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Abstract Background With the decline of cognitive function in vascular cognitive impairment, the burden on the family and society will increase. Therefore, early identification of vascular mild cognitive impairment (VaMCI) is crucial. The focus of early identification of VaMCI is on the attention of risk factors. Therefore, this study aimed to investigate the relationship between diabetes and VaMCI among the Chinese, hoping to predict the risk of VaMCI by diabetes and to move the identification of vascular cognitive impairment forward. Methods We collected data from seven clinical centers and nine communities in China. All participants were over 50 years of age and had cognitive complaints. We collected basic information of the participants, and cognitive function was professionally assessed by the Montreal Cognitive Assessment scale. Finally, logistic regression analysis was used to analyze the correlation between each factor and VaMCI. Results A total of 2020 participants were included, including 1140 participants with VaMCI and 880 participants with normal cognition. In univariate logistic regression analysis, age, heavy smoking, and diabetes had a positive correlation with VaMCI. At the same time, being married, high education, and light smoking had a negative correlation with VaMCI. After correction, only diabetes (OR = 1.04, 95% CI: 1.01–1.09, p = 0.05) had a positive correlation with VaMCI, and high education (OR = 0.60, 95% CI:.45–.81, p = 0.001) had a negative correlation with VaMCI. Conclusion In our study, we found that diabetes had a positive correlation with VaMCI, and high education had a negative correlation with VaMCI. Therefore, early identification and timely intervention of diabetes may reduce the risk of VaMCI and achieve early prevention of VaMCI.

In this paper, we demonstrate the significant impact of the solution flow and electrical field on the homogeneity of large-scale ZnO nanorod electrodeposition from an aqueous solution containing zinc nitrate and ammonium nitrate, primarily based on the X-ray fluorescence results. The homogeneity can be enhanced by adjusting the counter electrode size and solution flow rate. We have successfully produced relatively uniform nanorod arrays on an 8 × 10 cm2 i-ZnO-coated fluorine-doped tin oxide (FTO) substrate using a compact counter electrode and a vertical stirring setup. The as-grown nanorods exhibit similar surface morphologies and dominant, intense, almost uniform near-band-edge emissions in different regions of the sample. Additionally, the surface reflectance is significantly reduced after depositing the ZnO nanorods, achieving a moth-eye effect through subwavelength structuring. This effect of the nanorod array structure indicates that it can improve the utilization efficiency of light reception or emission in various optoelectronic devices and products. The large-scale preparation of ZnO nanorods is more practical to apply and has an extremely broad application value. Based on the research results, it is feasible to prepare large-scale ZnO nanorods suitable for antireflective coatings and commercial applications by optimizing the electrodeposition conditions.

BackgroundFunctional magnetic resonance imaging (fMRI) studies examining differences in the activity of brain networks between the first depressive episode (FDE) and recurrent depressive episode (RDE) are limited. The current study observed and compared the altered functional connectivity (FC) characteristics in the default mode network (DMN), cognitive control network (CCN), and affective network (AN) between the RDE and FDE. In addition, we further investigated the correlation between abnormal FC and clinical symptoms.MethodsWe recruited 32 patients with the RDE, 31 patients with the FDE, and 30 healthy controls (HCs). All subjects underwent resting-state fMRI. The seed-based FC method was used to analyze the abnormal brain networks in the DMN, CCN, and AN among the three groups and further explore the correlation between abnormal FC and clinical symptoms.ResultsOne-way analysis of variance showed significant differences the FC in the DMN, CCN, and AN among the three groups in the frontal, parietal, temporal, and precuneus lobes and cerebellum. Compared with the RDE group, the FDE group generally showed reduced FC in the DMN, CCN, and AN. Compared with the HC group, the FDE group showed reduced FC in the DMN, CCN, and AN, while the RDE group showed reduced FC only in the DMN and AN. Moreover, the FC in the left posterior cingulate cortices and the right inferior temporal gyrus in the RDE group were positively correlated with the 17-item Hamilton Rating Scale for Depression (HAMD-17), and the FC in the left dorsolateral prefrontal cortices and the right precuneus in the FDE group were negatively correlated with the HAMD-17.ConclusionsThe RDE and FDE groups showed multiple abnormal brain networks. However, the alterations of abnormal FC were more extensive and intensive in the FDE group.

ObjectiveThis study aimed to develop a diagnostic model of multi-kinematic parameters for patients with amnestic mild cognitive impairment (aMCI).MethodIn this cross-sectional study, 94 older adults were included (33 cognitively normal, CN; and 61 aMCI). We conducted neuropsychological battery tests, such as global cognition and cognitive domains, and collected gait parameters by an inertial-sensor gait analysis system. Multivariable regression models were used to identify the potential diagnostic variables for aMCI. Receiver operating characteristic (ROC) curves were applied to assess the diagnostic accuracy of kinematic parameters in discriminating aMCI from healthy subjects.ResultsMultivariable regression showed that multi-kinematic parameters were the potential diagnostic variables for aMCI. The multi-kinematic parameter model, developed using Timed Up and Go (TUG) time, stride length, toe-off/heel stride angles, one-leg standing (OLS) time, and braking force, showed areas under ROC (AUC), 0.96 [95% confidence interval (CI), 0.905–0.857]; sensitivity, 0.90; and specificity, 0.91. In contrast, a single kinematic parameter’s sensitivity was 0.26–0.95 and specificity was 0.21–0.90. Notably, the separating capacity of multi-kinematic parameters was highly similar to Montreal Cognitive Assessment (MoCA; AUC: 0.96 vs. 0.95). Compared to cognitive domain tests, the separating ability was comparable to Auditory Verbal Learning Test (AVLT) and Boston Naming Test (BNT; AUC: 0.96 vs. 0.97; AUC: 0.96 vs. 0.94).ConclusionWe developed one diagnostic model of multi-kinematic parameters for patients with aMCI in Foshan.

ObjectiveIn this study, we used amplitude of low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) to observe differences in local brain functional activity and its characteristics in patients with treatment-resistant depression (TRD) and non-treatment-resistant depression (nTRD), and to explore the correlation between areas of abnormal brain functional activity and clinical symptoms.MethodThirty-seven patients with TRD, 36 patients with nTRD, and 35 healthy controls (HCs) were included in resting-state fMRI scans. ALFF and ReHo were used for image analysis and further correlation between abnormal brain regions and clinical symptoms were analyzed.ResultsANOVA revealed that the significantly different brain regions of ALFF and ReHo among the three groups were mainly concentrated in the frontal and temporal lobes. Compared with the nTRD group, the TRD group had decreased ALFF in the left/right inferior frontal triangular gyrus, left middle temporal gyrus, left cuneus and bilateral posterior lobes of the cerebellum, and increased ALFF in the left middle frontal gyrus and right superior temporal gyrus, and the TRD group had decreased ReHo in the left/right inferior frontal triangular gyrus, left middle temporal gyrus, and increased ReHo in the right superior frontal gyrus. Compared with the HC group, the TRD group had decreased ALFF/ReHo in both the right inferior frontal triangular gyrus and the left middle temporal gyrus. Pearson correlation analysis showed that both ALFF and ReHo values in these abnormal brain regions were positively correlated with HAMD-17 scores (P < 0.05).ConclusionAlthough the clinical symptoms were similar in the TRD and nTRD groups, abnormal neurological functional activity were present in some of the same brain regions. Compared with the nTRD group, ALFF and ReHo showed a wider range of brain area alterations and more complex neuropathological mechanisms in the TRD group, especially in the inferior frontal triangular gyrus of the frontal lobe and the middle temporal gyrus of the temporal lobe.

BackgroundPrevious studies found that transcutaneous auricular vagus nerve stimulation (taVNS) was clinically effective in treating a case of treatment-resistant depression (TRD). However, the brain neural mechanisms underlying the immediate effects of taVNS treatment for TRD have not been elucidated.Materials and MethodsDifferences in the amplitude of low-frequency fluctuations (ALFF) between TRD and healthy control (HC) groups were observed. The TRD group was treated with taVNS for 30 min, and changes in ALFF in the TRD group before and after immediate treatment were observed. The ALFF brain regions altered by taVNS induction were used as regions of interest to analyze whole-brain functional connectivity (FC) changes in the TRD group.ResultsA total of 44 TRD patients and 44 HCs completed the study and were included in the data analysis. Compared with the HC group, the TRD group had increased ALFF in the left orbital area of the middle frontal gyrus. After taVNS treatment, ALFF in the left orbital area of the middle frontal gyrus and right middle frontal gyrus decreased in the TRD group, while ALFF in the right orbital area of the superior frontal gyrus increased. The FC in the left orbital area of the middle frontal gyrus with left middle frontal gyrus and the right inferior occipital gyrus was significantly increased.ConclusionTranscutaneous auricular vagus nerve stimulation demonstrates immediate modulation of functional activity in the emotional network, cognitive control network, and visual processing cortex, and may be a potential brain imaging biomarker for the treatment of TRD.

BackgroundPrevious studies in animals and humans indicated that transcutaneous vagus nerve stimulation (tVNS) and transcutaneous electrical acupoint stimulation (TEAS) on trigeminal nerve-innervated forehead acupoints can relief the symptoms of depression. However, due to the limited investigations on these two interventions, more research are needed to confirm their efficacy in depression. To improve the efficacy of the single treatment, we combined two treatments and created a novel non-invasive stimulation, transcutaneous electrical cranial-auricular acupoint stimulation (TECAS). To assess the efficacy and safety of TECAS, we compare it with a selective serotonin reuptake inhibitor (SSRI), escitalopram, for the treatment of depression.Methods/DesignThis is a multi-center, non-inferiority, randomized controlled trial that will involve 470 patients with mild to moderate depression. Patients will be randomly assigned to either the TECAS group or the escitalopram group in a 1:1 ratio. The TEAS group will receive two sessions of treatments per day for 8 consecutive weeks, and the escitalopram group will receive 8 weeks of oral escitalopram tablets prescribed by clinical psychiatrists as appropriate for their condition. The primary outcome is the clinical response as determined by Montgomery-Åsberg Depression Rating Scale (MADRS) scores at week 8, with −10% as the non-inferior margin. The secondary outcomes include the response rate determined by 17-item Hamilton Depression Rating Scale (HAMD-17), remission rate, changes from baseline in the scores on the MADRS, the HAMD-17, the Hamilton Anxiety Rating Scale (HAMA), the Pittsburgh Sleep Quality Index (PSQI), and the Short Form 36 Health Survey (SF-36).DiscussionThis will be the first randomized controlled trial to compare the efficacy of TECAS with escitalopram for depression. If effective, this novel intervention could have significant clinical and research implications for patients with depression.Clinical Trial Registration[ClinicalTrials.gov], identifier [NCT03909217].

Objective: To provide guidelines for the prevention of post-stroke dementia, we investigated whether stroke patients were aware of post-stroke dementia and their level of dementia-related knowledge. Methods: Five dementia-related questions were designed. A field survey was conducted in a question-and-answer method using the designed questions. The surveys assessed 3000 stroke patients (2 weeks–6 months after stroke attacks) from 14 hospitals/clinical centers in 7 provinces and cities across China. Results: Among 3000 stroke patients, 80.5% had heard of dementia, 39.1% knew that stroke can lead to dementia, 55.7% believed dementia can be prevented, 50.8% thought dementia can be cured, and only 8.8% had ever seen a doctor because of memory deterioration. Then, patients were classified into three groups, including a no cognitive impairment (NCI) group, a mild cognitive impairment (MCI) group, and a mild dementia (MD) group. Among the MCI and MD groups, only 8.7% (75/861) and 9.9% (64/649) of patients, respectively, had ever seen a doctor because of memory deterioration. According to our results, patients with a higher level of cognitive impairment had a lower awareness of dementia (P

A high-performance GaAs nanowire photodetector was fabricated based on the modification of Au nanoparticles (NPs). Au nanoparticles prepared by thermal evaporation were used to modify the defects on the surface of GaAs nanowires. Plasmons and Schottky barriers were also introduced on the surface of the GaAs nanowires, to enhance their light absorption and promote the separation of carriers inside the GaAs nanowires. The research results show that under the appropriate modification time, the dark current of GaAs nanowire photodetectors was reduced. In addition, photocurrent photodetectors increased from 2.39 × 10−10 A to 1.26 × 10−9 A. The responsivity of GaAs nanowire photodetectors correspondingly increased from 0.569 A∙W−1 to 3.047 A∙W−1. The reasons for the improvement of the photodetectors’ performance after modification were analyzed through the energy band theory model. This work proposes a new method to improve the performance of GaAs nanowire photodetectors.

BackgroundStudies on differences in brain function activity between the first depressive episode (FDE) and recurrent depressive episodes (RDE) are scarce. In this study, we used regional homogeneity (ReHo) and amplitude of low-frequency fluctuations (ALFF) as indices of abnormal brain function activity. We aimed to determine the differences in these indices between patients with FDE and those with RDE, and to investigate the correlation between areas of abnormal brain function and clinical symptoms.MethodsA total of 29 patients with RDE, 28 patients with FDE, and 29 healthy controls (HCs) who underwent resting-state functional magnetic resonance imaging were included in this study. The ReHo and ALFF measurements were used for image analysis and further analysis of the correlation between different brain regions and clinical symptoms.ResultsAnalysis of variance showed significant differences among the three groups in ReHo and ALFF in the frontal, parietal, temporal, and occipital lobes. ReHo was higher in the right inferior frontal triangular gyrus and lower in the left inferior temporal gyrus in the RDE group than in the FDE group. Meanwhile, ALFF was higher in the right inferior frontal triangular gyrus, left anterior cingulate gyrus, orbital part of the left middle frontal gyrus, orbital part of the left superior frontal gyrus, and right angular gyrus, but was lower in the right lingual gyrus in the RDE group than in the FDE group. ReHo and ALFF were lower in the left angular gyrus in the RDE and FDE groups than in the HC group. Pearson correlation analysis showed a positive correlation between the ReHo and ALFF values in these abnormal areas in the frontal lobe and the severity of depressive symptoms (P < 0.05). Abnormal areas in the temporal and occipital lobes were negatively correlated with the severity of depressive symptoms (P < 0.05).ConclusionThe RDE and FDE groups had abnormal neural function activity in some of the same brain regions. ReHo and ALFF were more widely distributed in different brain regions and had more complex neuropathological mechanisms in the RDE group than in the FDE group, especially in the right inferior frontal triangular gyrus of the frontal lobe.

ABSTRACT Background Depression is a common mental illness in childhood and adolescence, with an incidence of 4%–5%; it can lead to impairments in learning and social functioning. Transcutaneous auricular vagus nerve stimulation (taVNS) is a commonly used method of auricular acupuncture point stimulation, which is regarded as an effective treatment for adults with depression. The aim of this study was to investigate the efficacy and mechanism of taVNS for adolescents with mild to moderate depression. Methods This randomized controlled clinical trial will include 120 patients aged 12–16 years, all of whom are diagnosed with mild to moderate depression. Patients will be randomly assigned to a taVNS group and a drug control group (sertraline hydrochloride) at a ratio of 1:1. Patients will be evaluated using the 17‐item Hamilton Depression Scale, Hamilton Anxiety Rating Scale, Self‐Rating Depression Scale, Self‐Rating Anxiety Scale, and Pittsburgh Sleep Quality Index scores at baseline, as well as at the 2nd, 4th, 6th, 8th, and 12th weeks. To investigate the underlying neural mechanisms of taVNS treatment from the perspective of the default mode network, multimodal magnetic resonance imaging (MRI; i.e., structural MRI [sMRI], resting state MRI [rsMRI], and pseudocontinuous arterial spin‐labeled [pcASL] MRI) will be used to compare cerebral images among groups. MRI data will also be collected from 40 healthy volunteers to assess whether the participants exhibit normal development of structural and functional components. Discussion Depression is the most common mental disorder in adolescence. Drug treatment can improve depression symptoms; however, the side effects of drug treatments are often severe. This study proposes a simple physiotherapy that aims to treat adolescents with mild to moderate depression. The mechanism of taVNS in the treatment of depression will also be investigated. The results of this study will provide evidence to guide the application of taVNS in adolescents with depression.

Dementia affects millions of elderly worldwide causing remarkable costs to society, but effective treatment is still lacking. Acupuncture is one of the complementary therapies that has been applied to cognitive deficits such as Alzheimer’s disease (AD) and vascular cognitive impairment (VCI), while the underlying mechanisms of its therapeutic efficiency remain elusive. Neuroplasticity is defined as the ability of the nervous system to adapt to internal and external environmental changes, which may support some data to clarify mechanisms how acupuncture improves cognitive impairments. This review summarizes the up-to-date and comprehensive information on the effectiveness of acupuncture treatment on neurogenesis and gliogenesis, synaptic plasticity, related regulatory factors, and signaling pathways, as well as brain network connectivity, to lay ground for fully elucidating the potential mechanism of acupuncture on the regulation of neuroplasticity and promoting its clinical application as a complementary therapy for AD and VCI.

Time series forecasting and analysis are widely used in many fields and application scenarios. Time series historical data reflects the change pattern and trend, which can serve the application and decision in each application scenario to a certain extent. In this paper, we select the time series prediction problem in the atmospheric environment scenario to start the application research. In terms of data support, we obtain the data of nearly 3500 vehicles in some cities in China fromRunwoda Research Institute, focusing on the major pollutant emission data of non-road mobile machinery and high emission vehicles in Beijing and Bozhou, Anhui Province to build the dataset and conduct the time series prediction analysis experiments on them. This paper proposes a P-gLSTNet model, and uses Autoregressive Integrated Moving Average model (ARIMA), long and short-term memory (LSTM), and Prophet to predict and compare the emissions in the future period. The experiments are validated on four public data sets and one self-collected data set, and the mean absolute error (MAE), root mean square error (RMSE), and mean absolute percentage error (MAPE) are selected as the evaluationmetrics. The experimental results show that the proposed P-gLSTNet fusion model predicts less error, outperforms the backbone method, and is more suitable for the prediction of time-series data in this scenario. [ABSTRACT FROM AUTHOR]