BACKGROUND:Upper lumbar spinal stenosis is a multifactorial degenerative disorder of the spine.For narrowing of the spinal canal in the upper lumbar region(L1-L4),surgical decision-making is particularly complex.Existing minimally invasive surgeries each have their own advantages and limitations.Currently,there are few reports on biomechanical comparison and finite element analysis of different surgical methods for the treatment of high lumbar spinal stenosis.OBJECTIVE:To analyze the biomechanical impact of endoscopic unilateral laminotomy for bilateral decompression,transforaminal endoscopic lumbar decompression,and cross-overtop decompression in the treatment of upper lumbar spinal stenosis using endoscopy,and to verify the reliability and effectiveness of these three surgical techniques in treating upper lumbar spinal stenosis,providing a biomechanical basis for clinical decision-making.METHODS:The CT images of the lumbar spine of a healthy volunteer were selected,and the finite element model M0 of the normal lumbar L1-L5 segments was established using Mimics,Geomagic,Solid works,and Ansys software.The L2-L3 segment,representing upper lumbar characteristics,was chosen.Based on this model,the surgical models for endoscopic unilateral laminotomy for bilateral decompression(M1),transforaminal endoscopic lumbar decompression(M2),and cross-overtop decompression(M3)were established.Using software,the changes in the range of motion of the entire lumbar segment and the maximum Von Mises stress of the intervertebral discs were simulated and evaluated for each group of models under six loading conditions:flexion,extension,left lateral bending,right lateral bending,left rotation,and right rotation.RESULTS AND CONCLUSION:(1)Compared with model MO,the range of motion in M1,M2,and M3 increased under all six conditions,with M1 showing a greater increase.(2)M1 and M2 demonstrated significant increases in range of motion under forward bending,extension,and right rotation,while the increase under other conditions remained below 7％.(3)Compared with model M3,model M1 exhibited slightly increased overall joint range of motion during extension and left bending,while no significant changes were observed in other aspects,and the L1-L5 lumbar segments did not reach an unstable state.(4)In model M1,the maximum Von Mises stress of the intervertebral discs increased most significantly under flexion and extension loading conditions.However,under left lateral bending,right lateral bending,left rotation,and right rotation loading conditions,the increase did not exceed 5％.(5)These findings suggest that due to the sagittal anatomical characteristics of the facet joints,the unilateral laminotomy for bilateral decompression technique,while decompressing,involves resection of more facet joints,which impacts overall segmental stability.The transforaminal endoscopic lumbar decompression technique is suitable for patients with foraminal stenosis but cannot achieve complete decompression for those with severe ventral central stenosis.The Cross-Overtop technique effectively enlarges the volume of the central canal and lateral recess,optimizing decompression,and shows unique advantages in treating upper lumbar spinal stenosis.

OBJECTIVE:Postoperative recurrence is a common complication of percutaneous endoscopic lumbar discectomy for lumbar disc herniation,which can significantly increase the risk of reoperation.A well-performing risk prediction model can help identify high-risk groups early and prevent postoperative recurrence.This study systematically evaluated the risk prediction model for postoperative recurrence after percutaneous endoscopic lumbar discectomy to provide a reference for surgical decision-making.METHODS:The PubMed,Embase,Web of Science,CNKI,WanFang Data,VIP,and CBM were electronically searched to collect studies on the recurrence risk prediction models after percutaneous endoscopic lumbar discectomy from inception to July 1,2024.Two reviewers independently screened the literature and extracted data.The models' risk of bias,applicability,and report quality were assessed using prediction model risk of bias assessment tool(PROBAST)and Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis(TRIPOD)tools,respectively.Meta-analysis of postoperative recurrence rate of percutaneous endoscopic lumbar discectomy and related predictors was performed using Revman 5.4 software.RESULTS:(1)A total of 15 studies were included,all of which were retrospective studies,including 24 models for predicting the risk of recurrence after percutaneous endoscopic lumbar discectomy.(2)The PROBAST evaluation results indicated that all 15 studies exhibited a high risk of bias.Regarding applicability,two studies demonstrated a low risk,while 13 presented a high risk.(3)Regarding the TRIPOD reporting quality,the overall quality across the 15 studies was low.The primary reasons for this low compliance included the failure to report blinding,a lack of explanation for the sample size calculation method,lack of detailed description of missing data processing methods,and lack of information such as introduction to the model used.(4)Furthermore,the area under the receiver operating characteristic curve for the model ranged from 0.684 to 0.972,with the number of potential predictor variables varying from 15 to 28.(5)The results of meta-analysis showed that the postoperative recurrence rate of lumbar disc herniation patients treated with percutaneous endoscopic lumbar discectomy was 12％(95％CI=9.0％-15.0％),Modic changes(OR=6.72,95％CI=3.90-11.59),body mass index(OR=1.28,95％CI=1.10-1.49),work intensity(OR=3.22,95％CI=1.85-5.59),age(OR=2.28,95％CI=1.50-3.48),and smoking history(OR=2.65,95％CI=1.75-4.00)were independent influencing factors for postoperative recurrence of percutaneous endoscopic lumbar discectomy(all P＜0.05).CONCLUSION:The overall predictive performance of the recurrence risk prediction models after percutaneous endoscopic lumbar discectomy is satisfactory;however,the model exhibits a high overall risk of bias and applicability,coupled with low reporting quality.Additionally,there is a lack of prospective research and external validation.Future,risk prediction models should consider factors such as Modic changes,body mass index,work intensity,age,and smoking history as potential predictors.

BACKGROUND:Obesity is not only related to metabolic diseases such as diabetes and cardiovascular disease,but also closely related to the increased risk of cognitive decline,dementia and other neurodegenerative diseases.Studies have found that aerobic exercise and resistance exercise can help improve obesity-related cognitive impairment,but their therapeutic effects and related mechanisms of action are still unclear.OBJECTIVE:To explore the protective effects of aerobic and resistance exercises on the nervous center of obesity-related cognitive impairment mice.METHODS:Forty-eight 8-week-old C57BL/6J wild-type male mice were randomly divided into four groups:a control group was fed normally for 20 weeks;a high fat group was fed with high fat diet(60％fat energy)for 20 weeks;an aerobic exercise group was fed with 12 weeks of high-fat diet followed by 8 weeks of aerobic exercise;and a resistance exercise group was fed with 12 weeks of high-fat diet followed by 8 weeks of resistance exercise.After the exercise intervention,body mass was weighed,insulin tolerance and glucose tolerance were tested to evaluate insulin resistance,and cognitive function of mice in each group was detected by new object recognition experiment and Y-maze experiment.The morphology of hippocampal and cortical tissue cells was observed by hematoxylin-eosin staining.The mRNA relative expression levels of tumor necrosis factor-α and interleukin-6 were detected by real-time fluorescence quantitative PCR,and the protein expressions of Bax,Bcl-2,nuclear factor-κB,Cleaved Caspase-1,Caspase-3,synapsin 1 and brain-derived neurotrophic factor were detected by western blot.RESULTS AND CONCLUSION:(1)Compared with the control group,the body mass of mice increased in the high-fat group(P＜0.05),accompanied by insulin resistance and cognitive dysfunction,the expression levels of nuclear factor-κB,Bax,Caspase-3,Cleaved Caspase-1 in the hippocampus were significantly increased(P＜0.05),the expression levels of brain-derived neurotrophic factor,synapsin 1and Bcl-2 proteins were significantly decreased(P＜0.05),Bcl-2/Bax ratio was significantly decreased(P＜0.05),and the mRNA levels of inflammatory cytokines,tumor necrosis factor-α and interleukin-6,were significantly up-regulated(P＜0.05).(2)Compared with the high-fat group,the above indexes were significantly improved in the aerobic exercise group(P＜0.05),while in the resistance exercise group,the body mass of mice was significantly decreased,the levels of inflammatory cytokines tumor necrosis factor-α and interleukin-6 mRNA were significantly decreased(P＜0.05),the protein expression of Caspase-3 was significantly decreased(P＜0.05),and the protein expression of brain-derived neurotrophic factor was significantly up-regulated(P＜0.05),but no significant changes were observed in the other indexes(P＞0.05).In conclusion,long-term exercise can reduce insulin resistance,down-regulate the expression of nuclear factor-κB pathway,weaken inflammatory response,inhibit neuronal apoptosis and improve synaptic plasticity,resulting in neuroprotective effects,and effectively alleviate obesity-related cognitive dysfunction in obese mice.The therapeutic effect of aerobic exercise is superior to that of resistance exercise.

Objective: To explore the influencing factors of anxiety symptoms and to construct a predictive model based on machine learning algorithms, so as to provide support for the prevention and management of anxiety symptoms among junior high school students. Methods: From April to May 2023, a stratified random cluster sampling method was adopted to select 8 176 junior high school students from Zhengzhou and Shangqiu citys. All participants completed the Adolescent Self rating Life Events Checklist, the 10item Connor-Davidson Resilience Scale, the School Connectedness Scale, the Parent-Child Cohesion Questionnaire, and the 7 item Generalized Anxiety Disorder Scale. Logistic regression analysis identified the associated factors of anxiety symptoms among junior high school students. Predictive models were constructed using Logistic regression, Random Forest, and eXtreme Gradient Boosting (XGBoost) algorithms, with SHapley Additive exPlanations analysis explaining the optimal model. Results: The detection rate of anxiety symptoms among junior high school students was 16.3%. Logistic regression analysis showed that junior high school students who were female ( OR =1.22), in the ninth grade ( OR =1.27), living in urban areas ( OR =1.37), having a father with a college education or above ( OR =1.26), having a mother with a senior high school education ( OR =1.26), and experiencing higher levels of negative life events ( OR =1.05) reported a higher risk of anxiety symptoms(all P <0.05). In contrast, those with moderate family economic status ( OR =0.71), moderate academic burden ( OR =0.59), low academic burden ( OR =0.54), moderate sleep quality ( OR =0.46), good sleep quality ( OR =0.26), excellent sleep quality ( OR =0.15), higher levels of psychological resilience ( OR =0.96), higher levels of school connectedness ( OR =0.96), and higher levels of parent-child cohesion ( OR =0.98) reported a lower risk of anxiety symptoms (all P <0.05). Three machine learning models demonstrated good predictive performance for anxiety symptoms among junior high school students (all AUC>0.8), with the XGBoost model achieving the best predictive performance. SHAP analysis revealed that negative life events, sleep quality, school connectedness, psychological resilience and parent-child cohesion were the top five relevant factors for predicting anxiety symptoms. Conclusions The detection rate of anxiety symptoms among junior high school students is relatively high. The XGBoost model is the optimal predictive model for anxiety symptoms in the population. Negative life events, sleep quality, school connectedness, psychological resilience, and parent-child cohesion are significant correlates of anxiety symptoms among junior high school students.

This paper summarizes Professor WANG Yaoxian's experience in treating diabetic kidney disease （DKD） from the perspective of spleen and stomach based on the "internal heat leading to concretions" theory. It is considered that internal heat leading to concretions constitutes the core pathogenesis of DKD， with the spleen and stomach serving as the source of internal heat； therefore， treatment should be based on regulating the spleen and stomach. In the early stage of DKD， dysfunction of the spleen and stomach leads to the initial generation of internal heat. Common syndrome patterns include gastrointestinal heat accumulation and constrained heat in the liver and stomach， for which modified Gegen Qinlian Decoction （葛根芩连汤） can be used to clear heat bind while modified Dachaihu Decoction （大柴胡汤） is used to clear stomach and soothe liver， respectively. In the middle stage of DKD， weakness of the spleen and stomach results in the initial formation of concretions and conglomerations. Common patterns include spleen deficiency with prevalence of dampness and deficiency of both the spleen and kidney. Treatment emphasizes strengthening the spleen and resolving dampness， raising yang and boosting the stomach with modified Shengyang Yiwei Decoction （升阳益胃汤）， or supplementing spleen and boosting kidney， dissipating bind and dispe-ring concretions with modified Shenqi Dihuang Decoction （参芪地黄汤）， respectively. In the late stage of DKD， it is characterized by spleen and stomach depletion， and rampant accumulation of turbidity and toxin， and the common syndrome patterns are damp-turbidity obstruction in the middle jiao （焦） and spleen-kidney yang deficiency. Treatment aims to remove turbidity and harmonize the stomach， or to warm the kidney and strengthen the spleen while elimina-ting turbidity， using modified Dahuang Gancao Decoction（大黄甘草汤） and Jupi Zhuru Decoction （橘皮竹茹汤） or modified Baoyuan Decoction （保元汤） and Lizhong Decoction （理中汤）， respectively. In clinical practice， appropriate formulas and medications are flexibly selected according to specific syndromes.

ObjectiveTo construct and validate a clinical prediction model for inflammatory remission outcomes in rheumatoid arthritis （RA） patients with liver and kidney deficiency syndrome treated with Bushen Zhiwang Decoction （补肾治尪汤， BZD） based on metabolomics. MethodsA prospective cohort study was conducted， enrol-ling 60 RA patients with liver and kidney deficiency syndrome. All patients were treated with BZD and conventional-dose oral conventional synthetic disease-modifying antirheumatic drugs （csDMARDs） for 12 months. Clinical data were collected， and the change in disease activity score in 28 joints （DAS28） after treatment compared with baseline （△DAS28） was used as the primary outcome and grouping criterion. Peripheral blood samples were collected before treatment to analyze plasma metabolites. Differential analysis and least absolute shrinkage and selection operator （LASSO） regression were used to preliminarily screen differential metabolites， followed by machine learning algorithms to further identify a core metabolite combination. Based on the expression levels of the core metabolite combination， a novel metabolite index， namely the metabolomics-based inflammatory remission score （Met-IRS）， was calculated using standar-dized metabolite values， and its clinical applicability was evaluated. A clinical prediction model was constructed by integrating clinical characteristics and Met-IRS， and the model performance was assessed. ResultsAmong the 60 patients， those with △DAS28 ≥ 0.27 were assigned to the high inflammatory remission group， while those with △DAS28 ＜ 0.27 were assigned to the low inflammatory remission group， with 30 cases in each group. Compared to the low inflammatory remission group， the high inflammatory remission group showed a higher frequency of methotrexate use and a lower positive rate of rheumatoid factor （RF） （P＜0.05）. Seven core metabolites were identified as the optimal combination， including mangiferic acid， fatty acid-hydroxy fatty acid ester 40∶6， fatty acid-hydroxy fatty acid ester 18∶0， fatty acid-hydroxy fatty acid ester 36∶1， glucosylceramide， lysophosphatidylcholine 22∶5， and pregnanetriol ketone. The calculated Met-IRS comprehensively reflected the characteristics of differential metabolites and demonstrated clinical applicability. Met-IRS was significantly higher in the high inflammatory remission group than in the low inflammatory remission group， and was positively correlated with high inflammatory remission outcomes （P＜0.05）. Based on the variables Met-IRS， methotrexate use， leflunomide use， and RF positivity， a clinical prediction model for inflammatory remission in RA treatment （Cj-RTRM） was constructed. Model performance evaluation demonstrated that the model had good clinical predictive ability， with an area under the receiver operating characteristic curve （AUC） of 0.880， sensitivity 0.967， specificity 0.700 and Youden's index 0.667. ConclusionThe clinical prediction model Cj-RTRM constructed based on the metabolomics-based inflammatory remission score Met-IRS can effectively predict clinical inflammatory remission outcomes in RA patients treated with BZD and accurately identify the advantageous population for this treatment. This model provides guiding evidence for dynamic inflammation monitoring， targeted management， and identification of populations with advantages in traditional Chinese medicine.

Objective To analyze the case data of farmers' foodborne disease surveillance reports in Guizhou Province from 2022 to 2024, and to provide reference for the precise prevention and control of foodborne diseases among farmers in Guizhou Province. Methods Case data of foodborne disease surveillance reports of farmers were systematically collected from 2022 to 2024 in Guizhou Province. Descriptive epidemiological methods were used to analyze the temporal, geographical, and demographic distribution of foodborne diseases among farmers, along with their primary clinical symptoms and pathogen detection results. Results From 2022 to 2024, a total of 22,882 cases of foodborne diseases were reported among farmers in Guizhou Province. The majority of clinical symptoms (97.81%) were related to the digestive system, with summer being the peak season. While females outnumbered males, the gender difference was statistically insignificant (P >0.05). The 36-55 age group accounted for the highest proportion (38.83%), with Zunyi City (34.89%) and Qiandongnan Prefecture (23.21%) reporting the most cases. Fungal products were the most frequently reported suspected food items (26.96%), and home-made preparation was the primary processing method (58.63%). A total of 1 210 fecal samples were collected through active monitoring with an overall detection rate of 13.22%. Norovirus showed the highest detection rate (9.92%, 120/1 210). Statistically significant differences were observed among different seasons, age groups, regions, types and processing methods of suspected food exposure, and pathogen detection rates (P <0.001). Conclusion Foodborne disease prevention and control among farmers in Guizhou Province should focus on the risks of wild mushroom poisoning in summer and homemade foods, and continuously improve farmers' awareness of the dangers of foodborne diseases and food safety.

ObjectiveCerebrospinal fluid (CSF) plays a crucial role in maintaining the homeostasis of the central nervous system (CNS). CSF rapidly exchanges with interstitial fluid (ISF) via the glymphatic system within the brain parenchyma. CSF-ISF circulation and its associated mechanisms are often referred to as the brain lymphatic system. This system is connected directly to meningeal lymphatic vessels (mLVs), jointly performing the function of clearing metabolic waste from the CNS. Emerging evidence indicates that this system is closely associated with the onset and progression of neurodegenerative diseases (NDs) such as Alzheimer’s disease (AD). Importantly, abnormal CSF circulation is not only a downstream consequence of AD pathology, but also a risk factor. In AD, the dynamics of CSF flow within the CNS are diminished, immune dysregulation occurs, and this may increase the risk of AD by exacerbating the burden of amyloid β-protein (Aβ). In the mouse model of AD, impaired CSF flow compromises this clearance function, leading to cognitive deficits. Clinically, acupuncture at cognition-related acupoints is commonly used for the prevention and treatment of AD. However, whether its therapeutic effects are mediated through the modulation of CSF dynamics remains unclear. This study aimed to evaluate the impact of acupuncture on CSF flow and investigate its acupoint specificity. MethodsMice were randomly assigned to experimental groups for the different electroacupuncture groups with the following acupoints: Baihui point (GV 20), Ear point, Neiguan point (PC 6), and Tianshu point (ST 25). Wild-type mice on a C57BL/6J background were used as controls. Fluorescent tracer was injected into the cisterna magna to label CSF flow. Fluorescence imaging was employed to assess the distribution of CSF within the brain before and after acupuncture stimulation. ResultsFollowing tracer injection into the cisterna magna, fluorescence signals rapidly reached the cerebellum and medulla—the regions closest to the injection site. Fluorescence intensity was higher in ventral brain regions compared to dorsal regions, likely due to greater vascular density in ventral areas facilitating CSF-ISF exchange. Electroacupuncture at the GV 20 produced the most pronounced enhancement of CSF across the whole brain, while stimulation at the ST 25 primarily augmented flow within subcortical regions. In contrast, electroacupuncture at the Ear point or the PC 6 had no observable effect on CSF in mice. ConclusionElectroacupuncture promotes CSF flow into the brain parenchyma in an acupoint-specific manner, with GV 20 exhibiting the most pronounced enhancement of CSF dynamics. These findings suggest that acupuncture-mediated facilitation of CSF flow may represent a potential therapeutic strategy for preventing or delaying age-related cognitive decline.

ObjectiveTo clarify whether METTL14 mediates the core role of acupuncture at Neiguan (PC6) in promoting myelination and improving behavior in young autistic rats through gene intervention technology. MethodsThe ASD model was established by intraperitoneal injection of valproic acid (VPA) in pregnant rats. Male offspring were intracerebroventricularly injected with adenovirus-packaged METTL14 shRNA (sh-METTL14) or its control (sh-NC) on postnatal day 1, with a model group set as well. Subsequently, the juvenile rats were divided into model group, acupuncture group, acupuncture+sh-NC group, and acupuncture+sh-METTL14 group. The acupuncture group received acupuncture at Neiguan (PC6) from postnatal day 7, once daily for 21 consecutive days. Neurobehavioral changes were evaluated by behavioral tests; METTL14 knockdown efficiency and the expression of METTL14, METTL3, and PTEN were detected by quantitative real-time PCR (qRT-PCR) and Western blot (WB); PTEN m⁶A levels were measured by RNA immunoprecipitation-qPCR (RIP-qPCR); myelin ultrastructure, expression of myelin basic protein (MBP) and neurofascin 155 (NF155), and dendritic spine density were observed using transmission electron microscopy (TEM), enzyme-linked immunosorbent assay (ELISA), immunofluorescence, qRT-PCR, and primary neuron culture. ResultsBehaviorally, knockdown of METTL14 significantly counteracted the beneficial effects of acupuncture in improving self-grooming, open field exploration, three-chamber social interaction, and Morris water maze learning and memory (P<0.05, P<0.01). Compared with the acupuncture+sh-NC group, the acupuncture+sh-METTL14 group showed significantly decreased mRNA and protein expression of hippocampal METTL14 (P<0.01), and the upregulating effects of acupuncture on METTL3 and PTEN expression were reversed (P<0.01). Meanwhile, knockdown of METTL14 significantly inhibited the acupuncture-induced increase in PTEN m⁶A levels (P<0.01). Morphologically, knockdown of METTL14 attenuated the improvement of myelin structure by acupuncture, reversed the downregulation of MBP and upregulation of NF155 induced by acupuncture, and blocked the increase in dendritic spine density (P<0.05, P<0.01). ConclusionMETTL14 is a key molecule mediating the therapeutic effect of acupuncture at Neiguan. Acupuncture at Neiguan upregulates METTL14, thereby enhancing m⁶A methylation modification of PTEN mRNA to stabilize its expression, ultimately promoting myelin development and improving behavioral symptoms in ASD juvenile rats. This preliminarily reveals the modern biological connotation of “opening Xuanfu and dredging myelin”.

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.