Parkinson's disease (PD) is a common neurodegenerative disease, which has attracted more and more attention. Many artificial intelligence methods have been used for the diagnosis of PD. In this study, an enhanced fuzzy k-nearest neighbor (FKNN) method for the early detection of PD based upon vocal measurements was developed. The proposed method, an evolutionary instance-based learning approach termed CBFO-FKNN, was developed by coupling the chaotic bacterial foraging optimization with Gauss mutation (CBFO) approach with FKNN. The integration of the CBFO technique efficiently resolved the parameter tuning issues of the FKNN. The effectiveness of the proposed CBFO-FKNN was rigorously compared to those of the PD datasets in terms of classification accuracy, sensitivity, specificity, and AUC (area under the receiver operating characteristic curve). The simulation results indicated the proposed approach outperformed the other five FKNN models based on BFO, particle swarm optimization, Genetic algorithms, fruit fly optimization, and firefly algorithm, as well as three advanced machine learning methods including support vector machine (SVM), SVM with local learning-based feature selection, and kernel extreme learning machine in a 10-fold cross-validation scheme. The method presented in this paper has a very good prospect, which will bring great convenience to the clinicians to make a better decision in the clinical diagnosis.
Tumor immunotherapy has shown great progress for the treatment of cancer; however, both endogenous and exogenous T cells are inhibited by the immunosuppressive tumor microenvironment. Tumor-associated macrophages (TAMs) in the microenvironment play pivotal and complex roles in tumor development and progression. Macrophages are categorized as M1 and M2 types. Relevant studies suggest that M2 TAMs correlate with poor prognosis. Colony-stimulating factor 1 receptor (CSF1R) controls the formation, differentiation and function of M2 macrophages, which helps tumors grow, metastasize and secrete immunosuppressive cytokines. The objectives of this study were to establish two types of third-generation chimeric antigen receptors (CARs) that could specifically target human CSF1R, and to introduce the CARs into NK92MI cells and normal human peripheral blood T cells through lentiviral transduction to produce CAR-natural killer (NK) and -T cells. We then tested their cytotoxicity against cell lines and peripheral blood monocytes expressing CSF1R. In vitro experiments confirmed that third-generation CARs had good target specificity and cytotoxicity. It was expected that CAR-NK and -T cells could specifically kill M2 TAMs in the tumor microenvironment and remove their inhibitory effect. Therefore, CSF1R-targeting CAR-NK and -T cells could represent a novel cellular immunotherapy strategy in conjunction with other antibody-based drugs and targeted therapeutics.
Objectives To compare the performance of conventional radiography, ldCT, and MRI in the diagnosis of sacroiliitis in suspected axial spondyloarthritis (axSpA). Methods Patients presenting with > 3 months chronic back pain were assessed by axSpA-experienced rheumatologists and diagnosed as axSpA or not; axSpA patients were then considered nr-axSpA or AS using plain radiography. Non-axSpA patients were recruited as controls, and divided into non-inflammatory and inflammatory groups on the basis of inflammatory back pain and/or CRP/ESR elevation. Clinical variables, pelvic radiography, sacroiliac joint (SIJ) ldCT, and SIJ MRI were obtained. Results A total of 121 patients were included and had SIJ radiography and ldCT, of whom 71 additionally had an SIJ MRI. These included 23 non-inflammatory controls, 21 inflammatory controls, 32 nr-axSpA cases, and 45 AS cases. Fourteen of 32 (44%) nr-axSpA patients had positive ldCT scans, 21/24 (88%) had MRI-BMO, and 11/24 (46%) had MRI-structural lesions. ldCT had high specificity with only 1/23 (4%) non-inflammatory controls being positive. MRI-BMO had the highest sensitivity for nr-axSpA, but compared with ldCT lower specificity, with 5/15 (33%) of non-inflammatory controls being positive, and similar sensitivity for AS (20/22 (91%) vs 44/44 for ldCT). Conclusions ldCT identifies evidence of radiographic change in a significant proportion of nr-axSpA cases and is highly specific for axSpA. MRI-BMO lesions are more sensitive than either conventional radiography or MRI-structural assessment for axSpA. The relative position of these imaging modalities in screening for axSpA needs to be reconsidered, also taking into account the costs involved. Key Points • ldCT is more sensitive for erosions or sclerosis in axSpA than plain radiography, with 44% of patients with nr-axSpA having evidence of AS-related sacroiliac joint changes on ldCT. • MRI-structural lesions are no more sensitive but are less specific for AS than ldCT. • MRI-BMO is the most sensitive test for nr-axSpA of the modalities tested but is less specific for axSpA than for ldCT. Keywords axSpA. Conventional radiography. Diagnostics. ldCT. Imaging procedures. MRI Matthew A. Brown and Dan Chen contributed equally to this work.
The aim of the study is to investigate the diffusion characteristics of Alzheimer’s disease (AD) patients using an ultra-high b-values apparent diffusion coefficient (ADC_uh) and diffusion kurtosis imaging (DKI). A total of 31 AD patients and 20 healthy controls (HC) who underwent both MRI examination and clinical assessment were included in this study. Diffusion weighted imaging (DWI) was acquired with 14 b-values in the range of 0 and 5000 s/mm2. Diffusivity was analyzed in selected regions, including the amygdala (AMY), hippocampus (HIP), thalamus (THA), caudate (CAU), globus pallidus (GPA), lateral ventricles (LVe), white matter (WM) of the frontal lobe (FL), WM of the temporal lobe (TL), WM of the parietal lobe (PL) and centrum semiovale (CS). The mean, median, skewness and kurtosis of the conventional apparent diffusion coefficient (ADC), DKI (including two variables, Dapp and Kapp) and ADC_uh values were calculated for these selected regions. Compared to the HC group, the ADC values of AD group were significantly higher in the right HIP and right PL (WM), while the ADC_uh values of the AD group increased significantly in the WM of the bilateral TL and right CS. In the AD group, the Kapp values in the bilateral LVe, bilateral PL/left TL (WM) and right CS were lower than those in the HC group, while the Dapp value of the right PL (WM) increased. The ADC_uh value of the right TL was negatively correlated with MMSE (mean, r=-0.420, p=0.019). The ADC value and Dapp value have the same regions correlated with MMSE. Compared with the ADC_uh, combining ADC_uh and ADC parameters will result in a higher AUC (0.894, 95%CI=0.803-0.984, p=0.022). Comparing to ADC or DKI, ADC_uh has no significant difference in the detectability of AD, but ADC_uh can better reflect characteristic alternation in unconventional brain regions of AD patients.
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