TRPC6 inhibitor (BI 764198) to reduce risk and severity of ARDS due to COVID-19: a phase II randomised controlled trial.

BACKGROUND: Despite the availability of COVID-19 vaccinations, there remains a need to investigate treatments to reduce the risk or severity of potentially fatal complications of COVID-19, such as acute respiratory distress syndrome (ARDS). This study evaluated the efficacy and safety of the transient receptor potential channel C6 (TRPC6) inhibitor, BI 764198, in reducing the risk and/or severity of ARDS in patients hospitalised for COVID-19 and requiring non-invasive, supplemental oxygen support (oxygen by mask or nasal prongs, oxygen by non-invasive ventilation or high-flow nasal oxygen). METHODS: Multicentre, double-blind, randomised phase II trial comparing once-daily oral BI 764198 (n=65) with placebo (n=64) for 28 days (+2-month follow-up). PRIMARY ENDPOINT: proportion of patients alive and free of mechanical ventilation at day 29. Secondary endpoints: proportion of patients alive and discharged without oxygen (day 29); occurrence of either in-hospital mortality, intensive care unit admission or mechanical ventilation (day 29); time to first response (clinical improvement/recovery); ventilator-free days (day 29); and mortality (days 15, 29, 60 and 90). RESULTS: No difference was observed for the primary endpoint: BI 764198 (83.1%) versus placebo (87.5%) (estimated risk difference -5.39%; 95% CI -16.08 to 5.30; p=0.323). For secondary endpoints, a longer time to first response (rate ratio 0.67; 95% CI 0.46 to 0.99; p=0.045) and longer hospitalisation (+3.41 days; 95% CI 0.49 to 6.34; p=0.023) for BI 764198 versus placebo was observed; no other significant differences were observed. On-treatment adverse events were similar between trial arms and more fatal events were reported for BI 764198 (n=7) versus placebo (n=2). Treatment was stopped early based on an interim observation of a lack of efficacy and an imbalance of fatal events (Data Monitoring Committee recommendation). CONCLUSIONS: TRPC6 inhibition was not effective in reducing the risk and/or severity of ARDS in patients with COVID-19 requiring non-invasive, supplemental oxygen support. TRIAL REGISTRATION NUMBER: NCT04604184.

Effects of central and unilateral posteroanterior mobilization on cervical lordosis, muscle stiffness and ROM in patient with ankylosing spondylitis: case study.

[Purpose] The aim of this study was to determine the effects of central and unilateral posteroanterior (PA) mobilization on cervical lordosis, muscle stiffness and range of motion in a patient with ankylosing spondylitis (AS). [Subject and Methods] The subject of this case study was diagnosed with AS in 1997. At baseline, variance was measured without any intervention during the first 3 days (2016.6.13-2016.6.15). Cervical PA mobilization was applied to each segment from C2-C7 from the 4th to the 11th day for 8 days. Intervention was not performed from the 12th to the 15th days for 4 days. Variances were measured a final time without intervention on the 16th day (2016.6.28). [Results] Cervical lordosis was seen to have increased. Muscle stiffness was significantly decreased after intervention and the effect of treatment lasted for five days without any additional intervention. The cervical flexion and extension angles were increased. However these increases were not statistically significant. Both the lateral flexion and left rotation angle were significantly increased and the effects of treatment lasted for five days without any additional intervention. [Conclusion] These results suggest that central and unilateral PA mobilization is effective in increasing cervical lordosis and range of motion, and decreasing muscle stiffness in patients with AS.

Effect of eye movements and proprioceptive neuromuscular facilitation on balance and head alignment in stroke patients with neglect syndrome.

[Purpose] The purpose of this study was to assess the effect of eye movements and proprioceptive neuromuscular facilitation (PNF) on patients with neglect syndrome. [Subjects and Methods] The subjects were randomly allocated to 2 groups: the eye movements (EM) group; and the PNF with eye movements (PEM) group. The program was conducted five times each week for 6 weeks. Balance (both static and dynamic) and head alignment (craniovertebral angle and cranial rotation angle) were measured before and after testing. [Results] In measurements of static balance, the EM group showed significant improvement in sway length and sway area when examined in the eyes-open condition, but not when examined in the eyes-closed condition. The PEM group showed significant improvement when examined under both conditions. In the assessment of dynamic balance, both groups showed significant improvement in measurements of sway areas. With respect to head alignment, there were no significant differences pre- and post-testing in either the craniovertebral angle or the cranial rotation angle in the EM group, but the PEM group showed significant differences in both measurements. [Conclusion] These results suggest that in stroke patients with neglect syndrome, PNF with eye movements, rather than eye movements alone, has a greater positive effect on balance and head alignment.

The effects of taping, stretching, and joint exercise on hip joint flexibility and range of motion.

[Purpose] This study aimed to examine the effects of joint exercise, taping, and stretching on hip joint flexion, flexibility, and range of motion. [Subjects and Methods] Forty-five college students in their 20s were randomly assigned and equally divided into three groups, as follows: a stretching group, a taping and exercise group, and an exercise group. Changes in trunk range of motion and hip joint flexibility of the three groups were measured before and after the intervention. [Results] Comparison between flexibility before and after the intervention revealed statistically significant changes in all three groups. Moreover, the evaluation of joint range of motion after the intervention showed that there were statistically significant changes in all three groups. [Conclusion] Taping, stretching, and joint exercise are considered effective for the increase in flexibility and joint range of motion.

Effects of joint position on the distraction distance during grade III glenohumeral joint distraction in healthy individuals.

[Purpose] The study investigated the effects of joint position on the distraction distance during Grade III glenohumeral joint distraction in healthy individuals. [Subjects and Methods] Twenty adults in their forties without shoulder disease were randomly divided into neutral position group (NPG; n = 7), resting position group (RPG; n = 7), and end range position group (ERPG; n = 6). After Kaltenborn Grade III distraction for 40s, the distance between glenoid fossa and humeral head was measured by ultrasound. [Results] The average distances between the humeral head and glenoid fossa before distraction were 2.86 ± 0.81, 3.21 ± 0.47, and 3.55 ± 0.59 mm for the NP, RP, and ERP groups. The distances after applying distraction were 3.12 ± 0.51, 3.86 ± 0.55, and 4.35 ± 0.32 mm. Between-group comparison after applying distraction revealed no significant differences between the NP and RP groups, while there was a statistically significant difference between the NP and RP groups, as well as between the NP and ERP groups. [Conclusion] Joint space was largest in ERP individuals when performing manual distraction.

A Comparative Study of Automated Machine Learning Platforms for Exercise Anthropometry-Based Typology Analysis: Performance Evaluation of AWS SageMaker, GCP VertexAI, and MS Azure.

The increasing prevalence of machine learning (ML) and automated machine learning (AutoML) applications across diverse industries necessitates rigorous comparative evaluations of their predictive accuracies under various computational environments. The purpose of this research was to compare and analyze the predictive accuracy of several machine learning algorithms, including RNNs, LSTMs, GRUs, XGBoost, and LightGBM, when implemented on different platforms such as Google Colab Pro, AWS SageMaker, GCP Vertex AI, and MS Azure. The predictive performance of each model within its respective environment was assessed using performance metrics such as accuracy, precision, recall, F1-score, and log loss. All algorithms were trained on the same dataset and implemented on their specified platforms to ensure consistent comparisons. The dataset used in this study comprised fitness images, encompassing 41 exercise types and totaling 6 million samples. These images were acquired from AI-hub, and joint coordinate values (x, y, z) were extracted utilizing the Mediapipe library. The extracted values were then stored in a CSV format. Among the ML algorithms, LSTM demonstrated the highest performance, achieving an accuracy of 73.75%, precision of 74.55%, recall of 73.68%, F1-score of 73.11%, and a log loss of 0.71. Conversely, among the AutoML algorithms, XGBoost performed exceptionally well on AWS SageMaker, boasting an accuracy of 99.6%, precision of 99.8%, recall of 99.2%, F1-score of 99.5%, and a log loss of 0.014. On the other hand, LightGBM exhibited the poorest performance on MS Azure, achieving an accuracy of 84.2%, precision of 82.2%, recall of 81.8%, F1-score of 81.5%, and a log loss of 1.176. The unnamed algorithm implemented on GCP Vertex AI showcased relatively favorable results, with an accuracy of 89.9%, precision of 94.2%, recall of 88.4%, F1-score of 91.2%, and a log loss of 0.268. Despite LightGBM's lackluster performance on MS Azure, the GRU implemented in Google Colab Pro displayed encouraging results, yielding an accuracy of 88.2%, precision of 88.5%, recall of 88.1%, F1-score of 88.4%, and a log loss of 0.44. Overall, this study revealed significant variations in performance across different algorithms and platforms. Particularly, AWS SageMaker's implementation of XGBoost outperformed other configurations, highlighting the importance of carefully considering the choice of algorithm and computational environment in predictive tasks. To gain a comprehensive understanding of the factors contributing to these performance discrepancies, further investigations are recommended.

A Systematic Review and Meta-Analysis of the Effectiveness of Virtual Reality-Based Rehabilitation Therapy on Reducing the Degree of Pain Experienced by Individuals with Low Back Pain.

BACKGROUND: The concept of virtual reality (VR)-based rehabilitation therapy for treating people with low back pain is of growing research interest. However, the effectiveness of such therapy for pain reduction in clinical settings remains controversial. METHODS: The present study was conducted according to the reporting guidelines presented in the Preferred Reporting Items for Systematic Reviews and Meta-analyses statement. We searched the PubMed, Embase, CENTRAL, and ProQuest databases for both published and unpublished papers. The Cochrane risk of bias tool (version 2) was used to evaluate the quality of the selected studies. GRADEprofiler software (version 3.6.4) was used to evaluate the level of evidence. We analyzed the included research results using RevMan software (version 5.4.1). RESULTS: We included a total of 11 articles in the systematic review and meta-analysis, with a total of 1761 subjects. Having assessed the quality of these studies, the risk of bias was generally low with high heterogeneity. The results revealed a small to medium effect (standardized mean difference = ±0.37, 95% confidence interval: 0.75 to 0) based on evidence of moderate overall quality. CONCLUSION: There is evidence that treatment using VR improves patients' pain. The effect size was small to medium, with the studies presenting evidence of moderate overall quality. VR-based treatment can reduce pain; therefore, it may help in rehabilitation therapy.

Highly Selective and pH-Stable Reverse Osmosis Membranes Prepared via Layered Interfacial Polymerization.

Ultrathin and smooth polyamide (PA) reverse osmosis (RO) membranes have attracted significant interest due to their potential advantages of high permeance and low fouling propensity. Although a layered interfacial polymerization (LIP) technique aided by the insertion of a polyelectrolyte interlayer has proven effective in fabricating ultrathin and uniform membranes, the RO performance and pH stability of the fabricated LIP membrane remain inadequate. In this study, a poly(piperazineamide) (PIPA) layer prepared via interfacial polymerization (IP) was employed as an interlayer to overcome the limitations of the prototype LIP method. Similar to the control polyelectrolyte-interlayered LIP membrane, the PIPA-interlayered LIP (pLIP) membrane had a much thinner (~20 nm) and smoother selective layer than the membrane fabricated via conventional IP due to the highly surface-confined and uniform LIP reaction. The pLIP membrane also exhibited RO performance exceeding that of the control LIP and conventional IP-assembled membranes, by enabling denser monomer deposition and a more confined interfacial reaction. Importantly, the chemically crosslinked PIPA interlayer endowed the pLIP membrane with higher pH stability than the control polyelectrolyte interlayer. The proposed strategy enables the fabrication of high-performance and pH-stable PA membranes using hydrophilic supports, which can be applied to other separation processes, including osmosis-driven separation and organic solvent filtration.

Deep Learning Approaches to Automated Video Classification of Upper Limb Tension Test.

The purpose of this study was to classify ULTT videos through transfer learning with pre-trained deep learning models and compare the performance of the models. We conducted transfer learning by combining a pre-trained convolution neural network (CNN) model into a Python-produced deep learning process. Videos were processed on YouTube and 103,116 frames converted from video clips were analyzed. In the modeling implementation, the process of importing the required modules, performing the necessary data preprocessing for training, defining the model, compiling, model creation, and model fit were applied in sequence. Comparative models were Xception, InceptionV3, DenseNet201, NASNetMobile, DenseNet121, VGG16, VGG19, and ResNet101, and fine tuning was performed. They were trained in a high-performance computing environment, and validation and loss were measured as comparative indicators of performance. Relatively low validation loss and high validation accuracy were obtained from Xception, InceptionV3, and DenseNet201 models, which is evaluated as an excellent model compared with other models. On the other hand, from VGG16, VGG19, and ResNet101, relatively high validation loss and low validation accuracy were obtained compared with other models. There was a narrow range of difference between the validation accuracy and the validation loss of the Xception, InceptionV3, and DensNet201 models. This study suggests that training applied with transfer learning can classify ULTT videos, and that there is a difference in performance between models.

Latent profile analysis of lifestyle characteristics and health risk behaviors among Koreans who have completed industrial accident care.

This study investigated the characteristics and health behavior profiles of 1,803 workers who had experienced industrial accidents. Average weekly exercise days, average number of cigarettes smoked per day, average daily sleep duration, and number of days of alcohol consumption were selected to investigate health behavior profiles. Specifically, latent profile analysis was applied to identify the health behavior profiles of people who had completed industrial accident care; the latent classes were the health-conscious type (n=240), the potential-risk type (n=850), and the high-risk type (n=713). Comparison of the health-conscious and potential-risk types indicated that younger subjects, the employed, and those with lower social status and life satisfaction were more likely to be the potential-risk type. Comparison of the health-conscious and high-risk types revealed that males, younger subjects, the employed, those without chronic illnesses, and those with lower social status and life satisfaction were more likely to be the high-risk type. The results suggest that industrial accident victims who have completed accident care have different health behaviors and it is necessary to improve health promotion based on health type characteristics.

Impact of the number of painful stimuli on life satisfaction among Korean industrial accident workers completing convalescence: dual mediating effects of self-esteem and sleeping time.

This study examined the impact of the number of painful stimuli on life satisfaction among workers who experienced an industrial accident and investigated how self-esteem and sleeping time affected life satisfaction. The Korea Workers' Compensation & Welfare Service conducted the first nationwide panel survey on occupational health and safety insurance in 2013-2014 through a stratified systematic sampling on 2,000 industrial accident workers who completed convalescence. Based on the dataset, our study analyzed 1,832 workers experiencing an industrial accident after excluding 168 disease patients. For the research model analysis, a four-stage hierarchical regression analysis technique was applied using the SPSS regression analysis Macro program of PROCESS Procedure. To test mediated indirect effects of the self-esteem and sleeping time, the bootstrapping technique was applied. Life satisfaction, self-esteem and sleeping time decreased as the number of painful stimuli increased. Life satisfaction decreased as self-esteem and sleeping time decreased. On balance, the partial mediation model confirmed that self-esteem and sleeping time both mediate the impact of the number of painful stimuli on life satisfaction.

Nanoscale Pillar-Enhanced Tribological Surfaces as Antifouling Membranes.

We present a nonconventional membrane surface modification approach that utilizes surface topography to manipulate the tribology of foulant accumulation on water desalination membranes via imprinting of submicron titanium dioxide (TiO2) pillar patterns onto the molecularly structured, flat membrane surface. This versatile approach overcomes the constraint of the conventional approach relying on interfacial polymerization that inevitably leads to the formation of ill-defined surface topography. Compared to the nonpatterned membranes, the patterned membranes showed significantly improved fouling resistance for both organic protein and bacterial foulants. The use of hydrophilic TiO2 as a pattern material increases the membrane hydrophilicity, imparting improved chemical antifouling resistance to the membrane. Fouling behavior was also interpreted in terms of the topographical effect depending on the relative size of foulants to the pattern dimension. In addition, computational fluid dynamics simulation suggests that the enhanced antifouling of the patterned membrane is attributed to the enhancement in overall and local shear stress at the fluid-TiO2 pattern interface.

Tailor-made polyamide membranes for water desalination.

Independent control of the extrinsic and intrinsic properties of the polyamide (PA) selective layer is essential for designing thin-film composite (TFC) membranes with performance characteristics required for water purification applications besides seawater desalination. Current commercial TFC membranes fabricated via the well-established interfacial polymerization (IP) approach yield materials that are far from ideal because their layer thickness, surface roughness, polymer chemistry, and network structure cannot be separately tailored. In this work, tailor-made PA-based desalination membranes based on molecular layer-by-layer (mLbL) assembly are presented. The mLbL technique enables the construction of an ultrathin and highly cross-linked PA selective layer in a precisely and independently controlled manner. The mLbL-assembled TFC membranes exhibit significant enhancements in performance compared to their IP-assembled counterparts. A maximum sodium chloride rejection of 98.2% is achieved along with over 2.5 times higher water flux than the IP-assembled counterpart. More importantly, this work demonstrates the broad applicability of mLbL in fabricating a variety of PA-based TFC membranes with nanoscale control of the selective layer thickness and roughness independent of the specific polyamide chemistry.

Layer-by-layer assembly of graphene oxide nanosheets on polyamide membranes for durable reverse-osmosis applications.

Improving membrane durability associated with fouling and chlorine resistance remains one of the major challenges in desalination membrane technology. Here, we demonstrate that attractive features of graphene oxide (GO) nanosheets such as high hydrophilicity, chemical robustness, and ultrafast water permeation can be harnessed for a dual-action barrier coating layer that enhances resistance to both fouling and chlorine-induced degradation of polyamide (PA) thin-film composite (TFC) membranes while preserving their separation performance. GO multilayers were coated on the PA-TFC membrane surfaces via layer-by-layer (LbL) deposition of oppositely charged GO nanosheets. Consequently, it was shown that the conformal GO coating layer can increase the surface hydrophilicity and reduce the surface roughness, leading to the significantly improved antifouling performance against a protein foulant. It was also demonstrated that the chemically inert nature of GO nanosheets enables the GO coating layer to act as a chlorine barrier for the underlying PA membrane, resulting in a profound suppression of the membrane degradation in salt rejection upon chlorine exposure.

Molecular layer-by-layer assembled thin-film composite membranes for water desalination.

Molecular layer-by-layer (mLbL) assembled thin-film composite membranes fabricated by alternating deposition of reactive monomers on porous supports exhibit both improved salt rejection and enhanced water flux compared to traditional reverse osmosis membranes prepared by interfacial polymerization. Additionally, the well-controlled structures achieved by mLbL deposition further lead to improved antifouling performance.