Natural products have shown great potential in the research and development of antitumor drugs. However， their clinical application is severely limited by inherent drawbacks such as poor water solubility， low stability， and low bioavailability. Cell membrane biomimetic nanoparticles， as a novel drug delivery system， have provided new strategies to overcome this bottleneck. This review systematically summarizes the preparation methods （e.g.， membrane extrusion， ultrasonic fusion， and microfluidic electroporation） and characterization techniques （e.g.， particle size， Zeta potential， and membrane surface protein detection） of cell membrane biomimetic nanoparticles， with a focus on the application of these derived from various sources in delivering antitumor natural products. Cell membrane biomimetic nanoparticles are endowed with unique biological functions， including low immunogenicity conferred by stem cell membranes， prolonged systemic circulation enabled by red blood cell membranes， and homologous targeting facilitated by tumor cell membranes. Despite these advancements， the technology still faces challenges such as difficulties in large-scale production， high costs， and limited characterization methods. Future research needs to further optimize the relevant processes to promote the clinical translation of cell membrane-biomimetic nanoparticles， thereby offering an efficient and safe novel delivery approach for antitumor therapy using natural products.

Objective To explore the characteristics and correlation between perivascular spaces (PVS) and diffusion tensor image analysis along perivascular spaces (DTI-ALPS) index in patients with amnestic mild cognitive impairment (aMCI). Methods A retrospective study was conducted on a total of 118 participants, including cognitive normal (CN) healthy controls and aMCI patients, recruited from the Department of Neurology, Zhongshan Hospital, Fudan University from September 2020 to September 2022. All participants underwent structural magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI). An automatic segmentation algorithm was used to quantify PVS metrics in the brain, and DTI-ALPS index was calculated based on DTI. Differences in DTI-ALPS index and PVS metrics between the CN and aMCI groups were compared. Multivariate logistic regression was used to identify independent factors influencing aMCI. Correlation analysis was performed to assess relationships among DTI-ALPS index, PVS metrics, and cognitive scores. Results A total of 80 CN healthy controls and 38 aMCI patients were included. The DTI-ALPS index was significantly lower in the aMCI group compared with the CN group (1.28±0.18 vs 1.37±0.21, P＝0.018), while differences in PVS metrics between groups were not statistically significant. Multivariate logistic regression analysis indicated that DTI-ALPS index was an independent factor affecting aMCI (OR＝0.097, 95%CI 0.011–0.833, P＝0.033). Correlation analysis revealed a positive relationship between DTI-ALPS index and MMSE score (r＝0.210, P＝0.023) as well as PVS length in the centrum semiovale (r＝0.216, P＝0.019). Conclusions The DTI-ALPS index may serve as an imaging biomarker for identifying early cognitive impairment, and patients with aMCI exhibit abnormal DTI-ALPS indices, suggesting that brain glymphatic system dysfunction may occur prior to morphological changes.

Objective To explore the safety and feasibility of 5G remote robot-assisted thoracoscopic anatomic lobectomy and segmentectomy. Methods A retrospective analysis was conducted on patients who underwent 5G remote robot-assisted thoracoscopic anatomic lobectomy or segmentectomy between July and September 2024. The surgeries were performed collaboratively by Shanghai Chest Hospital, Affiliated Hospital of Yangzhou University, and The First Affiliated Hospital of Nanchang University. Perioperative outcomes were recorded and analyzed. Results Ten patients were included, comprising 4 anatomic lobectomies and 6 segmentectomies. The median age was 61.0 (56.0, 72.0) years. The median intraoperative bi-directional network latency was 52.5 (39.0, 54.0) ms. There were no instances of network interruption, robot-related adverse events, or conversions to open thoracotomy. The median postoperative chest tube drainage volume was 500.0 (375.0, 600.0) mL, and the median hospital stay was 5.5 (4.0, 6.0) days. No complications of Clavien-Dindo grade Ⅱor higher occurred. All patients were recurrence-free and alive during the 6-month postoperative follow-up period. Conclusion 5G remote robot-assisted thoracoscopic surgery demonstrates high safety and operational stability. This technology shows promising potential for clinical application and is worthy of further development and utilization.

Objective: To construct a prediction model for sleep disorders in shift workers of a chemical fiber enterprise, so as to provide the basis for early identification and prevention of sleep disorders in shift workers. Methods: Shift workers were sampled from a chemical fiber enterprise in Tongxiang City, Zhejiang Province using a cluster sampling method from August 2022 to July 2024. Demographic information, length of service and average weekly working hours were collected through questionnaire surveys. Depressive symptoms, anxiety symptoms and sleep disorders were evaluated using the Pittsburgh Sleep Quality Index, Patient Health Questionnaire and Generalized Anxiety Disorder Questionnaire, respectively. The shift workers were randomly divided into a training set and a validation set at a ratio of 7∶3. Predictive factors were selected using a multivariable logistic regression model based on the training set, and a nomograph model for prediction of sleep disorders in shift workers was established. The predictive values of the model were evaluated using the receiver operating characteristic (ROC) curve and calibration curve based on the training set and validation set. Results: Totally 673 shift workers were included, with a median age of 32 (interquartile range, 12) years. There were 493 males, accounting for 73.25%. There were 471 (69.99%) workers in the training set and 202 (30.01%) workers in the validation set. There were 274 workers with sleep disorders, accounting for 40.71%. The equation for the prediction model was ln[p/(1-p)]=-8.391+1.906×average weekly working hours+1.822×depressive symptoms+1.667×anxiety symptoms. The area under the ROC curve was 0.769 (95%CI: 0.661-0.835) for the training set and 0.655 (95%CI: 0.593-0.737) for the validation set, and Hosmer-Lemeshow test showed a good fitting effect (both P>0.05). Conclusion The nomograph model constructed by average weekly working hours, depressive symptoms and anxiety symptoms can be used to predict the risk of sleep disorders in shift workers of a chemical fiber enterprise.

Objective To analyze the underestimated influencing factors of ductal carcinoma in situ(DCIS)detected by ultrasound-guided fine needle aspiration cytology(US-FNAC),and to construct and validate the nomogram prediction model.Methods A total of 105 patients with DCIS diagnosed by US-FNAC in Yixing Hospital of Traditional Chinese Medicine from January 2020 to June 2023 were retrospectively selected.All patients were female and aged 40-76 years.According to postoperative pathological results,they were assigned to underestimated group(n=27)and non-underestimated group(n=78).The clinical data of the patients were collected to analyze the influencing factors of the underestimation of DCIS,and a nomogram prediction model was constructed.The receiver operating characteristic curve(ROC)was drawn,and the area under the curve(AUC)was used to analyze the predictive efficacy of the prediction model for the underestimated risk of DCIS before operation.Results Univariate analysis showed that the proportions of palpable masses,tumor size>2 cm,microcalcification,and breast imaging reporting and data system(BI-RADS)4B-5 in the underestimated group were higher than those in the non-underestimated group(P<0.05).Binary logistic regression analysis showed that tumor size[(odds ratio,OR)=4.453,95%(confidence interval,C I):1.890-10.486],microcalcification(OR=3.079,95%CI:1.650-5.742),BI-RADS classification(OR=5.211,95%CI:2.528-10.740)were the independent risk factors for preoperative underestimation of DCIS(P<0.05).Internal validation of the nomogram prediction model based on the above factors showed that the C-index was 0.865(95%CI:0.785-0.952),and the correction curve for predicting the underestimation of DCIS was close to the ideal curve(P>0.05).ROC curve showed that the nomogram model had a sensitivity of 87.90%,a specificity of 88.60%,and an AUC of 0.895(95%CI:0.823-0.966).Conclusion Tumor size,microcalcification and BI-RADS classification are independent risk factors for preoperative underestimation of DCIS.The nomogram prediction model based on these factors can better evaluate the risk of preoperative underestimation of DCIS.

Traditional experimental methods are insufficient in the study of layered double hydroxides (LDHs) supramolecular structure and hydration expansion performance, and information on interlayer anionic arrangement and structural water molecules cannot be obtained. Aspartic acid intercalated magnesium aluminum hydrotalcite was synthesized using coprecipitation and ion exchange. The structure of hydrotalcite precursor and its aspartic acid composite materials was characterized by X-ray powder diffraction, differential thermal analysis, and infrared spectroscopy, and Materials Studio software was used to simulate the molecular dynamics of microstructure and hydration properties of LDHs intercalated with the aspartic acid drug. The prepared composite material had a regular layered structure and a single crystal phase. After intercalation with aspartic acid, the interlayer spacing increased from 0.84 nm to 1.13−1.17 nm; after intercalation, the thermal decomposition temperature of aspartic acid increased from 249 °C to 334 °C, greatly improving its thermal stability. The interlayer spacing of the intercalated hydrotalcite obtained from the experiment was close to the molecular dynamics simulation results when Nw=3−4. As more water molecules were inserted between the layers, the greater the interlayer distance became. Hydration energy increased gradually and tended to a certain value. The total number of hydrogen bonds increased gradually, the hydrogen bonds between laminates and anions decreased gradually, but the hydrogen bonds between laminates and water molecules increased gradually. The simulation results are close to the experimental results, which can lay a foundation for the design and synthesis of LDHs-based drug composites.

ObjectiveTraditional Chinese medicine (TCM) constitutes a valuable cultural heritage and an important source of antitumor compounds. Poria (Poria cocos (Schw.) Wolf), the dried sclerotium of a polyporaceae fungus, was first documented in Shennong’s Classic of Materia Medica and has been used therapeutically and dietarily in China for millennia. Traditionally recognized for its diuretic, spleen-tonifying, and sedative properties, modern pharmacological studies confirm that Poria exhibits antioxidant, anti-inflammatory, antibacterial, and antitumor activities. Pachymic acid (PA; a triterpenoid with the chemical structure 3β-acetyloxy-16α-hydroxy-lanosta-8,24(31)-dien-21-oic acid), isolated from Poria, is a principal bioactive constituent. Emerging evidence indicates PA exerts antitumor effects through multiple mechanisms, though these remain incompletely characterized. Neuroblastoma (NB), a highly malignant pediatric extracranial solid tumor accounting for 15% of childhood cancer deaths, urgently requires safer therapeutics due to the limitations of current treatments. Although PA shows multi-mechanistic antitumor potential, its efficacy against NB remains uncharacterized. This study systematically investigated the potential molecular targets and mechanisms underlying the anti-NB effects of PA by integrating network pharmacology-based target prediction with experimental validation of multi-target interactions through molecular docking, dynamic simulations, and in vitro assays, aimed to establish a novel perspective on PA’s antitumor activity and explore its potential clinical implications for NB treatment by integrating computational predictions with biological assays. MethodsThis study employed network pharmacology to identify potential targets of PA in NB, followed by validation using molecular docking, molecular dynamics (MD) simulations, MM/PBSA free energy analysis, RT-qPCR and Western blot experiments. Network pharmacology analysis included target screening via TCMSP, GeneCards, DisGeNET, SwissTargetPrediction, SuperPred, and PharmMapper. Subsequently, potential targets were predicted by intersecting the results from these databases via Venn analysis. Following target prediction, topological analysis was performed to identify key targets using Cytoscape software. Molecular docking was conducted using AutoDock Vina, with the binding pocket defined based on crystal structures. MD simulations were performed for 100 ns using GROMACS, and RMSD, RMSF, SASA, and hydrogen bonding dynamics were analyzed. MM/PBSA calculations were carried out to estimate the binding free energy of each protein-ligand complex. In vitro validation included RT-qPCR and Western blot, with GAPDH used as an internal control. ResultsThe CCK-8 assay demonstrated a concentration-dependent inhibitory effect of PA on NB cell viability. GO analysis suggested that the anti-NB activity of PA might involve cellular response to chemical stress, vesicle lumen, and protein tyrosine kinase activity. KEGG pathway enrichment analysis suggested that the anti-NB activity of PA might involve the PI3K/AKT, MAPK, and Ras signaling pathways. Molecular docking and MD simulations revealed stable binding interactions between PA and the core target proteins AKT1, EGFR, SRC, and HSP90AA1. RT-qPCR and Western blot analyses further confirmed that PA treatment significantly decreased the mRNA and protein expression of AKT1, EGFR, and SRC while increasing the HSP90AA1 mRNA and protein levels. ConclusionIt was suggested that PA may exert its anti-NB effects by inhibiting AKT1, EGFR, and SRC expression, potentially modulating the PI3K/AKT signaling pathway. These findings provide crucial evidence supporting PA’s development as a therapeutic candidate for NB.

Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by progressive cognitive decline, functional impairment, and neuropsychiatric symptoms. It represents the most prevalent form of dementia among the elderly population. Accumulating evidence indicates that oxidative stress plays a pivotal role in the pathogenesis of AD. Notably, elevated levels of oxidative stress have been observed in the brains of AD patients, where excessive reactive oxygen species (ROS) can cause extensive damage to lipids, proteins, and DNA, ultimately compromising neuronal structure and function. Amyloid β‑protein (Aβ) has been shown to induce mitochondrial dysfunction and calcium overload, thereby promoting the generation of ROS. This, in turn, exacerbates Aβ aggregation and enhances tau phosphorylation, leading to the formation of two pathological features of AD: extracellular Aβ plaque deposition and intracellular neurofibrillary tangles (NFTs). These events ultimately culminate in neuronal death, forming a vicious cycle. The interplay between oxidative stress and these pathological processes constitutes a core link in the pathogenesis of AD. The signaling pathways mediating oxidative stress in AD include Nrf2, RCAN1, PP2A, CREB, Notch1, NF‑κB, ApoE, and ferroptosis. Nrf2 signaling pathway serves as a key regulator of cellular redox homeostasis, exerts important antioxidant capacity and protective effects in AD. RCAN1 signaling pathway, as a calcineurin inhibitor, and modulates AD progression through multiple mechanisms. PP2A signaling pathway is involved in regulating tau phosphorylation and neuroinflammation processes. CREB signaling pathway contributes to neuroplasticity and memory formation; activation of CREB improves cognitive function and reduce oxidative stress. Notch1 signaling pathway regulates neuronal development and memory, participates in modulation of Aβ production, and interacts with Nrf2 toco-regulate antioxidant activity. NF‑κB signaling pathway governs immune and inflammatory responses; sustained activation of this pathway forms “inflammatory memory”, thereby exacerbating AD pathology. ApoE signaling pathway is associated with lipid metabolism; among its isoforms, ApoE-ε4 significantly increases the risk of AD, leading to elevated oxidative stress, abnormal lipid metabolism, and neuroinflammation. The ferroptosis signaling pathway is driven by iron-dependent lipid peroxidation, and the subsequent release of lipid peroxidation products and ROS exacerbate oxidative stress and neuronal damage. These interconnected pathways form a complex regulatory network that regulates the progression of AD through oxidative stress and related pathological cascades. In terms of therapeutic strategies targeting oxidative stress, among the drugs currently used in clinical practice for AD treatment, memantine and donepezil demonstrate significant therapeutic efficacy and can improve the level of oxidative stress in AD patients. Some compounds with antioxidant effects (such asα-lipoic acid and melatonin) have shown certain potential in AD treatment research and can be used as dietary supplements to ameliorate AD symptoms. In addition, non-drug interventions such as calorie restriction and exercise have been proven to exerted neuroprotective effects and have a positive effect on the treatment of AD. By comprehensively utilizing the therapeutic characteristics of different signaling pathways, it is expected that more comprehensive multi-target combination therapy regimens and combined nanomolecular delivery systems will be developed in the future to bypass the blood-brain barrier, providing more effective therapeutic strategies for AD.

Objective To investigate the clinical manifestations of traditional Chinese medicine(TCM)and their associations with TCM constitutions in individuals who have migrated to plateau areas,and to provide a scientific basis for plateau health management.Methods Migrants living in areas above 3000 m were selected as research subjects.Data were collected by using TCM symptom assessment scales and constitution assessment scales.Descriptive statistical analysis was conducted to determine the incidence and severity of symptoms among individuals with different migration durations,and core symptoms were identified.Factor analysis was performed by using SPSS software to extract symptom clusters and explore the correlation between core symptoms and TCM constitutions.Results Among individuals who migrated to plateau areas,the incidence of discomfort symptoms was 83.44％.The five most common symptoms were dry skin(67.94％),forgetfulness(56.03％),dry mouth(52.06％),yellow urine(48.73％),and insomnia(47.14％).In the top 10 symptoms with the highest increase in incidence,yellow urine(33.51％)and forgetfulness(26.33％)were both present in the top 10 symptoms across different migration durations.Factor analysis extracted 5,2,4,and 6 symptom clusters from the overall population,individuals who migrated within 1 year,those who migrated for 1-2 years,and those who migrated over 2 years,respectively.Qi-deficiency constitution(QDC),blood stasis constitution(BSC),qi stagnation constitution(QSC),phlegm-dampness constitution(PDC),and dampness-heat constitution(DHC)were significantly positively correlated with forgetfulness.Conclusion Migrating to plateau areas can induce discomfort symptoms,and both the number and incidence of symptoms increase with longer migration durations.The number and incidence of high-frequency symptoms(incidence≥30％)increase with prolonged migration time.There are differences in the composition and severity of symptom clusters across different migration durations.QDC,BSC,QSC,PDC,and DHC are closely related to forgetfulness and can be considered risk constitutions for forgetfulness.Timely attention to changes in symptom clusters and constitutions can help prevent and mitigate the occurrence and development of symptoms.

G protein-coupled receptors(GPCRs)are the largest family of membrane proteins in eukaryotes,with nearly 800 genes coding for these proteins.They are involved in many physiological processes,such as light perception,taste and smell,neurotransmitter,metabolism,endocrine and exocrine,cell growth and migration.Importantly,GPCRs and their ligands are the targets of approximately one third of all mar-keted drugs.GPCRs are traditionally known for their role in transmitting signals from the extracellular environment to the cell's interior via the plasma membrane.However,emerging evidence suggests that GPCRs are also localized on mitochondria,where they play critical roles in modulating mitochondrial functions.These mitochondrial GPCRs(mGPCRs)can influence processes such as mitochondrial respi-ration,apoptosis,and reactive oxygen species(ROS)production.By interacting with mitochondrial signaling pathways,mGPCRs contribute to the regulation of energy metabolism and cell survival.Their presence on mitochondria adds a new layer of complexity to the understanding of cellular signaling,highlighting the organelle's role as not just an energy powerhouse but also a crucial hub for signal transduction.This expanding understanding of mGPCR function on mitochondria opens new avenues for research,particularly in the context of diseases where mitochondrial dysfunction plays a key role.Ab-normalities in the phase conductance pathway of GPCRs located on mitochondria are closely associated with the development of systemic diseases such as cardiovascular disease,diabetes,obesity and Alz-heimer's disease.In this review,we examined the various types of GPCRs identified on mitochondrial membranes and analyzed the complex relationships between mGPCRs and the pathogenesis of various diseases.We aim to provide a clearer understanding of the emerging significance of mGPCRs in health and disease,and to underscore their potential as therapeutic targets in the treatment of these conditions.