Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

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.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective Cervical disc herniation(CDH)is one of the common orthopaedic diseases.With the in-depth study of it and the development of cervical implants,the establishment of cervical fusion animal models has become an indispensable part.Notably however,studies of the establishment and evaluation of cervical fusion animal models in China are currently lacking.This study aimed to provide a suitable animal model and evaluation scheme for implants for cervical spine-related research.Methods Small-tailed Han sheep were chosen for anterior cervical discectomy fusion(ACDF)after modified surgery,and a polyetheretherketone(PEEK)interbody fusion cage(Cage)(control group),3D-printed Ti6Al4V Cage(group 1),and new method Ti6Al4V Cage(group 2)were implanted in different cervical segments(C2/3～C4/5)in each sheep,respectively.Hematology and histopathological analyses were carried out after surgery to evaluate recovery of sheep and the biosafety of the materials.Bone in-growth and bone fusion were assessed by X-ray,computed tomography(CT),Micro-CT and quantitative analysis,hard tissue section staining,and biomechanical tests.Results The modified ACDF ovine model was established successfully.There were no significant differences in important hematology indexes(P＞0.05)and histopathological analysis showed no pathological changes,such as inflammatory cell infiltration.The implants had good biosafety.Furthermore,X-ray and CT examinations showed that the position of internal fixation and the interbody fusion were good.Micro-CT and quantitative analysis at 3 and 6 months after operation showed that compared with PEEK Cage group,the bone volume/total volume and trabecular number were significantly increased(P＜0.01)while the trabecular spacing was significantly decreased in the new method Ti6Al4V and 3D-printed Ti6Al4V groups compared with the PEEK Cage group(P＜0.01).Moreover,the new method new method Ti6Al4V Cage group had more bone growth(P＜0.01).Hard tissue section staining demonstrated that the pores of the new method Ti6Al4V Cage and 3D-printed Ti6Al4V Cage had obvious bone growth and relatively dense pores in the new method Ti6Al4V and 3D-printed Ti6Al4V groups,and the combination was slightly better than that of PEEK Cage.Biomechanical evaluation indicated that the new method Ti6Al4V Cage and 3D-printed Ti6Al4V Cage reduced the range of cervical flexion-extension,lateral bending,and axial rotation(P＜0.05)compared with the PEEK cage,as well as enhancing the stability of the cervical vertebra,and the new method Ti6Al4 V Cage was more advantageous(P＜0.05).Conclusions After the establishment of the modified ACDF ovine model,reasonable and effective assessment method were used to demonstrate the suitability and effectiveness of the model and the good biosecurity of all three Cage materials.Compared with the PEEK Cage,the new method Ti6Al4V Cage and 3D-printed Ti6Al4V Cages showed better performances in terms of bone growth and bone fusion,which could enhance the stability of the cervical vertebrae.The new method Ti6Al4V Cage was particularly advantageous.

Objective To analyze the daily quality assurance(QA)measurement results of IBA Sphinx Compact device on the Mevion compact pencil beam scanning proton therapy system for evaluating its clinical application value in proton therapy.Methods The daily QA measurement of Mevion S250i proton therapy system was carried out with Sphinx Compact device for 30 consecutive days,and the measurement results were analyzed.Results The average deviation between the positioning laser and the image center was(0.42±0.27)mm in 30 days.All of the proximal and distal depth errors of the high-and low-energy pencil beams were within 0.50 mm.The position deviation of all the spots measured did not exceed 1.00 mm,and the size deviation was less than 7.5%.The deviation between the image center and the beam center was not more than 0.75 mm.The relative deviation of the flatness of the rectangular field was about 0.5%.The deviation of the output dose of the square field was within 1.0%.Conclusion The proton system daily QA measurement items recommended by AAPM TG-224 report can be accurately and rapidly measured with Sphinx Compact device.The device is a practical and efficient daily QA tool with high practical value in clinic.

Objective:To verify and calibrate the CT modeling curves of three CT devices in RayStation proton treatment planning system (TPS).Methods:CT-mass density (CT-MD) curves were established by CT Hounsfield units of different tissue substitute materials obtained by scanning the model with CT equipment. CT-stopping power (CT-SP) curves were established by calculation based on the chemical composition of various human tissues. The equivalent water thickness of tissue substitute modules was calculated with different CT modeling curves in TPS. The actual equivalent water thickness of various modules was measured by a Bragg peak detector, and compared with the calculated values of TPS to verify the accuracy of different CT models.Results:The differences of CT modeling curves were significantly different under different tube voltage scanning protocols. Compared with CT-MD curves, CT-SP curves based on the stoichiometric calibration were more suitable for proton dose calculation. However, the values of stopping power corresponding to high CT values still needed to be optimized, and the calculation error after calibration was less than 3%.Conclusion:The method of verifying and calibrating CT unit curves of proton TPS is described, proving that the CT-SP curves after stoichiometric calculation are more suitable for proton dose calculation.

Ossification of the posterior longitudinal ligament (OPLL) is a condition comprising ectopic bone formation from spinal ligaments. This disease is a leading cause of myelopathy in the Asian population. However, the molecular mechanism underlying OPLL and efficient preventive interventions remain unclear. Here, we performed single-cell RNA sequencing and revealed that type I interferon (IFN) signaling was activated in the ossified ligament of patients with OPLL. We also observed that IFN-β stimulation promoted the osteogenic differentiation of preosteoblasts in vitro and activated the ossification-related gene SPP1, thereby confirming the single-cell RNA sequencing findings. Further, blocking the IFN-α/β subunit 1 receptor (IFNAR1) using an anti-IFNAR1 neutralizing antibody markedly suppressed osteogenic differentiation. Together, these results demonstrated that the type I IFN signaling pathway facilitated ligament ossification, and the blockade of this signaling might provide a foundation for the prevention of OPLL.
Humans ; Signal Transduction ; Interferon Type I/metabolism* ; Ossification of Posterior Longitudinal Ligament/genetics* ; Gene Expression Profiling ; Single-Cell Analysis ; Osteogenesis/genetics* ; Receptor, Interferon alpha-beta/metabolism* ; Male ; Female ; Cell Differentiation ; Middle Aged

Emerging evidence indicates that the gut microbiome contributes to the host immune response to infectious diseases. Here, to explore the role of the gut microbiome in the host immune responses in COVID-19, we conducted shotgun metagenomic sequencing and immune profiling of 14 severe/critical and 24 mild/moderate COVID-19 cases as well as 31 healthy control samples. We found that the diversity of the gut microbiome was reduced in severe/critical COVID-19 cases compared to mild/moderate ones. We identified the abundance of some gut microbes altered post-SARS-CoV-2 infection and related to disease severity, such as Enterococcus faecium, Coprococcus comes, Roseburia intestinalis, Akkermansia muciniphila, Bacteroides cellulosilyticus and Blautia obeum. We further analyzed the correlation between the abundance of gut microbes and host responses, and obtained a correlation map between clinical features of COVID-19 and 16 severity-related gut microbe, including Coprococcus comes that was positively correlated with CD3⁺/CD4⁺/CD8⁺ lymphocyte counts. In addition, an integrative analysis of gut microbiome and the transcriptome of peripheral blood mononuclear cells (PBMCs) showed that genes related to viral transcription and apoptosis were up-regulated in Coprococcus comes low samples. Moreover, a number of metabolic pathways in gut microbes were also found to be differentially enriched in severe/critical or mild/moderate COVID-19 cases, including the superpathways of polyamine biosynthesis II and sulfur oxidation that were suppressed in severe/critical COVID-19. Together, our study highlighted a potential regulatory role of severity related gut microbes in the immune response of host.
COVID-19 ; Clostridiales ; Gastrointestinal Microbiome ; Humans ; Immunity ; Leukocytes, Mononuclear ; SARS-CoV-2

Objective:To describe the baseline characteristics of the subjects enrolled in the China Quantitative CT (QCT) big data program in 2018—2019.Methods:Based on baseline data from the Chinese health big data project from January 2018 to December 2019 from the eligible enrolled population, measurements of bone mineral density (BMD) and visceral adipose tissue (VAT) were performed using Mindways′ QCT Pro Model 4 system. The baseline data of age, gender, regional distribution, height, weight, abdominal circumference, blood pressure, blood routine and blood biochemical tests were analyzed. And the single factor analysis of variance (ANOVA) was used to check the age related trend of BMD and VAT in both genders.Results:After screening the inclusion exclusion criteria and outliers of the main indicators, 86 113 people were enrolled in the project. The enrollment rate was 92.47%, including 35 431 (41.1%) women and 50 682 (58.9%) men, and the ratio of men to women was 1.43. The mean age was (50.3±12.7) years in all the subjects, and it was (50.2±12.8) years and (50.4±12.5) years in men and women, respectively, and there was no statistical difference between the two genders ( P>0.05). Total of 43 833 people were enrolled in east China, it was the largest group by region (50.90%), it was followed by central China (16 434 people, 19.08%), and the number of people enrolled in Northeast China was the lowest (2 914 people, 3.38%). The rate of completing of health information indicators related to the main outcome of the study were all above 70%, and there were significant differences between men and women (all P<0.05). The mean BMD was (139.33±46.76) mg/cm 3 in women, (135.90±36.48) mg/cm 3 in men, which showed a decreasing trend with age in both gender (both P<0.001); the mean intra-abdominal fat area was (116.39±56.23) cm 2 in women, (191.67±77.07) cm 2 in men, and there was an increasing trend with age in both men and women (both P<0.001). Conclusions:There are gender differences in BMD and VAT measured by QCT with different age tendency, and there are gender differences in health information index. Regional factors should also be taken into account for regional differences in the inclusion of data.