Multiview Hilbert transformation in full-ring transducer array-based photoacoustic computed tomography

Based on the photoacoustic (PA) effect, PA tomography directly measures specific optical absorption, i.e., absorbed optical energy per unit volume. We recently developed a full-ring ultrasonic transducer array-based photoacoustic computed tomography (PACT) system for small-animal whole-body imaging. The system has a full-view detection angle and high in-plane resolution (∼100  μm). However, due to the bandpass frequency response of the piezoelectric transducer elements and the limited elevational detection coverage of the full-ring transducer array, the reconstructed images present bipolar (i.e., both positive and negative) pixel values, which cause ambiguities in image interpretation for physicians and biologists. We propose a multiview Hilbert transformation method to recover the unipolar initial pressure for full-ring PACT. The effectiveness of the proposed algorithm was first validated by numerical simulations and then demonstrated with ex vivo mouse brain structural imaging and in vivo mouse whole-body imaging

Community-Aware Efficient Graph Contrastive Learning via Personalized Self-Training

In recent years, graph contrastive learning (GCL) has emerged as one of the optimal solutions for various supervised tasks at the node level. However, for unsupervised and structure-related tasks such as community detection, current GCL algorithms face difficulties in acquiring the necessary community-level information, resulting in poor performance. In addition, general contrastive learning algorithms improve the performance of downstream tasks by increasing the number of negative samples, which leads to severe class collision and unfairness of community detection. To address above issues, we propose a novel Community-aware Efficient Graph Contrastive Learning Framework (CEGCL) to jointly learn community partition and node representations in an end-to-end manner. Specifically, we first design a personalized self-training (PeST) strategy for unsupervised scenarios, which enables our model to capture precise community-level personalized information in a graph. With the benefit of the PeST, we alleviate class collision and unfairness without sacrificing the overall model performance. Furthermore, the aligned graph clustering (AlGC) is employed to obtain the community partition. In this module, we align the clustering space of our downstream task with that in PeST to achieve more consistent node embeddings. Finally, we demonstrate the effectiveness of our model for community detection both theoretically and experimentally. Extensive experimental results also show that our CEGCL exhibits state-of-the-art performance on three benchmark datasets with different scales.Comment: 12 pages, 7 figure

PO-272 Cancer immunotherapy impedes skeletal muscle repair

Objective To observe the difference of the capacity of skeletal muscle repair and the corresponding immune response in melanoma mice treated with cancer immunotherapy after acute skeletal muscle contusion. Methods  96 males C57BL/6 mice were used in this experiment. They were divided into control group and injury group. The control group included normal control group (C group, n = 8), tumor control group (T group, n = 8) and tumor immunotherapy group (A group, n = 8).The skeletal muscle injury group was divided into normal injury group (D group, n = 24), tumor mice injury group (DT group, n = 24) and cancer immunotherapy injury group (DA group, n = 24). B16 cells were injected subcutaneously into the dorsum of C57/BL mice to prepare melanoma mice model. Immunotherapy is the injection of anti CTLA-4 and anti PD-1 antibodies. The model of gastrocnemius muscle contusion was established. At different time points after damage, mice were sacrificed. The gastrocnemius muscle of mice was made into cryosections. After HE staining and Mason staining, the regeneration of skeletal muscle and the healing of fibrotic scar were observed. The expression of CD8 T Cells and Regulatory T Cells (Treg) were detected by immunofluorescence. Results 1.H&E staining of muscle slices at 7 days after injury showed that myofibers in the non-injured muscles are polygonal in shape with peripheral nuclei. Quantitative evaluation of the skeletal muscle in the cancer immunotherapy injury group (DA group) showed that the number of centrally nucleated fibers was significantly lower than that in the other injury groups（D group，DT group）and there was an enlarged interstitial space. Immunotherapy leads to greater muscle degeneration: vacuolated myofibers could be seen. Collagen deposition was detected by Masson trichrome staining, and collagen deposits were found in the injury group. However, the regenerated muscles of the cancer immunotherapy injury group (DA group) showed more collagen deposits than those of the other injury groups（D group，DT group）, no collagen deposits were found in the control group. On 14 day after injury, the density of muscle fibers in the other injury groups（D group，DT group） was higher than that in immunotherapy group (DA group), which was about 1.5 times of that in immunotherapy group (DA group). The other injury groups（D group，DT group） showed a larger proportion of regenerated muscle fibers with different diameters, whereas the cancer immunotherapy injury group (DA group) had fewer regenerated muscle fibers. Compared with the control group, the mice in the other injury groups（D group，DT group）still had a small amount of collagen deposits, the mice in the cancer immunotherapy injury group (DA group) had more collagen deposits. 3.On 21 day after injury, the average diameter on 21 day higher than that on day 7 in the three injury groups. The mean muscle fiber diameter in the other injury groups（D group，DT group） was significantly larger than that in the immunotherapy injury group. In addition, the regenerated muscle fibers in the other injury groups（D group，DT group） showed better organization and basically returned to normal compared with the immunotherapy group (DA group). There were still some collagen deposits in the immunotherapy group (DA group) mice, but no collagen deposits were found in the other injury groups（D group，DT group）mice. 4.Immunofluorescence staining showed that CD8 T cells were continuously expressed and no Treg cells were found in the immunotherapy group (DA group) mice at 7, 14 and 21 days after contusion. In the other injury groups（D group，DT group）, Treg and CD8 T cells were expressed in skeletal muscle tissue adjacent to the regenerated muscle fibers on 7 days. On day 14, a small number of CD8 T cells and a large number of Treg cells infiltrated the damaged muscles. On day 21, almost no CD8 T cells were detected, and Treg cells continued to express. There was no expression of Treg cells and CD8 T cells in the control group. Conclusions Cancer immunotherapy will delay the repair of damaged skeletal muscle and reduce the capacity of skeletal muscle repair and regeneration. &nbsp

CLR: Channel-wise Lightweight Reprogramming for Continual Learning

Continual learning aims to emulate the human ability to continually accumulate knowledge over sequential tasks. The main challenge is to maintain performance on previously learned tasks after learning new tasks, i.e., to avoid catastrophic forgetting. We propose a Channel-wise Lightweight Reprogramming (CLR) approach that helps convolutional neural networks (CNNs) overcome catastrophic forgetting during continual learning. We show that a CNN model trained on an old task (or self-supervised proxy task) could be ``reprogrammed" to solve a new task by using our proposed lightweight (very cheap) reprogramming parameter. With the help of CLR, we have a better stability-plasticity trade-off to solve continual learning problems: To maintain stability and retain previous task ability, we use a common task-agnostic immutable part as the shared ``anchor" parameter set. We then add task-specific lightweight reprogramming parameters to reinterpret the outputs of the immutable parts, to enable plasticity and integrate new knowledge. To learn sequential tasks, we only train the lightweight reprogramming parameters to learn each new task. Reprogramming parameters are task-specific and exclusive to each task, which makes our method immune to catastrophic forgetting. To minimize the parameter requirement of reprogramming to learn new tasks, we make reprogramming lightweight by only adjusting essential kernels and learning channel-wise linear mappings from anchor parameters to task-specific domain knowledge. We show that, for general CNNs, the CLR parameter increase is less than 0.6\% for any new task. Our method outperforms 13 state-of-the-art continual learning baselines on a new challenging sequence of 53 image classification datasets. Code and data are available at https://github.com/gyhandy/Channel-wise-Lightweight-ReprogrammingComment: ICCV 202

The change of non-alcoholic fatty liver disease is associated with risk of incident diabetes

Background & aimsThe effect of change in non-alcoholic fatty liver disease (NAFLD) status on incident diabetes has not been well studied. We aimed to investigate the association of NAFLD development and remission with the risk of incident diabetes during a median of 3.5-year follow-up.MethodsA total of 2690 participants without diabetes were recruited in 2011-2012 and assessed for incident diabetes in 2014. Abdominal ultrasonography was used to determine the change of NAFLD. 75 g oral glucose tolerance test (OGTT) was performed to determine diabetes. NAFLD severity was assessed using Gholam’s model. The odds ratios (ORs) for incident diabetes were estimated by logistic regression models.ResultsNAFLD was developed in 580 (33.2%) participants and NAFLD remission occurred in 150 (15.9%) participants during a median of 3.5-year follow-up. A total of 484 participants developed diabetes during follow-up, including 170 (14.6%) in consistent non-NAFLD group, 111 (19.1%) in NAFLD developed group, 19 (12.7%) in NAFLD remission group, and 184 (23.2%) in sustained NAFLD group. The development of NAFLD increased the risk of incident diabetes by 43% (OR, 1.43; 95%CI, 1.10-1.86) after adjustment for multiple confounders. Compared with sustained NAFLD group, remission of NAFLD reduced the risk of incident diabetes by 52% (OR, 0.48; 95%CI, 0.29-0.80). The effect of NAFLD alteration on incident diabetes was not changed after adjustment for body mass index or waist circumference, change of body mass index or waist circumference. In NAFLD remission group, participants with non-alcoholic steatohepatitis (NASH) at baseline were more likely to develop diabetes (OR, 3.03; 95%CI, 1.01-9.12).ConclusionsNAFLD development increases the risk of incident diabetes, whereas NAFLD remission reduces the risk of incident diabetes. Moreover, presence of NASH at baseline could attenuate the protective effect of NAFLD remission on incident diabetes. Our study suggests that early intervention of NAFLD and maintenance of non-NAFLD are important for prevention of diabetes

Dichroism-sensitive photoacoustic computed tomography

Photoacoustic computed tomography (PACT), a fast-developing modality for deep tissue imaging, images the spatial distribution of optical absorption. PACT usually treats the absorption coefficient as a scalar. However, the absorption coefficients of many biological tissues exhibit an anisotropic property, known as dichroism or diattenuation, which depends on molecular conformation and structural alignment. Here, we present a novel imaging method called dichroism-sensitive PACT (DS-PACT), which measures both the amplitude of tissue’s dichroism and the orientation of the optic axis of uniaxial dichroic tissue. By modulating the polarization of linearly polarized light and measuring the alternating signals through lock-in detection, DS-PACT can boost dichroic signals from biological tissues. To validate the proposed approach, we experimentally demonstrated the performance of DS-PACT by imaging plastic polarizers and ex vivo bovine tendons deep inside scattering media. We successfully detected the orientation of the optic axis of uniaxial dichroic materials, even at a depth of 4.5 transport mean free paths. We anticipate that the proposed method will extend the capability of PACT to imaging tissue absorption anisotropy

Biological and genomic analysis of a symbiotic nitrogen fixation defective mutant in Medicago truncatula

Medicago truncatula has been selected as one of the model legume species for gene functional studies. To elucidate the functions of the very large number of genes present in plant genomes, genetic mutant resources are very useful and necessary tools. Fast Neutron (FN) mutagenesis is effective in inducing deletion mutations in genomes of diverse species. Through this method, we have generated a large mutant resource in M. truncatula. This mutant resources have been used to screen for different mutant using a forward genetics methods. We have isolated and identified a large amount of symbiotic nitrogen fixation (SNF) deficiency mutants. Here, we describe the detail procedures that are being used to characterize symbiotic mutants in M. truncatula. In recent years, whole genome sequencing has been used to speed up and scale up the deletion identification in the mutant. Using this method, we have successfully isolated a SNF defective mutant FN007 and identified that it has a large segment deletion on chromosome 3. The causal deletion in the mutant was confirmed by tail PCR amplication and sequencing. Our results illustrate the utility of whole genome sequencing analysis in the characterization of FN induced deletion mutants for gene discovery and functional studies in the M. truncatula. It is expected to improve our understanding of molecular mechanisms underlying symbiotic nitrogen fixation in legume plants to a great extent

The diacylglycerol kinase α/Atypical PKC/β1 integrin pathway in SDF-1α mammary carcinoma invasiveness

Diacylglycerol kinase α (DGKα), by phosphorylating diacylglycerol into phosphatidic acid, provides a key signal driving cell migration and matrix invasion. We previously demonstrated that in epithelial cells activation of DGKα activity promotes cytoskeletal remodeling and matrix invasion by recruiting atypical PKC at ruffling sites and by promoting RCP-mediated recycling of α5β1 integrin to the tip of pseudopods. In here we investigate the signaling pathway by which DGKα mediates SDF-1α-induced matrix invasion of MDA-MB-231 invasive breast carcinoma cells. Indeed we showed that, following SDF-1α stimulation, DGKα is activated and localized at cell protrusion, thus promoting their elongation and mediating SDF-1α induced MMP-9 metalloproteinase secretion and matrix invasion. Phosphatidic acid generated by DGKα promotes localization at cell protrusions of atypical PKCs which play an essential role downstream of DGKα by promoting Rac-mediated protrusion elongation and localized recruitment of β1 integrin and MMP-9. We finally demonstrate that activation of DGKα, atypical PKCs signaling and β1 integrin are all essential for MDA-MB-231 invasiveness. These data indicates the existence of a SDF-1α induced DGKα - atypical PKC - β1 integrin signaling pathway, which is essential for matrix invasion of carcinoma cells