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Comparative analysis of indocyanine green dosages for optimal fluorescence imaging in laparoscopic cholecystectomy
A microengineered 3D human neurovascular unit model to probe the neuropathogenesis of herpes simplex encephalitis
Association of phosphorylation status of ERK and genetic MAPK alterations in pediatric tumors
Abstract The mitogen-activated protein kinase (MAPK) pathway is one of the most frequently altered pathways in pediatric cancer. Activating genomic MAPK-alterations and phosphorylation of the MAPK downstream target ERK (pERK) were analyzed in the PTT2.0 registry to identify potential targets for MAPK-directed treatment in relapsed pediatric CNS tumors, sarcomas and other solid tumors. The present study investigates the association of ERK phosphorylation and genomic MAPK pathway alterations (mutations, fusions, amplifications) in the PTT2.0 dataset. PTT2.0 registry cases with available genomic and immunohistochemistry data (n = 235) were included. Samples with and without detected activating genomic MAPK alterations were compared regarding ERK phosphorylation, quantified by immunohistochemistry H-score. The association of pERK intensity and the presence of MAPK alteration was analyzed using a univariable binary logistic regression model.The mean pERK H-score was significantly higher in samples with activating genomic MAPK alterations. pERK H-score positively correlated with the presence of MAPK alterations. However, the pERK H-score predicted MAPK alterations only with a sensitivity of 58.3% and a specificity of 83.8%. The highest mean pERK H-scores were observed in low-grade gliomas, enriched for MAPK alterations, and in ependymoma, where MAPK alterations were absent. Although there is an association between pERK level and activating genetic MAPK alterations, the predictive power of pERK H-score for genetic MAPK alterations is low in pediatric tumors. Tumors/groups with absent genetic MAPK alterations but high pERK indicate a dissociation of the two parameters, as well as a possible MAPK pathway activation in the absence of genetic MAPK alterations.
Optimization of process parameter for green die sinking electrical discharge machining: a novel hybrid decision-making approach
Abstract Electrical discharge machining (EDM) generates toxic emissions and hazardous waste, posing significant health risks for operators and environmental concerns. Aligning with the UN Sustainable Development Goals (SDGs) for Good Health & Well-being (SDG 3) and Responsible Consumption & Production (SDG 12), it is crucial to optimize EDM to reduce its environmental impact. This study introduces a Decision Support System (DSS) that uses a new approach to prospect theory based on exponential-logarithmic single-valued neutrosophic sets (± Log-SVNS) to find the best EDM parameters for “green” die-sinking EDM. Taguchi orthogonal array has been used to design the EDM experiments considering different levels of following process parameters: peak current, pulse duration, dielectric level, and flushing pressure. Log-SVNS structures expert evaluations on output responses which includes process time, tool wear ratio, energy consumption, aerosol concentration, and dielectric usage, and aggregates them with hybrid averaging and geometric operators. The proposed method employs prospect theory to finally determine the optimal machining parameters. The best performance is seen when the peak current is 2 A, the pulse duration is 520 µs, the dielectric level is 80 mm, and the flushing pressure is 0.5 kg/cm². This outcome is based on the µLog-SVNS hybrid average TODIM (TOmada de Decisao Interativa Multicriterio) method. The hybrid geometric TODIM method finds that experiment number 3 is the best and the parameters are as follows: peak current of 2 A, pulse duration of 261 µs, dielectric level of 60 mm, and flushing pressure of 0.7 kg/cm². Sensitivity analysis confirms the robustness of these results, and comparative analysis with existing methods demonstrates the effectiveness of the proposed method in establishing optimal parameters.
Longitudinal relationship between atherosclerosis and progression of periodontitis in community-dwelling people in Nagasaki Islands Study
A new method for Phytophthora cactorum culturing using host plant materials to prepare agar medium
Immunostimulatory effects mechanism of polysaccharide extracted from Acanthopanax senticosus on RAW 264.7 cells through activating the TLR/MAPK/NF-κB signaling pathway
Disparities in the impact of drought on agriculture across countries
Abstract Over the last several decades, droughts driven by climate change have damaged agricultural production as the planet warms. It is crucial for the future of the global food supply to develop effective adaptation strategies. However, not all countries and regions are affected equally by drought. We fit a hierarchical Bayesian model with a dataset containing 60 years of country-level drought and agricultural productivity data to probabilistically identify the susceptibility of various countries and regions to drought. We find that regions such as Eastern Africa and Southern Asia are highly susceptible to drought, with each region exhibiting a >90% chance that drought has negatively affected agriculture, leading to estimated historical agricultural losses of >14%, while Eastern Asia is the most drought-resilient region, with only a 44% probability that drought has negatively affected agriculture in this region. The results of this study can help inform the allocation of future resources to enhance agricultural resilience in the most vulnerable regions. Additionally, they provide a foundation for case studies examining specific countries or regions that demonstrate notable resilience or susceptibility to drought.