Comparison of Effectiveness of Intraarticular Hyaluronate and Corticosteroid injections in Adhesive Capsulitis: A Systematic Review and Meta-analysis.

BACKGROUND: Adhesive capsulitis of the shoulder causes inflammation and adhesions in the shoulder joint capsule, leading to pain and limited range of motion (ROM). Intraarticular corticosteroid (CS) and hyaluronic acid (HA) injections are common therapeutic options for adhesive capsulitis, but their comparative effectiveness remains unclear. OBJECTIVES: To provide a robust comparison of the outcomes of HA and CS, we conducted a meta-analysis of relevant previous studies that examined the therapeutic effects of intraarticular HA and CS injections in patients with adhesive capsulitis. STUDY DESIGN: Systematic review and meta-analysis. METHODS: This meta-analysis of randomized controlled trials compared the effectiveness of intraarticular HA and CS injections. Of the 10,205 articles, 7 met our predetermined criteria and were included in the analysis. RESULTS: Patients who received CS injections demonstrated superior pain reduction and functional improvement at 2-4 weeks after injection to those who received HA injections. Nevertheless, comparable outcomes were observed between the 2 groups at 6 and 12 weeks. The active or passive range of motion of the shoulder joint was not significantly different between patients who received HA injections and those who received CS injections. LIMITATIONS: The meta-analysis included only a small number of studies, and the number of HA injections examined in those studies varied from one to 3 at a time, whereas an CS injection was performed only once in most of the included studies. CONCLUSIONS: The administration of intraarticular HA injection emerges as a commendable therapeutic option for patients with adhesive capsulitis, particularly for those requiring repetitive injections or at risk of developing side effects from injections of CS. Although intraarticular CS injections offer accelerated short-term (2-4 weeks) pain relief and functional improvement, comparable effects were observed within 6 and 12 weeks after intraarticular HA and CS injections.

Deep-learning model accurately classifies multi-label lung ultrasound findings, enhancing diagnostic accuracy and inter-reader agreement.

Despite the increasing use of lung ultrasound (LUS) in the evaluation of respiratory disease, operators' competence constrains its effectiveness. We developed a deep-learning (DL) model for multi-label classification using LUS and validated its performance and efficacy on inter-reader variability. We retrospectively collected LUS and labeled as normal, B-line, consolidation, and effusion from patients undergoing thoracentesis at a tertiary institution between January 2018 and January 2022. The development and internal testing involved 7580 images from January 2018 and December 2020, and the model's performance was validated on a temporally separated test set (n = 985 images collected after January 2021) and two external test sets (n = 319 and 54 images). Two radiologists interpreted LUS with and without DL assistance and compared diagnostic performance and agreement. The model demonstrated robust performance with AUCs: 0.93 (95% CI 0.92-0.94) for normal, 0.87 (95% CI 0.84-0.89) for B-line, 0.82 (95% CI 0.78-0.86) for consolidation, and 0.94 (95% CI 0.93-0.95) for effusion. The model improved reader accuracy for binary discrimination (normal vs. abnormal; reader 1: 87.5-95.6%, p = 0.004; reader 2: 95.0-97.5%, p = 0.19), and agreement (k = 0.73-0.83, p = 0.01). In conclusion, the DL-based model may assist interpretation, improving accuracy and overcoming operator competence limitations in LUS.

Effect of Dialysis on Structural Brain Connectivity in Patients with End-Stage Renal Disease.

INTRODUCTION: Patients with end-stage renal disease (ESRD) are known to have reduced structural and functional brain connectivity in the brain regions associated with cognitive function. However, the effect of dialysis on brain connectivity remains unclear. This study aimed to evaluate the effects of dialysis on structural brain connectivity in patients with ESRD. METHODS: This prospective study included 20 patients with ESRD in the pre-dialysis stage and 35 healthy controls. The patients underwent T2-weighted and three-dimensional T1-weighted magnetic resonance imaging before and 3 months after dialysis initiation. Moreover, the cortical thickness was calculated. We applied graph theoretical analysis to calculate the structural covariance network based on cortical thickness. We compared the cortical thickness and structural covariance network of patients with ESRD in the pre-dialysis stage with those of healthy controls and with those of patients with ESRD in the post-dialysis stage. RESULTS: The mean cortical thickness in both hemispheres was lower in patients with ESRD in the pre-dialysis stage than in healthy controls (2.296 vs. 2.354, p = 0.030; 2.282 vs. 2.362, p = 0.004, respectively) and was higher in patients with ESRD in the post-dialysis stage than in those in the pre-dialysis stage (2.333 vs. 2.296, p = 0.001; 2.322 vs. 2.282, p = 0.002, respectively). Analysis of the structural covariance network revealed that the assortative coefficient was lower in patients with ESRD in the pre-dialysis stage than in healthy controls (-0.062 vs. -0.031, p = 0.029) and was higher in patients with ESRD in the post-dialysis stage than in those in the pre-dialysis stage (-0.002 vs. -0.062, p = 0.042). CONCLUSION: We observed differences in the cortical thickness and structural covariance networks before and after dialysis in patients with ESRD. This indicates that dialysis affects structural brain connectivity, contributing to the understanding of the pathophysiological mechanism of cognitive function alterations resulting from dialysis in patients with ESRD.

Critical assessment of recent advancements in chitosan-functionalized iron and geopolymer-based adsorbents for the selective removal of arsenic from water.

Inorganic arsenic (As), a known carcinogen and major contaminant in drinking water, affects over 140 million people globally, with levels exceeding the World Health Organization's (WHO) guidelines of 10 µg L-1. Developing innovative technologies for effluent handling and decontaminating polluted water is critical. This paper summarizes the fundamental characteristics of chitosan-embedded composites for As adsorption from water. The primary challenge in selectively removing As ions is the presence of phosphate, which is chemically similar to As(V). This study evaluates and summarizes innovative As adsorbents based on chitosan and its composite modifications, focusing on factors influencing their adsorption affinity. The kinetics, isotherms, column models, and thermodynamic aspects of the sorption processes were also explored. Finally, the adsorption process and implications of functionalized chitosan for wastewater treatment were analyzed. There have been minimal developments in water disinfection using metal-biopolymer composites for environmental purposes. This field of study offers numerous research opportunities to expand the use of biopolymer composites as detoxifying materials and to gain deeper insights into the foundations of biopolymer composite adsorbents, which merit further investigation to enhance adsorbent stability.

Chitinase 3-like-1 Inhibits Innate Antitumor and Tissue Remodeling Immune Responses by Regulating CD47-SIRPα- and CD24-Siglec10-Mediated Phagocytosis.

Innate immune responses such as phagocytosis are critically linked to the generation of adaptive immune responses against the neoantigens in cancer and the efferocytosis that is essential for homeostasis in diseases characterized by lung injury, inflammation, and remodeling as in chronic obstructive pulmonary disease (COPD). Chitinase 3-like-1 (CHI3L1) is induced in many cancers where it inhibits adaptive immune responses by stimulating immune checkpoint molecules (ICPs) and portends a poor prognosis. CHI3L1 is also induced in COPD where it regulates epithelial cell death. In this study, we demonstrate that pulmonary melanoma metastasis inhibits macrophage phagocytosis by stimulating the CD47-SIRPα and CD24-Siglec10 phagocytosis checkpoint pathways while inhibiting macrophage "eat me" signals from calreticulin and HMGB1. We also demonstrate that these effects on macrophage phagocytosis are associated with CHI3L1 stimulation of the SHP-1 and SHP-2 phosphatases and inhibition of the accumulation and phosphorylation of cytoskeleton-regulating nonmuscle myosin IIa. This inhibition of innate immune responses such as phagocytosis provides a mechanistic explanation for the ability of CHI3L1 to stimulate ICPs and inhibit adaptive immune responses in cancer and diseases such as COPD. The ability of CHI3L1 to simultaneously inhibit innate immune responses, stimulate ICPs, inhibit T cell costimulation, and regulate a number of other oncogenic and inflammation pathways suggests that CHI3L1-targeted therapeutics are promising interventions in cancer, COPD, and other disorders.

Damage-Free Plasma Source for Atomic-Scale Processing.

As atomic-scale etching and deposition processes become necessary for manufacturing logic and memory devices at the sub-5 nm node, the limitations of conventional plasma technology are becoming evident. For atomic-scale processes, precise critical dimension control at the sub-1 nm scale without plasma-induced damage and high selectivity between layers are required. In this paper, a plasma with very low electron temperature is applied for damage-free processing on the atomic scale. In plasmas with an ultralow electron temperature (ULET, Te < 0.5 eV), ion energies are very low, and the ion energy distribution is narrow. The absence of physical damage in ULET plasma is verified by exposing 2D structural material. In the ULET plasma, charging damage and radiation damage are also expected to be suppressed due to the extremely low Te. This ULET plasma source overcomes the limitations of conventional plasma sources and provides insights to achieve damage-free atomic-scale processes.

Application of noncontact sensors for cardiopulmonary physiology and body weight monitoring at home: A narrative review.

Monitoring health status at home has garnered increasing interest. Therefore, this study investigated the potential feasibility of using noncontact sensors in actual home settings. We searched PubMed for relevant studies published until February 19, 2024, using the keywords "home-based," "home," "monitoring," "sensor," and "noncontact." The studies included in this review involved the installation of noncontact sensors in actual home settings and the evaluation of their performance for health status monitoring. Among the 3 included studies, 2 monitored respiratory status during sleep and 1 monitored body weight and cardiopulmonary physiology. Measurements such as heart rate, respiratory rate, and body weight obtained with noncontact sensors were compared with the results obtained from polysomnography, polygraphy, and commercial scales. All included studies demonstrated that noncontact sensors produced results comparable to those of standard measurement tools, confirming their excellent capability for biometric measurements. Overall, noncontact sensors have sufficient potential for monitoring health status at home.

Apple polyphenols prevent patulin-induced intestinal damage by modulating the gut microbiota and metabolism of the gut-liver axis.

Patulin (PAT), a foodborne toxin, causes severe intestinal damage. To mitigate this health threat, mice were pretreated with apple polyphenols (AP) in their drinking water (0.01 % and 0.05 %) for eight weeks, followed by exposure to PAT during the last two weeks. Subsequently, histopathological and biochemical evaluations of intestinal tissues were conducted, alongside assessments of alterations in gut microbiota, colonic content metabolome, and hepatic metabolome. Consequently, AP alleviated PAT-induced villus and crypt injury, mucus depletion, GSH level decline, GSH-Px and SOD activity reduction, and MPO activity elevation. Notably, AP counteracted PAT-mediated microbiota disruptions and promoted the abundance of beneficial bacteria (Dubosiella, Akkermansia, Lachnospiraceae, and Lactobacillus). Furthermore, AP counteracted PAT-induced metabolic disorders in the colonic contents and liver. Ultimately, AP prevented intestinal injury by regulating the gut microbiota and amino acid, purine, butanoate, and glycerophospholipid metabolism in the gut-liver axis. These results underscore the potential of AP to prevent foodborne toxin-induced intestinal damage.

Identification of novel drug targets for osteoarthritis by integrating genetics and proteomes from blood.

BACKGROUND: Osteoarthritis (OA) is a degenerative osteoarticular disease, involving genetic predisposition. How the risk variants confer the risk of OA through their effects on proteins remains largely unknown. Therefore, we aimed to discover new and effective drug targets for OA and its subtypes. METHODS: A proteome-wide association study (PWAS) was performed based on OA and its subtypes genome-wide association studies (GWAS) summary datasets and the protein quantitative trait loci (pQTL) data. Subsequently, Mendelian randomization (MR) and colocalization analysis was conducted to estimate the associations between protein and OA risk. The replication analysis was performed in an independent dataset of human plasma pQTL data. RESULTS: The abundance of seven proteins was causally related to OA, two proteins to knee OA and six proteins to hip OA, respectively. We replicated 2 of these proteins using an independent pQTL dataset. With the further support of colocalization, and higher ECM1 level was causally associated with a higher risk of OA and hip OA. Higher PCSK1 level was causally associated with a lower risk of OA. And higher levels of ITIH1, EFEMP1, and ERLEC1 were associated with decreased risk of hip OA. CONCLUSION: Our study provides new insights into the genetic component of protein abundance in OA and a promising therapeutic target for future drug development.