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This study utilized the U-Net deep learning model to automate the segmentation of three-dimensional after-loaded metal source applicators, aiming to expedite treatment planning, reduce patient wait times, and enhance the treatment process. Using CT images from cervical cancer patients treated between December 2020 and August 2023, 27 images formed the training set, 3 were for validation, and 10 for testing. The model’s performance was evaluated against expert delineations using metrics like the Dice similarity coefficient (DSC), Hausdorff distance 95% (HD95), and others. The results were integrated into an after-loading planning system to locate applicator pathways and assess dose accuracy and feasibility. For the test group, the DSC ranged from 0.90 to 0.93, HD95 from 0.79 to 0.80 mm, and ASSD from 0.03 to 0.22 mm, with an average segmentation time of 65 seconds, significantly faster than manual delineation. The automatic pathways closely matched the original plan’s dosimetric parameters (P >0.05), indicating the system’s potential for safe application in after-loading planning for cervical cancer treatment. The U-Net-based region-growing method shows promise in improving the efficiency and accuracy of after-loaded applicator segmentation.

Abstract Non-line-of-sight (NLOS) imaging aims at reconstructing targets obscured from the direct line of sight. Existing NLOS imaging algorithms require dense measurements at regular grid points in a large area of the relay surface, which severely hinders their availability to variable relay scenarios in practical applications such as robotic vision, autonomous driving, rescue operations and remote sensing. In this work, we propose a Bayesian framework for NLOS imaging without specific requirements on the spatial pattern of illumination and detection points. By introducing virtual confocal signals, we design a confocal complemented signal-object collaborative regularization (CC-SOCR) algorithm for high-quality reconstructions. Our approach is capable of reconstructing both the albedo and surface normal of the hidden objects with fine details under general relay settings. Moreover, with a regular relay surface, coarse rather than dense measurements are enough for our approach such that the acquisition time can be reduced significantly. As demonstrated in multiple experiments, the proposed framework substantially extends the application range of NLOS imaging.

ObjectiveTo explore the advantages of dosimetry and the treatment efficiency of tangent-arc technology in deep inspiration breath-hold radiotherapy for breast cancer.MethodsForty patients with left-sided breast cancer who were treated in our hospital from May 2020 to June 2021 were randomly selected and divided into two groups. The first group’s plan was a continuous semi-arc that started at 145° ( ± 5°) and stopped at 325° ( ± 5°). The other group’s plan, defined as the tangent-arc plan, had two arcs: the first arc started at 145° ( ± 5°) and stopped at 85° ( ± 5°), and the second arc started at 25° ( ± 5°) and stopped at 325° ( ± 5°). We compared the target dose, dose in organs at risk (OARs), and treatment time between the two groups.ResultsThe target dose was similar between the continuous semiarc and tangent-arc groups. The V5 of the right lung was significantly different between the two groups (Dif 5.52, 95% confidence interval 1.92-9.13, t=3.10, P=0.004), with the patients in the continuous semi-arc and tangent-arc groups having lung V5 values of (9.16 ± 1.62)%, and (3.64 ± 0.73)%, respectively. The maximum dose to the spinal cord was (1835.88 ± 222.17) cGy in the continuous semi-arc group and (599.42 ± 153.91) cGy in the tangent-arc group, yielding a significant difference between the two groups (Dif 1236.46, 95% confidence interval 689.32-1783.6, t=4.57, P

Abstract Radiotherapy requires the target area and the organs at risk to be contoured on the CT image of the patient. During the process of organs-at-Risk (OAR) of the chest and abdomen, the doctor needs to contour at each CT image. The delineations of large and varied shapes are time-consuming and laborious. This study aims to evaluate the results of two automatic contouring softwares on OARs definition of CT images of lung cancer and rectal cancer patients. The CT images of 15 patients with rectal cancer and 15 patients with lung cancer were selected separately, and the organs at risk were manually contoured by experienced physicians as reference structures. And then the same datasets were automatically contoured based on AiContour (version 3.1.8.0, Manufactured by Linking MED, Beijing, China) and Raystation (version 4.7.5.4, Manufactured by Raysearch, Stockholm, Sweden) respectively. Deep learning auto-segmentations and Atlas were respectively performed with AiContour and Raystation. Overlap index (OI), Dice similarity index (DSC) and Volume difference (Dv) were evaluated based on the auto-contours, and independent-sample t-test analysis is applied to the results. The results of deep learning auto-segmentations on OI and DSC were better than that of Atlas with statistical difference. There was no significant difference in Dv between the results of two software. With deep learning auto-segmentations, auto-contouring results of most organs in the chest and abdomen are good, and with slight modification, it can meet the clinical requirements for planning. With Atlas, auto-contouring results in most OAR is not as good as deep learning auto-segmentations, and only the auto-contouring results of some organs can be used clinically after modification.

A Non-line-of-sight reconstruction framework with collaborative regularization of the hidden scene and the signal is proposed to obtain albedo and surface normal of the targets with robustness to noise.

Abstract Although reports implicate radioresistance as an important obstacle for the management of breast cancer, its molecular mechanism is elusive. Herein, we found that high HDGF levels are expressed significantly in breast cancer and exhibit a positive association with poor survival prognosis. Heparin-binding growth factor (HDGF) was upregulated in radioresistant breast cancer cells, however, its knockdown could reduce breast cancer radioresistant both in vitro and in vivo. Additionally, the binding of RXRα to HDGF promoter blocked HDGF transcriptional activity, consequently inhibiting breast cancer radioresistance. The enhanced radioresistant activity of HDGF is induced by TKT and STAT3, impacting the STAT3-Tyr705 and STAT3-Ser727 phosphorylation and STAT3 transcriptional activity. Notably, HDGF depletion renders radioresistant hypersensitive to the drug that targets STAT3 phosphorylation. This article demonstrates the novel function of HDGF as a promising molecular target for predicting radioresistance in breast cancer.

The nearly analytic discrete (NAD) method is a kind of finite difference method with advantages of high accuracy and stability. Previous studies have investigated the NAD method for simulating wave propagation in the time-domain. This study applies the NAD method to solving three-dimensional (3D) acoustic wave equations in the frequency-domain. This forward modeling approach is then used as the “engine” for implementing 3D frequency-domain full waveform inversion (FWI). In the numerical modeling experiments, synthetic examples are first given to show the superiority of the NAD method in forward modeling compared with traditional finite difference methods. Synthetic 3D frequency-domain FWI experiments are then carried out to examine the effectiveness of the proposed methods. The inversion results show that the NAD method is more suitable than traditional methods, in terms of computational cost and stability, for 3D frequency-domain FWI, and represents an effective approach for inversion of subsurface model structures.

This study was conducted to determine the effects of 25-hydroxycholecalciferol (25-OH-D3) on performance, egg quality, tibia quality, and serum hormones concentration in laying hens reared under high stocking density. A total of 800 45-week-old Lohmann laying hens were randomly allotted into a 2 × 2 factorial design with 2 levels of dietary 25-OH-D3 levels (0 and 69 μg/kg) and 2 rates of stocking densities [506 (low density) and 338 (high density) cm2/hen]. Laying hens were monitored for 16 wk. High stocking density decreased laying rate, egg weight, and feed intake compared with low stocking density (P < 0.01) during 1 to 8 wk and 1 to 16 wk. Overall, high stocking density increased eggshell lightness value and decreased shell redness and yellowness value, strength, thickness, and relative weight compared with low stocking density (P < 0.05). Dietary supplementation with 25-OH-D3 reduced the value of the eggshell lightness and increased its yellowness and eggshells weight (P ≤ 0.05). The increase in eggshell thickness was more pronounced when 25-OH-D3 was supplemented to layers under high stocking density (interaction, P < 0.05). Layers under high stocking density had lower ash content and calcium content in the tibia than layers under low stocking density (P = 0.04); dietary 25-OH-D3 increased tibia strength compared with no addition (P = 0.05). Layers under high stocking density had higher serum concentrations of 25-OH-D3, corticosterone (CORT), lipopolysaccharide (LPS), and osteocalcin (OC; P < 0.05), lower content of parathyroid hormone (PTH) compared with layers under low stocking density (P < 0.01). Dietary 25-OH-D3 increased serum concentration of 25-OH-D3, carbonic anhydrase (CA), and calcitonin (CT) (P < 0.01) and reduced corticosterone, lipopolysaccharide and osteocalcin concentration (P ≤ 0.05). The increase effect in PTH was more pronounced when 25-OH-D3 was supplemented to layers under high stocking density (interaction, P = 0.05). Overall, the results gathered in this study indicate that high stocking density result in reducing production performance, shell color and quality, and tibia health, whereas dietary 25-OH-D3 was able to maintain tibia health and to mitigate the negative impact of high stocking density on productive performance.

ABSTRACT: The high stocking density is a major stress factor that adversely affects the health and performance of poultry. Therefore, the object of this study was conducted to explore whether dietary 25-hydroxyvitamin D (25-OH-D3) could improve gut health of laying hens reared under high stocking density. A 2 × 2 factorial design was used in this 16-week study, in which 800 45-week-old Lohmann laying hens were allocated into two levels of dietary 25-OH-D3 levels (0 and 69 µg/kg) and two rates of stocking densities [506 (low density, LD) and 338 (high density, HD) cm2/hen]. Compared with the layers with LD, the layers with HD had lower crypt depth in duodenum (P(Density) < 0.05), lower short chain fatty acid (propionic and butyric acid) contents in cecum (P(Density) < 0.05), and lower mRNA expression of intestinal barrier associated protein (claudin-1, mucin-1 and mucin-2). Exposed layer to HD also led to lower intestinal antioxidative capacity [superoxide dismutase (SOD), catalase (CAT), total antioxidant capacity (T-AOC), and higher malondialdehyde (MDA) content] in small intestine (P(Density) < 0.05), lower bacterial abundance of Bacteroidetes (phylum), Spirochaetes (phylum) and Bacteroides (genus; P(Density) < 0.05), higher bacterial enrichment of Lactobacillaceae (genus) and Firmicutes/Bacteroidetes ratio (P(Density) < 0.05) in cecum. Dietary 25-OH-D3 increased the villus height in duodenum and jejunum (P(25-OH-D3) < 0.05), decreased Chao 1 and ACE indexes in cecum (P(25-OH-D3) < 0.05), and it also up-regulated the mRNA expression of claudin-1, mucin-1 and mucin-2 (P(25-OH-D3) < 0.05). Layers treated with 25-OH-D3 led to an enhanced antioxidative enzyme activity of CAT (P(25-OH-D3) < 0.05). Additionally, the effect of 25-OH-D3 reversed the effect of HD on T-AOC and MDA content (P(Interaction) < 0.05). In HD layers, 25-OH-D3 administration decreased the enrichment of Bacteroidetes (phylum), increased Firmicutes (phylum), and Firmicutes/Bacteroidetes ratio (P(Interaction) < 0.05). These results suggest that supplementing 25-OH-D3 in diets may elevate gut health through the improvement of intestinal barrier function, antioxidant capacity and cecal microbiota composition in laying hens with high stocking density.

Peroxisome proliferator activated receptor-alpha (PPARα) and Egl nine homolog 3 (EGLN3) play critical roles in facilitating the adaptation to a hypoxic environment. However, the relationship between EGLN3 and PPARα variants and hypoxic adaptation remains poorly understood in Tibetan chickens. To better understand the effects of genetic variation, we sequenced exons of PPARα and EGLN3 in 138 Lowland chickens (LC) from 7 breeds that were located in Emei, Miyi, Shimian, Wanyuan, Pengxian, and Muchuan in the Sichuan province, and Wenchang in the Hainan province (altitudes for these locations are below 1800 meters). Total 166 Tibetan chickens (TC) from 7 subpopulations that were located in Shigatse, Lhoka, Lhasa, Garze, Aba, Diqing and Yushu in the Tibetan area were also sequenced (altitudes greater than 2700 meters). One single-nucleotide polymorphism (rs316017491, C > T) was identified in EGLN3 and was shared by TC and LC with no significant difference for allele frequencies between them (P > 0.05). Six single-nucleotide polymorphisms (SNP1, A29410G; SNP2, rs13886097; SNP3, T29467C; SNP4, rs735915170; SNP5, rs736599044; and SNP6, rs740077421) including one non-synonymous mutation (SNP2, T > C) were identified in PPARα. This is the first report of SNP1 and SNP3. There was a difference between TC and LC for allele frequencies (P

The second-order nonlinear elliptic system −Δu=f1(x)uα+g1(x)u−β+h1(x)uγP(v), −Δv=f2(x)vα+g2(x)v−β+h2(x)vγP(u) with 0