Direct cell-to-cell transfer in stressed tumor microenvironment aggravates tumorigenic or metastatic potential in pancreatic cancer.

Pancreatic cancer exhibits a characteristic tumor microenvironment (TME) due to enhanced fibrosis and hypoxia and is particularly resistant to conventional chemotherapy. However, the molecular mechanisms underlying TME-associated treatment resistance in pancreatic cancer are not fully understood. Here, we developed an in vitro TME mimic system comprising pancreatic cancer cells, fibroblasts and immune cells, and a stress condition, including hypoxia and gemcitabine. Cells with high viability under stress showed evidence of increased direct cell-to-cell transfer of biomolecules. The resulting derivative cells (CD4

A Unified Approach for Comprehensive Analysis of Various Spectral and Tissue Doppler Echocardiography

Doppler echocardiography offers critical insights into cardiac function and phases by quantifying blood flow velocities and evaluating myocardial motion. However, previous methods for automating Doppler analysis, ranging from initial signal processing techniques to advanced deep learning approaches, have been constrained by their reliance on electrocardiogram (ECG) data and their inability to process Doppler views collectively. We introduce a novel unified framework using a convolutional neural network for comprehensive analysis of spectral and tissue Doppler echocardiography images that combines automatic measurements and end-diastole (ED) detection into a singular method. The network automatically recognizes key features across various Doppler views, with novel Doppler shape embedding and anti-aliasing modules enhancing interpretation and ensuring consistent analysis. Empirical results indicate a consistent outperformance in performance metrics, including dice similarity coefficients (DSC) and intersection over union (IoU). The proposed framework demonstrates strong agreement with clinicians in Doppler automatic measurements and competitive performance in ED detection

Self supervised convolutional kernel based handcrafted feature harmonization: Enhanced left ventricle hypertension disease phenotyping on echocardiography

Radiomics, a medical imaging technique, extracts quantitative handcrafted features from images to predict diseases. Harmonization in those features ensures consistent feature extraction across various imaging devices and protocols. Methods for harmonization include standardized imaging protocols, statistical adjustments, and evaluating feature robustness. Myocardial diseases such as Left Ventricular Hypertrophy (LVH) and Hypertensive Heart Disease (HHD) are diagnosed via echocardiography, but variable imaging settings pose challenges. Harmonization techniques are crucial for applying handcrafted features in disease diagnosis in such scenario. Self-supervised learning (SSL) enhances data understanding within limited datasets and adapts to diverse data settings. ConvNeXt-V2 integrates convolutional layers into SSL, displaying superior performance in various tasks. This study focuses on convolutional filters within SSL, using them as preprocessing to convert images into feature maps for handcrafted feature harmonization. Our proposed method excelled in harmonization evaluation and exhibited superior LVH classification performance compared to existing methods.Comment: 11 pages, 7 figure

Study on the Applicability of Dynamic Factor Standards by Comparison of Spring Constant Based Dynamic Factor of Ballasted and Concrete Track Structures

Dynamic factor evaluation method calculation methods outlined by Eisenmann (DAFEisenmann) and the American Railway Engineering Association (DAFArea) are used to calculate the dynamic factor during design and for trackside measurement, respectively, in nations where the construction of concrete track structures is relatively new. In this situation, dynamic factor calculation methods may be incorrect, and this is demonstrated by comparison of the respective track types’ total spring constant. A finite element analysis of a standard design railway track is conducted, and the design total spring constant (TSC, or K) obtained from the time history function analysis is compared to the TSC of existing tracks through trackside measurement results. The comparison result shows that TSC obtained by finite element analysis result is 22% higher than that of the trackside measurement value, indicating that the TSC is conservative in the current track design. Considering the proportional relationship between TSC and dynamic factor, it is estimated that the dynamic factor currently being applied in track design is also conservative. Based on these findings, an assessment of the applicability of different dynamic factors (DAFEisenmann and DAFArea), theoretical calculation and field measurement (DAFField) using the probabilistic analysis of wheel loads from the field measurement data is conducted. A correlative analysis between DAFEisenmann and DAFArea shows that DAFEisenmann and DAFArea were estimated to be higher by 33% and 27% in ballasted track and by 39% and 30% in concrete track than the dynamic factor derived from field measurement, respectively, which indicates that the dynamic factor currently in use can potentially lead to over-estimation in track design and maintenance

Numerical analysis on the formation of P-orientation near coarse precipitates in FCC crystals during recrystallization

Particles or precipitates in physical metallurgy are important microstructural components which control mechanical properties and phase transformation behaviors such as the recrystallization, grain growth and anisotropy of metallic materials. In particular, particle stimulated nucleation followed by an oriented growth of P-oriented grains is a commonly accepted premise, and many industrial grade cold rolled Al alloys exhibit strong P-texture after annealing. Accordingly, substantial efforts have been invested in texture and engineering studies to explore exactly how particle stimulated nucleation leads to the formation of P-oriented grains after annealing in cold-rolled Al alloys. Despite extensive experimental observations on the formation of P-oriented grains, the theoretical grounds for the formation of P-oriented grains is not yet fully established. In this work, we employ crystal plasticity theory and strain energy release maximization theory to uncover the nucleation mechanism of P-orientations near a coarse precipitate of a plane strain compressed Al alloy. The strain energy release maximization theory used in this work demonstrates that the nucleation of P-orientation is primarily possible due to stable P-orientations and near P-orientations formed during plane strain compression, which act as nuclei that recrystallize into P-orientations. ? 2017 Acta Materialia Inc.113sciescopu

Driving Pathfinding of Unmanned Autonomous Ground Vehicle using Measurement Data Diffusion

The state of road changes quite often due to the automobiles and pedestrians when the main driving unit controls the unmanned autonomous vehicle along the planned path. The vehicle acknowledges of whether there are obstacles on the driving path using a sensor array and creates the new driving path and adaptively updates route to control the vehicle. This research proposes a novel way to find the possible driving path by diffusing the measurement data collected by the sensor array which contains the unscaled info of the detected obstacles. With the possible driving field, we can recognize whether the current path would be affected by the obstacles, and also possibly create a new driving path to avoid them. Using the driving map created by this way, we made a new driving path applying A* algorithm and tested on a unmanned autonomous vehicle (i.e., converted KIA Soul). As a result, after creating the new driving path, we were able to carry out the avoidance driving safely at low speed, also the vehicle drives swiftly and smoothly when we modified the avoidance path within the possible driving field

Study on the Applicability of Dynamic Stability Evaluation Criteria by Comparison of Trackside Measurement Results of Different Track Structures

Countries such as Korea adopt design codes, evaluation criteria and specifications from standards originating abroad; this leads to a lack of distinction of the separate applications of dynamic stability evaluation parameters between various track structures of different track moduli. This paper discusses the applicability of the dynamic stability evaluation method of railway track structures by assessing 10 different types of railway track sections of a newly constructed railway operation line (5 ballasted and 5 concrete type track structures) by field instrumentation testing. Parameters of track support stiffness (TSS), wheel load fluctuation, derailment coefficient, and rail displacement are measured. The respective results are first compared to the standard criteria (design specification) and comparisons between the different track types are presented as ratios. Findings show that while all of the tracks satisfy the design specification requirements, each track type measurement result varies by a noticeable degree, particularly when comparing between concrete and ballast type track structures. Results of the study demonstrate that using the same dynamic stability evaluation criteria can lead to an incorrect assessment of the track performance evaluation of track structure, and a separate evaluation parameter for ballasted and concrete track structures is required

Persistent Continental Shelf Carbon Sink at the Ieodo Ocean Research Station in the Northern East China Sea

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Persistent Continental Shelf Carbon Sink at the Ieodo Ocean Research Station in the Northern East China Sea

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