Robust Compensation of Electromechanical Delay during Neuromuscular Electrical Stimulation of Antagonistic Muscles

Neuromuscular electrical stimulation (NMES) can potentially be used to restore the limb function in persons with neurological disorders, such as spinal cord injury (SCI), stroke, etc. Researches on control system design has so far focused on relatively simple unidirectional NMES applications requiring stimulation of single muscle group. However, for some advanced tasks such as pedaling or walking, stimulation of multiple muscles is required. For example, to extend as well as flex a limb joint requires electrical stimulation of an antagonistic muscle pair. This is due to the fact that muscles are unidirectional actuators. The control challenge is to allocate control inputs to antagonist muscles based on the system output, usually a limb angle error to achieve a smooth and precise transition between antagonistic muscles without causing discontinuities. Furthermore, NMES input to each muscle is delayed by an electromechanical delay (EMD), which arises due to the time lag between the electrical excitation and the force development in muscle. And EMD is known to cause instability or performance loss during closed-loop control of NMES. In this thesis, a robust delay compensation controller for EMDs in antagonistic muscles is presented. A Lyapunov stability analysis yields uniformly ultimately bounded tracking for a human limb joint actuated by antagonistic muscles. The simulation results indicate that the controller is robust and effective in switching between antagonistic muscles and compensating EMDs during a simulated NMES task. Further experiments on a dual motor testbed shows its feasibility as an NMES controller for human antagonistic muscles

Dendritic cells contribute to perivascular adipose tissue dysfunction in type 2 diabetes

T2DM is a chronic disease characterized by low-grade inflammation in adipose tissue. Recent investigations have shown that a variety of immune cells can accumulate in adipose tissue contributing to the development of chronic inflammation. To date focus has been placed on specific immune cell populations including B and T lymphocytes, M1 macrophages, neutrophils, mast cells and natural killer cells. However, it remains uncertain about the exact immune cell populations in adipose tissue during T2DM. The dendritic cell is a potent antigen presenting cell that has been demonstrated to participate in the chronic inflammation associated with multiple diseases, including autoimmune disease, atherosclerosis and type 1 diabetes. Thus, it was hypothesized that dendritic cells would also play a role in the development of chronic inflammation elicited by T2DM. Firstly, our data obtained in db/db mice (T2DM murine model) provide evidence that dendritic cells do, indeed, accumulate in multiple depots of perivascular and visceral adipose tissue. Importantly, the dendritic cells target the adipose tissue rather than accumulating within the vascular wall, accompanied with increased production of pro-inflammatory factors TNF-[alpha] and IL-6 in adipose tissue. Secondly, depletion of dendritic cells within adipose tissue in db/db (db[subscript Flt3l-]/ db[subscript Flt3l-]) mice attenuated the pro-inflammatory environment. As perivascular adipose tissue exerts anti-contractile actions and potentiates vasorelaxation under physiological conditions, we examined the effects of fat from db/db mice on vascular function. The data showed that in db/db mice, both of these 'vaso-protective' effects were lost at early (6-10 weeks) and later (18-22 weeks) stages of T2DM in the presence of inflamed mesenteric adipose tissue. Depletion of dendritic cells in db[subscript Flt3l-]/ db[subscript Flt3l-]- mice greatly attenuated inflammation in perivascular adipose tissue (decreased secretion of TNF-[alpha] and IL-6) compared to the db/db and partially restored vascular function. Collectively, our studies demonstrate that the accumulation of dendritic cells in adipose tissue contributes to the pathogenesis of chronic inflammation in T2DM, resulting in impairment of anti-contractile and pro-relaxant actions of perivascular adipose tissue. Deletion of dendritic cells restores these physiological actions of adipose tissue.Includes biblographical reference

In-silico Antigenicity Determination and Clustering of Dengue Virus Serotypes

Emerging or re-emerging dengue virus (DENV) causes dengue fever epidemics globally. Current DENV serotypes are defined based on genetic clustering, while discrepancies are frequently observed between the genetic clustering and the antigenicity experiments. Rapid antigenicity determination of DENV mutants in high-throughput way is critical for vaccine selection and epidemic prevention during early outbreaks, where accurate prediction methods are seldom reported for DENV. Here, a highly accurate and efficient in-silico model was set up for DENV based on possible antigenicity-dominant positions (ADPs) of envelope (E) protein. Independent testing showed a high performance of our model with AUC-value of 0.937 and accuracy of 0.896 through quantitative Linear Regression (LR) model. More importantly, our model can successfully detect those cross-reactions between inter-serotype strains, while current genetic clustering failed. Prediction cluster of 1,143 historical strains showed new DENV clusters, and we proposed DENV2 should be further classified into two subgroups. Thus, the DENV serotyping may be re-considered antigenetically rather than genetically. As the first algorithm tailor-made for DENV antigenicity measurement based on mutated sequences, our model may provide fast-responding opportunity for the antigenicity surveillance on DENV variants and potential vaccine study

CE-BLAST makes it possible to compute antigenic similarity for newly emerging pathogens

Major challenges in vaccine development include rapidly selecting or designing immunogens for raising cross-protective immunity against different intra-or inter-subtypic pathogens, especially for the newly emerging varieties. Here we propose a computational method, Conformational Epitope (CE)-BLAST, for calculating the antigenic similarity among different pathogens with stable and high performance, which is independent of the prior binding-assay information, unlike the currently available models that heavily rely on the historical experimental data. Tool validation incorporates influenza-related experimental data sufficient for stability and reliability determination. Application to dengue-related data demonstrates high harmonization between the computed clusters and the experimental serological data, undetectable by classical grouping. CE-BLAST identifies the potential cross-reactive epitope between the recent zika pathogen and the dengue virus, precisely corroborated by experimental data. The high performance of the pathogens without the experimental binding data suggests the potential utility of CE-BLAST to rapidly design cross-protective vaccines or promptly determine the efficacy of the currently marketed vaccine against emerging pathogens, which are the critical factors for containing emerging disease outbreaks.Peer reviewe

Proteochemometric Modeling of the Antigen-Antibody Interaction : New Fingerprints for Antigen, Antibody and Epitope-Paratope Interaction

Despite the high specificity between antigen and antibody binding, similar epitopes can be recognized or cross-neutralized by paratopes of antibody with different binding affinities. How to accurately characterize this slight variation which may or may not change the antigen-antibody binding affinity is a key issue in this area. In this report, by combining cylinder model with shell structure model, a new fingerprint was introduced to describe both the structural and physical-chemical features of the antigen and antibody protein. Furthermore, beside the description of individual protein, the specific epitope-paratope interaction fingerprint (EPIF) was developed to reflect the bond and the environment of the antigen-antibody interface. Finally, Proteochemometric Modeling of the antigen-antibody interaction was established and evaluated on 429 antigen-antibody complexes. By using only protein descriptors, our model achieved the best performance (R-2 = 0: 91; Q(test)(2) = 0: 68) among peers. Further, together with EPIF as a new cross-term, our model (R-2 = 0: 92; Q(2) test = 0: 74) can significantly outperform peers with multiplication of ligand and protein descriptors as a cross-term (R2Peer reviewe

Enhancing Working Memory Based on Mismatch Negativity Neurofeedback in Subjective Cognitive Decline Patients: A Preliminary Study

Mismatch negativity (MMN) is suitable for studies of preattentive auditory discriminability and the auditory memory trace. Subjective cognitive decline (SCD) is an ideal target for early therapeutic intervention because SCD occurs at preclinical stages many years before the onset of Alzheimer's disease (AD). According to a novel lifespan-based model of dementia risk, hearing loss is considered the greatest potentially modifiable risk factor of dementia among nine health and lifestyle factors, and hearing impairment is associated with cognitive decline. Therefore, we propose a neurofeedback training based on MMN, which is an objective index of auditory discriminability, to regulate sensory ability and memory as a non-pharmacological intervention (NPI) in SCD patients. Seventeen subjects meeting the standardized clinical evaluations for SCD received neurofeedback training. The auditory frequency discrimination test, the visual digital N-back (1-, 2-, and 3-back), auditory digital N-back (1-, 2-, and 3-back), and auditory tone N-back (1-, 2-, and 3-back) tasks were used pre- and post-training in all SCD patients. The intervention schedule comprised five 60-min training sessions over 2 weeks. The results indicate that the subjects who received neurofeedback training had successfully improved the amplitude of MMN at the parietal electrode (Pz). A slight decrease in the threshold of auditory frequency discrimination was observed after neurofeedback training. Notably, after neurofeedback training, the working memory (WM) performance was significantly enhanced in the auditory tone 3-back test. Moreover, improvements in the accuracy of all WM tests relative to the baseline were observed, although the changes were not significant. To the best of our knowledge, our preliminary study is the first to investigate the effects of MMN neurofeedback training on WM in SCD patients, and our results suggest that MMN neurofeedback may represent an effective treatment for intervention in SCD patients and the elderly with aging memory decline

Integration of multiple-omics data to reveal the shared genetic architecture of educational attainment, intelligence, cognitive performance, and Alzheimer’s disease

Growing evidence suggests the effect of educational attainment (EA) on Alzheimer’s disease (AD), but less is known about the shared genetic architecture between them. Here, leveraging genome-wide association studies (GWAS) for AD (N = 21,982/41,944), EA (N = 1,131,881), cognitive performance (N = 257,828), and intelligence (N = 78,308), we investigated their causal association with the linkage disequilibrium score (LDSC) and Mendelian randomization and their shared loci with the conjunctional false discovery rate (conjFDR), transcriptome-wide association studies (TWAS), and colocalization. We observed significant genetic correlations of EA (rg = −0.22, p = 5.07E-05), cognitive performance (rg = −0.27, p = 2.44E-05), and intelligence (rg = −0.30, p = 3.00E-04) with AD, and a causal relationship between EA and AD (OR = 0.74, 95% CI: 0.58–0.94, p = 0.013). We identified 13 shared loci at conjFDR <0.01, of which five were novel, and prioritized three causal genes. These findings inform early prevention strategies for AD

Disconnection between plant–microbial nutrient limitation across forest biomes

11 páginas.- 7 figuras.- 1 tabla.- 41 referencias.- Additional supporting information can be found online in the Supporting Information section at the end of this article..- Read the free Plain Language Summary for this article on the Journal blog.Nitrogen (N) and phosphorus (P) are essential elements limiting plant–microbial growth in forest ecosystems. However, whether the pattern of plant–microbe nutrient limitation is consistent across forest biomes and the associated potential mechanisms remain largely unclear, limiting us to better understand the biogeochemical processes under future climate change. Here, we investigated patterns of plant–microbial N/P limitation in forests across a wide environmental gradient and biomes in China to explore the divergence of plant–microbial N/P limitation and the driving mechanisms. We revealed that 42.6% of the N/P limitation between plant–microbial communities was disconnected. Patterns in plant–microbial N/P limitations were consistent only for 17.7% of N and 39.7% of P. Geospatially, the inconsistency was more evident at mid-latitudes, where plants were mainly N limited and microbes were mainly P limited. Furthermore, our findings were consistent with the ecological stoichiometry of plants and microbes themselves and their requirements. Whereas plant N and P limitation was more strongly responsive to meteorological conditions and atmospheric deposition, that of microbes was more strongly responsive to soil chemistry, which exacerbated the plant–microbe N and P limitation divergence. Our work identified an important disconnection between plant and microbial N/P limitation, which should be incorporated into future Earth System Model to better predict forest biomes–climate change feedback. Read the free Plain Language Summary for this article on the Journal blog. © 2023 The Authors. Functional Ecology © 2023 British Ecological SocietyNational Natural Science Foundation of China, Grant/Award Number: 42207107; Catalan Government Grant, Grant/Award Number: SGR2017-1005; Fundación Ramón Areces grant, Grant/Award Number: CIVP20A6621; National Key Research and Development Program of China, Grant/Award Number: 2021YFD1901205; Open Fund of Key Laboratory of Agro-Ecological Processes in Subtropical Region, Chinese Academy of Sciences, Grant/Award Number: ISA2021101; Spanish Government, Grant/Award Number: PID2019-110521GB-I00 and PID2020-115770RB-I00; Strategic Priority Research Program of Chinese Academy of Sciences, Grant/Award Number: XDB40020202Peer reviewe