OBJECTIVE To provide a scientific basis for the quality evaluation and clinical application of Qingwen hufei granules. METHODS Fourteen batches of Qingwen hufei granules were used as samples to establish high-performance liquid chromatography （HPLC） fingerprints using the Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine （2012 Edition）. The chromatographic peaks were identified and the similarity was evaluated. Cluster analysis （CA）， principal component analysis （PCA）， and orthogonal partial least squares-discriminant analysis （OPLS-DA） were used to conduct chemical pattern recognition analysis on the 14 batches of samples. Meanwhile， the contents of neochlorogenic acid （NGA）， chlorogenic acid （CHA）， cryptochlorogenic acid （CGA）， forsythoside A （FTA）， 3，5-O-dicaffeoylquinic acid （3，5-O- DA）， 4，5-O-dicaffeoylquinic acid （4，5-O-DA）， and angoroside C （AGC） in the samples were determined by HPLC. RESULTS The methodological investigation results of both the fingerprint and the content determination complied with the relevant requirements. Fourteen common peaks were indicated in the HPLC fingerprints of the 14 batches of samples， and 7 of them were identified [NGA （peak 2）， CHA （peak 3）， CGA （peak 5）， FTA （peak 11）， 3，5-O-DA （peak 12）， 4，5-O-DA （peak 13）， and AGC （peak 14）]； the similarity of each sample was greater than 0.94. The results of CA and PCA showed that the samples could be classified into 3 categories； the results of OPLS-DA indicated that peak 4 （unknown）， peak 11 （FTA）， peak 8 （unknown）， peak 9 （unknown）， and peak 1 （unknown） were the differential components. The content ranges of NGA， CHA， CGA， 3，5-O-DA， FTA， 4，5-O-DA and AGC in the 14 batches of samples were 0.210 4-0.458 7， 0.269 1-0.506 3， 0.228 1-0.461 1， 0.443 9-1.044 6， 0.066 7-0.155 7， 0.062 8-0.143 8， and 0.057 4-0.105 7 mg/g， respectively. CONCLUSIONS The HPLC fingerprint and multi-component content determination methods established in this study are efficient and reliable， and can be used for the quality evaluation of Qingwen hufei granules.

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.

Objective To explore the prevalence of depressive symptoms in postoperative patients with ovarian cancer and to analyze its influencing factors from multiple dimensions, including clinical characteristics, psychological factors, and laboratory indicators. Methods A cross-sectional study was conducted, which enrolled 235 postoperative patients with ovarian cancer. Depressive status was assessed using the patient health questionnaire, and the demographic, pathological, and medical record data of the patients were collected using the generalized anxiety disorder scale, Pittsburgh sleep quality index, European organization for research and treatment of cancer quality of life questionnaire core 30, and ECOG performance status score. Peripheral blood tumor marker (CA125), routine blood test, lymphocyte subsets, and serum cytokine levels were measured. Univariate and multivariate binary logistic regression analysis were used for statistical analysis. Results The prevalence of depression in postoperative patients with ovarian cancer was 39.15% (92/235). Univariate analysis showed that ECOG score ≥ 2 points, pain, anxiety, poor sleep quality, low quality of life, low life satisfaction, tumor recurrence, six or more cycles of chemotherapy, as well as higher levels of CA125, NLR, and NAR, and lower hemoglobin levels were significantly associated with depression (all P<0.05). Multivariate binary Logistic regression analysis showed that anxiety (OR=1.975, 95%CI: 1.231-3.170), sleep efficiency (OR=4.181, 95%CI: 1.211-14.43), sleep latency (OR=34.806, 95%CI: 4.258-284.542), ECOG performance status score, cognitive function (OR=0.918, 95%CI: 0.868-0.97), and life satisfaction were independent risk factors for depression (all P<0.05). Laboratory indicators were not independent influencing factors in the multivariate Logistic regression model. Conclusion Depression in postoperative patients with ovarian cancer is influenced by physiological, psychological, and social factors. Clinical management should focus on patients with anxiety, sleep disorders, poor physical condition, and low life satisfaction, and a comprehensive prevention and treatment strategy centered on psychological intervention and taking into account symptom management and social support should be implemented.

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.

Inflammatory diseases (IDs) are a general term of diseases characterized by chronic inflammation as the primary pathogenetic mechanism, which seriously affect the quality of patient′s life and cause significant social and medical burden. Current drugs for IDs include nonsteroidal anti-inflammatory drugs, corticosteroids, immunomodulators, biologics, and antioxidants, but these drugs may cause gastrointestinal side effects, induce or worsen infections, and cause non-response or intolerance. Given the outstanding performance of metal polyphenol network (MPN) in the fields of drug delivery, biomedical imaging, and catalytic therapy, its application in the diagnosis and treatment of IDs has attracted much attention and significant progress has been made. In this paper, we first provide an overview of the types of IDs and their generating mechanisms, then sort out and summarize the different forms of MPN in recent years, and finally discuss in detail the characteristics of MPN and their latest research progress in the diagnosis and treatment of IDs. This research may provide useful references for scientific research and clinical practice in the related fields.

Objective To observe the predictive factors of poor prognosis in patients with acute basilar artery occlusion(BAO)who got first-pass effect(FPE)after mechanical thrombectomy(MT).Methods Eighty-two acute BAO patients who got FPE following MT were retrospectively collected and divided into good prognosis group(modified Rankin scale[mRS]score≤3,n=48)and poor prognosis group(mRS score＞3,n=34)90 days after treatments.The data were compared between groups,and variables which showed P＜0.1 were included in multivariate logistic regression analysis to identify independent predictors of poor prognosis in acute BAO patients who got FPE after MT.Results Higher age of patients,pre-treatment National Institute Health stroke scale(NIHSS)and neutrophil-to-lymphocyte ratio(NLR),also higher proportions of patients with diabetes mellitus,atrial fibrillation(AF)and cardioembolic stroke in trial of org 10 172 in acute stroke treatment(TOAST)classification were found in poor prognosis group than those in good prognosis group(all P＜0.05).Conversely,patients in poor prognosis group had lower pre-treatment Glasgow coma scale(GCS)scores,lower posterior circulation-Alberta stroke program early CT score(pc-ASPECTS)and basilar artery on CT angiography(BATMAN)scores(all P＜0.05).Multivariate logistic regression analysis revealed patients complicated with AF(OR[95%CI]=29.769[1.470,602.943])and elevated pre-treatment NLR(OR[95%CI]=1.212[1.016,1.446])had relatively poor prognosis(both P＜0.05),whereas those with increased pre-treatment GCS score(OR[95%CI]=0.615[0.429,0.882]),elevated pc-ASPECTS(OR[95%CI]=0.263[0.092,0.748])and higher BATMAN score(OR[95%CI]=0.260[0.085,0.796])had relatively better prognosis(all P＜0.05).Conclusion Complicated with AF,low pre-treatment GCS score,high NLR,low pc-ASPECTS and low BATMAN score were all predictive factors for poor prognosis in acute BAO patients who got FPE after MT.

Objective:To investigate the molecular characteristics of low-risk acute myeloid leukemia(AML)at recurrence,and analyze the factors affecting retreatment efficacy and prognosis.Methods:A retrospective analysis was conducted on the clinical and laboratory data of 31 patients with newly diagnosed low-risk AML who relapsed during consolidation treatment or follow-up after treatment in our hospital from April 2017 to January 2023.Gene mutations before and after relapse were compared,retreatment efficacy following relapse was evaluated,and univariate and multivariate analyses were performed to identify factors influencing treatment efficacy and prognosis.Results:Gene sequencing results after relapse showed that the most common newly acquired mutation was FLT3-ITD,while RAS mutation detected at initial diagnosis were predisposed to loss of expression during relapse.The median overall survival(OS)after relapse for the entire cohort was 349(170-528)days,with non-hematopoietic stem cell transplantation(HSCT)group and HSCT group demonstrating median survival times of 210(106-314)days and not reached,respectively(P=0.001).Multivariate analysis revealed that age ≥60 years was a significant risk factor for achieving remission after retreatment in initially diagnosed low-risk AML patients who experienced relapse(OR=18.222,95％CI:1.188-279.597,P=0.037).Additionally,DNMT3A mutation was identified as an independent risk factor for OS(HR=13.165,95％CI:2.018-85.877,P=0.007),while HSCT post-relapse demonstrated significant survival benefits(HR=0.133,95％CI:0.025-0.698,P=0.017)and served as an independent protective factor for OS.Conclusion:Relapsed low-risk AML is often associated with loss of RAS and novel mutations in FLT3-ITD.Age ≥ 60 years and DNMT3A mutations were identified as independent adverse factors for achieving subsequent remission and post-relapse survival,respectively,while HSCT significantly improved patient outcomes.

Objective:To investigate the effect of traditional Chinese medicine chronic disease management model based on empowerment theory in patients with chronic heart failure(CHF).Methods:A total of 115 CHF patients admitted in Guangdong Provincial Hospital of Chinese Medicine between January 2020 and December 2021 were se-lected.Patients received traditional Chinese medicine chronic disease management model based on empowerment theory according to voluntary principle,and were followed up for 12 months.Exercise capacity,scores of Tradition-al Chinese Medicine Symptom Grading and Quantification Scale,Hospital Anxiety and Depression Scale(HADS)and Minnesota Living with Heart Failure Questionnaire(MLHFQ)were compared between before and after inter-vention.Results:Compared to before intervention,scores of Traditional Chinese Medicine Symptom Grading and Quantification Scale[(6.40±6.11)points vs.(8.88±6.72)points],HADS[(5.95±4.68)points vs.(7.69±5.95)points],MLHFQ[(13.10±10.54)points vs.(25.53±11.16)points]and 3m round-trip movement time[(7.54±1.70)s vs.(8.86±3.65)s]were significantly lower,and right hand grip strength[(27.23±10.49)kg vs.(26.10±9.94)kg]and 6-minute walking distance[(464.79±80.78)m vs.(415.55±79.33)m]were sig-nificantly higher after 12-month intervention(P＜0.05 or＜0.01).Conclusion:The traditional Chinese medicine chronic disease management model based on empowerment theory may improve clinical symptoms of traditional Chi-nese medicine,mental state,exercise capacity and quality of life in patients with chronic heart failure.

Objective:To investigate the application and effectiveness of the scaffolding teaching method in improving the teaching effect of septic shock and cultivating learning interest among medical students.Methods:A total of 52 medical students participating in intensive care internship were randomly divided into traditional teaching group and scaffolding teaching group,with 26 students in each group. The students in the traditional teaching group received traditional teaching,while those in the scaffolding teaching group received scaffolding teaching; assessments were performed in both groups. The two groups were compared in terms of theoretical assessment score,case assessment score,and degree of satisfaction with teaching. SPSS 25.0 was used to perform the t-test and the chi-square test. Results:There was no significant difference in theoretical assessment score at the time of department enrollment between the two groups [(5.31±1.05) vs. (5.35±0.94), P=0.890]. Compared with the traditional teaching group,the scaffolding teaching group had significantly higher scores in theoretical assessment [(7.19±1.17) vs. (6.39±1.20), P=0.017],specialized physical examination in case assessment [(7.15±0.66) vs. (6.29±0.59), P<0.001],and diagnosis and treatment regimen [(7.58±0.66) vs. (6.83±0.60), P<0.001],as well as significantly more interest in critical care medicine ( χ2=4.59, P=0.032). Conclusions:In the teaching process of the diagnosis and treatment of septic shock,building various types of scaffolds based on the basic knowledge of students can stimulate their interest and improve teaching effectiveness,which holds promise for further application in critical care medicine teaching.

Objective:A model for predicting sentinel lymph node metastasis was established based on positron emission tomography(PET)-related metabolic parameters and clinicopathological characteristics.Methods:A retro-spective analysis was conducted on 211 patients diagnosed with breast cancer through surgical pathology from January 2016 to March 2023 in Meizhou People's Hospital,who underwent whole-body PET/CT examinations prior to surgery.Clinical,pathological,and PET-related metabolic parameters were collected.The study analyzed the association be-tween clinicopathological characteristics of the primary breast cancer lesion,PET metabolic parameters,and sentinel lymph node metastasis.A logistic regression predictive model was constructed using Broussonetia papyrifera.Results:Breast cancer primary lesion PET-suspicious axillary lymph nodes,vascular tumor thrombus,estrogen receptor(ER),and progesterone receptor(PR)showed statistically significant differences between the two groups(all P<0.05),while maxi-mum tumor diameter,SUVmax tumor location,maximum standardized uptake value(SUVmax),metabolic tumor volume(MTV),total lesion glycolysis(TLG),tumor location,number of lesions,pathological type,histological grade,neural inva-sion,Homo sapiens epidermal growth factor receptor 2(HER-2),and nuclear-associated antigen Ki-67(Ki-67)showed no statistically significant differences between the two groups(all P>0.05).Parameters with P<0.05 in the univariate analysis were subjected to multivariate logistic regression analysis,and the logistic regression model was established as Logit(P)=-0.437×vascular tumor thrombus+4.685×suspicious axillary lymph node metastasis.The predictive model AUC was 0.738(P<0.001,95%CI:0.664～0.812),with sensitivity and specificity of 63.4%and 74.4%,respectively.Con-clusion:PET findings of the primary breast cancer lesion regarding suspicious axillary lymph node metastasis,vascular tumor thrombus,ER and PR are associated with sentinel lymph node metastasis.The predictive model established based on PET-detected suspicious axillary lymph node metastasis and vascular tumor thrombus in primary breast cancer lesions has certain value in predicting sentinel lymph node metastasis,potentially providing a non-invasive examination modality for clinical practice.