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.

Immobilized enzyme-based enzyme electrode biosensors, characterized by high sensitivity and efficiency, strong specificity, and compact size, demonstrate broad application prospects in life science research, disease diagnosis and monitoring, etc. Immobilization of enzyme is a critical step in determining the performance (stability, sensitivity, and reproducibility) of the biosensors. Random immobilization (physical adsorption, covalent cross-linking, etc.) can easily bring about problems, such as decreased enzyme activity and relatively unstable immobilization. Whereas, directional immobilization utilizing amino acid residue mutation, affinity peptide fusion, or nucleotide-specific binding to restrict the orientation of the enzymes provides new possibilities to solve the problems caused by random immobilization. In this paper, the principles, advantages and disadvantages and the application progress of enzyme electrode biosensors of different directional immobilization strategies for enzyme molecular sensing elements by specific amino acids (lysine, histidine, cysteine, unnatural amino acid) with functional groups introduced based on site-specific mutation, affinity peptides (gold binding peptides, carbon binding peptides, carbohydrate binding domains) fused through genetic engineering, and specific binding between nucleotides and target enzymes (proteins) were reviewed, and the application fields, advantages and limitations of various immobilized enzyme interface characterization techniques were discussed, hoping to provide theoretical and technical guidance for the creation of high-performance enzyme sensing elements and the manufacture of enzyme electrode sensors.

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.

Microglia, the resident immune cells in the central nervous system (CNS), rapidly transition from a resting to an active state in the acute phase of ischemic brain injury. This active state mediates a pro-inflammatory response that can exacerbate the injury. Targeting the pro-inflammatory response of microglia in the semi-dark band during this acute phase may effectively reduce brain injury. Shionone (SH), an active ingredient extracted from the dried roots and rhizomes of the genus Aster (Asteraceae), has been reported to regulate the inflammatory response of macrophages in sepsis-induced acute lung injury. However, its function in post-stroke neuroinflammation, particularly microglia-mediated neuroinflammation, remains uninvestigated. This study found that SH significantly inhibited lipopolysaccharide (LPS)-induced elevation of inflammatory cytokines, including interleukin-1β (IL-1β), tumor necrosis factor-α (TNF-α), and inducible nitric oxide synthase (iNOS), in microglia in vitro. Furthermore, the results demonstrated that SH alleviated infarct volume and improved behavioral performance in middle cerebral artery occlusion (MCAO) mice, which may be attributed to the inhibition of the microglial inflammatory response induced by SH treatment. Mechanistically, SH potently inhibited the phosphorylation of serine-threonine protein kinase B (AKT), mammalian target of rapamycin (mTOR), and signal transducer and activator of transcription 3 (STAT3). These findings suggest that SH may be a potential therapeutic agent for relieving ischemic stroke (IS) by alleviating microglia-associated neuroinflammation.
Animals ; Microglia/immunology* ; Mice ; Male ; Mice, Inbred C57BL ; Brain Ischemia/immunology* ; Neuroinflammatory Diseases/drug therapy* ; Neuroprotective Agents/administration & dosage* ; Interleukin-1beta/genetics* ; STAT3 Transcription Factor/genetics* ; TOR Serine-Threonine Kinases/genetics* ; Tumor Necrosis Factor-alpha/genetics* ; Proto-Oncogene Proteins c-akt/immunology* ; Nitric Oxide Synthase Type II/genetics* ; Lipopolysaccharides

Ambient air pollution is increasingly being recognized as a risk factor for heart failure; however, its effects on cardiac biomarkers remain unclear. This scoping review assessed the existing evidence on the association between air pollution and cardiac biomarkers in heart failure, described the key concepts, synthesized data, and identified research gaps. Following the PRISMA-ScR guidelines, PubMed, Embase, Web of Science, and CNKI databases were searched for studies on air pollution, heart failure, and biomarkers. A total of 765 records were screened, and 81 full texts were assessed for eligibility, resulting in 15 studies. The results showed that the exposure to particulate matter was associated with elevated N-terminal pro-B-type natriuretic peptide and troponin levels. Several studies have linked particulate matter exposure to a higher cardiovascular risk and heart failure biomarkers. Inflammatory and oxidative stress markers were consistently elevated across studies, supporting the biological relevance of these associations. However, few studies have focused specifically on populations with heart failure or clinically relevant biomarkers, and the evidence for gaseous pollutants remains inconclusive. These findings highlight the need to integrate environmental risk assessment into heart failure care and inform policy efforts to reduce the pollution-related cardiovascular burden. Further research should address these gaps through improved exposure assessments and the integration of mechanistic evidence.
Heart Failure/epidemiology* ; Biomarkers/metabolism* ; Humans ; Air Pollution/adverse effects* ; Air Pollutants/adverse effects* ; Particulate Matter/adverse effects* ; Environmental Exposure ; Natriuretic Peptide, Brain/blood* ; Oxidative Stress ; Troponin/blood*

Objective To investigate the regulatory mechanism of the central nervous system in patients with refractory overactive bladder (rOAB) using diffusion tensor imaging (DTI) and graph theory analysis. Methods A total of 43 rOAB patients (rOAB group) and 46 matched healthy controls (HC group) were recruited during May and Nov.2024. All participants were scanned with DTI, and surveyed with the overactive bladder symptom score (OABSS), and overactive bladder questionnaire (OAB-q). Their age, gender, height, weight, and educational years were collected.DTI plus graph theory analysis was employed to explore the alterations in global and local topological properties of the brain structural network in rOAB patients. Brain regions showing significant group differences in structural metrics [specifically, the right paracentral lobule (PCL.R) ]were further used as seed points for functional connectivity (FC) analysis. Correlations between the nodal clustering coefficient (NCp) of the identified region, FC strength, OABSS, and OAB-q score were investigated. Results The OABSS [8 (6,10) vs.0 (0,1) ]and OAB-q [71 (53,80) vs.20 (19,24) ]were higher in the rOAB group than the HC group (P<0.001). Graph theory analysis revealed no statistically significant differences in global network metrics between the two groups (P>0.05). However, the NCp was significantly higher in the PCL.R of rOAB group compared to HC group (P<0.05, FDR-corrected).FC analysis using the PCL.R as a seed region demonstrated significantly reduced FC value in the left cerebellar crus Ⅱ (Cerebelum_Crus2_L) of the rOAB group (P<0.05, FDR-corrected). Partial correlation analysis showed that the NCp of PCL.R was positively correlated with both OABSS (r=0.255, P=0.018) and OAB-q score (r=0.257, P=0.017). Conversely, the FC of Cerebelum_Crus2_L was significantly negatively correlated with OABSS (r=-0.545, P<0.001) and OAB-q score (r=-0.535, P<0.001). Conclusion Patients with rOAB exhibit distinct brain structural network alterations compared to healthy individuals, primarily manifestation in the NCp value of PCL.R increased, and the FC intensity of Cerebelum_Crus2_L is significantly weakened. These alterations in the topological properties of the structural network may be implicated in the pathogenesis of rOAB.

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 explore the expression of epidermal growth factor and nuclear transcrip-tion factor kappa B(NF-κB)in elderly gliomas and their roles in malignant progression of the dis-ease.Methods A total of 240 elderly glioma patients undergoing surgical resection in our hospital from January 2020 to January 2023 were enrolled and served as an observation group.Another 100 patients receiving surgical treatment due to traumatic brain injury in our hospital during the same period were recruited and served as the control group.Immunohistochemical assay was used to detect the expression of epidermal growth factor and NF-κB in brain tissue.Cox regression analy-sis was employed to determine the independent influencing factors of malignant progression in the elderly glioma patients.Results The observation group had significantly higher epidermal growth factor expression score and NF-κB expression score than the control group(7.44±1.16 vs 3.68±0.51,6.49±1.02 vs 3.56±0.64,P＜0.01).The age,tumor pathological grade,surgical approach,postoperative radiotherapy,and epidermal growth factor and NF-κB expression levels were inde-pendent factors affecting the progression of elderly glioma patients(P＜0.05,P＜0.01).Conclusion The epidermal growth factor and NF-κB expression levels are independent influen-cing factors of progressive disease in elderly glioma patients,and can serve as evaluation indicators for postoperative progression in the patients.

Objective:To develop a preoperative CT-based radiomics model integrating multidimensional features for the accurate prediction of TFE3-rearranged renal cell carcinoma（TFE3-rRCC）.Methods:This study retrospectively enrolled 865 pathologically confirmed renal cell carcinoma（RCC）patients in The First Affiliated Hospital of Naval Medical University from June 2013 to June 2023，including 60 cases of TFE3-rRCC and 805 cases of non-TFE3 RCC（comprising clear cell RCC，papillary RCC，and chromophobe RCC）. Among them，627 were male and 238 were female，with a mean age of（54.1 ± 12.7）years（range：14?82 years）. The median maximum tumor diameter was 4.0（2.6，6.0）cm. Based on the chronological order of CT examinations，the patients were divided into training（ n=478），validation（ n=206），and test（ n=181）sets in an approximate 6∶2∶2 ratio. Using precontrast and corticomedullary phase CT images，we extracted peritumoral imaging features，habitat features，3D radiomic features，and 2.5D deep learning radiomic features. A deep learning radiomics score（DLR-SCORE）prediction model was constructed using least absolute shrinkage and selection operator（LASSO）regression. The diagnostic performance of the model was evaluated by receiver operating characteristic（ROC）curve analysis，with the area under the curve（AUC）as the primary metric. Additionally，sensitivity，specificity，and accuracy were calculated based on the confusion matrix. Results:A total of 12 442 features were extracted from non-contrast and corticomedullary phase CT images，from which eight key features were selected to construct the DLR-SCORE model. The model demonstrated diagnostic accuracies for TFE3-rRCC of 98.5%（471/478）in the training set，81.6%（168/206）in the validation set，and 86.2%（156/181）in the test set. The AUC of ROC curve was 0.98（95% CI 0.96?1.00）in the training set，0.83（95% CI 0.71?0.94）in the validation set，and 0.88（95% CI 0.76?1.00）in the test set. In the test set，the DLR-SCORE model achieved a sensitivity of 88.9%（16/18）and a specificity of 85.9%（140/163）for detecting TFE3-rRCC. Conclusions:The DLR-SCORE model integrating multidimensional CT radiomics features demonstrated favorable predictive performance for TFE3-rRCC，offering a promising noninvasive tool to assist preoperative diagnosis.