Insertion of external ventricular drainage (EVD) is an effective neurosurgical treatment approach. The accuracy of EVD insertion is related to potential complications, and the precise placement of the catheter tip can reduce the incidence of complications. With the progress of medical technology, the research and application of EVD catheterization technology are developing rapidly. This paper reviews the traditional blind catheterization, computed tomography, ultrasound guidance, mixed reality navigation system, laser positioning neural navigation, mobile device neural navigation, stereotactic system, and the visualization technology of the whole process of neuroendoscope assisted ventricle puncture to guide EVD catheterization to provide references for clinical decision-making by medical staff.
Humans ; Drainage/methods* ; Catheterization/methods* ; Cerebral Ventricles/surgery*

The article introduces the formation process of bacterial infection and encrustation on the surface of ureteral stents, elaborates in detail on six surface modification methods for ureteral stents, namely impregnation, spraying, vapor deposition, chemical grafting, self-assembly, and electrospinning, then analyzes the advantages and limitations of each technique during application. Meanwhile, it introduces three commonly used materials for ureteral stents, namely polymers, metals, and biodegradable materials, and further explains the commonly used surface modification methods corresponding to different materials. Looking ahead, with the continuous strengthening of the multi-technology integration trend and the continuous advancement of new material research and development, it is expected that a more ideal ureteral stent can be developed.
Stents ; Ureter ; Surface Properties ; Humans

BACKGROUND:Cervical spondylosis is a chronic degenerative disease that has become one of the most common and frequent diseases threatening human health.At present,the initial diagnosis of the cervical spine and its surrounding structures mainly relies on the interpretation of medical images by radiologists,which not only requires a high level of technical requirements for operators,but also has the disadvantages of strong subjectivity,high labor intensity,and low efficiency.With the rapid development of artificial intelligence technology,its powerful data processing and image recognition capabilities have shown broad application prospects in the medical field.Deep learning has also made certain progress in the research of spinal diseases.OBJECTIVE:To summarize the current status and research progress in the application of artificial intelligence technology in cervical spine imaging images in recent years,evaluating the performance of artificial intelligence models as well as future trends and challenges to be overcome.METHODS:The first author searched the relevant articles in WanFang,CNKI,and PubMed in June 2024.The Chinese search terms were"artificial intelligence,deep learning,cervical spine."English serach terms were"artificial intelligence,Al,cervical vertebrae,cervical."Finally,101 articles were included and analyzed.RESULTS AND CONCLUSION:(1)Artificial intelligence technology can realize automatic segmentation of cervical vertebrae and measurement of curvature change by segmentation,classification,landmarks recognition of medical image parts,detect cervical vertebral fracture,nerve root,and spinal cord type cervical spondylosis,identify cervical spine ossification of posterior longitudinal ligament,and predict post-surgery related risk factors and cervical vertebra maturation classification.(2)Although artificial intelligence technology has shown great potential in the field of cervical spine research,it is still in the early stages of exploration and rapid development,with unlimited room for development and innovation.

OBJECTIVE To evaluate the clinical efficacy and safety of Jianwei xiaoshi oral liquid in the treatment of functional dyspepsia （FD） in children， and provide evidence-based basis for clinical use of the drug. METHODS Retrieved from CNKI， VIP， Wanfang， CBM， Cochrane Library and PubMed， randomized controlled trials （RCTs） about Jianwei xiaoshi oral liquid in the treatment of FD in children were collected from the inception to Apr. 2024. The control group was treated with conventional western drugs （including gastrointestinal motion-promoting， antacids or acid-suppressing drugs）， and the trial group was treated with Jianwei xiaoshi oral liquid alone or combined with conventional Western drugs （drug dosage and course of treatment were the same as the control group）. Meta-analysis was performed using RevMan 5.3 software after quality evaluation with the Cochrane risk bias assessment tool 6.1. RESULTS Totally 16 literature were employed which included 1 962 patients. The results of meta-analysis showed that the total clinical effective rate of Jianwei xiaoxi oral liquid in the treatment of FD in children of trial group was significantly higher than that of the control group [RR＝1.18， 95%CI （1.13， 1.22）， P＜0.000 01]. In this study， subgroup analysis was conducted on the usage and dosage， course of treatment， and combination or not in trial group， as well as the type of conventional Western drugs. The results showed that the total clinical effective rate of trial group was significantly higher than that of control group； the relief time of abdominal distension and abdominal pain in trial group [MD＝－2.54， 95%CI （－3.10， －1.98）]， loss of appetite relief time [MD＝－2.12， 95%CI （－2.63， －1.61）]， nausea and vomiting relief time [MD＝－1.70， 95%CI （－2.27， －1.14）]， and belching relief time [MD＝－1.61， 95%CI （－2.44， －0.78）] were shorter than that of the control group significantly （P＜0.05）. In addition， compared with control group， the levels of gastrin [SMD＝1.63， 95%CI （0.98， 2.29）] and motilin [SMD＝2.06， 95%CI （1.58， 2.54）] as well as gastric antral emptying rate [MD＝5.99， 95%CI （2.78， 9.21）] in trial group were increased significantly， while the level of somatostatin was decreased significantly [SMD＝－1.30， 95%CI （－1.57， －1.02）] （P≤0.000 3）. CONCLUSIONS Jianwei xiaoshi oral liquid， whether used alone or in combination with other medications， and regardless of the treatment course or dosage and usage， is effective in treating FD in children， with good safety.

Objective To evaluate the accuracy of dose-length product (DLP) values in CT dose reports by comparing them with the DLP values measured using a pencil-type ionization chamber. Methods Experiments were conducted using four CT scanners with different detector row numbers from two manufacturers (A and B), along with a head phantom and a pencil-type ionization chamber. Other scanning parameters were fixed, while pairwise combinations of kV and mAs were tested. The DLP values were measured under various scanning conditions using the pencil-type ionization chamber (DLP_measured) and the corresponding DLP values in CT dose reports were recorded (DLP_reported). All data were subjected to statistical analysis. Results Differences were observed between DLP_reported and DLP_measured values. The smallest mean absolute value of ΔDLP was approximately 2.526 mGy·cm observed on the 40-row CT scanner of manufacturer A. There was a difference between the ΔDLPs of the four CT scanners. Both DLP_reported and DLP_measured exhibited a linear relationship with mAs. Conclusion The percentage errors between DLP_reported and DLP_measured values for all four CT scanners were within the national standard tolerance of 15%. DLP values in CT dose reports can serve as a reference for assessing patient radiation dose during scanning. However, for radiation dose-related research, data measured using dosimetric instruments such as pencil-type ionization chamber are recommended.

BACKGROUND: The effect of the interval between previous Helicobacter pylori (H. pylori) eradication and rescue treatment on therapeutic outcomes remains unknown. The aim of this study was to investigate the association between eradication rates and treatment interval durations in H. pylori infections. METHODS: This prospective observational study was conducted from December 2021 to February 2023 at six tertiary hospitals in Shandong, China. We recruited patients who were positive for H. pylori infection and required rescue treatment. Demographic information, previous times of eradication therapy, last eradication therapy date, and history of antibiotic use data were collected. The patients were divided into four groups based on the rescue treatment interval length: Group A, ≥4 weeks and ≤3 months; Group B, >3 and ≤6 months; Group C, >6 and ≤12 months; and Group D, >12 months. The primary outcome was the eradication rate of H. pylori . Drug compliance and adverse events (AEs) were also assessed. Pearson's χ2 test or Fisher's exact test was used to compare eradication rates between groups. RESULTS: A total of 670 patients were enrolled in this study. The intention-to-treat (ITT) eradication rates were 88.3% (158/179) in Group A, 89.6% (120/134) in Group B, 89.1% (123/138) in Group C, and 87.7% (192/219) in Group D. The per-protocol (PP) eradication rates were 92.9% (156/168) in Group A, 94.5% (120/127) in Group B, 94.5% (121/128) in Group C, and 93.6% (190/203) in Group D. There was no statistically significant difference in the eradication rates between groups in either the ITT ( P = 0.949) or PP analysis ( P = 0.921). No significant differences were observed in the incidence of AEs ( P = 0.934) or drug compliance ( P = 0.849) between groups. CONCLUSION: The interval duration of rescue treatment had no significant effect on H. pylori eradication rates or the incidence of AEs. REGISTRATION ClinicalTrials.gov , NCT05173493.
Humans ; Helicobacter Infections/drug therapy* ; Helicobacter pylori/pathogenicity* ; Male ; Female ; Prospective Studies ; Middle Aged ; Anti-Bacterial Agents/adverse effects* ; Adult ; Aged ; Treatment Outcome ; Proton Pump Inhibitors/therapeutic use*

Kirsten rat sarcoma viral oncogene homolog (KRAS) protein inhibitors are a promising class of therapeutics, but research on molecules that effectively penetrate the blood-brain barrier (BBB) remains limited, which is crucial for treating central nervous system (CNS) malignancies. Although molecular generation models have recently advanced drug discovery, they often overlook the complexity of biological and chemical factors, leaving room for improvement. In this study, we present a structure-constrained molecular generation workflow designed to optimize lead compounds for both drug efficacy and drug absorption properties. Our approach utilizes a variational autoencoder (VAE) generative model integrated with reinforcement learning for multi-objective optimization. This method specifically aims to enhance BBB permeability (BBBp) while maintaining high-affinity substructures of KRAS inhibitors. To support this, we incorporate a specialized KRAS BBB predictor based on active learning and an affinity predictor employing comparative learning models. Additionally, we introduce two novel metrics, the knowledge-integrated reproduction score (KIRS) and the composite diversity score (CDS), to assess structural performance and biological relevance. Retrospective validation with KRAS inhibitors, AMG510 and MRTX849, demonstrates the framework's effectiveness in optimizing BBBp and highlights its potential for real-world drug development applications. This study provides a robust framework for accelerating the structural enhancement of lead compounds, advancing the drug development process across diverse targets.

BACKGROUND:Cervical spondylosis is a chronic degenerative disease that has become one of the most common and frequent diseases threatening human health.At present,the initial diagnosis of the cervical spine and its surrounding structures mainly relies on the interpretation of medical images by radiologists,which not only requires a high level of technical requirements for operators,but also has the disadvantages of strong subjectivity,high labor intensity,and low efficiency.With the rapid development of artificial intelligence technology,its powerful data processing and image recognition capabilities have shown broad application prospects in the medical field.Deep learning has also made certain progress in the research of spinal diseases.OBJECTIVE:To summarize the current status and research progress in the application of artificial intelligence technology in cervical spine imaging images in recent years,evaluating the performance of artificial intelligence models as well as future trends and challenges to be overcome.METHODS:The first author searched the relevant articles in WanFang,CNKI,and PubMed in June 2024.The Chinese search terms were"artificial intelligence,deep learning,cervical spine."English serach terms were"artificial intelligence,Al,cervical vertebrae,cervical."Finally,101 articles were included and analyzed.RESULTS AND CONCLUSION:(1)Artificial intelligence technology can realize automatic segmentation of cervical vertebrae and measurement of curvature change by segmentation,classification,landmarks recognition of medical image parts,detect cervical vertebral fracture,nerve root,and spinal cord type cervical spondylosis,identify cervical spine ossification of posterior longitudinal ligament,and predict post-surgery related risk factors and cervical vertebra maturation classification.(2)Although artificial intelligence technology has shown great potential in the field of cervical spine research,it is still in the early stages of exploration and rapid development,with unlimited room for development and innovation.

Collagen contains abundant cell binding motifs, which are conducive to adhesion, migration, and differentiation, maintain cell vitality and promote cell proliferation. However, pure collagen hydrogel has some shortcomings such as poor mechanical properties, poor thermal stability and fast degradation. Numerous studies have shown that the properties of collagen can be improved by combining it with natural polysaccharides such as alginate, chitosan, hyaluronic acid and cellulose. In this paper, the research status and biological application fields of four kinds of composite hydrogels, including collagen-alginate composite hydrogels, collagen-chitosan hydrogels, collagen-hyaluronic acid hydrogels and collagen-cellulose hydrogels, were summarized. The common preparation methods of four kinds of composite hydrogels were introduced, and the future development direction of collagen-based composite hydrogels was prospected.
Hydrogels/chemical synthesis* ; Collagen/chemistry* ; Polysaccharides/chemistry* ; Alginates/chemistry* ; Hyaluronic Acid/chemistry* ; Chitosan/chemistry* ; Biocompatible Materials/chemistry* ; Humans ; Tissue Engineering/methods* ; Cellulose/chemistry* ; Tissue Scaffolds