Objective:To evaluate the levels and source of cadmium exposure by dietary pathway among middle-aged and elderly people ≥40 in cadmium-contaminated areas of China.Methods:A total of 7 193 people aged 40-89 years from four typical cadmium-contaminated areas in China were selected as the study subjects. Food Frequency Questionnaire (FFQ), Total Diet Study (TDS) and a 3-day-24-hour dietary recall survey were conducted. Dietary cadmium intake and food sources through dietary pathways were assessed based on cadmium content in foods, consumption amounts and intake frequencies.Results:The mean age of the participants was 63.39±12.21 years, with 50.05% being males. The average monthly dietary cadmium intake was 7.39 μg/(kg·BW). Staple foods and vegetables were the primary sources of dietary cadmium intake, accounting for 57.51% and 32.48%, respectively. The monthly dietary cadmium intake in all surveyed regions did not exceed the Provisional Tolerable Monthly Intake (PTMI) recommended by the Joint FAO/WHO Expert Committee on Food Additives (JECFA).Conclusion:The monthly dietary cadmium intake among middle-aged and elderly people in cadmium-contaminated areas of China is relatively low, with the risk remaining at an acceptable level. Staple foods and vegetables are the most significant contributors to dietary cadmium intake.

Objective:To develop and evaluate a deep learning-based automatic measurement model for panoramic ultrasound biomicroscopy (UBM) images.Methods:A diagnostic test study was conducted.Preoperative UBM examination results of 372 patients who underwent implantable collamer lens (ICL) implantation were collected at the Eye Center of Renmin Hospital of Wuhan University between February 2021 and March 2023.A total of 1 368 panoramic UBM images were obtained to establish an image database.The dataset was divided into a training set (760 images), a validation set (86 images) and an internal test set (522 images).An expert panel consisting of three ophthalmologists annotated the images.The UNet+ + network was used to automatically segment anterior segment tissues, such as the cornea, lens and iris.In addition, image processing techniques and geometric localization algorithms were developed to automatically identify the anatomical landmarks of pupil diameter (PD), anterior chamber depth (ACD), angle-to-angle distance (ATA) and sulcus-to-sulcus distance (STS) to complete the measurement of these parameters.Additionally, 480 panoramic UBM images of 135 patients (240 eyes) from Aier Eye Hospital of Wuhan University were used as an external test set to further evaluate the performance of the model in different centers.The consistency between the measurements from the model and expert panel, the Pentacam system was assessed.Finally, 150 images were randomly selected from the external test set for a human-machine comparison to further evaluate the model's performance.This study adhered to the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of Renmin Hospital of Wuhan University (No.WDRY-2022-K109) and Aier eye Hospital of Wuhan University (No.2023IRBKY120903).Written informed consent was obtained from each subject.Results:In the internal test dataset and external test dataset, with manual labeling as the reference standard, the model achieved a mean Dice coefficient of not less than 0.882.At least 95.65% of the anatomical landmark localization results had Euclidean distance differences within 250 μm.The intraclass correlation coefficients (ICCs) for the measurements of PD, ACD, angle-to-angle ATA, and STS were at least 0.958, with mean relative errors not exceeding 2.407%.With the Pentacam measurements as the reference standard, the ICCs for PD in the internal and external test sets were 0.540 and 0.466, respectively, while the ICCs for ACD were 0.946 and 0.908, respectively.In the human-machine comparison, the ICCs between the model's measurements and those of senior experts were all not lower than 0.969.Conclusions:The deep learning-based model can automatically measure anterior segment parameters from preoperative panoramic UBM images of patients undergoing ICL surgery.The model demonstrates a consistency comparable to that of senior experts, while providing higher efficiency.In terms of ACD measurement, the model shows good agreement between the measurements obtained from the model and Pentacam system.

Objective:To develop and evaluate a deep learning-based automatic measurement model for panoramic ultrasound biomicroscopy (UBM) images.Methods:A diagnostic test study was conducted.Preoperative UBM examination results of 372 patients who underwent implantable collamer lens (ICL) implantation were collected at the Eye Center of Renmin Hospital of Wuhan University between February 2021 and March 2023.A total of 1 368 panoramic UBM images were obtained to establish an image database.The dataset was divided into a training set (760 images), a validation set (86 images) and an internal test set (522 images).An expert panel consisting of three ophthalmologists annotated the images.The UNet+ + network was used to automatically segment anterior segment tissues, such as the cornea, lens and iris.In addition, image processing techniques and geometric localization algorithms were developed to automatically identify the anatomical landmarks of pupil diameter (PD), anterior chamber depth (ACD), angle-to-angle distance (ATA) and sulcus-to-sulcus distance (STS) to complete the measurement of these parameters.Additionally, 480 panoramic UBM images of 135 patients (240 eyes) from Aier Eye Hospital of Wuhan University were used as an external test set to further evaluate the performance of the model in different centers.The consistency between the measurements from the model and expert panel, the Pentacam system was assessed.Finally, 150 images were randomly selected from the external test set for a human-machine comparison to further evaluate the model's performance.This study adhered to the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of Renmin Hospital of Wuhan University (No.WDRY-2022-K109) and Aier eye Hospital of Wuhan University (No.2023IRBKY120903).Written informed consent was obtained from each subject.Results:In the internal test dataset and external test dataset, with manual labeling as the reference standard, the model achieved a mean Dice coefficient of not less than 0.882.At least 95.65% of the anatomical landmark localization results had Euclidean distance differences within 250 μm.The intraclass correlation coefficients (ICCs) for the measurements of PD, ACD, angle-to-angle ATA, and STS were at least 0.958, with mean relative errors not exceeding 2.407%.With the Pentacam measurements as the reference standard, the ICCs for PD in the internal and external test sets were 0.540 and 0.466, respectively, while the ICCs for ACD were 0.946 and 0.908, respectively.In the human-machine comparison, the ICCs between the model's measurements and those of senior experts were all not lower than 0.969.Conclusions:The deep learning-based model can automatically measure anterior segment parameters from preoperative panoramic UBM images of patients undergoing ICL surgery.The model demonstrates a consistency comparable to that of senior experts, while providing higher efficiency.In terms of ACD measurement, the model shows good agreement between the measurements obtained from the model and Pentacam system.

Objective:To evaluate the levels and source of cadmium exposure by dietary pathway among middle-aged and elderly people ≥40 in cadmium-contaminated areas of China.Methods:A total of 7 193 people aged 40-89 years from four typical cadmium-contaminated areas in China were selected as the study subjects. Food Frequency Questionnaire (FFQ), Total Diet Study (TDS) and a 3-day-24-hour dietary recall survey were conducted. Dietary cadmium intake and food sources through dietary pathways were assessed based on cadmium content in foods, consumption amounts and intake frequencies.Results:The mean age of the participants was 63.39±12.21 years, with 50.05% being males. The average monthly dietary cadmium intake was 7.39 μg/(kg·BW). Staple foods and vegetables were the primary sources of dietary cadmium intake, accounting for 57.51% and 32.48%, respectively. The monthly dietary cadmium intake in all surveyed regions did not exceed the Provisional Tolerable Monthly Intake (PTMI) recommended by the Joint FAO/WHO Expert Committee on Food Additives (JECFA).Conclusion:The monthly dietary cadmium intake among middle-aged and elderly people in cadmium-contaminated areas of China is relatively low, with the risk remaining at an acceptable level. Staple foods and vegetables are the most significant contributors to dietary cadmium intake.

OBJECTIVE To explore the clinical characteristics of Mycoplasma pneumoniae pneumonia(MPP)after COVID-19 epidemic so as to offer help for early clinical diagnosis and treatment.METHODS The clinical data that were collected from the MPP patients who were treated in the fever clinic of the First Medical Center of Chinese PLA General Hospital from Jul.2023 to Aug.2024 were retrospectively analyzed.The results of laboratory tests for the different age groups of patients complicated with other pathogens were statistically analyzed.RESULTS Of totally 161 MPP patients who were enrolled in the study,78(48.85％)were male,and 83(51.55％)were fe-male;the average age was(32.98±14.35)years old,and the patients aged between 20 and 40 years old accoun-ted for 43.48％(70 cases).The enrolled patients were divided into the simple MPP group with 92(57.14％)ca-ses and the MPP+mixed group with 69(42.86％)cases according to the result of etiological test of sputum;the patients of MPP+mixed group were divided into the MPP+bacteria group with 42(60.87％)cases,the MPP+fungi group with 10(14.49％)cases,and the MPP+viruses group with 17(24.64％)cases.There was significant difference in the age among the groups(P＜0.05);there were no significant differences in the sex,white blood cell counts and percentage of mononuclear cells among the groups,the percentage of lymphocytes was highest in the simple MPP group,the levels of C-reactive protein(CRP)and interleukin-6(IL-6)were highest in the MPP+bacteria group,and there were significant differences(P＜0.05).All of the patients were divided into three groups:the ≤20-year-old group the＞20-40-year old group and the＞40-year-old group.There were no sig-nificant differences in the white blood cell counts,percentage of lymphocytes,percentage of mononuclear cells and IL-6 level among the three groups,and the CRP level was highest in the＞20-40-year old group(P=0.025).Ran-dom forest model analysis showed that the weight of CRP was highest(22.65％)among the clinical characteristics of the MPP patients,which played a key role in construction of model.As for other factors,the weight of age was 17.02％,the percentage of lymphocytes 15.34％,the white blood cells counts 14.86％,the percentage of mono-nuclear cells 14.39％,the IL-6 13.61％,the gender 2.13％.CONCLUSION MPP maintains common among the patients aged less than 40 years old after the COVID-19 epidemic,nearly half of the patients are complicated with the infections of other pathogens,and CRP is more helpful for the clinical diagnosis and treatment of the MPP in early stage.

OBJECTIVE To explore the clinical characteristics of Mycoplasma pneumoniae pneumonia(MPP)after COVID-19 epidemic so as to offer help for early clinical diagnosis and treatment.METHODS The clinical data that were collected from the MPP patients who were treated in the fever clinic of the First Medical Center of Chinese PLA General Hospital from Jul.2023 to Aug.2024 were retrospectively analyzed.The results of laboratory tests for the different age groups of patients complicated with other pathogens were statistically analyzed.RESULTS Of totally 161 MPP patients who were enrolled in the study,78(48.85％)were male,and 83(51.55％)were fe-male;the average age was(32.98±14.35)years old,and the patients aged between 20 and 40 years old accoun-ted for 43.48％(70 cases).The enrolled patients were divided into the simple MPP group with 92(57.14％)ca-ses and the MPP+mixed group with 69(42.86％)cases according to the result of etiological test of sputum;the patients of MPP+mixed group were divided into the MPP+bacteria group with 42(60.87％)cases,the MPP+fungi group with 10(14.49％)cases,and the MPP+viruses group with 17(24.64％)cases.There was significant difference in the age among the groups(P＜0.05);there were no significant differences in the sex,white blood cell counts and percentage of mononuclear cells among the groups,the percentage of lymphocytes was highest in the simple MPP group,the levels of C-reactive protein(CRP)and interleukin-6(IL-6)were highest in the MPP+bacteria group,and there were significant differences(P＜0.05).All of the patients were divided into three groups:the ≤20-year-old group the＞20-40-year old group and the＞40-year-old group.There were no sig-nificant differences in the white blood cell counts,percentage of lymphocytes,percentage of mononuclear cells and IL-6 level among the three groups,and the CRP level was highest in the＞20-40-year old group(P=0.025).Ran-dom forest model analysis showed that the weight of CRP was highest(22.65％)among the clinical characteristics of the MPP patients,which played a key role in construction of model.As for other factors,the weight of age was 17.02％,the percentage of lymphocytes 15.34％,the white blood cells counts 14.86％,the percentage of mono-nuclear cells 14.39％,the IL-6 13.61％,the gender 2.13％.CONCLUSION MPP maintains common among the patients aged less than 40 years old after the COVID-19 epidemic,nearly half of the patients are complicated with the infections of other pathogens,and CRP is more helpful for the clinical diagnosis and treatment of the MPP in early stage.

Objective:To explore the clinical application value of a deep learning algorithm-based ultrasound biomicroscopy (UBM) image analysis system for primary angles-closure glaucoma (PACG) anterior located ciliary body.Methods:A diagnostic test study was conducted.A total of 2 132 UBM images from 726 eyes of 378 PACG patients who underwent UBM examination were collected at Renmin Hospital of Wuhan University from August 2022 to December 2023.The dataset was divided into a training set of 1 599 images and a test set of 533 images, and a deep learning algorithm was employed to construct a model.An additional 334 UBM images from 101 eyes of 69 PACG patients treated at Huangshi Aier Eye Hospital were selected to conduct external testing.A separate set of another 110 UBM images were selected for a human-machine competition to compare the accuracy and speed between anterior located ciliary body evaluation system and three senior ophthalmologists.Furthermore, eight junior ophthalmologists assessed the 110 UBM images independently without and with the assistance of the model, and the differences between the two evaluations were analyzed to assess the assisstance effect of the model.This study adhered to the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of Renmin Hospital of Wuhan University (No.WDRY-2022-K109).Results:The model achieved an accuracy of 93.43% for anterior located ciliary body identification in the internal test set, with a sensitivity of 84.30% and a specificity of 97.78%.The model also performed well on the external test set with an accuracy of 92.81%.In the human-machine competition, the model's accuracy was comparable to that of the senior ophthalmologists and outperformed two of the three senior ophthalmologists.The average total time of the three senior ophthalmologists was 726.73 seconds, approximately 12.47 times longer than the model's 58.30 seconds.With model assistance, the diagnostic accuracy of the eight junior ophthalmologists was 86.71%, which was significantly higher than 76.25% without model assistance ( χ2=-7.550, P<0.001).And the image evaluation time was (714.91±213.82)seconds, which was significantly lower than (987.90±238.56)seconds without model assistance ( t=2.774, P<0.05). Conclusions:The UBM image analysis system based on a deep learning algorithm demonstrates high accuracy in diagnosing anterior located ciliary body in PACG and provides a strong support for the UBM image recognition training of junior ophthalmologists.

Objective:To investigate the effects of self-made Hezhong-Jianpi Decoction on gastrointestinal motility and level of inflammatory cell factors in patients with reflux esophagitis. Methods:A total of 102 patients with reflux esophagitis who met the inclusion criteria in our hospital from May 2016 to September 2018 were divided into two group according to the random number table method, 51 cases in each group. The control group was treated with conventional western medicine. The intervention group was treated with self-made Hezhong-Jianpi Decoction based on the control group. Both groups were treated for 8 weeks. The levels of serum gastrin (GAS) and motilin (MTL) were detected by radioimmunoassay, the levels of TNF-α, IL-6 and IL-17 were detected by ELISA, the adverse reactions during the treatment were recorded, and the clinical efficacy was evaluated. Results:The total effective rate of the experimental group was 92.1% (47/51) and that of the control group was 72.5% (37/51). The difference between the two groups was statistically significant ( χ2=6.746, P=0.009). After the treatment, the levels of serum GAS (152.93 ± 26.85 ng/L vs. 134.30 ± 29.88 ng/L, t=3.312), MTL (291.58 ± 29.75 ng/L vs. 262.40 ± 38.71 ng/L, t=4.268) in the intervention group were significantly higher than those in the control group ( P<0.05), and serum TNF-α, IL-6, IL-17 levels were significantly lower than those in the control group ( t value were 4.653, 5.362, 4.759, respectively, all Ps<0.01). During the treatment, the incidence of adverse reactions was 9.8% (5/51) in the control group and 12.0% (6/51) in the intervention group, and there was no significant difference between the two groups ( χ2=0.102, P=0.750). Conclusions:The self-made Hezhong-Jianpi Decoction combined with the conventional western medicine can promote the gastrointestinal motility of patients with reflux esophagitis, reduce the inflammatory reaction and improve the clinical efficacy.

Objective Aiming at detecting Staphylococcus aureus、Pseudomonas aeruginosa and Klebsiella pneumoniae in laboratory animals,the paper provides a rapid,sensitive and simple test method.Methods According to Staphylococcus aureus nuc gene,Pseudomonas aeruginosa LasI gene,Klebsiella pneumonia PhoE gene and general 16S rRNA gene, designed specific primers;Through the optimization of multiplex PCR primer concentrations and annealing temperature, the specificity and sensitivity of detection, establishing multiplex PCR system.Application of the PCR system test specimens of artificial infections and experiment animal feces is compared with traditional test method.Results Multiplex PCR amplification of Staphylococcus aureus (153 bp), Pseudomonas aeruginosa (600 bp) with Klebsiella pneumoniae (368 bp) and general (520 bp).The multiplex sensitivity for the purpose of 10pg, specificity of detection was not detected from other pathogens.Application of establishing multiplex PCR system to detect the artificial positive samples, and detect 1 Pseudomonas aeruginosa positive case in 76 fecals.Conclusions This paper established the multiplex PCR method which has the advantages of specific,sensitive,simple and rapid, and provides a reliable way for rapid test in laboratory animals microbiology.

Objective: To establish a screening system for anti-metastatic small-molecule compounds based on perinucleolar compartment (PNC) prevalence in liver cancer cells and to investigate its validity. Methods: Polypyrimidine tract-binding protein (PTB) monoclonal antibody was used to measure the PNC prevalence in HepG2, HepG2M, and Huh7 cells, and wound healing assay and transwell assay were used to analyze the migration and invasion abilities of hepatoma cells. HepG2M cells were used as the model for the screening of anti-metastatic small-molecule compounds, and after the treatment with the compounds A1, A4, and E696, qPCR was used to measure the expression of metastasis-related miRNAs (miR-141 and miR-200c). A one-way analysis of variance was used for comparison of data between multiple groups. Results: PTB immunofluorescence assay showed that HepG2M cells had the highest PNC prevalence, followed by Huh7 and HepG2 cells, and PNC prevalence was positively correlated with the metastasis and invasion abilities of hepatoma cells. The PNC prevalence of HepG2M cells was reduced to 22.88% ±4.61% by A1, 14.22% ± 3.05% by A4, and 26.12% ± 4.94% by E696. Wound healing assay showed that the 48-hour scratch ratio increased from 17.70% ± 3.34% to 64.50% ± 2.65%, 83.40% ± 5.10%, and 57.20% ± 3.06% (F = 171.1, P < 0.01), respectively. Transwell assay showed that the number of invasive cells was reduced from 264.33 ± 30.50 to 104.33 ± 13.50, 58.00 ± 11.00, and 111.33 ± 19.50 (F = 59.87, P < 0.01), respectively. The anti-metastatic effect of these three compounds was positively correlated with their ability to destroy PNC. A4 upregulated the expression of miR-141 and miR-200c in a dose-dependent manner, and after HepG2M cells were treated with A4 at a concentration of 5 μM, 10 μM, or 20 μM, the level of miR-141 was increased to 3.61 ± 0.78, 8.12 ± 1.15, and 18.24 ± 2.44 folds (F = 88.01, P < 0.01), respectively, and that of miR-200c was increased to 2.82 ± 0.43, 4.82 ± 0.89, and 10.74 ± 1.22 folds (F = 87.94, P < 0.01), respectively. Conclusion The screening system for anti-metastatic small-molecule compounds based on PNC prevalence can provide an effective technical platform for research and development of anti-metastatic drugs for liver cancer.