NIK signaling axis regulates dendritic cell function in intestinal immunity and homeostasis.

Dendritic cells (DCs) play an integral role in regulating mucosal immunity and homeostasis, but the signaling network mediating this function of DCs is poorly defined. We identified the noncanonical NF-κB-inducing kinase (NIK) as a crucial mediator of mucosal DC function. DC-specific NIK deletion impaired intestinal immunoglobulin A (IgA) secretion and microbiota homeostasis, rendering mice sensitive to an intestinal pathogen, Citrobacter rodentium. DC-specific NIK was required for expression of the IgA transporter polymeric immunoglobulin receptor (pIgR) in intestinal epithelial cells, which in turn relied on the cytokine IL-17 produced by TH17 cells and innate lymphoid cells (ILCs). NIK-activated noncanonical NF-κB induced expression of IL-23 in DCs, contributing to the maintenance of TH17 cells and type 3 ILCs. Consistent with the dual functions of IL-23 and IL-17 in mucosal immunity and inflammation, NIK deficiency also ameliorated colitis induction. Thus, our data suggest a pivotal role for the NIK signaling axis in regulating DC functions in intestinal immunity and homeostasis.

Melatonin as an immunomodulator in CD19-targeting CAR-T cell therapy: managing cytokine release syndrome.

BACKGROUND: Chimeric antigen receptor CAR-T cell therapies have ushered in a new era of treatment for specific blood cancers, offering unparalleled efficacy in cases of treatment resistance or relapse. However, the emergence of cytokine release syndrome (CRS) as a side effect poses a challenge to the widespread application of CAR-T cell therapies. Melatonin, a natural hormone produced by the pineal gland known for its antioxidant and anti-inflammatory properties, has been explored for its potential immunomodulatory effects. Despite this, its specific role in mitigating CAR-T cell-induced CRS remains poorly understood. METHODS: In this study, our aim was to investigate the potential of melatonin as an immunomodulatory agent in the context of CD19-targeting CAR-T cell therapy and its impact on associated side effects. Using a mouse model, we evaluated the effects of melatonin on CAR-T cell-induced CRS and overall survival. Additionally, we assessed whether melatonin administration had any detrimental effects on the antitumor efficacy and persistence of CD19 CAR-T cells. RESULTS: Our findings demonstrate that melatonin effectively mitigated the severity of CAR-T cell-induced CRS in the mouse model, leading to improved overall survival outcomes. Remarkably, melatonin administration did not compromise the antitumor effectiveness or persistence of CD19 CAR-T cells, indicating its compatibility with therapeutic goals. These results suggest melatonin's potential as an immunomodulatory compound to alleviate CRS without compromising the therapeutic benefits of CAR-T cell therapy. CONCLUSION: The study's outcomes shed light on melatonin's promise as a valuable addition to the existing treatment protocols for CAR-T cell therapies. By attenuating CAR-T cell-induced CRS while preserving the therapeutic impact of CAR-T cells, melatonin offers a potential strategy for optimizing and refining the safety and efficacy profile of CAR-T cell therapy. This research contributes to the evolving understanding of how to harness immunomodulatory agents to enhance the clinical application of innovative cancer treatments.

High-power polarization-maintaining LP11-mode fiber laser based on long-period fiber grating for precise welding.

An LP11-mode output all-fiber laser was presented, utilizing long-period fiber gratings (LPFGs) and polarization-maintaining optical fiber (PMF). The LPFG was designed and fabricated, achieving a 90.56% efficiency in LP01 to LP11 mode conversion. Furthermore, the transmission stability of LP11-mode in the PMF was also explored, with the spatial mode overlap ratio exceeding 0.95. Ultimately, the high-power polarization-maintaining (PM) fiber laser, capable of the LP11 mode output, was constructed, with the output power of 600 W and the beam quality M2 of 2.84. During the process of welding a thick Al-plate, the LP11 fiber laser exhibits a notable 1.88 times greater depth of fusion compared to the commercial single-mode fiber laser, when operating at the laser welding head speed of 100 mm/s. For applications demanding non-circular symmetric high-order modes, this research holds substantial potential for widespread adoption within the field of industrial processing.

Diverse bacterial hosts and potential risk of antibiotic resistomes in ship ballast water revealed by metagenomic binning.

Ship ballast water promoting the long-range migration of antibiotic resistance genes (ARGs) has raised a great concern. This study attempted to reveal ARGs profile in ballast water and decipher their hosts and potential risk using metagenomic approaches. In total, 710 subtypes across 26 ARG types were identified among the ballast water samples from 13 ships of 11 countries and regions, and multidrug resistance genes were the most dominant ARGs. The composition of ARGs were obviously different across samples, and only 5% of the ARG subtypes were shared by all samples. Procrustes analysis showed the bacterial community contributed more than the mobile genetic elements (MGEs) in shaping the antibiotic resistome. Further, 79 metagenome-assembled genomes (46 genera belong to four phyla) were identified as ARG hosts, with predominantly affiliated with the Proteobacteria. Notably, potential human pathogens (Alcaligenes, Mycolicibacterium, Rhodococcus and Pseudomonas) were also recognized as the ARG hosts. Above 30% of the ARGs hosts contained the MGEs simultaneously, supporting a pronounced horizontal gene transfer capability. A total of 43 subtypes (six percent of overall ARGs) of ARGs were assessed with high-risk, of which 23 subtypes belonged to risk Rank I (including rsmA, ugd, etc.) and 20 subtypes to the risk Rank II (including aac(6)-I, sul1, etc.). In addition, antibiotic resistance risk index indicated the risk of ARGs in ballast water from choke points of maritime trade routes was significantly higher than that from other regions. Overall, this study offers insights for risk evaluation and management of antibiotic resistance in ballast water.

Regulation of B-1 cell numbers and B cell-mediated antibody production by Inpp4b.

T and B lymphocytes are crucial players in cellular and humoral immune responses. The development, activation and differentiation of T and B lymphocytes are regulated by the best characterized PI3K-PI (3,4,5) P3-AKT phosphoinositide signalling pathway. As a branch of the phosphoinositide signalling pathway, the lipid phosphatase INPP4B inhibits AKT activation through degrading the phosphoinositide signalling messenger PI (3,4) P2. However, the role of Inpp4b in T and B lymphocytes remains elusive. Here, we reported that Inpp4b was highly expressed in human and murine T- and B-1 lymphocytes. Despite its higher expression in T lymphocytes, neither T cell development and homeostasis nor in vitro T cell activation and CD4+ T cell differentiation were altered upon loss of Inpp4b. Interestingly, combined direct phenotype analysis of Inpp4b conventional knockout mice and adoptive transfer studies revealed that ablation of Inpp4b intrinsically reduced peritoneal B-1 cells rather B-2 cells. Moreover, Inpp4b deficiency led to impaired thymus independent (TI) and thymus dependent (TD) antigens-induced antibody production. Further in vitro analysis revealed that CD40-mediated B cell proliferation was impaired upon ablation of Inpp4b. Our findings reveal that Inpp4b is required in regulating B-1 cell numbers and B cell-mediated antibody production.

Anti-noise computational imaging using unsupervised deep learning.

Computational imaging enables spatial information retrieval of objects with the use of single-pixel detectors. By combining measurements and computational methods, it is possible to reconstruct images in a variety of situations that are challenging or impossible with traditional multi-pixel cameras. However, these systems typically suffer from significant loss of imaging quality due to various noises when the measurement conditions are single-photon detecting, undersampling and complicated. Here, we provide an unsupervised deep learning (UnDL) based anti-noise approach to deal with this problem. The proposed method does not require any clean experimental data to pre-train, so it effectively alleviates the difficulty of model training (especially for the biomedical imaging scene which is difficult to obtain training ground truth inherently). Our results show that an UnDL based imaging approach outperforms conventional single-pixel computational imaging methods considerably in reconstructing the target image against noise. Moreover, the well-trained model is generalized to image a real biological sample and can accurately image 64 × 64 resolution objects with a high speed of 20 fps at 5% sampling ratio. This method can be used in various solvers for general computational imaging and is expected to effectively suppress noises for high-quality biomedical imaging in generalizable complicated environments.

Icariin Ameliorates Alzheimer's Disease Pathology by Alleviating Myelin Injury in 3 × Tg-AD Mice.

Alzheimer's disease (AD) is a neurodegenerative disease characterized by excessive deposition of ß amyloid (Aß), hyperphosphorylation of tau protein, and neuronal cell death. Recent studies have shown that myelin cell damage, which leads to cognitive dysfunction, occurs before AD-related pathological changes. Here, we examine the effect of icariin (ICA), a prenylated flavonol glycoside, in improving cognitive function in AD model mice. ICA has been reported to exhibit cardiovascular protective functions and antiaging effects. In this study, we used 3 × Tg-AD mice as an AD model. The Morris water maze and Y maze tests were performed to assess the learning and memory of the mice. Immunofluorescence analysis of Aß1-42 deposition and myelin basic protein (MBP) expression in the mouse hippocampus was performed. Tau protein phosphorylation and MBP protein expression in the hippocampus were further analyzed by Western blotting. Myelin damage in the mouse optic nerve was evaluated by electron microscopy, and LFB staining was performed to assess myelin morphology in the mouse corpus callosum. MBP, Mpp5, and Egr2 transcript levels were quantified by qPCR. We observed that ICA treatment improved the learning and memory of 3 × Tg-AD mice and reduced Aß deposition and tau protein phosphorylation in the hippocampus. Moreover, this treatment protocol increased myelin-related gene expression and reduced myelin damage.

TRAF3 promotes ROS production and pyroptosis by targeting ULK1 ubiquitination in macrophages.

Disrupted mitochondrial function and reactive oxygen species (ROS) generation cause cellular damage and oxidative stress-induced macrophage inflammatory cell death. It remains unclear how mitochondrial dysfunction relates to inflammasome activation and pyroptotic cell death. In this study, we demonstrated that tumor necrosis factor receptor-associated factor 3 (TRAF3) regulates mitochondrial ROS production and promotes TLR agonist LPS plus nigericin (LPS/Ng)-induced inflammasome and pyroptosis in mouse primary macrophages and human monocyte THP-1 cells. Co-IP assays confirmed that TRAF3 forms a complex with TRAF2 and cIAP1 and mediates ubiquitin and degradation of Unc-51 like autophagy activating kinase 1 (ULK1). Moreover, knockdown of ULK1 in THP-1 cells significantly promoted LPS/Ng-induced inflammasome by activating caspase 1 and mature IL-1ß. Apoptosis inducing factor (AIF) translocation from mitochondrial to nuclear was observed in ULK1-deficient THP-1 cells under LPS/Ng stimulation, which mediates LPS/Ng-induced cell death in ULK1 deficient macrophages. In conclusion, this study identified a novel role of TRAF3 in regulation of ULK1 ubiquitination and inflammasome signaling and provided molecular mechanisms by which ubiquitination of ULK1 controls mitochondrial ROS production, inflammasome activity, and AIF-dependent pyroptosis.

Protective effect of α-asarone and ß-asarone on Aß -induced inflammatory response in PC12 cells and its.

To investigate effects of α-asarone and ß-asarone on induced PC12 cell injury and related mechanisms. Aß toxic injury cell model was induced by Aß in PC12 cells. PC12 cells were divided into blank control group, model control group, α-asarone group (0.5, 1.0, ß-asarone group (6.3, 12.5, vasoactive intestinal peptide (VIP) group, and VIP antagonist control group. Cell survival rate was detected by CCK-8 kit; cell apoptosis rate was detected by flow cytometry. The levels of inflammatory cytokines interleukin (IL)-1, , tumor necrosis factor (TNF)-α, oxidation-related inducible nitric oxide synthase (iNOS), nitric oxide (NO), apoptosis factors caspase-3 and p53 were detected by ELISA method. The expressions of C-Jun N-terminal kinase (JNK) and p38 mitogen-activated protein kinase (p38MAPK) were detected by Western blotting. Compared with model control group, cell survival rates of group, ß-asarone group and VIP group increased; the cell apoptosis rate decreased; levels of apoptosis-related factors caspase-3, p53, inflammatory factors IL-1, TNF-α decreased; IL-10 level increased; levels of oxidization-related factors iNOS and NO decreased; the expression of JNK and p38MAPK protein decreased (all <0.05). After VIP antagonist intervention, the survival rate of ß-asarone group decreased; apoptosis rate increased; apoptosis related factors caspase-3, p53, inflammatory factors IL-1, TNF-α increased; IL-10 decreased; oxidation related factors iNOS and NO increased; the expression of JNK and p38MAPK protein increased (all <0.05); while there were no significant changes in these indicators of α-asarone group (all >0.05). α-asarone and ß-asarone have protective effects on PC12 cell injury induced by Aß. ß-asarone may inhibit inflammatory factors and oxidation-related factors through promoting VIP secretion, regulating JNK/MAPK pathway, and reducing PC12 cell apoptosis; however, the effect of α-asarone may be not related to VIP secretion.

SP1-induced upregulation of lncRNA CTBP1-AS2 accelerates the hepatocellular carcinoma tumorigenesis through targeting CEP55 via sponging miR-195-5p.

As reported in many research, LncRNA CTBP1 divergent transcript (CTBP1-AS2) remarkably affects the progression of several tumors. However, the precise role and function of CTBP1-AS2 in hepatocellular carcinoma (HCC) remained unknown. We found that CTBP1-AS2 expressions were increased in HCC samples and cells. After treatment with microwave ablation (MWA), CTBP1-AS2 was distinctly up-regulated in residual HCC tissues compared with HCC samples. CTBP1-AS2 was upregulated under the induction of the nuclear transcription factor SP1. As revealed by the clinical assays, high CTBP1-AS2 expression usually related to lymph node metastasis, clinical stage and weaker prognosis specific to HCC patients. Functionally, CTBP1-AS2 knockdown suppressed HCC cells in terms of the proliferation, migration, invasion, chemotherapy resistance as well as EMT progress, but promoted apoptosis. Mechanistically, CTBP1-AS2 was a sponge of miR-195-5p for elevating CEP55 expression, a target of miR-195-5p, and thereby exhibited its oncogenic roles in HCC progression. Overall, an emerging regulatory mechanism of SP1/CTBP1-AS2/miR-195-5p/CEP55 axis was reported in the paper, which possibly served as a new therapeutic HCC treatment target.

Photon-limited single-pixel imaging.

Photon-limited imaging technique is desired in tasks of capturing and reconstructing images by detecting a small number of photons. However, it is still a challenge to achieve high photon-efficiency. Here, we propose a novel photon-limited imaging technique that explores the consistency of photon detection probability in a single pulse and light intensity distribution in a single-pixel correlated imaging system. We demonstrated theoretically and experimentally that our technique can reconstruct a high-quality 3D image by using only one pulse each frame, thereby achieving a high photon efficiency of 0.01 detected photons per pixel. Long-distance field experiments for 100 km cooperative target and 3 km practical target are conducted to verify its feasibility. Compared with the conventional single-pixel imaging, which requires hundreds or thousands of pulses per frame, our technique saves two orders of magnitude in the consumption of total light power and acquisition time.

Acori tatarinowii rhizoma extract ameliorates Alzheimer's pathological syndromes by repairing myelin injury and lowering Tau phosphorylation in mice.

It has been shown that Acori tatarinowii rhizoma (ATR) extract can improve cognitive functions in Alzheimer Diseas (AD) patients or animal models. In this study, we have examined the activity of ATR in 3×Tg-AD model mice with different comprehensive behavioral tests like the Morris water maze and Y-maze test assay for behavior. Moreover, we performed LFB staining for myelin determination in the AD model mouse. By analyzing different pathways, we determined key proteins that are beneficial for ameliorating AD syndrome in the mouse. Periluminally, ATR treatment improved the learning and memory ability that was determined by comprehensive behavioral tests. Moreover, treatment reduces the p-Tau accumulation in the 3×Tg-AD mouse and the level of p-Tau accumulation was at per with the wildtype control mouse and improves the myelin lining in 3×Tg-AD mouse. In conclusion, our results indicate that ATR-treatment can improve the learning ability of AD model mice and the hyperphosphorylation of Tau protein was decreased. ATR can protect myelin lining from damage in AD syndrome.

Acute toxicity evaluation of nanoparticles mixtures using luminescent bacteria.

As the application of nanoparticles (NPs) and their release to the environment has increased, it is important to verify their toxicity, with a special emphasis on particle solubilization and the interaction of NP mixtures. In the current study, a model luminescent bacteria, Vibrio fischeri, was employed to test the acute toxicity of individual NPs and their binary mixtures, including metal NPs (ZnNPs, CuNPs) and metal oxide NPs (ZnONPs, CuONPs). The independent action model was used to reflect the synergistic, additive, or antagonistic interactions of binary mixtures of these NPs. The results showed that the median effective concentration (EC50) inhibited the luminescence of V. fischeri were 20.5, 4.1, 11.6, and 118.7 mg L-1 for ZnNPs, CuNPs, ZnONPs, and CuONPs, respectively, suggesting that the toxicity of these NPs to V. fischeri were as the following order: CuNPs > ZnONPs > ZnNPs > CuONPs. The combined effect of NPs were found to be antagonistic for CuNPs-ZnONPs and CuNPs-CuONPs, synergistic for CuONPs-ZnNPs, CuNPs-ZnNPs, and ZnONPs-CuONPs, and additive for ZnNPs-ZnONPs, revealing a complex pattern of possible interactions. The differences of dissolved metal ions partly accounted for the different combined toxicity of binary mixtures of NPs. The findings have important implications for better understanding the true environmental risk of NP mixtures.

Photon-limited imaging through scattering medium based on deep learning.

Imaging under ultra-weak light conditions is affected by Poisson noise heavily. The problem becomes worse if a scattering media is present in the optical path. Speckle patterns detected under ultra-weak light condition carry very little information which makes it difficult to reconstruct the image. Off-the-shelf methods are no longer available in this condition. In this paper, we experimentally demonstrate the use of a deep learning network to reconstruct images through scattering media under ultra-weak light illumination. The weak light limitation of this method is analyzed. The random Poisson detection under weak light condition obtains partial information of the object. Based on this property, we demonstrated better performance of our method by enlarging the training dataset with multiple detections of the speckle patterns. Our results demonstrate that our approach can reconstruct images through scattering media from close to 1 detected signal photon per pixel (PPP) per image.

Image reconstruction through dynamic scattering media based on deep learning.

Under complex scattering conditions, it is very difficult to capture clear object images hidden behind the media by modelling the inverse problem. With regard to dynamic scattering media, the challenge increases. For solving the inverse problem, we propose a new class-specific image reconstruction algorithm. The method based on deep learning classifies blurred scattering images according to scattering conditions and then recovers to clear images hidden behind the media. The deep learning network is used to learn the mapping relationship between the object and the scattering image rather than characterizing the scattering media explicitly or parametrically. 25000 scattering images are obtained under five sets of dynamic scattering condition to verify the feasibility of the proposed method. In addition, the generalizability of the method has been verified successfully. Compared with common CNN method, it's confirmed that our algorithm has better performance in reconstructing higher-quality images. Furthermore, for a given scattering image with unknown scattering condition, the closest scattering condition information can be given by classification network, and then the corresponding clear image is restored by reconstruction network.

Ambient temperature-mediated enzymic activities and intestinal microflora in Lymantria dispar larvae.

To understand how ambient temperature affect the gypsy moth larvae, and provide a theoretical basis for pest control in different environments. Fourth instar gypsy moth larvae were incubating for 3 hr at 15℃, 20℃, 25℃, 30℃, 35℃, and 40℃, respectively. Afterward, digestive and antioxidant enzyme activities, total antioxidant capacity, and intestinal microflora community were analyzed to reveal how the caterpillars respond to ambient temperature stress. Results showed that both digestive and antioxidant enzymes were regulated by the ambient temperature. The optimum incubation temperatures of protease, amylase, trehalase, and lipase in gypsy moth larvae were 30℃, 25℃, and 20℃, respectively. When the incubation temperature was deviated optimum temperatures, digestive enzyme activities would be downregulated depending on the extent of temperature stress. In addition, glutathione S-transferase, peroxidase, catalase, and polyphenol oxidase would be activated under a sufferable temperature stress, but superoxide dismutase and carboxylesterase (CarE) would be inhibited. In addition, results showed that the top two abundant phyla were Proteobacteria and Firmicutes. The phylum Firmicutes abundance was decreased and phylum Proteobacteria abundance was increased by ambient temperature stress. Moreover, it suggested that gypsy moth caterpillars at different ambient temperature mainly differed from each other by Escherichia-Shigella and Bifidobacterium in control, Acinetobacter in T15, and Lactobacillus in T40, respectively.

Photon-limited face image super-resolution based on deep learning.

With one single photon camera (SPC), imaging under ultra weak-lighting conditions may have wide-ranging applications ranging from remote sensing to night vision, but it may seriously suffer from the problem of under-sampled inherent in SPC detection. Some approaches have been proposed to solve the under-sampled problem by detecting the objects many times to generate high-resolution images and performing noise reduction to suppress the Poission noise inherent in low-flux operation. To address the under-sampled problem more effectively, a new approach is developed in this paper to reconstruct high-resolution images with lower-noise by seamlessly integrating low-light-level imaging with deep learning. In our new approach, all the objects are detected only once by SPC, where a deep network is learned to reduce noise and reconstruct high-resolution images from the detected noisy under-sampled images. In order to demonstrate our proposal is feasible, we first select a special category to verify by experiment, which are human faces. Such deep network is able to recover high-resolution and lower-noise face images from new noisy under-sampled face images and the resolution can achieve 4× up-scaling factor. Our experimental results have demonstrated that our proposed method can generate high-quality images from only ~0.2 detected signal photon per pixel.

Photon efficiency of computational ghost imaging with single-photon detection.

Photon-limited imaging has significant application under extreme environments, in which the photon efficiency is an important parameter. In this paper, we investigate the photon efficiency of computational ghost imaging with single-photon detection. By exploiting the Poisson statistical characteristics of single-photon counting, the relationships between the photon efficiency and the signal-to-noise ratio of the retrieved image are theoretically obtained, and both are closely related to the distribution characteristics of target and spatial modulation in the ghost imaging framework. To verify the availability of the built theoretical model for the photon efficiency, a specific computational ghost imaging with a binary object and the first-photon imaging algorithm is rigorously demonstrated in theory and in experiment. Our investigation paves the way for optimization of photon-limited ghost imaging.

Single-photon-counting polarization ghost imaging.

We proposed a method for polarization ghost imaging based on single photon counting. With the time-correlated single-photon-counting technique, we can construct photon time distribution histograms and select a distance gate to accurately estimate the light intensity. Experiments are performed to realize discrimination of the object from the background of different materials in weak illumination. In the situation that ambient noise is significantly stronger than the signal, our method still can retrieve an image as ambient noise is mostly filtered out through distance gate selection. We suppose that our method may facilitate applications in remote target discrimination and biological imaging.

Object authentication based on compressive ghost imaging.

Ghost imaging is a transverse imaging technique that allows an object to be reconstructed using the correlation between a pair of light fields. As known, in ghost imaging configurations, a large number of realizations are usually required for reconstruction of the objects. To reduce the number of realizations, Chen et al. [Opt. Lett.38, 546-548 (2013)OPLEDP0146-959210.1364/OL.38.000546] demonstrated an object authentication method with computational ghost imaging using realizations of less than 5% of the Nyquist limit. In this paper, we have further improved this method using a "compressive sensing algorithm" instead of a "classical correlation algorithm in computational ghost imaging." As a result, the realizations for object authentication were further reduced from 5% of the Nyquist limit to 3% of the Nyquist limit.