Robust myoelectric pattern recognition methods for reducing users' calibration burden: challenges and future.

Myoelectric pattern recognition (MPR) has evolved into a sophisticated technology widely employed in controlling myoelectric interface (MI) devices like prosthetic and orthotic robots. Current MIs not only enable multi-degree-of-freedom control of prosthetic limbs but also demonstrate substantial potential in consumer electronics. However, the non-stationary random characteristics of myoelectric signals poses challenges, leading to performance degradation in practical scenarios such as electrode shifting and switching new users. Conventional MIs often necessitate meticulous calibration, imposing a significant burden on users. To address user frustration during the calibration process, researchers have focused on identifying MPR methods that alleviate this burden. This article categorizes common scenarios that incur calibration burdens as based on data distribution shift and based on dynamic data categories. Then further investigated and summarized the popular robust MPR algorithms used to reduce the user's calibration burden. We categorize these algorithms as based on data manipulate, feature manipulation and, model structure. And describes the scenarios to which each method is applicable and the conditions required for calibration. Finally, this review is concluded with the advantages of robust MPR and the remaining challenges and future opportunities.

Direct interaction of platelet with tumor cell aggravates hepatocellular carcinoma metastasis by activating TLR4/ADAM10/CX3CL1 axis.

Metastasis is the main culprit of cancer-related death and account for the poor prognosis of hepatocellular carcinoma. Although platelets have been shown to accelerate tumor cell metastasis, the exact mechanism remained to be fully understood. Here, we found that high blood platelet counts and increased tumor tissue ADAM10 expression indicated the poor prognosis of HCC patients. Meanwhile, blood platelet count has positive correlation with tumor tissue ADAM10 expression. In vitro, we revealed that platelet increased ADAM10 expression in tumor cell through TLR4/NF-κB signaling pathway. ADAM10 catalyzed the shedding of CX3CL1 which bound to CX3CR1 receptor, followed by inducing epithelial to mesenchymal transition and activating RhoA signaling in cancer cells. Moreover, knockdown HCC cell TLR4 (Tlr4) or inhibition of ADAM10 prevented platelet-increased tumor cell migration, invasion and endothelial permeability. In vivo, we further verified in mice lung metastatic model that platelet accelerated tumor metastasis via cancer cell TLR4/ADAM10/CX3CL1 axis. Overall, our study provides new insights into the underlying mechanism of platelet-induced HCC metastasis. Therefore, targeting the TLR4/ADAM10/CX3CL1 axis in cancer cells hold promise for the inhibition of platelet-promoted lung metastasis of HCC.

An Observational Prospective Cohort Study of Vaccine Effectiveness Against Severe Acute Respiratory Syndrome Coronavirus 2 Infection of an Aerosolized, Inhaled Adenovirus Type 5-Vectored Coronavirus Disease 2019 Vaccine Given as a Second Booster Dose in Guangzhou City, China.

Using a prospective, observational cohort study during the post-"dynamic COVID-zero" wave in China, we estimated short-term relative effectiveness against Omicron BA.5 infection of inhaled aerosolized adenovirus type 5-vectored ancestral strain coronavirus disease 2019 (COVID-19) vaccine as a second booster dose approximately 1 year after homologous boosted primary series of inactivated COVID-19 vaccine compared with no second booster. Participants reported nucleic acid or antigen test results weekly until they tested positive or completed predesignated follow-up. After excluding participants infected <14 days after study entry, relative effectiveness among the 6576 participants was 61% in 18- to 59-year-olds and 38% in ≥60-year-olds and was sustained for 12 weeks.

EMG-Driven Musculoskeletal Model Calibration With Wrapping Surface Personalization.

Muscle forces and joint moments estimated by electromyography (EMG)-driven musculoskeletal models are sensitive to the wrapping surface geometry defining muscle-tendon lengths and moment arms. Despite this sensitivity, wrapping surface properties are typically not personalized to subject movement data. This study developed a novel method for personalizing OpenSim cylindrical wrapping surfaces during EMG-driven model calibration. To avoid the high computational cost of repeated OpenSim muscle analyses, the method uses two-level polynomial surrogate models. Outer-level models specify time-varying muscle-tendon lengths and moment arms as functions of joint angles, while inner-level models specify time-invariant outer-level polynomial coefficients as functions of wrapping surface parameters. To evaluate the method, we used walking data collected from two individuals post-stroke and performed four variations of EMG-driven lower extremity model calibration: 1) no calibration of scaled generic wrapping surfaces (NGA), 2) calibration of outer-level polynomial coefficients for all muscles (SGA), 3) calibration of outer-level polynomial coefficients only for muscles with wrapping surfaces (LSGA), and 4) calibration of cylindrical wrapping surface parameters for muscles with wrapping surfaces (PGA). On average compared to NGA, SGA reduced lower extremity joint moment matching errors by 31%, LSGA by 24%, and PGA by 12%, with the largest reductions occurring at the hip. Furthermore, PGA reduced peak hip joint contact force by 47% bodyweight, which was the most consistent with published in vivo measurements. The proposed method for EMG-driven model calibration with wrapping surface personalization produces physically realistic OpenSim models that reduce joint moment matching errors while improving prediction of hip joint contact force.

A Novel Airway-Organoid Model Based on a Nano-Self-Assembling Peptide: Construction and Application in Adenovirus Infection Studies.

Purpose: Hydrogels containing the nano-self-assembling peptide RADA16-I (Nanogels) were utilized as scaffolds to establish airway organoids and an adenovirus-infected model. The results support in vitro adenovirus studies, including isolation and culture, pathogenesis research, and antiviral drug screening. Methods: HSAEC1-KT, HuLEC-5a and HELF cells were cocultured in RADA16-I hydrogel scaffolds to construct an airway organoid model. Adenovirus was used to infect this model for adenovirus-related studies. The morphological characteristics and the proliferation and activity of airway organoids before and after adenovirus infection were evaluated. The expression of the airway organoid marker proteins CC10, KRT8, AQP5, SPC, VIM and CD31 was detected. TEM and qPCR were used to detect adenovirus proliferation in airway organoids. Results: HSAEC1-KT, HuLEC-5a and HELF cells cocultured at 10:7:2 self-assembled into airway organoids and maintained long-term proliferation in a RADA16-I hydrogel 3D culture system. The organoids stably expressed the lumen-forming protein KRT8 and the terminal airway markers AQP5 and SPC. Adenoviruses maintained long-term proliferation in this model. Conclusion: An airway-organoid model of adenovirus infection was constructed in vitro from three human lung-derived cell lines on RADA16-I hydrogels. The model has potential as a novel research tool for adenovirus isolation and culture, pathogenesis research, and antiviral drug screening.

Application of silver nanoparticles for improving motor recovery after spinal cord injury via reduction of pro-inflammatory M1 macrophages.

Silver nanoparticles (AgNPs) possess anti-inflammatory activities and have been widely deployed for promoting tissue repair. Here we explored the efficacy of AgNPs on functional recovery after spinal cord injury (SCI). Our data indicated that, in a SCI rat model, local AgNPs delivery could significantly recover locomotor function and exert neuroprotection through reducing of pro-inflammatory M1 survival. Furthermore, in comparison with Raw 264.7-derived M0 and M2, a higher level of AgNPs uptake and more pronounced cytotoxicity were detected in M1. RNA-seq analysis revealed the apoptotic genes in M1 were upregulated by AgNPs, whereas in M0 and M2, pro-apoptotic genes were downregulated and PI3k-Akt pathway signaling pathway was upregulated. Moreover, AgNPs treatment preferentially reduced cell viability of human monocyte-derived M1 comparing to M2, supporting its effect on M1 in human. Overall, our findings reveal AgNPs could suppress M1 activity and imply its therapeutic potential in promoting post-SCI motor recovery.

Real-World Effectiveness of Primary Series and Booster Doses of Inactivated Coronavirus Disease 2019 Vaccine Against Omicron BA.2 Variant Infection in China: A Retrospective Cohort Study.

BACKGROUND: China has been using inactivated coronavirus disease 2019 (COVID-19) vaccines as primary series and booster doses to protect the population from severe to fatal COVID-19. We evaluated primary and booster vaccine effectiveness (VE) against Omicron BA.2 infection outcomes. METHODS: This was a 13-province retrospective cohort study of quarantined close contacts of BA.2-infected individuals. Outcomes were BA.2 infection, COVID-19 pneumonia or worse, and severe/critical COVID-19. Absolute VE was estimated by comparison with an unvaccinated group. RESULTS: There were 289 427 close contacts ≥3 years old exposed to Omicron BA.2 cases; 31 831 turned nucleic acid amplification test-positive during quarantine, 97.2% with mild or asymptomatic infection, 2.6% with COVID-19 pneumonia, and 0.15% with severe/critical COVID-19. None died. Adjusted VE (aVE) against any infection was 17% for primary series and 22% when boosted. Primary series aVE in adults >18 years was 66% against COVID-19 pneumonia or worse and 91% against severe/critical COVID-19. Booster dose aVE was 74% against pneumonia or worse, and 93% against severe/critical COVID-19. CONCLUSIONS: Inactivated COVID-19 vaccines provided modest protection from infection, very good protection against pneumonia, and excellent protection against severe/critical COVID-19. Booster doses are necessary to provide strongest protection.

Characteristics of fibrotic-foci-like lung adenocarcinoma on 18 F-FDG PET/computed tomography and HRCT.

PURPOSE: To assess the characteristics of fibrotic-foci-like lung adenocarcinoma on 18 F-fluorodeoxyglucose PET/computed tomography ( 18 F-FDG PET/CT) and high-resolution computed tomography (HRCT). MATERIAL AND METHODS: This was a retrospective study with 20 cases in the fibrotic-foci-like lung adenocarcinoma group; the control group was old fibrotic-foci of the lung with 20 cases. The following 18 F-FDG PET/CT and HRCT features were evaluated: the maximum standardized uptake value (SUVmax); the tumor-to-background ratios of SUVmax (TBRmax); the long-to-short diameter ratio (L/S); anatomic location; location type; internal characteristics; marginal characteristics and surrounding structures. In the fibrotic-foci-like lung adenocarcinoma group, a comparison of 18 F-FDG uptake between the metastatic group ( n  = 10) and the non-metastatic group ( n  = 10) was performed. Finally, the comparison of diagnostic accuracy for fibrotic-foci-like lung adenocarcinoma between 18 F-FDG PET/CT and HRCT was performed. RESULTS: The SUVmax [2.6 (1.7-7.9) vs. 1.0 (0.7-1.4)], TBRmax [2.9 (2.1-9.9) vs. 1.3 (1.2- 1.7)], L/S [2.4 (1.7-3.8) vs. 4.0 (3.2-6.3)], ground-glass opacity (GGO) [13/20 (65.0%) vs. 4/20 (20.0%)], and vessel convergence [7/20 (35.0%) vs. 1/20 (5.0%)] were found to be statistically significant differences between the fibrotic-foci-like lung adenocarcinoma group and the old fibrotic-foci group ( P  < 0.05). SUVmax [7.9 (4.7-8.8) vs. 1.7 (1.2-2.2)] and TBRmax [9.9 (6.5-11.0) vs. 2.1 (1.6-2.9)] were found to be statistically significant differences between the metastatic group and the non-metastatic group ( P  < 0.05). 18 F-FDG PET/CT showed the higher diagnostic accuracy for fibrotic-foci-like lung adenocarcinoma than HRCT [95.0% (19/20) vs. 65.0% (13/20), P  < 0.05]. CONCLUSION: The specific characteristics of fibrotic-foci-like lung adenocarcinoma on 18 F-FDG PET/CT and HRCT were high 18 F-FDG uptake, GGO, and vessel convergence, which could be distinguished from old fibrotic-foci of the lung.

Copper-Catalyzed C2- or C3-Thioglycosylation of Indoles with N-(Thioglycosides)succinimides: An Effective Strategy for the Total Synthesis of Isatindigotindolosides.

Isatindigotindolosides, indoles containing a 1-S-ß-glucopyranosyl unit at position C2, show promising bioactivity. Here, we report a copper-catalyzed C2- or C3-thioglycosylation of indoles with N-(thioglycosides)succinimides to construct indole alkaloid glucosides. This reaction is widely tolerant of functional groups, as various indoles and thioglycosides are suitable. It also provides a reliable method for performing late-stage modifications of natural products, such as gramine and melatonin. Total syntheses of isatindigotindolosides I and II were successfully accomplished using the C2-thioglycosylation reaction as a key step.

A computational method for estimating trunk muscle activations during gait using lower extremity muscle synergies.

One of the surgical treatments for pelvic sarcoma is the restoration of hip function with a custom pelvic prosthesis after cancerous tumor removal. The orthopedic oncologist and orthopedic implant company must make numerous often subjective decisions regarding the design of the pelvic surgery and custom pelvic prosthesis. Using personalized musculoskeletal computer models to predict post-surgery walking function and custom pelvic prosthesis loading is an emerging method for making surgical and custom prosthesis design decisions in a more objective manner. Such predictions would necessitate the estimation of forces generated by muscles spanning the lower trunk and all joints of the lower extremities. However, estimating trunk and leg muscle forces simultaneously during walking based on electromyography (EMG) data remains challenging due to the limited number of EMG channels typically used for measurement of leg muscle activity. This study developed a computational method for estimating unmeasured trunk muscle activations during walking using lower extremity muscle synergies. To facilitate the calibration of an EMG-driven model and the estimation of leg muscle activations, EMG data were collected from each leg. Using non-negative matrix factorization, muscle synergies were extracted from activations of leg muscles. On the basis of previous studies, it was hypothesized that the time-varying synergy activations were shared between the trunk and leg muscles. The synergy weights required to reconstruct the trunk muscle activations were determined through optimization. The accuracy of the synergy-based method was dependent on the number of synergies and optimization formulation. With seven synergies and an increased level of activation minimization, the estimated activations of the erector spinae were strongly correlated with their measured activity. This study created a custom full-body model by combining two existing musculoskeletal models. The model was further modified and heavily personalized to represent various aspects of the pelvic sarcoma patient, all of which contributed to the estimation of trunk muscle activations. This proposed method can facilitate the prediction of post-surgery walking function and pelvic prosthesis loading, as well as provide objective evaluations for surgical and prosthesis design decisions.

Computational evaluation of psoas muscle influence on walking function following internal hemipelvectomy with reconstruction.

An emerging option for internal hemipelvectomy surgery is custom prosthesis reconstruction. This option typically recapitulates the resected pelvic bony anatomy with the goal of maximizing post-surgery walking function while minimizing recovery time. However, the current custom prosthesis design process does not account for the patient's post-surgery prosthesis and bone loading patterns, nor can it predict how different surgical or rehabilitation decisions (e.g., retention or removal of the psoas muscle, strengthening the psoas) will affect prosthesis durability and post-surgery walking function. These factors may contribute to the high observed failure rate for custom pelvic prostheses, discouraging orthopedic oncologists from pursuing this valuable treatment option. One possibility for addressing this problem is to simulate the complex interaction between surgical and rehabilitation decisions, post-surgery walking function, and custom pelvic prosthesis design using patient-specific neuromusculoskeletal models. As a first step toward developing this capability, this study used a personalized neuromusculoskeletal model and direct collocation optimal control to predict the impact of ipsilateral psoas muscle strength on walking function following internal hemipelvectomy with custom prosthesis reconstruction. The influence of the psoas muscle was targeted since retention of this important muscle can be surgically demanding for certain tumors, requiring additional time in the operating room. The post-surgery walking predictions emulated the most common surgical scenario encountered at MD Anderson Cancer Center in Houston. Simulated post-surgery psoas strengths included 0% (removed), 50% (weakened), 100% (maintained), and 150% (strengthened) of the pre-surgery value. However, only the 100% and 150% cases successfully converged to a complete gait cycle. When post-surgery psoas strength was maintained, clinical gait features were predicted, including increased stance width, decreased stride length, and increased lumbar bending towards the operated side. Furthermore, when post-surgery psoas strength was increased, stance width and stride length returned to pre-surgery values. These results suggest that retention and strengthening of the psoas muscle on the operated side may be important for maximizing post-surgery walking function. If future studies can validate this computational approach using post-surgery experimental walking data, the approach may eventually influence surgical, rehabilitation, and custom prosthesis design decisions to meet the unique clinical needs of pelvic sarcoma patients.

EMG-driven musculoskeletal model calibration with estimation of unmeasured muscle excitations via synergy extrapolation.

Subject-specific electromyography (EMG)-driven musculoskeletal models that predict muscle forces have the potential to enhance our knowledge of internal biomechanics and neural control of normal and pathological movements. However, technical gaps in experimental EMG measurement, such as inaccessibility of deep muscles using surface electrodes or an insufficient number of EMG channels, can cause difficulties in collecting EMG data from muscles that contribute substantially to joint moments, thereby hindering the ability of EMG-driven models to predict muscle forces and joint moments reliably. This study presents a novel computational approach to address the problem of a small number of missing EMG signals during EMG-driven model calibration. The approach (henceforth called "synergy extrapolation" or SynX) linearly combines time-varying synergy excitations extracted from measured muscle excitations to estimate 1) unmeasured muscle excitations and 2) residual muscle excitations added to measured muscle excitations. Time-invariant synergy vector weights defining the contribution of each measured synergy excitation to all unmeasured and residual muscle excitations were calibrated simultaneously with EMG-driven model parameters through a multi-objective optimization. The cost function was formulated as a trade-off between minimizing joint moment tracking errors and minimizing unmeasured and residual muscle activation magnitudes. We developed and evaluated the approach by treating a measured fine wire EMG signal (iliopsoas) as though it were "unmeasured" for walking datasets collected from two individuals post-stroke-one high functioning and one low functioning. How well unmeasured muscle excitations and activations could be predicted with SynX was assessed quantitatively for different combinations of SynX methodological choices, including the number of synergies and categories of variability in unmeasured and residual synergy vector weights across trials. The two best methodological combinations were identified, one for analyzing experimental walking trials used for calibration and another for analyzing experimental walking trials not used for calibration or for predicting new walking motions computationally. Both methodological combinations consistently provided reliable and efficient estimates of unmeasured muscle excitations and activations, muscle forces, and joint moments across both subjects. This approach broadens the possibilities for EMG-driven calibration of muscle-tendon properties in personalized neuromusculoskeletal models and may eventually contribute to the design of personalized treatments for mobility impairments.

A congenital CMV infection model for follow-up studies of neurodevelopmental disorders, neuroimaging abnormalities, and treatment.

Congenital cytomegalovirus (cCMV) infection is the leading infectious cause of neurodevelopmental disorders. However, the neuropathogenesis remains largely elusive due to a lack of informative animal models. In this study, we developed a congenital murine CMV (cMCMV) infection mouse model with high survival rate and long survival period that allowed long-term follow-up study of neurodevelopmental disorders. This model involves in utero intracranial injection and mimics many reported clinical manifestations of cCMV infection in infants, including growth restriction, hearing loss, and impaired cognitive and learning-memory abilities. We observed that abnormalities in MRI/CT neuroimaging were consistent with brain hemorrhage and loss of brain parenchyma, which was confirmed by pathological analysis. Neuropathological findings included ventriculomegaly and cortical atrophy associated with impaired proliferation and migration of neural progenitor cells in the developing brain at both embryonic and postnatal stages. Robust inflammatory responses during infection were shown by elevated inflammatory cytokine levels, leukocyte infiltration, and activation of microglia and astrocytes in the brain. Pathological analyses and CT neuroimaging revealed brain calcifications induced by cMCMV infection and cell death via pyroptosis. Furthermore, antiviral treatment with ganciclovir significantly improved neurological functions and mitigated brain damage as shown by CT neuroimaging. These results demonstrate that this model is suitable for investigation of mechanisms of infection-induced brain damage and long-term studies of neurodevelopmental disorders, including the development of interventions to limit CNS damage associated with cCMV infection.

Sanguinarine Attenuates Collagen-Induced Platelet Activation and Thrombus Formation.

Sanguinarine, a benzophenanthridine alkaloid, has been described to have an antiplatelet activity. However, its antithrombotic effect and the mechanism of platelet inhibition have not thoroughly been explored. The current study found that sanguinarine had an inhibitory effect on thrombus formation. This inhibitory effect was quite evident both in the flow-chamber assays as well as in a murine model of FeCl3-induced carotid artery thrombosis. Further investigations also revealed that sanguinarine inhibited the collagen-induced human platelet aggregation and granule release. At the same time, it also prevented platelet spreading and adhesion to immobilized fibrinogen. The molecular mechanisms of its antiplatelet activity were found to be as follows: 1. Reduced phosphorylation of the downstream signaling pathways in collagen specific receptor GPVI (Syk-PLCγ2 and PI3K-Akt-GSK3ß); 2. Inhibition of collagen-induced increase in the intracellular Ca2+ concentration ([Ca2+]i); 3. Inhibition of integrin αIIbß3 outside-in signaling via reducing ß3 and Src (Tyr-416) phosphorylation. It can be concluded that sanguinarine inhibits collagen-induced platelet activation and reduces thrombus formation. This effect is mediated via inhibiting the phosphorylation of multiple components in the GPVI signaling pathway. Current data also indicate that sanguinarine can be of some clinical value to treat cardiovascular diseases involving an excess of platelet activation.

Evaluation of Synergy Extrapolation for Predicting Unmeasured Muscle Excitations from Measured Muscle Synergies.

Electromyography (EMG)-driven musculoskeletal modeling relies on high-quality measurements of muscle electrical activity to estimate muscle forces. However, a critical challenge for practical deployment of this approach is missing EMG data from muscles that contribute substantially to joint moments. This situation may arise due to either the inability to measure deep muscles with surface electrodes or the lack of a sufficient number of EMG channels. Muscle synergy analysis (MSA) is a dimensionality reduction approach that decomposes a large number of muscle excitations into a small number of time-varying synergy excitations along with time-invariant synergy weights that define the contribution of each synergy excitation to all muscle excitations. This study evaluates how well missing muscle excitations can be predicted using synergy excitations extracted from muscles with available EMG data (henceforth called "synergy extrapolation" or SynX). The method was evaluated using a gait data set collected from a stroke survivor walking on an instrumented treadmill at self-selected and fastest-comfortable speeds. The evaluation process started with full calibration of a lower-body EMG-driven model using 16 measured EMG channels (collected using surface and fine wire electrodes) per leg. One fine wire EMG channel (either iliopsoas or adductor longus) was then treated as unmeasured. The synergy weights associated with the unmeasured muscle excitation were predicted by solving a nonlinear optimization problem where the errors between inverse dynamics and EMG-driven joint moments were minimized. The prediction process was performed for different synergy analysis algorithms (principal component analysis and non-negative matrix factorization), EMG normalization methods, and numbers of synergies. SynX performance was most influenced by the choice of synergy analysis algorithm and number of synergies. Principal component analysis with five or six synergies consistently predicted unmeasured muscle excitations the most accurately and with the greatest robustness to EMG normalization method. Furthermore, the associated joint moment matching accuracy was comparable to that produced by initial EMG-driven model calibration using all 16 EMG channels per leg. SynX may facilitate the assessment of human neuromuscular control and biomechanics when important EMG signals are missing.

Study on Adenovirus Infection in vitro with Nanoself-Assembling Peptide as Scaffolds for 3D Culture.

PURPOSE: To construct a three-dimensional (3D) culture model of adenovirus in vitro using the nanoself-assembling peptide RADA16-I as a 3D cell culture scaffold combined with virology experimental technology to provide a novel research method for virus isolation and culture, pathogenesis research, antiviral drug screening and vaccine preparation. METHODS: The nanoself-assembling peptide RADA16-I was used as a 3D scaffold material for 293T cell culture, and adenovirus was cultured in the cells. The growth, morphological characteristics and pathological effects of 3D-cultured 293T cells after adenovirus infection were observed with an inverted microscope and MTS. The proliferation of adenovirus in 293T cells was observed by TEM and detected by qPCR. The levels of TNF-α and IL-8 secreted by adenovirus-infected 293T cells in the RADA16-I 3D culture system were detected by ELISA. RESULTS: The 293T cells grew well in the RADA16-I 3D culture system for a prolonged period of time. The adenovirus infection persisted for a long time with multiple proliferation peaks, which closely resembled those of in vivo infections. The adenovirus virions amplified in the 3D system remained infectious. There were multiple secretion peaks of TNF-α and IL-8 secretion levels in adenovirus-infected 293T cells cultured in 3D culture systems. CONCLUSION: The nanoself-assembling peptide RADA16-I can be used as a 3D scaffold for adenovirus isolation, culture and research. The 3D culture system shows more realistic in vivo effects than two-dimensional (2D) culture.

Three-dimensional culture and clinical drug responses of a highly metastatic human ovarian cancer HO-8910PM cells in nanofibrous microenvironments of three hydrogel biomaterials.

BACKGROUND: Ovarian cancer is a highly aggressive malignant disease in gynecologic cancer. It is an urgent task to develop three-dimensional (3D) cell models in vitro and dissect the cell progression-related drug resistance mechanisms in vivo. In the present study, RADA16-I peptide has the reticulated nanofiber scaffold networks in hydrogel, which is utilized to develop robust 3D cell culture of a high metastatic human ovarian cancer HO-8910PM cell line accompanied with the counterparts of Matrigel and collagen I. RESULTS: Consequently, HO-8910PM cells were successfully cultivated in three types of hydrogel biomaterials, such as RADA16-I hydrogel, Matrigel, and collagen I, according to 3D cell culture protocols. Designer RADA16-I peptide had well-defined nanofiber networks architecture in hydrogel, which provided nanofiber cell microenvironments analogous to Matrigel and collagen I. 3D-cultured HO-8910PM cells in RADA16-I hydrogel, Matrigel, and collagen I showed viable cell proliferation, proper cell growth, and diverse cell shapes in morphology at the desired time points. For a long 3D cell culture period, HO-8910PM cells showed distinct cell aggregate growth patterns in RADA16-I hydrogel, Matrigel, and collagen I, such as cell aggregates, cell colonies, cell clusters, cell strips, and multicellular tumor spheroids (MCTS). The cell distribution and alignment were described vigorously. Moreover, the molecular expression of integrin ß1, E-cadherin and N-cadherin were quantitatively analyzed in 3D-cultured MCTS of HO-8910PM cells by immunohistochemistry and western blotting assays. The chemosensitivity assay for clinical drug responses in 3D context indicated that HO-8910PM cells in three types of hydrogels showed significantly higher chemoresistance to cisplatin and paclitaxel compared to 2D flat cell culture, including IC50 values and inhibition rates. CONCLUSION: Based on these results, RADA16-I hydrogel is a highly competent, high-profile, and proactive nanofiber scaffold to maintain viable cell proliferation and high cell vitality in 3D cell models, which may be particularly utilized to develop useful clinical drug screening platform in vitro.

Dynamic Autonomous Cross Consortium Chain Mechanism in e-Healthcare.

Safe and scalable dynamic autonomous data interaction between medical institutions can increase the number of clinical trial records, which is of great significance for improving the level of medical trial collaboration, especially for clinical decision-making with regard to rare diseases. Through a preset authorization access and consensus mechanism, consortium chain provides integrity and traceability management for medical clinical data. However, how to enable users have ownership of their own medical data and share their medical data safely and dynamically between different medical institutions remains an area of particular concern. To achieve dynamic communication between medical consortium chains, this paper proposes (i) a cross-chain communication mechanism by simplifying the heterogeneous node communication topology and (ii) the construction rules of the node identity credibility path-proof to carry out dynamic construction and verification of the path-proof for cross-chain transactions. In addition, the consensus of the cross-chain transaction is modeled as a threshold digital signature process with multiple privileged subgroups; thus, the intra-chain consortium consensus based on the verification node list is extended to the cross-chain consensus. A smart contract deployment and execution scheme based on rational node value transfer mechanism is proposed by analyzing the value transfer game between nodes. Experimental results showed that the proposed scheme can not only enable patients to share their records safely and autonomously in an authorized medical consortium chain within milliseconds but also realize dynamic adaptive interaction among heterogeneous consortium chains.

How Well Do Commonly Used Co-contraction Indices Approximate Lower Limb Joint Stiffness Trends During Gait for Individuals Post-stroke?

Muscle co-contraction generates joint stiffness to improve stability and accuracy during limb movement but at the expense of higher energetic cost. However, quantification of joint stiffness is difficult using either experimental or computational means. In contrast, quantification of muscle co-contraction using an EMG-based Co-Contraction Index (CCI) is easier and may offer an alternative for estimating joint stiffness. This study investigated the feasibility of using two common CCIs to approximate lower limb joint stiffness trends during gait. Calibrated EMG-driven lower extremity musculoskeletal models constructed for two individuals post-stroke were used to generate the quantities required for CCI calculations and model-based estimation of joint stiffness. CCIs were calculated for various combinations of antagonist muscle pairs based on two common CCI formulations: Rudolph et al. (2000) (CCI 1) and Falconer and Winter (1985) (CCI 2). CCI 1 measures antagonist muscle activation relative to not only total activation of agonist plus antagonist muscles but also agonist muscle activation, while CCI 2 measures antagonist muscle activation relative to only total muscle activation. We computed the correlation between these two CCIs and model-based estimates of sagittal plane joint stiffness for the hip, knee, and ankle of both legs. Although we observed moderate to strong correlations between some CCI formulations and corresponding joint stiffness, these associations were highly dependent on the methodological choices made for CCI computation. Specifically, we found that: (1) CCI 1 was generally more correlated with joint stiffness than was CCI 2, (2) CCI calculation using EMG signals with calibrated electromechanical delay generally yielded the best correlations with joint stiffness, and (3) choice of antagonist muscle pairs significantly influenced CCI correlation with joint stiffness. By providing guidance on how methodological choices influence CCI correlation with joint stiffness trends, this study may facilitate a simpler alternate approach for studying joint stiffness during human movement.