Objective:To investigate the application value of dual-energy computer tomo-graphy (CT) multi-parameter imaging in predicting the pathological grade of pancreatic ductal adeno-carcinoma (PDAC).Methods:The retrospective cohort study was conducted. The clinicopatholo-gical data of 147 patients with PDAC who were admitted to The Fifth Affiliated Hospital of Wenzhou Medical University from January 2017 to August 2023 were collected. There were 102 males and 45 females, aged (59±10)years. All patients underwent preoperative dual-energy CT examination and postoperative histopathological examination. The 147 patients were divided into a training set of 103 cases and a test set of 44 cases by stratified random sampling at a ratio of 7∶3. The training set was used to construct the prediction model, and the test set was used to verify the effectiveness of prediction model. Observation indicators: (1) analysis of factors affecting the pathological grade of PDAC patients in the training set; (2) construction and evaluation of the fusion prediction model for pathological grade of PDAC. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. Univariate and multivariate analyses were conducted using the Logistic regression model. The performance of the model was evaluated by receiver operating characteristic (ROC) curve, and the area under the curve (AUC), accuracy, sensitivity and specificity were calculated. The Delong test was used to analyze the effec-tiveness of model. The calibration curve and decision curve of Hosmer-Lemeshow test were used to evaluate the consistency and clinical application value of the nomogram, respectively. Results:(1) Analysis of factors affecting the pathological grade of PDAC patients in the training set. Results of multivariate analysis showed that tumor cystic necrosis, vascular invasion, standardized iodine concentration (NIC) in venous phase, effective atomic number (Zeff) in venous phase, and energy spectrum curve slope (λ HU) in venous phase were all independent factors affecting the pathological grade of PDAC patients in the training set ( odds ratio=4.326, 3.887, 4.155, 5.389, 3.164, 95% confidence interval as 1.167-16.033, 1.111-13.592, 1.707-10.113, 1.284-22.613, 1.247-8.028, P<0.05). (2) Construction and evaluation of the fusion prediction model for pathological grade of PDAC. Accor-ding to the results of multivariate analysis, tumor cystic necrosis, vascular invasion, NIC in venous phase, Zeff in venous phase and λ HU in venous phase were all included to construct the clinical-imaging fusion prediction nomogram model. The AUC, accuracy, sensitivity and specificity of the fusion prediction model in the training set were 0.938 (95% confidence interval as 0.896-0.981), 87.38%, 89.74% and 85.94%, respectively. The above indicators of the fusion prediction model in the test set were 0.893 (95% confidence interval as 0.802-0.985), 84.09%, 82.35% and 85.19%, respectively. Results of Delong test showed that there was no significant difference in AUC between the training set and the test set ( Z=0.343, P>0.05). Results of Hosmer-Lemeshow test showed that the fusion prediction model had a good fit in the training set and the test set ( χ2=3.042, 7.545, P>0.05). Results of calibration curve showed that the predictive ability of the fusion prediction model was good. Conclusions:Multiple parameters in venous phase of the dual-energy CT can be used as imaging markers for preoperative evaluation of the pathological grade of patients with PDAC. Establishing a clinical-imaging fusion prediction model can effectively predict the pathological grade of PDAC.

Objective:To investigate the disparities in breast cancer burden and changing epidemiological trends between China and the United States(US)from 1990 to 2021 and identify the key driving factors.Methods:The Global Burden of Disease database(1990-2021)was utilized to analyze breast cancer incidence,mortality,and disability adjusted life years(DALYs)in China and the US;we also assessed the as-sociations with risk factors(e.g.,obesity and smoking)through regression models and spatiotemporal analysis.Results:China's breast can-cer age-standardized incidence rate(ASIR)surged from 9.08/100,000 in 1990 to 19.36/100,000 in 2021,whereas the US ASIR declined from 44.37/100,000 to 37.49/100,000.Regarding the age-standardized mortality rate(ASMR),China saw a marginal reduction from 4.70/100,000 to 4.40/100,000,whereas the US experienced a significant decline from 13.03/100,000 to 9.28/100,000,narrowing the mortality gap from 2.8-fold to 2.1-fold.Key risk factors contributing to mortality and DALYs included smoking,exposure to secondhand smoke,low physical activity,high red meat and alcohol intake,elevated fasting blood glucose levels,and high body mass index.The rising cancer incidence in China is associated with the westernization of lifestyles and changes in fertility patterns,whereas the United States has achieved a dual de-cline in both incidence and mortality rates through widespread screening and control of hormone replacement therapy.Conclusions:Both the incidence and mortality rates of breast cancer in China rank among the highest globally,with incidence rates still increasing,indicating severe issues in prevention and control.In contrast,although the incidence rate in the US is higher than that in China,it shows a declining trend.To alleviate the growing burden of breast cancer,China must further enhance the intensity and coverage of breast cancer screening.

Objective:To investigate the enhancement effect of deep progressive reconstruction (DPR) algorithm on image quality and standardized uptake value (SUV) of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) in obese patients. Methods:The images of a total of 27 obese patients,who underwent 18F-FDG PET/CT in Affiliated Nanjing Hospital of Nanjing Medical University from September 2023 to May 2024,were retrospectively enrolled. The images of all patients were collected by using uMI 780 PET/CT. Ordered subset expectation maximization (OSEM) iterative algorithm and DPR algorithm were adopted to reconstruct PET images,and measure counting rate of scattering coincidence of PET/CT images,counting rate of true coincidence,noise equivalent counting rate (NECR) and scattering fraction (SF). The quality indicators of PET images included signal-to-noise ratio (SNR),the maximum SUV (SUVmax) of lesions,the tumor-to-background ratio (TBR),the contrast-to-noise ratio (CNR) and the visual scores of 18F-FDG PET/CT images on livers were evaluated. The differences and consistency of various indicators between DPR and OSEM reconstruction algorithms were further analyzed. Results:The average 18F-FDG PET/CT injection activity of 27 patients was (0.12±0.01) mCi (1 mCi=37 MBq)/kg,and the counting rate of true coincidence,NECR and SF of PET images were respectively (153.73±25.09),(44.81±8.47) kcps and (36.77±1.91)％. The SNR of liver obtained by DPR algorithm was (15.83±3.60),which was significantly higher than that (9.06±1.87) of OSEM algorithm,with statistically significant (t=20.6,P<0.05),and there was significantly correlation in liver SNR between two algorithms (R2=0.91,P<0.05). In 27 uptake 18F-FDG PET/CT lesions,the SUVmax,TBR and CNR of lesions that were obtained from OSEM algorithm were respectively (5.86±1.49),(1.95±0.49) and (17.74±4.77),which were lower than corresponding those of DPR algorithm,and the differences were significant (t=9.03,8.79,15.49,P<0.05),respectively. There were significant correlations in SUVmax,TBR and CNR between the two algorithms (R2=0.71,0.70,0.76,P<0.05),respectively. The visual scores of PET images obtained from the DPR algorithm was 4 (3,5) scores,which was significantly higher than 3 (2,4) scores of OSEM algorithm,and the difference of that between two algorithms was significant (U=396,P<0.05). Conclusion:The scattering effect of 18F-FDG PET/CT imaging is stronger in obese patients,whose counting rate of equivalent effect of noise is lower. The DPR reconstruction algorithm can significantly improve the SNR and lesion contrast of PET images than the OSEM algorithm,which has significant gain effect on the SUVmax of lesions,and it can significantly improve the quality of 18F-FDG PET/PET images in obese patients.

Objective To understand the current status of traditional Chinese medicine(TCM)systematic reviews/Meta-analysis over the past 10 years.Methods Cochrane Database of Systematic Reviews,PubMed,Web of Knowledge,CNKI,SinoMed,WanFang Data,VIP databases,as well as the Cochrane Register and PROSPERO registration platform were searched to collect TCM-related systematic reviews/Meta-analysis published between January 2015 and December 2024.Literature was screened,and standardization of institutions,countries,and journals was performed.Data cleaning was conducted,and trends in publication years,high-frequency diseases,journals,institutions,and highly cited papers were analyzed.Results A total of 11,174 papers were included,involving approximately 56,656 authors from 1,422 institutions across 44 countries,covering 1,300 journals and 1,070 diseases.The top five institutions in terms of publications were Beijing University of Chinese Medicine(954 papers),Guangzhou University of Chinese Medicine(928 papers),China Academy of Chinese Medical Sciences(537 papers),Tianjin University of Chinese Medicine(460 papers),and Chengdu University of Chinese Medicine(393 papers).Foreign institutions with the highest publication volumes were concentrated in South Korea,Iran,and Australia.The most frequently published Chinese journal was Zhongyi Clinical Research with 332 papers,while the most published English journal was Evidence-Based Complementary and Alternative Medicine with 311 papers.There were 282 single-author papers involving 271 authors,and the most cited paper was referenced 323 times,The three most frequently studied diseases were diabetes(267 papers,2.39％),angina pectoris(214 papers,1.92％),and osteoarthritis(210 papers,1.88％).Non-pharmacological interventions such as acupuncture(1,265 papers,11.32％),auricular therapy(101 papers,0.90％),and Tai Chi(98 papers,0.88％)were most frequently reported.In pharmacological interventions,studies on Tripterygium wilfordii tablets(76 papers,0.68％)and Danhong injection(54 papers,0.48％)were more common.Conclusion The systematic reviews/Meta-analysis method is widely used in the field of TCM,and the field continues to grow.Active academic teams,institutions,and journals have emerged.Over the past decade,there has been a considerable body of evidence in Chinese systematic reviews on TCM for chronic diseases such as diabetes,angina pectoris,and osteoarthritis.In English-language studies,non-pharmacological therapies like acupuncture have been more widely reported,and some high-impact studies have emerged.However,challenges remain,such as issues with research transparency and methodological standardization.Future efforts should focus on establishing transparent systems and quality control mechanisms to further enhance the reliability,accuracy,and dissemination of TCM evidence-based research.

In order to study the effects of prostaglandin D2(PGD2)on cow bone marrow-derived macrophages induced by E.coli,cultured cow bone marrow-derived macrophages were taken as the research object.The effects of endogenous and exogenous PGD2 on the secretion and phagocytosis of E.coli induced proinflammatory cytokines(IL-1β,IL-6 and TNF-α)in macrophages were ana-lyzed.The results showed that the synthesis of PGD2 in macrophages induced by E.coli is depend-ent on the natural pattern recognition receptors TLR2,TLR4 and NLRP3.Inhibition of endogenous PGD2can down-regulate the secretion of pro-inflammatory cytokines(IL-1β,IL-6 and TNF-α)in E.coli induced macrophages(P＜0.001),and inhibition of endogenous PGD2 can enhance the kill-ing function of macrophages to a certain extent(P＜0.01).In addition,exogenous PGD2 could up-regulate the secretion of pro-inflammatory cytokines(IL-1β,IL-6 and TNF-α)in macrophages af-ter E.coli stimulation(P＜0.01),and exogenous PGD2 could weaken the killing function of mac-rophages within a certain concentration range(P＜0.01).Results indicated that PGD2 had certain effects on the secretion of cytokines and phagocytosis and killing function of macrophages induced by E.coli.

Objective:To investigate the enhancement effect of deep progressive reconstruction (DPR) algorithm on image quality and standardized uptake value (SUV) of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) in obese patients. Methods:The images of a total of 27 obese patients,who underwent 18F-FDG PET/CT in Affiliated Nanjing Hospital of Nanjing Medical University from September 2023 to May 2024,were retrospectively enrolled. The images of all patients were collected by using uMI 780 PET/CT. Ordered subset expectation maximization (OSEM) iterative algorithm and DPR algorithm were adopted to reconstruct PET images,and measure counting rate of scattering coincidence of PET/CT images,counting rate of true coincidence,noise equivalent counting rate (NECR) and scattering fraction (SF). The quality indicators of PET images included signal-to-noise ratio (SNR),the maximum SUV (SUVmax) of lesions,the tumor-to-background ratio (TBR),the contrast-to-noise ratio (CNR) and the visual scores of 18F-FDG PET/CT images on livers were evaluated. The differences and consistency of various indicators between DPR and OSEM reconstruction algorithms were further analyzed. Results:The average 18F-FDG PET/CT injection activity of 27 patients was (0.12±0.01) mCi (1 mCi=37 MBq)/kg,and the counting rate of true coincidence,NECR and SF of PET images were respectively (153.73±25.09),(44.81±8.47) kcps and (36.77±1.91)％. The SNR of liver obtained by DPR algorithm was (15.83±3.60),which was significantly higher than that (9.06±1.87) of OSEM algorithm,with statistically significant (t=20.6,P<0.05),and there was significantly correlation in liver SNR between two algorithms (R2=0.91,P<0.05). In 27 uptake 18F-FDG PET/CT lesions,the SUVmax,TBR and CNR of lesions that were obtained from OSEM algorithm were respectively (5.86±1.49),(1.95±0.49) and (17.74±4.77),which were lower than corresponding those of DPR algorithm,and the differences were significant (t=9.03,8.79,15.49,P<0.05),respectively. There were significant correlations in SUVmax,TBR and CNR between the two algorithms (R2=0.71,0.70,0.76,P<0.05),respectively. The visual scores of PET images obtained from the DPR algorithm was 4 (3,5) scores,which was significantly higher than 3 (2,4) scores of OSEM algorithm,and the difference of that between two algorithms was significant (U=396,P<0.05). Conclusion:The scattering effect of 18F-FDG PET/CT imaging is stronger in obese patients,whose counting rate of equivalent effect of noise is lower. The DPR reconstruction algorithm can significantly improve the SNR and lesion contrast of PET images than the OSEM algorithm,which has significant gain effect on the SUVmax of lesions,and it can significantly improve the quality of 18F-FDG PET/PET images in obese patients.

Objective:To investigate the application value of dual-energy computer tomo-graphy (CT) multi-parameter imaging in predicting the pathological grade of pancreatic ductal adeno-carcinoma (PDAC).Methods:The retrospective cohort study was conducted. The clinicopatholo-gical data of 147 patients with PDAC who were admitted to The Fifth Affiliated Hospital of Wenzhou Medical University from January 2017 to August 2023 were collected. There were 102 males and 45 females, aged (59±10)years. All patients underwent preoperative dual-energy CT examination and postoperative histopathological examination. The 147 patients were divided into a training set of 103 cases and a test set of 44 cases by stratified random sampling at a ratio of 7∶3. The training set was used to construct the prediction model, and the test set was used to verify the effectiveness of prediction model. Observation indicators: (1) analysis of factors affecting the pathological grade of PDAC patients in the training set; (2) construction and evaluation of the fusion prediction model for pathological grade of PDAC. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. Univariate and multivariate analyses were conducted using the Logistic regression model. The performance of the model was evaluated by receiver operating characteristic (ROC) curve, and the area under the curve (AUC), accuracy, sensitivity and specificity were calculated. The Delong test was used to analyze the effec-tiveness of model. The calibration curve and decision curve of Hosmer-Lemeshow test were used to evaluate the consistency and clinical application value of the nomogram, respectively. Results:(1) Analysis of factors affecting the pathological grade of PDAC patients in the training set. Results of multivariate analysis showed that tumor cystic necrosis, vascular invasion, standardized iodine concentration (NIC) in venous phase, effective atomic number (Zeff) in venous phase, and energy spectrum curve slope (λ HU) in venous phase were all independent factors affecting the pathological grade of PDAC patients in the training set ( odds ratio=4.326, 3.887, 4.155, 5.389, 3.164, 95% confidence interval as 1.167-16.033, 1.111-13.592, 1.707-10.113, 1.284-22.613, 1.247-8.028, P<0.05). (2) Construction and evaluation of the fusion prediction model for pathological grade of PDAC. Accor-ding to the results of multivariate analysis, tumor cystic necrosis, vascular invasion, NIC in venous phase, Zeff in venous phase and λ HU in venous phase were all included to construct the clinical-imaging fusion prediction nomogram model. The AUC, accuracy, sensitivity and specificity of the fusion prediction model in the training set were 0.938 (95% confidence interval as 0.896-0.981), 87.38%, 89.74% and 85.94%, respectively. The above indicators of the fusion prediction model in the test set were 0.893 (95% confidence interval as 0.802-0.985), 84.09%, 82.35% and 85.19%, respectively. Results of Delong test showed that there was no significant difference in AUC between the training set and the test set ( Z=0.343, P>0.05). Results of Hosmer-Lemeshow test showed that the fusion prediction model had a good fit in the training set and the test set ( χ2=3.042, 7.545, P>0.05). Results of calibration curve showed that the predictive ability of the fusion prediction model was good. Conclusions:Multiple parameters in venous phase of the dual-energy CT can be used as imaging markers for preoperative evaluation of the pathological grade of patients with PDAC. Establishing a clinical-imaging fusion prediction model can effectively predict the pathological grade of PDAC.

Objective To carry out emergency medical system modification design for EC135 P3H helicopter without compromising the original airframe structure so as to enhance aeromedical rescue capabilities.Methods Firstly,the original cabin seats were removed and medical floor was installed in the cabin;secondly,the medical chair,medical stretcher trolley and its fixing components,storage boxes and oxygen cylinders were mounted onto the floor;finally,a medical equipment fixing frame was formed based on the original helicopter sill structure so as to accommodate medical devices such as defibrillators,ventilators and injection pumps.The modification design scheme had its effectiveness verified with overall aircraft load balance analysis,mechanical analysis,dynamic impact tests of seats and actual modification and flight tests.Results EC135 P3H helicopter proved to meet all the airworthiness certification requirements after emergency medical system modification.Conclusion The proposed modification scheme enables EC135 P3H helicopter to rapidly transition between standard and medical configurations,enhancing its emergency medical rescue capabilities and providing references for medical modifications of helicopters with similar configurations.

Objective To carry out emergency medical system modification design for EC135 P3H helicopter without compromising the original airframe structure so as to enhance aeromedical rescue capabilities.Methods Firstly,the original cabin seats were removed and medical floor was installed in the cabin;secondly,the medical chair,medical stretcher trolley and its fixing components,storage boxes and oxygen cylinders were mounted onto the floor;finally,a medical equipment fixing frame was formed based on the original helicopter sill structure so as to accommodate medical devices such as defibrillators,ventilators and injection pumps.The modification design scheme had its effectiveness verified with overall aircraft load balance analysis,mechanical analysis,dynamic impact tests of seats and actual modification and flight tests.Results EC135 P3H helicopter proved to meet all the airworthiness certification requirements after emergency medical system modification.Conclusion The proposed modification scheme enables EC135 P3H helicopter to rapidly transition between standard and medical configurations,enhancing its emergency medical rescue capabilities and providing references for medical modifications of helicopters with similar configurations.

Objective:This study aims to explore the intervention effects of five different intelligent rehabilitation technologies, namely immersive virtual reality (imVR), non-fully immersive virtual reality (Nf-imVR), augmented reality, brain-computer interface (BCI), and rehabilitation robot (RT), on the upper limb function and activities of daily living of stroke patients with upper limb dysfunction.Methods:A computer-based search was conducted in PubMed, Web of Science, Embase, Cochrane Library, China National Knowledge Infrastructure, and Wanfang Databases for randomized controlled trials (RCT) on the intervention effects of different intelligent rehabilitation technologies on stroke patients with upper limb dysfunction. Manual search and other retrieval methods were also supplemented. The retrieval time limit was from the establishment of the databases to May 31, 2024. Data were extracted and the methodological quality was evaluated, and a network Meta-analysis was performed using Stata 17.0 software.Results:A total of 34 articals were included, involving 1 926 patients, and the studies included five intelligent rehabilitation technologies. The control groups all received dose-matched conventional physical training. The results of the network Meta-analysis showed that, compared with the dose-matched conventional physical training, in terms of improving upper limb function, the BCI had the best effect, followed by imVR, RT, Nf-imVR, and augmented reality in sequence; in terms of improving activities of daily living, the BCI still had the best effect, followed by imVR, RT, augmented reality, and Nf-imVR in sequence. The clustering ranking of upper limb function and activities of daily living was BCI >imVR > RT > Nf-imVR > augmented reality in turn.Conclusions:Intelligent rehabilitation technologies have advantages in improving the upper limb function and activities of daily living of stroke patients with upper limb dysfunction, and the BCI has obvious advantages.