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Abstract Background Evaluating outcome reliability is critical in real-world evidence studies. Overall survival is a common outcome in these studies; however, its capture in real-world data (RWD) sources is often incomplete and supplemented with linked mortality information from external sources. Conflicting recommendations exist for censoring overall survival in real-world evidence studies. This simulation study aimed to understand the impact of different censoring methods on estimating median survival and log hazard ratios when external mortality information is partially captured. Methods We used Monte Carlo simulation to emulate a non-randomized comparative effectiveness study of two treatments with RWD from electronic health records and linked external mortality data. We simulated the time to death, the time to last database activity, and the time to data cutoff. Death events after the last database activity were attributed to linked external mortality data and randomly set to missing to reflect the sensitivity of contemporary real-world data sources. Two censoring schemes were evaluated: (1) censoring at the last activity date and (2) censoring at the end of data availability (data cutoff) without an observed death. We assessed the performance of each method in estimating median survival and log hazard ratios using bias, coverage, variance, and rejection rate under varying amounts of incomplete mortality information and varying treatment effects, length of follow-up, and sample size. Results When mortality information was fully captured, median survival estimates were unbiased when censoring at data cutoff and underestimated when censoring at the last activity. When linked mortality information was missing, censoring at the last activity date underestimated the median survival, while censoring at the data cutoff overestimated it. As missing linked mortality information increased, bias decreased when censoring at the last activity date and increased when censoring at data cutoff. Conclusions Researchers should consider the completeness of linked external mortality information when choosing how to censor the analysis of overall survival using RWD. Substantial bias in median survival estimates can occur if an inappropriate censoring scheme is selected. We advocate for RWD providers to perform validation studies of their mortality data and publish their findings to inform methodological decisions better.

Aim: To contextualize the effectiveness of tisagenlecleucel versus real-world standard of care (SoC) in relapsed/refractory follicular lymphoma. Materials & methods: A retrospective indirect matched comparison study using data from the phase II ELARA trial and the US Flatiron Health Research Database. Results: Complete response rate was 69.1 versus 17.7% and the overall response rate was 85.6 versus 58.1% in tisagenlecleucel versus SoC, post weighting by odds. For overall survival, an estimated reduction in the risk of death was observed in favor of tisagenlecleucel over SoC. The hazard ratio for progressionfree survival was 0.45 (95% CI: 0.26, 0.88), and for time-to-next treatment was 0.34 (95% CI: 0.15, 0.78) with tisagenlecleucel versus SoC. Conclusion: A consistent trend toward improved efficacy end points was observed in favor of tisagenlecleucel versus SoC.

Background and Aims: Running can induce advantageous cardiovascular effects such as improved arterial stiffness and blood-supply perfusion. However, the differences between the vascular and blood-flow perfusion conditions under different levels of endurance-running performance remains unclear. The present study aimed to assess the vascular and blood-flow perfusion conditions among 3 groups (44 male volunteers) according to the time taken to run 3 km: Level 1, Level 2, and Level 3. Methods: The radial blood pressure waveform (BPW), finger photoplethygraphy (PPG), and skin-surface laser-Doppler flowmetry (LDF) signals of the subjects were measured. Frequency-domain analysis was applied to BPW and PPG signals; time- and frequency-domain analyses were applied to LDF signals. Results: Pulse waveform and LDF indices differed significantly among the three groups. These could be used to evaluate the advantageous cardiovascular effects provided by long-term endurance-running training, such as vessel relaxation (pulse waveform indices), improvement in blood supply perfusion (LDF indices), and changes in cardiovascular regulation activities (pulse and LDF variability indices). Using the relative changes in pulse-effect indices, we achieved almost perfect discrimination between Level 3 and Level 2 (AUC = 0.878). Furthermore, the present pulse waveform analysis could also be used to discriminate between the Level-1 and Level-2 groups. Conclusions: The present findings contribute to the development of a noninvasive, easy-to-use, and objective evaluation technique for the cardiovascular benefits of prolonged endurance-running training.

Head orientation prediction is one of the solutions to reduce end-to-end latency on Virtual Reality (VR) systems and is important since it can alleviate negative effects like motion sickness. This study compared head orientation prediction models from two different electromyography (EMG) systems: surface EMG (sEMG) and High-Density EMG (HD-EMG). The deep learning method was used to train the prediction model, and the results showed that the model with input from the pre-processed sEMG + IMU sensor outperformed the model with input from the HD-EMG + IMU sensor. However, the decreasing performance from HD-EMG was compensated by its comfort and the ease of use of its electrode. This tradeoff between performance and usability with sEMG compared to HD-EMG should be a consideration for users who want to choose between performance and ease of use for head orientation prediction purposes. Comparison with state-of-the-art head prediction methods proved that the sEMG-based model offers better performance in predictions when users change their head directions, which was quantified by calculating the dt peaks. In other words, our sEMG-based prediction model is suitable for VR applications, which require the user to perform high-intensity or abrupt movements, such as in FPS games or exercise/sports games.

Background: The few previous studies that focused on the effects of compression garments (CG) on distance running performance have simultaneously measured electromyogram, physiological, and perceptual parameters. Therefore, this study investigated the effects of CG on muscle activation and median frequency during and after distance running, as well as blood-lactate concentration and rating of perceived exertion (RPE) during distance running. Methods: Eight healthy male recreational runners were recruited to randomly perform two 40 min treadmill running trials, one with CG, and the other with control garment made of normal cloth. The RPE and the surface electromyography (EMG) of 5 lower extremity muscles including gluteus maximus (GM), rectus femoris (RF), semitendinosus (ST), tibialis anterior (TA), and gastrocnemius (GAS) were measured during the running trial. The blood-lactate levels before and after the running trial were measured. Results: Wearing CG led to significant lower muscle activation (p 0.05). Conclusion: Wearing CG was associated with significantly lower muscle activation and higher median frequency in the running-related key muscles during distance running. This finding suggested that wearing CG may improve muscle function, which might enhance running performance and prevent muscle fatigue.

Objective: This study hypothesized that the suture anchor of tibial fixation method of PMMR repair technique is the main factor which reduce the gap formation or over displacement of tear site in initial healing, and then investigated the fixation stability of 4 different tibial fixations through cyclic and ultimate failure load testing of meniscal root sutures. Methods: Twenty-four porcine tibiae with intact medial meniscus roots were randomly assigned into 4 groups: transosseous suture, washer, suture anchor, or screw with washer. Each sample underwent cyclic loading followed by a load-to-failure test. Displacement, maximum load to failure, stiffness, and elongation at failure load were recorded. Results: The maximum average load and displacement at failure for each of the repair groups were as follows: transosseous suture, 232.8 N and 12.16 mm; washer, 189.9 N and 21.5 mm; suture anchor, 140.6 N and 13.8 mm; and screw with washer, 167.9 N and 18.9 mm. The maximum stiffness values for each of the repair groups were as follows: transosseous suture, 19.5 ± 0.7 N/mm; washer, 21.5 ± 1.4 N/mm; suture anchor, 13.8 ± 0.7 N/mm; and screw with washer, 18.9 ± 3.9 N/mm. The mean elongation across the repairs for each of the repair groups after 1000 loading cycles was: transosseous suture, 3.74 ± 0.28 mm; washer, 3.04 ± 0.13 mm; suture anchor, 2.25 ± 0.33 mm; and screw with washer, 2.43 ± 0.19 mm. The mean elongation was significantly less with the suture anchor than with the other techniques (p < .05). Conclusion: Under physiological loading, our results indicate that a slower rehabilitation program with limited flexion and only partial weight bearing is advised when using a suture anchor because of the lower maximum load and stiffness. The translational potential of this article: Tibial fixation using a washer or a screw with a washer is an effective and cost-saving technique when an option is required with high stiffness and low displacement at failure.

Abstract Background Precise evaluation of the hip abductor and adductor muscles function in total hip arthroplasty (THA) patients during gait could help prevent postoperative complications and optimize the rehabilitation training program. The purpose of this study was to elucidate the effects of THA on the hip abductor and adductor muscle lengths and moment arms of in vivo patients during gait. Methods Ten unilateral THA patients received CT scans and dual fluoroscopic imaging for the hip kinematics during gait. The hip abductor and adductor muscle insertions were digitized on the 3D hip model for the determination of their dynamic lines of action and moment arms. Changes in the hip abductor and adductor muscle lengths and moment arms of THA patients between the implanted and non-implanted sides were quantified during gait. Results The adductor longus, adductor brevis, and pectineus of the implanted hips had significantly (P < 0.05) less elongation than that of the non-implanted side during the stance phase. The gluteus medius, gluteus minimus, and piriformis moment arms of the implanted side were significantly shorter. The piriformis muscle moment arm was significantly larger. In the double support phase, the adductor magnus and adductor longus moment arms of the implanted sides were significantly decreased. Conclusions Results suggested that the adverse effects of THA on hip stability. Development of a rehabilitation program considering the effects of THA is essential. Accurate surgical techniques may reduce the impact of THA on the peripheral muscles.

Routine cervical cancer screening has significantly decreased the incidence and mortality of cervical cancer. As selection of proper screening modalities depends on well-validated clinical decision algorithms, retrospective review correlating cytology and HPV test results with cervical biopsy diagnosis is essential for validating and revising these algorithms to changing technologies, demographics, and optimal clinical practices. However, manual categorization of the free-text biopsy diagnosis into discrete categories is extremely laborious due to the overwhelming number of specimens, which may lead to significant error and bias. Advances in machine learning and natural language processing (NLP), particularly over the last decade, have led to significant accomplishments and impressive performance in computer-based classification tasks. In this work, we apply an efficient version of an NLP framework, FastText™, to an annotated cervical biopsy dataset to create a supervised classifier that can assign accurate biopsy categories to free-text biopsy interpretations with high concordance to manually annotated data (>99.6%). We present cases where the machine-learning classifier disagrees with previous annotations and examine these discrepant cases after referee review by an expert pathologist. We also show that the classifier is robust on an untrained external dataset, achieving a concordance of 97.7%. In conclusion, we demonstrate a useful application of NLP to a real-world pathology classification task and highlight the benefits and limitations of this approach.

Introduction: Falls are among the most significant factors affecting older adults' lives. Almost 30%~50% of older adults have experienced a fall. Therefore, walking appropriately is crucial for older adults. Consequently, it is necessary to design walking support equipment. This study investigated the effects of a novel additional elastic hip flexor band on angle (abduction, adduction, dorsiflexion, and plantar flexion), gait (step length, step cadence, and height between ground and toe), and vertical ground reaction force at comfortable and maximum walking speeds in older adults. Methods: Twenty healthy adults aged 65-74 years voluntarily participated in this study. Each subject randomly wore the novel additional elastic hip flexor band at 0%, 50%, and 100% extension while walking three times at comfortable and maximum speeds. A three-dimensional motion capture system and AMTI force plate were used to measure their kinematic and kinetic parameters during walking. The analyzed gait cycle was defined as the right heel touching the force plate to touching the ground again after three steps. All kinematic and kinetic parameters at different walking speeds were compared using repeated measure two-way analysis of variance. Results: Older adults who wore the additional elastic hip flexor band at 50% and 100% extension had greater maximum hip flexion angles than those who wore it at 0% extension (p < 0.05). Older adults who wore the additional elastic hip flexor band at 100% extension had higher toe elevations than those who wore it at 0% extension (p < 0.05). Conclusion: Older adults who wore the additional elastic hip flexor band showed increased hip flexion and extension angles. These findings suggest that the novel additional elastic hip flexor band might help older adults cross the threshold, go upstairs, get on the buses, and perform other daily activities. It might also further reduce their fall risk. [ABSTRACT FROM AUTHOR]

Background: Walking while performing cognitive and motor tasks simultaneously interferes with gait performance and may lead to falls in older adults with mild cognitive impairment (MCI). Executive function, which seems to play a key role in dual-task gait performance, can be improved by combined physical and cognitive training. Virtual reality (VR) has the potential to assist rehabilitation, and its effect on physical and cognitive function requires further investigation. The purpose of this study was to assess the effects of VR-based physical and cognitive training on executive function and dual-task gait performance in older adults with MCI, as well as to compare VR-based physical and cognitive training with traditional combined physical and cognitive training.Method: Thirty-four community-dwelling older adults with MCI were randomly assigned into either a VR-based physical and cognitive training (VR) group or a combined traditional physical and cognitive training (CPC) group for 36 sessions over 12 weeks. Outcome measures included executive function [Stroop Color and Word Test (SCWT) and trail making test (TMT) A and B], gait performance (gait speed, stride length, and cadence) and dual-task costs (DTCs). Walking tasks were performed during single-task walking, walking while performing serial subtraction (cognitive dual task), and walking while carrying a tray (motor dual task). The GAIT Up system was used to evaluate gait parameters including speed, stride length, cadence and DTCs. DTC were defined as 100 * (single-task gait parameters − dual-task gait parameters)/single-task gait parameters.Results: Both groups showed significant improvements in the SCWT and single-task and motor dual-task gait performance measures. However, only the VR group showed improvements in cognitive dual-task gait performance and the DTC of cadence. Moreover, the VR group showed more improvements than the CPC group in the TMT-B and DTC of cadence with borderline significances.Conclusion: A 12-week VR-based physical and cognitive training program led to significant improvements in dual-task gait performance in older adults with MCI, which may be attributed to improvements in executive function.

This study classified the gait patterns of normal and stroke participants by using time- and frequency-domain features obtained from data provided by an inertial measurement unit sensor placed on the subject’s lower back (L5). Twenty-three participants were included and divided into two groups: healthy group (young and older adults) and stroke group. Time- and frequency-domain features from an accelerometer were extracted, and a feature selection method comprising statistical analysis and signal-to-noise ratio (SNR) calculation was used to reduce the number of features. The features were then used to train four Support Vector Machine (SVM) kernels, and the results were subsequently compared. The quadratic SVM kernel had the highest accuracy (93.46%), as evaluated through cross-validation. Moreover, when different datasets were used on model testing, both the quadratic and cubic kernels showed the highest accuracy (96.55%). These results demonstrated the effectiveness of this study’s classification method in distinguishing between normal and stroke gait patterns, with only using a single sensor placed on the L5.

Buckypaper consisting of a carbon nanotube (CNT) sheet has a great potential for sensing and structural applications due to the exceptional piezoresistive and mechanical properties of CNTs. In this work, buckypaper was impregnated with the epoxy resin to improve the fragility and handling capability. The mechanical properties of the buckypaper/epoxy composite were determined by the tensile and nanoindentation tests. A thermogravimetric analyzer (TGA) was used to evaluate the thermal stability. Strain and temperature sensing performances of the buckypaper/epoxy composite based on the piezoresistive effect were investigated using a meter source. Experimental results indicated that the elastic modulus and ultimate strength of the buckypaper/epoxy composite were increased by 82% and 194%, respectively, in comparison with the pristine buckypaper, while the strain and temperature sensitivities were decreased by 33% and 0.2%, respectively. A significant increase of the tensile strength accompanied with a moderate decrease of the strain sensitivity demonstrates that the overall performance of buckypaper/epoxy composite is better than that of pristine buckypaper.

We study the foot plantar sensor placement by a deep reinforcement learning algorithm without using any prior knowledge of the foot anatomical area. To apply a reinforcement learning algorithm, we propose a sensor placement environment and reward system that aims to optimize fitting the center of pressure (COP) trajectory during the self-selected speed running task. In this environment, the agent considers placing eight sensors within a 7 × 20 grid coordinate system, and then the final pattern becomes the result of sensor placement. Our results show that this method (1) can generate a sensor placement, which has a low mean square error in fitting ground truth COP trajectory, and (2) robustly discovers the optimal sensor placement in a large number of combinations, which is more than 116 quadrillion. This method is also feasible for solving different tasks, regardless of the self-selected speed running task.

In this work, buckypaper composed of multi-walled carbon nanotubes (MWCNT) was prepared through a vacuum filtration process. The effect of MWCNT aspect ratio on the buckypaper performance was investigated. The freestanding and highly flexible buckypaper can be used as a sensor to attach on a complex surface monitoring the strain and temperature at the critical area. The mechanical properties of the buckypaper were examined using the tensile and nanoindentation tests. The strain and temperature sensitivities of the buckypaper were evaluated through the four-point bending and thermal chamber tests, respectively. In addition, the microstructure and thermal stability of the buckypaper were studied by scanning electron microscopy (SEM) and thermogravimetric analyzer (TGA), respectively. Experimental results showed that the mechanical properties such as Young’s modulus, tensile strength, fracture strain, and hardness of the buckypaper made of high aspect ratio MWCNTs were significantly superior to the buckypaper consisted of low aspect ratio MWCNTs, while the strain and temperature sensitivities of the buckypaper composed of low aspect ratio MWCNTs were better than that of the buckypaper made of high aspect ratio MWCNTs.

Evaluations are vital to quantify the functionalities of athletic footwear, such as the performance of slip resistance, shock absorption, and rebound. Computational technology has progressed to become a promising solution for accelerating product development time and providing customized products in order to keep up with the competitive contemporary footwear market. In this research, the effects of various tread pattern designs on traction performance in a normal gait were analyzed by employing an approach that integrated computational simulation and gait analysis. A state-of-the-art finite element (FE) model of a shoe was developed by digital sculpting technology. A dynamic plantar pressure distribution was automatically applied to interpret individualized subject conditions. The traction performance and real contact area between the shoe and the ground during the gait could be characterized and predicted. The results suggest that the real contact area and the structure of the outsole tread design influence the traction performance of the shoe in dry conditions. This computational process is more efficient than mechanical tests in terms of both cost and time, and it could bring a noticeable benefit to the footwear industry in the early design phases of product development.

This study is aimed at determining the effects of midsole thickness on movement characteristic during side cutting movement. Fifteen athletes performed side-step cutting while wearing shoes with varying midsole thicknesses. Temporal-spatial and ground reaction force variables as well as foot and ankle frontal kinematics were used to describe breaking and propulsive movement characteristics and modulation strategies. Regardless of midsole thickness, temporal-spatial variables and breaking and propulsive force during side cutting were statistically unchanged. Significantly greater peaks of ankle inversion and plantarflexion with a thicker sole and greater midtarsal pronation with a thinner sole were observed. Current results demonstrated that hypotheses formed solely based on material testing were insufficient to understand the adaptations in human movement because of the redundancy of the neuromusculoskeletal system. Participants were able to maintain temporal-spatial performance during side cutting while wearing shoes with midsoles of varying thicknesses. Increased pronation for a thinner sole might help reduce the force of impact but might be associated with an increased risk of excessive stress on soft tissue. Increased peak of ankle inversion and plantarflexion for a thicker sole may be unfavorable for the stability of ankle joint. Information provided in human movement testing is crucial for understanding factors associated with movement characteristics and injury and should be considered in the future development of shoe design.

Electromyography (EMG) sensors have been used to study the sequence of muscle contractions during sit-to-stand (STS) in post-stroke patients. However, the majority of the studies used wired sensors with a limited number of placements. Using the latest improved wearable technology with 16 sensors, the current study was a thorough investigation to evaluate the contraction sequences of eight key muscles on the trunk and bilateral limbs during STS in post-stroke patients, as it became feasible. Multiple wearable sensors for the detection of muscle contraction sequences showed that the post-stroke patients performed STS with abnormal firing sequences, not only in the primary mover on the sagittal plane during raising, but also in the tibialis anterior, which may affect anticipatory postural adjustment in the gluteus medius, which may affect balance control. The abnormal tibialis anterior contraction until the early ascending phase and the delayed firing of the gluteus muscles highlight the importance of whole-kinetic-chain monitoring of contraction sequences using wearable sensors. The findings can be helpful for the design of therapeutic exercises.

This study aimed to find the correlation between conventional Arch Index (AI) measurements and our prototype of a simplified insole-based plantar pressure measurement system and to find out the effective plantar pressure sensor position. Twenty-one subjects participated in this study, which was divided into two groups: 10 subjects with flatfoot and 11 subjects with normal foot. Five force sensitive resistance sensors were used on this prototype using Arduino as the data acquisition device. Two types of trials, namely static and dynamic, were conducted to validate our system against the ink-type AI measurement as a golden standard. The results showed that in the static trial, there was a high linear correlation with the medial arch sensor configuration, while in the dynamic trial, there was a high linear correlation in the medial arch sensor configuration and sensor 5 configuration. This study showed that both static and dynamic tests using the self-developed device could effectively determine most of the flatfoot subjects and suggests that in the future, it can be applied in clinical applications because of its advantages when compared to the expensive-high tech graphic input board and conventional tools, like ink-type based measurements.

The aim of this study was to conduct a comprehensive analysis of the placement of multiple wearable sensors for the purpose of analyzing and classifying the gaits of patients with neurological disorders. Seven inertial measurement unit (IMU) sensors were placed at seven locations: the lower back (L5) and both sides of the thigh, distal tibia (shank), and foot. The 20 subjects selected to participate in this study were separated into two groups: stroke patients (11) and patients with neurological disorders other than stroke (brain concussion, spinal injury, or brain hemorrhage) (9). The temporal parameters of gait were calculated using a wearable device, and various features and sensor configurations were examined to establish the ideal accuracy for classifying different groups. A comparison of the various methods and features for classifying the three groups revealed that a combination of time domain and gait temporal feature-based classification with the Multilayer Perceptron (MLP) algorithm outperformed the other methods of feature-based classification. The classification results of different sensor placements revealed that the sensor placed on the shank achieved higher accuracy than the other sensor placements (L5, foot, and thigh). The placement-based classification of the shank sensor achieved 89.13% testing accuracy with the Decision Tree (DT) classifier algorithm. The results of this study indicate that the wearable IMU device is capable of differentiating between the gait patterns of healthy patients, patients with stroke, and patients with other neurological disorders. Moreover, the most favorable results were reported for the classification that used the combination of time domain and gait temporal features as the model input and the shank location for sensor placement.

Kinases play fundamental roles in the brain. Through complex signaling pathways, kinases regulate the strength of protein:protein interactions (PPI) influencing cell cycle, signal transduction, and electrical activity of neurons. Changes induced by kinases on neuronal excitability, synaptic plasticity and brain connectivity are linked to complex brain disorders, but the molecular mechanisms underlying these cellular events remain for the most part elusive. To further our understanding of brain disease, new methods for rapidly surveying kinase pathways in the cellular context are needed. The bioluminescence-based luciferase complementation assay (LCA) is a powerful, versatile toolkit for the exploration of PPI. LCA relies on the complementation of two firefly luciferase protein fragments that are functionally reconstituted into the full luciferase enzyme by two interacting binding partners. Here, we applied LCA in live cells to assay 12 kinase pathways as regulators of the PPI complex formed by the voltage-gated sodium channel, Nav1.6, a transmembrane ion channel that elicits the action potential in neurons and mediates synaptic transmission, and its multivalent accessory protein, the fibroblast growth factor 14 (FGF14). Through extensive dose-dependent validations of structurally-diverse kinase inhibitors and hierarchical clustering, we identified the PI3K/Akt pathway, the cell-cycle regulator Wee1 kinase, and protein kinase C (PKC) as prospective regulatory nodes of neuronal excitability through modulation of the FGF14:Nav1.6 complex. Ingenuity Pathway Analysis shows convergence of these pathways on glycogen synthase kinase 3 (GSK3) and functional assays demonstrate that inhibition of GSK3 impairs excitability of hippocampal neurons. This combined approach provides a versatile toolkit for rapidly surveying PPI signaling, allowing the discovery of new modular pathways centered on GSK3 that might be the basis for functional alterations between the normal and diseased brain.