OBJECTIVE To investigate the effects of galangin on rheumatoid arthritis （RA） in rats by regulating the Janus kinase 3 （JAK3）/signal transducer and activator of transcription 3 （STAT3） pathway. METHODS Fifty male SD rats were taken， and an emulsion composed of bovine type Ⅱ collagen and Freund’s complete adjuvant was injected subcutaneously to establish an induced arthritis model. The rats that were successfully modeled were randomly divided into model group， low， medium and high dose groups of galangin （1， 5， 15 mg/kg）， and methotrexate group （positive control， 2 mg/kg）， with 10 rats in each group. Another 10 normal rats were taken as the normal group. Starting from the 15th day of modeling， each group of rats was gavaged with the corresponding drug solution or normal saline containing 0.5% Tween 80 once a day for 28 consecutive days. The arthritis index （AI） scores and paw volume of rats were compared before and after gavage administration. Twenty-four hours after the last administration， the serum levels of interleukin-6 （IL-6）， tumor necrosis factor-α （TNF-α）， IL-4 and IL-10 were determined， the pathological changes in ankle joint synovial tissue were observed， and the protein expressions of UNC-51 like kinase 1 （ULK1）， Beclin-1， microtubule-associated protein 1 light chain 3 （LC3）， B cell lymphoma 2 （Bcl-2）， Bcl-2-associated X protein （Bax）， caspase-3， JAK3， phosphorylated JAK3 （p-JAK3）， STAT3 and phosphorylated STAT3 （p-STAT3） in the synovial tissue of the ankle joint were detected， as well as the fluorescence intensity of LC3-positive areas. RESULTS Compared with the model group， the pathological changes such as cellular proliferation of ankle joint synovial tissue and infiltration of inflammatory cells in rats of each administration group showed improvement. Moreover， their AI scores and paw pad volumes （on day 28 after gavage）， the levels of IL-6 and TNF-α， the protein expression of Bcl-2， and the phosphorylation levels of JAK3 and STAT3 were all significantly reduced （ P ＜0.05）. The levels of IL-4 and IL-10， the protein expressions of ULK1， Beclin-1， Bax， caspase-3 and LC3， as well as the fluorescence intensity of LC3-positive areas， were all significantly increased （ P ＜0.05）. Moreover， the effect of galangin was in a dose-dependent manner （ P ＜0.05）. CONCLUSIONS Galangin can induce sustained autophagy in synovial tissue cells of RA rats， promote cell apoptosis， inhibit synovial cell proliferation， and alleviate persistent inflammatory responses. The above anti-RA effects may be related to the inhibition of the JAK3/STAT3 pathway.

Chronic diabetic wounds, severely complicated by multidrug-resistant (MDR) bacterial infections, represent a profound and escalating global health crisis. The intrinsically hostile microenvironment of diabetic wounds, characterized by localized hypoxia, persistent oxidative stress, and poor vascularization, creates an ideal niche for opportunistic pathogens such as Staphylococcus aureus and Pseudomonas aeruginosa. These bacteria readily construct dense extracellular polymeric substance (EPS) biofilms, which not only physically shield the microbes from host immune responses but also actively trap the wound in a state of chronic, unresolved inflammation. Consequently, conventional systemic and topical antibiotic therapies are becoming increasingly futile, as poor perfusion at the wound site restricts drug bioavailability, while the rapid genetic evolution of bacteria and the impenetrable nature of biofilms lead to catastrophic treatment failures, often culminating in severe tissue necrosis and lower-extremity amputations. To circumvent the limitations of traditional antimicrobials, therapeutic gas delivery has emerged as a highly promising, paradigm-shifting strategy. Gaseous signaling molecules, particularly nitric oxide (NO), carbon monoxide (CO), hydrogen sulfide (H₂S), and hydrogen (H₂), possess unique physicochemical properties that allow them to seamlessly penetrate dense biofilm matrices and cellular membranes. Once inside, these gases operate via multi-targeted mechanisms that are incredibly difficult for bacteria to develop resistance against; for instance, NO induces severe lipid peroxidation and DNA cleavage in bacteria, CO downregulates pro-inflammatory cytokines, H₂S significantly accelerates endothelial cell migration for neovascularization, and H₂ acts as a powerful selective antioxidant to neutralize tissue-damaging reactive oxygen species (ROS). Together, these therapeutic gases not only exert broad-spectrum bactericidal effects but also actively reprogram the wound bed by promoting the critical M1-to-M2 macrophage polarization and stimulating angiogenesis. Despite their immense biological potential, the direct clinical translation of gas therapies is severely hindered by inherent physicochemical drawbacks, including extreme volatility, short physiological half-lives, poor aqueous solubility, and the high risk of off-target systemic toxicity, if applied indiscriminately. To conquer these immense pharmacokinetic barriers, cutting-edge advancements in materials science have driven the development of gas-releasing micro- and nanoplatforms. Utilizing sophisticated carriers such as metal-organic frameworks (MOFs), mesoporous silica, polymeric nanoparticles, liposomes, and injectable hydrogels, researchers can now encapsulate gas-donor molecules to achieve sustained, localized delivery. More importantly, these advanced nanoplatforms are ingeniously engineered to be stimuli-responsive. By exploiting the pathological hallmarks of the diabetic wound environment, such as elevated glucose concentrations, acidic pH, and overexpressed ROS, or by utilizing external triggers like near-infrared (NIR) light irradiation and ultrasound, these intelligent platforms ensure on-demand, precise spatio-temporal gas release. This often allows for powerful synergistic combinations, such as photothermal or photodynamic therapy coupled with gas release, thereby obliterating biofilms while sparing healthy tissue. While the therapeutic outcomes of these smart delivery systems in eradicating MDR infections and accelerating tissue repair are unprecedented, several critical challenges remain before widespread clinical adoption, as long-term biosafety profiles of the carrier nanomaterials, complexities in large-scale good manufacturing practice (GMP) production, and stringent regulatory hurdles must be rigorously addressed. Looking forward, the next frontier lies in the realm of precision medicine and theranostics, where future research must focus on the seamless integration of these gas-releasing platforms with flexible, wearable biosensors capable of continuously monitoring wound biomarkers (e.g., pH, temperature, uric acid) in real-time. Coupled with artificial intelligence algorithms to govern automated, closed-loop adaptive dosing, these next-generation smart dressings hold the ultimate potential to comprehensively transform the clinical management of complex, infected diabetic wounds.

ObjectiveTo analyze the epidemiological and etiological characteristics of a cluster of human metapneumovirus (HMPV) infection in a kindergarten in Gongshu District of Hangzhou City in May 2024, and to provide reference for the prevention and control of similar outbreaks. MethodsAn on-site investigation was conducted using an epidemiological case investigation form. Throat swab specimens collected from cases were screened for 13 respiratory pathogens using real-time fluorescent polymerase chain reaction (PCR). For HMPV nucleic acid positive specimens, the F gene of HMPV was used as the target gene for amplification and sequencing. The sequencing results were then compared with sequences in GenBank database to determine the virus subtypes and perform phylogenetic analyses. ResultsThe outbreak occurred in a kindergarter junior class with a total of 28 preschoolers and 3 teachers and childcare workers. A total of 11 cases (10 preschoolers and 1 teacher) were identified, including 8 male cases and 3 female cases. Clinical manifestations included fever in all 11 cases (100.00%), cough in 8 cases (72.72%), catarrhal symptoms in 4 cases (36.36%), and headache in 3 cases (27.27%). All symptoms were mild, and no severe cases were observed. A total of 11 throat swab samples were collected. Real-time fluorescent PCR test results showed that 3 samples were positive for HMPV nucleic acid, 2 samples were positive for both HMPV and Streptococcus pneumoniae, and 1 sample was positive for both HMPV and rhinovirus. The sequences of the 6 HMPV nucleic acid positive specimens were amplified and analyzed using specific primers, and all were determined to be HMPV subtype A2b. The F gene fragment sequence showed the highest similarity to PV081665.1/Brazil/2024 (99.65%), and also exhibited high similarity to PP683455.1/Indonesia/2021 (99.48%), PV016275.1/Beijing/2024 (99.31%), and PV052230.1/USA/2024 (99.13%). ConclusionThis cluster of acute respiratory tract infection was caused by HMPV subtype A2b, with co-infection of rhinovirus and Streptococcus pneumoniae. The F gene fragment sequences of the HMPV in this outbreak were highly homologous to those of the A2b strains isolated from Brazil, Beijing, Indonesia, and the the United States.

Chronic diabetic wounds, severely complicated by multidrug-resistant (MDR) bacterial infections, represent a profound and escalating global health crisis. The intrinsically hostile microenvironment of diabetic wounds, characterized by localized hypoxia, persistent oxidative stress, and poor vascularization, creates an ideal niche for opportunistic pathogens such as Staphylococcus aureus and Pseudomonas aeruginosa. These bacteria readily construct dense extracellular polymeric substance (EPS) biofilms, which not only physically shield the microbes from host immune responses but also actively trap the wound in a state of chronic, unresolved inflammation. Consequently, conventional systemic and topical antibiotic therapies are becoming increasingly futile, as poor perfusion at the wound site restricts drug bioavailability, while the rapid genetic evolution of bacteria and the impenetrable nature of biofilms lead to catastrophic treatment failures, often culminating in severe tissue necrosis and lower-extremity amputations. To circumvent the limitations of traditional antimicrobials, therapeutic gas delivery has emerged as a highly promising, paradigm-shifting strategy. Gaseous signaling molecules, particularly nitric oxide (NO), carbon monoxide (CO), hydrogen sulfide (H₂S), and hydrogen (H₂), possess unique physicochemical properties that allow them to seamlessly penetrate dense biofilm matrices and cellular membranes. Once inside, these gases operate via multi-targeted mechanisms that are incredibly difficult for bacteria to develop resistance against; for instance, NO induces severe lipid peroxidation and DNA cleavage in bacteria, CO downregulates pro-inflammatory cytokines, H₂S significantly accelerates endothelial cell migration for neovascularization, and H₂ acts as a powerful selective antioxidant to neutralize tissue-damaging reactive oxygen species (ROS). Together, these therapeutic gases not only exert broad-spectrum bactericidal effects but also actively reprogram the wound bed by promoting the critical M1-to-M2 macrophage polarization and stimulating angiogenesis. Despite their immense biological potential, the direct clinical translation of gas therapies is severely hindered by inherent physicochemical drawbacks, including extreme volatility, short physiological half-lives, poor aqueous solubility, and the high risk of off-target systemic toxicity, if applied indiscriminately. To conquer these immense pharmacokinetic barriers, cutting-edge advancements in materials science have driven the development of gas-releasing micro- and nanoplatforms. Utilizing sophisticated carriers such as metal-organic frameworks (MOFs), mesoporous silica, polymeric nanoparticles, liposomes, and injectable hydrogels, researchers can now encapsulate gas-donor molecules to achieve sustained, localized delivery. More importantly, these advanced nanoplatforms are ingeniously engineered to be stimuli-responsive. By exploiting the pathological hallmarks of the diabetic wound environment, such as elevated glucose concentrations, acidic pH, and overexpressed ROS, or by utilizing external triggers like near-infrared (NIR) light irradiation and ultrasound, these intelligent platforms ensure on-demand, precise spatio-temporal gas release. This often allows for powerful synergistic combinations, such as photothermal or photodynamic therapy coupled with gas release, thereby obliterating biofilms while sparing healthy tissue. While the therapeutic outcomes of these smart delivery systems in eradicating MDR infections and accelerating tissue repair are unprecedented, several critical challenges remain before widespread clinical adoption, as long-term biosafety profiles of the carrier nanomaterials, complexities in large-scale good manufacturing practice (GMP) production, and stringent regulatory hurdles must be rigorously addressed. Looking forward, the next frontier lies in the realm of precision medicine and theranostics, where future research must focus on the seamless integration of these gas-releasing platforms with flexible, wearable biosensors capable of continuously monitoring wound biomarkers (e.g., pH, temperature, uric acid) in real-time. Coupled with artificial intelligence algorithms to govern automated, closed-loop adaptive dosing, these next-generation smart dressings hold the ultimate potential to comprehensively transform the clinical management of complex, infected diabetic wounds.

Lung cancer， with persistently high incidence and mortality rates， remains a significant global health challenge. By taking the study on the experience in diagnosis and treatment of lung cancer with phlegm-dampness and blood stasis syndrome by distinguished traditional Chinese medicine physicians of the Sichuan School as an example， the diagnosis and treatment system for lung cancer with phlegm-dampness and blood stasis syndrome， which was formed in response to the humid and foggy environment of the Sichuan Basin， possesses unique value. However， traditional inheritance modes face challenges such as fragmentation， lack of standardization， and insufficient quantification， which hinder the promotion and application of this experience. This research focused on how to leverage multimodal data and artificial intelligence-generated content （AIGC） to achieve precise analysis， intelligent inheritance， and clinical innovation of the experience in diagnosis and treatment of lung cancer with phlegm-dampness and blood stasis syndrome by distinguished traditional Chinese medicine physicians of the Sichuan School. By integrating multimodal data （encompassing four diagnostic methods of traditional Chinese medicine， modern medical imaging， clinical laboratory tests， molecular biology， and regional environmental information）， a precise diagnosis and treatment system integrating macro and micro perspectives for the "disease， syndrome， and pathogenesis" was constructed. The research yielded the following results： （1） In precise syndrome differentiation， the objective quantification of the phlegm-dampness and blood stasis syndrome was achieved. By constructing a "four diagnostic methods， imaging， and molecule" correlation model， the study revealed intrinsic links between tongue and pulse parameters and the tumor microenvironment， as well as between regional climatic factors and syndrome characteristics， enabling real-time dynamic monitoring of efficacy. （2） In elucidating patterns， the study systematically explored the syndrome differentiation thoughts of Sichuan School physicians， such as the timing of purgation and tonification. A "pathogenesis， syndrome complex， and prescriptions and herb" network model was constructed， which accurately elucidated the synergistic action mechanisms of core herb pairs and quantified the dynamic compatibility patterns of reinforcing healthy Qi and eliminating pathogenic factors. （3） In intelligent empowerment， an auxiliary system integrating intelligent syndrome differentiation， treatment plan generation， and efficacy evaluation was built. This system can fuse regional characteristics with individual data， dynamically generate and optimize personalized prescriptions aligned with the experience of Sichuan School， and predict efficacy trends and potential adverse reactions. The integration of multimodal data and AIGC can effectively facilitate the structured inheritance and clinical translation of distinguished physicians' experience. The established intelligent diagnosis and treatment model integrating traditional Chinese medicine and Western medicine demonstrates clear potential in prolonging patients' progression-free survival， alleviating symptoms， and reducing adverse reactions to treatment. This study provides a referential methodological framework for the traditional Chinese medicine experience in diagnosis and treatment of lung cancer， especially the empirical inheritance and modernized development of regional academic schools. It contributes to advancing clinical diagnosis and treatment toward greater precision and personalization.

Cilia,as cellular sensory organelles,actively partici-pate in and regulate cellular processes such as autophagy and metabolic breakdown during their generation and transportation.Autophagy,on the other hand,is a cell self-protection mecha-nism that maintains cellular homeostasis by clearing aggregates and damaged organelles.Combining recent research findings,this review comprehensively elucidates the bidirectional crosstalk between primary cilia and autophagy.Specifically,it highlights the crucial role of cilia-dependent signaling pathways in activa-ting cellular autophagy and how autophagy regulates cilia genera-tion and length by degrading specific ciliary proteins.Moreover,the dysregulation of primary cilia and autophagy is closely asso-ciated with the clinical manifestations and pathogenesis of vari-ous ciliopathy-related diseases such as polycystic kidney disease and tuberous sclerosis.In terms of pharmacotherapy,this review provides a comprehensive and in-depth overview of small mole-cule inhibitors targeting ciliogenesis,including cytoskeletal drugs and Hedgehog signaling pathway inhibitors.Despite the current limitations in clinical use,these drugs lay the groundw-ork for developing highly specific targeted small molecule inhibi-tors of ciliogenesis and for the treatment of ciliopathies and canc-ers.By systematically discussing ciliogenesis,autophagy,disea-ses and drugs,this review offers new insights for further elucida-ting the crosstalk between ciliogenesis and autophagy,exploring their pathological mechanisms in disease development,and de-veloping therapeutic strategies in the future.

AIM To investigate the effects of Rutong Ruanjian Tablets on angiogenesis in cancer tissues of rats with preneoplastic breast cancer(PBC).METHODS 60 female SD rats were randomly divided into a blank group of 10 rats and a model group of 50 rats for the establishment of the PBC models of Liver-Qi Stagnation and Blood Stasis Pattern with 9 weeks of oral administration of 7,12-dimethylbenz[a]anthracene(DMBA)and cervical ligation.After successful modeling,the rats were randomly divided into the model group,the tamoxifen group(3.2 mg/kg),the Rutong Ruanjian Tablets group(128 mg/kg),the 3,5-difluorobenzoyl group(DAPT,5 mg/kg),and the Rutong Ruanjian Tablets(128 mg/kg via gavage)+DAPT(5 mg/kg intraperitoneal injection)group,for 1 month corresponding drug administration,with 10 rats in each group.Then the rats had their cancer progression and syndrome scores observed;their angiogenesis evaluated by assessment of microvascular density(MVD);their vascular endothelial growth factor(VEGF)expression assessed by immunohistochemistry;and their mRNA and protein expressions of proteins related to the DLL4/Notch1/Hes1 pathway measured using RT-qPCR,immunohistochemistry and Western blot.RESULTS During carcinogenesis of rats induced by DMBA,there was gradual disappearance of E-cadherin expression and consistency of HE staining result with the PBC progression confirming the success of the modeling.Compared with the blank group,the model group showed increased MVD values,mRNA expression of Notch1 and Hes1,and protein expressions of VEGF,DLL4,Notch1 and Hes1(P＜0.05,P＜0.01).Compared with the model group,the Rutong Ruanjian Tablets group exhibited reduced MVD values,mRNA expression of Notch1 and Hes1,and protein expressions of VEGF,DLL4,Notch1 and Hes1(P＜0.05,P＜0.01).The Rutong Ruanjian Tablets+DAPT group showed reduced mRNA expression of Notch1 and Hes1,and protein expressions of DLL4,Notch1 and Hes1 compared to the Rutong Ruanjian Tablets group(P＜0.05,P＜0.01).CONCLUSION Rutong Ruanjian Tablets can inhibit angiogenesis and attenuate cancer progression in PBC rats of Liver-Qi Stagnation and Blood Stasis Pattern,and the mechanism may lie in the downregulation of DLL4/Notch1/Hes1 signaling pathway related proteins.

Objective To translate Evidence-Informed Decision-Making Competence Measure for Chinese nurses and test its validity and reliability.Methods A research group was set up to use the Brislin translation model to translate the original scale into Chinese,and the back translation,cross-cultural adaptation,pre-experiment and cognitive interview were conducted to finally form the Chinese version of the Evidence-Informed Decision-Making Competence Measure for nurses.A total of 1 247 nurses from 7 tertiary A hospitals in Beijing,Hubei,Hunan and Xinjiang were selected by convenience sampling method in April 2024 to test its reliability and validity.Results 1 026 effective question-naires were collected,with an effective recovery rate of 82.28％.The Chinese version of the Evidence-Informed Decision-Making Competence Measure included 25 items,including knowledge/skill,attitude and behavior.A total of 3 common factors were extracted from exploratory factor analysis,and the cumulative variance contribution rate was 91.725％.The content validity index at the item level was 0.83-1.00;the content validity index at the scale level was 0.988;the calibration association validity was 0.496.The Cronbach's α coefficient of the whole scale was 0.992;the half-point reliability was 0.930;the retest reliability was 0.927.Conclusion The Chinese version of Evidence-Informed Decision-Making Competence Measure for nurses has good reliability and validity,and it can be used to evaluate the evidence-informed decision-making competence of Chinese nurses,provide references for promoting evidence-based nursing practice and evidence-informed decision-making.

Objective To evaluate the effect of remimazolam on the incidence of postoperative delirium(POD)in elderly lung cancer patients undergoing thoracoscopic surgery.Methods A total of 114 elderly patients who underwent unilateral thoracoscopic lung surgery at the Affiliated Hospital of Xuzhou Medical University from October 2024 to April 2025 were recruited in this trial.Patients were randomly assigned to remimazolam group(group R)and propofol group(group P).Anesthesia induction and maintenance were performed with remimazolam and propofol,respectively.In R group,0.5 mg of flumazenil was intravenously injected at the end of the surgery for specific antagonism.The incidence of delirium and Quality of Recovery-15(QoR-15)scores on the first and third postoperative days were compared between the two groups.Intraoperative hemodynamic parameters,total opi-oid dosage,fluid balance,tracheal tube extubation time after surgery,and the incidence of adverse reactions were recorded.Results There were no statistically significant differences between the groups in the incidence of POD or in QoR-15 scores(P>0.05).Compared with group P,patients in group R had a shorter extubation time(P<0.05),more stable hemodynamics,lower incidences of intra-operative hypotension and bradycardia,and reduced requirement for vasoactive drugs(P<0.05).The consumption of rescue analgesics in the post-anesthesia care unit(PACU)was also lower in group R(P<0.05).No significant differences were observed between the groups in the amounts of sufentanil and remifentanil administered,fluid balance,bispectral index(BIS)values,or the inci-dence of nausea and vomiting(P>0.05).Conclusion In elderly patients undergoing elective thoracoscopic sur-gery,remimazolam-based induction and maintenance of anesthesia did not significantly alter the incidence of POD or compromise postoperative recovery quality compared with propofol.However,the remimazolam group required fewer vasoactive agents and exhibited a shorter tracheal extubation time.

Objective To develop a fused model based on combined intratumor-peritumor radiomics features and clinical risk factors to accurately predict the efficacy of radiotherapy for hepatocellular carcinoma(HCC).Methods A retrospective study was conducted on 124 HCC patients(95 males and 29 females)undergoing IMRT at the radiotherapy center of some hospital,who were divided into a training set and a validation set in a 7∶3 ratio.According to relevant standards for evaluating solid tumor treatment efficacy the patients at the progressive disease phase were enrolled into a non-response group,and the ones at the phases of complete response,partial response and stable disease were included into a response group.Firstly,radiomics features were extracted from pre-radiotherapy contrast-enhanced CT images,and were screened with the least absolute shrinkage and selection operator(LASSO)regression to obtain valuable radiomics features;secondly,the scores of intratumor radiomics features,peritumor radiomics features and combined intratumor-peritumor radiomics features underwent binary Logistic regression(LR)analysis by using the glmnet package in R software(version 4.2.0),so as to construct three models for intratumor radiomics features,peritumor radiomics features and combined intratumor-peritumor radiomics features;finally,a fused model was established based on the scores of combined intratumor-peritumor radiomics features and clinical risk factors,and the corresponding Nomogram,calibration curve and clinical decision curve were plotted.R software(version 4.4.1)was used for image analysis and statistical analysis.Results The fused model based on the scores of combined intratumor-peritumor radiomics features and clinical risk factors achieved an AUC of 0.87 on both the training and validation sets,outperforming the models based solely on intratumor radiomics features,peritumor radiomics features or combined intratumor-peritumor radiomics features.The Nomogram plot showed the prediction probability of the fused model for the short-term treatment response rate was 10%-90%within the total score range of 42-93 points,and the calibration and clinical decision curves indicated that the fused model gained advantages in prediction and clinical application.Conclusion The fused model based on the scores of combined intratumor-peritumor radiomics features and clinical risk factors predicts the short-term efficacy of HCC radiotherapy effectively,providing references for formulating radiotherapy plans and guiding subsequent treatment decisions.