ObjectiveTo systematically evaluate the application of narrative education in undergraduate nursing teaching， to understand the current application status of narrative education， and to provide a theoretical basis for the subsequent establishment of a sound narrative education system. MethodsA systematic search was conducted for studies published in Chinese and English databases on applying narrative education to undergraduate nursing teaching， with the search period ranging from database inception to February 23， 2025. Literature was screened， and relevant information was extracted. A rigorous quality evaluation was conducted on the included studies， and a descriptive analysis was performed on their content. ResultsA total of 20 papers were included， involving 3，180 research subjects， all of whom were undergraduate nursing students. The results of descriptive analysis showed that the teaching model of narrative education primarily encompassed reading narrative works， watching films and videos， performing narrative scenarios， and writing reflective journals. The course setting and content covered pre-teaching preparation and in-teaching implementation. The evaluation of teaching effectiveness included the evaluation of teachers’ teaching methods （student evaluation/self-evaluation） and the evaluation of students’ learning effectiveness （course grade evaluation/humanistic care scale/empathy scale assessment， and others）. ConclusionNarrative education combines abstract concepts with concrete clinical situations， which not only enriches students’ learning experiences but also enhances their humanistic literacy. Meanwhile， it provides teachers with opportunities to develop their narrative teaching skills， which requires them to possess profound professional knowledge and employ narrative techniques to guide students in reflection and critical thinking， thereby improving teaching quality and learning outcomes. Future efforts should consistently deepen the connotation research of narrative education and build a systematic nursing education system.

Objective To evaluate the feasibility and safety of Remodeling+Ring (modified Yacoub) for patients with aortic root aneurysm. Methods The clinical data of patients who underwent modified Yacoub surgery at West China Hospital of Sichuan University from July 2020 to May 2023 were retrospectively analyzed. Results Four male patients were enrolled, with an average age of (47.3±10.3) years and body surface area of (1.9±0.2) m2. One patient had bicuspid aortic valve. Aortic valve regurgitation was mild in three patients and moderate in one patient. Preoperative New York Heart Association (NYHA) heart function was gradeⅠin one patient and gradeⅡin three patients. The maximum diameter of the aortic sinus was (59.3±8.1) mm. All four patients recovered and were discharged without a second thoracotomy. No postoperative complications such as brain injury, infection, respiratory failure or renal insufficiency occurred. During the follow-up of (17.0±13.1) months, two patients showed no regurgitation of the aortic valve, two patients exhibited mild regurgitation. Three patients had a heart function of gradeⅠ and one patient of gradeⅡ. Conclusion Modified Yacoub technique is safe and effective for patients with aortic root aneurysm.

Kui was first recorded in The Rites of Zhou and is the earliest domesticated wild vegetable in China. In the Qi Min Yao Shu, Kui was called “the master of all vegetables” and has a long history of application in China. As a medicine, Kuizi was first recorded in Shen Nong’s Herbal Classic, which has a history of more than 2 000 years of medicinal use and a long history of clinical application. By researching the ancient and modern herbal literature, the first herbs texts of Kui were examined, various recorded texts, confused products and the history of the original medicinal use were clarified. It was concluded that the ancient herbal texts recorded the base plant of Kui as Malva verticillata L. belonging to family Malvaceae, which provided scientific basis for the development and utilization of Kui.

ObjectiveThe malaria parasites remodel the host erythrocyte structure by exporting parasite proteins that interact with the membrane skeleton proteins of red blood cells (RBCs), facilitating their intracellular survival and pathogenicity. Skeleton-binding protein 1 (SBP1) is a conserved exported protein across Plasmodium species. In Plasmodium falciparum, SBP1 has been reported to interact with erythrocyte membrane skeleton proteins 4.1R and spectrin, while its contribution to erythrocyte remodeling and parasite virulence in Plasmodium berghei (Pb) remains unclear. This study aims to determine whether PbSBP1 associates with the host cytoskeletal protein 4.1R and to investigate its role in the remodeling of host RBCs and the pathogenicity of Plasmodium berghei. MethodsIn Plasmodium berghei, the relationship between PbSBP1 and the erythrocyte cytoskeletal protein 4.1R was examined using co-immunoprecipitation. A Pbsbp1 gene knockout mutant of Plasmodium berghei (Pbsbp1∆) was generated based on the principle of double crossover homologous recombination. The deformability of erythrocytes infected with Pbsbp1∆ parasites was assessed using microfluidic methods. Microchannels with an array of cylindrical pillars were used to detect modifications in infected RBC deformability. The infected RBCs were squashed between the rows and recovered between the columns and the transit velocity (μm/s) of infected RBCs travelling through the microchannel was recorded. The component of the erythrocyte membrane skeleton junctional complex, tropomodulin (TMOD), was fluorescently labeled, and the cytoskeletal network of infected erythrocytes was imaged using super-resolution stochastic optical reconstruction microscopy (STORM) to analyze ultrastructural changes in the cytoskeleton of wild-type (WT) and Pbsbp1∆-infected erythrocytes. Actin-based junctional complexes were displayed as individual clusters by the labeled TMOD in the STORM images, and the cluster densities and distances between adjacent clusters of infected RBCs were calculated. Additionally, rodent malaria models (BALB/c mice) and experimental cerebral malaria models (C57BL/6 mice) were employed to monitor the growth of Pbsbp1∆ and WT parasites during the intraerythrocytic stage and their capacity to induce cerebral malaria in mice. ResultsPbSBP1 may participate in the remodeling of infected erythrocytes through direct or indirect interaction with the erythrocyte cytoskeletal protein 4.1R. Microfluidic assays revealed that the deformability of erythrocytes infected with Pbsbp1∆ parasites was significantly enhanced compared to those infected with WT parasites. STORM imaging further demonstrated that the ultrastructure of the erythrocyte cytoskeleton in Pbsbp1∆-infected cells was altered relative to that in WT-infected erythrocytes. The distances between nearest neighbors of clusters had a tendency to increase while the cluster densities were decreased in Pbsbp1∆-infected RBCs compared to WT-infected RBCs. Subsequent phenotypic analysis indicated that the growth rate of Pbsbp1∆ parasites during the intraerythrocytic stage was significantly slower than that of WT parasites, and their ability to induce cerebral malaria in mice was also attenuated. These findings suggest that PbSBP1 is involved in the remodeling of the erythrocyte membrane skeleton, likely through its direct or indirect interaction with protein 4.1R, thereby regulating the deformability of infected erythrocytes and influencing the pathogenicity of the blood-stage parasites. ConclusionThis study establishes a role for PbSBP1 in host erythrocyte remodeling and parasite virulence, providing new research strategies for the prevention and treatment of malaria.

ObjectiveStroke poses a heavy burden due to its high mortality and morbidity rates. Accurate and real-time detection of lesions is pivotal for prompt clinical intervention and favorable prognosis. Electrical impedance tomography (EIT) and microwave tomography (MWT) have emerged as compelling alternatives for stroke screening, owing to their non-ionizing, non-invasive and portable nature. EIT provides information on tissue conductivity, and MWT offers high sensitivity to changes in dielectric properties. However, single-modality imaging is inherently limited, EIT suffers from low sensitivity to deep-seated tissues and severe ill-posedness of inverse problems, whereas MWT is challenged by strong nonlinearity in inverse scattering and susceptibility to modeling errors. Consequently, the clinical utility of standalone EIT or MWT for stroke diagnosis remains constrained by poor spatial resolution and imaging artifacts. To improve the accuracy and robustness of stroke imaging, a dual-modality fusion conditional denoising diffusion probabilistic model (DM-DDPM) was proposed for high-precision dual-modality image reconstruction. MethodsA dual-encoder network with a symmetric architecture and independently trained parameters was constructed to extract heterogeneous features separately from EIT boundary voltage measurements and MWT scattered field signals. Attentional feature fusion (AFF) is employed to integrate complementary information from the two modalities adaptively, generating robust fused priors that suppress redundant noise while preserving key physical characteristics. Subsequently, the fused priors are embedded into a Transformer-based diffusion model via a cross attention mechanism to guide the reverse denoising process. This approach effectively reduces artifacts and enhances the stability of conductivity distribution reconstruction. Time step embedding is introduced to enable the network to perceive the diffusion stage and further improve the accuracy of noise prediction. ResultsSimulated experiments demonstrated that DM-DDPM significantly outperforms single-modality and multi-modality networks under various noise levels. A head model simulation dataset was constructed based on COMSOL Multiphysics, and tests were carried out under 50 dB, 40 dB and 30 dB signal-to-noise ratio levels. At 30 dB, the average relative error (RE) was below 0.20, while the structural similarity index measure (SSIM) and correlation coefficient (CC) remained above 0.90 and 0.89, respectively. Compared with single-modality and multi-modality networks, artifacts were significantly reduced, lesion edges were clearer, and localization was more accurate. The model maintains high reconstruction quality and strong robustness for single, double, and triple lesions simultaneously. Furthermore, physical experiments were conducted using a 16-electrode EIT system and a 16-antenna MWT system with asynchronous data acquisition. These experiments confirmed the feasibility of the method in real-world scenarios and demonstrated that it can robustly reconstruct simulated lesions despite environmental interference and measurement noise, validating its reliability for practical clinical applications. ConclusionThe proposed method effectively combines complementary dual-modality information with a conditional diffusion model. Low accuracy and poor noise resistance in single-modality imaging were effectively addressed, while the noise amplification issue caused by direct multimodal data fusion was avoided. The proposed algorithm exhibits strong anti-noise interference ability and high imaging stability in both simulation and physical experiments. Precise localization of stroke lesions with different quantities was achieved, providing a high-precision, and practical technical support for clinical stroke detection.

Diabetic sarcopenia (DS) is a common but often ignored skeletal muscle complication in individuals with diabetes mellitus. It is characterized by progressive loss of skeletal muscle mass, reduced muscle strength, and impaired physical performance, which may further increase the risk of falls, disabilities, metabolic disorders, and adverse clinical outcomes. Traditionally, DS has been attributed mainly to hyperglycemia, insulin resistance, aging-related muscle decline, and chronic complications of diabetes. However, increasing evidence suggests that lipid metabolic disturbance and pathological lipid metabolic reprogramming are not merely secondary consequences of diabetes, but may actively participate in the initiation and progression of DS. Under diabetic conditions, impaired fatty acid uptake, transport, oxidation, and storage disrupt skeletal muscle metabolic homeostasis, leading to ectopic lipid deposition and accumulation of lipotoxic intermediates. These lipid-derived metabolites can aggravate insulin resistance, impair mitochondrial energy production, enhance oxidative stress, activate chronic low-grade inflammation, and disturb protein synthesis and degradation balance, thereby accelerating skeletal muscle atrophy and functional decline. Lipid metabolic dysregulation may also interact with multiple pathological processes involved in DS, including mitochondrial dysfunction, inflammatory signaling, oxidative damage, impaired autophagy, and gut microbiota imbalance. These mechanisms do not occur independently; instead, they form a complex bidirectional vicious cycle with diabetes-related metabolic disorders. Specifically, mitochondrial dysfunction reduces fatty acid oxidative capacity, which further promotes lipid accumulation and lipotoxicity. Inflammatory activation can impair insulin signaling and muscle protein metabolism, while lipid overload may in turn amplify inflammatory responses. Similarly, gut microbiota dysbiosis and altered microbial metabolites may influence systemic inflammation, lipid metabolism, and skeletal muscle homeostasis. Therefore, lipid metabolic reprogramming provides an important mechanistic perspective for understanding the progression of DS from metabolic disturbance to structural and functional muscle impairment. Exercise intervention is an effective and clinically feasible non-pharmacological strategy for the prevention and management of DS. Both aerobic exercise and resistance training have been shown to improve insulin sensitivity, enhance fatty acid oxidation, increase mitochondrial biogenesis, reduce ectopic lipid deposition, and attenuate lipotoxic metabolite accumulation. These adaptations not only improved glucose and lipid metabolism, but also increased the preservation of muscle mass, muscle strength, and physical function. Moreover, combined exercise strategies may provide complementary benefits by integrating the metabolic advantages of aerobic exercise with the anabolic and functional effects of resistance training. Based on analyses of publicly available datasets and literature evidences, this review systematically summarizes the role of lipid metabolic disorders in the pathogenesis of DS, with particular attention to the molecular mechanisms linking lipid dysregulation to insulin resistance, chronic inflammation, oxidative stress, mitochondrial dysfunction, and gut microbiota disturbance. Furthermore, this review discusses the potential mechanisms by which exercise intervention improves DS through the regulation of lipid metabolic reprogramming, and outlines exercise prescription strategies in terms of modality, intensity, frequency, and duration. Understanding the interaction between lipid metabolism and skeletal muscle dysfunction may provide new theoretical evidence for early identification, mechanistic research, and precision exercise therapy in DS. Overall, targeting pathological lipid metabolic reprogramming through exercise intervention represents a promising and clinically actionable approach for improving muscle health and prognosis in individuals with DS.

Kynurenine pathway (KP) is a major catabolic route of tryptophan, generating a series of bioactive metabolites including kynurenine, kynurenic acid (KA), quinolinic acid, and 3-hydroxykynurenine. Beyond its fundamental role in amino acid metabolism, KP exerts critical regulatory functions in neurodevelopment, synaptic plasticity, and immune modulation. Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition with onset in early childhood, characterized by persistent deficits in social communication and restricted, repetitive behaviors. Despite extensive research, the etiological mechanisms underlying ASD remain highly complex and incompletely understood, involving genetic, environmental, and immunological factors. Emerging clinical evidence has consistently revealed a significant imbalance in KP metabolites in individuals with ASD, often accompanied by altered ratios of neuroprotective versus neurotoxic byproducts. However, the primary drivers of this metabolic dysregulation and its causative contribution to ASD pathogenesis are not yet fully elucidated. In this review, we systematically review the enzymatic steps of KP and the principal physiological functions of its major metabolites, with particular emphasis on their dual roles in neuroprotection and neurotoxicity. We then analyze the potential pathogenic mechanisms through which KP dysfunction may contribute to ASD, focusing on two interconnected etiological dimensions. First, KP imbalance can promote oxidative stress, which in turn triggers chronic inflammatory responses via microglial activation and release of pro-inflammatory cytokines, thereby disrupting neuronal homeostasis. Second, aberrant KP metabolism affects neurotransmitter systems, particularly glutamatergic and dopaminergic signaling, leading to impaired neural circuit development and synaptic pruning. By integrating current findings on the KP-ASD association, this review offers a comprehensive etiological framework and a clinically relevant paradigm. Furthermore, we highlight that specific KP metabolites, such as the KA/quinolinic acid ratio, hold promise as peripheral biomarkers for early diagnosis and disease stratification. Finally, we discuss the therapeutic potential of targeting KP enzymes or receptors for personalized intervention strategies, while acknowledging the challenges in translating these findings into clinical practice.

Objective To explore the relationship between systemic immune-inflammation index(SII),red blood cell distribution width(RDW),25-hydroxy-vitamin-D[25(OH)D]levels and frailty index in elderly pa-tients with type 2 diabetes mellitus(T2DM).Methods A total of 197 elderly patients with T2DM admitted to the hospital from March 2023 to March 2024 were collected as the research subjects.The patients were divided into the frailty group(106 cases)and the non-frailty group(91 cases)according to the scores of the clinical frailty scale.The clinical data and the levels of SII,RDW and 25(OH)D of the two groups were compared.Pearson correlation analysis was used to analyze the correlations between the levels of SII,RDW and 25(OH)D and the frailty index of elderly patients with T2DM.Logistic regression was used to analyze the influencing factors of frailty in elderly patients with T2DM.Results Compared with the non-frailty group,the proportion of women,the history of falls within 1 year,and the age of the frailty group increased,while the body mass in-dex and the proportion of men decreased,and the differences were statistically significant(P＜0.05).The SII and RDW levels in the non-frailty group were lower than those in the frailty group,and the 25(OH)D level was higher than that in the frailty group,and the differences were statistically significant(P＜0.05).Pearson correlation analysis showed that SII and RDW levels were positively correlated with frailty index,and 25(OH)D level was negatively correlated with frailty index in elderly T2DM patients(P＜0.05).Logistic regression analysis showed that female,age ≥ 74.25 years old,SII≥ 938.36,RDW≥ 15.19％,and 25(OH)D≥48.42 nmol/L were independent risk factors for frailty in elderly T2DM patients(P＜0.05).Conclusion The levels of SII,RDW and 25(OH)D in elderly patients with T2DM are related to the frailty index.

With the rapid development of artificial intelligence and machine learning algorithms in the med-ical field,as well as the high-quality development requirements put forward by the state for hospitals and vari-ous departments,the development of laboratory medicine shows a new trend.The development of clinical labo-ratory has evolved from the initial test suite to the test pathway based on clinical pathway and diagnosis-relat-ed groups payment,and then to clinical laboratory omics.Clinical laboratory omics refers to the use of high-throughput methods to obtain a large number of laboratory project results data.Combined with the clinical characteristics of patients,statistical methods and machine learning algorithms are commonly used to reveal the information behind a large number of medical data to assist clinicians in diagnosis and treatment.Clinical laboratory omics may be a new trend in the future development of laboratory medicine,and it is likely to play an important role in the field of laboratory medicine.

With reference to the Information and Documentation-Resource Description (GB/T 3792-2021) and Bibliographical Description for Ancient Chinese Books (GB/T 3792.7-2008) and other cataloging standards and rules, drawing on the practical experience of cataloging ancient TCM books, Bibliographical Cataloging for Ancient TCM Books was formulated. This standard specifies the entry items and their order of ancient TCM books, cataloging identifier, cataloging text, cataloging information source, and cataloging item details. The standard can provide standardized and unified guiding principles and methods for the work of ancient TCM books, and promote the sharing and utilization of ancient TCM books.