The Proctor's reporting guideline for implementation strategies represents a landmark framework in the field of implementation science, aiming to address the issue of inconsistent reporting in implementation research by standardizing the naming, definition, and operationalization of implementation strategies, thereby enhancing the credibility and utility of research findings. This paper provides an in-depth interpretation of the core connotations of this reporting guideline and illustrates its application in developing interview outlines and specifying implementation strategies, using a brief smoking cessation intervention project as a case study. Through this reporting guideline, abstract recommendations for implementation are systematically transformed into clear, multidimensional operational guides, significantly improving the transparency of strategy connotations and the replicability of actual execution. Meanwhile, the case study highlights the flexibility of the guideline, which allows researchers to adapt the content and format of strategies based on local resources and cultural contexts, thus enhancing practical adaptability while maintaining scientific rigor. However, the application of Proctor's reporting guideline still faces challenges, primarily manifested in the potential confusion surrounding the constructs of temporality and dose in practice, as well as the challenges that the inherent flexibility of the guideline may pose to the assessment of fidelity and effectiveness. Despite these limitations, the reporting guideline remains a vital tool for implementation research; future efforts should focus on optimizing its application—through refining operational guidelines, standardizing flexible adaptations, and involving stakeholders—to better guide implementation studies and continuously promote high-quality development in the field.

The early angiopathy of systemic sclerosis (SSc) is a key hub connecting inflammation and fibrosis. The animal models that simulate the pathological characteristics of SSc are of great significance to study the etiology, pathogenesis and treatment of SSc with vascular involvement. This review of the characteristics of different animal models of SSc with vascular involvement provides a reference for relevant researchers to select appropriate models in the process of exploring the pathogenesis of SSc with vascular involvement.

Objective To analyze the clinical, imaging, pathological characteristics and prognosis of renal mucinous tubular and spindle cell carcinoma (MTSCC), so as to provide preference for the differential diagnosis and clinical management of this disease.Methods A retrospective analysis was conducted on the clinical and follow-up data of 14 patients diagnosed with renal MTSCC at the Eastern Theater Command General Hospital during June 2021 and Aug.2025.Relevant literature was reviewed.Results Of the 14 patients, 10 were female (71.4%) and 4 were male (28.6%), with a mean age of 56.9 years. Pathological staging included pT1a in 6 cases, pT1b in 7 cases, and pT2b in 1 case.The median tumor diameter was 4.5 (range 2.0-11.0) cm.Twelve cases (85.7%) were asymptomatic and detected incidentally.On ultrasonography, most tumors exhibited well-defined margins and regular morphology (9/10, 90%) and appeared as homogeneous hypoechoic masses (7/10, 70%).All lesions demonstrated hypovascular features on imaging studies.Ten patients (71.4%) underwent laparoscopic radical nephrectomy, and 4(28.6%) received partial nephrectomy.Histologically, a distinctive architecture composed of tubular structures, spindle-shaped cells, and mucinous stroma was exhibited.Immunohistochemically, the positive rates of PAX-8, VIMENTIN and CK7 in tumor cells were 100% (13/13), 91.7% (11/12) and 84.6% (11/13), respectively.The Ki-67 proliferation index ranged from 2.0% to 40.0%.During a median follow-up of 25.0 (range4.9-0.0) months, no local recurrence or distant metastasis was observed.Conclusion Renal MTSCC is a rare subtype of renal cell carcinoma, typically lacking specific clinical symptoms and characterized by hypovascular imaging features.The tumor generally follows an indolent course with a favorable prognosis.For localized tumors, partial nephrectomy should be the primary consideration.For cases with high-risk pathological features such as sarcomatoid changes, due attention should be paid to the potential invasiveness and follow-up should be closely conducted.

Electroencephalography (EEG) is a non-invasive neurophysiological monitoring technique. It records the electrical activity of the cerebral cortex using electrodes placed on the scalp surface. Owing to its high safety, portability, and millisecond-level temporal resolution, EEG has been widely utilized in a variety of fields, including clinical diagnosis, brain-computer interfaces (BCIs), and cognitive neuroscience research. However, due to its microvolt-level amplitude, EEG is highly susceptible to various artifacts, including electrooculographic (EOG), electrocardiographic (ECG), electromyographic (EMG), and power line interference (PLI). These artifacts can obscure genuine neural activity and introduce spurious electrophysiological features. Consequently, they may compromise EEG signal quality, thereby reducing the reliability of downstream analyses. To address this issue, numerous EEG artifact removal methods have been developed, including both traditional denoising techniques and deep learning-based approaches. Traditional EEG denoising methods have long served as the primary solutions for artifact removal. Representative approaches include filtering, regression, and blind source separation. Although these methods have demonstrated effectiveness in specific scenarios, they suffer from several inherent limitations. Filtering assumes that artifacts and EEG signals can be separated in the frequency domain, but many artifacts, such as EOG and EMG, overlap with EEG spectra, which may lead to the loss of valuable neural information. Regression methods require high-quality artifact references to estimate and subtract contaminations, limiting their effectiveness in reference-free scenarios. Blind source separation can remove artifacts without external references, but it typically requires the number of EEG channels to exceed the number of sources, restricting its application in single- or low-channel EEG recordings. Deep learning-based EEG denoising methods address these limitations effectively. First, they learn the nonlinear mapping between contaminated and clean EEG directly from data in an end-to-end manner. This approach does not rely on assumptions about spectral separability, thereby preserving neural activity more completely. Second, the reference information is incorporated during the training phase, allowing the trained model to perform artifact removal independently without external references. Third, deep learning models can be flexibly designed to accommodate various recording setups, achieving robust denoising for both high-density and single-channel EEG. Collectively, these advantages enable deep learning-based methods to overcome the main challenges of traditional approaches, providing more accurate and reliable EEG signal recovery. The superior denoising performance of deep learning-based EEG denoising methods has attracted increasing attention in EEG artifact removal research. As a result, many deep learning-based denoising methods have been developed and successfully applied in neural engineering areas. However, a systematic review of the techniques and applications in this field is still lacking. To address this gap, this paper reviews recent advances in deep learning-based EEG denoising from four perspectives: technical principle, benchmark dataset, denoising model, and evaluation method. Representative applications in neural signal analysis and BCI decoding are also summarized. Furthermore, the advantage, existing challenge, and future research direction of deep learning-based EEG denoising are discussed. This review aims to provide valuable theoretical insights and technical guidance for researchers. It is also expected to promote further advances and broader applications of deep learning-based EEG denoising techniques.

Implementation science aims to facilitate the efficient dissemination and sustainable application of evidence based interventions, and has accordingly generated a variety of theories, models, and frameworks. Among these, the Exploration, Preparation, Implementation, and Sustainment (EPIS) frameworkfunctions both as a process model and a determinant framework, emphasizing the staged and iterative nature of implementation, and systematically explaining the influence of multilevel factors on implementation processes and outcomes through four dimensions: outer context, inner context, bridging factors, and innovation factors. The EPIS framework has been widely applied in health and public service settings internationally, yet its use in China based research remains relatively limited. This article systematically introduces the core components and application methods of the EPIS framework, and illustrates its value in identifying key influencing factors, developing implementation strategies, and optimizing implementation outcomes through case examples from the health sector, aiming to provide a methodological reference for implementation research and the promotion of evidence based interventions in China.

Renal fibrosis is the common pathological endpoint of many forms of chronic kidney disease (CKD), yet the mechanisms determining effective repair versus persistent fibrotic remodeling remain incompletely understood. Peritubular capillaries (PTCs) are not merely passive targets of fibrotic injury, but form a dynamic vascular microenvironment linking regional perfusion, oxygen delivery, tubular metabolism, endothelial barrier integrity, pericyte support, immune-cell trafficking, and extracellular matrix (ECM) remodeling. We propose that PTC abnormalities should not be interpreted simply as reduced capillary density, but as a multidimensional disturbance of microvascular structure and function. Structural vascular preservation does not necessarily indicate effective microcirculation: anatomically detectable capillaries may still exhibit impaired perfusion, barrier dysfunction, abnormal endothelial-pericyte interactions, disturbed oxygen metabolism, or reduced network connectivity. Conversely, increased angiogenesis does not necessarily signify successful vascular repair if vessels remain immature, poorly perfused, or inadequately integrated into the existing network. To organize these abnormalities, we conceptualize PTC remodeling into four predominant but nonexclusive states: endothelial barrier disruption with inflammatory adhesion; endothelial-pericyte uncoupling with no-reflow; dysregulated angiogenesis with network simplification; and capillary rarefaction with fibrotic matrix locking. These states are not sequential stages of CKD. They may coexist within the same kidney, overlap within the same anatomical region, and vary with disease etiology, injury phase, vascular compartment, and treatment exposure. We further propose six dimensions for evaluating PTC status—structural presence, functional perfusion, barrier integrity, pericyte coupling, oxygen metabolism, and network connectivity—so that vascular quantity, function, and reparative capacity are assessed separately rather than inferred from a single endothelial marker or capillary-density measurement. Mechanistically, these states converge on a bidirectional microvascular-fibrotic feedback loop. Barrier disruption facilitates leukocyte recruitment and alters vascular paracrine signaling. Endothelial-pericyte uncoupling compromises capillary stability, whereas abnormal pericyte contraction may increase local vascular resistance and contribute to no-reflow before overt capillary loss. Dysregulated angiogenesis may generate vessels that fail to mature or connect to an effective perfusion network. Progressive capillary rarefaction compromises oxygen delivery, while sustained tubular transport demand and mitochondrial dysfunction may aggravate regional oxygen supply-demand mismatch. Injured tubules, immune cells, endothelial cells, pericytes, and fibroblasts communicate through soluble mediators, extracellular vesicles, direct cell contact, and cell-matrix signaling. Importantly, fibrosis is not merely a downstream consequence of microvascular injury. Altered ECM may increase diffusion distance, modify mechanotransduction, impair endothelial survival and migration, and restrict capillary reopening and regeneration. We use the term matrix locking to describe this sustained constraint on vascular repair, while emphasizing that current evidence does not establish irreversible disease in humans. This framework also has therapeutic implications. PTC-directed treatment should not be reduced to increasing vessel number or uniformly promoting angiogenesis. Instead, intervention should be matched to the dominant and potentially reversible abnormality: preserving endothelial barrier function; restoring endothelial-pericyte stability and reducing pathological microvascular resistance; normalizing angiogenesis so that vascular growth is accompanied by maturation, barrier competence, network integration, and effective perfusion; and, in advanced rarefaction, relieving matrix-related constraints while supporting vascular regeneration. The context- and time-dependent effects of signaling through VEGF, Tie2, PDGF-B/PDGFRβ, eNOS/NO, and related pathways indicate that the same molecular signal may exert different effects depending on disease context and timing. Therapeutic efficacy should therefore be evaluated by restoration of effective microcirculation and tissue function rather than by isolated molecular changes or capillary counts alone. Despite increasing mechanistic evidence, the translational basis for this framework remains limited. Most causal and interventional data derive from animal or cell models, whereas human evidence is largely limited to pathological observations, patient-sample associations, and prognostic studies. Currently available circulating and urinary candidate biomarkers generally lack sufficient specificity for PTC injury or state assignment, and no standardized quantitative thresholds have been externally validated. The four-state model should therefore be regarded as a hypothesis-generating analytical framework rather than a clinicopathological classification system. Future studies should integrate spatially resolved tissue phenotyping, blood and urine biomarkers, and dynamic microcirculatory assessment in longitudinal cohorts. They should test reproducibility, assess prognostic value beyond conventional pathology, estimated glomerular filtration rate, and proteinuria, and determine whether changes in PTC status precede or mediate therapeutic benefit. Linking reproducible microvascular phenotypes to defined mechanisms, treatment response, and long-term renal outcomes will be essential to determine whether state-directed assessment and restoration of the PTC microenvironment can ultimately inform patient stratification and therapeutic decision-making.

Consciousness, which underpins human perception, cognition, and behavioural responses, has long been a major focus of neuroscience and medicine. Alterations in consciousness occur not only during reversible processes such as sleep and anaesthesia, but also in pathological conditions, including disorders of consciousness (DOC) and brain injury. With recent advances in the synchronized acquisition and analysis of multimodal physiological signals, such as electroencephalography (EEG) and electrocardiography (ECG), the dynamic interactions between the heart and brain have become increasingly apparent. A growing body of evidence indicates that heart-brain interactions are closely associated with the maintenance and transition of consciousness states, offering a novel perspective for elucidating their underlying mechanisms and supporting relevant clinical assessments. Current approaches to heart-brain interaction analysis for consciousness-state assessment can be broadly grouped into three categories: ECG-based methods, EEG-based methods, and heart-brain coupling analysis. These approaches characterize heart-brain interactions during changes in consciousness from the complementary perspectives of autonomic regulation, cortical interoceptive processing, and cross-system information transfer, respectively. Nevertheless, this field remains at an early stage. Most studies have focused on a single experimental context or a fixed analytical method, with insufficient systematic consideration of the applicability and limitations of different approaches. Moreover, the mechanisms underlying the emergence and alteration of consciousness remain incompletely understood. Accordingly, this review examines heart-brain interaction methods employed in recent consciousness-state assessment studies in accordance with progressively deeper analytical perspectives, and systematically evaluates the advantages and limitations of these methods across distinct consciousness-related conditions. Heart rate variability (HRV) is one of the classical ECG-based indices used to investigate heart-brain interactions. It refers to fluctuations in consecutive interbeat intervals over a specified time period and is regarded as a physiological measure of autonomic nervous system regulation that may indirectly reflect the strength of heart-brain interactions. Depending on the analytical dimension, HRV analysis is commonly divided into time-domain, frequency-domain, and complexity-index analyses. These approaches characterize autonomic activity in terms of temporal fluctuations, the distribution of frequency components, and nonlinear dynamical properties, respectively. Although extensive research supports their physiological interpretation, they cannot characterize directional interactions from the heart to the brain. Among EEG-based methods for heart-brain interaction analysis, EEG activity directly related to cardiac fluctuations has received particular attention. One of the most widely used measures is the heartbeat-evoked potential (HEP). HEP-based approaches are considered to directly reflect the capacity of the cerebral cortex to process cardiac afferent signals and may be especially advantageous for characterizing rapidly changing consciousness levels, such as those observed during sleep. However, they do not comprehensively capture dynamic bidirectional information exchange between the brain and heart and are susceptible to cardiac artefacts, respiration, and variation in preprocessing procedures. Heart-brain coupling analysis quantifies functional associations between ECG and EEG through cross-system interaction measures, thereby assessing dynamic interactions between the heart and brain. It emphasizes information transfer, feedback regulation, and cross-timescale coordination between the two systems, offering a more comprehensive perspective for investigating changes in consciousness during sleep, anaesthesia, and DOC. However, the neurophysiological mechanisms and physiological interpretation of individual computational indices have not yet been fully established, and the robustness of their results and their potential for clinical generalization require further validation. Finally, this review summarizes the commonalities and differences among the three classes of methods across research domains involving different consciousness states. It further argues that heart-brain interaction research requires deeper investigation at both the mechanistic level of consciousness and the level of clinical application. Current challenges and key issues are identified, and future directions and feasible pathways for heart-brain interaction research are discussed, with the aim of providing new perspectives for researchers in related fields.

ObjectiveTo clarify the independent and synergistic effects of dyslipidemia in the progression of hepatic steatosis in metabolic dysfunction-associated fatty liver disease （MAFLD）. MethodsA total of 7 697 participants who underwent physical examination in Beijing Friendship Hospital， Capital Medical University， from January 2022 to December 2024 were enrolled， and finally 2 177 patients with MAFLD were enrolled as subjects. Transient elastography was used to quantify the severity of hepatic steatosis （grades S1-S3）. The multivariable ordinal Logistic regression analysis was used to investigate the independent and synergistic associations of serum triglyceride （TG）， high-density lipoprotein cholesterol （HDL-C）， and low-density lipoprotein cholesterol （LDL-C） with the severity of hepatic steatosis， and their interactions and potential nonlinear relationships with metabolic factors were also examined. One-way analysis of variance or Kruskal-Wallis H test was used for comparison of continuous data between groups， and chi-square test was used for comparison of categorical data between groups. ResultsAn increase in TG （odds ratio ［OR］=1.77， 95% confidence interval ［CI］： 1.48 — 2.10， P<0.001） and a reduction in HDL-C （OR=1.35， 95%CI： 1.11 — 1.65， P=0.003） were independently associated with a greater severity of hepatic steatosis， with the strongest association when both abnormalities coexisted （OR=2.40， 95%CI： 1.87 — 3.07， P<0.001）. The dose-response relationship analysis further revealed a nonlinear threshold effect of TG on hepatic steatosis at the threshold of 1.51 mmol/L （P_nonlinearity=0.001）， below which the severity of steatosis increased more rapidly with the increase in TG concentration （P=0.001）. The subgroup analysis showed that the association between the reduction in HDL-C and the severity of steatosis was observed only in males， young adults （aged <45 years）， and metabolically healthier subgroups （without diabetes， obesity， hyperuricemia or hypertension）. Significant interactions were observed between the presence or absence of obesity and the abnormal levels of TG and HDL‑C （both P_interaction<0.05）. The association of the increase in LDL-C with steatosis was confined to specific subgroups （without obesity or hyperuricemia）. ConclusionThe increase in TG and the reduction in HDL-C are independently associated with the severity of hepatic steatosis in MAFLD. The synergistic effect of blood lipids and their interactions with metabolic factors may further refine risk stratification， so as to provide a basis for precise management of MAFLD.

ObjectiveTo explore the role of cucurbitacin B （CuB） in inducing ferroptosis in 4T1 cells and its mechanism. MethodsThe effects of CuB（0.2， 0.4， 0.8 μmol·L^-1）on the proliferation ability of 4T1 cells in vitro were detected using the methyl thiazolyl tetrazolium （MTT） assay. The clonogenic ability of 4T1 cells was detected by the plate cloning assay， and the levels of lactate dehydrogenase （LDH） in 4T1 cells were detected by the use of a kit. The mitochondrial membrane potential and reactive oxygen species （ROS） levels in 4T1 cells were detected by flow cytometry， and the mitochondrial ultrastructure of 4T1 cells was observed by transmission electron microscopy. The western blot was used to detect the expression of ferroptosis-related protein p53 in 4T1 cells， solute carrier family 7 member 11 （SCL7A11）， glutathione peroxidase 4 （GPX4）， long-chain acyl-CoA synthetase 4 （ACSL4）， transferrin receptor protein 1 （TFR1）， and ferritin heavy chain 1 （FTH1）. ResultsCompared with that in the blank group， the survival rate of 4T1 cells in CuB groups was significantly decreased （P<0.05）， and the number of cell clones in CuB groups was significantly reduced （P<0.01）. In addition， compared with that in the blank group， the leakage of LDH in cells in CuB groups was significantly increased （P<0.01）， and the mitochondrial membrane potential of cells in CuB groups decreased significantly （P<0.01）. Cellular ROS levels were significantly elevated in CuB groups （P<0.01）. The mitochondria of cells in CuB groups were obviously wrinkled， and the mitochondrial cristae were reduced or even disappeared. Compared with that in the blank group， the protein expression of p53， ACSL4， and TFR1 were significantly up-regulated in CuB groups （P<0.05）， and that of SLC7A11， GPX4， and FTH1 were significantly down-regulated （P<0.05）. ConclusionCuB may inhibit SLC7A11 and GPX4 expression by up-regulating the expression of p53， which in turn regulates the p53/SLC7A11/GPX4 signaling pathway axis and accelerates the generation of lipid peroxidation substrate by up-regulating the expression of ACSL4. It up-regulates TFR1 expression to promote cellular uptake of Fe³⁺ and down-regulates the expression of FTH1 to reduce the ability of iron storage， resulting in an elevated free Fe²⁺ level. It catalyzes the Fenton reaction， generates excess ROS， imbalances the antioxidant system and iron metabolism， and then induces ferroptosis in 4T1 cells.

ObjectiveTo observe the clinical efficacy of tonifying kidney and replenishing essence on asthenozoospermia patients with the syndrome of kidney essence deficiency and the effects of this method on the adenosine 5′-monophosphate-activated protein kinase （AMPK）/mammalian target of rapamycin complex 1 （mTORC1） signaling pathway. MethodsSeventy-two eligible asthenozoospermia patients with the syndrome of kidney essence deficiency treated in the Affiliated Hospital of Chengdu University of Traditional Chinese Medicine from February 2023 to January 2024 were selected and randomly assigned into an observation group and a control group， with 36 patients in each group. The observation group received oral administration of Guilu Tianjing capsules， while the control group received oral administration of L-carnitine oral solution. The treatment course lasted for 4 weeks in both groups. The observed indicators included sperm progressive motility rate （PR）， total sperm motility （PR+NP）， percentage of normal mitochondrial membrane potential （MMP）， and traditional Chinese medicine （TCM） symptom scores before and after treatment in both groups. A three-month follow-up was instituted to record the conception status of the patients’ spouses. Additionally， eight patients were randomly selected from the eligible patients in the observation group， and four healthy males with normal semen routine examination results were included as the control group for the determination of protein expression. Western blotting was conducted to assess the expression of AMPK， phosphorylated （p）-AMPK， regulatory-associated protein of mTOR （RAPTOR） and p-RAPTOR， and PTEN-induced putative kinase 1 （PINK1） in sperms from the observation group before and after treatment， as well as in the sperms of the control group. ResultsThe pregnancy rate of spouses in the observation group was 9.09% （3/33）， which was higher than that （3.33%， 1/30） in the control group. The total response rate was 84.8% （28/33） in the observation group and 66.7% （20/30） in the control group， with no statistically significant difference. After treatment， both groups were improved considering PR， PR+NP， MMP， and TCM symptom scores （P<0.01）. Moreover， the observation group exhibited more pronounced decreases in TCM symptom scores than the control group （P<0.05）， while the changes in PR， PR+NP， and MMP showed no statistical significance between groups. Compared with the control group， the asthenozoospermia group exhibited upregulations in phosphorylation levels of AMPK and RAPTOR and protein level of PINK （P<0.01）. The administration of Guilu Tianjing Capsules led to downregulations in the phosphorylation levels of AMPK and RAPTOR and protein level of PINK1 （P<0.01）. However， the protein levels of AMPK and RAPTOR demonstrated no significant difference between before and after treatment. During the study period， neither group of patients exhibited any notable adverse reactions. ConclusionGuilu Tianjing capsules can enhance the sperm motility and percentage of normal mitochondrial membrane potential in asthenozoospermia patients with the syndrome of kidney essence deficiency by downregulating the AMPK/mTORC1 signaling pathway， lowering the protein level of PINK1， and inhibiting excessive activation of mitophagy.