PC changes. Additionally, we examined the potential associations of the measures mentioned above with clinical variables within the BN group. RESULTS: Compared with the HC group, the BN group showed significantly decreased PC in the fronto-parietal network (FPN), cingulo-opercular network (CON), and cerebellum (Cere). Additionally, the number of intra-modular connections of the default mode network (DMN) and the number of the inter-modular connections between the DMN and CON, FPN and Cere, and CON and Cere in the BN group were lower than those in the HC group. The nodal level analysis showed that the BN group had a decreased PC of the anterior prefrontal cortex (aPFC), dorsal frontal cortex (dFC), inferior parietal lobule (IPL), thalamus, and angular gyrus. Further, these metrics were significantly correlated with clinical variables in the BN group. DISCUSSION: These findings may provide novel insights to capture atypical topologies associated with pathophysiology mechanisms and clinical symptoms underlying BN.

Cinnamaldehyde regulates mitochondrial quality against hydrogen peroxide induced apoptosis in mouse lung mesenchymal stem cells via the PINK1/Parkin signaling pathway.

Background: Idiopathic pulmonary fibrosis (IPF) is a fatal respiratory disease without effective treatments. Mitochondrial dysfunction weakens the ability of mesenchymal stem cells (MSCs) to repair the distal lung epithelium, which is a probable pathogenesis of IPF. In previous research, we found that cinnamaldehyde (CA) can maintain the mitochondrial morphology of MSCs. Methods: This present study evaluated the effect and mechanism of CA on murine lung MSCs using the hydrogen peroxide model. Antioxidant effects and mitochondrial function were determined using flow cytometry. The mRNA levels of mitochondrial dynamics and the expressions of autophagy-related proteins were also detected. Results: CA can increase the levels of SOD, MMP and ATP, decrease the rate of ROS and apoptosis, and restore the mitochondrial structure. CA can also improve the mRNA expression of MFN1, MFN2, FIS1, DRP1, OPA1, and PGC-1α, increase the expression of LC3 II and p62 and promote the PINK1/Parkin signaling pathway. Our results demonstrated that CA can control mitochondrial quality and avoid apoptosis, which may be associated with the regulation of the PINK1/Parkin signaling pathway.

Decreased modular segregation of the frontal-parietal network in major depressive disorder.

Major depressive disorder (MDD) is a common psychiatric condition associated with aberrant large-scale distributed brain networks. However, it is unclear how the network dysfunction in MDD patients is characterized by imbalance or derangement of network modular segregation. Fifty-one MDD patients and forty-three matched healthy controls (HC) were recruited in the present study. We analyzed intrinsic brain activity derived from resting-state functional magnetic resonance imaging (R-fMRI) and then examined brain network segregation by computing the participation coefficient (PC). Further intra- and inter-modular connections analysis were preformed to explain atypical PC. Besides, we explored the potential relationship between the above graph theory measures and symptom severity in MDD. Lower modular segregation of the frontal-parietal network (FPN) was found in MDD compared with the HC group. The MDD group exhibited increased inter-module connections between the FPN and cingulo-opercular network (CON), between the FPN and cerebellum (Cere), between the CON and Cere. At the nodal level, the PC of the anterior prefrontal cortex, anterior cingulate cortex, inferior parietal lobule (IPL), and intraparietal sulcus showed larger in MDD. Additionally, the inter-module connections between the FPN and CON and the PC values of the IPL were negatively correlated with depression symptom in the MDD group. These findings might give evidence about abnormal FPN in MDD from the perspective of modular segregation in brain networks.

Charting the dorsal-medial functional gradient of the default mode network in major depressive disorder.

Major depressive disorder (MDD) is a common and disabling psychiatric condition associated with aberrant functional activity of the default mode network (DMN). However, it is unclear how the DMN dysfunction in MDD patients is characterized by functional connectivity diversity or gradient and whether antidepressant therapy causes the abnormal functional gradient of the DMN to change toward normalization. In current work, we estimated the functional gradient of the DMN derived from resting state functional magnetic resonance imaging in MDD patients (n = 70) and matching healthy controls (n = 43) and identified MDD-related functional connectivity diversity of the DMN. The longitudinal changes of the DMN functional gradient in 36 MDD patients were assessed before and after 12-week antidepressant treatment. Compared to the healthy controls, the functional gradient of the DMN exhibited relatively relative compression along the dorsal-medial axis in MDD patients at baseline and antidepressant treatment could normalize these DMN gradient abnormalities. A regularized least-squares regression model based on DMN gradient features at baseline significantly predicted the change of Hamilton Depression Rating (HAMD) Scale scores after antidepressant treatment. The medial prefrontal cortex gradient had a more contribution to prediction of antidepressant efficacy. Our findings provided a novel insight into the neurobiological mechanism underlying MDD from the perspective of the DMN functional gradient.

Abnormal Dynamic Functional Connectivity of the Left Rostral Hippocampus in Predicting Antidepressant Efficacy in Major Depressive Disorder.

OBJECTIVE: Some pharmacological treatments are ineffective in parts of patients with major depressive disorder (MDD), hence this needs prediction of effective treatment responses. The study aims to examine the relationship between dynamic functional connectivity (dFC) of the hippocampal subregion and antidepressant improvement of MDD patients and to estimate the capability of dFC to predict antidepressant efficacy. METHODS: The data were from 70 MDD patients and 43 healthy controls (HC); the dFC of hippocampal subregions was estimated by sliding-window approach based on resting-state functional magnetic resonance imaging (R-fMRI). After 3 months treatment, 36 patients underwent second R-fMRI scan and were then divided into the response group and non-response group according to clinical responses. RESULTS: The result manifested that MDD patients exhibited lower mean dFC of the left rostral hippocampus (rHipp.l) compared with HC. After 3 months therapy, the response group showed lower dFC of rHipp.l compared with the non-response group. The dFC of rHipp.l was also negatively correlated with the reduction rate of Hamilton Depression Rating Scale. CONCLUSION: These findings highlighted the importance of rHipp in MDD from the dFC perspective. Detection and estimation of these changes might demonstrate helpful for comprehending the pathophysiological mechanism and for assessment of treatment reaction of MDD.

Altered dynamic functional connectivity of insular subregions could predict symptom severity of male patients with autism spectrum disorder.

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder characterized by difficulties with social communication and restricted or repetitive patterns of behavior. This disorder was characterized by widespread abnormalities involving distributed brain networks. As one such key network node, the insular cortex has been regarded as a research focus of ASD neuropathology. The insula is a functionally complex brain structure. However, it is not fully clear if dynamic characteristics of resting-state functional magnetic resonance imaging (R-fMRI) signals in insular heterogeneous could be used to depict abnormalities in ASD. To address this question, we investigated dynamic functional connectivity (dFC) of 12 insular subregions. Data were obtained from 44 individuals with ASD and 65 typically developing age-matched controls (TDC). We assessed dFC by sliding-window method and quantified its temporal variability. Multivariable linear regression models were constructed to determine whether dFC support complementary information about symptom severity of individuals with ASD rather than static functional connectivity (sFC). The results showed that individuals with ASD exhibited dFC and sFC alterations in distinct insular subregions. Some brain regions showed only abnormal dFC but not sFC with insular subregions. These abnormal dFC could significantly predict the symptom severity of individuals with ASD. Our findings might advance our knowledge about the potential of insular heterogeneity and dynamic characteristics in understanding the neuropathology mechanism of ASD and in developing neuroimaging biomarkers for clinical applications.

Effective Connectivity of Right Amygdala Subregions Predicts Symptom Improvement Following 12-Week Pharmacological Therapy in Major Depressive Disorder.

The low rates of treatment response still exist in the pharmacological therapy of major depressive disorder (MDD). Exploring an optimal neurological predictor of symptom improvement caused by pharmacotherapy is urgently needed for improving response to treatment. The amygdala is closely related to the pathological mechanism of MDD and is expected to be a predictor of the treatment. However, previous studies ignored the heterogeneousness and lateralization of amygdala. Therefore, this study mainly aimed to explore whether the right amygdala subregion function at baseline can predict symptom improvement after 12-week pharmacotherapy in MDD patients. We performed granger causality analysis (GCA) to identify abnormal effective connectivity (EC) of right amygdala subregions in MDD and compared the EC strength before and after 12-week pharmacological therapy. The results show that the abnormal EC mainly concentrated on the frontolimbic circuitry and default mode network (DMN). With relief of the clinical symptom, these abnormal ECs also change toward normalization. In addition, the EC strength of right amygdala subregions at baseline showed significant predictive ability for symptom improvement using a regularized least-squares regression predict model. These findings indicated that the EC of right amygdala subregions may be functionally related in symptom improvement of MDD. It may aid us to understand the neurological mechanism of pharmacotherapy and can be used as a promising predictor for symptom improvement in MDD.

Aberrant Effective Connectivity of the Ventral Putamen in Boys With Attention-Deficit/Hyperactivity Disorder.

OBJECTIVE: The connectivity alterations in the putamen were found in revealing the neural correlates of attention-deficit/hyperactivity disorder (ADHD), but whether the effective connectivity of the putamen is atypical in ADHD remains unclear. Investigating this abnormality contributes to describing the neural circuit of ADHD at the level of macrostructural organization. METHODS: Data were acquired from thirty-two boys with ADHD and fifty-two matched typically developing controls (TDC) from Peking University (Peking) dataset deposited at the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) platform. We examined the effective connectivity of the putamen using Granger causality analysis (GCA) and then determined whether these connections could differentiate ADHD from TDC. RESULTS: Compared with TDC, the ADHD group showed decreased effective connectivity from the left ventral rostral putamen (VRP) to left calcarine (CAL), right medial part of the superior frontal gyrus, left orbital part of superior frontal gyrus and left middle occipital gyrus (MOG). Increased effective connectivity from the left inferior occipital gyrus and right lingual gyrus to left VRP was also found in ADHD. The result of the classification accuracy showed that 72.3% of participants were correctly classified using support vector machine. Moreover, GCA values from the left VRP to left CAL and left MOG were significantly correlated with hyper/impulsive scores of patients with ADHD. CONCLUSION: The findings may help extend our understanding of the ADHD-related neural loops.

Brain state-dependent dynamic functional connectivity patterns in attention-deficit/hyperactivity disorder.

Attention-deficit/hyperactivity disorder (ADHD) patients have presented aberrant static brain networks, however identifying ADHD patients based on dynamic information in brain networks is not fully clear. Data were obtained from 32 boys with ADHD and 52 sex- and age-matched typically developing controls; a sliding-window method was used to assess dynamic functional connectivity (dFC), and two reoccurring dFC states (the hot and cool states) were then identified using a k-means clustering method. The results showed that ADHD patients had significant changes in occurrence, transitions times and dFC strength of the cingulo-opercular network (CON) and sensorimotor network (SMN) in the cool state. The severity of ADHD symptoms showed significant correlations with the regional amplitude of dFC fluctuations in the ventral medial prefrontal cortex (vmPFC), anterior medial prefrontal cortex (amPFC) and precuneus. These findings could provide insights on the state-dependent dynamic changes in large-scale brain connectivity and network configurations in ADHD.

Antidepressant Treatment-Induced State-Dependent Reconfiguration of Emotion Regulation Networks in Major Depressive Disorder.

Deficits in emotion regulation are the main clinical features, common risk factors, and treatment-related targets for major depressive disorder (MDD). The neural bases of emotion regulation are moving beyond specific functions and emphasizing instead the integrative functions of spatially distributed brain areas that work together as large-scale brain networks, but it is still unclear whether the dynamic interactions among these emotion networks would be the target of clinical intervention for MDD. Data were collected from 70 MDD patients and 43 sex- and age-matched healthy controls. The dynamic functional connectivity (dFC) between emotion regions was estimated via a sliding-window method based on resting-state functional magnetic resonance imaging (R-fMRI). A k-means clustering method was applied to classify all time windows across all participants into several dFC states reflecting recurring functional interaction patterns among emotion regions over time. The results showed that four dFC states were identified in the emotion networks. Their alterations of state-related occurrence proportion were found in MDD and subsequently normalized following 12-week antidepressant treatment. Baseline strong dFC could predict the reduction rate of Hamilton Depression Rating Scale (HAMD) scores. These findings highlighted the state-dependent reconfiguration of emotion regulation networks in MDD patients owing to antidepressant treatment.

High Value-Added Application of Two Renewable Sources as Healthy Food: The Nutritional Properties, Chemical Compositions, Antioxidant, and Antiinflammatory Activities of the Stalks of Rheum officinale Baill. and Rheum tanguticum Maxim. ex Regel.

Rhubarb plants (Rheum officinale and R. tanguticum) have edible stalks. In this work, we aimed to compare the nutritional properties, chemical compositions, and bioactivities of R. officinale (SRO) and R. tanguticum (SRT) stalks and to analyze the composition-function relationship. Results showed that the two stalks were good sources of fiber, as well as minerals. They contained abundant essential amino acids and essential fatty acids to regulate the immunity and prevent some chronic diseases; the contents of polyunsaturated fatty acids were 2,244.32 mg/100 g and 2,844.69 mg/100 g, respectively. The antioxidant activity were also proved. Metabolomics showed that SRO and SRT contained abundant phenolic acids. Due to the higher concentrations of flavones, SRT has better antiinflammatory activities than SRO by inhibiting NF-κB signaling pathway. Rhubarb stalks exhibited good safety in acute toxicity and cytotoxicity tests. This work indicated that the two stalks have nutritional value, safety, and bioactivities, and could be used as sources of nutritional ingredients for regulating the immunity of body in food industry.

Low-grade fever during COVID-19 convalescence: A report of 3 cases.

BACKGROUND: Low-grade fever during convalescence is an atypical symptom of coronavirus disease 2019 (COVID-19). Reports of such cases are rare, and the mechanism and outcome of low-grade fever during COVID-19 convalescence are not completely clear. We report 3 cases with low-grade fever during COVID-19 convalescence and highlight the main clinical, radiographic, and laboratory characteristics, thereby increasing the level of expertise in the clinical management of COVID-19 during convalescence and facilitating individualized decision-making. CASE SUMMARY: We describe 3 patients with COVID-19, two females aged 62 and 66 years and a male 55 years, who had low-grade fever during COVID-19 convalescence. All 3 patients had no other discomfort or comorbidities during low-grade process. Lesions on computed tomography in all 3 patients had resolved during this period. Two patients tested negative on two consecutive severe acute respiratory syndrome coronavirus 2 tests with an interval of at least 24 h between tests. Body temperature in all 3 patients returned to normal after several days without treatment, and fever recurrence was not observed. CONCLUSION: Enhancing the knowledge of low-grade fever during COVID-19 convalescence may increase the expertise in the delivery of optimal healthcare services.

Differentiating Boys with ADHD from Those with Typical Development Based on Whole-Brain Functional Connections Using a Machine Learning Approach.

PURPOSE: In recent years, machine learning techniques have received increasing attention as a promising approach to differentiating patients from healthy subjects. Therefore, some resting-state functional magnetic resonance neuroimaging (R-fMRI) studies have used interregional functional connections as discriminative features. The aim of this study was to investigate ADHD-related spatially distributed discriminative features derived from whole-brain resting-state functional connectivity patterns using machine learning. PATIENTS AND METHODS: We measured the interregional functional connections of the R-fMRI data from 40 ADHD patients and 28 matched typically developing controls. Machine learning was used to discriminate ADHD patients from controls. Classification performance was assessed by permutation tests. RESULTS: The results from the model with the highest classification accuracy showed that 85.3% of participants were correctly identified using leave-one-out cross-validation (LOOV) with support vector machine (SVM). The majority of the most discriminative functional connections were located within or between the cerebellum, default mode network (DMN) and frontoparietal regions. Approximately half of the most discriminative connections were associated with the cerebellum. The cerebellum, right superior orbitofrontal cortex, left olfactory cortex, left gyrus rectus, right superior temporal pole, right calcarine gyrus and bilateral inferior occipital cortex showed the highest discriminative power in classification. Regarding the brain-behaviour relationships, some functional connections between the cerebellum and DMN regions were significantly correlated with behavioural symptoms in ADHD (P < 0.05). CONCLUSION: This study indicated that whole-brain resting-state functional connections might provide potential neuroimaging-based information for clinically assisting the diagnosis of ADHD.

Betaine Effects on Morphology, Proliferation, and p53-induced Apoptosis of HeLa Cervical Carcinoma Cells in Vitro.

OBJECTIVES: To investigate the effects of betaine on HeLa cell growth and apoptosis and molecular mechanisms. MATERIALS AND METHODS: Concentrations of 0.1, 1.0, 5.0, 20.0, 100.0 mg/ml of betaine were used to evaluate the anticancer efficacy for HeLa cells respectively, and MCF-10A was also detected as a normal diploid cell control. RESULTS: We found that proliferation of HeLa cells was inhibited significantly upon exposure to increasing betaine levels with the MTT test (p<0.05). The percentage of S phase cells in the low dose groups (< 5mg/ml) were distinctly higher than in high dose groups, and the rates of Sub-G1 phase were the opposite (p<0.01); A high concentration of betaine (>5.0mg/ml) significantly promoted the apoptosis of HeLa cells (p<0.01). SOD activities of the low dose groups were slightly higher than the control group (p<0.05) and there were obvious synchronicity and correlation among the expression of promoting apoptosis genes Bax, P53, Caspase 3 and apoptosis suppression gene Bcl-2. In response to an apoptosis-inducing stimulus, p53 and cyclin D1 could be activated with blockage of the cell cycle at G1/S or S/G2 checkpoints. CONCLUSIONS: Our data showed that betaine could promote HeLa cells proliferation in vitro at low concentrations.In contrast, high concentrations could significantly inhibit cell growth and migration, and induce apoptosis of HeLa cells through caspase 3 signaling and further promoted necrosis. This might imply that betaine exhibits tumoricidal effects and acts as a biological response modifier in cancer treatment by inducing apoptosis and cell cycle arrest in a dose and time-dependent manner.

[Study on the ultraviolet protective effects of the cream of the total flavonoids from Oxytropis falcata].

OBJECTIVE: To study the protective effects of the cream of the total flavonoids from Oxytropis falcata on the destructed skin of mice induced by moderate-wave ultraviolet (UVB) irradiation. METHODS: Dorsal skin of Wistar mice were treated with the cream of the total flavonoids from Oxytropis falcata and then irradiated with UVB in the dosage of 5 min once a day for one week. The tissue of skin was pathological diagnosed and the activities or contents of superoxide dismutase (SOD), malondialdehyde (MDA), hydroxyproline (Hyp), glutathione peroxidease (GSH-Px), glutathione (GSH), glutathion-s-transferase (GST), catalase (CAT) and hydroxy radical (*OH) were determined with chromatometry. RESULTS: The ultraviolet protective effects of the cream could be observed with appearance and pathology examine. The cream could increase the activities of SOD (P < 0.001), GSH-Px (P < 0.001), GST (P < 0.05) and CAT (P < 0.01), raise the content of Hyp (P < 0.001) significantly. The cream could also decrease the contents of MDA and *OH (P < 0.001), and the activities of GSH significantly (P < 0.001). CONCLUSION: The cream of the total flavonoids from Oxytropis falcata has protective effect on the destructed skin of mice induced by moderate-wave ultraviolet (UVB) irradiation.