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In the production process of large-scale machinery and complex industries, the key performance indicator (KPI) prediction is an essential part of project scheduling and cost estimation. The continuous enrichment of sensor types and functions brings us massive soft-sensing parameters for regression, but also brings severe challenges to algorithm learning. In this paper, an improved ensemble feature selection based on decision tree (EFS-DT) strategy for KPI prediction is developed. On the one hand, the ensemble of multi-criteria filtering results broadens the selector’s perspective without the time cost of superposition. On the other hand, credibility and similarity analysis are designed to eliminate the concerns of Dempster’s combination rule about conflict. After re-evaluating the variable scores, more high-quality variables can be selected to build a more accurate and robust KPI prediction model. Finally, a realistic shield tunnel case in China is used to evaluate the feasibility and effectiveness of proposed approach.

The aim of this study was to explore the differences in cognitive and neurological functions between cerebral small vessel disease (CSVD) rats and normal rats, as well as to study the Toll- like receptor 4 (TLR4) expression in the hippocampus of CSVD rats to understand its role in this brain structure. Forty male, 12-week old, specific pathogen-free (SPF), spontaneously hypertensive rats (SHRs) were used as the observation group, while 20 12-week old, SPF, Wistar male rats were used as the control group. After each measurement, 10 rats in the observation group and 5 in the control group were decapitated to collect samples for determining the expression of TLR4 in the hippocampus. At T1, difference in the latency of rats in the observation group showed no statistically significance (p = 0.836), while at T2, T3 and T4, the observation group showed longer latency than did the control group (p 0.001). In addition, the latency of SHRs at T1 was the shortest (p 0.05) compared to the follow-ups (T2-T4) and were followed sequentially by T2, T3, and T4 (p 0.05). The latency was shorter than those at T1 and T2, and the shortest latency was found at T4 (p 0.05). CSVD rats exhibited poor cognitive and neurological functions compared to normal rats and high expression of TLR4 in the hippocampus. Based on these results, we suggest that TLR4 affects the cognitive function of CSVD rats, and, thus, may be a valuable target in the treatment of CSVD.

Background Cerebral small vessel disease (CSVD) can lead to leukodystrophy and cognitive impairment. The inflammatory response mediated by Toll-like receptor 4 (TLR4) is involved in the pathological process of CSVD, but the roles of TLR4 in vascular cognitive impairment (VCI) following CSVD are not clear. Objective To explore the roles and mechanisms of TLR4 in the development of VCI. Methods Male spontaneous hypertension rats (SHR) and Wistar Kyoto rats (WKY) were monitored for blood pressure (BP). The spatial learning and memory were assessed every 6 weeks using Morris water maze (MWM). Blood samples from femoral artery were collected and serum was isolated. Cerebral white matter damage was evaluated using a 3.0T magnetic resonance imaging (MRI) every 12 weeks. After 35 weeks, all rats were decapitated, and the expression of TLR4 in the hippocampus was determined using western blot. The number of positive cells of TLR4, active astrocyte and microglia in hippocampus were measured using immunohistochemistry and immunofluorescence. Results Compared with WKY, the BP of SHR was maintained at a high level. Spatial learning and memory declined. IL-1β and TNF-α levels were elevated. Cranial coronal scanning with T2-weighted MRI showed high signal intensity in corpus callosum and external capsule of SHR. Furthermore, in SHR, the expression of TLR4, GFAP, and Iba1 in the hippocampus were increased. Conclusion Hypertension can cause small vascular damage and partial white matter degeneration in the brain. SHR showed cognitive impairment with increasing age. High expression of TLR4 and glial cell response in hippocampus is one of the key mechanisms of this disease.

Background: Neuromyelitis optica (NMO) is a severe autoimmune disorder of inflammatory central nervous system, which often resulting in paralysis or blindness. Rituximab (RTX) is a mouse-human chimeric monoclonal antibody specific for the CD20 antigen on B lymphocytes used to treat many autoimmune diseases. To evaluate the effectiveness of RTX, Disability and relapses were measured by the Expanded Disability Status Scale (EDSS) and annualized relapse rate (ARR) ratio. This review performed a meta-analysis of the efficacy of rituximab use in NMO. Methods: We searched through the databases of PubMed, Embase, and Cochrane Library. We compiled 27 studies in this meta-analysis: 19 used ARR ratio, 23 used EDSS score, and there are 15 studies in the two main variables. Differences in the ARR ratio and EDSS score before and after rituximab therapy were the main efficacy measures. After a consistency test, the publication bias was evaluated and a sensitivity analysis was performed with mean difference (MD) of the efficacy of rituximab. Results: A meta-analysis of 27 studies with 607 participants total was conducted. NMO patients have antibodies against aquaporin 4 autoantibody (AQP4-Ab) were recorded in 456 of 607 (75.12%). Rituximab therapy resulted in a mean (WMD) −1.58 (95%CI, −1.85 to −1.32) reduction in the mean ARR ratio and a mean (WMD) −1.17 (95%CI, −1.37 to −0.97) reduction in the mean EDSS score. 351 of 558 patients (62.9%) reached a relapse-free state. 107 of 607 (17.63%) patients had adverse reactions. Conclusions: RTX has acceptable tolerance, reduces the frequency of relapse, and improves disability in most patients. However, treatment with RTX in reducing health-care costs， improving functional outcome and reducing adverse effects should be carefully addressed in future studies.

OBJECTIVE To investigate the role and potential mechanism of Toll-like receptor 4 (TLR4)/nuclear factor-kappa B (NF-κB) signaling pathway in cognitive impairment induced by cerebral small vascular disease (CSVD), so as to provide a reference for the clinical treatment of CSVD-induced cognitive impairment. METHODS Mice with TLR4 gene knockout (n = 20) and those with wild-type TLR4 gene (n = 40) aged 8-10 weeks old were divided into blank control group (Control group, n = 20), wild-type + CSVD group (WT + CSVD group, n = 20) and TLR4 gene knockout + CSVD group (TLR4 KO + CSVD group, n = 20). Allogeneic thrombosis (particle diameter: 50-70 mm) was injected to the mouse's external carotid artery to create a model of learning and memory dysfunction. Step-down test and Y-type maze test were utilized to examine the learning and memory abilities of the mice. Reverse transcription-polymerase chain reaction (RT-PCR) and immunoblotting techniques were adopted to measure the levels of apoptosis-related genes [B-cell lymphoma/leukemia-2 (Bcl-2), Bcl-2-associated X protein (Bax), C-caspase-3 and T-caspase-3] in the brain tissues of mice. Terminal dexynucleotidyl transferase (TdT)-mediated dUTP nick end labeling (TUNEL) method was applied to detect the apoptosis of neuronal cells in the brain tissues. Meanwhile, the levels of oxidative stress markers, including superoxide dismutase (SOD), gp91 and malondialdehyde (MDA), were measured. Finally, the expression level of TLR4/NF-κB pathway was detected. RESULTS The latency in the step-down test in the WT + CSVD group was remarkably longer than that in the Control group, and the number of errors was evidently larger than that in the Control group (p

Additional file 1: Appendix 1. Included search strategies, sensitivity analysis tables, and subgroup analyses Appendix 2. Sensitivity analysis supplementary table for systematic reviews. Table S3. Sensitivity analysis of AD associated with vitamin D Deficiency (serum 25(OH)D

Background: Neuromyelitis optica (NMO) is a severe autoimmune disorder of inflammatory central nervous system, which often resulting in paralysis or blindness. Rituximab (RTX) is a mouse-human chimeric monoclonal antibody specific for the CD20 antigen on B lymphocytes used to treat many autoimmune diseases. This review performed a meta-analysis of the efficacy of rituximab use in NMO. Methods: We searched through the databases of PubMed, Embase, and Cochrane Library. We compiled 28 studies in this meta-analysis: 19 used annualized relapse rate (ARR) ratio, 24 used Expanded Disability Status Scale (EDSS) score. Differences in the ARR ratio and EDSS score before and after rituximab therapy were the main efficacy measures. After a consistency test, the publication bias was evaluated and a sensitivity analysis was performed with mean difference (MD) of the efficacy of rituximab. Results: A meta-analysis of 28 studies with 613 participants total was conducted. NMO patients have antibodies against aquaporin 4 autoantibody (AQP4-Ab) were recorded in 440 of 613 (71.78%). The mean difference of ARR ratio after rituximab therapy was 1.59 (95% CI, 1.33 to 1.85), and a mean difference 1.14 (95%CI, 0.95 to 1.33) reduction in the mean EDSS score. 345 of 563 patients (61.28%) reached a relapse-free state. 94 of 613 (15.33%) patients had adverse reactions. Conclusions: RTX has acceptable tolerance, reduces the frequency of relapse, and improves disability in most patients. However, the potential impact of early diagnosis of NMO and treatment with RTX in reducing health-care costs and improving functional outcome should be carefully addressed in future studies.

Optical coherence tomography (OCT) is a new imaging technology which is widely used in the field of ophthalmology, and retinal tissue layers segmentation plays an important role in the diagnosis of retinal diseases. This paper proposed an OCT macular retinal segmentation method based on the prior information of retinal structure and the optimized boundary tracking algorithm and realized the automatic segmentation of nine retinal layers. After image preprocessing, according to the multi-scale morphological operations and retinal structure characteristics, the optimal initial points were acquired in the parafovea domain. According to the new definition of boundary description feature, this paper optimized the traditional boundary tracking algorithm, and segmented the retinal boundaries. This paper analyzed 100 retinal OCT images, which come from 50 healthy participants from 18 to 29 years old, then compared our segmentation results with graph-based segmentation results and manual segmentations labeled by two experts. Experimental results showed that our method can accurately and effectively segment nine retinal layers (mean square error of boundary position is 1.18 ± 0.40 pixels), and is close to the results of manual segmentation (1.06±0.22 pixels), better than the literature segmentation results (3.02±1.03 pixels).

Background: Optical coherence tomography (OCT) is widely used in ophthalmology for viewing the morphology of the retina, which is important for disease detection and assessing therapeutic effect. The diagnosis of retinal diseases is based primarily on the subjective analysis of OCT images by trained ophthalmologists. This paper describes an OCT images automatic analysis method for computer-aided disease diagnosis and it is a critical part of the eye fundus diagnosis. Methods: This study analyzed 300 OCT images acquired by Optovue Avanti RTVue XR (Optovue Corp., Fremont, CA). Firstly, the normal retinal reference model based on retinal boundaries was presented. Subsequently, two kinds of quantitative methods based on geometric features and morphological features were proposed. This paper put forward a retinal abnormal grading decision-making method which was used in actual analysis and evaluation of multiple OCT images. Results: This paper showed detailed analysis process by four retinal OCT images with different abnormal degrees. The final grading results verified that the analysis method can distinguish abnormal severity and lesion regions. This paper presented the simulation of the 150 test images, where the results of analysis of retinal status showed that the sensitivity was 0.94 and specificity was 0.92.The proposed method can speed up diagnostic process and objectively evaluate the retinal status. Conclusions: This paper aims on studies of retinal status automatic analysis method based on feature extraction and quantitative grading in OCT images. The proposed method can obtain the parameters and the features that are associated with retinal morphology. Quantitative analysis and evaluation of these features are combined with reference model which can realize the target image abnormal judgment and provide a reference for disease diagnosis