Objective: To investigate the impact of milk and egg supplementation on body composition and bone mineral density of rural primary school students in Yunnan Province, so as to provide a reference for developing targeted nutritional intervention strategies. Methods: In December 2023, a cluster sampling method was adopted to select students from grades one to three in four primary schools each from Jinggu and Shidian countys of Yunnan Province, as the intervention group (662 students). Additionally, two boarding primary schools were selected from each county based on the principle of matching scale and student numbers as the control group (455 students). Starting from April 2023, the intervention group received 200 mL milk and 50 g eggs during the break on school days for 8 months, while the control group maintained their usual diet behavior. Body composition was measured by using bioelectrical impedance analysis, and distal radial bone mineral density was assessed via dual energy X-ray absorptiometry in April and December 2023. The intervention effects were analyzed by using a difference in-differences approach. Results: The final measurements of body fat percentage, skeletal muscle mass and fat free mass of the intervention group and the control group of primary school students were significantly higher than the baseline values, and the net effect of milk and egg intervention on these body composition indicators was not statistically significant ( P >0.05, both before and after adjustment). In contrast, bone mineral density increased significantly by 0.02 g/cm 2 in the intervention group. The net intervention effect on bone mineral density was statistically significant ( β=0.02, 95%CI =0.00-0.04), and remained significant after model adjustment ( β=0.02, 95%CI =0.00-0.04) (both P < 0.05). Subgroup analysis showed statistically significant effects of the intervention among girls ( β=0.02, 95%CI =0.00-0.04), day students ( β=0.04, 95%CI =0.01-0.07), and students with normal nutritional status ( β=0.02, 95%CI =0.00-0.04) (all P <0.05). No significant effect of milk and egg supplementation was observed on body composition indicators (all P <0.05). Conclusions Milk and egg supplementation can improve bone mineral density among rural primary school students in Yunnan Province. It is recommended that rural school aged children should increase intake of milk and eggs to support growth and development.

Objective:To investigate whether biochanin A(BCA)has a protective effect against dextran sodium sulfate(DSS)-in-duced ulcerative colitis(UC)in mice.Methods:Thirty C57BL/6N mice were randomly divided into normal control group,DSS model group,sulfasalazine(SASP)-positive drug control group,and low/medium/high-dose(5 mg/kg,10 mg/kg,and 20 mg/kg)BCA groups.The mouse model of UC was induced by administering 2.5%DSS aqueous solution for 7 days.During the experimental period,both the normal control and model groups were given 0.5%carboxymethyl cellulose sodium solution daily by gavage.The positive control group was given 100 mg/kg SASP,while the BCA groups were given BCA suspensions at doses of 5 mg/kg,10 mg/kg,and 20 mg/kg.The ad-ministration lasted for 10 days.Body weight changes and fecal status of the mice were recorded every day;the colon was dissected,col-lected,and measured for its length.The colon was stained with Hematoxylin-Eosin for pathomorphological study.Quantitative poly-merase chain reaction was used to determine the levels of tumor necrosis factor-α(TNF-α),interleukin-6(IL-6),and interleukin-10(IL-10)in the colon.Immunofluorescence was used to determine the expression of tight junction proteins,zonula occluden-1(ZO-1)and occludin,in the colon.Results:It showed that 5 mg/kg and 10 mg/kg BCA significantly alleviated weight loss in mice with UC,while 5 mg/kg,10 mg/kg,and 20 mg/kg BCA reduced the disease activity index scores.Additionally,BCA showed similar effects to SASP in improving the structure and reducing the shortening of the colon in mice with UC.Compared with the model group,all BCA groups had significantly decreased TNF-α(P=0.024、P=0.060、P=0.003)and IL-6(P=0.002、P<0.001、P<0.001)and significantly increased IL-10(P=0.006、P=0.003、P<0.001),with varying degrees of up-regulated expression of tight junction proteins.Conclusion:BCA can effectively alleviate DSS-induced symptoms,reduce intes-tinal damage,and protect the intestinal barrier in mice with UC.

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 preliminary investigate the impact of the diagnosis-related groups (DRG) payment method reform on the diagnosis and treatment of inpatient medical insurance patients with neuromyelitis optica spectrum disorders (NMOSD), and to propose potential improvement strategies.Methods:A single-center, retrospective study. From October 1, 2020, to September 30, 2022, 44 hospitalized medical insurance patients with acute-phase NMOSD diagnosed and treated at the First Affiliated Hospital of Northwest University (Xi'an First Hospital) were included in the study. Among them, there were 11 males and 33 females, with an average age of (40.8±20.2) years. According to the implementation time of DRG payment, patients were divided into two groups: group A, which consists of cases one year before the implementation of DRG payment from October 1, 2020 to September 30, 2021, and group B, which consists of cases one year after the implementation of DRG payment from October 1, 2021 to September 30, 2022, with 20 and 24 cases, respectively. Detailed information such as hospitalization duration, treatment methods, and hospitalization costs of the two groups of patients was collected. Comparative analysis was conducted on hospitalization costs and treatment methods between the two groups. For intergroup comparison, t-test was used for normally distributed data, and Mann-Whitney U test was used for skewed distributed data. Results:Among the 44 patients, 5 cases (5/24, 20.8%) received plasma exchange (PE) treatment, all of whom were in group B. The numbers of patients who received and did not receive intravenous immunoglobulin (IVIG) treatment were 9 and 11 in group A, respectively, and 7 and 12 in group B (except for 5 cases who received PE treatment), respectively. Compared with group A, there was no significant decrease in hospitalization duration ( t=0.004) and total hospitalization costs ( Z=0.036), as well as costs for western medicine ( Z=0.036), examinations ( Z=0.011), laboratory tests ( Z=0.040), treatments ( Z=0.017), and nursing ( Z=3.131) in group B, and the differences were not statistically significant ( P>0.05). For patients receiving PE treatment, except for the cost of western medicine ( Z=0.062, P=0.804), the other costs ( Z=8.288, 5.013, 11.400, 10.925, 9.126) were significantly higher than those of patients not receiving PE treatment, and the hospitalization duration ( t=20.474) was significantly prolonged, with statistically significant differences ( P<0.05). The total hospitalization costs of patients receiving IVIG treatment were significantly higher than those not receiving IVIG treatment in both group A and group B, with statistically significant differences ( Z=7.690, 10.314; P<0.05). There was no statistically significant difference in the comparison of total hospitalization costs between patients receiving IVIG treatment in group A and group B ( Z=0.137, P>0.05). Conclusions:There is no significant decrease in various hospitalization costs of NMOSD medical insurance patients in Xi'an after the implementation of DRG payment, especially for patients receiving PE treatment. It is suggested to optimize the rate stratification of NMOSD patients when implementing DRG payment methods.

Traditional Chinese medicine （TCM） has a long history of application in China and has consistently played a vital role in treating diseases and saving lives. TCM prescriptions （compounds） constitute the primary form of clinical TCM treatment and significantly differ from western medicine （chemicals） due to the diverse composition and chemical constituents of TCM （compounds）. Nevertheless， the potential multi-component， multi-target， and multi-pathway action characteristics of TCM prescriptions also demonstrate their possible （complementary） therapeutic advantages when compared with single-component chemical drugs. Therefore， driven by the development of modern science and technology and the demands of the modernization and internationalization of TCM， modern theories regarding the complexity of TCM prescription effects have been continuously proposed： Different from the abstract language of traditional prescription theory， the modern TCM prescription theory is more inclined to illustrate the connotation of prescription compatibility concretely and vividly from an experimental and scientific perspective. In this paper， new theories on the complexity of TCM prescriptions proposed in recent years are summarized to provide research references and ideas for the greater role of TCM prescriptions and a better scientific understanding.

Objective:To construct an artificial intelligence (AI)-assisted system based on deep learning for corneal in vivo confocal microscopy (IVCM) image recognition and to evaluate its value in clinical applications. Methods:A diagnostic study was conducted.A total of 18 860 corneal images were collected from 331 subjects who underwent IVCM examination at Renmin Hospital of Wuhan University and Zhongnan Hospital of Wuhan University from May 2021 to September 2022.The collected images were used for model training and testing after being reviewed and classified by corneal experts.The model design included a low-quality image filtering model, a corneal image diagnosis model, and a 4-layer identification model for corneal epithelium, Bowman membrane, stroma, and endothelium, to initially determine normal and abnormal corneal images and corresponding corneal layers.A human-machine competition was conducted with another 360 database-independent IVCM images to compare the accuracy and time spent on image recognition by three senior ophthalmologists and the AI system.In addition, 8 trainees without IVCM training and with less than three years of clinical experience were selected to recognize the same 360 images without and with model assistance to analyze the effectiveness of model assistance.This study adhered to the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of Renmin Hospital of Wuhan University (No.WDRY2021-K148).Results:The accuracy of this diagnostic model in screening high-quality images was 0.954.Its overall accuracy in identifying normal/abnormal corneal images was 0.916 and 0.896 in the internal and external test sets, respectively.Its accuracy reached 0.983, 0.925 in the internal test sets and 0.988, 0.929 in the external test sets in identifying corneal layers of normal and abnormal images, respectively.In the human-machine competition, the overall recognition accuracy of the model was 0.878, which was similar to the average accuracy of the three senior physicians and was approximately 300 times faster than the experts in recognition speed.Trainees assisted by the system achieved an accuracy of 0.816±0.043 in identifying corneal layers of normal and abnormal images, which was significantly higher than 0.669±0.061 without model assistance ( t=6.304, P<0.001). Conclusions:A deep learning-based assistant system for corneal IVCM image recognition is successfully constructed.This system can discriminate normal/abnormal corneal images and diagnose the corresponding corneal layer of the images, which can improve the efficiency of clinical diagnosis and assist doctors in training and learning.

Fentanyl is a fully synthetic opioid with analgesic and anesthetic properties. It has become a primary driver of the deadliest opioid crisis in the United States and elsewhere, consequently imposing devastating social, economic, and health burdens worldwide. However, the neural mechanisms that underlie the behavioral effects of fentanyl and its analogs are largely unknown, and approaches to prevent fentanyl abuse and fentanyl-related overdose deaths are scarce. This review presents the abuse potential and unique pharmacology of fentanyl and elucidates its potential mechanisms of action, including neural circuit dysfunction and neuroinflammation. We discuss recent progress in the development of pharmacological interventions, anti-fentanyl vaccines, anti-fentanyl/heroin conjugate vaccines, and monoclonal antibodies to attenuate fentanyl-seeking and prevent fentanyl-induced respiratory depression. However, translational studies and clinical trials are still lacking. Considering the present opioid crisis, the development of effective pharmacological and immunological strategies to prevent fentanyl abuse and overdose are urgently needed.
Humans ; Fentanyl/therapeutic use* ; Opioid-Related Disorders/drug therapy* ; Drug Overdose/prevention & control* ; Analgesics, Opioid/adverse effects* ; Vaccines/therapeutic use* ; Brain

Accurate determination of drug concentration in blood samples is a necessary prerequisite for therapeutic drug monitoring (TDM) and the implementation of precise drug treatment, and it is also one of the important tasks of clinical laboratories.TDM plays an important role in clinical treatment in immunosuppressants (cyclosporine A, tacrolimus), psychotropic drugs (valproic acid, carbamazepine) and other drugs that require monitoring of drug concentration. There are many types of methods used for TDM for the detection of drug concentration in blood samples. At present, only a few immuno-assay methods were approved for marketing with detection systems and kits, most methods used for TDM are high performance liquid chromatography or liquid chromatography-tandem mass spectrometry which belong to laboratory developed tests (LDTs). Detection of TDM samples has many problems, such as incomparable testing results and large bias between different testing systems, including the biasbetween both different methods and different laboratories using the same method. There are several reasons:(1) the traceability chain has not been established, (2) the methods have not yet been standardized, (3) the coverage of the EQA plan is insufficient, (4) the awareness of TDM laboratories to participate in the EQA plan is insufficient, (5) TDM standardization is still in its infancy. These problems restrict the clinical application of TDM and the development of related research work. In order to solve these problems, it is necessary to: (1) Establish a reference system to realize the traceability of the test results; (2) While gradually increasing the TDM EQA plan items, the Trueness evaluation plan should be carried out as soon as possible; (3) Standardized TDM sample testing Technology; (4) Strengthen laboratory management and establish a complete quality management system.

Objective:To establish a candidate reference method for simultaneous determination of whole blood iron and copper based on ICP-MS technology.Methods:Cobalt (Co) was chosen as the internal standard, and was added gravimetrically into the standard solution and the whole blood sample. The whole blood sample was digested by electric heating plate and diluted. The isotopic ratios of 57Fe/ 59Co and 63Cu/ 59Co were measured by ICP-MS in the isotopic analysis mode. The precision, standard recovery and accuracy of the method were verified by measuring EQA materials and certified standard materials, and the performance of the method was further evaluated by method comparison. Results:The detection limit of iron is 0.136 mg/kg and the limit of quantification was 0.454 mg/kg in this method. The detection limit of copper in whole blood was 0.008 mg/kg and the limit of quantification was 0.027 mg/kg. The standard curve of copper ranges from 0.83-3.33 mg/kg, iron ranges from 167-667 mg/kg. The calibration curve of iron and copper was good linearity ( R 2>0.999 90). The precision of the method did well. The total CV range was 0.42%-0.68% for iron and 0.14%-0.94% for copper. The spike recoveries were all around 100%, the range of iron: 99.69%-100.07%; copper: 99.26%-100.51%. The correlation between this method and the existing clinical mass spectrometry methods was good. Conclusions:A candidate reference ICP-MS method for simultaneous determination of whole blood Fe and Cu was established. This is a simple and rapid method with good precision and spike recovery compared to the traditional one.