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 evaluate the diagnostic performance of the minimum-cost-path-based CT angiography-derived fractional flow reserve(MCP-FFR)and the deep learning-driven CT angiography-derived fractional flow reserve(DeepCL-FFR),and to particularly explore the potential value of the DeepCL algorithm in improving diagnostic accuracy within the"gray zone."Methods A retrospective analysis was conducted on 151 coronary vessels from 109 patients with coronary artery disease,who were hospitalized at the General Hospital of the People's Liberation Army between January 2020 and June 2021.Pearson correlation and Bland-Altman plots were employed to assess the correlation and agreement of the two CT-FFR methods with invasive FFR.A CT-FFR range of 0.70-0.80 was defined as the diagnostic"gray zone."The accuracy,sensitivity,specificity,positive predictive value,and negative predictive value for detecting hemodynamic abnormalities were calculated and analyzed.The DeLong test was used to compare the areas under the receiver operating characteristic curves(AUC)between the two CT-FFR calculation methods.Results Both CT-FFR methods exhibited a positive correlation with invasive FFR(MCP-FFR:r=0.75,P＜0.001;DeepCL-FFR:r=0.86,P＜0.001)and showed good agreement(MCP-FFR:mean difference=0.010,P=0.351;DeepCL-FFR:mean difference=-0.003,P=0.772).Both DeepCL-FFR(AUC 0.97,95％CI 0.94-0.99)and MCP-FFR(AUC 0.92,95％CI 0.88-0.97)demonstrated favorable diagnostic performance for detecting hemodynamic abnormalities(P=0.122).In the"gray zone"for hemodynamic abnormality,the diagnostic accuracy of MCP-FFR was 68.8％,whereas DeepCL-FFR increased it to 89.7％.DeepCL-FFR also exhibited superior diagnostic performance(AUC 0.89,95％CI 0.73-0.99)within the"gray zone,"which was significantly higher than that of MCP-FFR(AUC 0.71,95％CI 0.54-0.87)(P＜0.001).Conclusions The deep learning-driven coronary centerline extraction algorithm,DeepCL,demonstrates superior diagnostic performance in CT-FFR for detecting hemodynamic abnormalities,particularly by significantly improving diagnostic accuracy in the"gray zone."

Objective:To investigate the application value of photon-counting detector CT (PCD-CT) in preoperative identification of critical anatomical structures and surgical assessment in pancreatic cancer, and to compare its performance with conventional energy-integrating detector CT (EID-CT) in delineating tumor margins, vascular structures, and neural anatomy.Methods:This single-center retrospective matched case-control study included 25 patients with pathologically confirmed pancreatic ductal adenocarcinoma who underwent PCD-CT enhanced scanning and curative surgery at Peking Union Medical College Hospital between February and June 2025 (PCD-CT group). These patients were matched in a 1∶2 ratio to 50 patients who underwent EID-CT between January 2016 and December 2024 and subsequently received curative surgery (EID-CT group). Tumor boundary clarity, vascular visualization scores, and neural structure visibility were subjectively evaluated using the Likert scoring system. The assessed vessels included the celiac artery, common hepatic artery, superior mesenteric artery, splenic artery, portal vein, superior mesenteric vein, splenic vein, and pancreaticoduodenal arterial arcade. Imaging-based assessment of structural involvement was compared with intraoperative findings and pathological results to calculate diagnostic accuracy. Surgeons rated the usefulness of PCD-CT images for identifying key structures and determining resectability using a 5-point Likert scale. The Mann-Whitney U test was used for group comparisons of subjective scores, and categorical data were analyzed using the χ2 test or Fisher exact test. Results:The PCD-CT group showed significantly higher scores for tumor boundary clarity, vascular visualization, and neural structure detectability than those of the EID-CT group (all P<0.05). The accuracy of assessing superior mesenteric vein involvement was 96.0% (24/25) in the PCD-CT group and 72.0% (36/50) in the EID-CT group, with a significant difference ( χ2=6.00, P=0.014). Postoperative surgeon evaluations indicated that PCD-CT provided substantial assistance for both key structure identification [5 (5, 5)] and resectability assessment [5 (4, 5)]. Conclusion:PCD-CT demonstrates superior performance over EID-CT in preoperative delineation of tumor margins, vascular structures, and neural anatomy and in the assessment of structural involvement in pancreatic cancer. It provides valuable anatomical information to support preoperative evaluation and surgical decision-making.

Objective:This paper investigates residents'awareness and preference for Traditional Chinese Medicine intelligent diagnostic device(hereinafter referred to as the device),and provides basis and suggestions for further promoting the integrated development of artificial intelligence and traditional Chinese medicine clinical diagnosis.Method:A random sampling survey was conducted,and a Discrete Choice Experiment was designed to conduct an offline survey in Beijing.Use chi square test,count analysis,and conditional Logit model for data analysis.Result:A total of 480 valid questionnaires were collected and surveyed.Most respondents have heard of it(58.96%),a few have used it(31.67%),and most would recommend the device(71.25%).Knowing and using experience will increase the probability of recommendation.Residents attach the highest importance to annual average expenses;More inclined to use devices in the community that can see family data,connect data and hospitals,monitor electrocardiogram,provide comprehensive health reports,and have low annual costs;Willing to pay an additional 572 yuan per year for the comprehensive health report device.Conclusion:There should be more collaboration with hospitals in usage scenarios and cloud data.In addition,manufacturers should enrich output information and service methods of the e.

Objective:To investigate the application value of photon-counting detector CT (PCD-CT) in preoperative identification of critical anatomical structures and surgical assessment in pancreatic cancer, and to compare its performance with conventional energy-integrating detector CT (EID-CT) in delineating tumor margins, vascular structures, and neural anatomy.Methods:This single-center retrospective matched case-control study included 25 patients with pathologically confirmed pancreatic ductal adenocarcinoma who underwent PCD-CT enhanced scanning and curative surgery at Peking Union Medical College Hospital between February and June 2025 (PCD-CT group). These patients were matched in a 1∶2 ratio to 50 patients who underwent EID-CT between January 2016 and December 2024 and subsequently received curative surgery (EID-CT group). Tumor boundary clarity, vascular visualization scores, and neural structure visibility were subjectively evaluated using the Likert scoring system. The assessed vessels included the celiac artery, common hepatic artery, superior mesenteric artery, splenic artery, portal vein, superior mesenteric vein, splenic vein, and pancreaticoduodenal arterial arcade. Imaging-based assessment of structural involvement was compared with intraoperative findings and pathological results to calculate diagnostic accuracy. Surgeons rated the usefulness of PCD-CT images for identifying key structures and determining resectability using a 5-point Likert scale. The Mann-Whitney U test was used for group comparisons of subjective scores, and categorical data were analyzed using the χ2 test or Fisher exact test. Results:The PCD-CT group showed significantly higher scores for tumor boundary clarity, vascular visualization, and neural structure detectability than those of the EID-CT group (all P<0.05). The accuracy of assessing superior mesenteric vein involvement was 96.0% (24/25) in the PCD-CT group and 72.0% (36/50) in the EID-CT group, with a significant difference ( χ2=6.00, P=0.014). Postoperative surgeon evaluations indicated that PCD-CT provided substantial assistance for both key structure identification [5 (5, 5)] and resectability assessment [5 (4, 5)]. Conclusion:PCD-CT demonstrates superior performance over EID-CT in preoperative delineation of tumor margins, vascular structures, and neural anatomy and in the assessment of structural involvement in pancreatic cancer. It provides valuable anatomical information to support preoperative evaluation and surgical decision-making.

Objective To establish a backpack-based field emergency medical rescue equipment system to enhance emergency rescue efficiency.Methods A backpack-based field emergency medical rescue equipment system was preliminarily constructed with the concept of medical treatment in echelons and prolonged field care(PFC)and the method of capability-based equipment need analysis;with the Delphi method 15 experts from relevant fields were invited to execute two rounds of questionnaire consultations,and the final equipment system was determined after the equipment varieties and quantities were revised based on the expert opinions.Results The response rate for the two rounds of expert questionnaire surveys was 100%.The experts'authority coefficients were 0.8734 and 0.87,respectively;Kendall coefficients were 0.232 and 0.345(both P<0.001),indicating statistically significant results.Ultimately,a backpack-based field emer-gency medical rescue equipment system comprising 15 backpacks and 158 individual pieces of equipment was established.Conclusion The established system demonstrates a certain degree of specificity and practicability,providing references for the equipment allocation and utilization of emergency medical rescue teams.[Chinese Medical Equipment Journal,2025,46(10):17-22]

Objective:This paper investigates residents'awareness and preference for Traditional Chinese Medicine intelligent diagnostic device(hereinafter referred to as the device),and provides basis and suggestions for further promoting the integrated development of artificial intelligence and traditional Chinese medicine clinical diagnosis.Method:A random sampling survey was conducted,and a Discrete Choice Experiment was designed to conduct an offline survey in Beijing.Use chi square test,count analysis,and conditional Logit model for data analysis.Result:A total of 480 valid questionnaires were collected and surveyed.Most respondents have heard of it(58.96%),a few have used it(31.67%),and most would recommend the device(71.25%).Knowing and using experience will increase the probability of recommendation.Residents attach the highest importance to annual average expenses;More inclined to use devices in the community that can see family data,connect data and hospitals,monitor electrocardiogram,provide comprehensive health reports,and have low annual costs;Willing to pay an additional 572 yuan per year for the comprehensive health report device.Conclusion:There should be more collaboration with hospitals in usage scenarios and cloud data.In addition,manufacturers should enrich output information and service methods of the e.

Objective To explore the correlation between the rs7296288 single nucleotide polymorphism(SNP)of the DHH gene and the onset of depression.Methods From March 2018 to December 2019,480 patients with depression in Sichuan Provincial People's Hospital,Jining Mental Hospital,Yunnan Mental Health Center were collected as the case group,and 329 patients without depression were collected as the control group.Peripheral blood samples were collected and DNA was extracted.After multiple amplification and high-throughput sequencing,statistical software was used to analyze the relevant data.Results The rs7296288 polymorphism of the DHH gene,the AA genotype was 32.9％in the control group and 36.7％in the case group,with no statistical difference;the AC genotype was 52.8％in the control group and 47.7％in the case group,with no statistical difference;the CC genotype was 14.3％in the control group and 15.6％in the case group,with no statistical difference.The co-dominant,dominant,and recessive statistical models were not statistically significant.Subgroup analysis of the degree of depressive episodes,suicide attempts,and first-episode patients did not find an association between the rs7296288 SNP locus of the DHH gene and the clinical features of depression,that is,the SNP rs7296288 of the DHH gene had no significant correlation with depression.Conclusion The rs7296288 polymorphism of DHH gene is not correlated with the pathogenesis of depression.

Objective To establish a backpack-based field emergency medical rescue equipment system to enhance emergency rescue efficiency.Methods A backpack-based field emergency medical rescue equipment system was preliminarily constructed with the concept of medical treatment in echelons and prolonged field care(PFC)and the method of capability-based equipment need analysis;with the Delphi method 15 experts from relevant fields were invited to execute two rounds of questionnaire consultations,and the final equipment system was determined after the equipment varieties and quantities were revised based on the expert opinions.Results The response rate for the two rounds of expert questionnaire surveys was 100%.The experts'authority coefficients were 0.8734 and 0.87,respectively;Kendall coefficients were 0.232 and 0.345(both P<0.001),indicating statistically significant results.Ultimately,a backpack-based field emer-gency medical rescue equipment system comprising 15 backpacks and 158 individual pieces of equipment was established.Conclusion The established system demonstrates a certain degree of specificity and practicability,providing references for the equipment allocation and utilization of emergency medical rescue teams.[Chinese Medical Equipment Journal,2025,46(10):17-22]