ObjectiveTo explore the complex network relationships among pain, kinesiophobia, social participation and knee function in patients after total knee arthroplasty (TKA), and to analyze the moderating effects of different socio-structural factors on the rehabilitation network from an ethical equity perspective. MethodsA convenience sampling method was used to select 291 patients who underwent TKA in Qilu Hospital of Shandong University from May to July, 2023. Pain was assessed using Numerical Rating Scale, kinesiophobia with Chinese short version of the Tampa Scale for Kinesiophobia, social participation with Impact on Participation and Autonomy Questionnaire, and knee function with Hospital for Special Surgery Knee Score. A partial correlation network among pain, kinesiophobia, social participation and knee function was constructed using Graphical Least Absolute Shrinkage and Selection Operator. Key variables were identified through node centrality and bridge centrality analysis. Network Comparison Tests (NCT) were used to analyze network differences among subgroups based on different socio-structural characteristics. ResultsIn the network model, the nodes with the highest strength centrality were indoor participation, activity behavior and activity pain. Bridge centrality analysis indicated that activity pain, knee function, indoor participation and activity cognition were key bridge nodes. NCT revealed no significant differences in overall network structure or global strength among subgroups based on residence, education level or payment method (P > 0.05). However, significant differences in edge weights were found for specific edges such as activity cognition-activity behavior and knee function-indoor participation (P < 0.05). ConclusionThere is a network of interactions among pain, kinesiophobia, social participation and knee function in patients after TKA, with nodes such as indoor participation and activity pain playing key roles in the rehabilitation process. Although the overall rehabilitation network is similar across different socio-structural groups, variations exist in specific relational pathways among patients from rural areas, those with lower education levels, and those with out-of-pocket payment. This suggests that clinical rehabilitation interventions should focus on these core nodes and implement targeted support strategies for socio-structurally disadvantaged groups to promote rehabilitation equity.

ObjectiveTo explore the complex network relationships among pain, kinesiophobia, social participation and knee function in patients after total knee arthroplasty (TKA), and to analyze the moderating effects of different socio-structural factors on the rehabilitation network from an ethical equity perspective. MethodsA convenience sampling method was used to select 291 patients who underwent TKA in Qilu Hospital of Shandong University from May to July, 2023. Pain was assessed using Numerical Rating Scale, kinesiophobia with Chinese short version of the Tampa Scale for Kinesiophobia, social participation with Impact on Participation and Autonomy Questionnaire, and knee function with Hospital for Special Surgery Knee Score. A partial correlation network among pain, kinesiophobia, social participation and knee function was constructed using Graphical Least Absolute Shrinkage and Selection Operator. Key variables were identified through node centrality and bridge centrality analysis. Network Comparison Tests (NCT) were used to analyze network differences among subgroups based on different socio-structural characteristics. ResultsIn the network model, the nodes with the highest strength centrality were indoor participation, activity behavior and activity pain. Bridge centrality analysis indicated that activity pain, knee function, indoor participation and activity cognition were key bridge nodes. NCT revealed no significant differences in overall network structure or global strength among subgroups based on residence, education level or payment method (P > 0.05). However, significant differences in edge weights were found for specific edges such as activity cognition-activity behavior and knee function-indoor participation (P < 0.05). ConclusionThere is a network of interactions among pain, kinesiophobia, social participation and knee function in patients after TKA, with nodes such as indoor participation and activity pain playing key roles in the rehabilitation process. Although the overall rehabilitation network is similar across different socio-structural groups, variations exist in specific relational pathways among patients from rural areas, those with lower education levels, and those with out-of-pocket payment. This suggests that clinical rehabilitation interventions should focus on these core nodes and implement targeted support strategies for socio-structurally disadvantaged groups to promote rehabilitation equity.

ObjectiveTo explore the complex network relationships among pain, kinesiophobia, social participation and knee function in patients after total knee arthroplasty (TKA), and to analyze the moderating effects of different socio-structural factors on the rehabilitation network from an ethical equity perspective. MethodsA convenience sampling method was used to select 291 patients who underwent TKA in Qilu Hospital of Shandong University from May to July, 2023. Pain was assessed using Numerical Rating Scale, kinesiophobia with Chinese short version of the Tampa Scale for Kinesiophobia, social participation with Impact on Participation and Autonomy Questionnaire, and knee function with Hospital for Special Surgery Knee Score. A partial correlation network among pain, kinesiophobia, social participation and knee function was constructed using Graphical Least Absolute Shrinkage and Selection Operator. Key variables were identified through node centrality and bridge centrality analysis. Network Comparison Tests (NCT) were used to analyze network differences among subgroups based on different socio-structural characteristics. ResultsIn the network model, the nodes with the highest strength centrality were indoor participation, activity behavior and activity pain. Bridge centrality analysis indicated that activity pain, knee function, indoor participation and activity cognition were key bridge nodes. NCT revealed no significant differences in overall network structure or global strength among subgroups based on residence, education level or payment method (P > 0.05). However, significant differences in edge weights were found for specific edges such as activity cognition-activity behavior and knee function-indoor participation (P < 0.05). ConclusionThere is a network of interactions among pain, kinesiophobia, social participation and knee function in patients after TKA, with nodes such as indoor participation and activity pain playing key roles in the rehabilitation process. Although the overall rehabilitation network is similar across different socio-structural groups, variations exist in specific relational pathways among patients from rural areas, those with lower education levels, and those with out-of-pocket payment. This suggests that clinical rehabilitation interventions should focus on these core nodes and implement targeted support strategies for socio-structurally disadvantaged groups to promote rehabilitation equity.

Olfactory receptors (ORs) form the largest superfamily of G protein-coupled receptors (GPCRs). Traditionally recognized for their role in the nasal olfactory epithelium, where they mediate the sense of smell, accumulating evidence has firmly established their ectopic expression in non-olfactory tissues, including the intestine, lungs, and kidneys. The intestine, as the primary site for nutrient digestion and absorption, harbors a highly complex chemical environment. To adapt to this environment, the gut employs a sophisticated network of “chemosensors” to monitor luminal contents and maintain homeostasis. Among these sensors, intestinal ORs have emerged as crucial functional components, serving as a molecular bridge that connects environmental chemical signals—such as food-derived odorants—to specific physiological responses. This discovery has significantly deepened our understanding of how dietary flavors and compounds influence intestinal physiology at the molecular level. This review systematically summarizes the expression profiles, ligand classification, and biological functions of ORs within the gastrointestinal tract. Studies indicate that intestinal ORs exhibit distinct spatial distribution patterns across different gut segments and display cell-type specificity, particularly within enterocytes and enteroendocrine cells. These receptors function as versatile sensors capable of recognizing a wide variety of ligands, including exogenous dietary components, gut microbiota metabolites such as short-chain fatty acids, and endogenous small molecules like azelaic acid. Upon activation by specific ligands, intestinal ORs trigger intracellular signaling cascades, primarily involving the AC-cAMP-PKA pathway or calcium influx channels. A major focus of this review is to elucidate the molecular mechanisms by which these receptors regulate the secretion of gut hormones. Activation of specific ORs in enteroendocrine cells has been shown to stimulate the release of hormones such as glucagon-like peptide-1 (GLP-1), peptide YY (PYY), and serotonin (5-HT), thereby modulating systemic energy metabolism, glucose homeostasis, and gastrointestinal motility. Furthermore, the review addresses the critical roles of ORs in immune regulation and pathology. Evidence suggests that specific ORs contribute to the maintenance of intestinal immune homeostasis and may offer protection against inflammation. Beyond their involvement in inflammatory responses, ORs such as Olfr78 have been shown to regulate the differentiation and function of intestinal endocrine cells. Similarly, Olfr544 has been demonstrated to alleviate intestinal inflammation by remodeling the gut microbiome and metabolome. These findings collectively suggest that specific ORs hold promise as therapeutic targets for mitigating intestinal inflammation and maintaining gut homeostasis. Additionally, the review explores the emerging role of ORs in cancer. Although OR expression is often downregulated in tumor tissues compared to normal mucosa, activation of specific ORs by certain ligands can inhibit tumor cell proliferation and migration and induce apoptosis via pathways such as MEK/ERK and p38 MAPK. Conversely, other receptors, such as OR7C1, may serve as biomarkers for cancer-initiating cells. In conclusion, intestinal ORs represent a vital component of the gut’s sensory network. The review also discusses the translational potential of these findings. By elucidating the precise pairing relationships between dietary components and specific ORs, novel therapeutic strategies could be developed. Intestinal ORs may thus emerge as promising targets for nutritional and pharmacological interventions in metabolic diseases, inflammatory bowel diseases, and malignancies.

Objective To construct a dynamic prediction model for JC polyomavirus (JCV) reactivation after kidney transplantation. Methods A retrospective analysis was conducted on the clinical data of 128 recipients who met the inclusion criteria and received kidney transplantation in Nanfang Hospital, Southern Medical University, from June 2021 to December 2024. Dynamic Cox regression and dynamic restricted mean survival time (RMST) regression based on the landmark method were adopted to establish the dynamic prediction models, and Monte Carlo cross-validation was used to evaluate model performance. Results The dynamic models could predict the incidence and onset time of JCV reactivation within the subsequent 3 months according to covariates at each landmark time point from the 1st to the 6th month after transplantation. Remuzzi score, body mass index and warm ischemia time were independent risk factors for JCV reactivation, while a history of urinary BK polyomavirus reactivation served as a protective factor. The median values of the area under the curve, C-index and Brier score of the dynamic Cox model were 0.873, 0.851 and 0.065 respectively, and the C-index of the dynamic RMST model was 0.829, all of which were superior to those of the static model. Conclusions The landmark-based dynamic models exhibit excellent predictive performance, which may integrate baseline data and post-transplant follow-up information to realize dynamic assessment of the risk and time window of JCV reactivation, thereby providing evidence for optimizing post-operative monitoring and individualized intervention strategies.

ObjectiveTo investigate the novel post-translational modifications (PTMs) of SnRK2.6, a central component in the abscisic acid (ABA) signaling pathway, such as SUMOylation, and to establish a foundation for revealing the physiological functions and molecular mechanisms of SnRK2.6 regulated by these new modifications. MethodsThe interaction between SnRK2.6 and the SUMO E3 ligase SIZ1, as well as members of the SUMO protease family, was examined using yeast two-hybrid and in vitro pull-down assays. An in vitro SUMOylation system in Escherichia coli was utilized to determine whether SnRK2.6 undergoes SUMOylation. Mass spectrometry, combined with site-directed mutagenesis of candidate lysine residues, was employed to identify potential SUMOylation sites on SnRK2.6. In vitro de-SUMOylation assays were performed to assess whether SUMO proteases interacting with SnRK2.6 could catalyze the removal of SUMO moieties from modified SnRK2.6. The protein stability of SnRK2.6 was assessed in a cell-free degradation assay using bacterial-purified SnRK2.6 incubated with total protein extracts from Col and siz1 mutant seedlings. To dissect the genetic relationship between SnRK2.6 and SIZ1, stomatal aperture assays were performed under ABA treatment using snrk2.6, siz1, and snrk2.6 siz1 double mutant plants. ResultsSnRK2.6 physically interacts with SIZ1 and the SUMO protease ESD4, with the binding domains localized to the C-terminal region of SIZ1 and the N-terminal region of ESD4, respectively. SnRK2.6 was found to be SUMOylated, exhibiting two distinct high-molecular-mass bands ranging from 70 to 100 ku, indicative of modified forms. Bioinformatics analysis predicted four putative SUMOylation sites on lysine residues K57, K63, K142, and K190. Mass spectrometry identified three SUMOylation sites on K63, K142, and K174. However, individual or combinatorial point mutations on these sites had minimal impact on the pattern or intensity of SUMOylation signals, suggesting that these residues may not be responsible for the SUMOylation on SnRK2.6. Instead, such mutations only weaken the protein stability or accelerate the protein mobility of SnRK2.6. Therefore, the exact SUMOylation sites on SnRK2.6 remain unidentified. In de-SUMOylation experiments, incubation of GST-ESD4 with SUMOylated SnRK2.6 for 1-2 h led to the near-complete disappearance of both SUMOylated bands. In contrast, neither the GST control nor the catalytically inactive mutant GST-ESD4^C448S exhibited any de-SUMOylation activity. In protein turnover experiments, SnRK2.6 exhibited markedly enhanced half-life in siz1 compared with Col, indicating that SIZ1-dependent SUMOylation promotes SnRK2.6 turnover. Phenotypically, snrk2.6 mutants were completely insensitive to ABA-induced stomatal closure; siz1 mutants displayed pronounced hypersensitivity; and the snrk2.6 siz1 double mutant phenocopied snrk2.6—showing no significant response to ABA beyond that of the snrk2.6 mutant. These data indicate that SIZ1 acts as a negative regulator of ABA-triggered stomatal closure and SnRK2.6 functions as a positive regulator, and the inhibitory activity of SIZ1 is strictly dependent on SnRK2.6, placing SnRK2.6 genetically upstream of SIZ1 in the ABA signaling pathway. ConclusionSnRK2.6 undergoes SUMOylation, although the specific SUMOylation sites have not been defined. SnRK2.6 is dynamically regulated by reversible SUMOylation—catalyzed by SIZ1 and reversed by ESD4—which controls its protein stability. SUMOylation acts as a destabilizing signal for SnRK2.6, and SIZ1 exerts its negative effect on ABA-triggered stomatal closure probably through promoting SnRK2.6 degradation via SUMOylation. These findings uncover SUMOylation as a critical regulatory layer fine-tuning SnRK2.6 abundance in ABA signaling.

Objective: To analyze the demographic evolution of China over the forthcoming decade (2026-2035) and to systematically evaluate its potential implications for voluntary blood donation practices and the equilibrium of clinical blood supply and demand. Methods: Leveraging comprehensive blood collection and utilization data from 2021 to 2025 at the national, provincial (Shandong), and municipal (Zibo) levels, we identified and examined critical determinants influencing blood management systems. The DeepSeek-V3.2 large language model was deployed to project future population age structures, and to generate quantitative estimates for hospitalization volumes, clinical blood requirements, available blood supply, and donation frequencies for the target years 2030 and 2035, thereby furnishing an evidence base for strategic planning and priority-setting. Results: DeepSeek-derived projections indicate that the proportion of China's population aged 60 years and above will surpass 27% (370 million/1 380 million) by 2030 and exceed 30% (400 million/1 350 million) by 2035, signaling a marked acceleration in population aging. This demographic shift is projected to reduce the proportion of the national population eligible to donate blood from 59.2% (835 million out of 1.41 billion) to 52% (710 million out of 1.36 billion), while the demand for blood is expected to increase by 87.8% relative to 2024, rising from 26.927 million units to 50.56 million units. Sustaining blood supply-demand balance will necessitate progressive annual increases in donation rates. Under prevailing policy frameworks, the required blood donation rate among the eligible population in Shandong Province would need to rise by 122.57% by 2035 [from 20.07‰ (1.1641 million person-times/58 million people) to 44.67‰ (2.189 million person-times/49 million people)] to potentially satisfy projected clinical requirements. Conclusion: By integrating DeepSeek-V3.2, AI predictive models, and blood donation incentive measures, it is possible to monitor population demographics, forecast clinical blood demand, manage blood supplies, and ensure the long-term sustainability of clinical blood availability. It must be acknowledged, however, that the present analysis is constrained by a limited data foundation (comprising only five annual observation points); accordingly, the projections should be interpreted as directional trend indicators or methodological illustrations rather than definitive quantitative forecasts.

ObjectiveTo elucidate the critical role of rehabilitation medical records (including electronic records) in rehabilitation medicine's clinical practice and management, comprehensively analyzed the structure, core content and data standards of rehabilitation medical records, to develop a standardized medical record data architecture and core dataset suitable for rehabilitation medicine and to explore the application of rehabilitation data in performance evaluation and payment. MethodsBased on the regulatory documents Basic Specifications for Medical Record Writing and Basic Specifications for Electronic Medical Records (Trial) issued by National Health Commission of China, and referencing the World Health Organization (WHO) Family of International Classifications (WHO-FICs) classifications, International Classification of Diseases (ICD-10/ICD-11), International Classification of Functioning, Disability and Health (ICF), and International Classification of Health Interventions (ICHI Beta-3), this study constructed the data architecture, core content and data standards for rehabilitation medical records. Furthermore, it explored the application of rehabilitation record summary sheets (home page) data in rehabilitation medical statistics and payment methods, including Diagnosis-related Groups (DRG), Diagnosis-Intervention Packet (DIP) and Case Mix Index. ResultsThis study proposed a systematic standard framework for rehabilitation medical records, covering key components such as patient demographics, rehabilitation diagnosis, functional assessment, rehabilitation treatment prescriptions, progress evaluations and discharge summaries. The research analyzed the systematic application methods and data standards of ICD-10/ICD-11, ICF and ICHI Beta-3 in the fields of medical record terminology, coding and assessment. Constructing a standardized data structure and data standards for rehabilitation medical records can significantly improve the quality of data reporting based on the medical record summary sheet, thereby enhancing the quality control of rehabilitation services, effectively supporting the optimization of rehabilitation medical insurance payment mechanisms, and contributing to the establishment of rehabilitation medical performance evaluation and payment based on DRG and DIP. ConclusionStructured rehabilitation records and data standardization are crucial tools for quality control in rehabilitation. Systematically applying the three reference classifications of the WHO-FICs, and aligning with national medical record and electronic health record specifications, facilitate the development of a standardized rehabilitation record architecture and core dataset. Standardizing rehabilitation care pathways based on the ICF methodology, and developing ICF- and ICD-11-based rehabilitation assessment tools, auxiliary diagnostic and therapeutic systems, and supporting terminology and coding systems, can effectively enhance the quality of rehabilitation records and enable interoperability and sharing of rehabilitation data with other medical data, ultimately improving the quality and safety of rehabilitation services.

AIM: To screen and analyze the influencing factors of myopia among primary and secondary school students and establish a predictive model to provide ideas for the prevention and control measures of myopia among children and adolescents.METHODS:A total of 1 759 primary and secondary school students from 2 primary schools, 2 junior high schools, 2 senior high schools and 1 vocational high school in the urban area of Qingdao were sampled by means of stratified cluster sampling in September 2023. Vision screening and a questionnaire survey on influencing factors were carried out based on machine learning algorithms. The screening and determination were mainly conducted in accordance with the Standard Logarithmic Visual Acuity Chart(GB/T11533-2011)and the Specifications for Screening Myopia in Children and Adolescents. The influencing factors of myopia were analyzed and a prediction model was developed based on the machine learning algorithms LASSO in combination with XGBoost, and visualization was achieved through an interactive Nomogram. Statistical analysis was performed using R statistical software version 4.3.3.RESULTS:The screening prevalence of myopia among primary and secondary school students in the urban area of Qingdao was 70.61%(1 242 cases). The optimal predictive variables for screening were grade, gender, whether parents were myopic, daily indoor sedentary time, appropriate distance between eyes and books during reading and writing, daily sleep time, distance between eyes and TV screen when watching TV/playing video games exceeding 3 meters, the playground during breaks, total duration of tutorial classes, how often eyes are rested during near work, daily computer usage time, and average daily homework time after school, totaling 12 influencing factors. The AUCs of the training set and test set were 0.770(95%CI:0.751-0.789)and 0.732(95%CI:0.714-0.750), respectively.CONCLUSION: A machine learning-based prediction model was developed and validated to predict the risk of myopia onset in primary and secondary school students, accompanied by effective visualization techniques.

Objective: To examine the application of multi-disciplinary treatment (MDT) in the diagnosis and management of recurrence and metastasis of adenoid cystic carcinoma (ACC) of the palate, as well as the treatment of concurrent massive palatal bleeding. This article aimed to provide references for the diagnosis and treatment of patients with advanced oral cancer, along with strategies for managing massive hemorrhage. Methods: This article reported on the MDT process for a patient diagnosed with ACC of the left upper palate, who experienced skull base recurrence and lung metastasis following surgery and radiotherapy. The case was further complicated by massive palatal hemorrhage. Additionally, the article analyzed patients with ACC recurrence and significant hemorrhage in the context of relevant literature. The patient was a 36-year-old female with ACC located in the left palate, initially diagnosed at clinical stage T3N0M0 in 2013. She underwent an extensive resection of the palatal lesion, followed by radioactive 125I seed implantation, which was guided by a radiotherapy planning system (TPS) and a digital guide. The patient was monitored for four years post-surgery, during which no signs of tumor recurrence were observed. However, at the fifth year of follow-up, the patient developed recurrence with lung metastasis, classified as T4N0M1. Following a multidisciplinary consultation involving the oral and maxillofacial surgery, radiotherapy, medical oncology, and thoracic surgery, the patient underwent a procedure comprising left subtotal maxillary resection, autologous free flap transplantation, and thoracoscopic resection of pulmonary metastases. After surgery, the patient received 60 Gy of radiotherapy and was orally administered Anlotinib hydrochloride capsules to suppress tumor growth. After 31 months of follow-up, the patient reported experiencing slight bleeding in the mouth. A craniomaxillofacial CT scan revealed that the tumor had grown aggressively, resulting in destruction of the skull base. Consequently, the patient was admitted to the hospital. On the second day of admission, she experienced a sudden episode of oral bleeding. Despite the application of pressure, the bleeding continued unabated. An emergency tracheotomy was performed to relieve the obstruction of the patient’s respiratory tract, and a red blood cell suspension was transfused to address the hemorrhagic shock. Following an urgent consultation with the vascular interventional surgery department, super-selective embolization was promptly employed to effectively halt the bleeding and achieve rapid vascular occlusion. An individualized treatment plan was developed under MDT, incorporating postoperative radiotherapy, targeted therapies, and immunotherapy to manage the tumor. Results: Through the MDT model, the patient successfully achieved emergency hemostasis, and normal vital signs were restored. With the addition of radiotherapy and immune-targeted drug treatment, tumor progression was effectively controlled, leading to an improved quality of life for the patient, who successfully survived for 129 months with the tumor by July 2024. A review of the relevant literature indicated that MDT offered significant advantages in the management of adenoid cystic carcinoma. In selecting surgical methods, the team administering MDT could comprehensively evaluate factors such as the patient’s age, physical condition, tumor location, size, and extent of invasion to develop a personalized treatment plan. Radical surgical resection was a common treatment option for ACC. Postoperative tissue defects could be restored to their corresponding functions and aesthetic appearance through autologous tissue reconstruction, utilizing techniques such as peroneal myocutaneous flaps or iliac myocutaneous flaps, or by the implantation of artificial materials. In complex cases involving positive margins, recurrence, and metastasis, the MDT model employed interdisciplinary collaboration to devise a comprehensive treatment plan that may have included re-operation, radiotherapy, and chemotherapy, with the aim of minimizing the risk of ACC recurrence and controlling distant metastasis. Massive bleeding resulting from advanced oral cancer presented a complex medical challenge, influenced by various risk factors such as tumor type, metastasis, treatment options, and the patient’s overall condition. Early identification of bleeding risks, along with strategies to mitigate the adverse effects of bleeding on disease progression—through supportive care, medical treatment, surgical intervention, and interventional therapy—could significantly enhance patients’ quality of life. Conclusion The MDT model can provide comprehensive, precise, and personalized treatment plans for patients with advanced oral cancer and massive hemorrhage and improve the effectiveness of treatment strategies.