DNMT1/miR-152-3p/SOS1 signaling axis promotes self-renewal and tumor growth of cancer stem-like cells derived from non-small cell lung cancer.

BACKGROUND: CSLCs(Cancer stem cell-like cells), which are central to tumorigenesis, are intrinsically influenced by epigenetic modifications. This study aimed to elucidate the underlying mechanism involving the DNMT1/miR-152-3p/SOS1 axis in regulating the self-renewal and tumor growth of LCSLCs (lung cancer stem-like cells). MATERIALS AND METHODS: Target genes of miR-152-3p were predicted using TargetScan Human 8.0. Self-renewal and tumor growth of LCSLC were compared in suspension-cultured non-small cell lung cancer (NSCLC) cell lines H460 and A549 cell-derived globe cells. Functional effects of the DNMT1/miR-152-3p/SOS1 axis were assessed through gain-of-function experiments in vitro and in vivo. Additionally, luciferase reporter assays were employed to analyze the interaction among DNMT1, miR-152-3p, and SOS1. RESULTS: Our findings highlight a negative interaction between DNMT1 and miR-152-3p, resulting in reduced miR-152-3p level. This, in turn, leads to the alleviation of the inhibitory effect of miR-152-3p on the target gene SOS1, ultimately activating SOS1 and playing an essential role in self-renewal and tumor growth of LCSLC. However, the alteration of SOS1 does not affect DNMT1/miR-152-3p regulation. Therefore, it is reasonable to infer that the DNMT1/miR-152-3p negative feedback loop critically sustains self-renewal and tumor growth of LCSLC through SOS1. CONCLUSIONS: This study reveals a novel mechanism underpinning self-renewal and tumor growth of CSLC (cancer stem cell) in NSCLC and identifies potential therapeutic targets for NSCLC treatment.

Nonreciprocal magnon blockade based on nonlinear effects.

We present an alternative scheme to achieve nonreciprocal unconventional magnon blockade (NUMB) in a hybrid system formed by two microwave cavities and one yttrium iron garnet (YIG) sphere, where the pump and signal cavities interact nonlinearly with each other and the signal cavity is coupled to the YIG sphere. It is found that the nonlinear coupling occurs between the pump cavity and magnon modes due to the dispersive interactions among three bosonic modes. Meanwhile, the Kerr nonlinearity is present in the pump cavity. Based on these nonlinear effects, a nonreciprocal magnon blockade could be achieved with the help of the weak parametric driving of the pump cavity. The present work provides an alternative method to prepare single magnon resource, which may be helpful for quantum information processing.

Inducible IL-2 production and IL-2+ cell expansion are landmark events for T-cell activation of teleost.

As a multipotent cytokine, interleukin (IL)-2 plays important roles in activation, differentiation and survival of the lymphocytes. Although biological characteristics and function of IL-2 have been clarified in several teleost species, evidence regarding IL-2 production at the cellular and protein levels is still scarce in fish due to the lack of reliable antibody. In this study, we developed a mouse anti-Nile tilapia IL-2 monoclonal antibody (mAb), which could specifically recognize IL-2 protein and identify IL-2-producing lymphocytes of tilapia. Using this mAb, we found that CD3+ T cells, but not CD3- lymphocytes, are the main cellular source of IL-2 in tilapia. Under resting condition, both CD3+CD4-1+ T cells and CD3+CD4-1- T cells of tilapia produce IL-2. Moreover, the IL-2 protein level and the frequency of IL-2+ T cells significantly increased once T cells were activated by phytohemagglutinin (PHA) or CD3 plus CD28 mAbs in vitro. In addition, Edwardsiella piscicida infection also induces the IL-2 production and the expansion of IL-2+ T cells in the spleen lymphocytes. These findings demonstrate that IL-2 takes part in the T-cell activation and anti-bacterial adaptive immune response of tilapia, and can serve as an important marker for T-cell activation of teleost fish. Our study has enriched the knowledge regarding T-cell response in fish species, and also provide novel perspective for understanding the evolution of adaptive immune system.

Benchmarking Supervised and Self-Supervised Learning Methods in A Large Ultrasound Muti-task Images Dataset.

Deep learning in ultrasound(US) imaging aims to construct foundational models that accurately reflect the modality's unique characteristics. Nevertheless, the limited datasets and narrow task types have restricted this field in recent years. To address these challenges, we introduce US-MTD120K, a multi-task ultrasound dataset with 120,354 real-world two-dimensional images. This dataset covers three standard plane recognition and two diagnostic tasks in ultrasound imaging, providing a rich basis for model training and evaluation. We detail the data collection, distribution, and labelling processes, ensuring a thorough understanding of the dataset's structure. Furthermore, we conduct extensive benchmark tests on 27 state-of-the-art methods from both supervised and self-supervised learning(SSL) perspectives. In the realm of supervised learning, we analyze the sensitivity of two main feature computation methods to ultrasound images at the representational level, highlighting that models which judiciously constrain global feature computation could potentially serve as a viable analytical approach for US image analysis. In the context of self-supervised learning, we delved into the modelling process of self-supervised learning models for medical images and proposed an improvement strategy, named MoCo-US, a solution that addresses the excessive reliance on pretext task design from the input side. It achieves competitive performance with minimal pretext task design and enhances other SSL methods simply. The dataset and the code will be available at https://github.com/JsongZhang/CDOA-for-UMTD.

Fish Uses CTLA-4 Immune Checkpoint to Suppress mTORC1-Controlled T-Cell Glycolysis and Immunity.

As an immune checkpoint, cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) suppresses the activation, proliferation, and effector function of T cells, thus preventing an overexuberant response and maintaining immune homeostasis. However, whether and how this immune checkpoint functions in early vertebrates remains unknown. In the current study, using a Nile tilapia (Oreochromis niloticus) model, we investigated the suppression of T cell response by CTLA-4 in bony fish. Tilapia CTLA-4 is constitutively expressed in lymphoid tissues, and its mRNA and protein expression in lymphocytes are upregulated following PHA stimulation or Edwardsiella piscicida infection. Blockade of CTLA-4 signaling enhanced T cell activation and proliferation but inhibited activation-induced T cell apoptosis, indicating that CTLA-4 negatively regulated T cell activation. In addition, blocking CTLA-4 signaling in vivo increased the differentiation potential and cytotoxicity of T cells, resulting in an enhanced T cell response during E. piscicida infection. Tilapia CTLA-4 competitively bound the B7.2/CD86 molecule with CD28, thus antagonizing the CD28-mediated costimulatory signal of T cell activation. Furthermore, inhibition of mammalian/mechanistic target of rapamycin complex 1 (mTORC1) signaling, c-Myc, or glycolysis markedly impaired the CTLA-4 blockade-enhanced T cell response, suggesting that CTLA-4 suppressed the T cell response of tilapia by inhibiting mTORC1/c-Myc axis-controlled glycolysis. Overall, the findings indicate a detailed mechanism by which CTLA-4 suppresses T cell immunity in tilapia; therefore, we propose that early vertebrates have evolved sophisticated mechanisms coupling immune checkpoints and metabolic reprogramming to avoid an overexuberant T cell response.

SEG-LUS: A novel ultrasound segmentation method for liver and its accessory structures based on muti-head self-attention.

Although liver ultrasound (US) is quick and convenient, it presents challenges due to patient variations. Previous research has predominantly focused on computer-aided diagnosis (CAD), particularly for disease analysis. However, characterizing liver US images is complex due to structural diversity and a limited number of samples. Normal liver US images are crucial, especially for standard section diagnosis. This study explicitly addresses Liver US standard sections (LUSS) and involves detailed labeling of eight anatomical structures. We propose SEG-LUS, a US image segmentation model for the liver and its accessory structures. In SEG-LUS, we have adopted the shifted windows feature encoder combined with the cross-attention mechanism to adapt to capturing image information at different scales and resolutions and address context mismatch and sample imbalance in the segmentation task. By introducing the UUF module, we achieve the perfect fusion of shallow and deep information, making the information retained by the network in the feature extraction process more comprehensive. We have improved the Focal Loss to tackle the imbalance of pixel-level distribution. The results show that the SEG-LUS model exhibits significant performance improvement, with mPA, mDice, mIOU, and mASD reaching 85.05%, 82.60%, 74.92%, and 0.31, respectively. Compared with seven state-of-the-art semantic segmentation methods, the mPA improves by 5.32%. SEG-LUS is positioned to serve as a crucial reference for research in computer-aided modeling using liver US images, thereby advancing the field of US medicine research.

Interstitial pneumonia disease induced by osimertinib combined with savolitinib targeted therapy in a lung cancer patient: A case report.

RATIONALE: MET-TKI is a late-stage treatment for drug-resistant NSCLC that has been marketed in recent years, and interstitial lung disease may be a rare adverse reaction. This case reports the development of interstitial lung disease in a patient with advanced lung cancer who developed during treatment with savolitinib after resistance to osimertinib. PATIENT CONCERNS: A 74-year-old female diagnosed with lung adenocarcinoma was referred to our hospital with chest tightness and shortness of breath following treatment with osimertinib plus savolitinib. DIAGNOSE: Chest CT of the patient shows interstitial changes in both lungs, and drug-related interstitial lung disease is considered in the context of the patient previous condition. INTERVENTIONS: The patient is treated with methods such as glucocorticoids, anti-infection, and mechanical ventilation. OUTCOMES: At the 1-year follow-up visit, the patient condition of interstitial lung disease was relatively stable. The patient has passed away due to tumor progression. LESSONS: This case reported interstitial lung disease following osimertinib plus savolitinib. This suggests that healthcare providers should be aware of early symptoms of interstitial lung disease during treatment and treat them appropriately to prevent symptoms from worsening.

Full T-cell activation and function in teleosts require collaboration of first and co-stimulatory signals.

Mammalian T-cell responses require synergism between the first signal and co-stimulatory signal. However, whether and how dual signaling regulates the T-cell response in early vertebrates remains unknown. In the present study, we discovered that the Nile tilapia ( Oreochromis niloticus) encodes key components of the LAT signalosome, namely, LAT, ITK, GRB2, VAV1, SLP-76, GADS, and PLC-γ1. These components are evolutionarily conserved, and CD3ε mAb-induced T-cell activation markedly increased their expression. Additionally, at least ITK, GRB2, and VAV1 were found to interact with LAT for signalosome formation. Downstream of the first signal, the NF-κB, MAPK/ERK, and PI3K-AKT pathways were activated upon CD3ε mAb stimulation. Furthermore, treatment of lymphocytes with CD28 mAbs triggered the AKT-mTORC1 pathway downstream of the co-stimulatory signal. Combined CD3ε and CD28 mAb stimulation enhanced ERK1/2 and S6 phosphorylation and elevated NFAT1, c-Fos, IL-2, CD122, and CD44 expression, thereby signifying T-cell activation. Moreover, rather than relying on the first or co-stimulatory signal alone, both signals were required for T-cell proliferation. Full T-cell activation was accompanied by marked apoptosis and cytotoxic responses. These findings suggest that tilapia relies on dual signaling to maintain an optimal T-cell response, providing a novel perspective for understanding the evolution of the adaptive immune system.

Correlations between APACHE-II score and pressure parameters of mechanical ventilation in patients with ARDS and their value in prognostic evaluation.

Objective: To investigate the correlations between APACHE-II score and pressure parameters of mechanical ventilation in patients with acute respiratory distress syndrome (ARDS) and their value in prognostic evaluation. Methods: This was a retrospective study. The clinical data of 79 patients with ARDS treated in Shengzhou Hospital of Traditional Chinese Medicine from April 2020 to April 2022 were analyzed retrospectively. According to whether their APACHE-II scores were higher than 15, they were divided into low score group (n= 20) and high score group (n= 59). The plateau pressure (Pplat), driving pressure(ΔP) and mean airway pressure (Pmean) were compared. The correlation between APACHE-II score and pressure parameters of mechanical ventilation was analyzed. Based on the follow-up of 28-d survival, their Pplat, ΔP, Pmean and APACHE-II scores were compared. The value of APACHE-II score and pressure parameters in the prognostic evaluation of ARDS patients was analyzed. Results: Pplat, ΔP and Pmean in the low score group were significantly lower than those in the high score group(P<0.05). Pplat, ΔP, Pmean and APACHE-II score in the survival group were significantly lower than those in the control group(P<0.05). APACHE-II score showed significantly positive correlations with Pplat, ΔP and Pmean. The AUC of Pmean, Pplat, ΔP and APACHE-II score in predicting the prognosis and diagnosis of ARDS patients was 0.761, 0.833, 0.754 and 0.832, respectively. Conclusion: APACHE-II score of ARDS patients shows significantly positive correlations with pressure parameters of mechanical ventilation, and has diagnostic value for the prognosis of ARDS patients.

Micro SleepNet: efficient deep learning model for mobile terminal real-time sleep staging.

The real-time sleep staging algorithm that can perform inference on mobile devices without burden is a prerequisite for closed-loop sleep modulation. However, current deep learning sleep staging models have poor real-time efficiency and redundant parameters. We propose a lightweight and high-performance sleep staging model named Micro SleepNet, which takes a 30-s electroencephalography (EEG) epoch as input, without relying on contextual signals. The model features a one-dimensional group convolution with a kernel size of 1 × 3 and an Efficient Channel and Spatial Attention (ECSA) module for feature extraction and adaptive recalibration. Moreover, the model efficiently performs feature fusion using dilated convolution module and replaces the conventional fully connected layer with Global Average Pooling (GAP). These design choices significantly reduce the total number of model parameters to 48,226, with only approximately 48.95 Million Floating-point Operations per Second (MFLOPs) computation. The proposed model is conducted subject-independent cross-validation on three publicly available datasets, achieving an overall accuracy of up to 83.3%, and the Cohen Kappa is 0.77. Additionally, we introduce Class Activation Mapping (CAM) to visualize the model's attention to EEG waveforms, which demonstrate the model's ability to accurately capture feature waveforms of EEG at different sleep stages. This provides a strong interpretability foundation for practical applications. Furthermore, the Micro SleepNet model occupies approximately 100 KB of memory on the Android smartphone and takes only 2.8 ms to infer one EEG epoch, meeting the real-time requirements of sleep staging tasks on mobile devices. Consequently, our proposed model has the potential to serve as a foundation for accurate closed-loop sleep modulation.

Prussian blue nano-enzyme-assisted photodynamic therapy effectively eradicates MRSA infection in diabetic mouse skin wounds.

Antibiotic therapy can induce the generation of severe bacterial resistance, further challenging the usability of currently available drugs and treatment options. Therefore, it is essential to develop new strategies to effectively eradicate drug-resistant bacteria. Herein, we have reported a combinational strategy for the eradication of drug-resistant bacteria by using chlorin e6 (Ce6) loaded Prussian blue nanoparticles (PB NPs). This nanocomplex showed strong catalase activity and photodynamic properties. In vitro experiments demonstrated that CPB-Ce6 NPs effectively kill MRSA by generating ROS under laser irradiation. Meanwhile, the nano-enzyme activity of CPB NPs can decompose H2O2 in the bacterial microenvironment to upregulate the O2 level, which in turn alleviates hypoxia in the microenvironment and improves the antibacterial effect of PDT. In vivo results demonstrated that CPB-Ce6 NPs with laser irradiation effectively cleared MRSA and promoted infected wound repair in a diabetic mouse model and normal mice through upregulating VEGF. Moreover, CPB-Ce6 NPs showed excellent biosafety profiles in vitro and in vivo. From our point of view, this PDT based on PB NPs with nano-enzyme activity may provide an effective treatment for infections associated with drug-resistant microbes and tissue repair.

First Description of the Breeding Biology of the Spectacled Fulvetta (Fulvetta ruficapilla sordidior) in Southwest China.

The Spectacled Fulvetta (Fulvetta ruficapilla sordidior) is an endemic bird species to the southwest mountains of China, distributing from 1250 to 2500 m in the widespread broadleaved evergreen forest and occasionally in secondary scrubs. The present study describes its breeding biology for the first time. Fieldwork was conducted in the springs of 2017 and 2018 on Humashan Mountain, a hill mainly covered by secondary forest located at the eastern marginal of Kunming, the capital of Yunnan Province in Southwest China. This bird was found to initiate egg-laying mainly in March, and most nestlings fledged in late April and May. There were 16 nests found in total, which were located mainly in the dense shrubs at a height of 0.99 ± 0.40 m (n = 15). Of the 11 active nests, clutch size averaged 2.73 ± 0.45 (n = 11). Focal observations were made on nests; the incubation lasted for 13.67 ± 0.47 days (n = 3) with a notably high nest attendance, i.e., eggs were incubated 84.23% of the observation time. Nestlings fledged at 13.00 ± 0.71 days (n = 4), and parents feeding frequency increased as the nestlings grew. Overall, the cumulative hatching and fledgling rates were 71.43% and 35.71%, resulting in a nesting success rate of 45.45%.

Dietary restriction to optimize T cell immunity is an ancient survival strategy conserved in vertebrate evolution.

Recent advances highlight a key role of transient fasting in optimizing immunity of human and mouse. However, it remains unknown whether this strategy is independently acquired by mammals during evolution or instead represents gradually evolved functions common to vertebrates. Using a tilapia model, we report that T cells are the main executors of the response of the immune system to fasting and that dietary restriction bidirectionally modulates T cell immunity. Long-term fasting impaired T cell immunity by inducing intense autophagy, apoptosis, and aberrant inflammation. However, transient dietary restriction triggered moderate autophagy to optimize T cell response by maintaining homeostasis, alleviating inflammation and tissue damage, as well as enhancing T cell activation, proliferation and function. Furthermore, AMPK is the central hub linking fasting and autophagy-controlled T cell immunity in tilapia. Our findings demonstrate that dietary restriction to optimize immunity is an ancient strategy conserved in vertebrate evolution, providing novel perspectives for understanding the adaptive evolution of T cell response.

Identification of a cuproptosis and copper metabolism gene-related lncRNAs prognostic signature associated with clinical and immunological characteristics of hepatocellular carcinoma.

Background: The relationship between cuproptosis and HCC is still in the exploratory stage. Long noncoding RNAs (lncRNAs) have recently been linked to the progression of hepatocellular carcinoma (HCC). However, the clinical significance of lncRNAs associated with cuproptosis remains unclear. Methods: Based on The Cancer Genome Atlas (TCGA) liver hepatocellular carcinoma (LIHC) dataset, we identified characteristic prognostic lncRNAs by univariate, LASSO, and multifactorial regression analysis, and constructed a prognostic signature of cuproptosis-related lncRNAs in HCC. The role of lncRNAs were identified through CCK-8, clone formation in Huh-7 cells with high expression of FDX1. Prognostic potential of the characteristic lncRNAs was evaluated in each of the two cohorts created by randomly dividing the TCGA cohort into a training cohort and a test cohort in a 1:1 ratio. Immune profiles in defined subgroups of cuproptosis-related lncRNA features as well as drug sensitivity were analyzed. Results: We constructed a multigene signature based on four characteristic prognostic lncRNAs (AL590705.3, LINC02870, KDM4A-AS1, MKLN1-AS). These four lncRNAs participated in the development of cuproptosis. HCC patients were classified into high-risk and low-risk groups based on the median value of the risk score. The receiver operating characteristic curve area under the curve values for 1-, 3-, and 5-year survival were 0.773, 0.728, and 0.647, respectively, for the training cohort, and 0.764, 0.671, and 0.662, respectively, for the test cohort. Univariate and multifactorial regression analyses indicated that this prognostic feature was an independent prognostic factor for HCC. Principal component analysis plots clearly distinguished between low- and high-risk patients in terms of their probability of survival. Furthermore, gene set enrichment analysis showed that a variety of processes associated with tumor proliferation and progression were enriched in the high-risk group compared with the low-risk group. Moreover, there were significant differences in the expression of immune cell subpopulations, immune checkpoint genes, and potential drug screening, which provided distinct therapeutic recommendations for individuals with various risks. Conclusions: We constructed a novel cuproptosis-associated lncRNA signature with a significant predictive value for the prognosis of patients with HCC. Cuproptosis-associated lncRNAs are associated with the tumor immune microenvironment of HCC and even the efficacy of tumor immunotherapy.

Vehicle crash simulations for safety: Introduction of connected and automated vehicles on the roadways.

Traffic accidents are one main cause of human fatalities in modern society. With the fast development of connected and autonomous vehicles (CAVs), there comes both challenges and opportunities in improving traffic safety on the roads. While on-road tests are limited due to their high cost and hardware requirements, simulation has been widely used to study traffic safety. To make the simulation as realistic as possible, real-world crash data such as crash reports could be leveraged in the creation of the simulation. In addition, to enable such simulations to capture the complexity of traffic, especially when both CAVs and human-driven vehicles co-exist on the road, careful consideration needs to be given to the depiction of human behaviors and control algorithms of CAVs and their interactions. In this paper, the authors reviewed literature that is closely related to crash analysis based on crash reports and to simulation of mixed traffic when CAVs and human-driven vehicles co-exist, for studying traffic safety. Three main aspects are examined based on our literature review: data source, simulation methods, and human factors. It was found that there is an abundance of research in the respective areas, namely, crash report analysis, crash simulation studies (including vehicle simulation, traffic simulation, and driving simulation), and human factors. However, there is a lack of integration between them. Future research is recommended to integrate and leverage different state-of-the-art transportation-related technologies to contribute to road safety by developing an all-in-one-step crash analysis system.

Porcine Epidemic Diarrhea Virus nsp7 Inhibits MDA5 Dephosphorylation to Antagonize Type I Interferon Production.

Porcine epidemic diarrhea virus (PEDV) is a reemerging enteropathogenic coronavirus that causes high mortality in piglets and has catastrophic effects on the global pig industry. PEDV-encoded nonstructural protein 7 (nsp7) is an important component of the viral replication and transcription complex, and a previous study reported that it inhibits poly(I:C)-induced type I interferon (IFN) production, but the mechanism by which this occurs remains unclear. Here, we demonstrated that ectopic expression of PEDV nsp7 antagonized Sendai virus (SeV)-induced interferon beta (IFN-ß) production, as well as the activation of transcription factors interferon regulatory factor 3 (IRF3) and nuclear factor-kappa B (NF-κB) in both HEK-293T and LLC-PK1 cells. Mechanistically, PEDV nsp7 targets melanoma differentiation-associated gene 5 (MDA5) and interacts with its caspase activation and recruitment domains (CARDs), which sequester the interactions between MDA5 and the protein phosphatase 1 (PP1) catalytic subunits (PP1α and PP1γ), thereby suppressing MDA5 S828 dephosphorylation and keeping MDA5 inactive. Furthermore, PEDV infection attenuated MDA5 multimerization and MDA5-PP1α/-γ interactions. We also tested the nsp7 orthologs of five other mammalian coronaviruses and found that all of them except severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nsp7 inhibited MDA5 multimerization and SeV- or MDA5-induced IFN-ß production. Collectively, these results suggest that the inhibition of MDA5 dephosphorylation and multimerization may be a common strategy employed by PEDV and some other coronaviruses to antagonize MDA5-mediated IFN production. IMPORTANCE Since late 2010, a reemerging porcine epidemic diarrhea virus variant with high pathogenesis has swept through most pig farms in many countries, resulting in significant economic losses. Coronavirus nonstructural protein 7 (nsp7), conserved within the family Coronaviridae, combines with nsp8 and nsp12 to form the viral replication and transcription complex that is indispensable for viral replication. However, the function of nsp7 in the infection and pathogenesis of coronaviruses remains largely unknown. Our present study demonstrates that PEDV nsp7 specifically competes with PP1 for binding MDA5 and impedes the PP1-mediated dephosphorylation of MDA5 at S828, thereby blocking MDA5-mediated IFN production, revealing the complex mechanism utilized by PEDV nsp7 to efficiently escape host innate immunity.

Ultra-Attention: Automatic Recognition of Liver Ultrasound Standard Sections Based on Visual Attention Perception Structures.

Acquisition of a standard section is a prerequisite for ultrasound diagnosis. For a long time, there has been a lack of clear definitions of standard liver views because of physician experience. The accurate automated scanning of standard liver sections, however, remains one of ultrasonography medicine's most important issues. In this article, we enrich and expand the classification criteria of liver ultrasound standard sections from clinical practice and propose an Ultra-Attention structured perception strategy to automate the recognition of these sections. Inspired by the attention mechanism in natural language processing, the standard liver ultrasound views will participate in the global attention algorithm as modular local images in computer vision of ultrasound images, which will significantly amplify small features that would otherwise go unnoticed. In addition to using the dropout mechanism, we also use a Part-Transfer Learning training approach to fine-tune the model's rate of convergence to increase its robustness. The proposed Ultra-Attention model outperforms various traditional convolutional neural network-based techniques, achieving the best known performance in the field with a classification accuracy of 93.2%. As part of the feature extraction procedure, we also illustrate and compare the convolutional structure and the Ultra-Attention approach. This analysis provides a reasonable view for future research on local modular feature capture in ultrasound images. By developing a standard scan guideline for liver ultrasound-based illness diagnosis, this work will advance the research on automated disease diagnosis that is directed by standard sections of liver ultrasound.

IL-10 Negatively Controls the Primary T Cell Response of Tilapia by Triggering the JAK1/STAT3/SOCS3 Axis That Suppresses NF-κB and MAPK/ERK Signaling.

The braking mechanisms to protect the host from tissue damage and inflammatory disease caused by an overexuberant immune response are common in many T cell subsets. However, the negative regulation of T cell responses and detailed mechanisms are not well understood in early vertebrates. In the current study, using a Nile tilapia (Oreochromis niloticus) model, we investigated the suppression of T cell immunity by IL-10. Tilapia encodes an evolutionarily conserved IL-10, whose expression in lymphocytes is markedly induced during the primary adaptive immune response against Aeromonas hydrophila infection. Activated T cells of tilapia produce IL-10, which in turn inhibits proinflammatory cytokine expression and suppresses PHA-induced T cell activation. Moreover, administration of IL-10 impairs the proliferation of tilapia T cells, reduces their potential to differentiate into Th subsets, and cripples the cytotoxic function, rendering the animals more vulnerable to pathogen attack. After binding to its receptor IL-10Ra, IL-10 activates the JAK1/STAT3 axis by phosphorylation and enhances the expression of the suppressor of cytokine signaling 3 (SOCS3), which in turn attenuates the activation of the NF-κB and MAPK/ERK signaling pathways, thus suppressing the T cell response of tilapia. Our findings elucidate a negative regulatory mechanism of T cell immunity in a fish species and support the notion that the braking mechanism of T cells executed through IL-10 existed prior to the divergence of the tetrapod lineage from teleosts. Therefore, this study, to our knowledge, provides a novel perspective on the evolution of the adaptive immune system.

The spike gating flow: A hierarchical structure-based spiking neural network for online gesture recognition.

Action recognition is an exciting research avenue for artificial intelligence since it may be a game changer in emerging industrial fields such as robotic visions and automobiles. However, current deep learning (DL) faces major challenges for such applications because of the huge computational cost and inefficient learning. Hence, we developed a novel brain-inspired spiking neural network (SNN) based system titled spiking gating flow (SGF) for online action learning. The developed system consists of multiple SGF units which are assembled in a hierarchical manner. A single SGF unit contains three layers: a feature extraction layer, an event-driven layer, and a histogram-based training layer. To demonstrate the capability of the developed system, we employed a standard dynamic vision sensor (DVS) gesture classification as a benchmark. The results indicated that we can achieve 87.5% of accuracy which is comparable with DL, but at a smaller training/inference data number ratio of 1.5:1. Only a single training epoch is required during the learning process. Meanwhile, to the best of our knowledge, this is the highest accuracy among the non-backpropagation based SNNs. Finally, we conclude the few-shot learning (FSL) paradigm of the developed network: 1) a hierarchical structure-based network design involves prior human knowledge; 2) SNNs for content-based global dynamic feature detection.

Activated T cells are the cellular source of IL-22 that enhances proliferation and survival of lymphocytes in Nile tilapia.

As a pleiotropic cytokine mainly secreted by CD4+ T cells, interleukin (IL)-22 plays an important role in immune regulation and infection elimination. Despite IL-22 homologues have been identified in non-mammal, whether and how IL-22 participates in the adaptive immune response of early vertebrates have not been fully addressed. In this study, we identified an evolutionarily conserved IL-22 from Nile tilapia Oreochromis niloticus (defined as OnIL-22), proved by its properties regarding sequence, gene structure, functional domain, tertiary structure and phylogeny. IL-22 was broadly expressed in lymphoid-related tissues of tilapia, and with relatively higher levels in skin, gill, intestine and liver. The expression of OnIL-22 in spleen lymphocytes was markedly induced at the adaptive immune stage after Streptococcus agalactiae infection. Moreover, once lymphocytes were activated by PMA plus ionomycin or T-cell specific mitogen PHA in vitro, OnIL-22 expression was obviously up-regulated at both mRNA and protein levels. These results thus suggest that activated T cells produce IL-22 to take part in the adaptive immune response of tilapia. Furthermore, treatment of lymphocytes with recombinant OnIL-22 increased the expression of genes related to proliferation and survival, and further promoted the proliferation and reduced the apoptosis of lymphocytes during bacterial infection or T-cell activation. These cellular effects of IL-22 seem to be associated with JAK1/STAT3 axis downstream of IL-22, because IL-22 application not only elevated the mRNA expression of JAK1 and STAT3, but also enhanced their phosphorylation in lymphocytes. Altogether, we suggest that activated T cells produce IL-22 to promote lymphocyte proliferation and survival probability via JAK1/STAT3 signaling pathway, thus participating in adaptive immune response of Nile tilapia. Our study therefore provides helpful perspective for understanding the function and mechanism of adaptive immune system in teleost.