AIM:To analyze the characteristics and correlation of phacoemulsification parameters and anterior segment parameters in cataract patients with different blood glucose levels.METHODS:A total of 45 type 2 diabetic cataract patients(45 eyes)treated in our hospital from March 2023 to April 2024 were stratified into two groups based on glycosylated hemoglobin(HbA1c)levels: group A: HbA1c <7%(n=18)and group B: 7%≤HbA1c<8.5%(n=27); a total of 94 age-matched age-related cataract patients(94 eyes)were enrolled as the control group(group C). All underwent phacoemulsification with intraocular lens implantation. Anterior segment parameters, including corneal, lens and anterior chamber measurements, were recorded. Correlations between phacoemulsification parameters and anterior segment parameters were analyzed, and differences among groups were compared.RESULTS: In groups A and B, effective phacoemulsification time(EPT)negatively correlated with corneal endothelial cell density(CECD)(r=-0.315, P=0.035). Average phacoemulsification time(APT)positively correlated with the anterior corneal surface radius of curvature(Rm; r=0.402, P=0.006)and negatively correlated with the flat axis meridian curvature(K1), steep axis meridian curvature(K2), mean curvature(Km)of the anterior corneal surface, and lens density at 6 mm zones(PDZ3; all P<0.05). Average phacoemulsification energy(AVE)positively correlated with mean lens density(LD-mean), lens density at 2 mm zones(PDZ1), lens density at 4 mm zones(PDZ2), and PDZ3(all P<0.05), and negatively with pupil diameter(r=-0.385, P=0.009). In the group C, EPT showed a positive correlation with Pentacam nucleus staging(PNS)density grade, PDZ1, PDZ2, and PDZ3(all P<0.05). A positive correlation was observed between AVE and PNS classification(r=0.246, P=0.018). Conversely, AVE exhibited a negative correlation with CECD(r=-0.245, P=0.018). EPT in groups A and B was higher than that in the group C(P<0.05). Both EPT and APT in the group B were higher than those in the group A(P<0.05). In diabetic cataract patients, CECD, corneal density(CD), and posterior corneal surface height positively correlated with diabetes duration(P<0.05). Posterior corneal surface K1 and Rm positively correlated with 7%≤HbA1c<8.5%(P<0.05). Total corneal astigmatism negatively correlated with HbA1c, 2-hour post-breakfast blood glucose(2hPBG), and fasting insulin(FINS; P<0.05). CD and lens thickness(LT)positively correlated with FINS(P<0.05).CONCLUSION: Phacoemulsification parameters and blood glucose-related indices exhibited varying degrees of correlation with anterior segment parameters in cataract patients with different blood glucose levels. EPT in diabetic cataract patients was higher than that in age-related cataract patients, while EPT and APT in diabetic cataract patients with poor glycemic control were higher than those with good glycemic control.

Objective To investigate the mechanism of astragaloside Ⅰ,the active constituent of milkvetch root,in inhibiting podocyte injury and improving diabetic kidney disease.Methods According to the body weight,60 male db/db mice were randomly divided into the model group,astragaloside Ⅰ low-dose group(10 mg/kg),astragaloside Ⅰ medium-dose group(20 mg/kg),astragaloside Ⅰ high-dose group(40 mg/kg),and valsartan group(10mg/kg),with 12 mice per group.Twelve db/db littermate control db/m mice were used as the control group.The drug was administered by gavage for 8 weeks.Transmission electron microscope was used to observe the ultrastructure of the kidney;immunohistochemistry and Western blotting were used to detect the expression of nephrotic protein(nephrin),a marker of renal podocytes;enzyme-linked immunosorbent assay was used to detect the contents of interleukin-1β(IL-1β)and interleukin-18(IL-18)in the serum of mice;Western blotting was used to detect the protein expressions of NOD-like receptor thermoprotein domain-related protein 3(NLRP3),cysteinyl aspartate specific proteinase 1(Caspase-1),and Gasdermin D(GSDMD)in kidney tissue.Results Compared with the control group,the glomeruli of the model group showed obvious podocyte loss and foot process fusion;the protein expression of nephrin was decreased(P＜0.05);the contents of IL-1 β and IL-18 in serum were increased(P＜0.05);the protein expressions of NLRP3,Cleaved-Caspase-1,and GSDMD-N were increased(P＜0.05).Compared with the model group,the renal pathological damage in the astragaloside Ⅰ administration groups were alleviated;the protein expression of nephrin was increased(P＜0.05);the contents of IL-1β and IL-18 in serum were decreased(P＜0.05);the protein expressions of NLRP3,Cleaved-Caspase-1,and GSDMD-N were decreased(P＜0.05).Conclusion Astragaloside Ⅰ may play a role in intervening diabetic kidney disease by inhibiting pyroptosis and improving podocyte injury.

Objective:To assess the diagnostic efficacy of upper gastrointestinal endoscopic image assisted diagnosis system (ENDOANGEL-LD) based on artificial intelligence (AI) for detecting gastric lesions and neoplastic lesions under white light endoscopy.Methods:The diagnostic efficacy of ENDOANGEL-LD was tested using image testing dataset and video testing dataset, respectively. The image testing dataset included 300 images of gastric neoplastic lesions, 505 images of non-neoplastic lesions and 990 images of normal stomach of 191 patients in Renmin Hospital of Wuhan University from June 2019 to September 2019. Video testing dataset was from 83 videos (38 gastric neoplastic lesions and 45 non-neoplastic lesions) of 78 patients in Renmin Hospital of Wuhan University from November 2020 to April 2021. The accuracy, the sensitivity and the specificity of ENDOANGEL-LD for image testing dataset were calculated. The accuracy, the sensitivity and the specificity of ENDOANGEL-LD in video testing dataset for gastric neoplastic lesions were compared with those of four senior endoscopists.Results:In the image testing dataset, the accuracy, the sensitivity, the specificity of ENDOANGEL-LD for gastric lesions were 93.9% (1 685/1 795), 98.0% (789/805) and 90.5% (896/990) respectively; while the accuracy, the sensitivity and the specificity of ENDOANGEL-LD for gastric neoplastic lesions were 88.7% (714/805), 91.0% (273/300) and 87.3% (441/505) respectively. In the video testing dataset, the sensitivity [100.0% (38/38) VS 85.5% (130/152), χ2=6.220, P=0.013] of ENDOANGEL-LD was higher than that of four senior endoscopists. The accuracy [81.9% (68/83) VS 72.0% (239/332), χ2=3.408, P=0.065] and the specificity [ 66.7% (30/45) VS 60.6% (109/180), χ2=0.569, P=0.451] of ENDOANGEL-LD were comparable with those of four senior endoscopists. Conclusion:The ENDOANGEL-LD can accurately detect gastric lesions and further diagnose neoplastic lesions to help endoscopists in clinical work.

Objective:To construct a real-time artificial intelligence (AI)-assisted endoscepic diagnosis system based on YOLO v3 algorithm, and to evaluate its ability of detecting focal gastric lesions in gastroscopy.Methods:A total of 5 488 white light gastroscopic images (2 733 images with gastric focal lesions and 2 755 images without gastric focal lesions) from June to November 2019 and videos of 92 cases (288 168 clear stomach frames) from May to June 2020 at the Digestive Endoscopy Center of Renmin Hospital of Wuhan University were retrospectively collected for AI System test. A total of 3 997 prospective consecutive patients undergoing gastroscopy at the Digestive Endoscopy Center of Renmin Hospital of Wuhan University from July 6, 2020 to November 27, 2020 and May 6, 2021 to August 2, 2021 were enrolled to assess the clinical applicability of AI System. When AI System recognized an abnormal lesion, it marked the lesion with a blue box as a warning. The ability to identify focal gastric lesions and the frequency and causes of false positives and false negatives of AI System were statistically analyzed.Results:In the image test set, the accuracy, the sensitivity, the specificity, the positive predictive value and the negative predictive value of AI System were 92.3% (5 064/5 488), 95.0% (2 597/2 733), 89.5% (2 467/ 2 755), 90.0% (2 597/2 885) and 94.8% (2 467/2 603), respectively. In the video test set, the accuracy, the sensitivity, the specificity, the positive predictive value and the negative predictive value of AI System were 95.4% (274 792/288 168), 95.2% (109 727/115 287), 95.5% (165 065/172 881), 93.4% (109 727/117 543) and 96.7% (165 065/170 625), respectively. In clinical application, the detection rate of local gastric lesions by AI System was 93.0% (6 830/7 344). A total of 514 focal gastric lesions were missed by AI System. The main reasons were punctate erosions (48.8%, 251/514), diminutive xanthomas (22.8%, 117/514) and diminutive polyps (21.4%, 110/514). The mean number of false positives per gastroscopy was 2 (1, 4), most of which were due to normal mucosa folds (50.2%, 5 635/11 225), bubbles and mucus (35.0%, 3 928/11 225), and liquid deposited in the fundus (9.1%, 1 021/11 225).Conclusion:The application of AI System can increase the detection rate of focal gastric lesions.

Background The converter stations of high-voltage direct current (HVDC) transmission lines generate special total electric fields. At present, few investigations have been conducted on total electric fields in the workplace of converter stations from an perspective of occupational health. Objective To understand the current situation of total electric field strength in the workplace of converter stations. Methods Using purposive sampling, a calibrated HDEM-1 direct current (DC) total electric field strength measurement system was used to measure the total electric fields of 12 converter stations serving 6 DC lines in Southeast and Southwest China according to the Measurement method for total electric field strength and ion current density of the converter stations and DC transmission lines (DL/T 1089—2008). The results were evaluated according to occupational exposure limits recommended by The limits of electromagnetic environment at ±800 kV UHV DC converter station (DL/T 275—2012), the American Conference of Governmental Industrial Hygienists (ACGIH), and the International Commission on Non-Ionizing Radiation Protection (ICNIRP). Results A total of 615 check points were planned, the total electric field strength was 0.05-37.05 kV·m⁻¹, and the median was 10.45 kV·m⁻¹. The total electric field strength of 39 check points (6.3%) exceeded 25 kV·m⁻¹ (the limits of ACGIH and ICNIRP), and the total electric field strength of 12 check points (2.0%) exceeded 30 kV·m⁻¹ (the limit of DL/T 275—2012). There were statistically significant differences in the total electric field strength values and the proportions of exceeding 25 kV·m⁻¹ between the neutral regions and the positive regions and between the neutral regions and the negative regions (P < 0.01). The proportion of total electric field strength exceeding 30 kV·m⁻¹ in the negative regions was higher than that in the positive regions (P < 0.01). There were no significant differences in the total electric field strength of converter stations at different voltage levels and different altitudes (P > 0.05). There were no significant differences in the proportions of total electric field exceeding 25 kV·m⁻¹ and exceeding 30 kV·m⁻¹ in converter stations at different voltage levels and different altitudes (P > 0.05). Conclusion The total electric field in some workplace of converter stations exceeds selected limits. Converter station operators may be exposed to high-strength total electric field for a short time.

Establish a production line with controllable process and high intelligence, contribute to improve the quality and production efficiency of aconite processed by microwave, and promote the transformation and application of aconite processed by microwave. According to the principle of aconite detoxification and the characteristics of industrial microwave equipment, an industrial production line of aconite processed by microwave was established with diester alkaloids and monoester alkaloids as indicators, and pilot production was carried out. At the same time, the content of active constituents and efficacy were compared with that of the main processed products, such as Shengfupian, Baifupian and Heishunpian. The results showed that the industrial production of aconite processed by microwave can be divided into two stages: "Liquid seal to detoxification - drying and puffing". The content of monoester alkaloids in 10 batches of aconite processed by microwave was 0.071%-0.166% and the content of diester alkaloids was 0.004%-0.016%, which met the relevant requirements of the Chinese Pharmacopoeia in 2020. Compared with Heishunpian and Baifupian, the retention rate of the effective components of aconite processed by microwave was higher. Pharmacological experiments showed that aconite processed by microwave not only retained the anti-inflammatory and analgesic activities of Heishunpian and Baifupian, but also significantly increased the levels of leukocytes and lymphocytes in mice with liver cancer chemotherapy, enhanced the CD4/CD8 ratio in spleen cells of mice (P < 0.05), thus regulating the body's immunity. However, this effect of Baifupian was weak, while Heishunpian and Shengfupian had no such effect. Through the above research, this study established microwave processing line with controllable process and high intelligence, as well produced the aconite processed by microwave with low toxicity and stable quality. It laid a foundation for the industrialized continuous production and clinical positioning of aconite by microwave processed, and provided scientific support for the development and application of microwave technology in the field of traditional Chinese medicine. All animal experiments in this study were reviewed and approved by the Experimental Animal Ethics Committee of Chengdu University of Traditional Chinese Medicine before being carried out (Approval No. 2020-28).

Objective:To construct a risk prediction model for ICU delirium in patients with brain tumor surgery, and to verify the application value of the model in predicting the risk of ICU delirium in patients with brain tumor.Methods:Using the convenient sampling method, a total of 336 postoperative patients with brain tumors who were admitted to Neurosurgery ICU of East Hospital Affiliated to Tongji University from December 2020 to July 2021 were selected as the modeling group. Patients were divided into the delirium group ( n=101) and the non-delirium group ( n=235) according to the occurrence of ICU delirium. The patients were evaluated using Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) and Richmond Agitation Sedation Score (RASS) . Univariate analysis and binomial logistic regression analysis were used to explore the influencing factors of ICU delirium in patients after brain tumor surgery and to construct a predictive model. The area under receiver operating characteristic curve ( AUC) and Calibration curve were used to evaluate the discrimination and calibration of the model. The model was validated by 1 000 Bootstrap self-sampling methods. According to the same criteria, a total of 144 patients with brain tumors from August to November 2021 were selected as the validation group to verify the model. Results:The predictors that finally entered the model were age ( OR=1.033) , length of stay in neurosurgical ICU ( OR=1.298) , length of operation ( OR=1.006) , use of benzodiazepines ( OR=5.850) , physical restraint ( OR=2.820) , tumor diameter ( OR=1.385) and bilateral brain tumor mass ( OR=3.604) . The prediction model of AUC was 0.935 (95% CI: 0.911-0.960, P<0.01) , the Youden index was 0.747, the sensitivity was 92.1% and the specificity was 82.6%. The internal validation consistency index of the Bootstrap method was 0.916, and the calibration curve fit the ideal curve well. The model validation results showed that the sensitivity was 86.4%, the specificity was 85.0%. Conclusions:The prediction model of delirium risk in ICU patients after brain tumor surgery has good predictive performance, which can provide reference for medical staff to take preventive management measures in the early stage.

Background: Thyroid diseases are highly prevalent worldwide, but their diagnosis remains a challenge. We established reference intervals (RIs) for thyroid-associated hormones and evaluated the prevalence of thyroid diseases in China. Methods: After excluding outliers based on the results of ultrasound screening, thyroid antibody tests, and the Tukey method, the medical records of 20,303 euthyroid adults, who visited the Department of Health Care at Peking Union Medical College Hospital from January 2014 to December 2018, were analyzed. Thyroid-associated hormones were measured by the Siemens Advia Centaur XP analyzer. The RIs for thyroid-associated hormones were calculated according to the CLSI C28-A3 guidelines, and were compared with the RIs provided by Siemens. The prevalence of thyroid diseases over the five years was evaluated and compared using the chi-square test. Results: The RIs for thyroid stimulating hormone (TSH), free thyroxine (FT4), free triiodothyronine (FT3), total thyroxine (TT4), and total triiodothyronine (TT3) were 0.71–4.92 mIU/L, 12.2–20.1 pmol/L, 3.9–6.0 pmol/L, 65.6–135.1 nmol/L, and 1.2–2.2 nmol/L, respectively. The RIs of all hormones except TT4 differed significantly between males and females. The RIs of TSH increased with increasing age. The prevalence of overt hypothyroidism, overt hyperthyroidism, subclinical hypothyroidism, and subclinical hyperthyroidism was 0.5% and 0.8%, 0.2% and 0.6%, 3.8% and 6.1%, and 3.3% and 4.7% in males and females, respectively, which differed from those provided by Siemens. Conclusions Sex-specific RIs were established for thyroid-associated hormones, and the prevalence of thyroid diseases was determined in the Chinese population.

Objective:To assess the influence of an artificial intelligence (AI) -assisted diagnosis system on the performance of endoscopists in diagnosing gastric cancer by magnifying narrow banding imaging (M-NBI).Methods:M-NBI images of early gastric cancer (EGC) and non-gastric cancer from Renmin Hospital of Wuhan University from March 2017 to January 2020 and public datasets were collected, among which 4 667 images (1 950 images of EGC and 2 717 of non-gastric cancer)were included in the training set and 1 539 images (483 images of EGC and 1 056 of non-gastric cancer) composed a test set. The model was trained using deep learning technique. One hundred M-NBI videos from Beijing Cancer Hospital and Renmin Hospital of Wuhan University between 9 June 2020 and 17 November 2020 were prospectively collected as a video test set, 38 of gastric cancer and 62 of non-gastric cancer. Four endoscopists from four other hospitals participated in the study, diagnosing the video test twice, with and without AI. The influence of the system on endoscopists′ performance was assessed.Results:Without AI assistance, accuracy, sensitivity, and specificity of endoscopists′ diagnosis of gastric cancer were 81.00%±4.30%, 71.05%±9.67%, and 87.10%±10.88%, respectively. With AI assistance, accuracy, sensitivity and specificity of diagnosis were 86.50%±2.06%, 84.87%±11.07%, and 87.50%±4.47%, respectively. Diagnostic accuracy ( P=0.302) and sensitivity ( P=0.180) of endoscopists with AI assistance were improved compared with those without. Accuracy, sensitivity and specificity of AI in identifying gastric cancer in the video test set were 88.00% (88/100), 97.37% (37/38), and 82.26% (51/62), respectively. Sensitivity of AI was higher than that of the average of endoscopists ( P=0.002). Conclusion:AI-assisted diagnosis system is an effective tool to assist diagnosis of gastric cancer in M-NBI, which can improve the diagnostic ability of endoscopists. It can also remind endoscopists of high-risk areas in real time to reduce the probability of missed diagnosis.

OBJECTIVE: To analyze the characteristics of noise hazard in a nuclear power station. METHODS: The workplaces and working posts which exposed to occupational noise from two 1 000 MW power units in one nuclear power station in Guangdong Province was selected as study subjects using the convenience sampling method. Occupational health survey, noise measurement in the workplace and personal noise dosage measurement were used to monitor noise exposure, and to analyze the characteristics of occupational noise in the nuclear power station. RESULTS: The noise sources of the nuclear power plant were mainly distributed in the nuclear island, conventional island, and peripheral workshops. A total of 237 points of noise intensity were measured in the workplace. The intensity of noise ranged from 66.0 to 99.6 dB(A). The noise intensity in 62.4%(148/237) of points was equal or greater than 80.0 dB(A) and 34.2%(81/237) equal or greater than 85.0 dB(A). The percentage of detection points with noise intensity was equal or greater than 85.0 dB(A) from low to high were nuclear island, conventional island, and peripheral workshops with 22.0%, 37.5% and 53.8% respectively(P<0.01). The personal noise intensity of three positions including inspectors of operation department, preparation and main engine positions of mechanical department exceeded the occupational exposure limit(OEL), and the percentage of positions whose noise intensity exceeded the OEL was 9.7%(3/31). CONCLUSION: High-intensity noise sources of the nuclear power plant are widely distributed in the workshop areas of nuclear island, conventional island, and peripheral workshops. The noise level of some positions exceeded the standards of noise intensity. The prevention and control measures of noise hazards in posts with excessive noise should be strengthened.