Shared and differing functional connectivity abnormalities of the default mode network in mild cognitive impairment and Alzheimer's disease.

Alzheimer's disease (AD) and mild cognitive impairment (MCI) both show abnormal resting-state functional connectivity (rsFC) of default mode network (DMN), but it is unclear to what extent these abnormalities are shared. Therefore, we performed a comprehensive meta-analysis, including 31 MCI studies and 20 AD studies. MCI patients, compared to controls, showed decreased within-DMN rsFC in bilateral medial prefrontal cortex/anterior cingulate cortex (mPFC/ACC), precuneus/posterior cingulate cortex (PCC), right temporal lobes, and left angular gyrus and increased rsFC between DMN and left inferior temporal gyrus. AD patients, compared to controls, showed decreased rsFC within DMN in bilateral mPFC/ACC and precuneus/PCC and between DMN and left inferior occipital gyrus and increased rsFC between DMN and right dorsolateral prefrontal cortex. Conjunction analysis showed shared decreased rsFC in mPFC/ACC and precuneus/PCC. Compared to MCI, AD had decreased rsFC in left precuneus/PCC and between DMN and left inferior occipital gyrus and increased rsFC in right temporal lobes. MCI and AD share a decreased within-DMN rsFC likely underpinning episodic memory deficits and neuropsychiatric symptoms, but differ in DMN rsFC alterations likely related to impairments in other cognitive domains such as language, vision, and execution. This may throw light on neuropathological mechanisms in these two stages of dementia.

Common and distinct cortical thickness alterations in youth with autism spectrum disorder and attention-deficit/hyperactivity disorder.

BACKGROUND: Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) are neurodevelopmental disorders with overlapping behavioral features and genetic etiology. While brain cortical thickness (CTh) alterations have been reported in ASD and ADHD separately, the degree to which ASD and ADHD are associated with common and distinct patterns of CTh changes is unclear. METHODS: We searched PubMed, Web of Science, Embase, and Science Direct from inception to 8 December 2023 and included studies of cortical thickness comparing youth (age less than 18) with ASD or ADHD with typically developing controls (TDC). We conducted a comparative meta-analysis of vertex-based studies to identify common and distinct CTh alterations in ASD and ADHD. RESULTS: Twelve ASD datasets involving 458 individuals with ASD and 10 ADHD datasets involving 383 individuals with ADHD were included in the analysis. Compared to TDC, ASD showed increased CTh in bilateral superior frontal gyrus, left middle temporal gyrus, and right superior parietal lobule (SPL) and decreased CTh in right temporoparietal junction (TPJ). ADHD showed decreased CTh in bilateral precentral gyri, right postcentral gyrus, and right TPJ relative to TDC. Conjunction analysis showed both disorders shared reduced TPJ CTh located in default mode network (DMN). Comparative analyses indicated ASD had greater CTh in right SPL and TPJ located in dorsal attention network and thinner CTh in right TPJ located in ventral attention network than ADHD. CONCLUSIONS: These results suggest shared thinner TPJ located in DMN is an overlapping neurobiological feature of ASD and ADHD. This alteration together with SPL alterations might be related to altered biological motion processing in ASD, while abnormalities in sensorimotor systems may contribute to behavioral control problems in ADHD. The disorder-specific thinner TPJ located in disparate attention networks provides novel insight into distinct symptoms of attentional deficits associated with the two neurodevelopmental disorders. TRIAL REGISTRATION: PROSPERO CRD42022370620. Registered on November 9, 2022.

Mechanical thrombectomy combined with intravenous thrombolysis for acute ischemic stroke: a systematic review and meta-analyses.

To assess the clinical value of mechanical thrombectomy (MT) combined with intravenous thrombolysis (IVT) in acute ischemic stroke (AIS) by comparing it with the MT alone. In this study, we conducted a comprehensive meta-analysis of both observational and randomized controlled studies (RCTs) to investigate various outcomes. Our search for relevant studies was conducted between January 2011 and June 2022 in four major databases: PubMed, Embase, WOS, and Cochrane Library. We collected data on several outcomes, including functional independence (FI; defined as modified Rankin Scale score of 0 to 2), excellent outcomes (mRS 0-1), successful recanalization (SR), symptomatic intracerebral hemorrhage (sICH), any intracerebral hemorrhage (aICH), and mortality at three months or discharge. The primary efficacy outcome and safety outcome were FI and sICH, respectively, whereas excellent outcomes and SR were considered secondary efficacy outcomes. Additionally, mortality and aICH were analyzed as secondary safety outcomes. We employed the Mantel-Haenszel fixed-effects model for RCTs when I2 < 50%, otherwise the random-effects model was utilized. For observational studies and subgroup analyses, we used the random-effects model to minimize potential bias. A total of 55 eligible studies (nine RCTs and 46 observational studies) were included. For RCTs, the MT + IVT group was superior in FI (OR: 1.27, 95% CI: 1.11-1.46), excellent outcomes (OR: 1.21, 95% CI: 1.03-1.43), SR (OR: 1.23, 95% CI: 1.05-1.45), mortality (OR: 0.72, 95% CI: 0.54-0.97) in crude analyses. In adjusted analyses, the MT + IVT group reduced the risk of mortality (OR: 0.65, 95% CI: 0.49-0.88). However, the difference in FI between the MT + IVT group and the MT alone group was not significant (OR: 1.17, 95% CI: 0.99-1.38, Fig. 3a). For observational studies, the results of FI (OR: 1.34, 95% CI: 1.16-1.33), excellent outcomes (OR: 1.30, 95% CI: 1.09-1.54), SR (OR: 1.23, 95% CI: 1.05-1.44), mortality (OR: 0.70, 95% CI: 0.64-0.77) in the MT + IVT group were better. Additionally, the MT + IVT group increased the risk of hemorrhagic transformation (HT) including sICH (OR: 1.16, 95% CI: 1.11-1.21) and aICH (OR: 1.24, 95% CI: 1.05-1.46) in crude analyses. In adjusted analyses, significant better outcomes were seen in the MT + IVT group on FI (OR: 1.36, 95% CI: 1.21-1.52), excellent outcomes (OR: 1.49, 95% CI: 1.26-1.75), and mortality (OR: 0.73, 95% CI: 0.56-0.94). The MT + IVT therapy did improve the prognosis for AIS patients and did not increase the risk of HT compared with MT alone therapy.

TaG-Net: Topology-Aware Graph Network for Centerline-Based Vessel Labeling.

Anatomical labeling of head and neck vessels is a vital step for cerebrovascular disease diagnosis. However, it remains challenging to automatically and accurately label vessels in computed tomography angiography (CTA) since head and neck vessels are tortuous, branched, and often spatially close to nearby vasculature. To address these challenges, we propose a novel topology-aware graph network (TaG-Net) for vessel labeling. It combines the advantages of volumetric image segmentation in the voxel space and centerline labeling in the line space, wherein the voxel space provides detailed local appearance information, and line space offers high-level anatomical and topological information of vessels through the vascular graph constructed from centerlines. First, we extract centerlines from the initial vessel segmentation and construct a vascular graph from them. Then, we conduct vascular graph labeling using TaG-Net, in which techniques of topology-preserving sampling, topology-aware feature grouping, and multi-scale vascular graph are designed. After that, the labeled vascular graph is utilized to improve volumetric segmentation via vessel completion. Finally, the head and neck vessels of 18 segments are labeled by assigning centerline labels to the refined segmentation. We have conducted experiments on CTA images of 401 subjects, and experimental results show superior vessel segmentation and labeling of our method compared to other state-of-the-art methods.

Shared and Disorder-Specific Alterations of Brain Temporal Dynamics in Obsessive-Compulsive Disorder and Schizophrenia.

BACKGROUND: Obsessive-compulsive disorder (OCD) and schizophrenia have distinct but also overlapping symptoms. Few studies have examined the shared and disorder-specific disturbances in dynamic brain function in the 2 disorders. STUDY DESIGN: Resting-state functional magnetic resonance imaging data of 31 patients with OCD and 49 patients with schizophrenia, all untreated, and 45 healthy controls (HCs) were analyzed using spatial group independent component (IC) analysis. Time-varying degree centrality patterns across the whole brain were clustered into 3 reoccurring states, and state transition metrics were obtained. We further explored regional temporal variability of degree centrality for each IC across all time windows. STUDY RESULTS: Patients with OCD and patients with schizophrenia both showed decreased occurrence of a state having the highest centrality in the sensorimotor and auditory networks. Additionally, patients with OCD and patients with schizophrenia both exhibited reduced dynamics of degree centrality in the superior frontal gyrus than controls, while dynamic degree centrality of the cerebellum was lower in patients with schizophrenia than with OCD and HCs. Altered dynamics of degree centrality nominally correlated with symptom severity in both patient groups. CONCLUSIONS: Our study provides evidence of transdiagnostic and clinically relevant functional brain abnormalities across OCD and schizophrenia in neocortex, as well as functional dynamic alterations in the cerebellum specific to schizophrenia. These findings add to the recognition of overlap in neocortical alterations in the 2 disorders, and indicate that cerebellar alterations in schizophrenia may be specifically important in schizophrenia pathophysiology via impact on cerebellar thalamocortical circuitry.

Patterns of brain dynamic functional connectivity are linked with attention-deficit/hyperactivity disorder-related behavioral and cognitive dimensions.

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) is a clinically heterogeneous neurodevelopmental disorder defined by characteristic behavioral and cognitive features. Abnormal brain dynamic functional connectivity (dFC) has been associated with the disorder. The full spectrum of ADHD-related variation of brain dynamics and its association with behavioral and cognitive features remain to be established. METHODS: We sought to identify patterns of brain dynamics linked to specific behavioral and cognitive dimensions using sparse canonical correlation analysis across a cohort of children with and without ADHD (122 children in total, 63 with ADHD). Then, using mediation analysis, we tested the hypothesis that cognitive deficits mediate the relationship between brain dynamics and ADHD-associated behaviors. RESULTS: We identified four distinct patterns of dFC, each corresponding to a specific dimension of behavioral or cognitive function (r = 0.811-0.879). Specifically, the inattention/hyperactivity dimension was positively associated with dFC within the default mode network (DMN) and negatively associated with dFC between DMN and the sensorimotor network (SMN); the somatization dimension was positively associated with dFC within DMN and SMN; the inhibition and flexibility dimension and fluency and memory dimensions were both positively associated with dFC within DMN and between DMN and SMN, and negatively associated with dFC between DMN and the fronto-parietal network. Furthermore, we observed that cognitive functions of inhibition and flexibility mediated the relationship between brain dynamics and behavioral manifestations of inattention and hyperactivity. CONCLUSIONS: These findings document the importance of distinct patterns of dynamic functional brain activity for different cardinal behavioral and cognitive features related to ADHD.

Brain alterations in sensorimotor and emotional regions associated with temporomandibular disorders.

OBJECTIVES: Temporomandibular disorders (TMD) are characterized by sensorimotor and psychological dysfunction, with evidence revealing the implication of a dysfunctional central nervous system. Previous magnetic resonance imaging (MRI) studies have reported brain alterations in TMD, but most studies focused on either structure or function by a single modality of MRI and investigated static functional connectivity (FC) in TMD. By combining structural and functional MRI data, the present study aimed to identify brain regions with structural abnormalities in TMD patients and examine static and dynamic FC seeded by these regions to investigate structural brain alterations and related disrupted FC underlying the pathophysiology of TMD. METHODS: We recruited 30 TMD patients and 20 healthy controls who underwent 3.0 T MRI scanning with T1-weighted images using a three-dimensional magnetization-prepared rapid gradient-echo sequence and resting state functional images using a gradient-echo echo-planar imaging sequence. Cortical thickness, volume, surface area, and subcortical volume were calculated, where brain areas with significant structural between-group differences were treated as seeds for static and dynamic FC analyses. RESULTS: In this preliminary study, we found between-group alterations in sensorimotor regions including decreased cortical thickness in the right sensorimotor cortex as well as decreased volume in the left putamen and associated reduced dynamic FC with the anterior midcingulate cortex; and alterations in emotion processing and regulation regions including decreased volume/surface area in the left posterior superior temporal gyrus and associated increased dynamic FC with the precuneus in TMD patients than controls, having all p < 0.05 with corrections for multiple comparisons. CONCLUSION: Our findings of structural and functional abnormalities in brain regions implicated in sensorimotor and emotional functions provided evidence for the biopsychosocial model of TMD and facilitated our understanding of the pathophysiological mechanism underlying TMD. The associations between neuroimaging results and clinical measurements of TMD warrant further exploration.

Evaluation of an automated intracranial aneurysm detection and rupture analysis approach using cascade detection and classification networks.

Intracranial aneurysm is commonly found in human brains especially for the elderly, and its rupture accounts for a high rate of subarachnoid hemorrhages. However, it is time-consuming and requires special expertise to pinpoint small aneurysms from computed tomography angiography (CTA) images. Deep learning-based detection has helped improve much efficiency but false-positives still render difficulty to be ruled out. To study the feasibility of deep learning algorithms for aneurysm analysis in clinical applications, this paper proposes a pipeline for aneurysm detection, segmentation, and rupture classification and validates its performance using CTA images of 1508 subjects. A cascade aneurysm detection model is employed by first using a fine-tuned feature pyramid network (FPN) for candidate detection and then applying a dual-channel ResNet aneurysm classifier to further reduce false positives. Detected aneurysms are then segmented by applying a traditional 3D V-Net to their image patches. Radiomics features of aneurysms are extracted after detection and segmentation. The machine-learning-based and deep learning-based rupture classification can be used to distinguish ruptured and un-ruptured ones. Experimental results show that the dual-channel ResNet aneurysm classifier utilizing image and vesselness information helps boost sensitivity of detection compared to single image channel input. Overall, the proposed pipeline can achieve a sensitivity of 90 % for 1 false positive per image, and 95 % for 2 false positives per image. For rupture classification the area under curve (AUC) of 0.906 can be achieved for the testing dataset. The results suggest feasibility of the pipeline for potential clinical use to assist radiologists in aneurysm detection and classification of ruptured and un-ruptured aneurysms.

Deep learning derived automated ASPECTS on non-contrast CT scans of acute ischemic stroke patients.

Ischemic stroke is the most common type of stroke, ranked as the second leading cause of death worldwide. The Alberta Stroke Program Early CT Score (ASPECTS) is considered as a systematic method of assessing ischemic change on non-contrast CT scans (NCCT) of acute ischemic stroke (AIS) patients, while still suffering from the requirement of experts' experience and also the inconsistent results between readers. In this study, we proposed an automated ASPECTS method to utilize the powerful learning ability of neural networks for objectively scoring CT scans of AIS patients. First, we proposed to use the CT perfusion (CTP) from one-stop stroke imaging to provide the golden standard of ischemic regions for ASPECTS scoring. Second, we designed an asymmetry network to capture features when comparing the left and right sides for each ASPECTS region to estimate its ischemic status. Third, we performed experiments in a large main dataset of 870 patients, as well as an independent testing dataset consisting of 207 patients with radiologists' scorings. Experimental results show that our network achieved remarkable performance, as sensitivity and accuracy of 93.7 and 92.4% in the main dataset, and 95.5 and 91.3% in the independent testing dataset, respectively. In the latter dataset, our analysis revealed a high positive correlation between the ASPECTS score and the prognosis of patients in 90DmRs. Also, we found ASPECTS score is a good indicator of the size of CTP core volume of an infraction. The proposed method shows its potential for automated ASPECTS scoring on NCCT images.

Altered single-subject gray matter structural networks in drug-naïve attention deficit hyperactivity disorder children.

Altered topological organization of brain structural covariance networks has been observed in attention deficit hyperactivity disorder (ADHD). However, results have been inconsistent, potentially related to confounding medication effects. In addition, since structural networks are traditionally constructed at the group level, variabilities in individual structural features remain to be well characterized. Structural brain imaging with MRI was performed on 84 drug-naïve children with ADHD and 83 age-matched healthy controls. Single-subject gray matter (GM) networks were obtained based on areal similarities of GM, and network topological properties were analyzed using graph theory. Group differences in each topological metric were compared using nonparametric permutation testing. Compared with healthy subjects, GM networks in ADHD patients demonstrated significantly altered topological characteristics, including higher global and local efficiency and clustering coefficient, and shorter path length. In addition, ADHD patients exhibited abnormal centrality in corticostriatal circuitry including the superior frontal gyrus, orbitofrontal gyrus, medial superior frontal gyrus, precentral gyrus, middle temporal gyrus, and pallidum (all p < .05, false discovery rate [FDR] corrected). Altered global and nodal topological efficiencies were associated with the severity of hyperactivity symptoms and the performance on the Stroop and Wisconsin Card Sorting Test tests (all p < .05, FDR corrected). ADHD combined and inattention subtypes were differentiated by nodal attributes of amygdala (p < .05, FDR corrected). Alterations in GM network topologies were observed in drug-naïve ADHD patients, in particular in frontostriatal loops and amygdala. These alterations may contribute to impaired cognitive functioning and impulsive behavior in ADHD.

Abnormalities of Cerebral White Matter Microstructure in Children With New-Onset, Untreated Idiopathic-Generalized Epilepsy.

Despite evidence for microstructural brain alterations in epilepsy patients, little is known about how these develop with age and the progress of the disease. The aim of this study was to investigate microstructural abnormalities of the white matter (WM) in children with new-onset, untreated idiopathic-generalized epilepsy (IGE) using the MRI technique of diffusion tensor imaging (DTI). The study was approved by the institutional review board, and all individuals or their parents gave signed informed consent. In total, 45 patients with IGE (age 5-18 years, male: female 26:19) and 32 healthy controls (HCs; age 5-18 years, male: female 21:11) were included. Voxel-based analysis (VBA) was used to compare patients and controls, and Pearson correlation analysis was used to investigate relationships between altered DTI metrics and clinical parameters. Compared with controls, patients with IGE showed increased mean diffusivity (MD) in the left splenium of the corpus callosum, increased fractional anisotropy (FA) in the right WM of the superior and middle frontal gyri, increased axial diffusivity (AD) in the WM of right corona radiata and left occipital lobe, and decreased AD in the WM of the left thalamus and the right middle cerebellar peduncle. There was no correlation between the altered diffusion parameters and clinical measures. Our study demonstrated several distinct microstructural impairments in children with new-onset, untreated IGE, of which altered AD might be the most sensitive marker of dysmyelination. The increased FA in the IGE group might suggest an initiating or compensatory mechanism that is activated prior to cognitive decline in these children.

Dysconnectivity of the amygdala and dorsal anterior cingulate cortex in drug-naive post-traumatic stress disorder.

Convergent studies have highlighted the amygdala-based and dorsal anterior cingulate cortex (dACC)-based circuit or network dysfunction in post-traumatic stress disorder (PTSD). However, previous studies are often complicated by various traumatic types, psychiatric comorbidities, chronic illness duration, and medication effect on brain function. Besides, little is known whether the functional integration with amygdala-dACC interaction disrupted or not in PTSD. Here, we investigated effective connectivity (EC) between the amygdala-dACC and rest of the cortex by applying psycho-physiological interaction (PPI) approach to resting-state functional magnetic resonance imaging data of 63 drug-naive PTSD patients and 74 matched trauma-exposed non-PTSD controls. Pearson correlation analysis was performed between EC values extracted from regions with between-group difference and clinical profiles in PTSD patients. We observed distinct amygdala-dACC interaction pattern between PTSD group and the control group, which is composed primarily by positive EC in the former and negative in the latter. In addition, compared with non-PTSD controls, PTSD patients showed increased EC between amygdala-dACC and the prefrontal cortex, left inferior parietal lobule, and bilateral ventral occipital cortex, and decreased EC between amygdala-dACC and the left fusiform gyrus. The EC increase between amygdala-dACC and the right middle frontal gyrus was negatively correlated with the clinician-administered PTSD scale scores in PTSD patients. Aberrent communication between amgydala-dACC and brain regions involved in central executive network and visual systems might be associated with the pathophysiology of PTSD. Further, these findings suggested that dysconnectivity of the amygdala and dACC could be adapted as a relatively early course diagnostic biomarker of PTSD.

Comparison of the clinical characteristics of patients with novel coronavirus pneumonia between China and overseas.

BACKGROUND: To explore the clinical manifestation, imaging examination, and serology of patients with novel coronavirus pneumonia (COVID-19) between China and overseas. METHODS: Ninety patients with COVID-19 who admitted to Fuzhou Pulmonary Hospital from January 23, 2020, to May 1, 2020, were included in this retrospective study. They were divided into domestic group and overseas group according to the origin regions. The clinical manifestations, imaging examination, serology, treatment, and prognosis between the two groups were compared and analyzed. RESULTS: The clinical manifestations of patients in the two groups mainly included fever (83.1% and 47.4%), cough (62% and 31.6%), expectoration (47.9% and 31.6%), anorexia (28.2% and 47.4%), fatigue (21.1% and 10.5%), and dyspnea (22.5% and 0%). The main laboratory characteristics in the two groups were decreased lymphocyte count, increased lactate dehydrogenase, decreased oxygenation index, decreased white blood cell count, increased erythrocyte sedimentation rate (ESR), and increased C-reactive protein. The computed tomography (CT) examinations of chest showed bilateral and peripheral involvement, with multiple patch shadows and ground glass shadows. However, pleural effusions were rare. CONCLUSION: Fever, cough, and dyspnea are more common in domestic cases than overseas cases. However, patients with COVID-19 from overseas may have the symptoms of loss of taste and smell that domestic cases do not have.

A multimodal meta-analysis of regional structural and functional brain alterations in type 2 diabetes.

Neuroimaging studies have identified brain structural and functional alterations of type 2 diabetes mellitus (T2DM) patients; however, there is no systematic information on the relations between abnormalities in these two domains. We conducted a multimodal meta-analysis of voxel-based morphometry and regional resting-state functional MRI studies in T2DM, including fifteen structural datasets (693 patients and 684 controls) and sixteen functional datasets (378 patients and 358 controls). We found, in patients with T2DM compared to controls, conjoint decreased regional gray matter volume (GMV) and altered intrinsic activity mainly in the default mode network including bilateral superior temporal gyrus/Rolandic operculum, left middle and inferior temporal gyrus, and left supramarginal gyrus; decreased GMV alone in the limbic system; and functional abnormalities alone in the cerebellum, insula, and visual cortex. This meta-analysis identified complicated patterns of conjoint and dissociated brain alterations in T2DM patients, which may help provide new insight into the neuropathology of T2DM.

Are glucagon-like peptide 1 analogues effective and safe in severe COVID-19 patients with type 2 diabetes?-a case report.

Many cases of novel coronavirus 2019 (COVID-19) have confirmed in many countries around the world. Due to the disorders of the immune system, diabetic patients are more likely to suffer from severe COVID-19. Glucagon-like peptide 1 analogues (GLP-1 analogues) commonly can be used to reduce blood sugar. There is no clear evidence that it can be safely and effectively used in patients with diabetes merged severe COVID-19. In this case, we described A 65-year-old male with hypertension and diabetes was diagnosed with severe COVID-19, he took liraglutide at doses ranging from 0.8 to 1.8 mg. Before admission, liraglutide was not used to reduce blood glucose. Hydroxychloroquine sulfate and abidol were used to antivirus and supportive treatment were used simultaneously during hospitalization. During treatment, the patient's own state was paid attention to, and blood glucose, liver function, kidney function, white blood cells, lymphocytes and other indicators were checked and chest CT was reviewed regularly, which could reflect changes in disease. After treatment, the patient's blood glucose was under control, and his liver function, renal function, white blood cells, lymphocytes and other indicators were normal and chest CT also improved. The case showed that liraglutide may be effective and safe used in patients with severe COVID-19 combined with type 2 diabetes, but more clinical trials are needed.

Decoupling of Gray and White Matter Functional Networks in Medication-Naïve Patients With Major Depressive Disorder.

BACKGROUND: Major depressive disorder (MDD) has been increasingly conceptualized as a disconnection syndrome. However, most studies have only focused on functional connectivity (FC) alterations in gray matter (GM), and the functional alterations in white matter (WM) remain largely unknown in MDD. PURPOSE: To investigate WM functional alterations and the functional interaction between GM and WM networks in medication-naïve MDD. STUDY TYPE: Prospective. SUBJECTS: Sixty-eight patients with MDD and 66 age- and sex-matched healthy controls (HCs). FIELD STRENGTH/SEQUENCE: Resting state-functional MRI (fMRI) using a gradient-echo imaging sequence and T1 -weighted images were acquired at 3.0T. ASSESSMENT: Functional GM and WM networks, based on resting-state blood oxygenation level-dependent (BOLD) signals, were identified by the K-means clustering algorithm, and FC matrices were obtained for each subject. STATISTICAL TESTS: Two-sample t-tests, Pearson chi-square test, and Pearson correlation analysis. RESULTS: Both the GM and WM of the visual network (GM1 and WM11) showed reduced FC with the sensorimotor network (WM5 and GM8), lateral temporal network (GM5 and WM6), cingulo-opercular network (GM9), and dorsal attention network (GM7) in MDD patients compared to controls (P < 0.05, false discovery rate [FDR]-corrected). Reduced FC between the anterior cingulum network (WM3) and the lateral temporal network (GM5 and WM6) and temporal pole network (GM13) and between GM13 and the medial temporal network (GM4) and medial prefrontal-subcortical network (GM10) were also observed in MDD patients (P < 0.05, FDR-corrected). In addition, the WM BOLD signal in the sensorimotor network was negatively correlated with illness duration (r = -0.286, P = 0.018). DATA CONCLUSION: Disconnectivity between the GM and WM networks in the perception-motor system may be the foundation of extensively disrupted connections in MDD. Furthermore, the observed decoupling between subsystems of the default mode network may help explain previous findings of persistent negative rumination and theory of mind deficits in depression. LEVEL OF EVIDENCE: 3. TECHNICAL EFFICACY: Stage 3.

Dynamic changes of T-lymphocyte subsets and the correlations with 89 patients with coronavirus disease 2019 (COVID-19).

BACKGROUND: In December 2019, an outbreak of coronavirus disease 2019 (COVID-19), caused by a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), occurred in Wuhan City, Hubei Province, China. The coronavirus has spread throughout the world, posing a severe threat to human health. By using flow cytometry, here we observed the dynamic changes of peripheral blood T lymphocyte subsets in COVID-19 patients, with an attempt to explore their roles in the pathogenesis of COVID-19 and their impacts on prognosis. METHODS: Eighty-nine COVID-19 patients were divided into a moderate group (n=70) and the severe/critical group (n=19) according to the disease severity. Furthermore, the severe/critical patients were divided into the improved group (n=14) and unimproved group (n=5) according to the outcomes. The absolute peripheral blood lymphocytes counts and subsets, including CD45+, CD3+, CD4+, and CD8+, in the acute phase, and flow cytometry measured the recovery phase for all patients. Then, the results were compared with those in the normal control group. RESULTS: The absolute counts of lymphocytes, T lymphocytes, and their subsets decreased during the acute phase in COVID-19 patients, especially in the severe/critical group. The T-lymphocyte count reached the lowest point on the 14th day in the severe/critical group. It rose with fluctuations to the normal level in the improved group as the immune function recovered; in the unimproved group, however, the T-lymphocyte count remained at a low level or even continued to decrease. The percentages of CD4+ and CD8+ T lymphocytes showed no visible change in the improved group; however, the percentage of CD8+ T cells dropped in the unimproved group, resulting in higher CD4+/CD8+ ratio. CONCLUSIONS: T lymphocytes count, and their subsets can be used for monitoring the immune functions and predicting the prognosis of COVID-19 patients.

Diagnostic and prognostic predictive values of circulating KL-6 for interstitial lung disease: A PRISMA-compliant systematic review and meta-analysis.

BACKGROUND: Past investigations showed inconsistent results for diagnostic and prognostic predictive values of Krebs von den Lungen-6 (KL-6) for interstitial lung disease (ILD). METHODS: Web of Science and PubMed were systematically searched on for articles exploring the association of KL-6 and ILDs published between September 1993 and March 2019. For comparisons between-groups, the standard mean difference and 95% confidence intervals (CIs) were computed as the effect sizes. For diagnostic studies, a summary of sensitivity, specificity, positive likelihood ratios, negative likelihood ratios, and diagnostic odds ratio, which indicated the accuracy of KL-6 in the differentiation of ILDs and no ILDs, were calculated from the true positive, true negative, false positive, and false negative of each study. In addition, the summary receive-operating characteristics curve was constructed to summarize the TP and FP rates. For follow-up study, we computed hazard ratios (HRs) and 95% CIs for mortality. ILD patients showed elevated concentrations of KL-6, compared to healthy controls and patients without ILD. RESULTS: The meta-analysis showed a sensitivity (0.85 [95% CI: 0.77-0.91]) and specificity (0.97 [95% CI: 0.90-0.99]) of KL-6 for ILDs. In addition, it showed elevated baseline circulating levels of KL-6 in subsequent active ILD, compared to subsequent inactive ILD. Moreover, there was a significant association between baseline levels of circulating KL-6 and mortality of ILD (HR 2.95, 95% CI 2.45-3.55, I = 65.9%, P = .032). CONCLUSION: In conclusion, the study suggested that circulating KL-6 showed diagnostic and prognostic predictive values for ILDs.

The Role of Old Photos in Reminiscence Therapy in Elderly Women With Depressive Symptoms: A Functional Magnetic Resonance Imaging Study.

BACKGROUND: Although evidence shows that reminiscence therapy relieves depression in the elderly, few studies have explored its mechanisms and it is unclear whether old public photos rather than personal photos are effective prompts. OBJECTIVES: The aims of this functional magnetic resonance imaging (fMRI) study with an event-related design were to explore whether old public photos can evoke autobiographical memories and compare brain-activation responses to photos between elderly women with depressive symptoms (DS) and normal controls (NC). METHODS: Elderly women with DS (n = 16) and NC (n = 18) were recruited from urban communities in Southwest China. Participants responded with a key press to indicate which of 40 photos evoked autobiographical memories at first sight during 3.0 T scanning. Afterward, they rated photos on a 9-point Likert-type scale on the degrees of recall (DOR), arousal, and pleasure elicited and the degree to which photos felt old. RESULTS: Mean DOR scores were 8.47 ± 0.77 and 1.37 ± 1.09 for high- and low-DOR photos, respectively. Response time was longer in DS compared to NC participants. Brain areas activated by exposure to high-DOR photos differed between groups, with reminiscence leading to decreased activation of the bilateral superior temporal gyrus, left inferior frontal gyrus, right parahippocampal gyrus, left cingulate gyrus, right insular lobe, and bilateral cerebellum anterior lobe in DS compared to NC participants. CONCLUSION: Old public photos can evoke autobiographical memory. DS are associated with brain dysfunction. Early intervention for DS is recommended in the elderly.