Humans ; Vascular Stiffness ; Coal Mining ; Occupational Diseases/epidemiology* ; Risk Factors ; Coal ; Miners

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.

Immune checkpoint inhibitors have cahnged the management of patients with metastatic bladder cancer, by leading to long-term response and prolonged survival in a subset of patients. Unfortunately, only one in five patients with metastatic bladder cancer responds to immune checkpoint inhibitors. Preclinical and early clinical evidence indicates that radiotherapy not only acts locally, but It also plays a "double-edged sword" role in the immune system. It is hypothesized that combining checkpoint inhibitors with radiotherapy might enhance an anti-tumor immune response and increase response rates. With a review of research progresses in recent years, we believe that immunotherapy combined with radiotherapy may have a good applied perspective and is expected to further change the treatment pattern of metastatic bladder cancer.

Deep vein thrombosis(DVT)is a common peripheral vascular disease in clinical practice.The lack of precise and efficient early diagnostic techniques renders it susceptible to being overlooked or misdiagnosed,and therefore,identifying trustworthy biomarkers is a major issue that has to be resolved.In this study,the endogenous metabolites in the urine of DVT rats were screened by metabolomics technology based on gas chromatograph-mass spectrometry(GC-MS)and the characteristic metabolites were identified by multiple feature selection algorithms and multivariate statistical analysis,for the development of a machine learning-based diagnostic model for DVT.The urine samples in metabolic cage in the thrombus development phase(between 48 and 72 h)of rats were collected,which was used as the models for inferior vena cava ligation.The metabolic profiles of the control group and DVT were obtained using the GC-MS method.A total of 176 kinds of endogenous metabolites were identified in rat urine through comparison with the FiehnLib database,26 kinds of differential metabolites associated with DVT were screened through a combination of the Mann-Whitney U test and orthogonal partial least squares discriminant analysis(OPLS-DA),and 13 kinds of significant metabolites strongly correlated with DVT were further evaluated in conjunction with various machine learning feature selection techniques.For DVT diagnosis,machine learning models such as Gaussian Naive Bayes(GNB),support vector machine(SVM),logistic regression(LR),and linear discriminant analysis(LDA)were developed.The diagnostic model constructed using 13 kinds of key metabolites demonstrated excellent accuracy and stability,and surpassed the predictive performance of the models utilizing 176 kinds of metabolites and 26 kinds of differential metabolites,as evidenced by examination and comparison of each model's efficacy.The study showed that the integration of multiple feature selection algorithms for analyzing metabolite information in DVT rat urine was capable of effectively identifying reliable potential markers of DVT.Furthermore,the developed machine learning model offered a novel technical approach for the automated diagnosis of DVT.

Objective:Considering the large amount and poor quality of clinical data, this study aims to explore the establishment of high-quality research database and its role in real-world research by taking the establishment of lymphoma research database as an example.Methods:The expert opinions in the field of lymphoma were collected, and the relevant guidelines and standards were referenced to establish a standard medical knowledge dataset. The electronic diagnosis and treatment data of lymphoma patients treated in Peking University Cancer Hospital from February 2005 to December 2020 were retrospectively extracted, the deep Learning, natural language processing were adopted to build a dynamic intelligent information integration and processing system of " lymphoma database based on electronic medical record system - biological sample information database - extended genetic information database" .Results:The research database not only meets the research needs of clinical researchers, but also realizes the management of traces in the whole process of application, approval, traceability and analysis of hospital medical record data and biological sample data. The total number of research variables in the database was 668, and the structured variables accounted for 46.0%. On December 25, 2021, there were 68 687 lymphoma patients in the database, the ratio of male to female patients was 8/9, and the proportion of patients with ≥3 visits accounted for 23.0%. In addition, researchers can superimpose searches in the database according to the target conditions, display the targeted medical records according to research hypothesis, and then establish a research cohort, conducting statistical modeling, and mining data information.Conclusions:By integrating management processes and using new natural language artificial intelligence technology to establish a high-level evidence-based database, it is helpful for the interconnection and resource sharing of hospital information systems, so as to achieve the purpose of providing reliable and detailed data for real-world research.

During coronavirus disease 2019 epidemic, the treatment of severe trauma has been impacted. The Consensus on emergency surgery and infection prevention and control for severe trauma patients with 2019 novel corona virus pneumonia was published online on February 12, 2020, providing a strong guidance for the emergency treatment of severe trauma and the self-protection of medical staffs in the early stage of the epidemic. With the Joint Prevention and Control Mechanism of the State Council renaming "novel coronavirus pneumonia" to "novel coronavirus infection" and the infection being managed with measures against class B infectious diseases since January 8, 2023, the consensus published in 2020 is no longer applicable to the emergency treatment of severe trauma in the new stage of epidemic prevention and control. In this context, led by the Chinese Traumatology Association, Chinese Trauma Surgeon Association, Trauma Medicine Branch of Chinese International Exchange and Promotive Association for Medical and Health Care, and Editorial Board of Chinese Journal of Traumatology, the Chinese expert consensus on emergency surgery for severe trauma and infection prevention during coronavirus disease 2019 epidemic ( version 2023) is formulated to ensure the effectiveness and safety in the treatment of severe trauma in the new stage. Based on the policy of the Joint Prevention and Control Mechanism of the State Council and by using evidence-based medical evidence as well as Delphi expert consultation and voting, 16 recommendations are put forward from the four aspects of the related definitions, infection prevention, preoperative assessment and preparation, emergency operation and postoperative management, hoping to provide a reference for severe trauma care in the new stage of the epidemic prevention and control.

The acute combination fractures of the atlas and axis in adults have a higher rate of neurological injury and early death compared with atlas or axial fractures alone. Currently, the diagnosis and treatment choices of acute combination fractures of the atlas and axis in adults are controversial because of the lack of standards for implementation. Non-operative treatments have a high incidence of bone nonunion and complications, while surgeries may easily lead to the injury of the vertebral artery, spinal cord and nerve root. At present, there are no evidence-based Chinese guidelines for the diagnosis and treatment of acute combination fractures of the atlas and axis in adults. To provide orthopedic surgeons with the most up-to-date and effective information in treating acute combination fractures of the atlas and axis in adults, the Spinal Trauma Group of Orthopedic Branch of Chinese Medical Doctor Association organized experts in the field of spinal trauma to develop the Evidence-based guideline for clinical diagnosis and treatment of acute combination fractures of the atlas and axis in adults ( version 2023) by referring to the "Management of acute combination fractures of the atlas and axis in adults" published by American Association of Neurological Surgeons (AANS)/Congress of Neurological Surgeons (CNS) in 2013 and the relevant Chinese and English literatures. Ten recommendations were made concerning the radiological diagnosis, stability judgment, treatment rules, treatment options and complications based on medical evidence, aiming to provide a reference for the diagnosis and treatment of acute combination fractures of the atlas and axis in adults.

Salvianolic acid B(Sal B) is the main water-soluble component of Salvia miltiorrhiza Bunge. Studies have found that Sal B has a good protective effect on blood vessels. Sal B can protect endothelial cells by anti-oxidative stress, inducing autophagy, inhibiting endoplasmic reticulum stress(ERS), inhibiting endothelial inflammation and adhesion molecule expression, inhibiting endothelial cell permeability, anti-thrombosis, and other ways. In addition, Sal B can alleviate endothelial cell damage caused by high glucose(HG). For vascular smooth muscle cell(VSMC), Sal B can reduce the synthesis and secretion of inflammatory factors by inhibiting cyclooxygenase. It can also play a vasodilatory role by inhibiting Ca~(2+) influx. In addition, Sal B can inhibit VSMC proliferation and migration, thereby alleviating vascular stenosis. Sal B also inhibits lipid deposition in the subendothelium, inhibits macrophage conversion to foam cells, and reduces macrophage apoptosis, thereby reducing the volume of subendothelial lipid plaques. For some atherosclerosis(AS) complications, such as peripheral artery disease(PAD), Sal B can promote angiogenesis, thereby improving ischemia. It should be pointed out that the conclusions obtained from different experiments are not completely consistent, which needs further research. In addition, previous pharmacokinetics showed that Sal B was poorly absorbed by oral administration, and it was unstable in the stomach, with a large first-pass effect in the liver. Sal B had fast distribution and metabolism in vivo and short drug action time. These affect the bioavailability and biological effects of Sal B, and the development of clinically valuable Sal B non-injectable delivery systems remains a great challenge.
Endothelial Cells ; Oxidative Stress ; Benzofurans/pharmacology* ; Lipids

Humans ; Intervertebral Disc Displacement/surgery* ; Skull ; Lumbar Vertebrae/surgery* ; Blindness ; Treatment Outcome ; Intervertebral Disc Degeneration/surgery*

Melatonin receptor 1B (MT2, encoded by the MTNR1B gene), a high-affinity receptor for melatonin, is associated with glucose homeostasis including glucose uptake and transport. The rs10830963 variant in the MTNR1B gene is linked to glucose metabolism disorders including gestational diabetes mellitus (GDM); however, the relationship between MT2-mediated melatonin signaling and a high birth weight of GDM infants from maternal glucose abnormality remains poorly understood. This article aims to investigate the relationship between rs10830963 variants and GDM development, as well as the effects of MT2 receptor on glucose uptake and transport in trophoblasts. TaqMan-MGB (minor groove binder) probe quantitative real-time polymerase chain reaction (qPCR) assays were used for rs10930963 genotyping. MT2 expression in the placenta of GDM and normal pregnant women was detected by immunofluorescence, western blot, and qPCR. The relationship between MT2 and glucose transporters (GLUTs) or peroxisome proliferator-activated receptor γ (PPARγ) was established by western blot, and glucose consumption of trophoblasts was measured by a glucose assay kit. The results showed that the genotype and allele frequencies of rs10830963 were significantly different between GDM and normal pregnant women (P<0.05). The fasting, 1-h and 2-h plasma glucose levels of G-allele carriers were significantly higher than those of C-allele carriers (P<0.05). Besides, the protein and messenger RNA (mRNA) expression of MT2 in the placenta of GDM was significantly higher than that of normal pregnant women (P<0.05). Melatonin could stimulate glucose uptake and GLUT4 and PPARγ protein expression in trophoblasts, which could be attenuated by MT2 receptor knockdown. In conclusion, the rs10830963 variant was associated with an increased risk of GDM. The MT2 receptor is essential for melatonin to raise glucose uptake and transport, which may be mediated by PPARγ.
Female ; Humans ; Pregnancy ; Blood Glucose/metabolism* ; Diabetes, Gestational/metabolism* ; Glucose/metabolism* ; Melatonin/metabolism* ; Polymorphism, Genetic ; PPAR gamma ; Receptor, Melatonin, MT2/genetics*