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 explore the prevalence of Helicobacter pylori (Hp) infection and its association with dietary and lifestyle habits among the adult physical examination population in Xuzhou area. Methods Retrospectively selected the physical examination population who underwent HP testing at our hospital's physical examination center from May 2021 to December 2023 as the research object. The prevalence of Hp infection in the population was analyzed based on the physical examination results. A questionnaire survey was used to collect information on the eating and living habits of all study subjects. Logistic regression was used to analyze the relationship between eating and living habits and Hp infection. Results A total of 1 354 physical examination people were included in the study, and the Hp infection rate was 37.30% (505/1354). The difference in Hp infection rates among people of different age groups is statistically significant (P<0.05), with the middle-aged population (41-59 years old) having the highest Hp positive infection rate (45.38%).High salt (41.11%), hot diet (40.56%), history of smoking (45.23%) and drinking (43.80%), less consumption of fruits and vegetables (43.73%), irregular exercise (41.29%), irregular diet People who frequently eat out (43.56%) and eat out frequently (42.57%) have a higher Hp infection rate (P<0.05).After adjusting for demographic factors such as gender, age, place of residence and education level, multivariate Logistic regression results showed that high-salt diet (OR=3.975, 95%CI: 2.670-5.917) and hot diet (OR=3.357, 95%CI: 2.291-4.919), smoking (OR=1.458, 95%CI: 1.082-1.964), drinking alcohol (OR=1.654, 95%CI: 1.279-2.138), eating fruits and vegetables (OR=1.759, 95%CI: 1.345-2.301), regular exercise (OR=1.822, 95%CI: 1.371-2.421), regular diet (OR=1.893, 95%CI: 1.391-2.575), eating out (OR=1.690, 95%CI: 1.277-2.237) were associated with the risk of Hp infection (P<0.05). Conclusion The positive infection rate of Hp among the physical examination population in Xuzhou is slightly lower than the average epidemic level in China. Cultivating healthy eating and living habits can effectively reduce the risk of Hp infection.

OBJECTIVE To investigate the efficacy and safety of Wuling capsules combined with fluoxetine in the treatment of adolescents with first-episode moderate-to-severe depressive disorder accompanied by insomnia. METHODS The clinical data of 476 adolescents with first-episode moderate-to-severe depression accompanied by insomnia admitted to our hospital from June 2022 to May 2025， were retrospectively collected. According to the initial treatment regimen， patients were divided into a control group （241 cases， treated with fluoxetine alone） and an observation group （235 cases， treated with Wuling capsules combined with fluoxetine）. The depression severity （Hamilton Depression Rating Scale-17 Item and the Self-Rating Depression Scale scores）， sleep quality （Pittsburgh Sleep Quality Index score， sleep latency， wake after sleep onset， total sleep time， sleep efficiency）， serum neuroendocrine indicator （cortisol） and inflammatory markers （C-reactive protein， interleukin-6） were compared between the two groups before treatment and at 4th and 8th weeks of treatment. The effective rate at 8th weeks and the occurrence of adverse drug reactions （ADRs） were also compared between the two groups. RESULTS Before treatment， there were no significant differences in depression severity， sleep quality， serum neuroendocrine indicator， and inflammatory markers between the two groups （ P ＞0.05）. At 4th and 8th weeks， both groups showed significant improvement in these indicators compared to those before treatment， with the observation group demonstrating significantly greater improvement than the control group at the corresponding time points （ P ＜0.05）. At 8th week， the eff ective rate of the observation group was 90.21%， significantly higher than 80.50% in the control group （ P ＜0.05）. The incidence of nausea， headache， fatigue， dry mouth， and palpitations， as well as the total incidence of ADRs， did not differ significantly between the two groups （ P ＞0.05）. CONCLUSIONS Wuling capsules combined with fluoxetine can significantly improve the effective rate in adolescents with first-episode moderate-to-severe depression accompanied by insomnia， accelerate the relief of depressive symptoms， improve sleep quality， and reduce serum neuroendocrine indicator and inflammatory markers， with a favorable safety profile.

Objective To investigate the current distribution of radiotherapy resources in Gansu Province, evaluate the equity of resource allocation, and provide a scientific basis for optimizing regional resource allocation. Methods A questionnaire survey was carried out to assess radiotherapy resources in medical institutions across Gansu Province, China. The equity of radiotherapy resource distribution and associated disparities were assessed using the Gini coefficient, Lorenz curve, and Theil index. Results A total of 23 medical institutions in Gansu Province provided radiotherapy services, comprising 39 radiotherapy devices and 438 professionals, of whom medical physicists accounted for 16.9%. The radiotherapy frequency was 0.47 cases per thousand population. The Gini coefficients for radiotherapy resource distribution ranged from 0.38 to 0.56 by population and from 0.52 to 0.70 by geography. The Theil index for radiotherapy resources ranged from 1.36 to 3.67. Conclusion Radiotherapy resources in Gansu Province were insufficient, and the capacity of radiotherapy service was suboptimal. The equity of radiotherapy resource allocation by geography was worse than that by population. Therefore, it is imperative to address the shortage of radiotherapy resources, strengthen the professional workforce, enhance the capacity radiotherapy service and resource utilization, optimize resource allocation, and promote regional equity in radiotherapy provision in Gansu Province.

Objective To investigate the epidemiological characteristics and changing trend of typhus in Shaanxi Province from 2005 to 2023 to provide a scientific basis for its prevention and control. Methods Excel 2007, SPSS 25.0, Joinpoint 4.9.1.0, and Geoda 1.6 were used for data collection and statistical analysis. Super Map was used for data visualization to describe the changing characteristics of the disease. Results A total of 394 typhus cases were reported in Shaanxi Province from 2005 to 2023. The average annual incidence of typhus was 0.054/100 000, showing a dynamic fluctuation trend(AAPC=-3.3, t=-0.3, P>0.05). The cases were mainly concentrated in Baoji, Hanzhong and Xi′an, accounting for 78.68%. The incidence peak was from May to October, accounting for 64.21% of annual incidence. The epidemic season was from May to October and December. The incidence of the disease was concentrated in the 40-69 age group, accounting for 58.88%, and the sex was 1.07:1. The main occupation was farmers, accounting for 72.08%. The median time from onset to diagnosis was 7 days. Global spatial autocorrelation analysis showed that there were significant spatial autocorrelations in 11 years from 2005 to 2023(P<0.05). Local spatial autocorrelation analysis detected a total of 43“high-high”clustering areas, mainly concentrated in Baoji City. Conclusions The overall incidence of typhus in Shaanxi Province showed a dynamic fluctuation trend, with notable seasonal and regional aggregation. The incidence of typhus was higher in middle-aged and elderly people in rural areas. Surveillance should be strengthened in typhus endemic areas in summer and autumn, and health education should be conducted for key population to form good health habits and reduce the incidence of typhus.

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 investigate the patterns of chronic disease comorbidity among permanent elderly residents in Xuhui District of Shanghai, and to analyze the impact of different comorbidity patterns on the elderly’s ability to perform activities of daily living. MethodsBased on data from the 2015 and 2021 Surveys on Health Status and Health Service Utilization among Permanent Residents in Xuhui District of Shanghai, the study included permanent residents who fully participated in both surveys, were aged 60 years or older at the 2015 survey, self-reported having a chronic disease, and reported no significant changes in their chronic disease status between the two surveys. A prospective cohort study design was adopted, using the 2015 data as the baseline and the 2021 survey data as follow-up data. Physical examinations and questionnaire surveys were conducted by the Shanghai Xuhui District Center for Disease Control and Prevention in the subdistricts and towns within the jurisdiction from April to July in both 2015 and 2021. Latent class analysis (LCA) was used to classify comorbidity patterns across 11 types of chronic diseases. The smaller the values of the Akaike information criterion (AIC), the Bayesian information criterion (BIC), and the sample-corrected Bayesian information criterion (aBIC), the better the model fits. The Barthel index (BI) and the Lawton and Brody Instrumental Activities of Daily Living Scale (LB-IADL) were used to assess the participants’ activities of daily living (ADL) and instrumental activities of daily living (IADL). Multiple linear regression and multivariate logistic regression models were used to analyze the association between different comorbidity patterns and ADL and IADL. ResultsA total of 1 608 study participants were enrolled. Among them, 671 (41.73%) self-reported having no chronic diseases. The prevalence of 11 types of chronic diseases was as follows: hypertension in 743 participants (46.21%), heart disease in 148 participants (9.20%), cerebrovascular disease in 37 participants (2.30%), diabetes or abnormal blood glucose in 310 participants (19.28%), other endocrine system diseases (non-diabetic) in 39 participants (2.43%), malignant tumors in 37 participants (2.30%), chronic lung disease in 16 participants (1.00%), gout in 8 participants (0.50%), musculoskeletal disorders in 34 participants (2.11%), gastric or digestive system diseases in 27 participants (1.68%), and dyslipidemia in 15 participants (0.93%). LCA was used to classify comorbidity patterns of chronic diseases among older adults into 1 to 9 latent category combinations. Model 5 (i.e., 5 latent categories) had the lowest BIC (7 112.69) and aBIC (6 909.38), with a relatively low AIC (6 768.20), indicating the best model fit; thus, five latent categories represented the optimal combination in this study. The five latent categories (and their respective proportions of study participants) were the healthy control group (41.73%), the hypertension group (31.28%), the diabetes-hypertension group (19.28%), the severe illness group (5.29%), and the other metabolic diseases group (2.43%). According to multiple linear regression analyses, compared with the healthy control group, the diabetes-hypertension group had significantly lower BI-20 scores (b=-0.952, 95%CI: -1.317‒ -0.587, P<0.001) and lower IADL scores (b=-0.744, 95%CI: -0.999‒ -0.489, P<0.001); the severe illness group (b=-0.644, 95%CI: -1.072‒ -0.217, P=0.003) and the hypertension group (b=-0.344, 95%CI: -0.562‒ -0.125, P=0.002) had lower IADL scores. According to multivariate logistic regression analyses, compared with the healthy control group, older adults in the diabetes-hypertension group had a higher risk of disability (OR=2.835, 95%CI: 1.392‒5.774), impaired ADL function (OR=2.470, 95%CI: 1.637‒3.726), and impaired IADL function (OR=1.739, 95%CI: 1.264‒2.392); older adults in the severe illness group had a higher risk of impaired ADL function (OR=2.206, 95%CI: 1.171‒4.155). ConclusionAmong the elderly participating in the Survey on Health Status and Health Service Utilization of Permanent Residents in Xuhui District of Shanghai, diabetes-hypertension is one of the key chronic disease comorbidity combinations and has adverse effects on both ADL and IADL. Community health management should prioritize the elderly with diabetes-hypertension comorbidity, and strengthen early screening and comprehensive interventions to slow the decline in ADL and IADL.

Collagen is a major structural protein in the matrix of animal cells and the most widely distributed and abundant functional protein in mammals. Collagen’s good biocompatibility, biodegradability and biological activity make it a very valuable biomaterial. According to the source of collagen, it can be broadly categorized into two types: one is animal collagen; the other is recombinant collagen. Animal collagen is mainly extracted and purified from animal connective tissues by chemical methods, such as acid, alkali and enzyme methods, etc. Recombinant collagen refers to collagen produced by gene splicing technology, where the amino acid sequence is first designed and improved according to one’s own needs, and the gene sequence of improved recombinant collagen is highly consistent with that of human beings, and then the designed gene sequence is cloned into the appropriate vector, and then transferred to the appropriate expression vector. The designed gene sequence is cloned into a suitable vector, and then transferred to a suitable expression system for full expression, and finally the target protein is obtained by extraction and purification technology. Recombinant collagen has excellent histocompatibility and water solubility, can be directly absorbed by the human body and participate in the construction of collagen, remodeling of the extracellular matrix, cell growth, wound healing and site filling, etc., which has demonstrated significant effects, and has become the focus of the development of modern biomedical materials. This paper firstly elaborates the structure, type, and tissue distribution of human collagen, as well as the associated genetic diseases of different types of collagen, then introduces the specific process of producing animal source collagen and recombinant collagen, explains the advantages of recombinant collagen production method, and then introduces the various systems of expressing recombinant collagen, as well as their advantages and disadvantages, and finally briefly introduces the application of animal collagen, focusing on the use of animal collagen in the development of biopharmaceutical materials. In terms of application, it focuses on the use of animal disease models exploring the application effects of recombinant collagen in wound hemostasis, wound repair, corneal therapy, female pelvic floor dysfunction (FPFD), vaginal atrophy (VA) and vaginal dryness, thin endometritis (TE), chronic endometritis (CE), bone tissue regeneration in vivo, cardiovascular diseases, breast cancer (BC) and anti-aging. The mechanism of action of recombinant collagen in the treatment of FPFD and CE was introduced, and the clinical application and curative effect of recombinant collagen in skin burn, skin wound, dermatitis, acne and menopausal urogenital syndrome (GSM) were summarized. From the exploratory studies and clinical applications, it is evident that recombinant collagen has demonstrated surprising effects in the treatment of all types of diseases, such as reducing inflammation, promoting cell proliferation, migration and adhesion, increasing collagen deposition, and remodeling the extracellular matrix. At the end of the review, the challenges faced by recombinant collagen are summarized: to develop new recombinant collagen types and dosage forms, to explore the mechanism of action of recombinant collagen, and to provide an outlook for the future development and application of recombinant collagen.

Objective To investigate the therapeutic efficacy of the combination of upper limb rehabilitation robots(ULRR)and ultrasound-guided extracorporeal shock wave(ESW)in the treatment of mild to moderate rotator cuff injuries.Methods A total of 90 patients with mild to moderate rotator cuff injuries,who were admitted to the Second Affiliated Hospital of Anhui Medical University between January 2023 and March 2024,were selected and randomly assigned to three groups:Group A(basic rehabilitation),Group B(basic rehabilitation+ESW),and Group C(basic rehabilitation+ESW+ULRR),with 30 patients in each group.Before and after treatment,shoulder pain was assessed using the visual analogue scale(VAS).Proprioception was evaluated based on shoulder joint position reproduction error.The integral electromyography(iEMG)and root mean square(RMS)values of the median tract,supraspinatus,infraspinatus,and deltoid muscles on the affected side were measured using surface electromyography(sEMG).The active range of motion(AROM)for external rotation,abduction,and forward flexion of the affected shoulder was measured using a standard goniometer.Overall shoulder function was evaluated using the Constant-Murley Shoulder Score(CMS).The clinical efficacy rate and patient satisfaction levels were compared among the three groups.Results After treatment,the VAS score and shoulder position reproduction deviation angle in all three groups significantly decreased.Additionally,the iEMG and RMS values of the middle deltoid,supraspinatus,and infraspinatus muscles;the AROM of shoulder external rotation,abduction,and forward flexion;and the CMS scores(including pain,activities of daily living,active range of motion,and muscle strength)all showed significant improvement.Furthermore,the degree of improvement in all evaluated parameters in Group C was significantly greater than that observed in Groups A and B(P<0.05).Moreover,Group C demon-strated a significantly higher clinical response rate and greater patient satisfaction compared to Groups A and B(P<0.05).Conclusion For patients with mild to moderate rotator cuff injuries,the integration of an upper limb rehabilitation robot with extracorporeal shock wave therapy demonstrates superior therapeutic outcomes,effectively alleviating pain,enhancing motor function and proprioception,and increasing overall patient satisfaction.

Objective:To investigate the correlation between peri-coronary fat attenuation index (FAI) and plaque formation in patients with myocardial bridge (MB) of the left anterior descending artery (LAD) using coronary computed tomography angiography (CCTA) and to develop an optimal predictive model to explore the potential application of FAI in the primary prevention of MB related atherosclerosis.Methods:In this retrospective study, prediction models associated with perivascular fat inflammation were developed and validated using both logistic regression and machine learning (ML) algorithm. A training dataset was collected from 253 patients who underwent ≥2 coronary computed tomography angiography (CCTA) with ≥3 months intervals from one tertiary hospital from January 2007 to April 2021 and had baseline CCTA showing no plaques in LAD MB. The median follow-up time was 3.2 years. According to the same criteria, a total of 75 LAD MB patients from four other hospitals were included to form an independent external validation dataset, with a median follow-up time of 1.8 years. Receiver operating characteristic (ROC) curve analysis with integrated discrimination improvement (IDI) and category net reclassification index (NRI) were used to compare the performance of the predictive models.Results:62 patients (24.5%) in the training dataset had proximal plaque formation in LAD MB, while 22 patients (29.3%) in the external validation dataset had plaque formation during the follow-up period. Baseline FAI within the longitudinal distance equal to 30 mm proximal to the MB entrance was an independent predictor ( OR=1.068, P=0.046). According to the model results, ROC curves were plotted. The AUC of Model 1 was 0.822, and the AUCs of Model 2 and 1 were 0.821 and 0.591 in the training dataset. After the DeLong test, the AUC of Model 1 was superior to that of Model 2 ( Z=2.839, P=0.005) and Model 1 ( Z=6.124, P<0.001). These findings were further validated in the external validation dataset, where ML-model 3 yielded the best predictive performance, outperforming the logistic regression-based Model 2 (categorical NRI=0.359, P=0.048; IDI=0.108, P=0.046). Conclusion:FAI measured within the 30 mm proximal to the entrance of MBs due to its prone to plaque development is an independent predictor for atherosclerotic plaque formation. The ML-prediction model based on a decision tree algorithm combines FAI, MB anatomical features, and patient risk factors, which is beneficial for patients undergoing routine CCTA examination to identify inflamed coronary arteries in advance and guide the clinical adoption of more targeted preventive treatment, including anti-inflammatory treatment.