ObjectiveThis paper aims to explore the risk factors for chronic atrophic gastritis （CAG） with turbidity toxin accumulation syndrome and establish a prediction model. MethodsClinical data of 180 patients with CAG who participated in the "clinical study of Xianglian Huazhuo Particles blocking CAG cancer transformation" of Hebei Sheng Zhong Yi Yuan from July 2021 to March 2022 were collected. After confounding factors were controlled by propensity score matching， patients were divided into a training set （namely dev） and a validation set （namely vad） in a seven to three ratio. The risk factors for CAG with turbidity toxin accumulation syndrome in the training set were investigated by using univariate Logistic regression analysis and least absolute shrinkage and selection operator （namely Lasso） regression algorithms. Subsequently， a model， named model 1se， was developed by using the training set data to predict the risk factors for CAG with turbidity toxin accumulation syndrome. The accuracy of the prediction model was assessed by using various methods， including the receiver operating characteristic （ROC） curve， Hosmer-Lemeshow test （H-L）， calibration plot， and decision curve analysis （DCA）. ResultsAge， body mass index （BMI）， family history of cancer， job and life satisfaction， yellow and greasy fur with slippery pulse， and heavy body sensation were independent risk factors of the model. The prediction model showed excellent predictive value for both the training and validation sets. ConclusionThe established prediction model for CAG with turbidity toxin accumulation syndrome has high discrimination and excellent calibration， which could provide an excellent clinical basis for disease diagnosis and individualized treatment of patients.

ObjectiveThis paper aims to explore the risk factors for chronic atrophic gastritis （CAG） with turbidity toxin accumulation syndrome and establish a prediction model. MethodsClinical data of 180 patients with CAG who participated in the "clinical study of Xianglian Huazhuo Particles blocking CAG cancer transformation" of Hebei Sheng Zhong Yi Yuan from July 2021 to March 2022 were collected. After confounding factors were controlled by propensity score matching， patients were divided into a training set （namely dev） and a validation set （namely vad） in a seven to three ratio. The risk factors for CAG with turbidity toxin accumulation syndrome in the training set were investigated by using univariate Logistic regression analysis and least absolute shrinkage and selection operator （namely Lasso） regression algorithms. Subsequently， a model， named model 1se， was developed by using the training set data to predict the risk factors for CAG with turbidity toxin accumulation syndrome. The accuracy of the prediction model was assessed by using various methods， including the receiver operating characteristic （ROC） curve， Hosmer-Lemeshow test （H-L）， calibration plot， and decision curve analysis （DCA）. ResultsAge， body mass index （BMI）， family history of cancer， job and life satisfaction， yellow and greasy fur with slippery pulse， and heavy body sensation were independent risk factors of the model. The prediction model showed excellent predictive value for both the training and validation sets. ConclusionThe established prediction model for CAG with turbidity toxin accumulation syndrome has high discrimination and excellent calibration， which could provide an excellent clinical basis for disease diagnosis and individualized treatment of patients.

Neurocritical care involves complex pathophysiological mechanisms, and its incidence is higher, injuries are more severe, and treatment is more challenging in high-altitude environments. This consensus, based on the latest domestic and international evidence-based medical data, establishes a standardized, goal-oriented framework for neurocritical care management applicable in high-altitude regions and nationwide. The consensus was developed following international standards for evidence quality assessment and underwent two rounds of Delphi expert consultation, resulting in 32 recommendation statements covering three parts: management systems, monitoring and assessment, and core strategies. Key updates include: advocating for the establishment of independent neurocritical care units and implementing precise tiered diagnosis and treatment based on the "Five Differences in Critical Care" concept; constructing a "trinity" multimodal brain monitoring system centered on cerebral blood flow, cerebral oxygenation, and brain function, emphasizing routine bedside transcranial Doppler ultrasound, cerebral oximetry, and continuous electroencephalography monitoring; shifting management strategies from mild hypothermia therapy to targeted temperature management, and defining the "446" target management pathway for the supercritical stage; emphasizing the assessment of static and dynamic cerebrovascular autoregulation functions through multimodal methods to achieve individualized optimal mean arterial pressure management; elevating cerebrospinal fluid management goals to the level of "glymphatic system" function maintenance; implementing a multidisciplinary collaborative, whole-process management model focusing on patients' long-term neurological functional outcomes; de-escalation criteria include multidimensional indicators such as recovery of brain structure, restoration of cerebrovascular autoregulation, improvement in cerebrospinal fluid dynamics, and reduction in biomarker levels; and integrating cutting-edge technologies like artificial intelligence into post-critical care management and rehabilitation planning. This consensus systematically integrates the entire process of neurocritical care management, reflecting the modern connotation of goal-oriented, dynamic, and multimodal integration in neurocritical care medicine. It aims to adapt to new trends such as deepening understanding of pathophysiological mechanisms, the integration of medicine and engineering, and the empowerment of artificial intelligence, thereby further advancing the discipline of critical care medicine.

ObjectiveTo explore the relationship between acne vulgaris and gut microbiota. MethodsA total of 29 clinical cases diagnosed with moderate-to-severe acne vulgaris and 26 healthy individuals as control subjects were recruited. Fecal specimens were collected from all participants， and further analysis of gut microbial communities was performed by leveraging high-throughput sequencing techniques that target the hypervariable regions of 16S rRNA genes. ResultsAssociations between acne vulgaris and alterations in gut microbiota were identified. At the phylum level， the relative abundance of Bacteroidota exhibited a statistically significant elevation in the acne vulgaris cohort when compared with the healthy control group （P<0.01）， while Cyanobacteria was significantly lower in the acne group （P<0.01）. At the genus level， the top five different bacterial taxa in both groups were Bacteroides， Escherichia⁃Shigella， Klebsiella， Roseburia， and Parabacteroides. Among them， Bacteroides， Roseburia， and Parabacteroides were more abundant in acne patients. Linear discriminant analysis identified five biomarkers all belonging to the Bacteroidota phylum in the acne and control groups. These biomarkers belong to the phylum Bacteroidetes. ConclusionThere are significant differences in the composition of intestinal microbiota between acne patients and healthy people. Changes in the richness of specific bacterial genera may become new targets for the diagnosis and treatment of acne.

Employing bibliometric methods and adhering to principles of textual research， this study systematically investigated prescription source， formula name， composition evolution， dose evolution， origin， processing， ancient and modern applications of Xiaofengsan. Xiaofengsan， also known as Renshen Xiaofengsan and Chantui Xiaofengsan， was first recorded in the Taiping Huimin Hejijufang（hereafter referred to as Jufang） of the Southern Song dynasty. The formula composition included Schizonepetae Spica， Glycyrrhizae Radix et Rhizoma， Chuanxiong Rhizoma， Notoptery Rhizoma et Radix， Bombyx Batryticatus， Saposhnikoviae Radix， Poria， Cicadae Periostracum， Pogostemonis Herba， Ginseng Radix et Rhizoma， Magnoliae Officinalis Cortex and Citri Reticulatae Pericarpium， a total of 12 medicinal materials. In terms of the evolution of formula composition， formulas across dynasties largely aligned with those recorded in Jufang， with only minor variations in application. The results of the formula dosage research indicated that one dose of medication in Jufang corresponded to the following modern dosages：Schizonepetae Spica of 82.6 g， Glycyrrhizae Radix et Rhizoma of 82.6 g， Chuanxiong Rhizoma of 82.6 g， Notoptery Rhizoma et Radix of 82.6 g， Bombyx Batryticatus of 82.6 g， Saposhnikoviae Radix of 82.6 g， Poria of 82.6 g， Cicadae Periostracum of 82.6 g， Pogostemonis Herba of 82.6 g， Ginseng Radix et Rhizoma of 82.6 g， Magnoliae Officinalis Cortex of 20.65 g and Citri Reticulatae Pericarpium of 20.65 g， the origins of all the constituent drugs were consistent with the 2020 edition of Pharmacopoeia of the People's Republic of China. The results of the investigation into the decoction method indicated that the aforementioned drugs should be finely ground into powder（pass through the No.5 sieve）， and 8.26 g was taken for each dose， which was taken with the clear liquid obtained by steeping tea leaves in boiling water for several minutes. This mixture was administered three times daily， 30 min after meals. The ancient functional indications of this formula mainly involved dispelling wind-heat， eliminating pathogenic factors and regulating the middle Jiao. It primarily treated all wind-heat syndromes manifesting as skin diseases， predominantly affecting the upper body， especially the head and face. The diseases involved in modern applications were mostly dermatological diseases， including urticaria， eczema， atopic dermatitis and others. In this paper， by combing the relevant ancient literature， the key information of Xiaofengsan was textual researched， in order to provide reference for the modern application and development of this formula.

Objective To analyze the clinical characteristics of measles cases in the measles elimination stage and to provide a scientific basis for the prevention, control, diagnosis and treatment of measles. Methods The descriptive epidemiological method was used to analyze the clinical characteristics of 442 confirmed measles cases in Hebei Province from 2018 to 2020. Results Among the 442 measles cases, the main symptoms were rash (96.61%), fever (90.50%), cough (56.11%), and Koplik spots (30.09%). Complications were mainly pneumonia (12.22%). There were significant differences in symptoms among different age groups (P < 0.05). The incidence of symptoms in children under 5 years old (except cough) was higher than that in other age groups. Immunization history had no significant impact on the symptoms of fever and rash (P > 0.05), but the incidence of symptoms such as cough, conjunctivitis, Koplik's spots and catarrhal rhinitis in the immunized group was lower than that in the non-immunized group (P < 0.05). The group with an interval of 0 days from fever to rash was the largest, and the proportion of people with an immunization history in the 0-day group (68.06%) was significantly higher than that in the 3-4-day group (49.44%) (P < 0.05). Pneumonia complications were mainly concentrated in children under 5 years old (87.03%), and most of the cases had a 0-dose immunization history (81.48%). Conclusion In the measles elimination stage, the incidence of fever and rash in cases is relatively high, while the incidence of Koplik spots is relatively low. The symptoms are more obvious in the younger age group. Vaccination can reduce the incidence of specific symptoms. The change in the time of rash appearance suggests that the diagnosis and treatment plan need to be adjusted. This study provides key data support for the formulation of measles prevention, control and treatment strategies.

ObjectiveTo delineate imaging findings using an imaging platform and investigate the correlation between MRI characteristics of spinal cord atrophy and clinical diagnosis in children with spinal cord injury (SCI). MethodsImaging data of 150 children with SCI admitted to Beijing Bo'ai Hospital, China Rehabilitation Research Center, from January, 2002 to March, 2024 were collected and imported into the imaging platform. The anteroposterior and transverse diameters of the middle part of the spinal cord at the cross-section with the most severe atrophy were measured, and the relevant indicators of the previous normal spinal cord segment were measured as controls; the radiomic features were extracted. Clinical data of the children including gender, age, cause of injury, sensory level, motor level, spinal cord injury level, injury severity and disease course were collected. ResultsSpinal cord atrophy was identified in 81 cases (54%), among which 78 cases (96%) were American Spinal Injury Association Impairment Scale (AIS) grade A and 3 cases (4%) were AIS grade C. The upper boundary of the spinal cord atrophy site strongly correlated with the injury level, motor level and sensory level (r > 0.8, P < 0.001). ConclusionMore than half of children with SCI may develop secondary spinal cord atrophy, the vast majority of whom suffer from complete spinal cord injury; the upper boundary of spinal cord atrophy is correlated with the injury level.

ObjectiveTo develop a full-process data platform of renal rehabilitation, diagnosis and quality control information. MethodsA hierarchical architectural design was proposed, adhering to clinical pathway models and standardized data protocols. The platform comprehensively covered assessment, intervention, follow-up and quality control for maintenance hemodialysis (MHD) patients. By integrating multidisciplinary resources and standardizing rehabilitation workflows, it delivered standardized and intelligent rehabilitation services. ResultsThe platform achieved standardized and intelligent management of rehabilitation services, effectively improved the physiological function, psychological state and quality of life convenience for MHD patients, while significantly reduced the economic and care burden on patients' families and society. ConclusionThe rehabilitation service model based on a full-process data platform may provide scientific and systematic support for MHD patients.

Objective:To evaluate the correlation between preoperative platelet function and in-hospital mortality in patients with acute Stanford A aortic dissection(ATAAD) undergoing emergency surgery.Methods:ATAAD emergency surgical patients who underwent preoperative thromboelastography(TEG) examination at three cardiovascular disease hospitals from January 2018 to December 2023 were consecutively selected in this study. The patients were divided into two groups according to whether the patient survived to discharge.Results:867 patients were included in this study. The in-hospital mortality was 11.2%(97 cases). Compared with the DG group(97 cases), the age, pericardial effusion volume, lactate concentration, and MA value of patients in the SG group(770 cases) were higher( P<0.001). Factors independently associated with in-hospital mortality were age(>60 years old), coronary hypoperfusion, pericardial effusion volume(>200.00 ml), and MA value(<60.6 mm). There was a correlation between MA value and in-hospital mortality( P=0.012), and the mediating effect between MA value and platelet count was not significant. Conclusion:There is a correlation between preoperative platelet function and in-hospital in ATAAD patients, and improving platelet function may be one of the important ways to improve the clinical prognosis of those patients.

Under the combined effects of globalization, human activities, climate change, pathogen variation and other multiple factors, various infectious diseases have shown different trends in prevalence, posing a serious threat to human health. Neurological infections and autoimmune diseases have always been at the forefront of the field of neurology, involving complex pathogenesis, depicting with diverse clinical manifestations and posing numerous challenges in treatment. Infections of pathogens can damage the nervous system directly or induce autoimmune reactions. In recent years, with a deeper understanding of the pathogenesis of infection and autoimmunity, especially the expansion of the autoantibody spectrum and the progress in molecular immunotherapy, the prognosis of infectious and autoimmune diseases has been significantly improved. However, the risk of relapse is still high. Uncovering the pathogenesis is crucial to seek opportunities for early treatment.