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[This corrects the article DOI: 10.3389/fmed.2026.1760287.].

Glioma is one of the most common primary malignant tumors of the central nervous system, and the prognosis is getting worse with the improvement of tumor grade. In recent years, with the in-depth study of the disease, researchers have found that microvascular mimicry seems to be the key factor of poor prognosis, but its specific mechanism has not been thoroughly studied, and the expression of microvascular mimicry in high-grade gliomas is closely related to the expression of NDRG1 gene. This research project is expected to control the occurrence and development of HGG by exploring the factors that affect the expression of NDRG1 gene. Retrospective RNA-seq data analysis was performed on Chinese Glioma Genome Atlas (CGGA) database and glioma patients from TCGA. Subsequently, 7 cases of CNSWHO3 grade patients and 36 cases of CNSWHO4 grade patients were selected based on postoperative pathological results, and clinical information of the patients was collected. Immunohistochemical staining of relevant proteins was conducted on patient tissues, and the results were recorded after double immunostaining scoring for each slide. Statistical analysis of the data was performed using relevant statistical methods. The analysis of two databases shows that NDRG1 is enriched in HGG samples. NDRG1 is an independent risk factor for overall survival (OS) in glioma patients, and plays an important role in promoting VM in glioma patients. Different protein immunohistochemistry double immunostaining scores show that the expression levels of NDRG1 and Vimentin are correlated with tumor grade in HGG patients. The expression of VM in samples is closely related to the expression level of NDRG1 (P=3.98E-04) and tumor CNSWHO grade (P=0.019). MVD in HGG patients is related to NDRG1 expression (P=0.035). The rest of the immunohistochemistry scores are not statistically significant (P>0.05). There is a trend of correlation between Vimentin expression and MVD in CNSWHO grade 4 HGG patients (P=0.07). NDRG1 exerts adverse effects on the CNSWHO grading of HGG by regulating the expression of VM and MVD in HGG patients, as well as the tumor EMT process.

The liver is perfused by both arterial and venous blood, with a resulting abnormal microenvironment selecting for more-aggressive malignancies. Hepatocellular carcinoma (HCC) is the most frequent primary liver cancer, the sixth most common cancer globally, and the third leading cause of cancer-related mortality worldwide. HCC is characterized by its hypervascularization. Improving the efficiency of anti-angiogenic treatment and mitigation of anti-angiogenic drug resistance are the top priorities in the development of non-surgical HCC therapies. Endoglin (CD105), a transmembrane glycoprotein, is one of the transforming growth factor β (TGF-β) co-receptors. Involvement of that protein in angiogenesis of solid tumours is well documented. Endoglin is a marker of activated endothelial cells (ECs), and is preferentially expressed in the angiogenic endothelium of solid tumours, including HCC. HCC is associated with changes in CD105-positive ECs within and around the tumour. The large spectrum of endoglin effects in the liver is cell-type- and HCC- stage-specific. High expression of endoglin in non-tumour tissue suggests that this microenvironment might play an especially important role in the progression of HCC. Evaluation of tissue expression, as well as serum concentrations of this glycoprotein in HCC, tends to confirm its role as an important biomarker in HCC diagnosis and prognosis. The role of endoglin in liver fibrosis and HCC progression also makes it an attractive therapeutic target. Despite these facts, the exact molecular mechanisms of endoglin functioning in hepatocarcinogenesis are still poorly understood. This review summarizes the current data concerning the role and signalling pathways of endoglin in hepatocellular carcinoma development and progression, and provides an overview of the strategies available for a specific targeting of CD105 in anti-angiogenic therapy in HCC.

Marburg virus (MARV) is a member of the filovirus family that causes hemorrhagic disease with high case fatality rates. MARV is on the priority list of the World Health Organization for countermeasure development highlighting its potential impact on global public health. We developed a vesicular stomatitis virus (VSV)-based vaccine expressing the MARV glycoprotein (VSV-MARV) and previously demonstrated uniform protection of nonhuman primates (NHPs) with a single dose. Here, we investigated the fast-acting potential of this vaccine by challenging NHPs with MARV 14, 7 or 3 days after a single dose vaccination with VSV-MARV. We found that 100% of the animals survived when vaccinated 7 or 14 days and 75% of the animal survived when vaccinated 3 days prior to lethal MARV challenge. Transcriptional analysis of whole blood samples indicated activation of B cells and antiviral defense after VSV-MARV vaccination. In the day -14 and -7 groups, limited transcriptional changes after challenge were observed with the exception of day 9 post-challenge in the day -7 group where we detected gene expression profiles indicative of a recall response. In the day -3 group, transcriptional analysis of samples from surviving NHPs revealed strong innate immune activation. In contrast, the animal that succumbed to disease in this group lacked signatures of antiviral immunity. In summary, our data demonstrate that the VSV-MARV is a fast-acting vaccine suitable for the use in emergency situations like disease outbreaks in Africa.

Marburg Virus Disease (MVD) is a life-threatening hemorrhagic fever, caused by two viruses-Marburg virus (MARV) and Ravn virus (RAVV)-that belong to the family Filoviridae. Due to its high mortality rate and the lack of licensed vaccines, MVD remains a major global health concern. In this study, a comprehensive immunoinformatics workflow was used to design a universal chimeric multi-epitope subunit vaccine targeting conserved antigenic regions of both viruses to reduce MVD-related mortality. Antigenicity analysis identified glycoproteins (GP) of MARV and RAVV as the most immunogenic viral proteins, and multiple sequence alignment revealed conserved regions suitable for epitope selection. Three highly conserved, antigenic, non-allergenic, and non-toxic CTL, HTL, and B-cell epitopes from each virus were incorporated into the final vaccine construct. The designed vaccine exhibited high antigenicity, non-allergenicity, solubility, and acceptable physicochemical properties. Structural modeling generated a high-quality 3D structure, and molecular docking revealed stable binding to human TLR4 with a docking score of − 229.46 kcal/mol, supported by multiple hydrogen bonds and non-bonded interactions, suggesting robust immune activation potential. Codon optimization produced a CAI value of 0.96 and 52.2% GC content, indicating efficient expression in E. coli K-12, further validated through in silico cloning. Immune simulations showed robust primary and secondary immune responses, including high levels of IgM, IgG, IFN-γ, IL-2, and strong memory cell formation. Molecular dynamics simulation analyses confirmed the stability (RMSD), compactness (Rg), and consistent hydrogen-bonding interactions between the designed vaccine and TLR4. Overall, the computational analyses indicate that the proposed chimeric multi-epitope vaccine is stable, highly immunogenic, and capable of eliciting protective immune responses, providing a strong basis for subsequent in vitro and in vivo validation.

The outcomes of patients with hepatocellular carcinoma (HCC) are unsatisfactory because of its high recurrence rate. The Vessels that encapsulate tumor clusters (VETC) pattern is a unique vascular structure. In this study, we investigated the clinical–pathological features of HCC patients with the VETC pattern. We retrospectively reviewed patients with HCC who underwent curative hepatectomy at Chang Gung Memorial Hospital between 2007 and 2013. The form of the VETC pattern was established using an anti-CD31 stain. The results were classified into positive (VETC+) and negative (VETC−) patterns. We investigated and compared demographic data between these two groups. Overall, 174 patients were classified into either the VETC+ or VETC− groups. The median followed-up period was 80.5 months. There were significant differences in the number of hepatitis B carriers, the occurrence of vascular invasion, tumor size, TNM staging, microvessel density, and recurrence (all p < 0.05). Regarding the prediction of disease-free survival, after COX regression multivariate analysis, VETC+ remained independently associated with recurrent episodes (p = 0.003). The intra-tumoral microvessel density, demonstrated by CD-31, was the only clinical–pathological feature independently associated with VETC+. Our study demonstrated that the VETC pattern is an independent factor of poor prognosis for DFS. Higher intra-tumoral microvessel density was significantly associated with the VETC pattern. Further studies are needed to validate our findings.

An increasing degree of digitalization in construction planning offers significant potential for building life cycle assessment (LCA) to reduce access barriers, as well as the assessment effort itself. To realize the widespread application of LCA tools and their potential to effectively minimize life cycle impacts, an open approach is required that allows for flexible application of comprehensive LCA studies and early integration in planning processes. The authors present an approach for LCA integration in all phases of digital planning which aims at a DGNB (Deutsche Gesellschaft für nachhaltiges Bauen) certification based on the open Building Information Modeling (BIM) standard Industry Foundation Classes (IFC). The approach takes into account varying levels of development and resulting data availability during integral planning phases, as well as resulting LCA application contexts. It goes beyond existing strategies and allows one to consider both BIM and LCA software through a workflow based on a single data format. The assessment framework is operationalized through standardized interface development and technical realization following the information delivery manual (IDM) process standardized for IFC interfaces. The Extensible Markup Language (XML) schema, as a specific implementation for certification, provides the target system for LCA data requirements and is generalized to a planning phase specific IDM base table. The technical realization based on respective model view definitions and distributed data suggests a pathway to the standardization of LCA-IFC integration based on an open approach. The overall approach exemplarily applies to the “LERNZENTRUM” at the Karlsruhe Institute of Technology (KIT) campus. We conclude that an open BIM approach for LCA integration in model-based planning is feasible, but requires several adjustments in IFC, LCA, and planning practice. Adding a lifecycle element to the IFC to connect BIM and LCA provides comprehensive feedback for informed decision making based on environmental impact.

Background Trigeminal neuralgia (TN) is a chronic pain syndrome more prevalent in patients with multiple sclerosis (MS), often presenting with earlier onset and more intense pain compared to non-MS patients. The management of TN in MS is complex due to the interaction between demyelination and neurovascular factors. Methods A retrospective analysis of 35 MS patients treated for TN with 65 procedures between 2010 and 2023 was conducted. Patients underwent surgical treatments guided by a flowchart and based on the presence of NVC and patient risk factors. Procedures included MVD, PBC, SRS and TRZ. Outcomes were assessed using BNI pain and hypoesthesia scales, focusing on pain recurrence and changes in antineuralgic medication. Results After first treatment, MVD (13 procedures) achieved a 100% success rate with a mean pain-free interval of 59.4 months, and 77% of patients reduced or stopped medication. PBC (16) had a 93.8% success rate and a recurrence time of 34 months. SRS showed an 80% success rate with a recurrence time of 7.4 months, while TRZ had a 50% success rate with 24 months of pain-free duration. After the first surgical intervention, 30.5% of patients were pain-free, increasing to 40% after the third treatment. At last follow-up (77,0 ± 68.7 months) it was demonstrated high pain-free rates (61.1%) and good long-term pain control. Conclusion The use of a tailored flowchart significantly improves outcomes in TN-MS patients. MVD provides the longest pain-free intervals when NVC is present, while PBC, SRS, and TRZ remain viable alternatives for those with contraindications. Personalized approaches enhance pain control and reduce recurrence.

Cultural heritage building information models (HBIMs) incorporate specific geometric and semantic data that are mandatory for supporting the workflows and decision making during a heritage study. The Industry Foundation Classes (IFC) open data exchange standard can be used to migrate these data between different software solutions as an openBIM approach, and has the potential to mitigate data loss. Specific data-exchange scenarios can be supported by firstly developing an Information Delivery Manual (IDM) and subsequently filtering portions of the IFC schema and producing a specialized Model View Definition (MVD). This paper showcases the creation of a specialized IDM for the heritage domain in consultation with experts in the restoration and preservation of built heritage. The IDM was then translated into a pilot MVD for heritage. We tested our developments on an HBIM case study, where a historic building was semantically enriched with information about the case study’s conservation plan and then checked against the specified IDM requirements using the developed MVD. We concluded that the creation of an IDM and then the MVD for the heritage domain are achievable and will bring us one step closer to BIM standardisation in the field of digitised cultural buildings.

The Marburg virus (MARV), responsible for severe hemorrhagic fevers with mortality rates as high as 90%, remains a significant public health threat. This study employs machine learning to identify inhibitors targeting the MARV Gene 4 Small ORF protein, crucial for the virus’s replication and immune evasion. The Gene 4 Small ORF protein is pivotal in taking over the host’s cellular mechanisms, facilitating unchecked viral replication and significant immune system disruption. Effective targeting of this protein holds promise for mitigating the viral lifecycle and entry, potentially curbing the severity of the disease outbreaks. A dataset from PubChem, including 301,745 compounds, was utilized to train models like Random Forest (RF), Gradient Boosting Machines (GBM), CatBoost (CB), AdaBoost (AB), and Logistic Regression (LR). The activity outcomes were classified with integers active as 1 and inactive as 0, followed by molecular descriptor generation using RDKit and PaDEL. The models were trained on an 80:20 split and validated on a novel dataset to ensure robustness, with performance metrics such as accuracy and AUC-ROC guiding evaluation. Morgan fingerprints outperformed PubChem fingerprints, achieving higher accuracy (76%), precision (80%), and ROC-AUC (84%). Among the machine learning models evaluated, RF and GBM were the best performers, with RF achieving the highest specificity (83%) and ROC-AUC (0.84). Validation on new datasets further confirmed the effectiveness of these models, with RF and GBM demonstrating strong predictive reliability for identifying potential inhibitors of the Marburg virus. A Web Application known as MARVpred was developed to predict the activity of compounds with anti-MARV properties from the ChEMBL database. MARVpred is freely accessible online (https://igmr.org/software/marvpred). This study signifies a critical step forward in the computational prediction of viral inhibitors, offering a valuable tool for accelerating the development of Marburg virus therapeutics.