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This study was based on a 30 m inside-foot long-pass scenario and aimed to preliminarily evaluate the agreement between MediaPipe Pose, DWPose, YOLO-Pose, and Xsens, as well as their practical utility under real-field conditions. Twelve elite male football players performed 15 consecutive long-passes, with data collected simultaneously using Xsens and two smartphones positioned at 15° and 35° to the right front of the participants. The Intraclass Correlation Coefficient (ICC (2,1)) and Bland-Altman analysis were used to evaluate discrete kinematic measures. Continuous kinematic agreement was assessed using Root Mean Square Error (RMSE) and the Coefficient of Multiple Determination (CMD), while Statistical Parametric Mapping (SPM) and Statistical non-Parametric Mapping (SnPM) compared differences across the entire analysis interval. Across the three models, CMD ranged from 0.13 ± 0.17 to 0.67 ± 0.25, and RMSE ranged from 9.88 ± 8.20° to 39.92 ± 10.44°. The SPM and SnPM results showed that significant differences were mainly concentrated in the bilateral hip, knee, and ankle joints. The three models cannot yet be used for field-based high-precision kinematic data measurement; however, MediaPipe Pose and DWPose may be selectively used for rapid screening of movement patterns and analysis of movement trends in football-specific technical movements.

The brittleness of 18-karat purple gold originates from the AuAl2 intermetallic compound. This study investigates the microstructural modification of the AuAl2 intermetallic compound by adding silicon (Si) and cobalt (Co) and by rapid solidification in copper molds. The samples with alloy additions from a traditional investment casting were compared with copper mold casting for grain boundary characteristics using SEM, EBSD, and TEM. SEM micrographs showed a reduction in grain size of copper mold casting from approximately within 150–200 μm to within 12–20 μm. EBSD showed a narrow grain size distribution in the Si–Co-modified alloy than in the Si-modified alloy, using the copper mold casting technique. TEM observations show that grain boundaries were closely packed, with ~80 nm-sized voids. XRD confirmed that all alloys retained the AuAl2 intermetallic phase, with peak broadening in the modified and fast-cooling samples indicating crystallographic refinement. These results confirm that Si-Co additions with a fast cooling rate effectively refine the microstructure of the AuAl2 intermetallic compound, making the alloy less brittle while preserving the purple gold color.

Sepsis-induced acute lung injury (SI-ALI) is a major cause of morbidity and mortality among septic patients. Recent evidence highlights the role of mitochondria-associated membranes (MAMs)-specialized contact sites between the endoplasmic reticulum (ER) and mitochondria-in regulating calcium signaling, lipid metabolism, energy homeostasis, and immune responses. Structural and functional alterations of MAMs are increasingly recognized as critical contributors to the pathogenesis of SI-ALI. This review aims to summarize the structural and functional characteristics of MAMs, elucidate their alterations and immunoregulatory roles in sepsis-induced lung injury, and discuss potential therapeutic strategies targeting MAMs to mitigate pulmonary damage. A comprehensive literature review was conducted using recent studies focused on the molecular structure, signaling mechanisms, and pathological changes of MAMs in sepsis and related inflammatory diseases. Emphasis was placed on calcium signaling, mitochondrial dysfunction, oxidative stress, and inflammasome activation. MAMs maintain close ER-mitochondria contacts (10-30 nm) through key proteins such as inositol 1,4,5-trisphosphate receptor (IP3R), glucose-regulated protein 75 (GRP75), voltage-dependent anion channel (VDAC), and mitofusin-2 (MFN2). During sepsis, oxidative stress and inflammatory cytokines disrupt these contacts, leading to impaired calcium transfer, mitochondrial dysfunction, and energy deficiency. Dysregulated MAMs promote NLR family pyrin domain containing 3 (NLRP3) inflammasome activation, excessive reactive oxygen species (ROS) production, and mitochondrial DNA (mtDNA) release, thereby amplifying inflammatory cascades and immune cell apoptosis. Therapeutic strategies that restore MAM integrity-such as upregulating MFN2, activating ER autophagy, or modulating calcium transport proteins-have shown potential to attenuate lung injury by improving mitochondrial metabolism and reducing oxidative stress. MAMs play essential roles in maintaining intracellular homeostasis and immune balance. Their structural and functional disruption contributes significantly to the progression of SI-ALI. Targeting MAMs offers promising therapeutic opportunities for preventing and treating sepsis-induced lung injury, although further mechanistic and clinical studies are warranted to translate these findings into practice.

Parents of children with congenital heart disease (CHD) serve as primary caregivers and play a central role in decisions regarding their children's health care, development, and overall well-being. Their health information behavior directly influences the care decisions and outcomes of their children. In China, the online health information environment is vast but varies in quality, which places a significant information-seeking burden on them in the digital age. Moreover, Chinese cultural backgrounds shape parents' views, perspectives, and practices related to health information. To date, there have been no studies in China reporting on the experiences of parents of children with CHD concerning their health information behavior. The aim of this study was to explore the experiences of health information behavior among parents of children with CHD during the disease journey through the lens of Chinese culture. This study used a descriptive phenomenological qualitative method. Face-to-face, semistructured, and in-depth interviews were conducted with parents of children with CHD from March to July 2025 at a tertiary grade A hospital located in Kunming, Yunnan Province, China. Data were collected and managed using the NVivo 12.0 software (QSR International), and thematic analysis was applied to identify and interpret participants' experiences and perspectives. A total of 24 parents of children with CHD participated in this study, including 6 fathers and 18 mothers. In total, 6 themes emerged from the data: (1) Looking for health information both online and offline; (2) Seeking health information from professionals and peers as well; (3) Evolving health information needs in the disease journey; (4) Showing diverse attitudes toward health information seeking; (5) Positive and negative feelings during health information behavior process; and (6) Disclosure versus concealment of children's disease information. Parents of children with CHD seek health information from both online and offline sources and also combine health information from professionals and peers. Medical institutions should provide authoritative information resources, while regulatory authorities should conduct professional reviews before disseminating health information online to foster a reliable information environment. Additional efforts should focus on utilizing rehabilitation narratives from peer networks, delivering personalized information support tailored to parents' information-seeking styles and children's disease stages, and offering training and services to stimulate and cultivate a conscious decision-making process regarding disease disclosure and sharing.

Background Parents of children with congenital heart disease (CHD) face chronic stress impairing family functioning and well-being. As a key protective factor, family resilience aids their adaptation. However, existing research predominantly measures general family resilience, neglecting heterogeneous resilience patterns and subgroup profiles. Our study uses person-centered Latent Profile Analysis (LPA) to identify latent family resilience classes in Chinese culture to provide tailored support. Methods This study adopted a cross-sectional survey design. From October 2024 to July 2025, convenience sampling was used to recruit 426 eligible parents of children with CHD from two tertiary hospitals in Yunnan Province, China. Data were collected using the General Information Questionnaire, Family Hardiness Index (FHI), Simplified Coping Style Questionnaire (SCSQ), and Social Support Rating Scale (SSRS). LPA was applied to classify the family resilience levels of these parents. Subsequently, univariate and multivariate ordinal logistic regression analyses were conducted to explore the factors associated with different latent classes of family resilience. Results A total of 400 valid questionnaires were collected, with an effective response rate of 93.9%. The mean total score for family resilience in parents of children with CHD was 58.13 ± 5.79, suggesting a moderate overall level of family resilience in this group. The family resilience of parents of children with CHD was classified into three latent profiles: “High family resilience responsibility-anchored type” ( N  = 51), “Low family resilience challenge-vulnerable type” ( N  = 25), and “Moderate family resilience balanced-stable type” ( N  = 324). Univariate analysis identified significant differences (all P  < 0.05) in the following factors: the number of the child’s cardiac diagnoses, place of residence, parental education, coping styles, family monthly income, and social support. Logistic regression revealed that coping styles, family monthly income, and social support were predictors of family resilience latent classes in CHD children’s parents. Conclusions Parents of children with CHD demonstrate heterogeneity in family resilience. Healthcare professionals should pay attention to the family resilience differences among parents of children with CHD and implement targeted intervention measures based on the characteristics of different subgroups, thereby enhancing parents’ family resilience and further promoting family well-being.

The timely identification of suicidal ideation on social media is pivotal for global suicide prevention efforts. Addressing the challenges posed by the unstructured nature of social media data, we present a novel Chinese-based dual-channel model, DSI-BTCNN, which leverages deep learning to discern patterns indicative of suicidal ideation. Our model is designed to process Chinese data and capture the nuances of text locality, context, and logical structure through a fine-grained text enhancement approach. It features a complex parallel architecture with multiple convolution kernels, operating on two distinct task channels to mine relevant features. We propose an information gain-based IDFN fusion mechanism. This approach efficiently allocates computational resources to the key features associated with suicide by assessing the change in entropy before and after feature partitioning. Evaluations on a customized dataset reveal that our method achieves an accuracy of 89.64%, a precision of 92.84%, an F1-score of 89.24%, and an AUC of 96.50%, surpassing TextCNN and BiLSTM models by an average of 4.66%, 12.85%, 3.08%, and 1.66%, respectively. Notably, our proposed model has an entropy value of 81.75, which represents a 17.53% increase compared to the original DSI-BTCNN model, indicating a more robust detection capability. This enhanced detection capability is vital for real-time social media monitoring, offering a promising tool for early intervention and potentially life-saving support.

Background Intensive care unit (ICU)-acquired weakness (ICUAW) is a prevalent complication in critically ill patients, marked by symmetrical respiratory and limb muscle weakness, which adversely affects long-term outcomes. Early identification of high-risk patients and prevention are essential to mitigate its impact. Traditional risk prediction models, based on cohort data, have limitations in addressing the complex, non-linear relationships among diverse risk factors due to patient heterogeneity and the dynamic nature of critical illness. Machine learning offers a promising alternative by integrating heterogeneous data—clinical, laboratory, and physiological—to enhance predictive accuracy and individualization. Additionally, machine learning can identify novel risk factors and mechanisms overlooked by conventional methods, supporting early intervention and targeted prevention strategies to improve patient prognosis. Therefore, this study aims to develop and validate risk prediction models for ICUAW based on multiple machine learning algorithms. Methods Four machine learning algorithms were employed. Bedside ultrasound machines were used to assess ICUAW in patients admitted to the ICU twice, once within 24 hours of ICU admission and once on the 7th day of ICU admission. Eighteen features screened through a previous umbrella review informed the models. The performance of the models was evaluated based on multiple assessment metrics, such as the area under the receiver operating characteristic curve (AUC). Results A total of 749 patients were enrolled in the study, and 382 patients (51%) developed ICUAW. Specifically, 524 patients were assigned to the training set, and 225 patients were assigned to the internal validation set. Among the four machine-learning models, AUC ranged from 0.830 to 0.978. The eXtreme Gradient Boosting exhibited the best performance, achieving an AUC of 0.978 (95%CI 0.962–0.994), with 0.924 accuracy, 0.911 sensitivity, 0.941 specificity, 0.924 F1 score, and a Brier score of 0.084. The results of the Decision Curve Analysis also corroborate these results. Conclusions A machine learning prediction model can be developed, leveraging its robust learning capabilities to identify patients at high risk of developing ICUAW. This approach facilitates standardized management of ICUAW, thereby potentially reducing its incidence.

HTLV‐1‐associated myelopathy/tropical spastic paraparesis (HAM/TSP) is a progressive neurological disorder with limited treatment options. We report a 54‐year‐old female with decade‐long, progressive HAM/TSP, previously refractory to rituximab, who experienced worsening spastic paraparesis and neurogenic bladder dysfunction. She showed remarkable improvement in spasticity, bladder function, and quality of life following combination therapy with efgartigimod and corticosteroids. This case highlights efgartigimod's potential as an adjunctive therapy for refractory HAM/TSP, suggesting a new immune modulation strategy and warranting further research into combination treatments.

With the rapid economic development and the continuous growth in the demand for new energy vehicles and energy storage systems, a significant number of waste lithium-ion batteries are expected to enter the market in the future. Effectively managing the processing and recycling of these batteries to minimize environmental pollution is a major challenge currently facing the lithium-ion battery industry. This paper analyzes and compares the recycling strategies for different components of lithium-ion batteries, providing a summary of the main types of batteries, existing technologies at various pre-treatment stages, and recycling techniques for valuable resources such as heavy metals and graphite. Currently, pyrometallurgy and hydrometallurgy processes have matured; however, their high energy consumption and pollution levels conflict with the principles of the current green economy. As a result, innovative technologies have emerged, aiming to reduce energy consumption while achieving high recovery rates and minimizing the environmental impact. Nevertheless, most of these technologies are currently limited to the laboratory scale and are not yet suitable for large-scale application.