Background-oriented Schlieren tomography using gated recurrent unit.

Current Background-oriented schlieren tomography (BOST) methods rely primarily on iterative algorithms for reconstruction. Before reconstruction, a weight projection matrix was generated by performing 3D ray tracing using the projection relationship between the cameras, depending on the camera calibration parameters and large weight projection matrix which introduce artifacts and greatly reduce computational efficiency in the reconstruction. Considering that CT reconstruction uses spatial projection sequences from multiple directions, this study draws inspiration from the Recurrent Neural network(RNN) and utilizes spatial correlation between adjacent projection data to propose a background-oriented schlieren reconstruction method based on a gated recurrent unit (GRU) neural network. First, the model architecture is designed and implemented. Subsequently, numerical simulations were conducted using a methane combustion model to evaluate the proposed method, which achieved an average mean relative error (MRE) of 0.23%. Finally, reconstruction experiments were performed on the actual flow-field data above a candle flame, with a reprojection correlation coefficient of 89% and an average reconstruction time of only 1.04 s per frame. The results demonstrate that the proposed method outperforms traditional iterative reconstruction methods in terms of reconstruction speed and accuracy. This provides a feasible solution for the real-time reconstruction of three-dimensional instantaneous flow fields.

A good preoperative immune prognostic index is precits a better prognosis for locally advanced rectal cancer patients with ypTNM stage II who underwent radical resection after neoadjuvant chemoradiotherapy.

BACKGROUND: No studies have investigated the role of IPI in assessing the prognosis of locally advanced rectal cancer (LARC) patients undergoing nCRT. OBJECTIVE: We attempted to combine neutrophil-to-lymphocyte ratio (NLR) and serum lactate dehydrogenase (sLDH) to generate a new rectal immune prognostic index (RIPI) to explore whether RIPI is associated with LARC prognosis. We aimed to identify whether there is a population that might benefit from RIPI in LARC. METHODS: LARC patients who underwent radical surgery after Neoadjuvant chemoradiotherapy (nCRT) were enrolled between February 2012 and May 2017. Based on the best cut-off points of NLR and sLDH, we developed RIPI. The patients were grouped as follows: (1) good, RIPI = 0, good, 0 factors; (2) poor, RIPI = 1, 1 or 2 factors. RESULTS: This study enrolled 642 patients. In yp TNM stage II patients, 5-year disease-free survival (DFS) differed significantly between the RIPI = 1 and RIPI = 0 groups (p = 0.03). Five-year DFS did not differ significantly between IPI = 0 and IPI = 1 groups in ypCR, stage I, stage II, and stage III. In multivariate analysis, the significant factor predicting DFS was pre-nCRT RIPI score (p = 0.035). CONCLUSION: The pre-nCRT RIPI was closely related to the prognosis of LARC patients undergoing nCRT. Particularly, RIPI is significant in evaluating the prognosis of ypTNM stage II LARC patients who underwent radical resection after nCRT.

Displacement extraction of background-oriented schlieren images using Swin Transformer.

Displacement extraction of background-oriented schlieren (BOS) is an essential step in BOS reconstruction, which directly determines the accuracy of the results. Typically, the displacement is calculated from the background images with and without inhomogeneous flow using the cross-correlation (CC) or optical flow (OF) method. This paper discusses the disadvantages of the CC and OF methods, and an end-to-end deep neural network was designed to estimate the BOS displacement. The proposed network is based on a Swin Transformer, which can build long-range correlations. A synthetic dataset used for training was generated using the simulated flow field by computational fluid dynamics. After training, the displacement can be obtained using the BOS image pair without additional parameters. Finally, the effectiveness of the proposed network was verified through experiments. The experiments illustrate that the proposed method performs stably on synthetic and real experimental images and outperforms conventional CC or OF methods and classic convolutional neural networks for OF tasks.

Direct background-oriented schlieren tomography using radial basis functions.

Background-oriented schlieren tomography (BOST) is effective for flow field measurement; however, different from general computed tomography (CT), the BOST utilizes the deflection of rays passing through an inhomogeneous field for measurement. It is sensitive to the refractive index gradient. Therefore, an additional integration step is typically employed to obtain the refractive index. In this article, a calculation method of projection matrix is proposed based on the radial basis function (RBF). The 3D distribution of the refractive index can be reconstructed directly. This method was first verified by numerical simulation. Then, the 3D instantaneous refractive index field above a candle flame was measured. The reprojection error was calculated by ray tracing. The results illustrate the accuracy and stability of the proposed method. This research provides a new and complete solution for the 3D instantaneous flow field (refractive index, density, or temperature) measurement.

Delineation of colorectal cancer ligand-receptor interactions and their roles in the tumor microenvironment and prognosis.

BACKGROUND: Immunotherapies targeting ligand-receptor interactions (LRIs) are advancing rapidly in the treatment of colorectal cancer (CRC), and LRIs also affect many aspects of CRC development. However, the pattern of LRIs in CRC and their effect on tumor microenvironment and clinical value are still unclear. METHODS: We delineated the pattern of LRIs in 55,539 single-cell RNA sequencing (scRNA-seq) samples from 29 patients with CRC and three bulk RNA-seq datasets containing data from 1411 CRC patients. Then the influence of tumor microenvironment, immunotherapy and prognosis of CRC patients were comprehensively investigated. RESULTS: We calculated the strength of 1893 ligand-receptor pairs between 25 cell types to reconstruct the spatial structure of CRC. We identified tumor subtypes based on LRIs, revealed the relationship between the subtypes and immunotherapy efficacy and explored the ligand-receptor pairs and specific targets affecting the abundance of tumor-infiltrating lymphocytes. Finally, a prognostic model based on ligand-receptor pairs was constructed and validated. CONCLUSION: Overall, through the comprehensive and in-depth investigation of the existing ligand-receptor pairs, this study provides new ideas for CRC subtype classification, a new risk screening tool for CRC patients, and potential ligand-receptor pair targets and pathways for CRC therapy.

Flexible multicamera calibration method with a rotating calibration plate.

Camera calibration is necessary for accurate image measurements, particularly in multicamera systems. The calibration process involves corresponding the coordinates of 3D calibration points with a 2D image and requires the establishment of a reliable 3D world coordinate system. This paper presents a convenient multicamera calibration method that uses a rotating calibration plate and multi-view stereo vision to calculate 3D points and their relationship with the image coordinates. Despite simple implementation, the rotation of the calibration plate presents numerous calibration points from various planes, increasing the stability of the solution and the noise reduction. The relocation accuracy and reprojection error are experimentally verified.

Conditional survival nomogram for patients with colon mucinous adenocarcinoma to predict prognosis: a dynamic survival analysis.

The aim was to assess conditional survival for colon mucinous adenocarcinoma (MAC) patients, and to construct nomograms to predict conditional survival probability. Survival analysis was done using conditional survival, which was defined as the probability of surviving additional y years for patients who have survived for x years. The mathematical definition was express as: CS (y|x) = S (x + y)/S (x). Cox regression analyses were used to identify prognostic factors. A nomogram is constructed to predict conditional disease-free survival (DFS) and overall survival (OS) probability according to years that already survive. A total of 179 colon MAC patients were included. The 5-year DFS was 67% after surgery, and the 5-year survival probability of patients, who already survived 1, 2, 3, and 4 years were 75%, 87%, 95%, and 98%, respectively. The 5-year OS was 73% after surgery and increased to 76%, 82%, 88%, and 92% at 1, 2, 3, and 4 years, respectively. Subgroup analyses demonstrated the superiority of conditional survival was more pronounced in advanced stages than in stage I. And pT stage, pN stage, and lymphovascular invasion were significantly associated with DFS and OS. Conditional survival nomograms were constructed to predict the 5-year conditional DFS and OS probability given survival for 1, 2, 3, 4 years after surgery. Conditional survival can provide dynamic survival probability according to years that already survive, especially for patients with advanced stages. Taking into account the years already survived accounted for, novel nomograms contributed to effectively predicting conditional survival.

Gating elements for carvacrol activation of the OTOP1 proton channel.

Otopetrin 1 (OTOP1) is a proton-activated channel crucial for animals' perception of sour taste. Despite its significance, the gating mechanism of OTOP1 remains poorly understood. Here, we demonstrate that carvacrol activates the mouse OTOP1 (mOTOP1) channel under neutral and acidic conditions. Functional analysis showed that carvacrol enhances pH fluorescence signals in OTOP1-expressing cells, with reduced efficacy at lower pH levels. Carvacrol selectively activates mOTOP1, while mOTOP2, mOTOP3, and Chelonia mydas OTOP1 (CmOTOP1) are insensitive to carvacrol activation under neutral pH. Through chimera and point mutation experiments, swapping S134 in transmembrane segment 3 (TM3) and T247 in the TM5-6 linker abolished carvacrol activation of mOTOP1 and conferred activation on CmOTOP1, suggesting these two residues are critical for carvacrol sensitivity. These findings highlight TM3 and TM5-6 linker as pivotal gating apparatus of OTOP1 channels and potential docking sites for drug design.

The prognostic model and immune landscape based on cancer-associated fibroblast features for patients with locally advanced rectal cancer.

Background: This study aimed to construct a nomogram based on CAF features to predict the cancer-specific survival (CSS) rates of locally advanced rectal cancer (LARC) patients. Methods: The EPIC algorithm was employed to calculate the proportion of CAFs. based on the differentially expressed genes between the high and low CAF proportion subgroups, prognostic genes were identified via LASSO and Cox regression analyses. They were then used to construct a prognostic risk signature. Moreover, the GSE39582 and GGSE38832 datasets were used for external validation. Lastly, the level of immune infiltration was evaluated using ssGSEA, ESTIMATE, CIBERSORTx, and TIMER. Results: A higher level of CAF infiltration was associated with a worse prognosis. Additionally, the number of metastasized lymph nodes and distant metastases, as well as the level of immune infiltration were higher in the high CAF proportion subgroup. Five prognostic genes (SMOC2, TUBAL3, C2CD4A, MAP1B, BMP8A) were identified and subsequently incorporated into the prognostic risk signature to predict the 1-, 3-, and 5-year CSS rates in the training and validation sets. Differences in survival rates were also determined in the external validation cohort. Furthermore, independent prognostic factors, including TNM stage and risk score, were combined to established a nomogram. Notably, our results revealed that the proportions of macrophages and neutrophils and the levels of cytokines secreted by M2 macrophages were higher in the high-risk subgroup. Finally, the prognostic genes were significantly associated with the level of immune cell infiltration. Conclusion: Herein, a nomogram based on CAF features was developed to predict the CSS rate of LARC patients. The risk model was capable of reflecting differences in the level of immune cell infiltration.