The construction of a training system for visiting physicians in the department of rare diseases in China is an important measure to improve the overall diagnosis and treatment capacity for rare diseases and address the critical challenge of insufficient knowledge and skills among clinicians in practice. This article systematically describes the visiting physician training system established by the Department of Rare Diseases at Peking Union Medical College Hospital. It summarizes the training objectives and positioning, design logic, and learning modules of the system, aiming to provide a reference for the construction of the specialized talent team for rare diseases in China.

Gorham-Stout disease(GSD) is a rare osteolytic disorder characterized by spontaneous and progressive osteolysis, along with abnormal angiogenesis and lymphangiogenesis, with no new bone formation. We present a case of a 15-year-old female admitted due to " recurrent right leg pain for 5 years, 11 months after undergoing right femoral fracture surgery". Through comprehensive integration of the patient's clinical phenotype, laboratory tests, imaging findings, pathological examinations, and molecular biological test results, GSD was considered highly likely. A multidisciplinary treatment approach was conducted, including a combination of zoledronic acid and sirolimus to inhibit osteolysis, along with rehabilitation training and orthopedic intervention, providing a personalized and comprehensive treatment strategy.

ObjectiveTo investigate the effects of metformin on the immune functions of immature dendritic cells （imDCs） and the underlying mechanisms. MethodsMouse bone marrow-derived imDCs were treated with different concentrations of metformin. The working concentration and treatment time of metformin in this study were determined based on the results of cell apoptosis and cell viability assays. The effects of metformin on the phagocytic capacity of imDCs was evaluated using an antigen endocytosis assay. The expression of cluster of differentiation 205 （CD205）， the polymerization of filamentous actin （F-actin）， and the underlying regulatory mechanisms were investigated through flow cytometry， laser confocal fluorescence microscopy， and Western blot. ResultsThe working concentrations of metformin were 1， 2， 4 mmol/L for 24 h determined by the apoptosis and cell viability assays.Metformin significantly suppressed the phagocytic capacity of imDCs， down-regulated the expression of the mannose receptor CD205 on the cell surface， which was closely associated with phagocytic function； metformin inhibited the RhoA-ROCK1-LIMK1-Cofilin signaling pathway， which inhibited the polymerization of F-actin and disturbed its dynamic remodeling of imDCs. ConclusionMetformin can inhibit the expression of CD205 and disrupt the remodeling of F-actin， thereby suppressing the antigen-capturing capacity of imDCs.

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.

Objective In order to understand the current resistance status of Aedes albopictus(Ae. albopictus) adult population to commonly used insecticides and the resistance dynamics development in Zhejiang Province and provide a theoretical basis for the scientific and rational use of hygienic insecticides. Methods Resistance determination was carried out using the diagnostic dose method(GB/T 26347-2010)recommended by WHO in the adult mosquito contact cylinder method to monitor the resistance of Ae. albopictus field populations in 11 cities and districts in Zhejiang Province in 2024. Results The monitoring result showed that adult Ae. albopictus in 11 areas were resistant or suspected resistant populations to both cis-cypermethrin and permethrin; suspected and resistant populations to the organophosphate insecticide malathion were as high as 81.82%; while suspected resistance to the carbamate insecticide residual carbofuran accounted for 45.45%, and the rest of the monitoring sites were sensitive to it. Conclusions The result suggest that the generalized resistance of Ae. albopictus populations to pyrethroids and organophosphorus insecticides in the field in Zhejiang Province needs to be highly emphasized. In future mosquito vector and mosquito-borne disease control, insecticides should be selected based on the resistance monitoring information, while following scientific guidelines for insecticide use.

Circadian rhythm is an endogenous biological clock mechanism that enables organisms to adapt to the earth’s alternation of day and night. It plays a fundamental role in regulating physiological functions and behavioral patterns, such as sleep, feeding, hormone levels and body temperature. By aligning these processes with environmental changes, circadian rhythm plays a pivotal role in maintaining homeostasis and promoting optimal health. However, modern lifestyles, characterized by irregular work schedules and pervasive exposure to artificial light, have disrupted these rhythms for many individuals. Such disruptions have been linked to a variety of health problems, including sleep disorders, metabolic syndromes, cardiovascular diseases, and immune dysfunction, underscoring the critical role of circadian rhythm in human health. Among the numerous systems influenced by circadian rhythm, the skin—a multifunctional organ and the largest by surface area—is particularly noteworthy. As the body’s first line of defense against environmental insults such as UV radiation, pollutants, and pathogens, the skin is highly affected by changes in circadian rhythm. Circadian rhythm regulates multiple skin-related processes, including cyclic changes in cell proliferation, differentiation, and apoptosis, as well as DNA repair mechanisms and antioxidant defenses. For instance, studies have shown that keratinocyte proliferation peaks during the night, coinciding with reduced environmental stress, while DNA repair mechanisms are most active during the day to counteract UV-induced damage. This temporal coordination highlights the critical role of circadian rhythms in preserving skin integrity and function. Beyond maintaining homeostasis, circadian rhythm is also pivotal in the skin’s repair and regeneration processes following injury. Skin regeneration is a complex, multi-stage process involving hemostasis, inflammation, proliferation, and remodeling, all of which are influenced by circadian regulation. Key cellular activities, such as fibroblast migration, keratinocyte activation, and extracellular matrix remodeling, are modulated by the circadian clock, ensuring that repair processes occur with optimal efficiency. Additionally, circadian rhythm regulates the secretion of cytokines and growth factors, which are critical for coordinating cellular communication and orchestrating tissue regeneration. Disruptions to these rhythms can impair the repair process, leading to delayed wound healing, increased scarring, or chronic inflammatory conditions. The aim of this review is to synthesize recent information on the interactions between circadian rhythms and skin physiology, with a particular focus on skin tissue repair and regeneration. Molecular mechanisms of circadian regulation in skin cells, including the role of core clock genes such as Clock, Bmal1, Per and Cry. These genes control the expression of downstream effectors involved in cell cycle regulation, DNA repair, oxidative stress response and inflammatory pathways. By understanding how these mechanisms operate in healthy and diseased states, we can discover new insights into the temporal dynamics of skin regeneration. In addition, by exploring the therapeutic potential of circadian biology in enhancing skin repair and regeneration, strategies such as topical medications that can be applied in a time-limited manner, phototherapy that is synchronized with circadian rhythms, and pharmacological modulation of clock genes are expected to optimize clinical outcomes. Interventions based on the skin’s natural rhythms can provide a personalized and efficient approach to promote skin regeneration and recovery. This review not only introduces the important role of circadian rhythms in skin biology, but also provides a new idea for future innovative therapies and regenerative medicine based on circadian rhythms.

ObjectiveThis study aims to develop and validate a novel multimodal predictive model， termed criss-cross network（CCNet）-directed graph neural network（DGNN）（CGN）， for accurate assessment of pulmonary nodule progression in high-risk individuals for lung cancer， by integrating longitudinal chest computed tomography（CT） imaging with both traditional Chinese and western clinical evaluation data. MethodsA cohort of 4 432 patients with pulmonary nodules was retrospectively analyzed. A twin CCNet was employed to extract spatiotemporal representations from paired sequential CT scans. Structured clinical assessment and imaging-derived features were encoded via a multilayer perceptron， and a similarity-based alignment strategy was adopted to harmonize multimodal imaging features across temporal dimensions. Subsequently， a DGNN was constructed to integrate heterogeneous features， where nodes represented modality-specific embeddings and edges denoted inter-modal information flow. Finally， model optimization was performed using a joint loss function combining cross-entropy and cosine similarity loss， facilitating robust classification of nodule progression status. ResultsThe proposed CGN model demonstrated superior predictive performance on the held-out test set， achieving an area under the receiver operating characteristic curve（AUC） of 0.830， accuracy of 0.843， sensitivity of 0.657， specificity of 0.712， Cohen's Kappa of 0.417， and F₁ score of 0.544. Compared with unimodal baselines， the CGN model yielded a 36%-48% relative improvement in AUC. Ablation studies revealed a 2%-22% increase in AUC when compared to simplified architectures lacking key components， substantiating the efficacy of the proposed multimodal fusion strategy and modular design. Incorporation of traditional Chinese medicine （TCM）-specific symptomatology led to an additional 5% improvement in AUC， underscoring the complementary value of integrating TCM and western clinical data. Through gradient-weighted activation mapping visualization analysis， it was found that the model's attention predominantly focused on nodule regions and effectively captured dynamic associations between clinical data and imaging-derived features. ConclusionThe CGN model， by synergistically combining cross-attention encoding with directed graph-based feature integration， enables effective alignment and fusion of heterogeneous multimodal data. The incorporation of both TCM and western clinical information facilitates complementary feature enrichment， thereby enhancing predictive accuracy for pulmonary nodule progression. This approach holds significant potential for supporting intelligent risk stratification and personalized surveillance strategies in lung cancer prevention.

Drug impurity control is essential for ensuring pharmaceutical quality.In this study,an unknown impurity at relative retention time(RRT)of 0.45 in Torasemide injection was systematically investigated using high performance liquid chromatography-ion trap time-of-flight mass spectrometry(LC-IT-TOF-MS/MS),forced degradation studies,and nuclear magnetic resonance(NMR)spectroscopy,aiming to elucidate its chemical structure,propose a formation mechanism,and establish a control strategy.By analysis of the ultraviolet absorption spectrum and high-resolution MS1 and MS2 data of the impurity,its possible structure was postulated.Subsequently,the target impurity was prepared via forced degradation experiment,and its structure was confirmed by NMR spectroscopy.A detailed analysis of its formation mechanism revealed that Torasemide first hydrolyzed in solution to form Torasemide sulfonamide,and then underwent condensation,dehydration,and cyclization reactions with trace amounts of formaldehyde in the excipient polyethylene glycol(PEG)400 to generate the impurity.It was experimentally proven that the target impurity was related to the residual oxygen content in Torasemide injection.Ultimately,by optimizing the prescription process,the target impurity level was controlled below the individual impurity limit of the final product(≤0.3%).This study provided valuable insights for enhancing the quality control of Torasemide injection.

Objective:To investigate the status of psychological distress, self-compassion, and self-management behaviors among patients with type 2 diabetes mellitus (T2DM), and explore the mediating role of self-compassion in the relationship between diabetes distress and self-management behaviors, and to provide a theoretical basis for the psychological intervention of patients with T2DM.Methods:A convenience sampling method was adopted to select 221 patients with T2DM hospitalized in the Department of Endocrinology and Metabolism, the First Hospital of China Medical University from November 2023 to April 2024. The General Information Form, the Diabetes Distress Scale-17, the Self-Compassion Scale and the Summary of Diabetes Self-Care Activity were utilized for investigation. A structural equation model was constructed with AMOS 24.0 to analyze the relationships among psychological distress, self-compassion, and self-management behaviors, and the mediating effect of self-compassion was tested using the Bootstrap method.Results:A total of 221 patients with T2DM were included, including 138 males and 83 females, aged (54.52 ±10.42) years old. The total score of psychological distress of patients with T2DM was (34.55 ± 18.82) points, the total score of self-compassion was (94.22 ± 26.04) points, and the total score of self-management behavior was (40.81 ± 22.64) points. Psychological distress in T2DM patients was significantly negatively correlated with both self-compassion ( r=-0.850, P<0.01) and self-management behaviors ( r=-0.736, P<0.01). In contrast, self-compassion was significantly positively correlated with self-management behaviors ( r=0.743, P<0.01). Self-compassion partially mediated the relationship between diabetes-related psychological distress and self-management behaviors, with a mediation effect size of -0.456. Conclusions:Psychological distress among T2DM patients is at a moderate level, and their self-management behaviors require urgent improvement. Psychological distress not only directly impacts self-management behaviors but also indirectly influences them through self-compassion. Healthcare professionals should prioritize enhancing patients′ self-compassion levels to mitigate the negative effects of psychological distress on their health behaviors.

Aim To investigate the effect of triptolide(TP)on corticosterone(CORT)-induced depression-like behaviors in mice and explore the antidepressant mechanism of TP based on the CREB/BDNF/TrkB sig-naling pathway.Methods Sixty 8-week-old male C57BL/6J mice were randomly divided into five groups:control group,CORT group,TP groups of low and high doses(10,30 μg·kg-1),and fluoxetine(FLU)group(10 mg·kg-1).Except for the control group,the other groups received subcutaneous injec-tions of CORT for three consecutive weeks to establish the model of depression.During the last two weeks of modeling,normal saline,TP and FLU were adminis-tered via intraperitoneal injection respectively.After the administration,depression-like behaviors in mice were assessed using forced swimming test,tail suspen-sion test,and sucrose preference test.Biochemical methods were used to measure the levels of SOD and MDA in the hippocampus and prefrontal cortex(PFC).Cell apoptosis was detected by TUNEL meth-od.Immunohistochemistry,immunofluorescence,and Western blotting were employed to detect the expres-sion of apoptosis/autophagy-related proteins,synaptic structure markers,and proteins related to the CREB/BDNF/TrkB signaling pathway.Results TP signifi-cantly ameliorated CORT-induced depression-like be-haviors in mice,mainly manifested by reduced immo-bility time in the tail suspension test and forced swim-ming test,and increased sucrose preference rate.TP alleviated CORT-induced oxidative stress by increasing SOD levels and reducing MDA production in brain tis-sue.Additionally,TP also inhibited apoptosis and ex-cessive autophagy of neurons in the hippocampus and prefrontal cortex,maintained synaptic plasticity,and significantly upregulated the expression of p-CREB,BDNF,and TrkB.Conclusions TP exhibits potential antidepressant effect in mice by upregulating the CREB/BDNF/TrkB signaling pathway,reducing oxida-tive stress,inhibiting excessive neuronal apoptosis and autophagy,and improving synaptic plasticity.