Alterations of plasma circulating microRNAs in BALB/c mice with Toxocara canis visceral and cerebral larva migrans.

BACKGROUND: Human toxocariasis is a neglected parasitic disease characterised by the syndromes visceral, cerebral, and ocular larva migrans. This disease is caused by the migrating larvae of Toxocara roundworms from dogs and cats, affecting 1.4 billion people globally. Via extracellular vesicles (EVs), microRNAs have been demonstrated to play roles in host-parasite interactions and proposed as circulating biomarkers for the diagnosis and follow-up of parasitic diseases. METHODS: Small RNA-seq was conducted to identify miRNAs in the infective larvae of T. canis and plasma EV-containing preparations of infected BALB/c mice. Differential expression analysis and target prediction were performed to indicate miRNAs involved in host-parasite interactions and miRNAs associated with visceral and/or cerebral larva migrans in the infected mice. Quantitative real-time polymerase chain reaction (PCR) was used to amplify circulating miRNAs from the infected mice. RESULTS: This study reports host and parasite miRNAs in the plasma of BALB/c mice with visceral and cerebral larva migrans and demonstrates the alterations of these miRNAs during the migration of larvae from the livers through the lungs and to the brains of infected mice. After filtering unspecific changes in an irrelevant control, T. canis-derived miRNAs and T. canis infection-induced differential miRNAs are predicted to modulate genes consistently involved in mitogen-activated protein kinase (MAPK) signalling and pathways regulating axon guidance and pluripotency of stem in the infected mice with visceral and cerebral larva migrans. For these plasma circulating miRNAs predicted to be involved in host-parasite crosstalk, two murine miRNAs (miR-26b-5p and miR-122-5p) are experimentally verified to be responsive to larva migrans and represent circulating biomarker candidates for visceral and cerebral toxocariasis in BALB/c mice. CONCLUSIONS: Our findings provide novel insights into the crosstalk of T. canis and the mammalian host via plasma circulating miRNAs, and prime agents and indicators for visceral and cerebral larva migrans. A deep understanding of these aspects will underpin the diagnosis and control of toxocariasis in humans and animals.

Oxytocin attenuates hypothalamic injury-induced cognitive dysfunction by inhibiting hippocampal ERK signaling and Aß deposition.

In clinical settings, tumor compression, trauma, surgical injury, and other types of injury can cause hypothalamic damage, resulting in various types of hypothalamic dysfunction. Impaired release of oxytocin can lead to cognitive impairment and affect prognosis and long-term quality of life after hypothalamic injury. Hypothalamic injury-induced cognitive dysfunction was detected in male animals. Behavioral parameters were measured to assess the characteristics of cognitive dysfunction induced by hypothalamic-pituitary stalk lesions. Brains were collected for high-throughput RNA sequencing and immunostaining to identify pathophysiological changes in hippocampal regions highly associated with cognitive function after injury to corresponding hypothalamic areas. Through transcriptomic analysis, we confirmed the loss of oxytocin neurons after hypothalamic injury and the reversal of hypothalamic-induced cognitive dysfunction after oxytocin supplementation. Furthermore, overactivation of the ERK signaling pathway and ß-amyloid deposition in the hippocampal region after hypothalamic injury were observed, and cognitive function was restored after inhibition of ERK signaling pathway overactivation. Our findings suggest that cognitive dysfunction after hypothalamic injury may be caused by ERK hyperphosphorylation in the hippocampal region resulting from a decrease in the number of oxytocin neurons, which in turn causes ß-amyloid deposition.

WASPSYN: A Challenge for Domain Adaptive Synapse Detection in Microwasp Brain Connectomes.

The size of image volumes in connectomics studies now reaches terabyte and often petabyte scales with a great diversity of appearance due to different sample preparation procedures. However, manual annotation of neuronal structures (e.g., synapses) in these huge image volumes is time-consuming, leading to limited labeled training data often smaller than 0.001% of the large-scale image volumes in application. Methods that can utilize in-domain labeled data and generalize to out-of-domain unlabeled data are in urgent need. Although many domain adaptation approaches are proposed to address such issues in the natural image domain, few of them have been evaluated on connectomics data due to a lack of domain adaptation benchmarks. Therefore, to enable developments of domain adaptive synapse detection methods for large-scale connectomics applications, we annotated 14 image volumes from a biologically diverse set of Megaphragma viggianii brain regions originating from three different whole-brain datasets and organized the WASPSYN challenge at ISBI 2023. The annotations include coordinates of pre-synapses and post-synapses in the 3D space, together with their one-to-many connectivity information. This paper describes the dataset, the tasks, the proposed baseline, the evaluation method, and the results of the challenge. Limitations of the challenge and the impact on neuroscience research are also discussed. The challenge is and will continue to be available at https://codalab.lisn.upsaclay.fr/competitions/9169. Successful algorithms that emerge from our challenge may potentially revolutionize real-world connectomics research and further the cause that aims to unravel the complexity of brain structure and function.

Global research hotspots and trends of acute rejection after liver transplantation from 1988 to 2022: a bibliometric analysis.

Background: Acute rejection (AR) is the predominant form of rejection observed in liver transplantation and plays a crucial role in transplant immunology. This study aims to utilize bibliometric analysis to understand the status quo, hotspots, and future trends of research on AR after liver transplantation. Methods: We searched the Web of Science Core Collection (WoSCC) for studies on AR after liver transplantation published from 1988 to 2022. The Bibliometric Online Analysis Platform, VOSviewer, and CiteSpace were used for analysis of all extracted publications. Results: This study included 2,398 articles published in 456 journals by 12,568 authors from 1,965 institutions in 55 countries/regions. The United States and its affiliated institution, the University of Pittsburgh, were the most productive contributors. Transplantation (n = 12,435) was the most frequently cited journal. Neuhaus P (n = 38) was the highest output author, and Demetris AJ (n = 670) was the most co-cited author. The research hotspots of AR after liver transplantation include pathogenesis, immunosuppressive therapy, and prognosis. Emerging research directions include regulatory T cells, immunosuppression minimization, intra-patient variability (IPV) of tacrolimus, and novel non-invasive diagnostic markers. Conclusion: Our study utilized bibliometric methods to analyze the study of AR after liver transplantation over the past 35 years. With the prolonged survival of liver transplant recipients, the most active areas currently focus on individualized treatment and improving patient prognosis. Minimizing adverse reactions to immunosuppressive therapy while simultaneously avoiding an increase in the risk of AR remains a future research focus.

Identification and phylogenetic analysis of Jingmen tick virus in Jiangxi Province, China.

Jingmen tick virus (JMTV) is a newly identified segmented flavivirus that has been recognized in multiple hosts, such as humans, buffalos, bats, rodents, mosquitos and ticks. Various clinical cases and studies manifested that JMTV is a true arbovirus with wide host spectrum and showed potential threats toward public health. JMTV has been reported in multiple countries in Asia, Europe, Africa, and America. Moreover, wild boars serve as an important intermediary between humans and the wild ecological system. In China, it has been reported in nine provinces, while the prevalence and the distribution of JMTV in most regions including Jiangxi Province are still unknown. Thus, to profile the distribution of JMTV in Jiangxi Province, an epidemiological investigation was carried out from 2020 to 2022. In current study, 66 ticks were collected from 17 wild boars in Jiangxi Province. The results showed that 12 out of 66 ticks were JMTV positive, indicating JMTV is prevalent in ticks and boars in Jiangxi Province. The genome sequences of JMTV strain WY01 were sequenced to profile viral evolution of JMTV in China. Phylogenetic analysis divided JMTV strains into two genotypes, Group I and Group II. WY01 belongs to Group II and it shares the closest evolutionary relationship with the Japan strains rather than the strains from neighboring provinces in China suggesting that JMTV might have complex transmission routes. Overall, current study, for the first time, reported that JMTV is prevalent in Jiangxi Province and provided additional information concerning JMTV distribution and evolution in China.

Toward DNN of LUTs: Learning Efficient Image Restoration with Multiple Look-Up Tables.

The widespread usage of high-definition screens on edge devices stimulates a strong demand for efficient image restoration algorithms. The way of caching deep learning models in a look-up table (LUT) is recently introduced to respond to this demand. However, the size of a single LUT grows exponentially with the increase of its indexing capacity, which restricts its receptive field and thus the performance. To overcome this intrinsic limitation of the single-LUT solution, we propose a universal method to construct multiple LUTs like a neural network, termed MuLUT. Firstly, we devise novel complementary indexing patterns, as well as a general implementation for arbitrary patterns, to construct multiple LUTs in parallel. Secondly, we propose a re-indexing mechanism to enable hierarchical indexing between cascaded LUTs. Finally, we introduce channel indexing to allow cross-channel interaction, enabling LUTs to process color channels jointly. In these principled ways, the total size of MuLUT is linear to its indexing capacity, yielding a practical solution to obtain superior performance with the enlarged receptive field. We examine the advantage of MuLUT on various image restoration tasks, including super-resolution, demosaicing, denoising, and deblocking. MuLUT achieves a significant improvement over the single-LUT solution, e.g., up to 1.1dB PSNR for super-resolution and up to 2.8dB PSNR for grayscale denoising, while preserving its efficiency, which is 100× less in energy cost compared with lightweight deep neural networks. Our code and trained models are publicly available at https://github.com/ddlee-cn/MuLUT.

Growth hormone promotes the reconstruction of injured axons in the hypothalamo-neurohypophyseal system.

JOURNAL/nrgr/04.03/01300535-202410000-00026/figure1/v/2024-02-06T055622Z/r/image-tiff Previous studies have shown that growth hormone can regulate hypothalamic energy metabolism, stress, and hormone release. Therefore, growth hormone has great potential for treating hypothalamic injury. In this study, we established a specific hypothalamic axon injury model by inducing hypothalamic pituitary stalk electric lesions in male mice. We then treated mice by intraperitoneal administration of growth hormone. Our results showed that growth hormone increased the expression of insulin-like growth factor 1 and its receptors, and promoted the survival of hypothalamic neurons, axonal regeneration, and vascular reconstruction from the median eminence through the posterior pituitary. Altogether, this alleviated hypothalamic injury-caused central diabetes insipidus and anxiety. These results suggest that growth hormone can promote axonal reconstruction after hypothalamic injury by regulating the growth hormone-insulin-like growth factor 1 axis.

Correlation between white blood cell count and intestinal resection in patients with acute mesenteric vein thrombosis.

OBJECTIVE: Acute mesenteric vein thrombosis (AMVT) is an acute abdominal disease with onset, rapid progression, and extensive intestinal necrosis that requires immediate surgical resection. The purpose of this study was to determine the risk factors for nosocomial intestinal resection in patients with AMVT. METHODS: We retrospectively analysed 64 patients with AMVT diagnosed by CTA at the Affiliated Hospital of Kunming University of Science and Technology from January 2013 to December 2021. We compared patients who underwent intestinal resection (42 patients) with those who did not undergo intestinal resection (22 patients). The area under the ROC curve was evaluated, and a forest map was drawn. RESULTS: Among the 64 patients, 6 (9.38%) had a fever, 60 (93.75%) had abdominal pain, 9 (14.06%) had a history of diabetes, 8 (12.5%) had a history of deep vein thrombosis (DVT), and 25 (39.06%) had ascites suggested by B ultrasound or CT after admission. The mean age of all patients was 49.86 ± 16.25 years. The mean age of the patients in the enterectomy group was 47.71 ± 16.20 years. The mean age of the patients in the conservative treatment group (without enterectomy) was 53.95 ± 15.90 years. In the univariate analysis, there were statistically significant differences in leukocyte count (P = 0.003), neutrophil count (P = 0.001), AST (P = 0.048), total bilirubin (P = 0.047), fibrinogen (P = 0.022) and DD2 (P = 0.024) between the two groups. The multivariate logistic regression analysis showed that admission white blood cell count (OR = 1.153, 95% CI: 1.039-1.280, P = 0.007) was an independent risk factor for intestinal resection in patients with AMVT. The ROC curve showed that the white blood cell count (AUC = 0.759 95% CI: 0.620-0.897; P = 0.001; optimal threshold: 7.815; sensitivity: 0.881; specificity: 0.636) had good predictive value for emergency enterectomy for AMVT. CONCLUSIONS: Among patients with AMVT, patients with a higher white blood cell count at admission were more likely to have intestinal necrosis and require emergency enterectomy. This study is helpful for clinicians to accurately determine whether emergency intestinal resection is needed in patients with AMVT after admission, prevent further intestinal necrosis, and improve the prognosis of patients.

A bibliometric analysis of macrophages associated with non-alcoholic fatty liver disease research from 2005 to 2023.

Non-alcoholic fatty liver disease (NAFLD) is a prevalent chronic liver condition associated with the risk of progressing to decompensated cirrhosis and hepatocellular carcinoma. While macrophages play a crucial role in the development of NAFLD, their heterogeneity and plasticity allow them to undertake diverse roles in immune response, tissue repair, and maintaining tissue homeostasis. Thus, the exact involvement of macrophages in the onset and progression of NAFLD remains to be further explored. This study aims to employ bibliometric analysis to elucidate the role of macrophages in the pathogenesis of NAFLD, analyze research focal points in this domain, and speculate on future research trends. The literature search, conducted using the Web of Science Core Collection, encompassed articles and reviews related to macrophages and NAFLD published between 2005 and 2023. A bibliometric analysis of 1264 extracted publications was performed using VOSviewer 1.6.17 and Citespace 6.1. R2, evaluating parameters such as spatial and temporal distribution, authors, thematic categories, topic distribution, references, and keywords. The findings revealed a steady global increase in publications in this field, with the United States contributing the most followed by China. The University of California System produced the highest volume of publications, while the Journal of Hepatology had the highest impact factors among the top 10 publishing journals. Tacke Frank emerged as both the most prolific author and the most cited. Co-occurrence and burst analysis of keywords and references highlighted the hotspots in this research area, emphasizing the mechanisms of NAFLD pathogenesis, metabolic regulation, immune modulation, and oxidative stress. Maintaining hepatic homeostasis by liver macrophages and macrophage polarization were identified as trending research directions in this field. Based on the bibliometric analysis, continued attention toward NAFLD therapeutic research involving hepatic macrophages is anticipated. As the mechanisms underlying NAFLD pathogenesis are further elucidated, the development of more treatment approaches related to macrophage immunology and metabolic regulation may expand therapeutic options. This study offers valuable insights into the current state and future trends in the field, providing beneficial guidance to researchers aiming to make significant contributions.

Chromosome-level genome assembly of navel orange cv. Gannanzao (Citrus sinensis Osbeck cv. Gannanzao).

Navel orange cv. Gannanzao is a variant of the navel orange cv. Newhall (Citrus sinensis Osbeck cv. Newhall) that exhibits an earlier maturation, making it commercially valuable. However, the mechanisms underlying its early maturation remain obscure. To address this question, we conducted genome sequencing and de novo assembly of navel orange cv. Gannanzao. The assembled genome sequence is 334.57 Mb in length with a GC content of 31.48%. It comprises 318 contigs (N50 = 3.23 Mb) and 187 scaffolds (N50 = 31.86 Mb). The Benchmarking Universal Single-Copy Orthologs test demonstrates 94.6% completeness. The annotation revealed 23,037 gene models, 164.95 Mb of repetitive sequences, and 2,554 noncoding RNAs. A comparative analysis identified 323 fruit ripening-related genes in navel orange cv. Gannanzao genome, while navel orange cv. Newhall genome contained 345 such genes. These genes were organized into 320 orthologous gene families, with 30.3% of them exhibiting differences in gene copy numbers between the 2 genomes. Additionally, we identified 15 fruit ripening-related genes that have undergone adaptive evolution, suggesting their potential role in advancing fruit maturation in navel orange cv. Gannanzao. Whole-genome sequencing and annotation of navel orange cv. Gannanzao provides a valuable resource to unravel the early maturation mechanism of citrus and enriches the genomic resources for citrus research.

Erratum: Citrus genomic resources unravel putative genetic determinants of Huanglongbing pathogenicity.

[This corrects the article DOI: 10.1016/j.isci.2023.106024.].

Current Progress and Challenges in Large-Scale 3D Mitochondria Instance Segmentation.

In this paper, we present the results of the MitoEM challenge on mitochondria 3D instance segmentation from electron microscopy images, organized in conjunction with the IEEE-ISBI 2021 conference. Our benchmark dataset consists of two large-scale 3D volumes, one from human and one from rat cortex tissue, which are 1,986 times larger than previously used datasets. At the time of paper submission, 257 participants had registered for the challenge, 14 teams had submitted their results, and six teams participated in the challenge workshop. Here, we present eight top-performing approaches from the challenge participants, along with our own baseline strategies. Posterior to the challenge, annotation errors in the ground truth were corrected without altering the final ranking. Additionally, we present a retrospective evaluation of the scoring system which revealed that: 1) challenge metric was permissive with the false positive predictions; and 2) size-based grouping of instances did not correctly categorize mitochondria of interest. Thus, we propose a new scoring system that better reflects the correctness of the segmentation results. Although several of the top methods are compared favorably to our own baselines, substantial errors remain unsolved for mitochondria with challenging morphologies. Thus, the challenge remains open for submission and automatic evaluation, with all volumes available for download.

Space-Time Super-Resolution for Light Field Videos.

Light field (LF) cameras suffer from a fundamental trade-off between spatial and angular resolutions. Additionally, due to the significant amount of data that needs to be recorded, the Lytro ILLUM, a modern LF camera, can only capture three frames per second. In this paper, we consider space-time super-resolution (SR) for LF videos, aiming at generating high-resolution and high-frame-rate LF videos from low-resolution and low-frame-rate observations. Extending existing space-time video SR methods to this task directly will meet two key challenges: 1) how to re-organize sub-aperture images (SAIs) efficiently and effectively given highly redundant LF videos, and 2) how to aggregate complementary information between multiple SAIs and frames considering the coherence in LF videos. To address the above challenges, we propose a novel framework for space-time super-resolving LF videos for the first time. First, we propose a novel Multi-Scale Dilated SAI Re-organization strategy for re-organizing SAIs into auxiliary view stacks with decreasing resolution as the Chebyshev distance in the angular dimension increases. In particular, the auxiliary view stack with original resolution preserves essential visual details, while the down-scaled view stacks capture long-range contextual information. Second, we propose the Multi-Scale Aggregated Feature extractor and the Angular-Assisted Feature Interpolation module to utilize and aggregate information from the spatial, angular, and temporal dimensions in LF videos. The former aggregates similar contents from different SAIs and frames for subsequent reconstruction in a disparity-free manner at the feature level, whereas the latter interpolates intermediate frames temporally by implicitly aggregating geometric information. Compared to other potential approaches, experimental results demonstrate that the reconstructed LF videos generated by our framework achieve higher reconstruction quality and better preserve the LF parallax structure and temporal consistency. The implementation code is available at https://github.com/zeyuxiao1997/LFSTVSR.

Luteolin attenuates acute liver allograft rejection in rats by inhibiting T cell proliferation and regulating T cell subsets.

Allograft rejection continues to be a significant cause of morbidity and graft failure for liver transplant recipients. Existing immunosuppressive regimens have many drawbacks, thus safe and effective long-term immunosuppressive regimens are still required. Luteolin (LUT), a natural component found in many plants, has a variety of biological and pharmacological effects and shows good anti-inflammatory activity in inflammatory and autoimmune diseases. Nevertheless, it remains unclear how it affects acute organ rejection after allogeneic transplantation. In this study, a rat liver transplantation model was constructed to investigate the effect of LUT on acute rejection of organ allografts. We found that LUT significantly protected the structure and function of liver grafts, prolonged recipient rat survival, ameliorated T cell infiltration, and downregulated proinflammatory cytokines. Moreover, LUT inhibited the proliferation of CD4+ T cells and Th cell differentiation but increased the proportion of Tregs, which is the key to its immunosuppressive effect. In vitro, LUT also significantly inhibited CD4+ T cell proliferation and Th1 differentiation. There may be important implications for improving immunosuppressive regimens for organ transplantation as a result of this discovery.

A Convenient All-Cell Optical Imaging Method Compatible with Serial SEM for Brain Mapping.

The mammalian brain, with its complexity and intricacy, poses significant challenges for researchers aiming to understand its inner workings. Optical multilayer interference tomography (OMLIT) is a novel, promising imaging technique that enables the mapping and reconstruction of mesoscale all-cell brain atlases and is seamlessly compatible with tape-based serial scanning electron microscopy (SEM) for microscale mapping in the same tissue. However, currently, OMLIT suffers from imperfect coatings, leading to background noise and image contamination. In this study, we introduced a new imaging configuration using carbon spraying to eliminate the tape-coating step, resulting in reduced noise and enhanced imaging quality. We demonstrated the improved imaging quality and validated its applicability through a correlative light-electron imaging workflow. Our method successfully reconstructed all cells and vasculature within a large OMLIT dataset, enabling basic morphological classification and analysis. We also show that this approach can perform effectively on thicker sections, extending its applicability to sub-micron scale slices, saving sample preparation and imaging time, and increasing imaging throughput. Consequently, this method emerges as a promising candidate for high-speed, high-throughput brain tissue reconstruction and analysis. Our findings open new avenues for exploring the structure and function of the brain using OMLIT images.

Hue Guidance Network for Single Image Reflection Removal.

Reflection from glasses is ubiquitous in daily life, but it is usually undesirable in photographs. To remove these unwanted noises, existing methods utilize either correlative auxiliary information or handcrafted priors to constrain this ill-posed problem. However, due to their limited capability to describe the properties of reflections, these methods are unable to handle strong and complex reflection scenes. In this article, we propose a hue guidance network (HGNet) with two branches for single image reflection removal (SIRR) by integrating image information and corresponding hue information. The complementarity between image information and hue information has not been noticed. The key to this idea is that we found that hue information can describe reflections well and thus can be used as a superior constraint for the specific SIRR task. Accordingly, the first branch extracts the salient reflection features by directly estimating the hue map. The second branch leverages these effective features, which can help locate salient reflection regions to obtain a high-quality restored image. Furthermore, we design a new cyclic hue loss to provide a more accurate optimization direction for the network training. Experiments substantiate the superiority of our network, especially its excellent generalization ability to various reflection scenes, as compared with state-of-the-arts both qualitatively and quantitatively. Source codes are available at https://github.com/zhuyr97/HGRR.

Self-Distilled Hierarchical Network for Unsupervised Deformable Image Registration.

Unsupervised deformable image registration benefits from progressive network structures such as Pyramid and Cascade. However, existing progressive networks only consider the single-scale deformation field in each level or stage and ignore the long-term connection across non-adjacent levels or stages. In this paper, we present a novel unsupervised learning approach named Self-Distilled Hierarchical Network (SDHNet). By decomposing the registration procedure into several iterations, SDHNet generates hierarchical deformation fields (HDFs) simultaneously in each iteration and connects different iterations utilizing the learned hidden state. Specifically, hierarchical features are extracted to generate HDFs through several parallel gated recurrent units, and HDFs are then fused adaptively conditioned on themselves as well as contextual features from the input image. Furthermore, different from common unsupervised methods that only apply similarity loss and regularization loss, SDHNet introduces a novel self-deformation distillation scheme. This scheme distills the final deformation field as the teacher guidance, which adds constraints for intermediate deformation fields on deformation-value and deformation-gradient spaces respectively. Experiments on five benchmark datasets, including brain MRI and liver CT, demonstrate the superior performance of SDHNet over state-of-the-art methods with a faster inference speed and a smaller GPU memory. Code is available at https://github.com/Blcony/SDHNet.

A procedure in mice to obtain intact pituitary-infundibulum-hypothalamus preparations: a method to evaluate the reconstruction of hypothalamohypophyseal system.

PURPOSE: The histopathological study of brain tissue is a common method in neuroscience. However, efficient procedures to preserve the intact hypothalamic-pituitary brain specimens are not available in mice for histopathological study. METHOD: We describe a detailed procedure for obtaining mouse brain with pituitary-hypothalamus continuity. Unlike the traditional methods, we collect the brain via a ventral approach. We cut the intraoccipital synchondrosis, transection the endocranium of pituitary, broke the spheno-occipital synchondrosis, expose the posterior edge of pituitary, separate the trigeminal nerve, then the intact pituitary gland was preserved. RESULT: We report an more effective and practical method to obtain continuous hypothalamus -pituitary preparations based on the preserve of leptomeninges. COMPARED WITH THE EXISTING METHODS: Our procedure effectively protects the integrity of the fragile infundibulum preventing the pituitary from separating from the hypothalamus. This procedure is more convenient and efficient. CONCLUSION: We present a convenient and practical procedure to obtain intact hypothalamic-pituitary brain specimens for subsequent histopathological evaluation in mice.

Citrus genomic resources unravel putative genetic determinants of Huanglongbing pathogenicity.

Citrus HLB caused by Candidatus Liberibacter asiaticus is a pathogen-triggered immune disease. Here, we identified putative genetic determinants of HLB pathogenicity by integrating citrus genomic resources to characterize the pan-genome of accessions that differ in their response to HLB. Genome-wide association mapping and analysis of allele-specific expression between susceptible, tolerant, and resistant accessions further refined candidates underlying the response to HLB. We first developed a phased diploid assembly of Citrus sinensis 'Newhall' genome and produced resequencing data for 91 citrus accessions that differ in their response to HLB. These data were combined with previous resequencing data from 356 accessions for genome-wide association mapping of the HLB response. Genes determinants for HLB pathogenicity were associated with host immune response, ROS production, and antioxidants. Overall, this study has provided a significant resource of citrus genomic data and identified candidate genes to be further explored to understand the genetic determinants of HLB pathogenicity.

Astragalus polysaccharides alleviate type 1 diabetes via modulating gut microbiota in mice.

Type 1 diabetes (T1D) is a serious health problem that needs to be addressed worldwide. Astragalus polysaccharides (APS), the main chemical components of Astragali Radix, have anti-diabetic activity. As most plant polysaccharides are difficult to digest and absorb, we hypothesised that APS exert hypoglycaemic effects through the gut. This study intends to investigate the modulation of T1D associated with gut microbiota by neutral fraction of Astragalus polysaccharides (APS-1). T1D mice were induced with streptozotocin and then treated with APS-1 for 8 weeks. Fasting blood glucose levels were decreased and the insulin levels were increased in T1D mice. The results demonstrated that APS-1 improved gut barrier function by regulating ZO-1, Occludin and Claudin-1 expression, and reconstructed gut microbiota by increasing the relative abundance of Muribaculum, Lactobacillus and Faecalibaculum. In addition, APS-1 significantly increased the levels of acetic acid, propionic acid, butyric acid and inhibited the expression of pro-inflammatory factors IL-6 and TNF-α in T1D mice. Further exploration revealed that APS-1 alleviation of T1D may be associated with short-chain fatty acids (SCFAs)-producing bacteria, and that SCFAs binds to GPRs and HDACs proteins and modulate the inflammatory responses. In conclusion, the study supports the potential of APS-1 as a therapeutic agent for T1D.