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 current distribution of radiotherapy resources in Gansu Province, evaluate the equity of resource allocation, and provide a scientific basis for optimizing regional resource allocation. Methods A questionnaire survey was carried out to assess radiotherapy resources in medical institutions across Gansu Province, China. The equity of radiotherapy resource distribution and associated disparities were assessed using the Gini coefficient, Lorenz curve, and Theil index. Results A total of 23 medical institutions in Gansu Province provided radiotherapy services, comprising 39 radiotherapy devices and 438 professionals, of whom medical physicists accounted for 16.9%. The radiotherapy frequency was 0.47 cases per thousand population. The Gini coefficients for radiotherapy resource distribution ranged from 0.38 to 0.56 by population and from 0.52 to 0.70 by geography. The Theil index for radiotherapy resources ranged from 1.36 to 3.67. Conclusion Radiotherapy resources in Gansu Province were insufficient, and the capacity of radiotherapy service was suboptimal. The equity of radiotherapy resource allocation by geography was worse than that by population. Therefore, it is imperative to address the shortage of radiotherapy resources, strengthen the professional workforce, enhance the capacity radiotherapy service and resource utilization, optimize resource allocation, and promote regional equity in radiotherapy provision in Gansu Province.

Objective: To explore the relationship between snack consumption and depressive symptoms in first year junior high school students with different left behind experiences in Yunnan Province, so as to provide a basis for improving depressive symptoms among first year junior high school students with different left behind experiences. Methods: From October to December 2022,a cluster random sampling method was used to select 8 500 first year junior high school students from 11 ethnic minority areas (Fugong County, Longling County, Longyang District, Luchun County, Mojiang County, Nanjian County, Qiaojia County, Shuangjiang County, Tengchong City, Yuanmou County, Zhenyuan County) in Yunnan Province for a questionnaire survey. The Chinese version of Depression Anxiety Stress Scale-21 was applied to assess depressive symptoms in first year junior high school students, and snack consumption was collected by employing food frequency questionnaire. The generalized linear model was used to analyze the association between first year junior high school students snack consumption and depressive symptoms, and the analysis was stratified according to left behind experience. Results: The detection rates of depressive symptoms among firstyear junior high school students with and without left behind experience were 36.25% and 26.91%, respectively. After controlling for confounding variables, the generalized linear model analysis showed that sweet snacks ( β=0.16, 95%CI =0.07-0.25), fast food ( β=0.14, 95%CI =0.04-0.23) and carbonated drinks ( β=0.09, 95%CI =0.01-0.17) of first year junior high school students with left behind experience (all P <0.05). Compared with those without such behavior, the risk of depressive symptoms was higher in consumption of fast food ( β=0.13, 95%CI =0.07-0.18) and carbonated drinks ( β=0.10, 95%CI =0.06-0.15)among first year junior high school students without left behind experience (both P <0.05). Conclusion Snack consumption among first year junior high school students in Yunnan may increase the risk of developing depressive symptoms, while first year junior high school students with left behind experience may have a greater risk of developing depressive symptoms.

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 evaluate the clinical efficacy of Huayu Tongluo Formula （化瘀通络方， HTF） in patients with mid-stage diabetic kidney disease of blood stasis syndrome and explore its potential mechanisms. MethodsA multi-center， randomized， double-blind， placebo-controlled clinical trial was conducted. Ninety patients of mid-stage diabetic kidney disease of blood stasis syndrome were divided into a control group of 46 cases and a treatment group of 44 cases. Both groups received conventional western medicine treatment， the treatment group additionally taking HTF， while the control group taking a placebo of the formula. The treatment was administered once daily for 24 weeks. The primary outcomes included 24-hour urine total protein （24 h-UTP）， serum albumin （Alb）， glycated hemoglobin （HbA1c）， and serum creatinine （Scr）.The secondary outcomes included changes in levels of endothelin-1 （ET-1）， nitric oxide （NO）， vascular endothelial growth factor （VEGF）， and traditional Chinese medicine （TCM） syndrome scores before and after treatment. Clinical efficacy was evaluated based on TCM syndrome scores and overall disease outcomes. Adverse reactions and endpoint events were recorded. ResultsIn the treatment group after treatment， 24 h-UTP， ET-1， and VEGF levels significantly decreased （P＜0.05）， Alb and NO levels significantly increased （P＜0.05）； while the TCM syndrome scores for edema， lumbar pain， numbness of limbs， dark purple lips， dark purple tongue or purpura， and thin， rough pulse all significantly decreased （P＜0.05）. In the control group， no significant changes were observed in any of the indicators after treatment （P＞0.05）.Compared with the control group， the treatment group showed significant reductions in 24 h-UTP， ET-1， and VEGF levels， and increases in Alb and NO levels （P＜0.05）. The TCM syndrome scores for edema， lumbar pain， dark purple tongue or purpura， and thin， rough pulse were all lower in the treatment group than in the control group （P＜0.05）. The total effective rate of TCM syndrome in the treatment group was 59.09% （26/44）， and the overall clinical effective rate was 45.45% （20/44）. In the control group， these rates were 15.22% （7/46） and 8.7% （4/46）， respectively， with the treatment group showing significantly better outcomes （P＜0.05）. A total of 7 adverse events occurred across both groups， with no significant difference （P＞0.05）. No endpoint events occurred during the study. ConclusionOn the basis of conventional treatment of Western medicine， HTF can further reduce urinary protein levels and improve clinical symptoms in patients with mid-stage diabetic kidney disease of blood stasis syndrome. The mechanism may be related to its effects on endothelial function.

ObjectiveIn order to provide a reference for the optimization of preparation process of stir-fried Glycyrrhizae Radix et Rhizoma（sf-GRR）， the quality changes during the processing was studied. MethodsGlycyrrhizae Radix et Rhizoma was processed by stir-frying for 17 min， and samples were collected every 1 min during the processing. The appearance color of the samples was determined by visual analysis technology， the moisture and extract of the process samples were detected by the drying method and the hot extraction method of alcohol-soluble extract in the general rules of the 2020 edition of Chinese Pharmacopoeia（part Ⅳ）， and the contents of liquiritin apioside， liquiritin， isoliquiritin apioside， isoliquiritin， licoricesaponin G₂ and glycyrrhizic acid in the process samples were determined by high performance liquid chromatography（HPLC）. Then principal component analysis（PCA）， partial least squares-discriminant analysis（PLS-DA） and Spearman correlation analysis were used for clustering， discrimination and correlation analysis of the appearance color， moisture， extract and the contents of six internal components. Based on artificial neural network and random forest algorithm， the prediction model of processing degree of sf-GRR was established. On this basis， based on the five principles of quality marker（Q-Maker）， explore the monitoring Q-Maker of sf-GRR. ResultsThe color of Glycyrrhizae Radix et Rhizoma deepened after stir-frying， and the appearance color of the sample changed from light yellow to dark yellow during processing. During the stir-frying process， the moisture content showed a decreasing trend with the extension of processing time， while the extract content showed an increasing trend with the extension of processing time. After stir-frying， the contents of liquiritin apioside， liquiritin and licoricesaponin G₂ showed an overall decreasing trend， while the contents of isoliquiritin apioside and isoliquiritin increased， and the content of glycyrrhizic acid increased slightly. The correlation analysis showed that moisture was positively correlated with brightness（L^*） and red/green value（a^*）， and negatively correlated with yellow/blue value（b^*） and total color difference（E^*ab）. Isoliquiritin apioside and isoliquiritin had negative correlation with L^* and a^*， and positive correlation with b^* and E^*ab. The processing process of sf-GRR could be divided into two stages of the early stage（0-14 min） and the late stage（15-17 min）， and could be divided into three stages of the early stage（0-6 min）， the middle stage（7-14 min） and the late stage（15-17 min） by combining the moisture， extract， the contents of 6 components and color values. Based on artificial neural network analysis and random forest algorithm， isoliquiritin apioside， isoliquiritin， liquiritin and glycyrrhizic acid were selected as monitoring markers for sf-GRR. ConclusionBased on the analysis of the exterior-interior indicators of process samples of sf-GRR， this paper ultimately identifies four processing monitoring markers， which can provide a basis for optimizing the processing technology of sf-GRR.

Objective:To investigate the current status of knowledge, attitude, and practice (KAP) of intensive care unit (ICU) medical staff for post-intensive care syndrome (PICS) and explore its influencing factors.Methods:The cross-sectional investigation study with stratified sampling was conducted. From June to September 2024, ICU medical staff from general hospitals in 5 regions (Chongqing, Beijing, Shaanxi, Jiangsu, and Gansu) were selected as the research subjects. The KAP of PICS questionnaire was distributed in the form of an electronic questionnaire. Observation indicators: (1) results of the questionnaire survey; (2) general information of ICU medical staff; (3) KAP scores of PICS and the correlation among various dimensions; (4) analysis of influencing factors for KAP of PICS. Comparison of measurement data with normal distribution between groups was conducted using the independent samples t test. One-way analysis of variance (ANOVA) was applied for com-parison among multiple groups, and post-hoc LSD test was used for pairwise comparison. Comparison of count data between groups was conducted using the chi-square test. Pearson correlation analysis was adopted for correlation analysis. Multiple linear regression analysis was used for univariate and multivariate analyses. Results:(1) Results of questionnaire survey. A total of 410 questionnaires were distributed and retrieved, among which 408 were valid, with an effective rate of 99.512%(408/410). (2) General information of ICU medical staff. Among the 408 ICU medical staff, there were 79 males and 329 females. Eight cases were under 25 years old, 248 cases were 25-35 years old, 132 cases were 36-40 years old, and 20 cases were over 40 years old. In terms of professional title, there were 10 junior nurses, 130 junior nurse practitioners, 228 intermediate nurse practitioners, and 40 senior nurse practitioners. About the educational background, 34 cases had a junior college degree, 347 cases had a bachelor's degree, and 27 cases had a master's degree or above. Regarding the hospital level, 25 nurses worked in secondary hospitals and 383 cases in tertiary hospitals. In terms of ICU type, 181 cases were from specialized ICU and 227 cases from general ICU. About working experience in ICU, 41 nurses had less than 5 years, 207 cases had 5-10 years, and 160 cases had more than 10 years. (3) KAP scores of PICS and the correlation among various dimensions. The total KAP score of PICS among the 408 ICU medical staff was 88.7±14.2, with 40.2±9.2 for the knowledge dimension, 22.0±5.6 for the attitude dimension, and 26.5±6.3 for the practice dimension. Pearson correlation analysis showed that the knowledge dimension of PICS among ICU medical staff was significantly positively correlated with both the attitude dimension and the practice dimension ( r=0.15, 0.69, P<0.05); the attitude dimension was positively correlated with the practice dimension ( r=0.23, P<0.05).(4) Analysis of influencing factors for KAP of PICS. Results of multivariate analysis showed that age (25-35 years old, 36-40 years old, over 40 years old), educational background and hospital level were independent influencing factors for the KAP of PICS among ICU medical staff ( t=2.23, 1.97, 2.84, 0.15, 2.04, P<0.05). Conclusions:The KAP of PICS among ICU medical staff is relatively good, while their practical ability still needs to be improved. Age, educational background, and hospital level are independent influencing factors for the KAP of PICS among ICU medical staff.

Aim To explore the mechanism by which dioscin regulates IL-17+γδT cells in the treatment of arthritis.Methods A collagen-induced arthritis(CIA)model was established in DBA/1 mice using bovine type Ⅱ collagen.The mice were randomly divid-ed into the CIA model group,methotrexate(MTX)positive control group,and dioscin low-dose(Dioscin-L),medium-dose(Dioscin-M),and high-dose(Dios-cin-H)groups.After intervention,the therapeutic effects were evaluated using scoring methods.Joint pathological damage was analyzed by hematoxylin and eosin(HE)staining.The levels of anti-collagen-spe-cific antibodies and the pro-inflammatory cytokine IL-17 were measured by ELISA.The expressions of γδT cells and their subtypes,as well as the secretion level of IL-17,were detected by flow cytometry.Results Dioscin significantly reduced the arthritis severity score in collagen-induced arthritis(CIA)mice,alleviated joint pathological damage,inhibited the production of IL-17 by splenic lymphocytes and the levels of anti-col-lagen-specific antibodies total IgG and IgG3,and de-creased the proportion of γδT cells in the lymph nodes,splenic γδT cells,and the Vδ4+T-cell subset.The level of IL-17 produced by the Vδ4 subtype in the lymph nodes of the intervention groups was lower than that in the model group,but the difference was not sta-tistically significant.Conclusion Dioscin has signifi-cant therapeutic effect on CIA,and its mechanism may be through the inhibition of γδT cells,but it is unlikely to be related to IL-17 derived from γδT cells.

Objective To explore the value of deep learning image reconstruction(DLIR)by comparing subjective and objec-tive evaluation of DLIR and adaptive statistical iterative reconstruction(ASIR-V)images in gastric cancer CT.Methods Abdominal CT images in the venous phase of 80 untreated patients with primary gastric cancer were included,and five CT reconstruction meth-ods of 50％ASIR-V,80％ASIR-V,DLIR-low(DLIR-L),DLIR-medium(DLIR-M)and DLIR-high(DLIR-H)were adopted,respec-tively.The objective evaluation included background standard deviation(SD),signal-to-noise ratio(SNR),contrast-to-noise ratio(CNR)values and pericancerous fat density resolution.The subjective evaluation included SD,overall image quality,the display of gastric cancer lesions,and diagnostic confidence in whether the serosal surface of the gastric wall was infiltrated.Results The subjective and objective evalua-tion indicators showed statistically significant differences among the five reconstruction models(P＜0.001).In terms of objective evalua-tion,the SD value of gastric cancer lesions in the DLIR-H was the lowest,while the SNR and CNR values were the highest among the five groups.In terms of subjective evaluation,the DLIR-M had the highest scores in gastric cancer lesions display,overall image quality and diagnostic confidence among the five groups.Conclusion Compared with ASIR-V,DLIR can significantly reduce image noise and improve image quality,and DLIR-M and DLIR-H are respectively the optimal subjective and objective reconstruction models for showing gastric cancer lesions.

Objective To analyze the symptomatic improvement effects of vitamin D in children with autism spectrum disorder(ASD)based on the microbiota-gut-brain axis.Methods Seventy-two children with ASD were randomly divided into an observation group and a control group,with 36 cases in each group.Three cases dropped out in the control group.The observation group received 1200 IU/day of vitamin D supplementation in addition to conventional rehabilitation training,while the control group received only conventional rehabilitation training.The intervention lasted for 12 weeks.Assessments were conducted before and after the intervention using the childhood autism rating scale(CARS),autism behavior checklist(ABC),and repetitive behavior scale-revised(RBS-R).Resting-state functional connectivity of the brain was measured using near-infrared functional imaging,and serum levels of 25(OH)D3,inflammatory cytokines,and gut microbiota were analyzed.The differences in these indicators before and after the intervention were compared between the two groups to evaluate clinical efficacy.Results The between-group differences in pre-and post-intervention changes showed that the observation group had significantly greater improvements than the control group in the following measures:CARS scores(-5.92±1.40 vs.-2.55±1.43),RBS-R scores(-5.99±1.01 vs.-3.10±1.47),resting-state brain functional connectivity(0.19±0.15 vs.0.10±0.18),serum 25(OH)D3 levels[(34.89±8.18)ng/mL vs.(0.68±6.73)ng/mL],serum interleukin-6(IL-6)levels[(-6.60±6.07)pg/mL vs.(-0.74±9.45)pg/mL],IL-1β levels[(-2.56±1.33)pg/mL vs.(-0.04±2.13)pg/mL],and tumor necrosis factor-α(TNF-α)levels[(-4.09±3.85)pg/mL vs.(0.21±4.05)pg/mL](P<0.05).Post-intervention,significant differences in gut microbial β-diversity were observed between the two groups(R2=0.030,P=0.040,Adonis).LEfSe analysis revealed that the observation group exhibited enrichment in Clostridia(LDA=4.747,P=0.003),Clostridiales(LDA=4.747,P=0.003),Clostridiaceae(LDA=3.476,P=0.001),Lachnospiraceae(LDA=4.709,P=0.004),Odoribacteraceae(LDA=3.458,P=0.027),Odoribacter(LDA=3.458,P=0.027),Burkholderiales(LDA=3.339,P=0.038),Firmicutes(LDA=4.764,P=0.003),and Betaproteobacteria(LDA=3.338,P=0.037).Conclusion Vitamin D supplementation can modulate gut microbial diversity in children with ASD,significantly influence the abundance of specific gut microbiota,reduce systemic inflammatory cytokines,enhance brain functional connectivity,and alleviate clinical symptoms of ASD.