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Precise Couinaud segmentation from preoperative liver computed tomography (CT) is crucial for surgical planning and lesion examination. However, this task is challenging as it is defined based on vessel structures, and there is no intensity contrast between adjacent Couinaud segments in CT images. To solve this challenge, we design a multi-scale point-voxel fusion framework, which can more effectively model the spatial relationship of points and the semantic information of the image, producing robust and smooth Couinaud segmentations. Specifically, we first segment the liver and vessels from the CT image and generate 3D liver point clouds and voxel grids embedded with the vessel structure. Then, our method with two input-specific branches extracts complementary feature representations from points and voxels, respectively. The local attention module adaptively fuses features from the two branches at different scales to balance the contribution of different branches in learning more discriminative features. Furthermore, we propose a novel distance loss at the feature level to make the features in the segment more compact, thereby improving the certainty of segmentation between segments. Our experimental results on three public liver datasets demonstrate that our proposed method outperforms several state-of-the-art methods by large margins. Specifically, in out-of-distribution (OOD) testing of LiTS dataset, our method exceeded the voxel-based 3D UNet by approximately 20% in Dice score, and outperformed the point-based PointNet2Plus by approximately 8% in Dice score. Our code and manual annotations of the public datasets presented in this paper are available online: https://github.com/xukun-zhang/Couinaud-Segmentation., Competing Interests: Declaration of competing interest The authors of the manuscript declare that there are no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Augmented reality for laparoscopic liver resection is a visualisation mode that allows a surgeon to localise tumours and vessels embedded within the liver by projecting them on top of a laparoscopic image. Preoperative 3D models extracted from Computed Tomography (CT) or Magnetic Resonance (MR) imaging data are registered to the intraoperative laparoscopic images during this process. Regarding 3D-2D fusion, most algorithms use anatomical landmarks to guide registration, such as the liver's inferior ridge, the falciform ligament, and the occluding contours. These are usually marked by hand in both the laparoscopic image and the 3D model, which is time-consuming and prone to error. Therefore, there is a need to automate this process so that augmented reality can be used effectively in the operating room. We present the Preoperative-to-Intraoperative Laparoscopic Fusion challenge (P2ILF), held during the Medical Image Computing and Computer Assisted Intervention (MICCAI 2022) conference, which investigates the possibilities of detecting these landmarks automatically and using them in registration. The challenge was divided into two tasks: (1) A 2D and 3D landmark segmentation task and (2) a 3D-2D registration task. The teams were provided with training data consisting of 167 laparoscopic images and 9 preoperative 3D models from 9 patients, with the corresponding 2D and 3D landmark annotations. A total of 6 teams from 4 countries participated in the challenge, whose results were assessed for each task independently. All the teams proposed deep learning-based methods for the 2D and 3D landmark segmentation tasks and differentiable rendering-based methods for the registration task. The proposed methods were evaluated on 16 test images and 2 preoperative 3D models from 2 patients. In Task 1, the teams were able to segment most of the 2D landmarks, while the 3D landmarks showed to be more challenging to segment. In Task 2, only one team obtained acceptable qualitative and quantitative registration results. Based on the experimental outcomes, we propose three key hypotheses that determine current limitations and future directions for research in this domain., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

As a country with abundant genetic resources of pigs, the domestication history of pigs in China and the adaptive evolution of Chinese pig breeds at different latitudes have rarely been elucidated at the genome-wide level. To fill this gap, we first assembled a high-quality chromosome-level genome of the Chenghua pig and used it as a benchmark to analyse the genomes of 272 samples from three genera of three continents. The divergence of the three species belonging to three genera, Phacochoerus africanus, Potamochoerus porcus, and Sus scrofa, was assessed. The introgression of pig breeds redefined that the migration routes were basically from southern China to central and southwestern China, then spread to eastern China, arrived in northern China, and finally reached Europe. The domestication of pigs in China occurred ∼12,000 years ago, earlier than the available Chinese archaeological domestication evidence. In addition, FBN1 and NR6A1 were identified in our study as candidate genes related to extreme skin thickness differences in Eurasian pig breeds and adaptive evolution at different latitudes in Chinese pig breeds, respectively. Our study provides a new resource for the pig genomic pool and refines our understanding of pig genetic diversity, domestication, migration, and adaptive evolution at different latitudes., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Yanzhi Jiang reports financial support was provided by Chengdu Livestock and Poultry Genetic Resources Protection Center (2022) and Sichuan Science and Technology Program., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Accurate tissue segmentation of thick-slice fetal brain magnetic resonance (MR) scans is crucial for both reconstruction of isotropic brain MR volumes and the quantification of fetal brain development. However, this task is challenging due to the use of thick-slice scans in clinically-acquired fetal brain data. To address this issue, we propose to leverage high-quality isotropic fetal brain MR volumes (and also their corresponding annotations) as guidance for segmentation of thick-slice scans. Due to existence of significant domain gap between high-quality isotropic volume (i.e., source data) and thick-slice scans (i.e., target data), we employ a domain adaptation technique to achieve the associated knowledge transfer (from high-quality "source" volumes to thick-slice "target" scans). Specifically, we first register the available high-quality isotropic fetal brain MR volumes across different gestational weeks to construct longitudinally-complete source data. To capture domain-invariant information, we then perform Fourier decomposition to extract image content and style codes. Finally, we propose a novel Cycle-Consistent Domain Adaptation Network (C 2 DA-Net) to efficiently transfer the knowledge learned from high-quality isotropic volumes for accurate tissue segmentation of thick-slice scans. Our C 2 DA-Net can fully utilize a small set of annotated isotropic volumes to guide tissue segmentation on unannotated thick-slice scans. Extensive experiments on a large-scale dataset of 372 clinically acquired thick-slice MR scans demonstrate that our C 2 DA-Net achieves much better performance than cutting-edge methods quantitatively and qualitatively.

With the rapid development of internet information technology, online public opinion's influence is infinitely magnified, seriously threatening social security and national governance. It is significant to clarify the spatial and temporal evolution rules of online public opinion on major epidemics and its influencing factors for the governance and guidance of online public opinion on major epidemics. In this paper, the spatiotemporal evolution analysis model of online public opinion and an analysis model of influencing factors were constructed. We selected the Baidu index and microblog crawler text data at the early stage of COVID-19 as the research objects and analyzed the evolution of online public opinion during the time period by using the optimal segmentation method, spatial autocorrelation analysis, and text analysis method. The spatiotemporal evolutionary influences and their influence are further analyzed using the geographic probe factor detection method. The results showed that the evolution of online public opinion in the early stage of the epidemic was closely related to the event's evolution and the prevention and control effect. In the time dimension, the early evolution of online public opinion has prominent periodic characteristics. In the geospatial dimension, there are significant spatial agglomeration effects and spillover effects. In the cyberspace dimension, there are significant differences in online public opinion heat, hot topics, and netizens' emotional tendencies at different stages. Furthermore, the severity of the epidemic, the number of Internet users, the number of media reports and the region's attributes jointly affect the spatial and temporal evolution pattern of online public opinions about the epidemic. The research results provide decision-making references for the government and planners to effectively manage online public opinion on emergencies and improve the government's public opinion governance capacity and level., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)

Preoperative observation of liver status in patients with liver tumors by abdominal Computed Tomography (CT) imaging is one of the essential references for formulating surgical plans. Preoperative vessel segmentation in the patient's liver region has become an increasingly important and challenging problem. Almost all existing methods first segment arterial and venous vessels on CT in the arterial and venous phases, respectively. Then, the two are directly registered to complete the reconstruction of the vascular system, ignoring the displacement and deformation of blood vessels caused by changes in body position and respiration in the two phases. We propose an unsupervised domain-adaptive two-stage vessel segmentation framework for simultaneous fine segmentation of arterial and venous vessels on venous phase CT. Specifically, we first achieve domain adaptation for arterial and venous phase CT using a modified cycle-consistent adversarial network. The newly added discriminator can improve the ability to generate and discriminate tiny blood vessels, making the domain-adaptive network more robust. The second-stage supervised training of arterial vessels was then performed on the translated arterial phase CT. In this process, we propose an orthogonal depth projection loss function to enhance the representation ability of the 3D U-shape segmentation network for the geometric information of the vessel model. The segmented venous vessels were also performed on venous phase CT in the second stage. Finally, we invited professional doctors to annotate arterial and venous vessels on the venous phase CT of the test set. The experimental results show that the segmentation accuracy of arterial and venous vessels on venous phase CT is 0.8454 and 0.8087, respectively. Our proposed framework can simultaneously achieve supervised segmentation of venous vessels and unsupervised segmentation of arterial vessels on venous phase CT. Our approach can be extended to other fields of medical segmentation, such as unsupervised domain adaptive segmentation of liver tumors at different CT phases, to facilitate the development of the community., Competing Interests: The authors declare that there are no conflicts of interest regarding the publication of this paper., (Copyright © 2022 Haopeng Kuang et al.)

Background A predictive tool is required to identify the cancer-specific survival in rectal cancer (RC) patients who have opted to receive preoperative radiotherapy. Methods A database containing the data on RC patients' records of Surveillance, Epidemiology, and End Results (SEER) receiving surgery during 2000-2014 was selected. All patients received neoadjuvant radiotherapy (NR). The correlation of clinicopathological parameters was analyzed using the Chi-square test and the survival risk factors were analyzed using the Cox proportional hazards analysis (univariate and multivariate). Finally, the nomogram was developed and validated to visually represent an accurate prediction of the probability of 3- and 5-year cancer-specific survival (CSS) based on the screened variables of the cohort. Results 11,499 rectal cancer patients were included in our cohort. Patients' records were randomly allocated to either the development or validation cohorts based on an equal ratio (1:1). Performing the multivariate Cox regression analysis incorporating these variables in the development cohort determined 11 independent prognostic factors. Statistically significant differences were recorded among subgroups using log-rank tests, which confirmed the appropriateness and acceptability of factor stratifications. Then, the nomogram was constructed and its concordance index (C-index) values in the development cohort (0.720) and validation cohort (0.717) were evaluated to be higher ( P <0.05) than those of the AJCC stage (0.631 and 0.633 respectively). Also, the 3-year AUC values of this nomogram were higher than those of the AJCC stage in both the development cohort (0.746 vs. 0.631) and the validation cohort (0.745 vs. 0.640). Using DCA curves, the predictive potential of the currently developed nomogram outperformed the conventional AJCC staging system. Conclusion The nomogram model might be a more reliable tool to predict prognosis accurately in rectal cancer patients receiving preoperative radiotherapy.

The aim of our study was to explore the value of the 8th edition TNM staging system on evaluating the prognosis of colorectal carcinoid. Colorectal carcinoid patients between 1988 and 2015 were selected in the Surveillance, Epidemiology, and End Results Program (SEER) database for analysis. About 4286 patients with colorectal carcinoid tumors were identified, of which were carcinoid tumor NOS (n = 1726), neuroendocrine carcinoma (NEC) (n = 1346) and other carcinoid tumor (OCT) (n = 591). Worsening 10-year CSS rates with increasing N status, M status, and SEER historic stage were demonstrated across all three above groups (all P < .05). In carcinoid tumor NOS, significant differences in CSS were found with increasing combined 8th AJCC stages (P < .001), except for that between stage II and stage III (10-year CSS rate: 82.6% vs 84.3%, P = .68). While combined 8th TNM stage in NEC and OTC exhibited greater separations in CSS despite on-going overlaps between groups. For carcinoid tumor NOS, stage II (HR = 3.37; 95% CI: 0.97-11.76), and stage III (HR = 2.09; 95% CI: 0.51-8.66) conferred no significant difference in CSS compared with stage I, while stage IV had an increasing HR of 5.09 (95% CI: 1.08-24.08). Although combined 8th AJCC stage had a good ability to distinguish 10-year CSS of patients with NEC or OCT, detailed 8th AJCC stage did not seem to be applicable. Detailed 8th AJCC categories of advanced stages in all the three groups conferred increased HRs with overlapping CIs. However, in the early and middle status, HRs did not increase with the increase of stages, or there was no difference in HRs between adjacent stages. Combined 8th TNM stage was not practical for judging the survival outcomes of colorectal carcinoid tumor NOS, especially in patients with stages II and III, but it provided useful prognostic information for NEC and OCT. However, for all carcinoid tumors, the prognostic values of detailed 8th AJCC stage were not enough accurate in the clinic. More optimized staging methods should be developed and validated in the future., (© 2020 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)

The low spatial frequency (LSF) component of visual information rapidly conveyed coarse information for global perception, while the high spatial frequency (HSF) component delivered fine-grained information for detailed analyses. The feedforward theorists deemed that a coarse-to-fine process was sufficient for a rapid scene recognition. Based on the response priming paradigm, the present study aimed to deeply explore how different spatial frequency interacted with each other during rapid scene recognition. The response priming paradigm posited that as long as the prime slide could be rapidly recognized, the prime-target system was behaviorally equivalent to a feedforward system. Adopting broad spatial frequency images, experiment 1 revealed a typical response priming effect. But in experiment 2, when the HSF and the LSF components of the same pictures were separately presented, neither the LSF-to-HSF sequence nor the HSF-to-LSF sequence reproduced the response priming effect. These results demonstrated that LSF or HSF component alone was not sufficient for rapid scene recognition and, further, that the integration of different spatial frequency needed some early feedback loops. These findings supported that the local recurrent processing loops among early visual cortex was involved during rapid scene recognition., Competing Interests: Declaration of competing interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)

The naturally occurring quercetin flavonoid, dihydroquercetin, is widely distributed in plant tissues and has a variety of biological activities. Herein, a magnetic molecularly imprinted solid-phase extraction was tailor made for selective determination of dihydroquercetin in Larix griffithiana using high-performance liquid chromatography. Amino-functionalized core-shell magnetic nanoparticles were prepared and characterized using scanning electron microscopy, transmission electron microscopy, vibrating sample magnetometry, and infrared spectroscopy. The polymer had an average diameter of 250 ± 2.56 nm and exhibited good stability and adsorption for template molecule, which is enriched by hydrogen bonding interaction. Multiple factors for extraction, including loading, washing, elution solvents, and extraction time, were optimized. The limit of detection was 1.23 μg/g. The precision determined at various concentration of dihydroquercetin was less than 4% and the mean recovery was between 74.64 and 101.80%. It has therefore been shown that this protocol can be used as an alternative extraction to quantify dihydroquercetin in L. griffithiana and purify quercetin flavonoid from other complex matrices., (© 2020 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

When face was inverted, dynamic gaze cues could still effectively direct attention despite the disruption of configural face processing, but the static gaze cues could not. The present study investigated the role of the motion cue in the dynamic Gaze-Cueing Effect (GCE). With schematic and real faces, we employed the gaze-cueing paradigm to examine the differences among three kinds of cues (static gaze cue, dynamic gaze cue and motion cue) based on behavioral results and event-related potentials. Behavioral results revealed significant GCE in all conditions. In the schematic face group, the motion cue (two symmetrical dots shifting slightly to the side) induced a significantly smaller GCE than the dynamic gaze cues (two symmetrical dots moving within a rounded circle), while in the real face group, the motion cue (that is, the inverted-face gaze cue) remained a strong GCE compared with other conditions. With regard to the ERP results, we found the early directing attention negativity (EDAN), which was sensitive to voluntary cues (e.g. arrow cue) rather than gaze cue, in the schematic motion cue condition, but not in the inverted-face gaze cue condition. We supposed that the motion cue (real face) could activate the configural face processing even when the face is inverted. This finding supported that EDAN reflected a cue-triggered attention shift., (Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Toxoplasma gondii, an obligate intracellular protozoan, is the causative agent of toxoplasmosis, which can cause serious public health problems. The current drugs used to treat toxoplasmosis have many limitations. This study evaluated the anti-T. gondii activity and potential mechanism of Licochalcone A (Lico A) in vitro and in vivo. The safe concentration of Lico A in HFF cells was determined by MTT cell viability assays. The presence of T. gondii was assessed by qPCR and Giemsa staining. Azithromycin and sulfadiazine, commonly used effective treatments, served as drug controls. T. gondii ultrastructural alterations were observed by electron microscopy. The anti-T. gondii activity of Lico A was evaluated using an in vivo mouse infection model. In vitro, Lico A had no negative effect on host cell viability at concentrations below 9 μg/mL; however, it did inhibit T. gondii proliferation in a dose-dependent manner, with a 50% inhibitory concentration (IC 50 ) of 0.848 μg/mL. Electron microscopy analyses indicated substantial structural and ultrastructural changes in tachyzoites after Lico A treatment. Nile Red staining assays demonstrated that Lico A caused lipid accumulation. Lico A treatment significantly increased the survival rate of BALB/c mice infected with T. gondii. Lico A achieved the same therapeutic effect as a commonly used clinical drugs (combination of sulfadiazine, pyrimethamine and folinic acid). In conclusion, Lico A has strong anti-T. gondii activity in vitro and in vivo and might be developed into a new anti-T. gondii drug. Moreover, Lico A may exert these effects by interfering with lipid metabolism in the parasite., (Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.)