Background Polycyclic aromatic hydrocarbons (PAHs) are widely known atmospheric pollutants, which can cause serious harm to human body and ecological environment. Objective To analyze the concentrations and sources of PAHs in atmospheric PM_2.5 in Zhifu District and Longkou City during the heating period in Yantai. Methods Two monitoring sites in Zhifu District and Longkou City of Yantai were selected, and PM_2.5 sample collection was carried out from April 2023 to March 2024. Gas chromatography-mass spectrometry was applied to analyze the concentrations of PAHs in atmospheric PM_2.5 during the heating period (from November 2023 to March 2024) and the non-heating period (from April to October 2023). The concentrations of PAHs in the two periods were compared and the sources of PAHs during the heating period were analyzed by characteristic ratio method. Results During the heating period, the total concentration ranges of PAHs in atmospheric PM_2.5 at the monitoring sites in Zhifu District and Longkou City of Yantai were (1.59-23.70) ng·m⁻³ and (2.08-149.72) ng·m⁻³ respectively, and the medians (M) and the 25th and 75th percentiles (P₂₅, P₇₅) were 4.99 (2.61, 8.09) ng·m⁻³ and 15.46 (8.15, 29.05) ng·m⁻³ respectively. The PAHs concentrations in Longkou City were significantly higher than those in Zhifu District in all months (P<0.05). The highest median total concentrations of PAHs in both sites were reported in January (8.14 ng·m⁻³ and 81.56 ng·m⁻³ respectively). In the non-heating period, the M (P₂₅, P₇₅) of the total PAHs concentrations at the two sites were 1.59 (1.59, 2.78) ng·m⁻³ and 4.11 (2.94, 7.97) ng·m⁻³ respectively, much lower than those in the heating period (P<0.01). The order of composition of PAHs by ring number in PM_2.5 at both sites was 4-ring> 5-ring> 6-ring, with the 4-ring contributing the largest proportion (65.33% and 46.39% respectively). Fluoranthene had the highest concentration among PAHs at both sites, with concentrations M (P₂₅, P₇₅) of 1.29 (0.51, 1.78) ng·m⁻³ and 2.32 (1.30, 3.82) ng·m⁻³ respectively. The characteristic ratios of fluoranthene/(fluoranthene + pyrene), fluoranthene/pyrene, benzo[a]anthracene/(benzo[a]anthracene + chrysene), pyrene/benzo[a]pyrene, benzo[a]pyrene/(benzo[a]pyrene + chrysene), benzo[a]pyrene/benzo[g,h,i]pyrene, and indeno[1,2,3-c,d]pyrene/(indeno[1,2,3-c,d]pyrene + benzo[g,h,i]pyrene) in Zhifu District were 0.62, 1.65, 0.41, 4.48, 0.50, 0.93 and 0.47 respectively, and those in Longkou were 0.57, 1.35, 0.40, 2.89, 0.29, 0.79 and 0.47 respectively. The results showed that PAHs pollutants were generated by combination of coal combustion, vehicle exhaust emissions and gasoline combustion. Conclusion During the heating period in Yantai area, the total concentration of PAHs in atmospheric PM_2.5 is significantly higher than that in the non-heating period. Among them, during the heating period, the pollution level in Longkou City is significantly higher than that in Zhifu District. The local PAHs may be sourced from mixed pollution, and the main sources include gasoline, and coal combustion and vehicle exhaust emissions.

Objective:To evaluate the accuracy of an artificial intelligence (AI) model in measuring key angles on pelvic radiographs of the hip and assess its effectiveness in diagnosing developmental dysplasia of the hip (DDH) and borderline developmental dysplasia of the hip (BDDH).Methods:A retrospective analysis was conducted using anteroposterior pelvic X-ray films from 1,029 patients with suspected DDH. The data were collected from the Department of Radiology, Fourth Medical Center of the Chinese PLA General Hospital. Among the patients, 273 were male, and 756 were female, with an average age of 57.01 ± 18.16 years (range, 12-88 years). The dataset was randomly divided into a training set (720 cases), a test set (206 cases), and a validation set (103 cases). Two radiologists identified and marked key anatomical points of the hip joint to establish the training dataset, which was then used to develop a deep learning-based AI model capable of locating these key anatomical positions. Using the identified anatomical points, the AI model automatically measured and calculated the Sharp angle, center-edge (CE) angle, and T?nnis angle in the test dataset. The measurement results from the AI model were compared with those of the radiologists to evaluate the model's accuracy. The validation set was used to optimize model parameters, and the test dataset was used to evaluate the diagnostic performance of DDH. Receiver operating characteristic (ROC) curves were employed to assess the diagnostic efficacy of the AI model for DDH and BDDH.Results:The accuracy rates of the AI model in measuring the left Sharp angle, CE angle, and T?nnis angle for diagnosing DDH were 89.8%, 90.1%, and 86.8%, respectively. For the right side, the accuracy rates were 93.7%, 92.2%, and 80.5%, respectively. There were no statistically significant differences in the mean values of the Sharp, T?nnis, and CE angles between manual and AI measurements ( P>0.05). Pearson correlation tests and intraclass correlation coefficient (ICC) analyses revealed high consistency between AI and manual measurements of the Sharp angle, T?nnis angle, and CE angle, with r-values and ICC values exceeding 0.75. Additionally, the AI model performed measurements significantly faster (1.7±0.1 s) than radiologists (88.1±8.4 s and 90.3±7.4 s, P<0.001). The areas under the ROC curves (AUCs) for diagnosing DDH using the Sharp angle, CE angle, and T?nnis angle measured by the AI model were 0.883, 0.922, and 0.908 (left side) and 0.924, 0.871, and 0.922 (right side), respectively. For diagnosing BDDH, the AUCs of the left and right CE angles measured by the AI model were 0.787 and 0.676, respectively. Kappa test results indicated good agreement between the AI model and manual measurements as well as final clinical diagnoses. For the CE angle, the κ value of the AI model was 0.663, while κ values for the Sharp and T?nnis angles were all greater than 0.800. Conclusion:The convolutional neural network-based AI model effectively and automatically measures the Sharp, CE, and T?nnis angles and demonstrates high diagnostic efficacy for DDH and BDDH.

Objective To explore the risk factors of apathy and correlations with cognitive function in patients with hypertension combined with cerebral small vessel disease(CSVD).Methods Totally 141 patients with hypertension combined with CSVD were prospectively enrolled and were divided into apathy group(n=43)and non-apathy group(n= 98)according to neuropsychiatric inventory-apathy scale(NPI-Apathy)scores.The general data,imaging marker scores and total imaging burden scores were compared between groups.In hypertension combined with CSVD patients,multivariate logistic regression analysis was performed to screen the independent risk factors of apathy,and Spearman correlation analysis was also performed to observe the correlation of apathy and cognitive function.Results The patients'age,high density lipoprotein cholesterol(HDL-C),Fazekas scores of lateral periventricular white matter hyper-intensity(WMH),cerebral microbleed of depth/infratentorial and total imaging burden scores of apathy group were all higher,while mini-mental state examination(MMSE)and Montreal cognitive assessment(MoCA)scores were both lower than those of non-apathy group(all P＜0.05).HDL-C and Fazekas scores of lateral periventricular WMH were both independent risk factors for apathy(both P＜0.05),while NPI-Apathy scores were moderately negatively correlated with cognitive function in patients with hypertension combined with CSVD(r=-0.543,-0.484,both P＜0.001).Conclusion HDL-C and Fazekas scores of lateral periventricular WMH were both independent risk factors for apathy in patients with hypertension combined with CSVD.The more severe the apathy,the lower the cognitive function.

Objective: To prospectively compare single-shot (SS) echo-planar imaging (EPI) and field-of-view optimized and constrained undistorted single-shot multiplexed sensitivity-encoding (FOCUS MUSE) for diffusion-weighted imaging (DWI) in evaluating thyroid-associated ophthalmopathy (TAO). Materials and Methods: SS EPI and FOCUS MUSE DWIs were obtained from 39 patients with TAO (18 male; mean ± standard deviation: 48.3 ± 13.3 years) and 26 healthy controls (9 male; mean ± standard deviation: 43.0 ± 18.5 years). Two radiologists scored the visual image quality using a 4-point Likert scale. The image quality score, signal-to-noise ratio (SNR), contrast-tonoise ratio (CNR), and apparent diffusion coefficient (ADC) of extraocular muscles (EOMs) were compared between the two DWIs. Differences in the ADC of EOMs were also evaluated. The performance of discriminating active from inactive TAO was assessed using receiver operating characteristic curves. The correlation between ADC and clinical activity score (CAS) was analyzed using Spearman correlation. Results: Compared with SS EPI DWI, FOCUS MUSE DWI demonstrated significantly higher image quality scores (P < 0.001), a higher SNR and CNR on the lateral rectus muscle (LRM) and medial rectus muscle (MRM) (P < 0.05), and a non-significant difference in the ADC of the LRM and MRM. Active TAO showed higher ADC than inactive TAO and healthy controls with both SS EPI and FOCUS MUSE DWIs (P < 0.001). Inactive TAO and healthy controls did not show a significant ADC difference with both DWIs. Compared with SS EPI DWI, FOCUS MUSE DWI demonstrated better discrimination of active from inactive TAO (AUC:0.925 vs. 0.779; P = 0.007). The ADC was significantly correlated with CAS in SS EPI DWI (r = 0.391, P < 0.001) and FOCUS MUSE DWI (r = 0.645, P < 0.001). Conclusion FOCUS MUSE DWI provides better images for evaluating EOMs and better performance in diagnosing active TAO than SS EPI DWI. The application of FOCUS MUSE will facilitate the DWI evaluation of TAO.

Objective:Construct the hospital"three in one"quality control system suitable for medical insurance DRG payment,and realize the safe,stable and efficient operation of medical insurance DRG actual payment. Methods:By using data aggregation and fusion technology,through standardized governance of data across the entire basin,optimization of the entire process quality control system and comprehensive intelligent quality control system management,the visualization and interactive analysis of data could be achieved,thereby improving the precision support of hospital operation efficiency. Results:After actual operation,the disease enrollment rate reached to 99％,the Case Mix Index (CMI) boosted from 0.96 to 1.32,the average length of hospital stay decreased by 1.07 days,the time consumption index and the cost consumption index both fell below 1. The supervision method extended from manual sampling to intelligent quality control,the supervision process extended from a fixed process to a dynamic process and the focus of supervision extends from the review of the settlement list to the supervision of medical behavior. Conclusion:Construct the hospital"three in one"quality control system is a necessary way to promote DRG paying medical institutions to enter the fast lane of standardization,collaboration and refined management,which made a beneficial attempt for the practical application of DRG payment in hospitals.

Objective:Construct the hospital"three in one"quality control system suitable for medical insurance DRG payment,and realize the safe,stable and efficient operation of medical insurance DRG actual payment. Methods:By using data aggregation and fusion technology,through standardized governance of data across the entire basin,optimization of the entire process quality control system and comprehensive intelligent quality control system management,the visualization and interactive analysis of data could be achieved,thereby improving the precision support of hospital operation efficiency. Results:After actual operation,the disease enrollment rate reached to 99％,the Case Mix Index (CMI) boosted from 0.96 to 1.32,the average length of hospital stay decreased by 1.07 days,the time consumption index and the cost consumption index both fell below 1. The supervision method extended from manual sampling to intelligent quality control,the supervision process extended from a fixed process to a dynamic process and the focus of supervision extends from the review of the settlement list to the supervision of medical behavior. Conclusion:Construct the hospital"three in one"quality control system is a necessary way to promote DRG paying medical institutions to enter the fast lane of standardization,collaboration and refined management,which made a beneficial attempt for the practical application of DRG payment in hospitals.

Objectives:To study the computed tomography features of banded adhesions(BA) and matted adhesions(MA) of adhesive small bowel obstruction(ASBO).Methods:We enrolled 150 patients operated on for ASBO. According to intraoperated findings, ASBO were classified into those caused by BA or MA. A multivariable logistic regression was established to analyze independent risk factors on Computed Tomography features.Results:There were significant differences in closed-loop sign (36.8% vs. 14.3%, P=0.002) mesenteric haziness (43.7% vs. 17.5%, P=0.001), beak sign (48.3% vs. 17.5%, P<0.001), fat notch sign (39.1% vs. 9.5%, P<0.001) and peritoneal fluid (54.0% vs. 34.9%, P=0.015) between the two groups. The presence of beak sign [ OR=6.15, 95% CI (2.55-14.84), P<0.001], fat notch sign [ OR=6.19, 95% CI (2.16-17.82), P=0.001] and mesenteric haziness [ OR=3.34, 95% CI (1.34-8.32), P=0.009] were independent risk factors with BA. Conclusion:Beak sign, fat notch sign and mesenteric haziness were independent risk factors for diagnosing BA.

Objective:To investigate the CT features of lepidic predominant adenocarcinoma (LPA) and other pathological subtypes in early-stage invasive pulmonary adenocarcinoma appearing as ground glass nodule (GGN); and to provide imaging-derived information for the clinical management of GGN.Methods:The clinical and CT data of patients with early-stage invasive pulmonary adenocarcinoma in the First Medical Center of PLA General Hospital from January to December 2019 were retrospectively reviewed. All patients presented with pure GGNs or mixed GGNs with a consolidation-to-tumor ratio (CTR)<0.5, with the pathological results confirmed by surgery. GGNs were divided into LPA and non-LPA (n-LPA) groups according to pathological subtypes. Univariate analysis was used to compare the clinical data and CT characteristics between the two groups. The multivariate analysis was performed for the indicators with statistically significant differences and a multivariate model was generated using the reverse elimination method. The area under the ROC curve (AUC) was used to evaluate the discriminatory power of this model for differentiation of LPA from n-LPA.Results:A total of 630 GGNs from 589 patients were analyzed, with 367 GGNs in LPA group and 263 GGNs in n-LPA group. In univariate analysis, the diameter [(14±5) mm], CT value [(-566±98) HU], and CTR [13.9% (0, 27.3%)] in the LPA group were significantly smaller than those in the n-LPA group [(15±5) mm, (-499±111) HU, 27.8%(7.7%, 40%)], respectively, P<0.05]. The frequency of mGGN, deep lobulation sign, burrs, vascular changes, bronchial changes, and clear tumor-lung interface were significantly higher in the n-LPA group than those in the LPA group ( P<0.05). Multivariate analysis results showed that mean CT values, CTR, deep lobulation sign, burr, vascular changes, and bronchial changes were independent predictors for predicting n-LPA ( P<0.05), which were included in the logistic model. Using the optimal cutoff value of 3.958, the logistic regression model for differentiate LPA from n-LPA had a sensitivity of 76.4%, a specificity of 78.7%, and an area under the curve of 0.840. Conclusion:The CT features are helpful for differentiating lepidic predominant subtype from other subtypes in early-stage invasive pulmonary adenocarcinoma presenting as a GGN.

Objective:To investigate the development status of mental health service of Shanghai mental health agencies,and to provide reference for further strengthening the standardized management of service agencies.Methods:In Shanghai,107 mental health service agencies (including psychiatric institutions,non-specialist medical institutions,non-specialist enterprise and public institutions,social institutions) were selected from Shanghai psychological service industry association.Each person in charge of these agencies was interviewed with an adapted 5 l-item questionnaire.A total of 89 valid questionnaires were collected.In this study,25 items of the questionnaire (belonging to the parts of agency information,mental health service situation and management of mental health service) were selected and analyzed.Results:All the surveyed agencies had been registered.The average age of these agencies for setting up mental health service was 8.9 years,and the average age of psychiatric institutions was the longest (18.6 years).Besides,psychiatric institutions attracted most of the clients (83.9％) in 2015.Among the professionals,only 32.5％ were full time,74.0％ were female,41.5％ were between 31 and 40 years old and 63.8％ were undergraduates.Psychiatrists,psychotherapists,counselors and psychometric person accounted for 78.0％ of the professionals in these agencies.Only 52.3％ of the agencies had full-time management personnel for mental health service.The most used method of assessing the quality of service and staff assessment was to obtain feedback from the client/family members (81.0％) and the assessment of the services (78.8％).Conclusion:The development of mental health service in Shanghai mental health agencies has been more normalized,but there is still a lack of full-time professionals.In addition,there is a lack of unified supervision and management mechanism for professionals.

Objective:To understand the status of supervision of mental health service industry in Shanghai, and to provide reference for further strengthening the construction of mental health service system in Shanghai. Methods: In Shanghai, 107 mental health service agencies (including psychiatric institutions, non-specialist medical institutions, non-specialist enterprise and public institutions, social institutions) were selected from Shanghai psychological service industry association. The survey was conducted with the Questionnaire on Current Situation of Mental Health Professional Service Agencies in Shanghai (agency survey), including the "relevant information of agency" and the "management of the agency in the field of mental health services"(whether the agency had supervision requirements on the mental health service personnel, whether the agency organized supervision, the source of supervisors and payment method), and the Questionnaire on Current Situation of Mental Health Service Professionals in Shanghai (professional survey), including "basic information on demography "and" psychological professional work" (the number of hours of supervision in 2015, the cost of supervision, and the form of supervision and payment method). These two parts of questionnaire were selected and analyzed. Results: Agency survey results showed that 80％ of non-specialist enterprises had no supervision requirements for mental health service personnel, supervisor in non-specialist medical institutions were mainly from psychiatric institution (52.9％). The cost of supervision in most psychiatric institutions was paid by the agency (39.1％) and the cost of supervision in most public institutions was paid by professional (37％). The professional institutions under the jurisdiction of other departments within the unit required less supervision of the professional staff than the independent institutions (P ＜ 0.001). Professional survey results showed that the number of supervision hours of mental health service professional in social institutions was more than that in the other three types of institutions (P ＜0.001), of which 47.9％ chosen to pay the cost of supervision by themselves. The proportion of their own payment in social institutions was higher than that in the other three types of institutions (P ＜0.001). Conclusion:The social institutions in Shanghai have the best supervision of social institutions, followed by the supervision of the medical institutions. The supervision of non-medical enterprises and their personnel needs to be improved.