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.

Objectives: . The prognostic value of the pretreatment albumin-to-alkaline phosphatase ratio (AAPR) in head and neck cancer (HNC) remains uncertain. This meta-analysis aimed to evaluate the predictive role of AAPR for survival outcomes in patients with HNC. Methods: . A comprehensive search of the Cochrane Library, PubMed, and Embase databases was conducted to identify relevant studies published up to July 30, 2024. We included studies on AAPR and survival outcomes in HNC patients. Results: . Eight studies comprising 1,737 HNC patients were analyzed using random-effects models. Lower AAPR values were significantly correlated with worse overall survival (hazard ratio [HR], 2.08), progression-free survival (HR, 2.00), and disease-free survival (HR, 2.18). Sensitivity analyses confirmed the robustness of these results, with no significant publication bias detected. Conclusion . Our findings suggest that pretreatment AAPR could serve as a valuable and cost-effective prognostic indicator in HNC, potentially aiding clinicians in risk stratification and treatment decision-making. However, additional validation studies are warranted to confirm its clinical applicability.

Methods: The clinical data of 26 patients diagnosed with irreducible atlantoaxial dislocation complicated by atlantodental bony obstruction were analyzed retrospectively. All patients underwent anterior retropharyngeal atlantodentoplasty, followed by posterior occipitocervical fusion. Details including surgical duration and blood loss volume were recorded. Radiographic data such as the anterior atlantodental interval, O–C2 angle, space available for the cord, clivus–canal angle, and cervical medullary angle, and clinical data including the Japanese Orthopedic Association (JOA) score were assessed. The fusion time of the grafted bone and the development of complications were examined. Results: In patients undergoing anterior retropharyngeal atlantodentoplasty, the surgical duration and blood loss volume were 120.1±16.4 minutes and 100.6±33.5 mL, respectively. The anterior atlantodental interval decreased significantly after the surgery (p <0.001). The O–C2 angle, space available for the cord, clivus–canal angle, and cervical medullary angle increased significantly after the surgery (p <0.001). The JOA score during the latest follow-up significantly increased compared with that before the surgery (p <0.001). The improvement rate of the JOA score was 80.8%±18.1%. The fusion time of the grafted bone was 3–8 months, with an average of 5.7±1.5 months. In total, 11 patients presented with postoperative dysphagia and three with irritating cough. However, none of them exhibited other major complications. Conclusions Anterior retropharyngeal atlantodentoplasty can anatomically reduce the atlantoaxial joint with a satisfactory clinical outcome in patients with irreducible atlantoaxial dislocation with atlantodental bony obstruction.

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.

Objective To construct radiomics-semantic models to predict the treatment resistance of chemoradiotherapy in brain gliomas based on MRI and clinical data of multicenter patients.Methods Among 2 108 brain gliomas patients from five medical institutions,132 patients had residual gliomas after surgery.The clinical risk factors and multimodal MRI were collected.All patients were divided into training set(n=95)and validation set(n=37).The treatment response of gliomas after standardized chemoradiotherapy were divided into resistant and non-resistant types.The semantic features of MRI were evaluated by two radiologists.Three different segmentation regions of interest(ROI)were delineated to extract radiomics features.And that three groups of radiomics models were con-structed based on different sequence MRIs.The radiomics model with the best predictive efficacy in each group was selected and combined with MRI semantic features,three radiomics-semantic models(combined models)were established.Finally,a MRI semantic model,three groups of radiomics models and three combined models were developed.Results Comparisons between the different models showed that the radiomics-semantic model based on pre-operative T2-fluid attenuated inversion recovery(FLAIR)sequence,had the best predictive efficacy,the area under the curve(AUC)in the training and validation sets were 0.866[95％confidence interval(CI)0.790-0.942]and 0.810(95％CI 0.667-0.952),respectively.The radiomics-semantic model based on postoperative T1 WI sequence performed the second best,with the AUC of the training and validation sets being 0.812(95％CI 0.726-0.898)and 0.711(95％CI 0.541-0.881),respectively.Conclusion The combined models based on MRI radiomics and semantic features are able to predict the treatment resistance of chemoradiotherapy in brain gliomas patients,and may be used as an important basis for optimizing treatment.

Objective:To investigate the predictive value of serum 25 hydroxyvitamin D3[25 (OH) D3], insulin-like growth factor 1 (IGF-1) and bone mineral density (BMD) in the occurrence of osteoporosis (OP) in postmenopausal women.Methods:A total of 87 postmenopausal women admitted to Shanxi Children’s Hospital from Jan. 2020 to Dec. 2023 were chosen and separated into OP group ( n=40) and non-OP group ( n=47) . The differences of clinical features, serum 25 (OH) D3, IGF-1 and BMD were compared, and the correlation analysis between serum 25 (OH) D3, IGF-1 and BMD (including L 1-4 BMD, femoral neck BMD and total hip BMD) was analyzed. Multivariate Logistic regression model and receiver operating characteristic (ROC) curve were used to analyze the influencing factors of OP occurrence in postmenopausal women and the predictive value of serum 25 (OH) D3 and IGF-1 combined with BMD for OP occurrence. Results:Compared with non-OP group, there were no significant differences in age, body mass index (BMI) , menopause time, serum calcium, serum phosphorus, alanine aminotransferase (ALT) , or aspartate aminotransferase (AST) levels in OP group ( t=1.42, 1.03, 1.71, 0.93, 0.76, 0.43, 0.04; P=0.161, 0.306, 0.092, 0.354, 0.452, 0.670, 0.966) , but the proportion of diabetes mellitus significantly increased ( χ2=4.37, P=0.037) . Compared with non-OP group, the levels of serum 25 (OH) D3 and IGF-1 and the values of L1-4 BMD, femoral neck BMD and total hip BMD in OP group significantly decreased ( t=5.37, 4.83, 8.31, 2.01, 3.11; P<0.001, P<0.001, P<0.001, P=0.048, P=0.003) . Correlation analysis showed that serum 25 (OH) D3 and IGF-1 were significantly positively correlated with L 1-4 BMD, femoral neck BMD and total hip BMD ( r=0.37, 0.42, 0.29, 0.33, 0.28, 0.29; P<0.001, P<0.001, P=0.024, P=0.015, P=0.032, P=0.021) . Multivariate Logistic analysis showed that serum 25 (OH) D3, IGF-1 and L 1-4 BMD were independent influencing factors for OP occurrence in postmenopausal women ( P=0.007, 0.019, 0.001) ROC curve showed that the area under the curve (AUC) values of serum 25 (OH) D3, IGF-1, L 1-4 BMD and their combination in the prediction of the occurrence of OP in postmenopausal women were 0.764, 0.752, 0.957 and 0.985, respectively. Conclusion:Serum 25 (OH) D3, IGF-1 and L 1-4 BMD can be used as predictors of OP occurrence in postmenopausal women, and the combined value of the three is higher.

Objective:To explore the mechanism by which atractylodin regulates the ROS (reactive oxygen species) /AKT signaling pathway to induce apoptosis and cell cycle arrest in endometrial cancer cells, and to provide theoretical support for its potential application in the treatment of endometrial cancer.Methods:Endometrial cancer cell lines (Ishikawa and HEC-1A) were selected as experimental models. Cells were treated with different concentrations (1, 5, 10, 20 μM) of atractylodin. Cell proliferation was assessed by CCK-8 assay, apoptosis was analyzed by flow cytometry (FCM), and protein expression levels of AKT, p-AKT, Bcl-2, Caspase-3, and other AKT signaling pathway-related proteins were detected by Western blot. ROS levels were measured by flow cytometry.Results:Atractylodin treatment significantly inhibited the proliferation of endometrial cancer cells. Flow cytometry analysis revealed a marked increase in the apoptotic cell population. Western blot results showed that atractylodin treatment significantly decreased p-AKT expression, reduced Bcl-2 protein levels, and increased Caspase-3 expression. ROS level analysis showed that atractylodin treatment significantly elevated intracellular ROS generation, suggesting that atractylodin might induce AKT pathway inhibition through ROS, leading to cell cycle arrest and apoptosis.Conclusions:Atractylodin regulates the ROS/AKT signaling pathway to induce apoptosis and cell cycle arrest in endometrial cancer cells, exhibiting potential anti-endometrial cancer effects. This study provides new theoretical evidence for the application of atractylodin in the treatment of endometrial cancer and reveals its underlying mechanisms.

Objective To compare the effects of different detector combinations of 320-row CT on the image quality and radiation dose of head CT to explore the feasibility of using a wide detector for head CT scanning.Methods Totally 100 patients underwent head CT scanning due to trauma or cerebrovascular disease at some hospital from June to August 2023 were collected prospectively and divided into group A and group B by using block randomization grouping method,with the length of the block group being 2 and 50 patients in each group.In group A,all the detectors had the widths at z-axis direction being 40×0.5 mm and head scanning was completed after multiple exposures;in group B,detector combinations with widths of 280×0.5 mm or 320×0.5 mm were chosen based on the patient's head size in the head-foot direction(z-axis direction),and head scanning was performed with a single-turn exposure.The remaining scanning and image reconstruction parameters in the two groups were kept completely consistent.The head image quality of the 2 groups was evaluated objectively and scored subjectively by 2 radiologists.The volume CT dose index(CTDIvol),dose length product(DLP)and exposure time of the 2 groups were recorded,and the effective dose(ED)was calculated.SPSS 22.0 software was used for statistical analysis.Results In terms of objective evaluation of image quality,at the level of the parietal skull group B had the CT value of gray matter,image noise and contrast to noise ratio(CNR)of the images higher than those of group A,and the differences were statistically significant(all P<0.05);at the level of the posterior skull group B had the CT values of gray and white matter,image noise and air noise lower while CNR higher than those of group A,and the differences were statistically significant(all P<0.05).In terms of subjective scoring of image quality,at the levels of parietal and posterior skull group A behaved better than group B,and the differences were statistically significant(all P<0.05).In group A 5 patients had obvious motion artifacts affecting the diagnosis and the image quality scores not higher than 2,and secondary scanning had to be carried out;In group B all the patients had no obvious motion artifacts and met the diagnosis requirements.When compared with group A Group B had the CTDIvol,DLP,ED and exposure time decreased by 17.44%,17.24%,17.48%and 85.53%,respectively,and the differences were statistically significant(all P<0.05).Conclusion A wide detector gains advantages over a 20 mm detector in image quality when 320-row CT is used for head CT scanning,with the diagnosis requirements satisfied.[Chinese Medical Equipment Journal,2025,46(4):57-62]

OBJECTIVE To carry out regular monitoring of carbapenem-resistant Klebsiella pneumoniae(CRKP)contamination status in the environment of intensive care unit(ICU)and take targeted prevention and control measures so as to reduce the incidence of hospital-associated infections with multidrug-resistant organisms(MDROs).METHODS The surfaces of surroundings of the patients who were colonized and infected with CRKP in the ICU of grade A tertiary hospital of Shanghai and the hands of relevant staff were sampled by stages from Jan 1,2021 to Jun 30,2024.The distribution of the CRKP strains in the surroundings were analyzed according to the locations positive for CRKP,and the disinfection measures were accordingly and continuously modified.The trend of isolation rate of CRKP strains from the ICU patients was analyzed during the time period when the measures were implemented.RESULTS Totally 266 environmental samples were collected during the baseline period(from Jan.1 2021 to Dec.31 2021),265 during intervention period(from Jan.1 2022 to Dec.31 2023),274 during con-solidation period(from Jan.1 to Jun.30 2024);the isolation rates of the CRKP strains were 4.51％,4.91％and 3.65％,respectively.The isolation rate of the strains was highest from the bed unit(10.40％),followed by the article for public use(6.74％),articles used by health care workers(2.98％)and diagnosis and treatment arti-cles(1.91％).The isolation rate of CRKP of the patients was 24.75％during the baseline period,15.48％during the intervention period,5.69％during the consolidation period,showing a continuously downward trend(x2=30.330,P＜0.001).CONCLUSION It is necessary to regularly carry out the environmental monitoring of CRKP strains,seek for the weak links of environmental disinfection and implement the intensified prevention and control measures so as to reduce the incidence of CRKP infection,which may provide theoretical bases for effective control of the CRKP strains.