Objective: To investigate the influence of sinus morphology on the safety of hydraulic sinus floor elevation surgery and provide a biomechanical basis for clinical treatment. Methods: After approval by the Medical Ethics Committee of the institution, cone beam computed tomography imaging data from nine patients were collected. The sinus morphologies were classified into slope, flat and concave types. Three-dimensional finite element models of maxillary sinuses with the aforementioned morphologies were constructed using Mimics, Geomagic, Solidworks, and ANSYS software, followed by a simulation of the hydraulic elevation process. The sinus membrane elevation height was set at 1-6 mm. The pressure required for elevation and the equivalent, compressive, tensile, and shear stresses generated on the sinus membrane were recorded and analyzed. The equivalent stress distribution on the sinus membrane was visualized using contour plots. Results: The elevation pressure and the equivalent, compressive, tensile, and shear stresses generated on the sinus membrane increased along with the elevation height. When the sinus membrane was lifted to 6 mm, the elevation pressure was (301.17 ± 98.1) kPa, (151.85 ± 3.7) kPa, and (149.36 ± 10.31) kPa in the slope, flat and concave finite element analysis models, respectively. The equivalent stress was (1 023.86 ± 201.99) kPa in the slope sinuses, comparing with (687.91 ± 69.08) kPa and (698.27 ± 96.09) kPa in the flat and concave sinuses. Higher elevation pressure and the equivalent stress, compressive stress and shear stress values were found in the slope sinus than in the flat and concave sinuses under the same elevation height (P < 0.05). Stress distribution analysis revealed that stress was uniformly distributed in the flat sinuses, followed by concave sinuses, but asymmetrically distributed in the slope sinuses Conclusions The slope sinuses demonstrated inferior safety and efficiency compared with the flat and concave sinuses when performing hydraulic sinus floor elevation surgery.

Objective To explore the relationship between intestinal flora imbalance and pulmonary function in patients with chronic obstructive pulmonary disease (COPD), and to analyze the related influencing factors. Methods A total of 310 patients with COPD who were admitted to Air Force Military Medical University Tangdu Hospital from June 2022 to December 2024 were retrospectively analyzed. Based on intestinal flora status, the enrolled patients were classified into imbalance group (n=83) and non-imbalance group (n=227). Logistic regression analysis was conducted to analyze the independent related factors of intestinal flora imbalance in COPD patients. Based on the above factors, a prediction model was constructed, and ROC curve analysis model was applied to analyze the predictive value of the model on intestinal flora imbalance. Results Logistic regression analysis revealed that age, IL-6, albumin, pulmonary function, long-term bed rest and long-term use of antibiotics were related to intestinal flora imbalance in COPD patients (all P<0.05). ROC results of the Logistic prediction model showed that the area under the curve, sensitivity, specificity and 95%CI were 0.961, 0.880, 0.996 and 0.932-0.989 respectively. Conclusion The intestinal flora imbalance in patients with COPD is closely related to lung function, age, inflammatory status, nutritional indicators, activity ability and antibiotic use.

Objective To provide scientific and normative guidance for capacity building and quality control standards for vision health management service institutions, thereby promoting the standardization and professional development of the industry, enhancing service quality, and improving the effectiveness of myopia prevention and control. Methods A multidisciplinary expert panel organized by Society of Vision Health Management, Chinese Health Association, based on standards such as the ^"Technical Specifications for Vision Health Management Services for Primary and Secondary School Students^" (T/CHAA 008-2019) and combined with field research data, revised and formed this consensus through multiple rounds of meetings and discussions. Results This consensus clarifies the positioning of service institutions, core service capability requirements (covering basic configuration, personnel and equipment, service processes, scope, and competency levels), and quality control points throughout the service process. It establishes an evaluation framework centered on ^"foundational support - service implementation - management effectiveness - outcome output.^" Conclusion This consensus provides systematic guidance for the standardized construction, capacity evaluation, and quality control of vision health management service institutions, which is of great significance for safeguarding the vision health of children and adolescents.

Chronic diabetic wounds, severely complicated by multidrug-resistant (MDR) bacterial infections, represent a profound and escalating global health crisis. The intrinsically hostile microenvironment of diabetic wounds, characterized by localized hypoxia, persistent oxidative stress, and poor vascularization, creates an ideal niche for opportunistic pathogens such as Staphylococcus aureus and Pseudomonas aeruginosa. These bacteria readily construct dense extracellular polymeric substance (EPS) biofilms, which not only physically shield the microbes from host immune responses but also actively trap the wound in a state of chronic, unresolved inflammation. Consequently, conventional systemic and topical antibiotic therapies are becoming increasingly futile, as poor perfusion at the wound site restricts drug bioavailability, while the rapid genetic evolution of bacteria and the impenetrable nature of biofilms lead to catastrophic treatment failures, often culminating in severe tissue necrosis and lower-extremity amputations. To circumvent the limitations of traditional antimicrobials, therapeutic gas delivery has emerged as a highly promising, paradigm-shifting strategy. Gaseous signaling molecules, particularly nitric oxide (NO), carbon monoxide (CO), hydrogen sulfide (H₂S), and hydrogen (H₂), possess unique physicochemical properties that allow them to seamlessly penetrate dense biofilm matrices and cellular membranes. Once inside, these gases operate via multi-targeted mechanisms that are incredibly difficult for bacteria to develop resistance against; for instance, NO induces severe lipid peroxidation and DNA cleavage in bacteria, CO downregulates pro-inflammatory cytokines, H₂S significantly accelerates endothelial cell migration for neovascularization, and H₂ acts as a powerful selective antioxidant to neutralize tissue-damaging reactive oxygen species (ROS). Together, these therapeutic gases not only exert broad-spectrum bactericidal effects but also actively reprogram the wound bed by promoting the critical M1-to-M2 macrophage polarization and stimulating angiogenesis. Despite their immense biological potential, the direct clinical translation of gas therapies is severely hindered by inherent physicochemical drawbacks, including extreme volatility, short physiological half-lives, poor aqueous solubility, and the high risk of off-target systemic toxicity, if applied indiscriminately. To conquer these immense pharmacokinetic barriers, cutting-edge advancements in materials science have driven the development of gas-releasing micro- and nanoplatforms. Utilizing sophisticated carriers such as metal-organic frameworks (MOFs), mesoporous silica, polymeric nanoparticles, liposomes, and injectable hydrogels, researchers can now encapsulate gas-donor molecules to achieve sustained, localized delivery. More importantly, these advanced nanoplatforms are ingeniously engineered to be stimuli-responsive. By exploiting the pathological hallmarks of the diabetic wound environment, such as elevated glucose concentrations, acidic pH, and overexpressed ROS, or by utilizing external triggers like near-infrared (NIR) light irradiation and ultrasound, these intelligent platforms ensure on-demand, precise spatio-temporal gas release. This often allows for powerful synergistic combinations, such as photothermal or photodynamic therapy coupled with gas release, thereby obliterating biofilms while sparing healthy tissue. While the therapeutic outcomes of these smart delivery systems in eradicating MDR infections and accelerating tissue repair are unprecedented, several critical challenges remain before widespread clinical adoption, as long-term biosafety profiles of the carrier nanomaterials, complexities in large-scale good manufacturing practice (GMP) production, and stringent regulatory hurdles must be rigorously addressed. Looking forward, the next frontier lies in the realm of precision medicine and theranostics, where future research must focus on the seamless integration of these gas-releasing platforms with flexible, wearable biosensors capable of continuously monitoring wound biomarkers (e.g., pH, temperature, uric acid) in real-time. Coupled with artificial intelligence algorithms to govern automated, closed-loop adaptive dosing, these next-generation smart dressings hold the ultimate potential to comprehensively transform the clinical management of complex, infected diabetic wounds.

ObjectiveTo analyze the epidemiological and etiological characteristics of a cluster of human metapneumovirus (HMPV) infection in a kindergarten in Gongshu District of Hangzhou City in May 2024, and to provide reference for the prevention and control of similar outbreaks. MethodsAn on-site investigation was conducted using an epidemiological case investigation form. Throat swab specimens collected from cases were screened for 13 respiratory pathogens using real-time fluorescent polymerase chain reaction (PCR). For HMPV nucleic acid positive specimens, the F gene of HMPV was used as the target gene for amplification and sequencing. The sequencing results were then compared with sequences in GenBank database to determine the virus subtypes and perform phylogenetic analyses. ResultsThe outbreak occurred in a kindergarter junior class with a total of 28 preschoolers and 3 teachers and childcare workers. A total of 11 cases (10 preschoolers and 1 teacher) were identified, including 8 male cases and 3 female cases. Clinical manifestations included fever in all 11 cases (100.00%), cough in 8 cases (72.72%), catarrhal symptoms in 4 cases (36.36%), and headache in 3 cases (27.27%). All symptoms were mild, and no severe cases were observed. A total of 11 throat swab samples were collected. Real-time fluorescent PCR test results showed that 3 samples were positive for HMPV nucleic acid, 2 samples were positive for both HMPV and Streptococcus pneumoniae, and 1 sample was positive for both HMPV and rhinovirus. The sequences of the 6 HMPV nucleic acid positive specimens were amplified and analyzed using specific primers, and all were determined to be HMPV subtype A2b. The F gene fragment sequence showed the highest similarity to PV081665.1/Brazil/2024 (99.65%), and also exhibited high similarity to PP683455.1/Indonesia/2021 (99.48%), PV016275.1/Beijing/2024 (99.31%), and PV052230.1/USA/2024 (99.13%). ConclusionThis cluster of acute respiratory tract infection was caused by HMPV subtype A2b, with co-infection of rhinovirus and Streptococcus pneumoniae. The F gene fragment sequences of the HMPV in this outbreak were highly homologous to those of the A2b strains isolated from Brazil, Beijing, Indonesia, and the the United States.

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.

Lung cancer， with persistently high incidence and mortality rates， remains a significant global health challenge. By taking the study on the experience in diagnosis and treatment of lung cancer with phlegm-dampness and blood stasis syndrome by distinguished traditional Chinese medicine physicians of the Sichuan School as an example， the diagnosis and treatment system for lung cancer with phlegm-dampness and blood stasis syndrome， which was formed in response to the humid and foggy environment of the Sichuan Basin， possesses unique value. However， traditional inheritance modes face challenges such as fragmentation， lack of standardization， and insufficient quantification， which hinder the promotion and application of this experience. This research focused on how to leverage multimodal data and artificial intelligence-generated content （AIGC） to achieve precise analysis， intelligent inheritance， and clinical innovation of the experience in diagnosis and treatment of lung cancer with phlegm-dampness and blood stasis syndrome by distinguished traditional Chinese medicine physicians of the Sichuan School. By integrating multimodal data （encompassing four diagnostic methods of traditional Chinese medicine， modern medical imaging， clinical laboratory tests， molecular biology， and regional environmental information）， a precise diagnosis and treatment system integrating macro and micro perspectives for the "disease， syndrome， and pathogenesis" was constructed. The research yielded the following results： （1） In precise syndrome differentiation， the objective quantification of the phlegm-dampness and blood stasis syndrome was achieved. By constructing a "four diagnostic methods， imaging， and molecule" correlation model， the study revealed intrinsic links between tongue and pulse parameters and the tumor microenvironment， as well as between regional climatic factors and syndrome characteristics， enabling real-time dynamic monitoring of efficacy. （2） In elucidating patterns， the study systematically explored the syndrome differentiation thoughts of Sichuan School physicians， such as the timing of purgation and tonification. A "pathogenesis， syndrome complex， and prescriptions and herb" network model was constructed， which accurately elucidated the synergistic action mechanisms of core herb pairs and quantified the dynamic compatibility patterns of reinforcing healthy Qi and eliminating pathogenic factors. （3） In intelligent empowerment， an auxiliary system integrating intelligent syndrome differentiation， treatment plan generation， and efficacy evaluation was built. This system can fuse regional characteristics with individual data， dynamically generate and optimize personalized prescriptions aligned with the experience of Sichuan School， and predict efficacy trends and potential adverse reactions. The integration of multimodal data and AIGC can effectively facilitate the structured inheritance and clinical translation of distinguished physicians' experience. The established intelligent diagnosis and treatment model integrating traditional Chinese medicine and Western medicine demonstrates clear potential in prolonging patients' progression-free survival， alleviating symptoms， and reducing adverse reactions to treatment. This study provides a referential methodological framework for the traditional Chinese medicine experience in diagnosis and treatment of lung cancer， especially the empirical inheritance and modernized development of regional academic schools. It contributes to advancing clinical diagnosis and treatment toward greater precision and personalization.

The theory of constitution in traditional Chinese medicine （TCM） has emerged as a new discipline in recent years. Constitution plays a vital role in the onset，progression，transformation，and prognosis of diseases. At present，some clinical scholars have adopted a novel diagnostic and treatment model of "constitution differentiation-disease identification-syndrome differentiation"，in which constitution is regarded as a core element throughout the diagnostic and therapeutic process. Constitution is closely associated with etiology，onset，pathogenesis，syndrome differentiation，and treatment. Against this background，the construction of animal models based on constitution holds far-reaching significance for advancing clinical research. This paper focuses on the construction and evaluation of rodent models with Qi-deficiency constitution，aiming to explore how to further induce Qi-deficiency syndromes and related disease states on the basis of Qi-deficiency constitution models，thereby developing an integrated animal model that embodies the trinity of "constitution-disease-syndrome". The establishment of this model not only provides a solid experimental foundation for the development of new therapies and drugs in TCM targeting specific constitutions，diseases，and syndromes，but also greatly promotes the modernization and scientific advancement of TCM theory. By comprehensively applying multidisciplinary technologies and methods，the study evaluates the model's validity，reliability，and practicality，with the aim of opening new avenues for future research in TCM and promoting the development of the field.

Dry eye disease(DED)is a common ocular surface disorder worldwide, primarily characterized by a loss of homeostasis of the tear film, and frequently associated with meibomian gland dysfunction(MGD), decreased tear film stability, ocular discomfort, and visual impairment. In recent years, factors such as the widespread use of digital devices,the aging population, and environmental changes have contributed to a significant increase in its global prevalence, making it a major public health concern. Red light therapy(RLT), also known as low-level laser therapy(LLLT)or photobiomodulation(PBM), is a non-invasive treatment that utilizes low-energy red or near-infrared light to irradiate tissues. It exerts photobiomodulatory effects to promote cellular repair and functional recovery. This therapy has demonstrated considerable potential in treating various ocular conditions. Its broader clinical application could improve therapeutic outcomes, alleviate patient discomfort and financial burden, and reduce the consumption of healthcare resources, thereby yielding significant socio-economic benefits. This paper systematically reviews the multifaceted mechanisms and application prospects of RLT in managing DED, including its anti-inflammatory effects, improvement of meibomian gland function, promotion of conjunctival goblet cell repair, and alleviation of visual fatigue, aiming to provide a theoretical foundation and practical reference for its clinical adoption.

The theory of constitution in traditional Chinese medicine （TCM） has emerged as a new discipline in recent years. Constitution plays a vital role in the onset，progression，transformation，and prognosis of diseases. At present，some clinical scholars have adopted a novel diagnostic and treatment model of "constitution differentiation-disease identification-syndrome differentiation"，in which constitution is regarded as a core element throughout the diagnostic and therapeutic process. Constitution is closely associated with etiology，onset，pathogenesis，syndrome differentiation，and treatment. Against this background，the construction of animal models based on constitution holds far-reaching significance for advancing clinical research. This paper focuses on the construction and evaluation of rodent models with Qi-deficiency constitution，aiming to explore how to further induce Qi-deficiency syndromes and related disease states on the basis of Qi-deficiency constitution models，thereby developing an integrated animal model that embodies the trinity of "constitution-disease-syndrome". The establishment of this model not only provides a solid experimental foundation for the development of new therapies and drugs in TCM targeting specific constitutions，diseases，and syndromes，but also greatly promotes the modernization and scientific advancement of TCM theory. By comprehensively applying multidisciplinary technologies and methods，the study evaluates the model's validity，reliability，and practicality，with the aim of opening new avenues for future research in TCM and promoting the development of the field.