Changes in Cortical Thickness in Patients With Early Parkinson’s Disease at Different Hoehn and Yahr Stages

Objectives: This study was designed to explore changes in cortical thickness in patients with early Parkinson’s disease (PD) at different Hoehn and Yahr (H-Y) stages and to demonstrate the association of abnormally altered brain regions with part III of the Unified Parkinson’s Disease Rating Scale (UPDRS-III).Materials and Methods: Sixty early PD patients and 29 age- and gender-matched healthy controls (HCs) were enrolled in this study. All PD patients underwent comprehensive clinical and neuropsychological evaluations and 3.0 T magnetic resonance scanning. Patients with H-Y stage ≤1.5 were included in the mild group, and all other patients were included in the moderate group. FreeSurfer software was used to calculate cortical thickness. We assessed the relationship between UPDRS-III and regional changes in cortical thinning, including the bilateral fusiform and the temporal lobe.Results: The average cortical thickness of the temporal pole, fusiform gyrus, insula of the left hemisphere and fusiform gyrus, isthmus cingulate cortex, inferior temporal gyrus, middle temporal cortex and posterior cingulate cortex of the right hemisphere exhibited significant decreasing trends in HCs group and PD groups (i.e., the mild group and moderate group). After controlling for the effects of age, gender, and disease duration, the UPDRS-III scores in patients with early PD were correlated with the cortical thickness of the left and right fusiform gyrus and the left temporal pole (p < 0.05).Conclusion: The average cortical thickness of specific brain regions reduced with increasing disease severity in early PD patients at different H-Y stages, and the UPDRS-III scores of early PD patients were correlated with cortical thickness of the bilateral fusiform gyrus and the left temporal pole

Effects of NH3 and alkaline metals on the formation of particulate sulfate and nitrate in wintertime Beijing

Sulfate and nitrate from secondary reactions remain as the most abundant inorganic species in atmospheric particle matter (PM). Their formation is initiated by oxidation (either in gas phase or particle phase), followed by neutralization reaction primarily by NH3, or by other alkaline species such as alkaline metal ions if available. The different roles of NH3 and metal ions in neutralizing H2SO4 or HNO3, however, are seldom investigated. Here we conducted semi-continuous measurements of SO4 2−, NO3 −, NH4 +, and their gaseous precursors, as well as alkaline metal ions (Na+, K+, Ca2+, and Mg2+) in wintertime Beijing. Analysis of aerosol acidity (estimated from a thermodynamic model) indicated that preferable sulfate formation was related to low pH conditions, while high pH conditions promote nitrate formation. Data in different mass fraction ranges of alkaline metal ions showed that in some ranges the role of NH3 was replaced by alkaline metal ions in the neutralization reaction of H2SO4 and HNO3 to form particulate SO4 2− and NO3 −. The relationships between mass fractions of SO4 2− and NO3 − in those ranges of different alkaline metal ion content also suggested that alkaline metal ions participate in the competing neutralization reaction of sulfate and nitrate. The implication of the current study is that in some regions the chemistry to incorporate sulfur and nitrogen into particle phase might be largely affected by desert/fugitive dust and sea salt, besides NH3. This implication is particularly relevant in coastal China and those areas with strong influence of dust storm in the North China Plain (NCP), both of which host a number of megacities with deteriorating air quality

E3 ubiquitin ligase CHIP facilitates Toll-like receptor signaling by recruiting and polyubiquitinating Src and atypical PKCζ

In mouse macrophages and dendritic cells, the CHIP E3 ubiquitin ligase is needed for transduction of signals initiated by TLR4 and TLR9 stimulation

Styrene–Acrylic Emulsion with “Transition Layer” for Damping Coating: Synthesis and Characterization

In order to study the dynamic mechanical properties of styrene–acrylic latex with a core/shell structure, a variety of latexes were synthesized by semi-continuous seeded emulsion polymerization based on “particle design” with the same material. The latexes were characterized by rotary viscosimeter, dynamic light scattering (DLS), Fourier transform infrared spectroscopy (FTIR), transmission electron microscope (TEM), dynamic mechanical analysis (DMA), and universal testing machine. The effects of difference at the glass transition temperature (Tg) of core and shell and the introduction of the “transition layer” on the damping and mechanical properties of latex film were studied. The results indicate that as the Tg of core and shell gets closer, the better the compatibility of core and shell, from phase separation to phase continuity. Furthermore, the introduction of the “transition layer” can effectively improve the tensile strength and tan δ (max) of the latex film. The tensile strength and maximum loss factor (f = 1 Hz) of latex with the “transition layer” increased by 36.73% and 29.11% respectively compared with the latex without the “transition layer”. This work provides a reference for the design of emulsion for damping coating

Genus Periploca (Apocynaceae): A Review of Its Classification, Phytochemistry, Biological Activities and Toxicology

The genus Periploca belongs to the family Apocynaceae, which is composed of approximately ten species of plants according to incomplete statistics. Most of these plants serve as folk medicines with a long history, especially Periploca sepium and Periploca forrestii. The botanical classifications, chemical constituents, biological activities and toxicities of the genus Periploca were summarized in the literature from 1897 to early 2019. Though the botanical classification of this genus is controversial, these species are well-known to be rich sources of diverse and complex natural products—above all, cardiac steroids and C21 pregnane steroids with special structures and obvious pharmacological activities. The various crude extracts and 314 isolated metabolites from this genus have attracted much attention in intensive biological studies, indicating that they are equipped with cardiotonic, anti-inflammatory, immunosuppressive, antitumor, antimicrobial, antioxidant, insecticidal and other properties. It is noteworthy that some cardiac glycosides showed hepatotoxicity and cardiotoxicity at certain doses. Therefore, in view of the medical and agricultural value of the genus Periploca, in-depth investigations of the pharmacology in vivo, the mechanisms of biological actions, and the pharmacokinetics of the active ingredients should be carried out in the future. Moreover, in order to ensure the safety of clinical medication, the potential toxicities of cardiac glycosides or other compounds should also be paid attention. This systematic review provides an important reference base for applied research on pharmaceuticals and pesticides from this genus

Improved Continuous Wavelet Transform for Modal Parameter Identification of Long-Span Bridges

Accurate and timely identification of modal parameters of long-span bridges is important for bridge health monitoring and wind tunnel tests. Wavelet analysis is one of the most advantageous methods for identification because of its good localization characteristics in both time and frequency domain. In recent years, the wavelet method has been applied more frequently in parameter identification of linear and nonlinear systems. In this article, based on wavelet ridges and wavelet skeleton, the improved modal parameter identification method was studied. To find the appropriate time-frequency resolution, an optimal wavelet basis design principle based on minimum Shannon entropy was proposed. Aiming at endpoint effect in wavelet transform, a prediction continuation method based on support vector machine (SVM) was proposed, which can effectively suppress the endpoint effect of the extended samples. In view of the fact that the ridges of metric matrices obtained by the traditional crazy climber algorithm cannot fully reflect the distribution of ridges of modulus value matrices of wavelet coefficients, an improved high-precision crazy climber algorithm was put forward to accurately identify the position of the ridge of wavelet coefficients. Finally, taking a long-span cable-stayed bridge and a long-span suspension bridge as the engineering background, improved continuous wavelet transform (CWT) was applied to modal parameter identification of bridge under ambient excitation. The modal parameters such as modal frequency, damping ratio, and mode shape were obtained. Compared with the calculation value of the numerical simulation of long-span cable-stayed bridge and wind tunnel test of long-span suspension bridge, the reliability of CWT for modal parameter identification of long-span bridges under ambient excitation was verified

A study of sparse representation-based classification for biometric verification based on both handcrafted and deep learning features

Abstract Biometric verification is generally considered a one-to-one matching task. In contrast, in this paper, we argue that the one-to-many competitive matching via sparse representation-based classification (SRC) can bring enhanced verification security and accuracy. SRC-based verification introduces non-target subjects to construct dynamic dictionary together with the client claimed and encodes the submitted feature. Owing to the sparsity constraint, a client can only be accepted when it defeats almost all non-target classes and wins a convincing sparsity-based matching score. This will make the verification more secure than those using one-to-one matching. However, intense competition may also lead to extremely inferior genuine scores when data degeneration occurs. Motivated by the latent benefits and concerns, we study SRC-based verification using two sparsity-based matching measures, three biometric modalities (i.e., face, palmprint, and ear) and their multimodal combinations based on both handcrafted and deep learning features. We finally approach a comprehensive study of SRC-based verification, including its methodology, characteristics, merits, challenges and the directions to resolve. Extensive experimental results demonstrate the superiority of SRC-based verification, especially when using multimodal fusion and advanced deep learning features. The concerns about its efficiency in large-scale user applications can be readily solved using a simple dictionary shrinkage strategy based on cluster analysis and random selection of non-target subjects