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Open in new tab Download slide OBJECTIVES This study aimed to assess the effectiveness of three-dimensional printing (3DP) in patients with complex hypertrophic cardiomyopathy requiring combined transaortic and transapical septal myectomy. METHODS We created 3DP models for 7 patients undergoing this surgery approach between June and October 2022 using silicone-like resin and conducted mock operations. The models were compared with echocardiography to identify abnormal muscle bundles and heart structures. These patients were then compared with a 1:2 matched group without 3DP, considering age, sex and additional operations. RESULTS The models mostly presenting with midventricular obstruction showed high consistency with original computed tomography data (r  = 0.978, P  <   0.001). 3DP identified more abnormal muscle bundles than echocardiography, primarily between the interventricular septum and apex. Excised specimens in mock operations mirrored those in actual myectomies. While cardiopulmonary bypass time was not significantly different, a near-20-min decrease was observed in the 3DP group (135.5 ± 31.1 vs 154.4 ± 36.6 min, P  =   0.054). CONCLUSIONS While no significant differences in surgical outcomes were observed, 3DP appeared to enhance the visualization and understanding of spatial structures (average Likert scale score 4.0), potentially contributing to surgical proficiency (overall rating score 3.9). The use of 3DP may offer additional value in the preparation and execution of operations for complex hypertrophic cardiomyopathy cases. [ABSTRACT FROM AUTHOR]

Soil salinization can decrease soil productivity and is a significant factor in causing land degradation. Precision mapping of salinization in agricultural fields would improve farmland management. This study focuses on the cropland in the Manas River Basin, located in the arid region of northwest China. It explores the potential of a soil mapping method, the Soil–Land Inference Model (SoLIM), which only requires a small number of soil samples to infer soil salinization of farmlands in arid areas. The model was utilized to create spatial distribution maps of soil salinity for the years 2009 and 2017, and changes in the distribution were analyzed. The research results indicate: (1) Through the analysis of sample point data, it was observed that soil salinity in the study area tends to accumulate in the surface layer (0–30 cm) in spring and in the subsoil layer (60–90 cm) during the crop growing season, with significant spatial variability. Therefore, it is necessary to conduct detailed salinity mapping. (2) Using field measurements as validation data, the simulation results of the SoLIM were compared with spatial interpolation methods and regression models. The SoLIM showed higher inference accuracy, with R2 values for the simulation results of the three soil layers all exceeding 0.5. (3) The SoLIM spatial inference showed salt accumulation in the northern part and desalination in the southern part. The findings of this study suggest that the SoLIM has the potential to effectively map soil salinization of croplands in arid areas, offering an efficient solution for monitoring soil salinity in arid oasis croplands. [ABSTRACT FROM AUTHOR]