Background: Disorders of the blood-brain barrier (BBB) arising from diabetes mellitus are closely related to diabetic encephalopathy. Previous research has suggested that neuron-glia antigen 2 (NG2)-glia plays a key role in maintaining the integrity of the BBB. However, the mechanism by which NG2-glia regulates the diabetic BBB remains unclear. Methods: Type 2 diabetes mellitus (T2DM) db/db mice and db/m mice were used. Evans-Blue BBB permeability tests and transmission electron microscopy techniques were applied. Tight junction proteins were assessed by immunofluorescence and transmission electron microscopy. NG2-glia number and signaling pathways were evaluated by immunofluorescence. Detection of matrix metalloproteinase-9 (MMP-9) in serum was performed using enzyme-linked immunosorbent assay (ELISA). Results: In T2DM db/db mice, BBB permeability in the hippocampus significantly increased from 16 weeks of age, and the structure of tight junction proteins changed. The number of NG2-glia in the hippocampus of db/db mice increased around microvessels from 12 weeks of age. Concurrently, the expression of MMP-9 increased in the hippocampus with no change in serum. Sixteen- week-old db/db mice showed activation of the Wnt/β-catenin signaling in hippocampal NG2-glia. Treatment with XAV-939 improved structural and functional changes in the hippocampal BBB and reduced MMP-9 secretion by hippocampal NG2-glia in db/db mice. It was also found that the upregulation of β-catenin protein in NG2-glia in the hippocampus of 16-week-old db/db mice was significantly alleviated by treatment with XAV-939. Conclusion The results indicate that NG2-glia can lead to structural and functional disruption of the diabetic BBB by activating Wnt/β-catenin signaling, upregulating MMP-9, and degrading tight junction proteins.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

The abnormal accumulation, structural change, and spread of tau protein in the brain are now considered important factors in the progression of Alzheimer’s disease (AD) and many other tau-related neurodegenerative diseases. Clinical and pathological studies have shown that the amount and distribution of abnormal tau protein are closely related to synaptic damage, neuronal loss, and cognitive decline. Therefore, tau protein has become an important target for disease-modifying therapy. However, tau is difficult to target because it has no fixed structure, lacks a clear active site, undergoes many post-translational modifications, and forms different abnormal structures in different diseases and disease stages. Therefore, the effective and selective removal of harmful tau species is both a major opportunity and a major challenge in drug discovery for neurodegenerative diseases. Proteolysis-targeting chimeras (PROTACs) offer a new strategy to deal with this problem. Unlike traditional inhibitors, PROTACs do not simply block protein function. Instead, they bring the target protein close to an E3 ubiquitin ligase, which leads to ubiquitination and degradation of the target protein by the proteasome. This event-driven mechanism may be especially useful for disease-related proteins such as tau protein, which are hard to inhibit with traditional small molecules. In recent years, tau protein-targeting PROTACs and related degradation strategies have shown promising effects in cell and animal models. These effects include reducing abnormal tau protein levels, lowering synaptic toxicity, regulating disease-related signaling pathways, and improving behavioral or cognitive outcomes. These studies support targeted tau protein degradation as a promising therapeutic approach, although many problems still need to be solved before clinical use. In this review, we summarize recent progress in the development of tau protein-targeting PROTACs and discuss the main factors that affect their design and activity. We focus on the choice of tau protein-binding ligands, their binding sites, and their ability to recognize abnormal tau protein rather than normal tau protein. We also discuss the selection of E3 ligase recruiters, linker length and structure, ternary complex formation, and structure-activity relationships that influence degradation potency and selectivity. In addition, we introduce new strategies beyond traditional proteasomal degradation, including the regulation of tau protein phosphorylation and autophagy-based clearance. These approaches may be more suitable for different tau species or different stages of disease. A major challenge for tau protein-targeting PROTACs is delivery to the central nervous system. Many PROTACs have high molecular mass, large polar surface area, flexible structures, and may be removed by efflux transporters. As a result, they often have poor ability to cross the blood-brain barrier and may not reach enough free drug levels in the brain. Therefore, the therapeutic potential of tau protein-targeting PROTACs depends not only on their ability to degrade tau protein in vitro, but also on whether they can achieve long-lasting, selective, and safe target engagement in important brain regions after practical administration. Future studies should focus on improving selectivity for abnormal tau protein, understanding E3 ligase function in neural cells, designing brain-penetrant molecules, developing better delivery methods, and testing these drugs in models that better reflect human disease. Overall, tau protein-targeting PROTACs are a promising and fast-developing strategy for treating tau-related diseases. However, their successful clinical translation will require progress in chemical biology, medicinal chemistry, neuroscience, drug delivery, and translational medicine.

Objective To propose a framework for risk assessment and stepwise management of pulmonary nodules based on existing guidelines and key studies, and to clarify the boundaries for triage, workup escalation, and referral in different detection scenarios. Methods A problem-oriented evidence synthesis approach was used, prioritizing Chinese expert consensus, Fleischner Society Guidelines, British Thoracic Society (BTS) Guidelines, and Lung-RADS. This was supplemented by studies on risk models, imaging measurements, liquid biopsy, tissue sampling, and surgical treatments. This paper is not presented as a formal consensus or a validated clinical pathway. Results A three-tiered framework consisting of basic non-invasive assessment, advanced assessment, and invasive diagnosis was established. It specified the applicable populations, boundaries for the use of risk models, imaging review, management of conflicting results, evaluation of histopathological consistency, and post-intervention follow-up. Liquid biopsy, genetic testing, and artificial intelligence were defined as investigational or adjunctive tools. Conclusion This framework can serve as a preliminary reference for multidisciplinary teams in developing local protocols. It cannot replace applicable guidelines, pathological diagnosis, shared decision-making with patients, or real-world validation.

Objective:To predict mechanical complications (MC) following spinal deformity surgery for adult spine deformity (ASD) using machine learning models, identify key risk factors, and develop a visualizable tool for individualized risk assessment.Methods:Clinical and radiological data from 525 patients with ASD who underwent surgery in our hospital between January 2017 and December 2021 were collected. Patients were randomly assigned to a training set (70%) and a test set (30%) for model development. The cohort included 88 males and 437 females, with a mean age of 42.2±18.1 years. Variables included demographic data, comorbidities, local and systemic radiological parameters, paraspinal muscle fat infiltration (FI), and vertebral bone quality (VBQ) scores. Multiple machine learning algorithms: Random Forest (RF), Gaussian Naive Bayes (GNB), Light GBM, Support Vector Machine (SVM), XGBoost (XGB), and Logistic Regression (LR) were trained and evaluated. Model performance was compared using the receiver operating characteristic curve (ROC) and precision-recall curve (PRC). SHAP (Shapley Additive Explanations) was used to rank risk factors, while LIME (Local Interpretable Model-Agnostic Explanations) was applied to visualize MC risk in individual cases.Results:Of the 525 patients, 135 (25.7%) developed postoperative MC. Among these, 80 (59.3%) experienced proximal junction kyphosis or failure (PJK/PJF), 7 (5.2%) had distal junction kyphosis or failure (DJK/DJF), 28 (20.7%) sustained rod fractures, and 29 (21.5%) showed significant loss of correction. In the validation cohort, the RF model achieved the highest area under the curve (AUC=0.80), followed by GNB (0.77), XGB (0.76), LR (0.74), LightGBM (0.73), and SVM (0.66). The RF model also demonstrated the best PRC value (0.58), highest sensitivity (0.65), and lowest Brier score (0.20). GNB, Light GBM, and LR models achieved the highest accuracy (0.78 each), while LightGBM exhibited the highest specificity (0.93). SHAP analysis identified higher preoperative VBQ scores, larger T 1 pelvic angle (TPA), and higher paraspinal muscle FI as the main risk factors for MC. Based on the RF model, a LIME-based tool was successfully constructed for individualized MC risk estimation. Conclusion:The RF model demonstrated the best overall predictive performance for MC. A machine learning-based prediction model has the potential to provide valuable guidance for surgical decision-making in ASD patients.

Pheochromocytoma is a neuroendocrine tumor that produces catecholamines, leading to elevated blood pressure and metabolic changes in patients. It can result in serious complications affecting the heart, brain, kidneys, and blood vessels, potentially becoming a primary cause of death. Most pheochromocytoma patients present with atypical symptoms, making misdiagnosis or missed diagnosis common. This article reports a case of pheochromocytoma crisis misdiagnosed as severe viral myocarditis and includes a review of the relevant literature.

Objective To initially explore the possibility of applying the fluorescence micro-optical sectioning tomography(fMOST)high-resolution 3D reconstruction system to the morphological study of the intestinal nervous system and to preliminarily establish a method for studying the morphology of the intestinal nervous system using this system.Methods fMOST high-resolution 3D reconstruction system was used to study the intestinal nervous system of C57BL/6 mice in detail.Based on this method,a new morphological method of the visceral nervous system of small animal models was explored at the single-cell level.Results Compared with the large intestine,the small intestine lacked the typical myenteric plexus(Auerbach),deep mucosal plexus(Henley),and submucosal superficial plexus(Meissner).Conclusion The result of this paper provide a clearer and systematic display of the anatomical structure of the enteric nervous system in C57BL/6 mice,and further clarify the similarities and differences between the enteric nervous system of mice and human,and provide a theoretical basis for its rational application in the study of digestive system diseases.The morphological study of fMOST high-resolution 3D reconstruction system is not limited to the central nervous system,but can be extended to the morphological study of multiple visceral nervous systems.

Background:To compare the efficacy and safety of monthly administrations of gonadotropin releasing hormone (GnRH) agonists LY01005 and Zoladex ? in Chinese patients with premenopausal breast cancer. Methods:From October 2020 to November 2021, 188 premenopausal breast cancer patients were enrolled in 34 hospitals and randomized 1:1 to receive either LY01005 or Zoladex ? every 28 days for a total of three injections. All patients concomitantly received oral tamoxifen (TAM). The primary efficacy endpoint was cumulative probability of maintaining menopausal level [oestradiol (E2) ≤30 pg/ml] from day 29 to day 85. The second efficacy endpoint included changes in E2, luteinizing hormone (LH), and follicle-stimulating hormone (FSH) compared with the baseline. Pharmacokinetics (PK), pharmacodynamics (PD), and safety were analyzed. The study also evaluated the pharmacokinetic and pharmacodynamic characteristics of LY01005. Results:A total of 188 patients were randomised and 187 patients received either LY01005 or Zoladex ?. Cumulative probabilities of maintaining menopausal level (E2≤30 pg/ml) from day 29 to day 85 were 93.1% for LY01005 and 86.3% for Zoladex ?. The between-group difference was 6.8% (95% CI: -2.3%, 15.9%) and primary efficacy in the LY01005 group was not inferior to that in the Zoladex ? group. Changes in E2, LH, and FSH levels compared with the baseline were equivalent between the two groups (E2: 89.34% to 90.23% vs. 82.11% to 85.02%; LH: 88.89% to 95.52% vs. 89.70% to 97.02%; FSH: 75.36% to 80.85% vs.73.07% to 80.24%, respectively). After three consecutive doses of LY01005, the LH and FSH levels of the subjects showed a transient increase after the first dose, reached a peak on the second day and then started to decrease. The LH and FSH reached a lower level and remained at or below that level until the 85th day. Both treatments were well-tolerated. Conclusion:LY01005 is as effective as Zoladex ? in suppressing E2 to menopausal levels in Chinese patients with premenopausal breast cancer, with a similar safety profile.

Objective:To evaluate the efficacy and safety of nebulized inhalation of recombinant human interferon (IFN) α1b injection in the treatment of respiratory syncytial virus (RSV) associated lower respiratory tract infections (pneumonia and bronchiolitis) in children.Methods:A randomized, double-blind, parallel, placebo-controlled add-on design was used.Children with pneumonia or bronchiolitis aged 2 months to 5 years who tested positive for RSV antigen within 72 hours of onset from 30 clinical trial sites including Beijing Children′s Hospital, Capital Medical University between February 2021 and December 2022 were included in this study and randomly divided into 2 groups at a ratio of 1∶1 based on a stratified-block method.Both groups received basic treatments such as cough control, asthma relieving, expectorant treatment, fever reduction, oxygen therapy, etc.The experimental group received additional nebulized inhalation of IFN α1b injection at a dose of 2.0 μg/(kg·time), twice a day.The control group received nebulized inhalation of placebo twice a day.Clinical efficacy was evaluated based on indicators such as the duration of clinical symptoms and signs, and the Kaplan-Meier method was used to calculate the median and 95% CI of the duration of clinical symptoms and signs.The Log-rank test was used to compared data between groups.Safety was assessed through the incidence of adverse reactions and laboratory tests, and the Chi-square test was used to analyze the difference between groups. Results:There were 123 children in the experimental group and 122 children in the control group.The median durations of all the 5 clinical symptoms and signs [including shortness of breath, wheezing, dyspnea (visible retractions), decreased transcutaneous oxygen saturation, and abnormal mental state] in the experimental group after treatment were slightly shortened than those in the control group [2.7 d(95% CI: 1.9-3.0 d)] vs.[2.9 d(95% CI: 2.6-3.6 d), P=0.027].The improvement in dyspnea (retractions) was especially pronounced in the experimental group, with a relief rate of 50.0% (0, 100%) on the first day of administration[compared with 0 (0, 50.0%) in the control group ( Z=2.002, P=0.025)].The median duration of dyspnea in the experimental group was nearly 1 day shorter than that in the control group [1.0 d(95% CI: 0.7-1.7 d) vs.1.8 d(95% CI: 1.0-2.5 d), P=0.046].There were no significant difference in hospital stay [6.0(5.0, 8.0) d vs.6.5(5.0, 8.0) d, Z=0.675, P=0.500], oxygen therapy duration [32.0(14.0, 96.3) h vs.39.0 (24.0, 83.2) h, Z=0.094, P=0.925], the recovery rate from clinical symptoms during treatment [(105/106, 99.1%) vs.(96/101, 95.0%)], and recurrence rate [(0/106, 0) vs.(2/101, 2.0%)] between the 2 groups (all P>0.05).However, the above-mentioned four indicators in the experimental group showed a trend of clinical benefits.The quantitative virus detection results showed that the RSV viral load in both groups decreased after treatment compared to before treatment.After 2 days of treatment, the decline rate of RSV viral load from the baseline was 0.90 lg copies/(mL·d) in the experimental group and 0.25 lg copies/(mL·d)in the control group, with a statistically significant difference ( P<0.05).Furthermore, there was no statistically significant difference in the incidence of adverse reactions between the 2 groups ( P>0.05).Importantly, no drug-related serious adverse reactions occurred in both groups. Conclusions:The nebulized inhalation therapy of IFN α1b demonstrates efficacy and safety in treating pediatric RSV associated lower respiratory tract infections.It particularly offers outstanding clinical therapeutic value for severe children.

With the widespread adoption of low-dose CT screening and the extensive application of high-resolution CT, the detection rate of sub-centimeter lung nodules has significantly increased. How to scientifically manage these nodules while avoiding overtreatment and diagnostic delays has become an important clinical issue. Among them, lung nodules with a consolidation tumor ratio less than 0.25, dominated by ground-glass shadows, are particularly worthy of attention. The therapeutic challenge for this group is how to achieve precise and complete resection of nodules during surgery while maximizing the preservation of the patient's lung function. The "watershed topography map" is a new technology based on big data and artificial intelligence algorithms. This method uses Dicom data from conventional dose CT scans, combined with microscopic (22-24 levels) capillary network anatomical watershed features, to generate high-precision simulated natural segmentation planes of lung sub-segments through specific textures and forms. This technology forms fluorescent watershed boundaries on the lung surface, which highly fit the actual lung anatomical structure. By analyzing the adjacent relationship between the nodule and the watershed boundary, real-time, visually accurate positioning of the nodule can be achieved. This innovative technology provides a new solution for the intraoperative positioning and resection of lung nodules. This consensus was led by four major domestic societies, jointly with expert teams in related fields, oriented to clinical practical needs, referring to domestic and foreign guidelines and consensus, and finally formed after multiple rounds of consultation, discussion, and voting. The main content covers the theoretical basis of the "watershed topography map" technology, indications, operation procedures, surgical planning details, and postoperative evaluation standards, aiming to provide scientific guidance and exploration directions for clinical peers who are currently or plan to carry out lung nodule resection using the fluorescent microscope watershed analysis method.