Cervical spinal cord injury without fracture-dislocation (CSCIWFD) is referred to as a special type of cervical spinal cord injury characterized by traumatic spinal cord dysfunction and no significant bony structural abnormalities on imagines. Duo to the high risk of missed diagnosis during the initial consultation, CSCIWFD may lead to progressive neurological deterioration or even complete paralysis, severely impacting patients′ prognosis. Currently, there are no established consensuses over the diagnosis and treatment of CSCIWFD, such as the lack of evidence-based standards for indications of non-surgical treatment and risk of secondary neurological injury, as well as debates over the optimal timing for surgical intervention and indications for different surgical approaches. To address these issues, the Spine Trauma Group of the Orthopedic Branch of the Chinese Medical Doctor Association organized experts in the relevant fields to formulate Diagnosis and treatment guideline for acute cervical spinal cord injury without fracture- dislocation in adults ( version 2025) . Based on evidence-based medicine and the principles of scientific rigor and clinical applicability, the guidelines proposed 11 recommendations covering terminology, diagnosis, evaluation treatment, and rehabilitation, etc., aiming to standardize the management of CSCIWFD.

Objective:To investigate the effects of toosendanin(TSN)on the proliferation,apoptosis,migration and invasion of esophageal squamous cell carcinoma(ESCC)KYSE150 cells,and to elucidate its underlying molecular mechanisms.Methods:CCK-8 assay,colony formation assay,and EdU assay were used to assess the effects of varying TSN concentrations(0.062 5,0.125,and 0.25 μmol/L)on KYSE150 cell proliferation.The impacts of TSN on the apoptosis,migration,and invasion of KYSE150 cells were evaluated using flow cytometry,wound healing assay,and Transwell chamber assay,respectively.The expression of hypoxia-inducible factor 1 alpha(HIF1A)in esophageal cancer tissues was analyzed using the GEPIA database.qPCR was used to detect the expression level of HIF1A mRNA in human esophageal epithelial Het-1A and KYSE150 cells,and in TSN-treated KYSE150 cells.Western blot(WB)was performed to detect the effects of TSN on the upstream signaling pathway AKT/mTOR of HIF1A and the expression of downstream proteins related to cell migration,invasion,and apoptosis.Results:TSN of varying concentrations significantly inhibited proliferation,migration,and invasion of KYSE150 cells and promoted apoptosis in a dose-dependent manner(P<0.05 or P<0.01).HIF1A mRNA was highly expressed in KYSE150 cells,and its expression was significantly downregulated after TSN treatment(P<0.05 or P<0.01).TSN markedly downregulated the expression of HIF1A and key upstream signaling proteins p-AKT and p-mTOR.In addition,TSN significantly suppressed the expression of downstream proteins associated with cell migration,invasion,and apoptosis,including N-cadherin,vimentin,Bcl-2,and caspase-3,while upregulating the expression of E-cadherin(P<0.05 or P<0.01).Conclusion:TSN inhibits the proliferation,migration,and invasion,and induces apoptosis in ESCC KYSE150 cells by down-regulating HIF1A expression through suppression of the AKT/mTOR signaling pathway.

Cervical spinal cord injury without fracture-dislocation (CSCIWFD) is referred to as a special type of cervical spinal cord injury characterized by traumatic spinal cord dysfunction and no significant bony structural abnormalities on imagines. Duo to the high risk of missed diagnosis during the initial consultation, CSCIWFD may lead to progressive neurological deterioration or even complete paralysis, severely impacting patients′ prognosis. Currently, there are no established consensuses over the diagnosis and treatment of CSCIWFD, such as the lack of evidence-based standards for indications of non-surgical treatment and risk of secondary neurological injury, as well as debates over the optimal timing for surgical intervention and indications for different surgical approaches. To address these issues, the Spine Trauma Group of the Orthopedic Branch of the Chinese Medical Doctor Association organized experts in the relevant fields to formulate Diagnosis and treatment guideline for acute cervical spinal cord injury without fracture- dislocation in adults ( version 2025) . Based on evidence-based medicine and the principles of scientific rigor and clinical applicability, the guidelines proposed 11 recommendations covering terminology, diagnosis, evaluation treatment, and rehabilitation, etc., aiming to standardize the management of CSCIWFD.

Spinal surgical site infection (SSI), especially deep SSI after internal fixation is difficult in treatment, with long course of disease and poor prognosis. At present, there are many controversies in the diagnosis and treatment of spinal SSI, with unsatisfactory overall efficacy of its diagnosis and treatment. Besides, no diagnosis and treatment guideline based on evidence-based medicine has been in existence. To this end, the Spinal Infection Group of the Orthopedic Branch of the Chinese Medical Doctor Association and the Spinal Infection Group of the Spinal Surgery Branch of the Chinese Rehabilitation Medicine Association jointly organized relevant experts to formulate Evidence-based clinical guideline for the diagnosis and treatment of surgical site infection in spinal trauma ( version 2024) based on an evidence-based approach. A total of 10 recommendations were proposed on the diagnosis and treatment of spinal SSI, so as to provide a clinical reference for the diagnosis and treatment of spinal SSI.

Objectives:To develop and validate predictive models for esophageal squamous cell carcinoma (ESCC) using circulating cell-free DNA (cfDNA) terminal motif analysis. The goal was to improve the non-invasive detection of early-stage ESCC and its precancerous lesions.Methods:Between August 2021 and November 2022, we prospectively collected plasma samples from 448 individuals at the Department of Endoscopy, Cancer Hospital, Chinese Academy of Medical Sciences for cfDNA extraction, library construction, and sequencing. We analyzed 201 cases of ESCC, 46 high-grade intraepithelial neoplasia (HGIN), 46 low-grade intraepithelial neoplasia (LGIN), 176 benign esophageal lesions, and 29 healthy controls. Participants, including ESCC patients and control subjects, were randomly assigned to a training set ( n=284) and a validation set ( n=122). The training cohort underwent z-score normalization of cfDNA terminal motif matrices and a selection of distinctive features differentiated ESCC cases from controls. The random forest classifier, Motif-1 (M1), was then developed through principal component analysis, ten-fold cross-validation, and recursive feature elimination. M1's efficacy was then validated in the validation and precancerous lesion sets. Subsequently, individuals with precancerous lesions were included in the dataset and participants were randomly allocated to newly formed training ( n=243), validation ( n=105), and test ( n=150) cohorts. Using the same procedure as M1, we trained the Motif-2 (M2) random forest model with the training cohort. The M2 model's accuracy was then confirmed in the validation cohort to establish the optimal threshold and further tested by performing validation in the test cohort. Results:We developed two cfDNA terminal motif-based predictive models for ESCC and associated precancerous conditions. The first model, M1, achieved a sensitivity of 90.0%, a specificity of 77.4%, and an area under the curve (AUC) of 0.884 in the validation cohort. For LGIN, HGIN, and T1aN0 stage ESCC, M1's sensitivities were 76.1%, 80.4%, and 91.2% respectively. Notably, the sensitivity for jointly predicting HGIN and T1aN0 ESCC reached 85.0%. Both the predictive accuracy and sensitivity increased in line with the cancer's progression ( P＜0.001). The second model, M2, exhibited a sensitivity of 87.5%, a specificity of 77.4%, and an AUC of 0.857 in the test cohort. M2's sensitivities for detecting precancerous lesions and ESCC were 80.0% and 89.7%, respectively, and it showed a combined sensitivity of 89.4% for HGIN and T1aN0 stage ESCC. Conclusions:Two predictive models based on cfDNA terminal motif analysis for ESCC and its precancerous lesions are developed. They both show high sensitivity and specificity in identifying ESCC and its precancerous stages, indicating its potential for early ESCC detection.

Ankylosing spondylitis (AS) combined with lower cervical fracture is often categorized into unstable fracture, with a high incidence of neurological injury and a high rate of disability and morbidity. As factors such as shoulder occlusion may affect the accuracy of X-ray imaging diagnosis, it is often easily misdiagnosed at the primary diagnosis. Non-operative treatment has complications such as bone nonunion and the possibility of secondary neurological damage, while the timing, access and choice of surgical treatment are still controversial. Currently, there are no clinical practice guidelines for the treatment of AS combined with lower cervical fracture with or without dislocation. To this end, the Spinal Trauma Group of Orthopedics Branch of Chinese Medical Doctor Association organized experts to formulate Clinical guidelines for the treatment of ankylosing spondylitis combined with lower cervical fracture in adults ( version 2024) in accordance with the principles of evidence-based medicine, scientificity and practicality, in which 11 recommendations were put forward in terms of the diagnosis, imaging evaluation, typing and treatment, etc, to provide guidance for the diagnosis and treatment of AS combined with lower cervical fracture.

Objectives:To develop and validate predictive models for esophageal squamous cell carcinoma (ESCC) using circulating cell-free DNA (cfDNA) terminal motif analysis. The goal was to improve the non-invasive detection of early-stage ESCC and its precancerous lesions.Methods:Between August 2021 and November 2022, we prospectively collected plasma samples from 448 individuals at the Department of Endoscopy, Cancer Hospital, Chinese Academy of Medical Sciences for cfDNA extraction, library construction, and sequencing. We analyzed 201 cases of ESCC, 46 high-grade intraepithelial neoplasia (HGIN), 46 low-grade intraepithelial neoplasia (LGIN), 176 benign esophageal lesions, and 29 healthy controls. Participants, including ESCC patients and control subjects, were randomly assigned to a training set ( n=284) and a validation set ( n=122). The training cohort underwent z-score normalization of cfDNA terminal motif matrices and a selection of distinctive features differentiated ESCC cases from controls. The random forest classifier, Motif-1 (M1), was then developed through principal component analysis, ten-fold cross-validation, and recursive feature elimination. M1's efficacy was then validated in the validation and precancerous lesion sets. Subsequently, individuals with precancerous lesions were included in the dataset and participants were randomly allocated to newly formed training ( n=243), validation ( n=105), and test ( n=150) cohorts. Using the same procedure as M1, we trained the Motif-2 (M2) random forest model with the training cohort. The M2 model's accuracy was then confirmed in the validation cohort to establish the optimal threshold and further tested by performing validation in the test cohort. Results:We developed two cfDNA terminal motif-based predictive models for ESCC and associated precancerous conditions. The first model, M1, achieved a sensitivity of 90.0%, a specificity of 77.4%, and an area under the curve (AUC) of 0.884 in the validation cohort. For LGIN, HGIN, and T1aN0 stage ESCC, M1's sensitivities were 76.1%, 80.4%, and 91.2% respectively. Notably, the sensitivity for jointly predicting HGIN and T1aN0 ESCC reached 85.0%. Both the predictive accuracy and sensitivity increased in line with the cancer's progression ( P＜0.001). The second model, M2, exhibited a sensitivity of 87.5%, a specificity of 77.4%, and an AUC of 0.857 in the test cohort. M2's sensitivities for detecting precancerous lesions and ESCC were 80.0% and 89.7%, respectively, and it showed a combined sensitivity of 89.4% for HGIN and T1aN0 stage ESCC. Conclusions:Two predictive models based on cfDNA terminal motif analysis for ESCC and its precancerous lesions are developed. They both show high sensitivity and specificity in identifying ESCC and its precancerous stages, indicating its potential for early ESCC detection.

Spinal surgical site infection (SSI), especially deep SSI after internal fixation is difficult in treatment, with long course of disease and poor prognosis. At present, there are many controversies in the diagnosis and treatment of spinal SSI, with unsatisfactory overall efficacy of its diagnosis and treatment. Besides, no diagnosis and treatment guideline based on evidence-based medicine has been in existence. To this end, the Spinal Infection Group of the Orthopedic Branch of the Chinese Medical Doctor Association and the Spinal Infection Group of the Spinal Surgery Branch of the Chinese Rehabilitation Medicine Association jointly organized relevant experts to formulate Evidence-based clinical guideline for the diagnosis and treatment of surgical site infection in spinal trauma ( version 2024) based on an evidence-based approach. A total of 10 recommendations were proposed on the diagnosis and treatment of spinal SSI, so as to provide a clinical reference for the diagnosis and treatment of spinal SSI.

Objective:To evaluate artificial intelligence constructed by deep convolutional neural network (DCNN) for the site identification in upper gastrointestinal endoscopy.Methods:A total of 21 310 images of esophagogastroduodenoscopy from the Cancer Hospital of Chinese Academy of Medical Sciences from January 2019 to June 2021 were collected. A total of 19 191 images of them were used to construct site identification model, and the remaining 2 119 images were used for verification. The performance differences of two models constructed by DCCN in the identification of 30 sites of the upper digestive tract were compared. One model was the traditional ResNetV2 model constructed by Inception-ResNetV2 (ResNetV2), the other was a hybrid neural network RESENet model constructed by Inception-ResNetV2 and Squeeze-Excitation Networks (RESENet). The main indices were the accuracy, the sensitivity, the specificity, positive predictive value (PPV) and negative predictive value (NPV).Results:The accuracy, the sensitivity, the specificity, PPV and NPV of ResNetV2 model in the identification of 30 sites of the upper digestive tract were 94.62%-99.10%, 30.61%-100.00%, 96.07%-99.56%, 42.26%-86.44% and 97.13%-99.75%, respectively. The corresponding values of RESENet model were 98.08%-99.95%, 92.86%-100.00%, 98.51%-100.00%, 74.51%-100.00% and 98.85%-100.00%, respectively. The mean accuracy, mean sensitivity, mean specificity, mean PPV and mean NPV of ResNetV2 model were 97.60%, 75.58%, 98.75%, 63.44% and 98.76%, respectively. The corresponding values of RESENet model were 99.34% ( P<0.001), 99.57% ( P<0.001), 99.66% ( P<0.001), 90.20% ( P<0.001) and 99.66% ( P<0.001). Conclusion:Compared with the traditional ResNetV2 model, the artificial intelligence-assisted site identification model constructed by RESENNet, a hybrid neural network, shows significantly improved performance. This model can be used to monitor the integrity of the esophagogastroduodenoscopic procedures and is expected to become an important assistant for standardizing and improving quality of the procedures, as well as an significant tool for quality control of esophagogastroduodenoscopy.

Ankylosing spondylitis (AS) combined with spinal fractures with thoracic and lumbar fracture as the most common type shows characteristics of unstable fracture, high incidence of nerve injury, high mortality and high disability rate. The diagnosis may be missed because it is mostly caused by low-energy injury, when spinal rigidity and osteoporosis have a great impact on the accuracy of imaging examination. At the same time, the treatment choices are controversial, with no relevant specifications. Non-operative treatments can easily lead to bone nonunion, pseudoarthrosis and delayed nerve injury, while surgeries may be failed due to internal fixation failure. At present, there are no evidence-based guidelines for the diagnosis and treatment of AS combined with thoracic and lumbar fracture. In this context, the Spinal Trauma Academic Group of Orthopedics Branch of Chinese Medical Doctor Association organized experts to formulate the Clinical guideline for the diagnosis and treatment of adult ankylosing spondylitis combined with thoracolumbar fracture ( version 2023) by following the principles of evidence-based medicine and systematically review related literatures. Ten recommendations on the diagnosis, imaging evaluation, classification and treatment of AS combined with thoracic and lumbar fracture were put forward, aiming to standardize the clinical diagnosis and treatment of such disorder.