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.

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 investigate the consistency and diagnostic efficacy of 1.5T and 3.0T MRI in the kidney clear cell likeli-hood score(ccLS)v2.0.Methods A retrospective collection was conducted on the data of 176 pathologically confirmed small renal mass(SRM).Two radiologists independently scored the MRI images using the ccLS v2.0.The Kappa test was used to assess inter-observer consistency,and receiver operating characteristic(ROC)curves were plotted to analyze the diagnostic efficacy.The area under the curve(AUC),sensitivity,specificity,positive predictive value(PPV),and negative predictive value(NP V)were calculated.Results The inter-observer consistency for ccLS v2.0 score was good for 1.5T MRI and excellent for 3.0T MRI(Kappa values were 0.754 and 0.836,respectively).On 1.5T MRI examination,a ccLS≥4 points was identified as the optimal threshold,with AUC of 0.935 and 0.923 for the two radiologists,sensitivities of 92.45％and 88.68％,and specificities of 88.00％and 92.00％,respec-tively.For 3.0T MRI examination,using the same threshold,the AUC were 0.933 and 0.901,with sensitivities of 91.43％and 90.00％,and specificities of 78.57％and 78.57％for both radiologists.Conclusion The ccLS v2.0 demonstrates good consistency across high and low field intensity MRI,and a threshold of ccLS≥4 pionts provides high diagnostic efficacy for clear cell renal cell carcinoma(ccRCC).

Objective To investigate the value of predicting microsatellite instability(MSI)status in endometrial cancer based on whole-tumor apparent diffusion coefficient(ADC)histogram.Methods The data of 131 endometrial cancer patients who underwent preoperative MRI examination and were confirmed by pathology were retrospectively analyzed.According to the pathological immu-nohistochemical results,they were divided into microsatellite stability(MSS)group(103 cases)and MSI group(28 cases).The whole-tumor volume of interest(VOI)was outlined using ITK-SNAP software,and ADC histogram analysis was performed using uAI Research Portal software.The t-test or Mann-Whitney U-test were used to compare the differences between the two groups,and multifactorial logistic regression analysis was used to screen independent predictors for the above parameters with differences.The area under the curve(AUC),sensitivity and specificity were calculated using the receiver operating characteristic(ROC)curve.Results The ADC histogram parameters that were statistically significant between groups were ADC10th,ADC90th,ADCmaximum,ADCmedian,ADCmean,ADCrange,ADCinterquartile range,ADCuniformity,ADCvariance,ADCenergy,ADCentropy,ADCtotal energy,ADCroot mean square,ADCmean absolute deviation,ADCrobust mean absolute deviation,all the above parameters were significantly smaller in the MSI group than in the MSS group.Further multifactorial logistic regression analysis results showed that ADCmedian[odds ratio(OR)=1.019,P=0.020]and ADCroot mean square(OR=0.977,P=0.005)were independent predictors of the MSI status in endometrial cancer.The results of ROC curve showed that the AUC of ADCmedian and ADCroot mean square for predicting MSI status were 0.699 and 0.731,respectively,and the AUC of combining the two parameters to predict MSI status was 0.760,with a sensitivity of 57.14%and a specificity of 86.41%.Conclusion The parameters of ADCmedian and ADCroot mean square based on whole-tumor ADC histogram can be used to predict the MSI status of endometrial cancer,and the combined use of these two parameters helps to improve the efficacy of predicting MSI.

AIM To investigate the effects of Congrong San on neuronal apoptosis and the Bax/Bcl-2/Caspase3 signaling pathway in a rat model of Alzheimer's disease(AD).METHODS A total of 60 2-month-old SD male rats were randomly divided into the blank group,the model group,the memantine hydrochloride group(0.025 g/kg)and low-dose,medium-dose and high-dose Congrong San groups(4.62,9.24,18.48 g/kg).All groups except the control group received stereotactic intracerebral injection of Aβ1-42 to establish AD models.Following the successful modeling,each group received its corresponding intragastric administration once daily for 28 consecutive days.After the administration,the rats had their learning and memory ability detected by the morris water maze test;their hippocampal neuronal morphology observed with HE and Nissl staining;their hippocampal neuronal apoptosis observed with TUNEL staining;and their hippocampal expressions of amyloid precursor protein(APP),β-site APP-cleaving enzyme 1(BACE1),and apoptosis-related proteins Bax,Bcl-2 and Caspase3 detected with Western blot assay.RESULTS Compared with the model group,the groups intervened with medium-dose and high-dose Congrong San exhibited improved learning and memory performance,alleviated hippocampal neuronal damage,increased Nissl body count(P＜0.01),reduced hippocampal apoptosis rate(P＜0.05,P＜0.01),decreased protein expressions of APP,BACE1,Bax and cleaved-Caspase3/Caspase3 ratio(P＜0.05,P＜0.01),and elevated Bcl-2 expression(P＜0.01).CONCLUSION Congrong San mitigates cognitive impairment,hippocampal neuronal damage,and apoptosis in AD rats,probably through inhibition of the Bax/Bcl-2/Caspase3 signaling pathway activation.

Objective To evaluate the efficacy and safety of high-power,short-duration radiofrequency catheter ablation for the treatment of persistent atrial fibrillation.Methods This retrospective study included 392 patients diagnosed with persistent atrial fibrillation who underwent catheter radiofrequency ablation at Suzhou Kowloon Hospital,Shanghai Jiao Tong University School of Medicine,from January 2019 to December 2023.Of these,256 patients were treated with high-power,short-duration ablation,and 136 patients with low-power,long-duration ablation.The following parameters were compared:radiofrequency ablation time,total procedure time,single-circle pulmonary vein isolation rate,immediate procedural success rate,number of ablation points,and perioperative complications(including pericardial tamponade,pseudoaneurysm,arteriovenous fistula,stroke,etc.).Follow-up assessments were conducted at 3,6,and 12 months post-surgery to evaluate the 12-month sinus rhythm maintenance rate.Results The ablation time in the high-power group was significantly shorter than that in the low-power group[(14.6±2.3)min vs.(30.3±4.2)min,P＜0.001],as was the total procedure time[(113.8±24.8)min vs.(128.5±26.7)min,P=0.001].There were no significant differences between the two groups in terms of pulmonary vein isolation rate(97.7％vs.94.9％,P=0.823),number of ablation points[(71.2±8.0)vs.(74.3±14.3),P=0.168],or perioperative complications(3.1％vs.4.4％,P=0.571).Regarding the maintenance rate of sinus rhythm at 12 months post-operation,the high-power group showed a higher rate than the low-power group,but no statistically significant difference was observed(82.8％vs.79.4％,P=0.399).Conclusions High-power,short-duration radiofrequency catheter ablation can improve procedural efficiency in the treatment of persistent atrial fibrillation.Its efficacy and safety are similar to those of the low-power,long-duration technique.

Objective To analyze the changes of neutrophil-to-albumin ratio(NPAR),monocyte-to-lymphocyte ratio(MLR),neutrophil-to-lymphocyte ratio(NLR)and interleukin-17A(IL-17A)in patients with severe autoimmune encephalitis(AE)and the predictive value of their combined detection for prognosis.Methods A total of 105 patients with severe AE admitted from May 2021 to April 2025 were selected as the severe group.During the same period,35 patients with mild-to-moderate AE and 35 healthy controls were enrolled in a 3:1:1 ratio as the mild-to-moderate group and control group respectively.The levels of NPAR,MLR,NLR and IL-17A were compared among the three groups.Patients with severe AE were observed for one month.According to the prognosis of patients,they were divided into poor prognosis subgroup[modified Rankin scale(mRS)score≥3,n=31]and good prognosis subgroup(mRS score<3,n=74).The levels of NPAR,MLR,NLR and IL-17A in the two groups were compared,to analyze the correlation between NPAR,MLR,NLR and IL-17A levels and mRS score in patients with severe AE,and to evaluate the predictive value of combined detection of the four indicators for prognosis in these patients.Results The levels of NPAR,MLR,NLR and serum IL-17A in mild-to-moderate group and severe group were higher than those in control group,which were higher in the severe group than in the mild-to-moderate group(P<0.05).The course of disease in the poor prognosis group was longer than that in the good prognosis group,and the proportion of patients with γ-aminobutyric acid B receptor antibody and the levels of NPAR,MLR,NLR and serum IL-17A were higher than those in the good prognosis group(P<0.05).Higher levels of NPAR,MLR,NLR and serum IL-17A were all risk factors for poor prognosis of patients with severe AE(OR=2.445,4.319,2.502,1.791,P<0.05).The levels of NPAR,MLR,NLR and serum IL-17A were positively correlated with the mRS score of patients with severe AE(r=0.546,0.519,0.554,0.561,P<0.001).The area under the receiver operating characteristic(ROC)curve(AUC)of NPAR,MLR,NLR and IL-17A detected in combination in predicting the prognosis of patients with severe AE was higher than that of the four indicators detected alone(P<0.05).Conclusion The changes in NPAR,MLR,NLR and IL-17A levels in patients with AE were closely related to the severity and prognosis of the disease.In the meantime,higher levels of NPAR,MLR,NLR and serum IL-17A were risk factors for poor prognosis,and the combined detection of the four indicators could effectively improve the predictive value for prognosis in patients with severe AE.

Objective:To explore the impact of plant and animal dietary behaviors on type 2 diabetes mellitus (T2DM) in older adults aged ≥65 in 18 longevity areas of China.Methods:The subjects were 5 223 older adults over 65 years old from the Healthy Ageing and Biomarkers Cohort Study (HABCS) in 18 longevity areas in China. Through a questionnaire survey and physical examination, information about their demographic characteristics, lifestyles, daily activities, self-health status, current diseases, and fasting venous blood were collected. Food Frequency and Questionnaire (FFQ) was used to collect data on food intake frequency. Based on the prior method, the plant-based diet index (PDI) and animal-based diet index (ADI) of 5 223 older adults were calculated. Subjects were divided into three groups (low-level group: PDI<39 or ADI<31, middle-level group: 39≤PDI≤42 or 31≤ADI≤34, high-level group: PDI>42 or ADI>34) by tertiles of PDI and ADI. Multivariate logistic regression was used to analyze the association between PDI and ADI and the risk of T2DM.Results:The average age of 5 223 subjects was (84.8±11.5) years, with the median ( Q1, Q3) of PDI about 41(38, 43) and the median ( Q1, Q3) of ADI about 33 (30, 35). The prevalence rate of T2DM was 16.41% (857/5 223). After adjusting for covariates, multivariate logistic regression showed that PDI was negatively associated with T2DM. Compared with the low-level group, the OR (95% CI) for T2DM in the high-level group was 0.83 (0.69-0.99). ADI was positively associated with T2DM, and compared with the low-level group, the OR (95% CI) for T2DM in the high-level group was 1.28 (1.06-1.55). For every one-point increase in PDI and ADI, the risk of T2DM decreased by 2% and increased by 3%, respectively, with the OR (95% CI) of 0.98 (0.96-1.00) and 1.03 (1.01-1.06), respectively. Conclusion:In Chinese older adults ≥65 years in 18 longevity areas, higher adherence to the plant-based behavior may be negatively associated with the risk of T2DM, while higher adherence to the animal-based behavior may be positively associated with the risk of T2DM.

Objective To investigate the consistency and diagnostic efficacy of 1.5T and 3.0T MRI in the kidney clear cell likeli-hood score(ccLS)v2.0.Methods A retrospective collection was conducted on the data of 176 pathologically confirmed small renal mass(SRM).Two radiologists independently scored the MRI images using the ccLS v2.0.The Kappa test was used to assess inter-observer consistency,and receiver operating characteristic(ROC)curves were plotted to analyze the diagnostic efficacy.The area under the curve(AUC),sensitivity,specificity,positive predictive value(PPV),and negative predictive value(NP V)were calculated.Results The inter-observer consistency for ccLS v2.0 score was good for 1.5T MRI and excellent for 3.0T MRI(Kappa values were 0.754 and 0.836,respectively).On 1.5T MRI examination,a ccLS≥4 points was identified as the optimal threshold,with AUC of 0.935 and 0.923 for the two radiologists,sensitivities of 92.45％and 88.68％,and specificities of 88.00％and 92.00％,respec-tively.For 3.0T MRI examination,using the same threshold,the AUC were 0.933 and 0.901,with sensitivities of 91.43％and 90.00％,and specificities of 78.57％and 78.57％for both radiologists.Conclusion The ccLS v2.0 demonstrates good consistency across high and low field intensity MRI,and a threshold of ccLS≥4 pionts provides high diagnostic efficacy for clear cell renal cell carcinoma(ccRCC).