Which SDM Model, CLIMEX vs. MaxEnt, Best Forecasts Aeolesthes sarta Distribution at a Global Scale under Climate Change Scenarios?

A precise evaluation of the risk of establishing insect pests is essential for national plant protection organizations. This accuracy is crucial in negotiating international trade agreements for forestry-related commodities, which have the potential to carry pests and lead to unintended introductions in the importing countries. In our study, we employed both mechanistic and correlative niche models to assess and map the global patterns of potential establishment for Aeolesthes sarta under current and future climates. This insect is a significant pest affecting tree species of the genus Populus, Salix, Acer, Malus, Juglans, and other hardwood trees. Notably, it is also categorized as a quarantine pest in countries where it is not currently present. The mechanistic model, CLIMEX, was calibrated using species-specific physiological tolerance thresholds, providing a detailed understanding of the environmental factors influencing the species. In contrast, the correlative model, maximum entropy (MaxEnt), utilized species occurrences and spatial climatic data, offering insights into the species' distribution based on observed data and environmental conditions. The projected potential distribution from CLIMEX and MaxEnt models aligns well with the currently known distribution of A. sarta. CLIMEX predicts a broader global distribution than MaxEnt, indicating that most central and southern hemispheres are suitable for its distribution, excluding the extreme northern hemisphere, central African countries, and the northern part of Australia. Both models accurately predict the known distribution of A. sarta in the Asian continent, and their projections suggest a slight overall increase in the global distribution range of A. sarta with future changes in climate temperature, majorly concentrating in the central and northern hemispheres. Furthermore, the models anticipate suitable conditions in Europe and North America, where A. sarta currently does not occur but where its preferred host species, Populus alba, is present. The main environmental variables associated with the distribution of A. sarta at a global level were the average annual temperature and precipitation rate. The predictive models developed in this study offer insights into the global risk of A. sarta establishment and can be valuable for monitoring potential pest introductions in different countries. Additionally, policymakers and trade negotiators can utilize these models to make science-based decisions regarding pest management and international trade agreements.

The Role of ICP Monitoring in Minimally Invasive Surgery for the Management of Intracerebral Hemorrhage.

Intracerebral hemorrhage (ICH) is the second major stroke type, with high incidence, high disability rate, and high mortality. At present, there is no effective and reliable treatment for ICH. As a result, most patients have a poor prognosis. Minimally invasive surgery (MIS) is the fastest treatment method to remove hematoma, which is characterized by less trauma and easy operation. Some studies have confirmed the safety of MIS, but there are still no reports showing that it can significantly improve the functional outcome of ICH patients. Intracranial pressure (ICP) monitoring is considered to be an important part of successful treatment in traumatic brain diseases. By monitoring ICP in real time, keeping stable ICP could help patients with craniocerebral injury get a good prognosis. In the course of MIS treatment of ICH patients, keeping ICP stable may also promote patient recovery. In this review, we will take ICP monitoring as the starting point for an in-depth discussion.

Surgical Robotics for Intracerebral Hemorrhage Treatment: State of the Art and Future Directions.

Intracerebral hemorrhage (ICH) is a stroke subtype with high mortality and disability, and there are no proven medical treatments that can improve the functional outcome of ICH patients. Robot-assisted neurosurgery is a significant advancement in the development of minimally invasive surgery for ICH. This review encompasses the latest advances and future directions of surgical robots for ICH. First, three robotic systems for neurosurgery applied to ICH are illustrated. Second, the key technologies of robot-assisted surgery for ICH are introduced in aspects of stereotactic technique and navigation, the puncture instrument, and hematoma evacuation. Finally, the limitations of current surgical robots are summarized, and the possible development direction is discussed, which is named "multisensor fusion and intelligent aspiration control of minimally invasive surgical robot for ICH". It is expected that the new generation of surgical robots for ICH will facilitate quantitative, precise, individualized, standardized treatment strategies for ICH.

Integrative genomic analysis facilitates precision strategies for glioblastoma treatment.

Glioblastoma (GBM) is the most common form of malignant primary brain tumor with a dismal prognosis. Currently, the standard treatments for GBM rarely achieve satisfactory results, which means that current treatments are not individualized and precise enough. In this study, a multiomics-based GBM classification was established and three subclasses (GPA, GPB, and GPC) were identified, which have different molecular features both in bulk samples and at single-cell resolution. A robust GBM poor prognostic signature (GPS) score model was then developed using machine learning method, manifesting an excellent ability to predict the survival of GBM. NVP-BEZ235, GDC-0980, dasatinib and XL765 were ultimately identified to have subclass-specific efficacy targeting patients with a high risk of poor prognosis. Furthermore, the GBM classification and GPS score model could be considered as potential biomarkers for immunotherapy response. In summary, an integrative genomic analysis was conducted to advance individual-based therapies in GBM.