scAnnoX: an R package integrating multiple public tools for single-cell annotation.

Background: Single-cell annotation plays a crucial role in the analysis of single-cell genomics data. Despite the existence of numerous single-cell annotation algorithms, a comprehensive tool for integrating and comparing these algorithms is also lacking. Methods: This study meticulously investigated a plethora of widely adopted single-cell annotation algorithms. Ten single-cell annotation algorithms were selected based on the classification of either reference dataset-dependent or marker gene-dependent approaches. These algorithms included SingleR, Seurat, sciBet, scmap, CHETAH, scSorter, sc.type, cellID, scCATCH, and SCINA. Building upon these algorithms, we developed an R package named scAnnoX for the integration and comparative analysis of single-cell annotation algorithms. Results: The development of the scAnnoX software package provides a cohesive framework for annotating cells in scRNA-seq data, enabling researchers to more efficiently perform comparative analyses among the cell type annotations contained in scRNA-seq datasets. The integrated environment of scAnnoX streamlines the testing, evaluation, and comparison processes among various algorithms. Among the ten annotation tools evaluated, SingleR, Seurat, sciBet, and scSorter emerged as top-performing algorithms in terms of prediction accuracy, with SingleR and sciBet demonstrating particularly superior performance, offering guidance for users. Interested parties can access the scAnnoX package at https://github.com/XQ-hub/scAnnoX.

Discovery of an independent poor-prognosis subtype associated with tertiary lymphoid structures in breast cancer.

Introduction: Tertiary lymphoid structures (TLSs) are ectopic lymphoid formations that arise in non-lymphoid tissues due to chronic inflammation. The pivotal function of TLSs in regulating tumor invasion and metastasis has been established across several cancers, such as lung cancer, liver cancer, and melanoma, with a positive correlation between increased TLS presence and improved prognosis. Nevertheless, the current research about the clinical significance of TLSs in breast cancer remains limited. Methods: In our investigation, we discovered TLS-critical genes that may impact the prognosis of breast cancer patients, and categorized breast cancer into three distinct subtypes based on critical gene expression profiles, each exhibiting substantial differences in prognosis (p = 0.0046, log-rank test), with Cluster 1 having the best prognosis, followed by Cluster 2, and Cluster 3 having the worst prognosis. We explored the impact of the heterogeneity of these subtypes on patient prognosis, the differences in the molecular mechanism, and their responses to drug therapy and immunotherapy. In addition, we designed a machine learning-based classification model, unveiling highly consistent prognostic distinctions in several externally independent cohorts. Results: A notable marker gene CXCL13 was identified in Cluster 3, potentially pivotal in enhancing patient prognosis. At the single-cell resolution, we delved into the adverse prognosis of Cluster 3, observing an enhanced interaction between fibroblasts, myeloid cells, and basal cells, influencing patient prognosis. Furthermore, we identified several significantly upregulated genes (CD46, JAG1, IL6, and IL6R) that may positively correlate with cancer cells' survival and invasive capabilities in this subtype. Discussion: Our study is a robust foundation for precision medicine and personalized therapy, presenting a novel perspective for the contemporary classification of breast cancer.

A neuromorphic dataset for tabletop object segmentation in indoor cluttered environment.

Event-based cameras are commonly leveraged to mitigate issues such as motion blur, low dynamic range, and limited time sampling, which plague conventional cameras. However, a lack of dedicated event-based datasets for benchmarking segmentation algorithms, especially those offering critical depth information for occluded scenes, has been observed. In response, this paper introduces a novel Event-based Segmentation Dataset (ESD), a high-quality event 3D spatial-temporal dataset designed for indoor object segmentation within cluttered environments. ESD encompasses 145 sequences featuring 14,166 manually annotated RGB frames, along with a substantial event count of 21.88 million and 20.80 million events from two stereo-configured event-based cameras. Notably, this densely annotated 3D spatial-temporal event-based segmentation benchmark for tabletop objects represents a pioneering initiative, providing event-wise depth, and annotated instance labels, in addition to corresponding RGBD frames. By releasing ESD, our aim is to offer the research community a challenging segmentation benchmark of exceptional quality.

OncoCTMiner: streamlining precision oncology trial matching via molecular profile analysis.

By establishing omics sequencing of patient tumors as a crucial element in cancer treatment, the extensive implementation of precision oncology necessitates effective and prompt execution of clinical studies for approving molecular-targeted therapies. However, the substantial volume of patient sequencing data, combined with strict clinical trial criteria, increasingly complicates the process of matching patients to precision oncology studies. To streamline enrollment in these studies, we developed OncoCTMiner, an automated pre-screening platform for molecular cancer clinical trials. Through manual tagging of eligibility criteria for 2227 oncology trials, we identified key bio-concepts such as cancer types, genes, alterations, drugs, biomarkers and therapies. Utilizing this manually annotated corpus along with open-source biomedical natural language processing tools, we trained multiple named entity recognition models specifically designed for precision oncology trials. These models analyzed 460 952 clinical trials, revealing 8.15 million precision medicine concepts, 9.32 million entity-criteria-trial triplets and a comprehensive precision oncology eligibility criteria database. Most significantly, we developed a patient-trial matching system based on cancer patients' clinical and genetic profiles, which can seamlessly integrate with the omics data analysis platform. This system expedites the pre-screening process for potentially suitable precision oncology trials, offering patients swifter access to promising treatment options. Database URL  https://oncoctminer.chosenmedinfo.com.

Low-complexity clustered polynomial nonlinear filter-based electrical dispersion pre-compensation scheme in IM/DD transmission systems.

A polynomial nonlinear filter (PNLF)-based electrical dispersion pre-compensation (pre-EDC) scheme assisted with Gerchberg-Saxton (GS) algorithm is proposed to compensate the chromatic dispersion (CD) for intensity-modulation and direct-detection (IM/DD) optical transmission systems, where PNLF is utilized to fit the nonlinear transfer function of the iterative GS algorithm-based pre-EDC scheme to realize a low-complexity non-iterative CD pre-compensation. The capability of PNLF to fit the nonlinear iterative process enables the PNLF-based pre-EDC scheme to compensate for CD-induced linear distortions and address CD-induced nonlinear distortions, which are typically captured through iterative approaches. Additionally, to further reduce the computational complexity, we also introduce the k-means clustering algorithm to eliminate the weight redundancy and propose a lower-complexity clustered PNLF-based pre-EDC scheme. Simulation results show that PNLF-based and clustered PNLF-based pre-EDC schemes save 76.0% and 97.5% complexity with only 0.3 dB receiver sensitivity penalty at 20% forward error correction (FEC) threshold, compared with GS-based pre-EDC scheme in C-band 56 GBaud 80-km on-off keying (OOK) system. Furthermore, the effectiveness of PNLF-based and clustered PNLF-based pre-EDC schemes is also evaluated through the experimental demonstration. Experimental results show that under C-band 32 GBaud 80-km OOK system, bit error ratio (BER) satisfying 20% FEC threshold is achieved by applying PNLF-based and clustered PNLF-based pre-EDC schemes, which save 78.3% and 94.2% complexity with only 0.4 dB receiver sensitivity penalty compared with GS-based pre-EDC scheme, respectively. The research results indicate that the (clustered) PNLF-based pre-EDC scheme has the great application potential for CD compensation in high-performance and low-cost IM/DD optical transmission systems.

Characterization and Application of Guar Gum/Polyvinyl Alcohol-Based Food Packaging Films Containing Betacyanins from Pokeweed (Phytolacca acinosa Roxb.) Berries and Silver Nanoparticles.

Food packaging films were prepared by using guar gum/polyvinyl alcohol (GP) as the film matrix, 2% Ag nanoparticles (AgNPs) as reinforcing filler and antimicrobial agent, and 1%, 2% and 3% pokeweed betacyanins (PB) as the colorant and antioxidant agent. The structures and color-changing, barrier, mechanical, thermal and antioxidant/antibacterial properties of different films were measured. The results show that the PB were pH-sensitive pigments with pink, purple and yellow colors at pH 3-8, pH 9-11 and pH 12, respectively. PB improved the compatibility of guar gum and polyvinyl alcohol through hydrogen bonds. The films with PB showed a color-changing capacity under ammonia vapor and good color stability in chilled storage. AgNPs and PB elevated the barrier capacity of GP film to light, water vapor and oxygen gas. Meanwhile, AgNPs and PB improved the stiffness, thermal stability and antioxidant/antibacterial activity of GP film. The film with AgNPs and 3% PB showed the highest barrier capacity, stiffness, thermal stability and antioxidant/antimicrobial activity. In shrimp spoilage test, the films with AgNPs and 2% and 3% PB indicated shrimp freshness through film color changes. The results reveal the potential use of the prepared films in active and smart packaging.

Low host immune pressure may be associated with the development of hepatocellular carcinoma: a longitudinal analysis of complete genomes of the HBV 1762T, 1764A mutant.

Background: It has been reported that hepatitis B virus (HBV) double mutations (A1762T, G1764A) are an aetiological factor of hepatocellular carcinoma (HCC). However, it is unclear who is prone to develop HCC, among those infected with the mutant. Exploring HBV quasispecies, which are strongly influenced by host immune pressure, may provide more information about the association of viral factors and HCC. Materials and methods: Nine HCC cases and 10 controls were selected from the Long An cohort. Serum samples were collected in 2004 and 2019 from subjects with HBV double mutations and the complete genome of HBV was amplified and sequenced using next-generation sequencing (NGS). Results: The Shannon entropy values increased from 2004 to 2019 in most cases and controls. There was no significant difference in mean intrahost quasispecies genetic distances between cases and controls. The change in the values of mean intrahost quasispecies genetic distances of the controls between 2004 and 2019 was significantly higher than that of the cases (P<0.05). The viral loads did not differ significantly between cases and controls in 2004(p=0.086) but differed at diagnosed in 2019 (p=0.009). Three mutations occurring with increasing frequency from 2004 to 2019 were identified in the HCC cases, including nt446 C→G, nt514 A→C and nt2857T→C. Their frequency differed significantly between the cases and controls (P<0.05). Conclusions: The change in the values of mean intrahost quasispecies genetic distances in HCC was smaller, suggesting that HBV in HCC cases may be subject to low host immune pressure. Increasing viral loads during long-term infection are associated with the development of HCC. The novel mutations may increase the risk for HCC.

Development and application of intelligent packaging films based on guar gum, polyvinyl alcohol and hyacinth bean (Lablab purpureus (L.) sweet) anthocyanins.

The pH-response color-changeable films were prepared by adding different contents (1 %, 2 % and 3 %) of hyacinth bean anthocyanins (HBA) into guar gum/polyvinyl alcohol blend matrix. The structural characterization and optical, barrier, mechanical, thermal, antioxidant and color-changeable properties of the films were determined. The films were applied to monitor the freshness of chilled shrimp and pork. Results showed that HBA were pH-dependent color-changeable pigments that endowed the films with purple color. 2 % and 3 % of HBA improved the uniformity and compactness of the films by forming hydrogen bonds with film matrix. The barrier ability of the films against UV-vis light, water vapor and oxygen was significantly elevated by 2 % and 3 % of HBA. The mechanical, thermal and antioxidant properties of the films were improved by HBA. The films containing HBA were much sensitive to pH variation and ammonia vapor, presenting obvious color changes (purple→green→yellow-green). The films containing HBA showed good color stability when stored at 4 °C for 30 days. Moreover, the film containing 2 % HBA showed color changes (purple→green) when the chilled shrimp and pork decayed. The results suggested that the film containing 2 % HBA was suitable to monitor the freshness of meat products in intelligent packaging field.

Effects of sulfate on the photosynthetic physiology characteristics of Hydrocotyle vulgaris under zinc stress.

The effects of sulfate on the zinc (Zn) bioaccumulation characteristics and photophysiological mechanisms of the ornamental plant Hydrocotyle vulgaris were explored using a hydroponic culture under three Zn concentrations (300, 500 and 700mgL-1 ) with (400µmolL-1 ) or without the addition of sulfate. Results showed that: (1) tissue Zn concentrations and total Zn contents increased with increasing hydroponic culture Zn concentrations; and sulfate addition decreased Zn uptake and translocation from roots to shoots; (2) Zn exposure decreased photosynthetic pigment synthesis, while sulfate changed this phenomenon, especially for chlorophyll a under 300mgL-1 Zn treatment; (3) Zn exposure decreased photosynthetic function, while sulfate had positive effects, especially on the photosynthetic rate (Pn ) and stomatal conductance (Gs ); and (4) chlorophyll fluorescence parameters related to light energy capture, transfer and assimilation were generally downregulated under Zn stress, while sulfate had a positive effect on these processes. Furthermore, compared to photosynthetic pigment synthesis and photosynthesis, chlorophyll fluorescence was more responsive, especially under 300mgL-1 Zn treatment with sulfate addition. In general, Zn stress affected photophysiological processes at different levels, while sulfate decreased Zn uptake, translocation, and bioaccumulation and showed a positive function in alleviating Zn stress, ultimately resulting in plant growth promotion. All of these results provide a theoretical reference for combining H. vulgaris with sulfate application in the bioremediation of Zn-contaminated environments at the photophysiological level.

Preparation, Characterization, and Application of pH-Response Color-Changeable Films Based on Pullulan, Cooked Amaranth (Amaranthus tricolor L.) Juice, and Bergamot Essential Oil.

Pullulan-based smart packaging films were prepared by mixing cooked amaranth juice and bergamot essential oil. The impact of cooked amaranth juice and bergamot essential oil on the color-changeability, structural characterization, and barrier, antioxidant, mechanical and thermal properties of pullulan-based films was determined. Results showed the cooked amaranth juice contained pH-response color-changing betacyanins. The pullulan films containing cooked amaranth juice were color-changeable in pH 9-12 buffers and in ammonia vapor. The color-changeable property of betacyanins in cooked amaranth juice was unaffected by bergamot essential oils. The inner structure of pullulan films was greatly affected by cooked amaranth juice, forming big and ordered humps in film cross-sections. The crystallinity of pullulan films was improved by the combined addition of cooked amaranth juice and bergamot essential oil. Among the films, the pullulan film containing cooked amaranth juice and 6% bergamot essential oil showed the highest UV-vis light barrier property, antioxidant activity, and tensile strength; while the pullulan film containing cooked amaranth juice and 4% bergamot essential oil showed the highest oxygen barrier property and thermal stability. Moreover, the pullulan films containing cooked amaranth juice were able to monitor the freshness of shrimp by presenting color changes from reddish purple to dark red.

Fast and low-dose medical imaging generation empowered by hybrid deep-learning and iterative reconstruction.

Fast and low-dose reconstructions of medical images are highly desired in clinical routines. We propose a hybrid deep-learning and iterative reconstruction (hybrid DL-IR) framework and apply it for fast magnetic resonance imaging (MRI), fast positron emission tomography (PET), and low-dose computed tomography (CT) image generation tasks. First, in a retrospective MRI study (6,066 cases), we demonstrate its capability of handling 3- to 10-fold under-sampled MR data, enabling organ-level coverage with only 10- to 100-s scan time; second, a low-dose CT study (142 cases) shows that our framework can successfully alleviate the noise and streak artifacts in scans performed with only 10% radiation dose (0.61 mGy); and last, a fast whole-body PET study (131 cases) allows us to faithfully reconstruct tumor-induced lesions, including small ones (<4 mm), from 2- to 4-fold-accelerated PET acquisition (30-60 s/bp). This study offers a promising avenue for accurate and high-quality image reconstruction with broad clinical value.

Adaptation and Feasibility of the Mandarin Version of PEERS® for Autistic Adolescents.

PURPOSE: The Program for the Education and Enrichment of Relational Skills (PEERS®) is a group-based social skills training program for adolescents on the autism spectrum. Although the program has been shown to be effective in improving social skills in autistic adolescents, evidence of its effectiveness from the Mandarin-speaking Chinese population is sparse. The present study used a non-randomized, pre- and post-intervention research design to investigate the feasibility and cultural validity of the program, as well as examine the moderators of intervention outcomes. METHODS: Thirty-three autistic adolescents with intelligence quotient above 70 (Mage = 13.57, SDage = 1.43; Male: Female 25:8) and their parents received 14 concurrent 90-minute sessions. Adolescents' autistic traits, challenging behaviors, emotional functioning, socio-cognitive process, social environment factors (school support), and caregivers' well-being were evaluated. RESULTS: The findings suggest that with minor adjustments, the Mandarin version of PEERS® was generally acceptable and feasible for autistic adolescents and their parents. PEERS® may improve the social skills knowledge, reciprocal communication abilities, and emotional well-being of autistic adolescents. Also, participants with a higher level of school support, and parents with lower perceived subjective well-being at baseline may gain more benefits from PEERS®. The cultural adaptation and acceptability of the Mandarin Version of PEERS® were discussed. CONCLUSION: This feasibility study (Chinese Clinical Trial Registry: ChiCTR2200061417, 2022-06-23, retrospectively registered) provides a basis for further randomized control trials of the Mandarin version of PEERS®.

Low-complexity optimized detection with cluster assisting for C-band 64-Gb/s OOK transmission over 100-km SSMF.

In this paper, a low-complexity optimized detection scheme consisting of a post filter with weight sharing (PF-WS) and cluster-assisted log-maximum a posteriori estimation (CA-Log-MAP) is proposed. Besides, a modified equal-width discrete (MEWD) clustering algorithm is proposed to eliminate the training process during clustering. After channel equalization, optimized detection schemes improve performance by suppressing the in-band noise raised by the equalizers. The proposed optimized detection scheme was experimentally performed in a C-band 64-Gb/s on-off keying (OOK) transmission system over 100-km standard single-mode fiber (SSMF) transmission. Compared with the optimized detection scheme with the lowest complexity, the proposed method saves 69.23% required number of real-valued multiplications per symbol (RNRM) at 7% hard-decision forward error correction (HD-FEC). In addition, when the detection performance reaches saturation, the proposed CA-Log-MAP with MEWD saves 82.93% RNRM. Compared with the classic k-means clustering algorithm, the proposed MEWD has the same performance without a training process. To the best of our knowledge, this is the first time clustering algorithms have been applied to optimize decision schemes.

Honokiol reduces cadmium-induced oxidative injury and endosomal/lysosomal vacuolation via protecting mitochondrial function in quail (Coturnix japonica) liver tissues.

Cadmium (Cd) pollution in environment is toxic to birds. This study aimed to assess antagonistic effect of honokiol (HNK) on Cd-induced quail (Coturnix japonica) liver tissue damage and Cd-induced vacuolation in hepatocytes. We found that HNK alleviated Cd-induced liver pathological damage marked by elevated serum liver biochemical indicators, disordered antioxidant levels and trace elements in quails. HNK reduced Cd-induced liver cell apoptosis as assessed by western blotting and TUNEL staining. The ultrastructure of hepatocytes under transmission electron microscope revealed that Cd induced mitochondrial damage in addition to abnormal enlargement and increased vacuolar structure of cells. Mitochondrial damage and vacuolization were reduced in the HNK + Cd group. Cd induced an increase in the levels of endosomal/lysosomal-related genes, while HNK treatment reversed this effect. Finally, we demonstrated that vacuolation in buffalo rat liver 3A (BRL 3A) cells occurred primarily due to Cd-induced oxidative stress damage that reduces mitochondrial ATP content and indirectly led to dysfunction of ATP-dependent lipid kinase PIKfyve complex. In summary, we are the first to report that Cd induces abnormal enlargement of endosome/lysosomes in quail liver cells and HNK alleviated this phenomenon by reducing mitochondrial damage and increasing intracellular ATP level. This study demonstrated the toxic effect of Cd pollution on birds and how HNK mitigated these effect at the cellular level. Overall, more research on Cd pollution and HNK use in animal husbandry is warranted.

DLUT: Decoupled Learning-Based Unsupervised Tracker.

Unsupervised learning has shown immense potential in object tracking, where accurate classification and regression are crucial for unsupervised trackers. However, the classification and regression branches of most unsupervised trackers calculate object similarities by sharing cross-correlation modules. This leads to high coupling between different branches, thus hindering the network performance. To address the above issue, we propose a Decoupled Learning-based Unsupervised Tracker (DLUT). Specifically, we separate the training pipelines of different branches to unlock their inherent learning potential so that different branches can fully explore the focused feature regions of interest. Furthermore, we design independent adaptive decoupling-correlation modules according to the characteristics of each branch to obtain more discriminative and easily locatable feature response maps. Finally, to suppress the noise interference brought by unsupervised pseudo-label training and highlight the foreground object, we propose a novel suppression-ranking-based unsupervised training strategy. Extensive experiments demonstrate that our DLUT outperforms state-of-the-art unsupervised trackers.

Rat Hepatocytes Mitigate Cadmium Toxicity by Forming Annular Gap Junctions and Degrading Them via Endosome-Lysosome Pathway.

Gap junction protein connexin 43 (Cx43) plays a critical role in gap junction communication in rat hepatocytes. However, those located between hepatocytes are easily internalized following exposure to poisons. Herein, we investigated the potential of buffalo rat liver 3A (BRL 3A) cells to generate annular gap junctions (AGJs) proficient at alleviating cadmium (Cd) cytotoxic injury through degradation via an endosome-lysosome pathway. Our results showed that Cd-induced damage of liver microtubules promoted Cx43 internalization and increased Cx43 phosphorylation at Ser373 site. Furthermore, we established that Cd induced AGJs generation in BRL 3A cells, and AGJs were subsequently degraded through the endosome-lysosome pathway. Overall, our results suggested that Cx43 internalization and the generation of AGJs were cellular protective mechanisms to alleviate Cd toxicity in rat hepatocytes.

LPI-CSFFR: Combining serial fusion with feature reuse for predicting LncRNA-protein interactions.

Long non-coding RNAs (LncRNAs) play important roles in a series of life activities, and they function primarily with proteins. The wet experimental-based methods in lncRNA-protein interactions (lncRPIs) study are time-consuming and expensive. In this study, we propose for the first time a novel feature fusion method, the LPI-CSFFR, to train and predict LncRPIs based on a Convolutional Neural Network (CNN) with feature reuse and serial fusion in sequences, secondary structures, and physicochemical properties of proteins and lncRNAs. The experimental results indicate that LPI-CSFFR achieves excellent performance on the datasets RPI1460 and RPI1807 with an accuracy of 83.7 % and 98.1 %, respectively. We further compare LPI-CSFFR with the state-of-the-art existing methods on the same benchmark datasets to evaluate the performance. In addition, to test the generalization performance of the model, we independently test sample pairs of five model organisms, where Mus musculus are the highest prediction accuracy of 99.5 %, and we find multiple hotspot proteins after constructing an interaction network. Finally, we test the predictive power of the LPI-CSFFR for sample pairs with unknown interactions. The results indicate that LPI-CSFFR is promising for predicting potential LncRPIs. The relevant source code and the data used in this study are available at https://github.com/JianjunTan-Beijing/LPI-CSFFR.

Analysis of single-cell RNA-sequencing data identifies a hypoxic tumor subpopulation associated with poor prognosis in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is an aggressive subtype of mammary carcinoma characterized by low expression levels of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). Along with the rapid development of the single-cell RNA-sequencing (scRNA-seq) technology, the heterogeneity within the tumor microenvironment (TME) could be studied at a higher resolution level, facilitating an exploration of the mechanisms leading to poor prognosis during tumor progression. In previous studies, hypoxia was considered as an intrinsic characteristic of TME in solid tumors, which would activate downstream signaling pathways associated with angiogenesis and metastasis. Moreover, hypoxia-related genes (HRGs) based risk score models demonstrated nice performance in predicting the prognosis of TNBC patients. However, it is essential to further investigate the heterogeneity within hypoxic TME, such as intercellular communications. In the present study, utilizing single-sample Gene Set Enrichment Analysis (ssGSEA) and cell-cell communication analysis on the scRNA-seq data retrieved from Gene Expression Omnibus (GEO) database with accession number GSM4476488, we identified four tumor subpopulations with diverse functions, particularly a hypoxia-related one. Furthermore, results of cell-cell communication analysis revealed the dominant role of the hypoxic tumor subpopulation in angiogenesis- and metastasis-related signaling pathways as a signal sender. Consequently, regard the TNBC cohorts acquired from The Cancer Genome Atlas (TCGA) and GEO as train set and test set respectively, we constructed a risk score model with reliable capacity for the prediction of overall survival (OS), where ARTN and L1CAM were identified as risk factors promoting angiogenesis and metastasis of tumors. The expression of ARTN and L1CAM were further analyzed through tumor immune estimation resource (TIMER) platform. In conclusion, these two marker genes of the hypoxic tumor subpopulation played vital roles in tumor development, indicating poor prognosis in TNBC patients.

Multimodal MRI Reconstruction Assisted With Spatial Alignment Network.

In clinical practice, multi-modal magnetic resonance imaging (MRI) with different contrasts is usually acquired in a single study to assess different properties of the same region of interest in the human body. The whole acquisition process can be accelerated by having one or more modalities under-sampled in the k -space. Recent research has shown that, considering the redundancy between different modalities, a target MRI modality under-sampled in the k -space can be more efficiently reconstructed with a fully-sampled reference MRI modality. However, we find that the performance of the aforementioned multi-modal reconstruction can be negatively affected by subtle spatial misalignment between different modalities, which is actually common in clinical practice. In this paper, we improve the quality of multi-modal reconstruction by compensating for such spatial misalignment with a spatial alignment network. First, our spatial alignment network estimates the displacement between the fully-sampled reference and the under-sampled target images, and warps the reference image accordingly. Then, the aligned fully-sampled reference image joins the multi-modal reconstruction of the under-sampled target image. Also, considering the contrast difference between the target and reference images, we have designed a cross-modality-synthesis-based registration loss in combination with the reconstruction loss, to jointly train the spatial alignment network and the reconstruction network. The experiments on both clinical MRI and multi-coil k -space raw data demonstrate the superiority and robustness of the multi-modal MRI reconstruction empowered with our spatial alignment network. Our code is publicly available at https://github.com/woxuankai/SpatialAlignmentNetwork.

Identification of novel lipid biomarkers in xmrk- and Myc-induced models of hepatocellular carcinoma in zebrafish.

BACKGROUND: Hepatocellular carcinoma (HCC) is the predominant form of liver cancer and is accompanied by complex dysregulation of lipids. Increasing evidence suggests that particular lipid species are associated with HCC progression. Here, we aimed to identify lipid biomarkers of HCC associated with the induction of two oncogenes, xmrk, a zebrafish homolog of the human epidermal growth factor receptor (EGFR), and Myc, a regulator of EGFR expression during HCC. METHODS: We induced HCC in transgenic xmrk, Myc, and xmrk/Myc zebrafish models. Liver specimens were histologically analyzed to characterize the HCC stage, Oil-Red-O stained to detect lipids, and liquid chromatography/mass spectrometry analyzed to assign and quantify lipid species. Quantitative real-time polymerase chain reaction was used to measure lipid metabolic gene expression in liver samples. Lipid species data was analyzed using univariate and multivariate logistic modeling to correlate lipid class levels with HCC progression. RESULTS: We found that induction of xmrk, Myc and xmrk/Myc caused different stages of HCC. Lipid deposition and class levels generally increased during tumor progression, but triglyceride levels decreased. Myc appears to control early HCC stage lipid species levels in double transgenics, whereas xmrk may take over this role in later stages. Lipid metabolic gene expression can be regulated by either xmrk, Myc, or both oncogenes. Our computational models showed that variations in total levels of several lipid classes are associated with HCC progression. CONCLUSIONS: These data indicate that xmrk and Myc can temporally regulate lipid species that may serve as effective biomarkers of HCC progression.