Plasma alpha-trypsin inhibitor heavy chain 4 as an age-specific biomarker in the diagnosis and treatment of major depressive disorder.

Background: The diagnosis of major depressive disorder (MDD) mainly depends on subjective clinical symptoms, without an acceptable objective biomarker for the clinical application of MDD. Inter-alpha-trypsin inhibitor heavy chain 4 (ITIH4) showed a high specificity as biomarker for the diagnosis and treatment of MDD. The present study aimed to investigate differences in plasma ITIH4 in two different aged MDD patients and underlying pathological mechanisms of plasma ITIH4 in the occurrence and development of MDD. Methods: Sixty-five adult MDD patients, 51 adolescent MDD patients, and 64 healthy controls (HCs) were included in the present study. A 14-days' antidepressive treatment was conducted in all MDD patients. Psychological assessments were performed and plasma ITIH4 and astrocyte-related markers were detected for all participants. Results: (1) Plasma levels of ITIH4 in adult MDD patients were significantly higher than adolescent MDD patients and HCs, and significantly increased plasma ITIH4 levels was observed in adolescent MDD patients compared with HCs (2). There were positive correlations between plasma ITIH4 levels and 24-item Hamilton Depression Scale (HAMD-24) scores and plasma glial fibrillary acidic protein (GFAP) levels in MDD patients, however, plasma ITIH4 levels were significantly correlated with age just in adult MDD patients (3). Plasma ITIH4 showed area under the curve values of 0.824 and 0.729 to differentiate adult MDD patients and adolescent MDD patients from HCs, respectively (4). There was significant decrease in plasma levels of ITIH4 between before and after antidepressive treatment in adult MDD patients, but not in adolescent MDD patients (5). Changed value of ITIH4 levels were correlated with the changed value of GFAP levels and changed rate of HAMD-24 scores in adult MDD patients following antidepressive treatment. Conclusion: Plasma ITIH4 may be potential plasma biomarkers of MDD with age-related specificity, which was associated with depressive symptoms astrocyte-related pathologic changes, and antidepressive treatment efficacy.

Dynamic functional network connectivity in patients with a mismatch between white matter hyperintensity and cognitive function.

Objective: White matter hyperintensity (WMH) in patients with cerebral small vessel disease (CSVD) is strongly associated with cognitive impairment. However, the severity of WMH does not coincide fully with cognitive impairment. This study aims to explore the differences in the dynamic functional network connectivity (dFNC) of WMH with cognitively matched and mismatched patients, to better understand the underlying mechanisms from a quantitative perspective. Methods: The resting-state functional magnetic resonance imaging (rs-fMRI) and cognitive function scale assessment of the patients were acquired. Preprocessing of the rs-fMRI data was performed, and this was followed by dFNC analysis to obtain the dFNC metrics. Compared the dFNC and dFNC metrics within different states between mismatch and match group, we analyzed the correlation between dFNC metrics and cognitive function. Finally, to analyze the reasons for the differences between the mismatch and match groups, the CSVD imaging features of each patient were quantified with the assistance of the uAI Discover system. Results: The 149 CSVD patients included 20 cases of "Type I mismatch," 51 cases of Type I match, 38 cases of "Type II mismatch," and 40 cases of "Type II match." Using dFNC analysis, we found that the fraction time (FT) and mean dwell time (MDT) of State 2 differed significantly between "Type I match" and "Type I mismatch"; the FT of States 1 and 4 differed significantly between "Type II match" and "Type II mismatch." Correlation analysis revealed that dFNC metrics in CSVD patients correlated with executive function and information processing speed among the various cognitive functions. Through quantitative analysis, we found that the number of perivascular spaces and bilateral medial temporal lobe atrophy (MTA) scores differed significantly between "Type I match" and "Type I mismatch," while the left MTA score differed between "Type II match" and "Type II mismatch." Conclusion: Different mechanisms were implicated in these two types of mismatch: Type I affected higher-order networks, and may be related to the number of perivascular spaces and brain atrophy, whereas Type II affected the primary networks, and may be related to brain atrophy and the years of education.

Precise, Sensitive Detection of Viable Foodborne Pathogenic Bacteria with a 6-Order Dynamic Range via Digital Rolling Circle Amplification.

The presence of viable pathogenic bacteria in food can lead to serious foodborne diseases, thus posing a risk to human health. Here, we develop a digital rolling circle amplification (dRCA) assay that enables the precise and sensitive quantification of viable foodborne pathogenic bacteria. Directly targeting pathogenic RNAs via a ligation-based padlock probe allows for precisely discriminating viable bacteria from dead one. The one-target-one-amplicon characteristic of dRCA enables high sensitivity and a broad quantitative detection range, conferring a detection limit of 10 CFU/mL and a dynamic range of 6 orders. dRCA can detect rare viable bacteria, even at a proportion as low as 0.1%, which is 50 times more sensitive than the live/dead staining method. The high sensitivity for detecting viable bacteria accommodates dRCA for assessing sterilization efficiency. Based on the assay, we found that, for pasteurization, slightly elevating the temperature to 68 °C can reduce the heating time to 10 min, which may minimize nutrient degradation caused by high-temperature exposure. The assay can serve as a precise tool for estimating the contamination by viable pathogenic bacteria and assessing sterilization, which facilitates food safety control.

The alterations in CD4+Treg cells across various phases of major depression.

BACKGROUND: Major depression (MD) is recurrent and devastating mental disease with a high worldwide prevalence. Mounting evidence suggests neuroinflammation triggers cellular immune dysregulation, characterized by increased proportions of circulating monocytes, and T helper 17 cells and proinflammatory cytokines, thereby increasing susceptibility to MD. However, there is ambiguity in the findings of clinical studies that investigate CD4+ T regulatory (Treg) cells in MD. METHODS: The proportion of CD4+ Treg cell from blood mononuclear cells was examined using flow cytometry in healthy controls (HCs: n = 96) and patients with first (FEMD: n = 62) or recurrent (RMD: n = 41) disease episodes of MD at baseline (T0; hospital admission) and after a two-week antidepressant treatment (T14). All participants underwent comprehensive neuropsychological assessments. RESULTS: The initial scores on emotional assessments in patients with MD significantly differed from those of HCs. Both FEMD and RMD patients exhibited a significant decrease in CD4+ Treg cell proportion at baseline compared to HCs. Treg cell proportion rose significantly from T0 to T14 in FEMD patients, who responded to antidepressant therapy, whereas no significant changes were observed in FEMD patients in non-response as well as RMD patients. The improvement of 24-item Hamilton Depression Scale was correlate with changes of Treg cell proportion from T0 to T14 in FEMD patients in response, and the change in Treg cell proportion over a 14-day period exhibited an AUC curve of 0.710. CONCLUSIONS: A decrease in the proportion of CD4+ Treg cells points towards immune system abnormalities in patients with MD. Furthermore, our finding suggests that the immune activation state varies across different stages of depression.

Identifying gut microbiota with high specificity for ischemic stroke with large vessel occlusion.

Gut microbiota can regulate the metabolic and immunological aspects of ischemic stroke and modulate the treatment effects. The present study aimed to identify specific changes in gut microbiota in patients with large vessel occlusion (LVO) ischemic stroke and assess the potential association between gut microbiota and clinical features of ischemic stroke. A total of 63 CSVD patients, 64 cerebral small vessel disease (CSVD) patients, and 36 matching normal controls (NCs) were included in this study. The fecal samples were collected for all participants and analyzed for gut microbiota using 16S rRNA gene sequencing technology. The abundances of five gut microbiota, including genera Bifidobacterium, Butyricimonas, Blautia, and Dorea and species Bifidobacterium_longum, showed significant changes with high specificity in the LVO patients as compared to the NCs and CSVD patients. In LVO patients, the genera Bifidobacterium and Blautia and species Bifidobacterium_longum were significantly correlated with the National Institutes of Health Stroke Scale (NIHSS) scores at the admission and discharge of the patients. Serum triglyceride levels could significantly affect the association of the abundance of genus Bifidobacterium and species Bifidobacterium_longum with the NIHSS scores at admission and modified Rankin Scale (mRS) at discharge in LVO patients. The identification of five gut microbiota with high specificity were identified in the early stage of LVO stroke, which contributed to performed an effective clinical management for LVO ischemic stroke.

Macrophage Migration Inhibitory Factor as a Potential Plasma Biomarker of Cognitive Impairment in Cerebral Small Vessel Disease.

As the pathogenesis of cerebral small vessel disease with cognitive impairment (CSVD-CI) remains unclear, identifying effective biomarkers can contribute to the clinical management of CSVD-CI. This study recruited 54 healthy controls (HCs), 60 CSVD-CI patients, and 57 CSVD cognitively normal (CSVD-CN) patients. All participants underwent neuropsychological assessments and multimodal magnetic resonance imaging. Macrophage migration inhibitory factors (MIFs) were assessed in plasma. The least absolute shrinkage and selection operator model was used to determine a composite marker. Compared with HCs or CSVD-CN patients, CSVD-CI patients had significantly increased plasma MIF levels. In CSVD-CI patients, plasma MIF levels were significantly correlated with multiple cognitive assessment scores, plasma levels of blood-brain barrier (BBB)-related indices, white matter hyperintensity Fazekas scores, and the mean amplitude of low-frequency fluctuation in the right superior temporal gyrus. Higher plasma MIF levels were significantly associated with worse global cognition and information processing speed in CSVD-CI patients. The composite marker (including plasma MIF) distinguished CSVD-CI patients from CSVD-CN and HCs with >80% accuracy. Meta-analysis indicated that blood MIF levels were significantly increased in CSVD-CI patients. In conclusion, plasma MIF is a potential biomarker for early identification of CSVD-CI. Plasma MIF may play a role in cognitive decline in CSVD through BBB dysfunction and changes in white matter hyperintensity and brain activity.

Plasma circRNA HIPK2 as a putative biomarker for the diagnosis and prediction of therapeutic effects in major depressive disorder.

BACKGROUND: Circular RNAs (circRNAs) are a prevalent type of non-coding RNAs exhibiting extensive expression in mammalian cells. Owing to their involvement in diverse pathophysiological mechanisms of major depressive disorder (MDD) and their inherent stability in peripheral blood, circRNAs have emerged as potential biomarkers of considerable significance. This study aimed to identify and validate circular RNA HIPK2 (circHIPK2) in MDD patients and to investigate its potential as a biomarker for the diagnosis and prognosis of MDD. METHODS: Patients with MDD (n = 81) and healthy controls (HCs) (n = 48) were recruited for our study (October 2022 to June 2023). The expression of circHIPK2 in plasma was assessed using absolute quantitative polymerase chain reaction (qPCR). RESULTS: The expression of circHIPK2 in plasma of patients with MDD exhibited a significant increase compared to HCs. The circHIPK2 levels showed an area under the curve (AUC) of 0.796, corresponding to a specificity of 97.9% and a sensitivity of 60.4% in diagnosing MDD. Additionally, the rate of change in circHIPK2 over a 14-day period exhibited an AUC curve of 0.819, indicating its predictive value for antidepressive effects. CONCLUSIONS: CircHIPK2 could serve as a potential biomarker for diagnosing MDD and predicting therapeutic effects of MDD.

Non-inferiority of intermittent theta burst stimulation over the left V1 vs. classical target for depression: A randomized, double-blind trial.

BACKGROUND: Repetitive transcranial magnetic stimulation (rTMS) targeting the visual cortex (VC) has shown antidepressant effects for major depressive disorder (MDD) in sham-controlled trials, but comparisons with rTMS targeting the left dorsolateral prefrontal cortex (DLPFC) are lacking. We aimed to determine the non-inferiority of intermittent theta-burst stimulation (iTBS) over VC vs DLPFC for MDD. METHODS: Participants randomly received navigated iTBS over the left V1 or the left DLPFC twice daily for 14 days with a 3-month follow-up. The primary outcome was change in Hamilton Depression Rating Scale (HAMD-17) score from baseline to treatment end, with 2.5 points as the non-inferiority margin. Secondary outcomes included: improvement in Montgomery-Asberg Depression Rating Scale (MADRS), Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA); response and remission rates; suicidal ideation and adverse events. RESULTS: Of 75 randomized patients, 67 completed full treatment, including 52 first-episode patients and 15 relapsers. The primary outcome indicated the non-inferiority of VC (adjusted difference 1.14, lower 97.5 % CI -1.24; p = .002), confirmed by improvements in objective cognitive task and protein levels, as did most secondary outcomes. Reduced suicidal ideation after treatment, incidence of eye discomfort and pain score were lower in the VC group. CONCLUSIONS: Left VC iTBS has the potential to be non-inferior to DLPFC iTBS in most first-episode MDD in improving depressive symptoms and cognitive function, with less suicidal ideation and adverse events. LIMITATIONS: Given the limited sample size, the lack of a sham control and the use of antidepressants, the findings should be interpreted with caution.

Potential Association of Neutrophil Extracellular Traps With Cognitive Impairment in Cerebral Small Vessel Disease.

No acceptable biomarker can facilitate the early identification of cognitive impairment associated with cerebral small vessel disease (CSVD) in the older persons. The neutrophil extracellular traps (NETs) in the inflammation response of circulatory and central systems are essential in destroying the blood-brain barrier. The present study aims to explore the potential associations of plasma NETs with cognitive performance in CSVD. We recruited 146 CSVD patients and 66 healthy controls (HCs), and comprehensive neuropsychological assessments and multimodal magnetic resonance imaging were conducted. Three NETs markers, namely citrullination of histone H3, neutrophil elastase-DNA, and myeloperoxidase (MPO)-DNA, and 4 oxidative stress-related indexes in plasma samples, were measured. The plasma levels of 3 NETs markers were more significantly elevated in CSVD patients than in HCs. Significant correlations of the 3 NETs markers were observed with multiple cognitive domain scores. Furthermore, higher plasma malondialdehyde and NETs levels were significantly associated with the worse Montreal Cognitive Assessment scores among CSVD patients. Moreover, plasma MPO-DNA levels significantly mediated the effect of the amplitude of low-frequency fluctuation value within the bilateral caudate and the scores of global cognitive function, executive function, and information processing speed. Additionally, a panel of 3 NETs markers had the highest area under the curve value to distinguish the cognitively impaired CSVD patients from HCs and nonimpaired ones. Therefore, plasma NETs may be potential biomarkers for early diagnosis of CSVD-related cognitive impairment. Activated lipid peroxidation in circulation and impaired caudate function support potential associations of plasma NETs in cognitively impaired CSVD patients.

Alteration and clinical potential in gut microbiota in patients with cerebral small vessel disease.

Background: Cerebral small vessel disease (CSVD) is a cluster of microvascular disorders with unclear pathological mechanisms. The microbiota-gut-brain axis is an essential regulatory mechanism between gut microbes and their host. Therefore, the compositional and functional gut microbiota alterations lead to cerebrovascular disease pathogenesis. The current study aims to determine the alteration and clinical value of the gut microbiota in CSVD patients. Methods: Sixty-four CSVD patients and 18 matched healthy controls (HCs) were included in our study. All the participants underwent neuropsychological tests, and the multi-modal magnetic resonance imaging depicted the changes in brain structure and function. Plasma samples were collected, and the fecal samples were analyzed with 16S rRNA gene sequencing. Results: Based on the alpha diversity analysis, the CSVD group had significantly decreased Shannon and enhanced Simpson compared to the HC group. At the genus level, there was a significant increase in the relative abundances of Parasutterella, Anaeroglobus, Megasphaera, Akkermansia, Collinsella, and Veillonella in the CSVD group. Moreover, these genera with significant differences in CSVD patients revealed significant correlations with cognitive assessments, plasma levels of the blood-brain barrier-/inflammation-related indexes, and structural/functional magnetic resonance imaging changes. Functional prediction demonstrated that lipoic acid metabolism was significantly higher in CSVD patients than HCs. Additionally, a composite biomarker depending on six gut microbiota at the genus level displayed an area under the curve of 0.834 to distinguish CSVD patients from HCs using the least absolute shrinkage and selection operator (LASSO) algorithm. Conclusion: The evident changes in gut microbiota composition in CSVD patients were correlated with clinical features and pathological changes of CSVD. Combining these gut microbiota using the LASSO algorithm helped identify CSVD accurately.

The impact of iron deposition on the fear circuit of the brain in patients with Parkinson's disease and anxiety.

Objective: Anxiety is one of the most common psychiatric symptoms of Parkinson's disease (PD), and brain iron deposition is considered to be one of the pathological mechanisms of PD. The objective of this study was to explore alterations in brain iron deposition in PD patients with anxiety compared to PD patients without anxiety, especially in the fear circuit. Methods: Sixteen PD patients with anxiety, 23 PD patients without anxiety, and 26 healthy elderly controls were enrolled prospectively. All subjects underwent neuropsychological assessments and brain magnetic resonance imaging (MRI) examinations. Voxel-based morphometry (VBM) was used to study morphological brain differences between the groups. Quantitative susceptibility mapping (QSM), an MRI technique capable of quantifying susceptibility changes in brain tissue, was used to compare susceptibility changes in the whole brain among the three groups. The correlations between brain susceptibility changes and anxiety scores quantified using the Hamilton Anxiety Rating Scale (HAMA) were compared and analyzed. Results: PD patients with anxiety had a longer duration of PD and higher HAMA scores than PD patients without anxiety. No morphological brain differences were observed between the groups. In contrast, voxel-based and ROI-based QSM analyses showed that PD patients with anxiety had significantly increased QSM values in the medial prefrontal cortex, anterior cingulate cortex, hippocampus, precuneus, and angular cortex. Furthermore, the QSM values of some of these brain regions were positively correlated with the HAMA scores (medial prefrontal cortex: r = 0.255, p = 0.04; anterior cingulate cortex: r = 0.381, p < 0.01; hippocampus: r = 0.496, p < 0.01). Conclusion: Our findings support the idea that anxiety in PD is associated with iron burden in the brain fear circuit, providing a possible new approach to explaining the potential neural mechanism of anxiety in PD.

Combination of platelet-to-lymphocyte ratio and D-dimer for the identification of cardiogenic cerebral embolism in non-valvular atrial fibrillation.

Background: Non-valvular atrial fibrillation (NVAF) is the most common cause of cardiogenic cerebral embolism (CCE). However, the underlying mechanism between cerebral embolism and NVAF is indefinite, and there is no effective and convenient biomarker to identify potential risk of CCE in patients with NVAF in clinic. The present study aims to identify risk factors for interpreting the potential association of CCE with NVAF and providing valuable biomarkers to predict the risk of CCE for NVAF patients. Methods: 641 NVAF patients diagnosed with CCE and 284 NVAF patients without any history of stroke were recruited in the present study. Clinical data including demographic characteristics, medical history, and clinical assessments, were recorded. Meanwhile, Blood cell counts, lipid profiles, high-sensitivity C-reactive protein, and coagulation function-related indicators were measured. Least absolute shrinkage and selection operator (LASSO) regression analysis was utilized to build a composite indicator model based on the blood risk factors. Results: (1) CCE patients had significantly increased neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio (PLR), and D-dimer levels as compared with patients in the NVAF group, and these three indicators can distinguish CCE patients from ones in the NVAF group with an area under the curve (AUC) value of over 0.750, respectively. (2) Using the LASSO model, a composite indicator, i.e., the risk score, was determined based on PLR and D-dimer and displayed differential power for distinguishing CCE patients from NVAF patients with an AUC value of over 0.934. (3) The risk score was positively correlated with the National Institutes of Health Stroke Scale and CHADS2 scores in CCE patients. (4) There was a significant association between the change value of the risk score and the recurrence time of stroke in initial CCE patients. Conclusions: The PLR and D-dimer represent an aggravated process of inflammation and thrombosis in the occurrence of CCE after NVAF. The combination of these two risk factors can contribute to identifying the risk of CCE for patients with NVAF with an accuracy of 93.4%, and the greater in change of composite indicator, the shorter in the recurrence of CCE for NVAF patients.

Episodic Memory-Related Imaging Features as Valuable Biomarkers for the Diagnosis of Alzheimer's Disease: A Multicenter Study Based on Machine Learning.

BACKGROUND: Individualized and reliable biomarkers are crucial for diagnosing Alzheimer's disease (AD). However, lack of accessibility and neurobiological correlation are the main obstacles to their clinical application. Machine learning algorithms can effectively identify personalized biomarkers based on the prominent symptoms of AD. METHODS: Episodic memory-related magnetic resonance imaging (MRI) features of 143 patients with amnesic mild cognitive impairment (MCI) were identified using a multivariate relevance vector regression algorithm. The support vector machine classification model was constructed using these MRI features and verified in 2 independent datasets (N = 994). The neurobiological basis was also investigated based on cognitive assessments, neuropathologic biomarkers of cerebrospinal fluid, and positron emission tomography images of amyloid-ß plaques. RESULTS: The combination of gray matter volume and amplitude of low-frequency fluctuation MRI features accurately predicted episodic memory impairment in individual patients with amnesic MCI (r = 0.638) when measured using an episodic memory assessment panel. The MRI features that contributed to episodic memory prediction were primarily distributed across the default mode network and limbic network. The classification model based on these features distinguished patients with AD from normal control subjects with more than 86% accuracy. Furthermore, most identified episodic memory-related regions showed significantly different amyloid-ß positron emission tomography measurements among the AD, MCI, and normal control groups. Moreover, the classification outputs significantly correlated with cognitive assessment scores and cerebrospinal fluid pathological biomarkers' levels in the MCI and AD groups. CONCLUSIONS: Neuroimaging features can reflect individual episodic memory function and serve as potential diagnostic biomarkers of AD.

Machine learning-based characterization of cuprotosis-related biomarkers and immune infiltration in Parkinson's disease.

Background: Parkinson's disease (PD) is a neurodegenerative disease commonly seen in the elderly. On the other hand, cuprotosis is a new copper-dependent type of cell death that can be observed in various diseases. Methods: This study aimed to identify potential novel biomarkers of Parkinson's disease by biomarker analysis and to explore immune cell infiltration during the onset of cuprotosis. Gene expression profiles were retrieved from the GEO database for the GSE8397, GSE7621, GSE20163, and GSE20186 datasets. Three machine learning algorithms: the least absolute shrinkage and selection operator (LASSO), random forest, and support vector machine-recursive feature elimination (SVM-RFE) were used to screen for signature genes for Parkinson's disease onset and cuprotosis-related genes (CRG). Immune cell infiltration was estimated by ssGSEA, and cuprotosis-related genes associated with immune cells and immune function were examined using spearman correlation analysis. Nomogram was created to validate the accuracy of these cuprotosis-related genes in predicting PD disease progression. Classification of Parkinson's specimens using consensus clustering methods. Result: Three PD datasets from the Gene Expression Omnibus (GEO) database were combined after eliminating batch effects. By ssGSEA, we identified three cuprotosis-related genes ATP7A, SLC31A1, and DBT associated with immune cells or immune function in PD and more accurate for the diagnosis of Parkinson's disease course. Patients could benefit clinically from a characteristic line graph based on these genes. Consistent clustering analysis identified two subtypes, with the C2 subtype exhibiting higher immune cell infiltration and immune function. Conclusion: In conclusion, our study reveals that several newly identified cuprotosis-related genes intervene in the progression of Parkinson's disease through immune cell infiltration.

Potential of brain age in identifying early cognitive impairment in subcortical small-vessel disease patients.

Background: Reliable and individualized biomarkers are crucial for identifying early cognitive impairment in subcortical small-vessel disease (SSVD) patients. Personalized brain age prediction can effectively reflect cognitive impairment. Thus, the present study aimed to investigate the association of brain age with cognitive function in SSVD patients and assess the potential value of brain age in clinical assessment of SSVD. Materials and methods: A prediction model for brain age using the relevance vector regression algorithm was developed using 35 healthy controls. Subsequently, the prediction model was tested using 51 SSVD patients [24 subjective cognitive impairment (SCI) patients and 27 mild cognitive impairment (MCI) patients] to identify brain age-related imaging features. A support vector machine (SVM)-based classification model was constructed to differentiate MCI from SCI patients. The neurobiological basis of brain age-related imaging features was also investigated based on cognitive assessments and oxidative stress biomarkers. Results: The gray matter volume (GMV) imaging features accurately predicted brain age in individual patients with SSVD (R 2 = 0.535, p < 0.001). The GMV features were primarily distributed across the subcortical system (e.g., thalamus) and dorsal attention network. SSVD patients with age acceleration showed significantly poorer Mini-Mental State Examination and Montreal Cognitive Assessment (MoCA) scores. The classification model based on GMV features could accurately distinguish MCI patients from SCI patients (area under the curve = 0.883). The classification outputs of the classification model exhibited significant associations with MoCA scores, Trail Making Tests A and B scores, Stroop Color and Word Test C scores, information processing speed total scores, and plasma levels of total antioxidant capacity in SSVD patients. Conclusion: Brain age can be accurately quantified using GMV imaging data and shows potential clinical value for identifying early cognitive impairment in SSVD patients.

Circular RNA FUNDC1 for Prediction of Acute Phase Outcome and Long-Term Survival of Acute Ischemic Stroke.

Circular RNAs (CircRNAs) have shown promising potential in the diagnosis and the prediction of outcomes of stroke. This study aimed to explore the potential value of circRNAs for identifying acute neurological deterioration and estimating long-term survival for acute ischemic stroke (AIS). One hundred healthy controls and 200 patients with AIS within 72 h were recruited, 140 of whom were admitted within 24 h after onset. CircRNA levels in peripheral blood were measured by quantitative polymerase chain reaction (qPCR). Compared to the controls, the levels of three circRNAs were significantly increased in three subgroups of patients, including large artery atherosclerosis (LAA) stroke, small artery occlusion (SAO) stroke, and cardioembolism (CE) stroke (all P < 0.001). Among, LAA stroke patients had higher levels of circular RNA FUNDC1 (circFUNDC1) compared to SAO stroke patients (P = 0.015). CircFUNDC1 levels were positively correlated with National Institutes of Health Stroke Scale (NIHSS) scores on the 7th day only in LAA patients (P = 0.048, r = 0.226). It should be noted that the levels of circFUNDC1 in patients with early neurological deterioration (END), admitted within 24 h after onset, were significantly higher than those without END (P = 0.013). In addition, circFUNDC1 levels positively correlated with baseline NIHSS scores (P = 0.016, r = 0.203) or the 7th day NIHSS scores (P = 0.001, r = 0.289) in patients within 24 h after onset. Importantly, after 18 months of follow-up, a significant difference was observed on survival Kaplan-Meier curves (P = 0.042) between AIS patients with low (below cut-off) or high circFUNDC1 levels (above cut-off). Circulating circFUNDC1 could be a potential biomarker for predicting acute-phase outcome and long-term survival in AIS.

Platelet-Derived Amyloid-ß Protein Precursor as a Biomarker of Alzheimer's Disease.

BACKGROUND: Platelet proteins may be associated with Alzheimer's disease (AD) pathology. OBJECTIVE: To investigate the relationship between platelet proteins and cerebrospinal fluid (CSF) biomarkers of AD and cognition in individuals with memory decline to identify effective screening methods for detecting the early stages of the disease. METHODS: We classified 68 participants with subjective memory decline according to the ATN framework determined by CSF amyloid-ß (A), CSF p-tau (T), and t-tau (N). All participants underwent Mini-Mental State Examination (MMSE) and platelet-related protein content testing. RESULTS: Eighteen participants had normal AD biomarkers (NCs), 24 subjects had non-AD pathologic changes (non-AD), and 26 subjects fell within the Alzheimer's continuum (AD). The platelet amyloid-ß protein precursor (AßPP) ratio in the AD group was significantly lower than in the non-AD and NCs groups, and positively correlated with MMSE scores and CSF amyloid-ß42 level, which could affect MMSE scores through CSF amyloid-ß42. Levels of platelet phosphorylated-tau 231 and ser396/404 phosphorylated tau were elevated in both AD and non-AD compared to NCs. Additionally, the receiver operating characteristic analysis demonstrated that the platelet AßPP ratio was a sensitive identifier for differentiating the AD from NCs (AUC = 0.846) and non-AD (AUC = 0.768). And ser396/404 phosphorylated tau could distinguish AD from NCs. CONCLUSION: Our study was the first to find an association between platelet AßPP ratio and CSF biomarkers of AD, which contribute to the understanding of the peripheral changes in AD. These findings may help to discover potential feasible and effective screening tools for AD.

Selective activation of ABCA1/ApoA1 signaling in the V1 by magnetoelectric stimulation ameliorates depression via regulation of synaptic plasticity.

Emerging evidence suggests that dysfunction of the visual cortex may be involved in major depressive disorder (MDD). However, the underlying mechanisms remain unclear. We previously established that combined magnetic stimulation system treatment (c-MSST) resulted in an antidepressant effect in mice. In the present study, we found that V1-targeted c-MSST induced significant antidepressant effects in chronic unpredictable mild stress (CUMS)- and lipopolysaccharide (LPS)-treated mice. Proteomic screening investigation and repeatable validation revealed that expression of the V1 neuronal ATP-binding cassette transporter A1 (ABCA1) and apolipoprotein A-1 (ApoA1) was downregulated in CUMS mice, an effect that was normalized by c-MSST. Neuron-specific knockdown of ABCA1 in V1 blocked c-MSST's antidepressant effects. Mechanistically, CUMS reduced dendritic spine density and long-term plasticity in V1, and these deficits were reversed by c-MSST. V1-targeted c-MSST was found to induce rapid antidepressant effects that are mediated by alterations in synaptic plasticity via the ABCA1/ApoA1 signaling pathway in V1.

Effects of standard treatments on depressive/anxiety symptoms in patients with inflammatory bowel disease: A systematic review and meta-analysis.

OBJECTIVE: A combination of inflammatory bowel disease (IBD) and psychological comorbidities can influence the natural course of IBD. A systematic review and meta-analysis was performed to examine whether a standard IBD medical therapy without any antipsychotic intervention has beneficial effects on depression/anxiety in IBD patients. METHODS: PubMed and Web of Science databases were systematically searched for related literature from their inception to March 2020. The random-effects model was used to calculate the standardized mean difference (SMD). A total of 16 eligible studies were included in the present meta-analysis. RESULTS: Compared with baseline assessments, IBD patients with standard IBD medication had significantly reduced depression assessment scores (pooled SMD = 0.500; 95% confidence interval: 0.207, 0.793; P = 0.001). These results were obtained without any psychological interventions. Additionally, no significant differences in anxiety-related scores were detected between the baseline assessments and the end of therapy assessments (pooled SMD = 0.083; 95% confidence interval: -0.120, 0.285; P = 0.425). The meta-regression and subgroup analyses revealed that differences in assessment tools and medications might be the main source of heterogeneity. CONCLUSION: Standard IBD treatments can significantly alleviate the depressive symptoms in IBD patients. However, more studies are needed to analyze this association.