Prevalence and associated factors of apathy in Chinese ALS patients

ObjectivveThis study aimed to explore the prevalence and clinical correlates of apathy in amyotrophic lateral sclerosis (ALS) in a cohort of Chinese patients.MethodsA total of 1,013 ALS patients were enrolled in this study. Apathy was recorded during face-to-face interviews using Frontal Behavioral Inventory, and other patient characteristics, including depression, anxiety, and cognitive function, were collected using Hamilton Depression Rating Scale (HDRS), Hamilton Anxiety Rating Scale (HARS), and Chinese version of Addenbrooke’s Cognitive Examination-revised. Health-related quality of life of ALS patients and their caregivers was also evaluated, and the potential factors associated with apathy were explored using forward binary regression analysis. Survival was analyzed using the Cox proportional hazards model.ResultsThe prevalence of apathy in all patients was 28.9%. Patients in the late disease stage had a higher prevalence of apathy than those in the early disease stage. Furthermore, patients with apathy had a lower ALS Functional Rating Scale revised (ALSFRS-R) score, higher HDRS score, HARS score and higher proportion of reported problems in the anxiety/depression. Additionally, their caregivers had higher score of depression and higher Zarit-Burden Interview scores. Multivariate regression analysis revealed that apathy in ALS was associated with the onset region (p = 0.027), ALSFRS-R score (p = 0.007), depression (p = 0.001) and anxiety (p < 0.001). Apathy had a significant negative effect on survival in ALS patients (p = 0.032).ConclusionApathy is relatively common (28.9%) in Chinese patients with ALS. Apathy is related to both the severity of the disease, and the presentation of non-motor symptoms in ALS, such as depression and anxiety disorders. Apathy is an independent prognostic factor for survival and requires early intervention and management

Cystatin C is associated with poor survival in amyotrophic lateral sclerosis patients

BackgroundCystatin C (CysC) levels in amyotrophic lateral sclerosis (ALS) have been found changes, however, the associations between serum CysC levels and the progression and survival of ALS remain largely unknown.MethodsA total of 1,086 ALS patients and 1,026 sex-age matched healthy controls (HCs) were enrolled in this study. Serum CysC, other renal function, and metabolic parameters were measured. Correlation analysis and binary logistic regression were used to explore the factors related to serum CysC. Kaplan–Meier curve and Cox regression model were used for survival analysis.ResultsCysC levels were significantly higher in ALS patients compared to HCs (0.94 vs. 0.85 mg/L, p < 0.001). Compared with ALS patients with lower CysC levels, those with higher CysC levels had an older age of onset, significantly lower ALSFRS-R scores (40.1 vs. 41.3, p < 0.001), a faster disease progression rate (0.75 vs. 0.67, p = 0.011), and lower frontal lobe function scores (15.8 vs. 16.1, p = 0.020). In the correlation analysis, CysC levels were significantly negatively correlated with ALSFRS-R scores (r = −0.16, p < 0.001). Additionally, ALS patients with higher CysC levels had significantly shorter survival time (40.0 vs. 51.8, p < 0.001) compared to patients with lower CysC levels. Higher CysC levels were associated with a higher risk of death in Cox analysis (HR: 1.204, 95% CI: 1.012–1.433). However, when treatment was included in the model, the result was no longer significant.ConclusionCysC levels in ALS patients were higher compared to HCs. Higher CysC levels were associated with greater disease severity, faster progression rate and shorter survival, needing early intervention

HDAC3 maintains oocyte meiosis arrest by repressing amphiregulin expression before the LH surge.

It is known that granulosa cells (GCs) mediate gonadotropin-induced oocyte meiosis resumption by releasing EGF-like factors in mammals, however, the detailed molecular mechanisms remain unclear. Here, we demonstrate that luteinizing hormone (LH) surge-induced histone deacetylase 3 (HDAC3) downregulation in GCs is essential for oocyte maturation. Before the LH surge, HDAC3 is highly expressed in GCs. Transcription factors, such as FOXO1, mediate recruitment of HDAC3 to the amphiregulin (Areg) promoter, which suppresses AREG expression. With the LH surge, decreased HDAC3 in GCs enables histone H3K14 acetylation and binding of the SP1 transcription factor to the Areg promoter to initiate AREG transcription and oocyte maturation. Conditional knockout of Hdac3 in granulosa cells in vivo or inhibition of HDAC3 activity in vitro promotes the maturation of oocytes independent of LH. Taking together, HDAC3 in GCs within ovarian follicles acts as a negative regulator of EGF-like growth factor expression before the LH surge

Potential Fungi Isolated From Anti-biodegradable Chinese Medicine Residue to Degrade Lignocellulose

Traditional Chinese medicine is one of the ancient medicines which is popular in Asian countries, among which the residue produced by the use of anti-biodegradables is endless, and causes significant adverse impacts on the environment. However, the high acidity of anti-biodegradable residues and some special biological activities make it difficult for microorganisms to survive, resulting in a very low degradation rate of lignocellulose in naturally stacked residues, which directly impedes the degradation of residues. We aimed to identify the fungal strains that efficiently biodegrade anti-biodegradable residue and see the possibility to improve the biodegradation of it and other agricultural wastes by co-cultivating these fungi. We isolated 302 fungal strains from anti-biodegradable residue to test hydrolysis ability. Finally, we found Coniochaeta sp., Fomitopsis sp., Nemania sp., Talaromyces sp., Phaeophlebiopsis sp. which inhabit the anti-biodegradable residues are capable of producing higher concentrations of extracellular enzymes. Synergistic fungal combinations (viz., Fomitopsis sp. + Phaeophlebiopsis sp.; Talaromyces sp. + Coniochaeta sp. + Fomitopsis sp.; Talaromyces sp. + Fomitopsis sp. + Piloderma sp. and Talaromyces sp. + Nemania sp. + Piloderma sp.) have better overall degradation effect on lignocellulose. Therefore, these fungi and their combinations have strong potential to be further developed for bioremediation and biological enzyme industrial production

Effect of Bond-Slip on Dynamic Response of FRP-Confined RC Columns with Non-Linear Damping

As a composite material, the damping energy consumption mechanism of fiber reinforced polymer-confined reinforced concrete (FRP-C RC) structure is very complex. In previous dynamic calculation models, the bond-slip effect for steel bars was often ignored, which would lead to a considerable error in the response of the FRP-C RC structures. In this paper, a new numerical model of FRP-C RC columns considering the bond-slip for steel bars is established using a zero-length element and nonlinear beam-column elements in the OpenSees software, and the results of the model are verified by experimental results. Based on the complex damping theory, the loss factor expression and nonlinear damping model of FRP-C RC columns with the bond slip effect are proposed. Finally, the dynamic response of FRP-C RC columns with nonlinear damping under harmonic load is calculated and compared with the results available in literature. The results show that the proposed model considering steel bars’ bond-slip can provide better prediction for dynamic response of FRP-C RC columns and make the future seismic design of FRP-C RC columns safer

Effect of Bond-Slip on Dynamic Response of FRP-Confined RC Columns with Non-Linear Damping

As a composite material, the damping energy consumption mechanism of fiber reinforced polymer-confined reinforced concrete (FRP-C RC) structure is very complex. In previous dynamic calculation models, the bond-slip effect for steel bars was often ignored, which would lead to a considerable error in the response of the FRP-C RC structures. In this paper, a new numerical model of FRP-C RC columns considering the bond-slip for steel bars is established using a zero-length element and nonlinear beam-column elements in the OpenSees software, and the results of the model are verified by experimental results. Based on the complex damping theory, the loss factor expression and nonlinear damping model of FRP-C RC columns with the bond slip effect are proposed. Finally, the dynamic response of FRP-C RC columns with nonlinear damping under harmonic load is calculated and compared with the results available in literature. The results show that the proposed model considering steel bars’ bond-slip can provide better prediction for dynamic response of FRP-C RC columns and make the future seismic design of FRP-C RC columns safer

Measuring the effect of residual stress on the machined subsurface of Inconel 718 by nanoindentation.

Inconel 718 alloy is widely used in aero-engines and high-temperature environments. However, residual stress caused by processing and molding leads to an uneven distribution of internal pressure, which reduces the reliability of service process. Therefore, numerical simulation of the nanoindentation process was applied to evaluate the effect of residual stress on the machined subsurface of Inconel 718. A gradient material model of Inconel 718 was established in ABAQUS finite element software. Mechanical properties based on nanoindentation testing showed an influence of residual stress in combination with indenter geometry. The orthogonal experimental results show that under diverse residual stress states, the indenter's geometry can affect the pile-up of the material surface after nanoindentation and significantly influence the test results. With increases in piling-up, the error caused by residual stress on the characterization of the mechanical properties of the hardened layer increases. Through the establishment of a numerical model, the influence of residual stress can be predicted within nanoindentation depths of 300 nm

Effect of Ni

With the development of high voltage transmission, there is an urgent need to develop ZnO varistor ceramics with high anti-aging properties. The key is to manipulate the intrinsic defect concentration of ZnO varistor ceramics precisely. In this paper, ZnO varistor ceramics doped with different contents of Ni2O3 are taken to study the relationship between the microstructure and electrical properties, and the effect of ZnO varistor ceramics doped with different contents on intrinsic defect concentration is also considered. The results show that, best electrical performance is shown when the content of Ni2O3 is 1.2mol%, the electrical breakdown field E1mA is 356 V/mm, the nonlinear coefficient reaches 32, and the leakage current IL is 3.4 . While the amount of the doped Ni2O3 is more 0.8mol%, a new phase of Co2Cr5Sb5O4 phase is observed from X-ray diffraction. The SEM micrographs showed that the average grain size decreased monotonously from 14.56 m to 5.73 m with the amount of the doped Ni2O3 increased. According to the results of dielectric spectroscopy, the intrinsic defect concentration increased with the contents of the doped Ni2O3 increased. The increase of Zinc interstitial is much greater than that of Oxygen vacancies, which is harmful to Long-term aging characteristics of ZnO varistor ceramics

Recent Progress in Sensing and Computing Techniques for Human Activity Recognition and Motion Analysis

The recent scientific and technical advances in Internet of Things (IoT) based pervasive sensing and computing have created opportunities for the continuous monitoring of human activities for different purposes. The topic of human activity recognition (HAR) and motion analysis, due to its potentiality in human–machine interaction (HMI), medical care, sports analysis, physical rehabilitation, assisted daily living (ADL), children and elderly care, has recently gained increasing attention. The emergence of some novel sensing devices featuring miniature size, a light weight, and wireless data transmission, the availability of wireless communication infrastructure, the progress of machine learning and deep learning algorithms, and the widespread IoT applications has promised new opportunities for a significant progress in this particular field. Motivated by a great demand for HAR-related applications and the lack of a timely report of the recent contributions to knowledge in this area, this investigation aims to provide a comprehensive survey and in-depth analysis of the recent advances in the diverse techniques and methods of human activity recognition and motion analysis. The focus of this investigation falls on the fundamental theories, the innovative applications with their underlying sensing techniques, data fusion and processing, and human activity classification methods. Based on the state-of-the-art, the technical challenges are identified, and future perspectives on the future rich, sensing, intelligent IoT world are given in order to provide a reference for the research and practices in the related fields