ObjectiveTo investigate the effectiveness of teaching pedagogy based on outcome-based education (OBE) and conceive-design-implement-operate (CDIO) model in the teaching of exercise rehabilitation training. MethodsTwenty-seven postgraduate students majoring in exercise rehabilitation training of grade 2024 at Capital University of Physical Education and Sports were randomly divided into control group (n = 13) and experimental group (n = 14). The control group received routine teaching methods, while the experimental group received teaching of OBE-CDIO. After the course, theoretical scores, objective structured clinical examination (OSCE) scores and teaching satisfaction via questionnaire were compared between two groups. ResultsAfter the course, there was no significant difference in theoretical scores between two groups (t = 1.103, P > 0.05). Scores in all stations of OSCE were higher in the experimental group than in the control group (t > 2.181, P < 0.05), as well as the satisfaction scores of learning, enthusiasm, organization, group interaction, individual affinity, workload and examination (|t| > 3.781, P < 0.001). ConclusionThe teaching pedagogy based on the OBE-CDIO model can improve practical competence and teaching satisfaction among postgraduate students majoring in exercise rehabilitation training.

ObjectiveTo investigate the effectiveness of teaching pedagogy based on outcome-based education (OBE) and conceive-design-implement-operate (CDIO) model in the teaching of exercise rehabilitation training. MethodsTwenty-seven postgraduate students majoring in exercise rehabilitation training of grade 2024 at Capital University of Physical Education and Sports were randomly divided into control group (n = 13) and experimental group (n = 14). The control group received routine teaching methods, while the experimental group received teaching of OBE-CDIO. After the course, theoretical scores, objective structured clinical examination (OSCE) scores and teaching satisfaction via questionnaire were compared between two groups. ResultsAfter the course, there was no significant difference in theoretical scores between two groups (t = 1.103, P > 0.05). Scores in all stations of OSCE were higher in the experimental group than in the control group (t > 2.181, P < 0.05), as well as the satisfaction scores of learning, enthusiasm, organization, group interaction, individual affinity, workload and examination (|t| > 3.781, P < 0.001). ConclusionThe teaching pedagogy based on the OBE-CDIO model can improve practical competence and teaching satisfaction among postgraduate students majoring in exercise rehabilitation training.

ObjectiveTo investigate the effectiveness of teaching pedagogy based on outcome-based education (OBE) and conceive-design-implement-operate (CDIO) model in the teaching of exercise rehabilitation training. MethodsTwenty-seven postgraduate students majoring in exercise rehabilitation training of grade 2024 at Capital University of Physical Education and Sports were randomly divided into control group (n = 13) and experimental group (n = 14). The control group received routine teaching methods, while the experimental group received teaching of OBE-CDIO. After the course, theoretical scores, objective structured clinical examination (OSCE) scores and teaching satisfaction via questionnaire were compared between two groups. ResultsAfter the course, there was no significant difference in theoretical scores between two groups (t = 1.103, P > 0.05). Scores in all stations of OSCE were higher in the experimental group than in the control group (t > 2.181, P < 0.05), as well as the satisfaction scores of learning, enthusiasm, organization, group interaction, individual affinity, workload and examination (|t| > 3.781, P < 0.001). ConclusionThe teaching pedagogy based on the OBE-CDIO model can improve practical competence and teaching satisfaction among postgraduate students majoring in exercise rehabilitation training.

ObjectiveTo explore the effect of presentation-assimilation-discussion (PAD) classroom model-based classroom-community collaborative teaching on course of sports rehabilitation therapy under the background of sports-medicine integration. MethodsFrom Febrary, 2024 to June, 2025, a total of 46 undergraduate students majoring in sports rehabilitation (Grade 2022, Capital University of Physical Education and Sports) were randomly divided into control group (n = 23) and experimental group (n = 23). The control group received routine lectures combined with laboratory practice, while the experimental group was taught using a classroom-community collaborative teaching based on PAD classroom structure. The two groups were compared in terms of excellent rate in practical assessment, achievement in higher-order dimensions of Bloom's Taxonomy, real-case rehabilitation scenario transformation ability and teaching satisfaction at the end of the semester. ResultsAt the end of the semester, the excellent rate in practical assessment was 60.87% in the experimental group, higher than 21.74% in the control group (χ² = 7.725, P < 0.05), while the scores in the analyse, evaluation and creation dimensions of Bloom's Taxonomy were significantly higher (t > 8.490, P < 0.001), real-case rehabilitation scenario transformation ability was better (t > 3.873, P < 0.001) and teaching satisfaction was higher (χ² = 8.576, P = 0.003). ConclusionPAD-based classroom-community collaborative teaching can effectively improve practical skills, higher-order cognitive abilities and practical application abilities among students majoring in sports rehabilitation.

Optical microscopy is essential for exploring biological and material structures, with resolution determining the level of observable detail. The advent of super-resolution fluorescence microscopy has broken the diffraction limit, achieving nanoscale resolution. However, traditional assessment methods, such as the Rayleigh criterion and point spread function (PSF) width measurement, rely on empirical judgments and diffraction-limited models, rendering them inadequate for modern super-resolution imaging. This review systematically traces the evolution of resolution assessment methodologies, from classical criteria to advanced strategies tailored for various super-resolution modalities. We first discuss Fourier-based quantitative methods. Fourier ring correlation (FRC) and its 3D counterpart, Fourier shell correlation (FSC), objectively determine resolution by evaluating the statistical correlation of two independent image reconstructions in frequency space. These methods offer robustness against noise and provide a global resolution metric, but they require data independence and are computationally intensive. They have become the prevailing standards in electron and super-resolution microscopy. Subsequently, we examine adaptations for specific super-resolution techniques. For single-molecule localization microscopy (SMLM) techniques such as PALM and STORM, the Fourier image resolution (FIRE) method extends FRC by incorporating a physical model that accounts for localization precision and labeling density. For stimulated emission depletion (STED) microscopy and other nonlinear techniques, assessment strategies differ. While PSF shrinkage measurements using fluorescent beads are useful for system calibration, evaluating the effective resolution directly on biological samples is more practical. This is typically performed via linewidth analysis of known structures (e.g., microtubules) or edge-spread function measurements, capturing the effects of photobleaching and sample-induced aberrations. A major paradigm shift is parameter-free resolution estimation based on decorrelation analysis. This method analyzes the autocorrelation decay of a single image’s Fourier spectrum to identify the cutoff spatial frequency without requiring dual datasets or user-defined thresholds. Its high efficiency and broad applicability have been validated across widefield, confocal, STED, SIM, and SMLM modalities. Optimized rendering strategies for SMLM data further enhance its accuracy, and it is emerging as a tool for real-time optimization of experimental parameters. The review also addresses the “gold standard” of resolution validation using well-defined nanostructures, such as DNA origami and nuclear pore complexes, which provide ground truth for verifying resolution claims and detecting artifacts. In the era of artificial intelligence, deep learning plays a dual role: it powerfully enhances image resolution but also introduces challenges, as models may generate “hallucinations” or false details. This underscores the need for new validation metrics to verify the physical fidelity of AI-generated content. Finally, we outline future directions: developing unified cross-modality standards, enabling real-time dynamic resolution monitoring for live-cell imaging, creating techniques for generating local resolution maps to capture sample heterogeneity, and integrating intelligent error correction to ensure data veracity. By providing a comprehensive overview of resolution assessment progress and challenges, this review aims to equip researchers with the knowledge to select appropriate tools, thereby fostering rigorous quantitative imaging in the life and material sciences.

ObjectiveType I interferon (IFN-I) signaling is essential for antiviral innate immunity, yet its sustained or excessive activation contributes to the pathogenesis of several autoimmune diseases and interferonopathies, such as systemic lupus erythematosus and Aicardi-Goutières syndrome. Current strategies targeting this pathway, exemplified by JAK inhibitors, act mainly on downstream signal transduction and provide limited direct control over upstream IFN-I production, while also carrying the risk of broad immunosuppression. Phyllanthus emblica L. has long been used in traditional medicine for inflammatory disorders, but the bioactive constituent responsible for its regulation of IFN-I signaling and the underlying molecular mechanism have not been clearly defined. This study aimed to identify the active anti-inflammatory component of P. emblica and to characterize its mechanism of action on the IFN-I pathway in macrophages. MethodsActive components ofP. emblica and their candidate targets were screened by network pharmacology using the TCMSP and DrugBank databases (oral bioavailability≥30%, drug-likeness≥0.18) and intersected with inflammation-related genes retrieved from public databases. The predicted interaction between EGCG and IFN-I pathway proteins (TBK1, IRF3, STAT1) was evaluated by molecular docking, with BX795 and GSK8612 used as reference TBK1 inhibitors. Mechanistic experiments were performed in THP-1-derived macrophages and primary bone marrow-derived macrophages (BMDM). Upstream signaling was activated by transfection of the nucleic acid analogs poly(I∶C) and poly(dA∶dT) or by lipopolysaccharide (LPS) stimulation, whereas downstream signaling was activated by exogenous IFN-β. An siRNA-mediated TREX1 knockdown model was used to mimic endogenous nucleic acid-driven interferonopathy. Expression of IFN-β1 and interferon-stimulated genes (ISGs) was measured by RT-qPCR, protein phosphorylation by Western blot, and IFN-β secretion by ELISA. Cellular thermal shift assay (CETSA) and drug affinity responsive target stability (DARTS) were used to probe the interactionbetween EGCG and IRF3. ResultsNetwork pharmacology identified (-)-epigallocatechin-3-gallate (EGCG) as a candidate IFN-I-suppressive constituent of P. emblica, with predicted binding to TBK1, IRF3, and STAT1. Molecular docking yielded binding energies of -9.2, -7.2, and -8.2 kcal/mol for TBK1, IRF3, and STAT1, respectively, indicating an affinity for TBK1 comparable to that of the reference inhibitors BX795 (-5.7 kcal/mol) and GSK8612 (-6.4 kcal/mol). EGCG suppressed IFN-β1 and ISG mRNA expression under poly (I∶C), poly (dA∶dT), and LPS stimulation in both THP-1 macrophages and BMDM. At the protein level, EGCG reduced the phosphorylation of TBK1 and IRF3 without affecting the levels of the upstream sensors cGAS and RIG-I, and lowered IFN-β secretion in a concentration-dependent manner. CETSA and DARTS showed that EGCG did not enhance the thermal stability or protease resistance of IRF3, indicating that its effect on IRF3 is indirect. Following IFN-β stimulation, prolonged EGCG treatment reduced STAT1 phosphorylation in a time-dependent manner without an apparent change in IRF9, and partially attenuated ISG transcription; this effect was not monotonicly concentration-dependent, and CXCL10 showed the most consistent suppression. In TREX1-knockdown cells, the elevated mRNA levels of ISG15, ISG56, and CXCL10 were reduced by EGCG. ConclusionEGCG suppresses IFN-I responses by concurrently inhibiting TBK1-IRF3-dependent IFN‑β production and JAK-STAT1-mediated downstream transcription. These in vitro findings provide a mechanistic basis for the anti-inflammatory use of P. emblica in traditional medicine and identify EGCG as a candidate for further evaluation in interferon-driven autoimmune disease models.

ObjectiveTo analyze the distribution characteristics of competency structures in master's training programs in sports rehabilitation at Chinese universities based on the rehabilitation competency framework (RCF). MethodsUsing RCF as the theoretical analytical framework, master's training programs from Chinese universities offering sports rehabilitation programs or related training tracks were selected as study objects. A combination of text analysis and competency mapping was employed to conduct a systematic comparative analysis of training objectives, curriculum systems and training components. ResultsA total of 16 master's training programs in sports rehabilitation were included. Research-related competencies were well covered across the included programs, whereas competencies related to practice, and management and leadership were relatively insufficient. These competencies were often presented in fragmented or subsidiary forms and lacked systematic alignment with curriculum objectives and assessment mechanisms. In addition, insufficient coordination between curriculum systems and training components was observed. ConclusionThe current master's training programs in sports rehabilitation exhibit a certain degree of imbalance in their competency structure. This imbalance is mainly manifested in the insufficient and unsystematic integration of practice-related competencies as well as management and leadership competencies across training objectives, curriculum design, and assessment components. RCF enables a diagnostic analysis of the alignment between training elements and competency dimensions, allowing for the clear identification of structural gaps and biases within existing training systems. Consequently, it provides an explicit reference framework for practice-oriented curriculum reconstruction and the optimization of competency-based assessment mechanisms.

ObjectiveTo observe the clinical efficacy and safety of Modified Guomin Decoction （加味过敏煎， MGD） in patients with mild to moderate atopic dermatitis （AD） of the traditional Chinese medicine （TCM） pattern of heart fire and spleen deficiency， and to explore its possible mechanisms. MethodsIn this randomized， double-blind， placebo-controlled study， 72 patients with mild to moderate AD and the TCM pattern of heart fire and spleen deficiency were randomly divided into a treatment group and a control group， with 36 cases in each group. The treatment group received oral MGD granules combined with topical vitamin E emulsion， while the control group received oral placebo granules combined with topical vitamin E treatment. Both groups were treated twice daily for 4 weeks. Clinical efficacy， TCM syndrome scores， Visual Analogue Scale （VAS） for pruritus， Dermatology Life Quality Index （DLQI） scores， Scoring Atopic Dermatitis （SCORAD） and serum biomarkers， including interleukin-33 （IL-33）， interleukin-1β （IL-1β）， immunoglobulin E （IgE）， and tumor necrosis factor-α （TNF-α） were compared before and after treatment. Safety indexes was also assessed. ResultsThe total clinical effective rates were 77.78% （28/36） in the treatment group and 38.89% （14/36） in the control group， with cure rates of 19.44% （7/36） and 2.78% （1/36）， respectively. The treatment group showed significantly better clinical outcomes compared to the control group （P＜0.05）. The treatment group exhibited significant reductions in total TCM syndrome scores， including erythema， edema， papules， scaling， lichenification， pruritus， irritability， insomnia， abdominal distension， and fatigue scores， as well as reductions in VAS， DLQI， SCORAD， and serum IgE and IL-33 levels （P＜0.05 or P＜0.01）. Compared to the control group， the treatment group had significantly better improvements in all indicators except for insomnia （P＜0.05）. No adverse events occurred in either group. ConclusionMGD is effective and safe in treating mild to moderate AD patients with heart fire and spleen deficiency pattern. It significantly alleviates pruritus， improves TCM syndromes and quality of life， and enhances clinical efficacy， possibly through modulation of immune responses.

Membrane proteins are integral components of cellular membranes, accounting for approximately 30% of the mammalian proteome and serving as targets for 60% of FDA-approved drugs. They are critical to both physiological functions and disease mechanisms. Their functional protein-protein interactions form the basis for many physiological processes, such as signal transduction, material transport, and cell communication. Membrane protein interactions are characterized by membrane environment dependence, spatial asymmetry, weak interaction strength, high dynamics, and a variety of interaction sites. Therefore, in situ analysis is essential for revealing the structural basis and kinetics of these proteins. This paper introduces currently available in situ analytical techniques for studying membrane protein interactions and evaluates the characteristics of each. These techniques are divided into two categories: label-based techniques (e.g., co-immunoprecipitation, proximity ligation assay, bimolecular fluorescence complementation, resonance energy transfer, and proximity labeling) and label-free techniques (e.g., cryo-electron tomography, in situ cross-linking mass spectrometry, Raman spectroscopy, electron paramagnetic resonance, nuclear magnetic resonance, and structure prediction tools). Each technique is critically assessed in terms of its historical development, strengths, and limitations. Based on the authors’ relevant research, the paper further discusses the key issues and trends in the application of these techniques, providing valuable references for the field of membrane protein research. Label-based techniques rely on molecular tags or antibodies to detect proximity or interactions, offering high specificity and adaptability for dynamic studies. For instance, proximity ligation assay combines the specificity of antibodies with the sensitivity of PCR amplification, while proximity labeling enables spatial mapping of interactomes. Conversely, label-free techniques, such as cryo-electron tomography, provide near-native structural insights, and Raman spectroscopy directly probes molecular interactions without perturbing the membrane environment. Despite advancements, these methods face several universal challenges: (1) indirect detection, relying on proximity or tagged proxies rather than direct interaction measurement; (2) limited capacity for continuous dynamic monitoring in live cells; and (3) potential artificial influences introduced by labeling or sample preparation, which may alter native conformations. Emerging trends emphasize the multimodal integration of complementary techniques to overcome individual limitations. For example, combining in situ cross-linking mass spectrometry with proximity labeling enhances both spatial resolution and interaction coverage, enabling high-throughput subcellular interactome mapping. Similarly, coupling fluorescence resonance energy transfer with nuclear magnetic resonance and artificial intelligence (AI) simulations integrates dynamic structural data, atomic-level details, and predictive modeling for holistic insights. Advances in AI, exemplified by AlphaFold’s ability to predict interaction interfaces, further augment experimental data, accelerating structure-function analyses. Future developments in cryo-electron microscopy, super-resolution imaging, and machine learning are poised to refine spatiotemporal resolution and scalability. In conclusion, in situ analysis of membrane protein interactions remains indispensable for deciphering their roles in health and disease. While current technologies have significantly advanced our understanding, persistent gaps highlight the need for innovative, integrative approaches. By synergizing experimental and computational tools, researchers can achieve multiscale, real-time, and perturbation-free analyses, ultimately unraveling the dynamic complexity of membrane protein networks and driving therapeutic discovery.

The number of patients with reduced blood volume due to haemorrhage, fractures, severe infections, extensive burns and tumours is increasing, and traditional blood products are no longer able to meet the increasing clinical demand. Therefore, plasma substitutes have become particularly important in fluid resuscitation, especially artificial colloidal solutions, which have a sustained volume expansion time and a good volume expansion effect, and can significantly improve the circulatory status of patients. This article aims to review the classification of artificial colloidal plasma substitutes and their research progress in clinical practice, in order provide a more rigorous, professional and standardized reference for medicine.