Objective:To develop fluorescent nanoprobes with aggregation-induced emission characteristics and to systematically evaluate their optical properties, biosafety, anti-tumor activity, and imaging capability, thereby assessing their potential for early precision diagnosis and treatment of oral cancer in mice.Methods:Control probes (PEG@TPD) were prepared by encapsulating ( E)-4-(2-(4′-(1-phenyl-2,2-bis(4-methoxyphenyl)vinyl)biphenyl-4-yl)vinyl)-4-(dicyanomethylene)-4 H-chromene (TPD) using 1,2-distearoyl- SN-glycerol-3-phosphoethanolamine- N-polyethylene glycol 2000-maleimide as the carrier. Fluorescent nanoprobes (GE11-PEG@TPD) were subsequently fabricated by surface modification with the targeting GE11 peptide. The morphology and particle size of the nanoprobes were characterized by transmission electron microscopy and dynamic light scattering. The optical properties of the nanoprobes were analyzed using ultraviolet-visible spectrophotometry and fluorescence spectrophotometry. Mouse squamous carcinoma SCC-7 cells were randomly divided into six groups by the random number table method. The PBS, PEG@TPD, and GE11-PEG@TPD groups were not treated with light, while the PBS+L, PEG@TPD+L, and GE11-PEG@TPD+L groups were exposed to white light (25 W/cm 2, 10 min) at a nanoprobe concentration of 20 μg/ml (based on TPD concentration). Cell survival rate was assessed by the cell counting kit-8 assay. Cellular uptake, intracellular reactive oxygen species levels, and cytotoxicity were evaluated using laser scanning confocal microscopy. The apoptosis rate was evaluated by cell apoptosis assay. Twelve 6-week-old female C3H/HeN mice were randomly divided into two groups: PEG@TPD-1 group and GE11-PEG@TPD-1 group, with 6 mice in each group. Subcutaneous oral cancer models were established by injecting SCC-7 cell suspensions into the dorsal region of mice in two groups. Each mouse was intravenously administered 200 μl of PEG@TPD or GE11-PEG@TPD solution (1 mg/ml, based on TPD concentration). Tumor boundaries and scope were visualized using a small animal in vivo imaging system. At the optimal imaging time point, three mice from each group were euthanized, and major organs and tumor tissues were collected to measure probe accumulation. Statistical comparisons between two groups were performed using independent samples t-tests, while one-way or two-way analysis of variance was applied for multiple group comparisons. Results:Both PEG@TPD and GE11-PEG@TPD exhibited a relatively regular sphere, with average particle sizes of (92.76±8.80 and 117.50±6.40) nm, respectively. PEG@TPD showed two obvious absorption peaks at 352 and 444 nm. GE11 peptide showed a polypeptide characteristic absorption peak at 280 nm, GE11-PEG@TPD showed three characteristic absorption peaks at 280, 352 and 444 nm. Under dark conditions, cell survival rate remained above 80% even at a concentration of 160 μg/ml. After light irradiation, cell survival rate in the PEG@TPD+L group at 20 and 40 μg/ml [(68.2±5.2)% and (48.6±7.1)%] were higher than those in the GE11-PEG@TPD+L group [(55.0±2.8)% and (30.0±9.2)%], with statistically significant differences ( P<0.05, 0.01). At incubation time points of 2, 4, and 6 h, the relative fluorescence intensity of the GE11-PEG@TPD group (119.4±10.2, 192.9±14.2, and 234.1±4.8) were higher than those of the PEG@TPD group (98.6±7.5, 163.8±3.1, 204.6±11.2), with statistically significant differences (all P<0.05). The relative fluorescence intensity of the PEG@TPD+L and GE11-PEG@TPD+L group (68.5±4.7 and 86.8±10.0) were higher than those in the PBS, PEG@TPD, GE11-PEG@TPD, and PBS+L groups (6.1±8.0, 7.6±1.8, 4.7±4.2 and 21.1±7.6), with statistically significant differences (all P<0.01). And the difference between the GE11-PEG@TPD+L and PEG@TPD+L groups was also statistically significant ( P<0.05). Viable cell proportions in the PBS, PEG@TPD, GE11-PEG@TPD, and PBS+L groups all exceeded 95.0%, while those in the PEG@TPD+L and GE11-PEG@TPD+L groups decreased to (11.1±3.7)% and (4.3±1.1)%, respectively, with a statistically significant difference between them ( P<0.05). The apoptotic cell proportions in the PEG@TPD+L and GE11-PEG@TPD+L groups [(40.5±4.3)% and (55.3±7.4)%] were higher than those in the PBS, PEG@TPD, GE11-PEG@TPD, and PBS+L groups [(27.3±2.0)%, (28.2±1.9)%, (28.6±1.2)%, and (29.7±3.0)%], with statistically significant differences ( P<0.05, 0.01). Moreover, the difference between the GE11-PEG@TPD+L and the PEG@TPD+L groups was also statistically significant ( P<0.01). The mean fluorescence intensities of the GE11-PEG@TPD-1 group at 1, 3, 5, 8, and 24 h, as well as in ex vivo tumor tissues[(5.2±0.8, 5.9±0.7, 6.6±1.0, 7.9±0.6, 7.8±0.7 and 20.6±3.5)×10 6 p/s/cm 2/sr] were all higher than those in the PEG@TPD-1 group [(3.2±0.7, 4.2±0.7, 4.6±0.9, 5.1±0.9, 4.7±0.9 and 14.2±1.8)×10 6 p/s/cm 2/sr], with statistically significant differences ( P<0.05, 0.01). Conclusions:The fluorescent nanoprobes exhibit uniform particle size, high photostability, and good biocompatibility. They demonstrate significant tumor-killing effects at the cellular level and possess tumor-targeting capability in vivo, showing promising application potential for the early precision diagnosis and treatment of oral cancer.

BACKGROUND: Durvalumab after chemoradiotherapy (CRT) failed to bring survival benefits to patients with epidermal growth factor receptor ( EGFR ) mutations in PACIFIC study (evaluating durvalumab in patients with stage III, unresectable NSCLC who did not have disease progression after concurrent chemoradiotherapy). We aimed to explore whether locally advanced inoperable patients with EGFR mutations benefit from tyrosine kinase inhibitors (TKIs) and the optimal treatment regimen. METHODS: We searched the PubMed, Embase, the Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov databases from inception to December 31, 2022 and performed a meta-analysis based on a Bayesian framework, with progression-free survival (PFS) and overall survival (OS) as the primary endpoints. RESULTS: A total of 1156 patients were identified in 16 studies that included 6 treatment measures, including CRT, CRT followed by durvalumab (CRT-Durva), TKI monotherapy, radiotherapy combined with TKI (RT-TKI), CRT combined with TKI (CRT-TKI), and TKI combined with durvalumab (TKI-Durva). The PFS of patients treated with TKI-containing regimens was significantly longer than that of patients treated with TKI-free regimens (hazard ratio [HR] = 0.37, 95% confidence interval [CI], 0.20-0.66). The PFS of TKI monotherapy was significantly longer than that of CRT (HR = 0.66, 95% CI, 0.50-0.87) but shorter than RT-TKI (HR = 1.78, 95% CI, 1.17-2.67). Furthermore, the PFS of RT-TKI or CRT-TKI were both significantly longer than that of CRT or CRT-Durva. RT-TKI ranked first in the Bayesian ranking, with the longest OS (60.8 months, 95% CI = 37.2-84.3 months) and the longest PFS (21.5 months, 95% CI, 15.4-27.5 months) in integrated analysis. CONCLUSIONS: For unresectable stage III EGFR mutant NSCLC, RT and TKI are both essential. Based on the current evidence, RT-TKI brings a superior survival advantage, while CRT-TKI needs further estimation. Large randomized clinical trials are urgently needed to explore the appropriate application sequences of TKI, radiotherapy, and chemotherapy. REGISTRATION PROSPERO; https://www.crd.york.ac.uk/PROSPERO/ ; No. CRD42022298490.
Humans ; Carcinoma, Non-Small-Cell Lung/therapy* ; ErbB Receptors/genetics* ; Lung Neoplasms/drug therapy* ; Mutation/genetics* ; Protein Kinase Inhibitors/therapeutic use* ; Chemoradiotherapy ; Antibodies, Monoclonal/therapeutic use*

The exoskeleton robot for lower limb medical rehabilitation in foreign countries and China was introduced in terms of the research status,structure and working principle,and analysis was carried out over its key technologies.It's pointed out the exoskeleton robot for lower limb medical rehabilitation would be enhanced in energy endurance,safety and comfort,individualized and intelligent control,modularity and lightweight design.[Chinese Medical Equipment Journal,2025,46(1):88-100]

The exoskeleton robot for lower limb medical rehabilitation in foreign countries and China was introduced in terms of the research status,structure and working principle,and analysis was carried out over its key technologies.It's pointed out the exoskeleton robot for lower limb medical rehabilitation would be enhanced in energy endurance,safety and comfort,individualized and intelligent control,modularity and lightweight design.[Chinese Medical Equipment Journal,2025,46(1):88-100]

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Objective:To evaluate the quality of critical patient handover practice between emergency room and intensive care unit (ICU) nurses, and to provide a basis for structured handover process.Methods:From March to July 2023, a total of 223 pairs of nurses in emergency room and ICU (including EICU) of 5 Class 3 Grade A general hospitals in Suzhou were selected as the research objects by using cross-sectional survey method and convenience sampling method. Self-designed general information questionnaire and Patient Handover Practice Quality Scale were used to investigate the included 223 pairs of nurses in emergency room and ICU on the current situation of handover time and quality.Results:A total of 211 pairs of nurses were included, including 286 females (67.8%) and 136 males (32.2%). The average age of emergency department nurses was (27.31 ± 2.17) years old, and ICU nurses was (26.96 ± 3.04) years old. The total scores of the patient handover practice Quality Scale for nurses in the emergency room and ICU were (45.25 ± 6.26) and (43.55 ± 7.19) points respectively, and the scores of the information transmission dimension were (20.47 ± 5.43) and (17.66 ± 3.45) points. The scores of common understanding dimension were (7.59 ± 2.31) and (8.58 ± 2.46) points. The scores of work atmosphere dimension were (7.93 ± 2.11) and (8.39 ± 2.29) points. The scores of handover situation dimension were (5.33 ± 1.30) and (5.70 ± 1.53) points, and the differences were statistically significant ( t values were - 6.35-4.22, all P<0.05). There were statistically significant differences in the scores of handover practice quality between emergency room nurses and ICU nurses according to specialization, education background, working years and job category ( t values were - 4.91-2.56, all P<0.05). Conclusions:Emergency room nurses and ICU nurses have different requirements and expectations for handover procedures, so it is necessary to build a structured handover practice framework and carry out personalized handover practice training, in order to achieve the consistency of handover content and improve the quality of critical patients handover practice.

Objective:To explore the medication safety issues caused by unreasonable sugar-to-fat ratio in clinical practice of parenteral nutrition,providing a basis for the rational use of clinical nutritional drugs.Methods:From the beginning of the database construction until February 28,2023,relevant databases at home and abroad were searched to summarize and analyze the clinical adverse outcomes caused by unreasonable sugar-to-fat ratio prescriptions encountered in the included literature and clinical practice.Results:Eleven articles were included,and 1 case of patient discomfort was improved by adjusting the unreasonable sugar-to-fat ratio.A total of 86 patients were involved,including 51 males and 35 females,with an age range of 18 to 89 years.Among the 86 patients,there were 79 clinical adverse outcomes,including 8 deaths.The incidence rates of clinical adverse outcomes were as follows:abnormal liver function 46.8％(37/79),bile stasis 22.8％(18/79),fat overload syndrome 13.9％(11/79),liver steatosis 11.4％(9/79),platelet reduction 3.8％(3/79),and other 1.3％(1/79).Among the 86 patients,2 cases were clearly recorded to have improved clinical adverse outcomes after adjusting the sugar-to-fat ratio,and the others were not detailed.Conclusions:Inappropriate sugar-to-fat ratio may lead to safety issues related to parenteral nutrition medication and should be given clinical attention.

The present study aimed to explore the therapeutic effect and mechanism of non-polysaccharide fraction of Bletillae Rhizoma in the treatment of gastric ulcer by network pharmacology and animal experiments. UPLC-Q-TOF-MS/MS was employed to chara-cterize the chemical components of non-polysaccharide fraction of Bletillae Rhizoma, and the common targets of Bletillae Rhizoma and gastric ulcer were screened out by network pharmacology. The "drug-component-target-disease" network was constructed. Protein-protein interaction(PPI) network was established by STRING. Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) enrichment analyses were performed based on Matescape database to predict the therapeutic effect and mechanism of Bletillae Rhizoma. Finally, the gastric ulcer model was induced in mice by alcohol to verify the therapeutic effect and mechanism of non-polysaccharide fraction of Bletillae Rhizoma on gastric ulcer. Forty-seven chemical components were identified from non-polysaccharide fraction of Bletillae Rhizoma, among which gymnoside Ⅰ, gymnoside Ⅱ, militarine, bletilloside A, and shancigusin I might be the main active components of non-polysaccharide fraction of Bletillae Rhizoma against gastric ulcer. PPI network analysis revealed core targets such as albumin(ALB), serine/threonine kinase 1(AKT1), tumor necrosis factor(TNF), and epidermal growth factor receptor(EGFR). The KEGG enrichment analysis showed that non-polysaccharide fraction of Bletillae Rhizoma mainly exerted the therapeutic effect by regulating the phosphatidylinositol 3-kinase(PI3K)/protein kinase B(AKT) signaling pathway, mitogen-activated protein kinase(MAPK) signaling pathway, and Ras signaling pathway. The results of animal experiments showed that non-polysaccharide fraction of Bletillae Rhizoma could significantly improve alcohol-induced ulceration in mice to increase ulcer inhibition rate, decrease the levels of TNF-α, interleukin(IL)-1β, IL-6, vasoactive intestinal peptide(VIP), and thromboxane B2(TXB2), elevated the le-vels of IL-10, prostaglandin E2(PGE2), epidermal growth factor(EGF), and vascular endothelial growth factor(VEGF), down-re-gulate the protein levels of PI3K and AKT, and up-regulate the protein levels of p-PI3K and p-AKT. This study indicates that Bletillae Rhizoma may play a role in the treatment of gastric ulcer through multiple components, targets, and pathways and verifies partial prediction results of network pharmacology. The findings of this study provide a scientific and experimental basis for clinical application.
Animals ; Mice ; Stomach Ulcer/drug therapy* ; Proto-Oncogene Proteins c-akt ; Animal Experimentation ; Network Pharmacology ; Phosphatidylinositol 3-Kinases ; Tandem Mass Spectrometry ; Vascular Endothelial Growth Factor A ; Tumor Necrosis Factor-alpha ; Molecular Docking Simulation ; Drugs, Chinese Herbal/pharmacology*

In this study, ultra-performance liquid chromatography-quadrupole-time-of-flight tandem mass spectrometry(UPLC-Q-TOF-MS~E) was used to analyze the plasma components of Danzhi Xiaoyao Formula after oral administration. Forty-nine plasma components were found in the serum of rats by comparing the compound extract, drug-containing serum, and blank serum. Components, such as 6-hydroxycoumarin, poricoic acid F, deoxoglabrolide, 30-norhederagenin, kanzonol R, 3',6'-di-O-galloylpaeoniflorin, 16α-hydroxytrametenolic acid, 16-deoxyporicoic acid B, 3-O-acetyl-16α-hydroxytrametenolic acid, and 16α,25-dihydroxydehydroeburiconic acid, were first found in rat serum. Behavioral tests, including the tail suspension test, novel object recognition test, and novelty-suppressed feeding test, were conducted for behavioral analysis. It was confirmed that this formula had therapeutic effects on perimenopausal depression. Furthermore, in combination with the network pharmacology method, 53 core targets including MAPK1, HRAS, AKT1, EGFR, and ESR1 were screened, and these targets participated in 165 signaling pathways, including PI3K-AKT, AMPK, VEGFA, MAPK, and HIF-1. In summary, the potential effects of Danzhi Xiaoyao Formula in treating perimenopausal depression are associated with mechanisms in accelerating inflammation repair, improving neuroplasticity, affecting neurotransmitters, regulating estrogen levels, and promoting new blood vessel formation.
Animals ; Rats ; Chromatography, High Pressure Liquid ; Depression/drug therapy* ; Network Pharmacology ; Perimenopause ; Phosphatidylinositol 3-Kinases ; Drugs, Chinese Herbal/pharmacology* ; Molecular Docking Simulation