Dissecting embryonic and extraembryonic lineage crosstalk with stem cell co-culture.

Embryogenesis necessitates harmonious coordination between embryonic and extraembryonic tissues. Although stem cells of both embryonic and extraembryonic origins have been generated, they are grown in different culture conditions. In this study, utilizing a unified culture condition that activates the FGF, TGF-ß, and WNT pathways, we have successfully derived embryonic stem cells (FTW-ESCs), extraembryonic endoderm stem cells (FTW-XENs), and trophoblast stem cells (FTW-TSCs) from the three foundational tissues of mouse and cynomolgus monkey (Macaca fascicularis) blastocysts. This approach facilitates the co-culture of embryonic and extraembryonic stem cells, revealing a growth inhibition effect exerted by extraembryonic endoderm cells on pluripotent cells, partially through extracellular matrix signaling. Additionally, our cross-species analysis identified both shared and unique transcription factors and pathways regulating FTW-XENs. The embryonic and extraembryonic stem cell co-culture strategy offers promising avenues for developing more faithful embryo models and devising more developmentally pertinent differentiation protocols.

Kinome-wide siRNA screen identifies a DCLK2-TBK1 oncogenic signaling axis in clear cell renal cell carcinoma.

TANK-binding kinase 1 (TBK1) is a potential therapeutic target in multiple cancers, including clear cell renal cell carcinoma (ccRCC). However, targeting TBK1 in clinical practice is challenging. One approach to overcome this challenge would be to identify an upstream TBK1 regulator that could be targeted therapeutically in cancer specifically. In this study, we perform a kinome-wide small interfering RNA (siRNA) screen and identify doublecortin-like kinase 2 (DCLK2) as a TBK1 regulator in ccRCC. DCLK2 binds to and directly phosphorylates TBK1 on Ser172. Depletion of DCLK2 inhibits anchorage-independent colony growth and kidney tumorigenesis in orthotopic xenograft models. Conversely, overexpression of DCLK2203, a short isoform that predominates in ccRCC, promotes ccRCC cell growth and tumorigenesis in vivo. Mechanistically, DCLK2203 elicits its oncogenic signaling via TBK1 phosphorylation and activation. Taken together, these results suggest that DCLK2 is a TBK1 activator and potential therapeutic target for ccRCC.

Mapping cellular interactions from spatially resolved transcriptomics data.

Cell-cell communication (CCC) is essential to how life forms and functions. However, accurate, high-throughput mapping of how expression of all genes in one cell affects expression of all genes in another cell is made possible only recently through the introduction of spatially resolved transcriptomics (SRT) technologies, especially those that achieve single-cell resolution. Nevertheless, substantial challenges remain to analyze such highly complex data properly. Here, we introduce a multiple-instance learning framework, Spacia, to detect CCCs from data generated by SRTs, by uniquely exploiting their spatial modality. We highlight Spacia's power to overcome fundamental limitations of popular analytical tools for inference of CCCs, including losing single-cell resolution, limited to ligand-receptor relationships and prior interaction databases, high false positive rates and, most importantly, the lack of consideration of the multiple-sender-to-one-receiver paradigm. We evaluated the fitness of Spacia for three commercialized single-cell resolution SRT technologies: MERSCOPE/Vizgen, CosMx/NanoString and Xenium/10x. Overall, Spacia represents a notable step in advancing quantitative theories of cellular communications.

Modeling genotype-protein interaction and correlation for Alzheimer's disease: a multi-omics imaging genetics study.

Integrating and analyzing multiple omics data sets, including genomics, proteomics and radiomics, can significantly advance researchers' comprehensive understanding of Alzheimer's disease (AD). However, current methodologies primarily focus on the main effects of genetic variation and protein, overlooking non-additive effects such as genotype-protein interaction (GPI) and correlation patterns in brain imaging genetics studies. Importantly, these non-additive effects could contribute to intermediate imaging phenotypes, finally leading to disease occurrence. In general, the interaction between genetic variations and proteins, and their correlations are two distinct biological effects, and thus disentangling the two effects for heritable imaging phenotypes is of great interest and need. Unfortunately, this issue has been largely unexploited. In this paper, to fill this gap, we propose $\textbf{M}$ulti-$\textbf{T}$ask $\textbf{G}$enotype-$\textbf{P}$rotein $\textbf{I}$nteraction and $\textbf{C}$orrelation disentangling method ($\textbf{MT-GPIC}$) to identify GPI and extract correlation patterns between them. To ensure stability and interpretability, we use novel and off-the-shelf penalties to identify meaningful genetic risk factors, as well as exploit the interconnectedness of different brain regions. Additionally, since computing GPI poses a high computational burden, we develop a fast optimization strategy for solving MT-GPIC, which is guaranteed to converge. Experimental results on the Alzheimer's Disease Neuroimaging Initiative data set show that MT-GPIC achieves higher correlation coefficients and classification accuracy than state-of-the-art methods. Moreover, our approach could effectively identify interpretable phenotype-related GPI and correlation patterns in high-dimensional omics data sets. These findings not only enhance the diagnostic accuracy but also contribute valuable insights into the underlying pathogenic mechanisms of AD.

The innate immunity protein IFITM3 modulates γ-secretase in Alzheimer's disease.

Innate immunity is associated with Alzheimer's disease1, but the influence of immune activation on the production of amyloid-ß is unknown2,3. Here we identify interferon-induced transmembrane protein 3 (IFITM3) as a γ-secretase modulatory protein, and establish a mechanism by which inflammation affects the generation of amyloid-ß. Inflammatory cytokines induce the expression of IFITM3 in neurons and astrocytes, which binds to γ-secretase and upregulates its activity, thereby increasing the production of amyloid-ß. The expression of IFITM3 is increased with ageing and in mouse models that express familial Alzheimer's disease genes. Furthermore, knockout of IFITM3 reduces γ-secretase activity and the formation of amyloid plaques in a transgenic mouse model (5xFAD) of early amyloid deposition. IFITM3 protein is upregulated in tissue samples from a subset of patients with late-onset Alzheimer's disease that exhibit higher γ-secretase activity. The amount of IFITM3 in the γ-secretase complex has a strong and positive correlation with γ-secretase activity in samples from patients with late-onset Alzheimer's disease. These findings reveal a mechanism in which γ-secretase is modulated by neuroinflammation via IFITM3 and the risk of Alzheimer's disease is thereby increased.

Mapping developmental regionalization and patterns of cortical surface area from 29 post-menstrual weeks to 2 years of age.

Surface area of the human cerebral cortex expands extremely dynamically and regionally heterogeneously from the third trimester of pregnancy to 2 y of age, reflecting the spatial heterogeneity of the underlying microstructural and functional development of the cerebral cortex. However, little is known about the developmental patterns and regionalization of cortical surface area during this critical stage, due to the lack of high-quality imaging data and accurate computational tools for pediatric brain MRI data. To fill this critical knowledge gap, by leveraging 1,037 high-quality MRI scans with the age between 29 post-menstrual weeks and 24 mo from 735 pediatric subjects in two complementary datasets, i.e., the Baby Connectome Project (BCP) and the developing Human Connectome Project (dHCP), and state-of-the-art dedicated image-processing tools, we unprecedentedly parcellate the cerebral cortex into a set of distinct subdivisions purely according to the developmental patterns of the cortical surface. Our discovered developmentally distinct subdivisions correspond well to structurally and functionally meaningful regions and reveal spatially contiguous, hierarchical, and bilaterally symmetric patterns of early cortical surface expansion. We also show that high-order association subdivisions, where cortical folds emerge later during prenatal stages, undergo more dramatic cortical surface expansion during infancy, compared with the central regions, especially the sensorimotor and insula cortices, thus forming a distinct central-pole division in early cortical surface expansion. These results provide an important reference for exploring and understanding dynamic early brain development in health and disease.

HBV integrations reshaping genomic structures promote hepatocellular carcinoma.

OBJECTIVE: Hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC), mostly characterised by HBV integrations, is prevalent worldwide. Previous HBV studies mainly focused on a few hotspot integrations. However, the oncogenic role of the other HBV integrations remains unclear. This study aimed to elucidate HBV integration-induced tumourigenesis further. DESIGN: Here, we illuminated the genomic structures encompassing HBV integrations in 124 HCCs across ages using whole genome sequencing and Nanopore long reads. We classified a repertoire of integration patterns featured by complex genomic rearrangement. We also conducted a clustered regularly interspaced short palindromic repeat (CRISPR)-based gain-of-function genetic screen in mouse hepatocytes. We individually activated each candidate gene in the mouse model to uncover HBV integration-mediated oncogenic aberration that elicits tumourigenesis in mice. RESULTS: These HBV-mediated rearrangements are significantly enriched in a bridge-fusion-bridge pattern and interchromosomal translocations, and frequently led to a wide range of aberrations including driver copy number variations in chr 4q, 5p (TERT), 6q, 8p, 16q, 9p (CDKN2A/B), 17p (TP53) and 13q (RB1), and particularly, ultra-early amplifications in chr8q. Integrated HBV frequently contains complex structures correlated with the translocation distance. Paired breakpoints within each integration event usually exhibit different microhomology, likely mediated by different DNA repair mechanisms. HBV-mediated rearrangements significantly correlated with young age, higher HBV DNA level and TP53 mutations but were less prevalent in the patients subjected to prior antiviral therapies. Finally, we recapitulated the TONSL and TMEM65 amplification in chr8q led by HBV integration using CRISPR/Cas9 editing and demonstrated their tumourigenic potentials. CONCLUSION: HBV integrations extensively reshape genomic structures and promote hepatocarcinogenesis (graphical abstract), which may occur early in a patient's life.

Mapping Genetic Topography of Cortical Thickness and Surface Area in Neonatal Brains.

Adult twin neuroimaging studies have revealed that cortical thickness (CT) and surface area (SA) are differentially influenced by genetic information, leading to their spatially distinct genetic patterning and topography. However, the postnatal origins of the genetic topography of CT and SA remain unclear, given the dramatic cortical development from neonates to adults. To fill this critical gap, this study unprecedentedly explored how genetic information differentially regulates the spatial topography of CT and SA in the neonatal brain by leveraging brain magnetic resonance (MR) images from 202 twin neonates with minimal influence by the complicated postnatal environmental factors. We capitalized on infant-dedicated computational tools and a data-driven spectral clustering method to parcellate the cerebral cortex into a set of distinct regions purely according to the genetic correlation of cortical vertices in terms of CT and SA, respectively, and accordingly created the first genetically informed cortical parcellation maps of neonatal brains. Both genetic parcellation maps exhibit bilaterally symmetric and hierarchical patterns, but distinct spatial layouts. For CT, regions with closer genetic relationships demonstrate an anterior-posterior (A-P) division, while for SA, regions with greater genetic proximity are typically within the same lobe. Certain genetically informed regions exhibit strong similarities between neonates and adults, with the most striking similarities in the medial surface in terms of SA, despite their overall substantial differences in genetic parcellation maps. These results greatly advance our understanding of the development of genetic influences on the spatial patterning of cortical morphology.SIGNIFICANCE STATEMENT Genetic influences on cortical thickness (CT) and surface area (SA) are complex and could evolve throughout the lifespan. However, studies revealing distinct genetic topography of CT and SA have been limited to adults. Using brain structural magnetic resonance (MR) images of twins, we unprecedentedly discovered the distinct genetically-informed parcellation maps of CT and SA in neonatal brains, respectively. Each genetic parcellation map comprises a distinct spatial layout of cortical regions, where vertices within the same region share high genetic correlation. These genetic parcellation maps of CT and SA of neonates largely differ from those of adults, despite their highly remarkable similarities in the medial cortex of SA. These discoveries provide important insights into the genetic organization of the early cerebral cortex development.

eLIMS: Ensemble Learning-Based Spatial Segmentation of Mass Spectrometry Imaging to Explore Metabolic Heterogeneity.

Spatial segmentation is an essential processing method for image analysis aiming to identify the characteristic suborgans or microregions from mass spectrometry imaging (MSI) data, which is critical for understanding the spatial heterogeneity of biological information and function and the underlying molecular signatures. Due to the intrinsic characteristics of MSI data including spectral nonlinearity, high-dimensionality, and large data size, the common segmentation methods lack the capability for capturing the accurate microregions associated with biological functions. Here we proposed an ensemble learning-based spatial segmentation strategy, named eLIMS, that combines a randomized unified manifold approximation and projection (r-UMAP) dimensionality reduction module for extracting significant features and an ensemble pixel clustering module for aggregating the clustering maps from r-UMAP. Three MSI datasets are used to evaluate the performance of eLIMS, including mouse fetus, human adenocarcinoma, and mouse brain. Experimental results demonstrate that the proposed method has potential in partitioning the heterogeneous tissues into several subregions associated with anatomical structure, i.e., the suborgans of the brain region in mouse fetus data are identified as dorsal pallium, midbrain, and brainstem. Furthermore, it effectively discovers critical microregions related to physiological and pathological variations offering new insight into metabolic heterogeneity.

KLF13 promotes VSMCs phenotypic dedifferentiation by directly binding to the SM22α promoter.

Krüppel-like factor 13 (KLF13), a zinc finger transcription factor, is considered as a potential regulator of cardiomyocyte differentiation and proliferation during heart morphogenesis. However, its precise role in the dedifferentiation of vascular smooth muscle cells (VSMCs) during atherosclerosis and neointimal formation after injury remains poorly understood. In this study, we investigated the relationship between KLF13 and SM22α expression in normal and atherosclerotic plaques by bioanalysis, and observed a significant increase in KLF13 levels in the atherosclerotic plaques of both human patients and ApoE-/- mice. Knockdown of KLF13 was found to ameliorate intimal hyperplasia following carotid artery injury. Furthermore, we discovered that KLF13 directly binds to the SM22α promoter, leading to the phenotypic dedifferentiation of VSMCs. Remarkably, we observed a significant inhibition of platelet-derived growth factor BB-induced VSMCs dedifferentiation, proliferation, and migration when knocked down KLF13 in VSMCs. This inhibitory effect of KLF13 knockdown on VCMC function was, at least in part, mediated by the inactivation of p-AKT signaling in VSMCs. Overall, our findings shed light on a potential therapeutic target for treating atherosclerotic lesions and restenosis after vascular injury.

Challenges and improvements in HER2 scoring and histologic evaluation: insights from a national proficiency testing scheme for breast cancer diagnosis in China.

BACKGROUND: In 2022, our team launched the pioneering national proficiency testing (PT) scheme for the pathological diagnosis of breast cancer, rapidly establishing its credibility throughout China. Aiming to continuously monitor and improve the proficiency of Chinese pathologists in breast pathology, the second round of the PT scheme was initiated in 2023, which will expand the number of participating institutions, and will conduct a nationwide investigation into the interpretation of HER2 0, 1+, and 2+/FISH- categories in China. METHODS: The methodology employed in the current round of PT scheme closely mirrors that of the preceding cycle in 2022, which is designed and implemented according to the "Conformity assessment-General requirements for proficiency testing"(GB/T27043-2012/ISO/IEC 17043:2010). More importantly, we utilized a statistics-based method to generate assigned values to enhance their robustness and credibility. RESULTS: The final PT results, published on the website of the National Quality Control Center for Cancer ( http://117.133.40.88:3927 ), showed that all participants passed the testing. However, a few institutions demonstrated systemic biases in scoring HER2 0, 1+, and 2+/FISH- with accuracy levels below 59%, considered unsatisfactory. Especially, the concordance rate for HER2 0 cases was only 78.1%, indicating challenges in distinguishing HER2 0 from low HER2 expression. Meanwhile, areas for histologic type and grade interpretation improvement were also noted. CONCLUSIONS: Our PT scheme demonstrated high proficiency in diagnosing breast cancer in China. But it also identified systemic biases in scoring HER2 0, 1+, and 2+/FISH- at some institutions. More importantly, our study highlighted challenges in the evaluation at the extreme lower end of the HER2 staining spectrum, a crucial area for further research. Meanwhile, it also revealed the need for improvements in interpreting histologic types and grades. These findings strengthened the importance of robust quality assurance mechanisms, like the nationwide PT scheme conducted in this study, to maintain high diagnostic standards and identify areas requiring further training and enhancement.

CRKL dictates anti-PD-1 resistance by mediating tumor-associated neutrophil infiltration in hepatocellular carcinoma.

BACKGROUND & AIMS: The effectiveness of immune checkpoint inhibitor (ICI) therapy for hepatocellular carcinoma (HCC) is limited by treatment resistance. However, the mechanisms underlying immunotherapy resistance remain elusive. We aimed to identify the role of CT10 regulator of kinase-like (CRKL) in resistance to anti-PD-1 therapy in HCC. METHODS: Gene expression in HCC specimens from 10 patients receiving anti-PD-1 therapy was identified by RNA-sequencing. A total of 404 HCC samples from tissue microarrays were analyzed by immunohistochemistry. Transgenic mice (Alb-Cre/Trp53fl/fl) received hydrodynamic tail vein injections of a CRKL-overexpressing vector. Mass cytometry by time of flight was used to profile the proportion and status of different immune cell lineages in the mouse tumor tissues. RESULTS: CRKL was identified as a candidate anti-PD-1-resistance gene using a pooled genetic screen. CRKL overexpression nullifies anti-PD-1 treatment efficacy by mobilizing tumor-associated neutrophils (TANs), which block the infiltration and function of CD8+ T cells. PD-L1+ TANs were found to be an essential subset of TANs that were regulated by CRKL expression and display an immunosuppressive phenotype. Mechanistically, CRKL inhibits APC (adenomatous polyposis coli)-mediated proteasomal degradation of ß-catenin by competitively decreasing Axin1 binding, and thus promotes VEGFα and CXCL1 expression. Using human HCC samples, we verified the positive correlations of CRKL/ß-catenin/VEGFα and CXCL1. Targeting CRKL using CRISPR-Cas9 gene editing (CRKL knockout) or its downstream regulators effectively restored the efficacy of anti-PD-1 therapy in an orthotopic mouse model and a patient-derived organotypic tumor spheroid model. CONCLUSIONS: Activation of the CRKL/ß-catenin/VEGFα and CXCL1 axis is a critical obstacle to successful anti-PD-1 therapy. Therefore, CRKL inhibitors combined with anti-PD-1 could be useful for the treatment of HCC. IMPACT AND IMPLICATIONS: Here, we found that CRKL was overexpressed in anti-PD-1-resistant hepatocellular carcinoma (HCC) and that CRKL upregulation promotes anti-PD-1 resistance in HCC. We identified that upregulation of the CRKL/ß-catenin/VEGFα and CXCL1 axis contributes to anti-PD-1 tolerance by promoting infiltration of tumor-associated neutrophils. These findings support the strategy of bevacizumab-based immune checkpoint inhibitor combination therapy, and CRKL inhibitors combined with anti-PD-1 therapy may be developed for the treatment of HCC.

Circ_0098823 binding with IGF2BP3 regulates DNM1L stability to promote metastasis of hepatocellular carcinoma via mitochondrial fission.

Hepatocellular carcinoma (HCC) is highly metastatic and invasive. CircRNA participates in gene regulation of multiple tumor metastases, but little is known whether it is a bystander or an actual player in HCC metastasis. We aim to explore the molecular mechanisms of novel circRNAs in HCC metastasis. RT-qPCR was used to detect the expression of 13 circRNAs derived by the ERBB3 gene. The function of circ_0098823 and DNM1L in HCC cells were estimated by CCK-8, transwell assays, flow cytometry, electron microscope, and in vivo experiments. RNA binding protein of circ_0098823 was confirmed by RNA pull-down, mass spectrometry, and RNA immunoprecipitation. The expression of DNM1L after IGF2BP3 knockdown was detected by RT-qPCR and western blot. Circ_0098823 was significantly up-regulated both in HCC tissues and HGF induced cell lines. Circ_0098823 overexpression significantly enhanced proliferation, migration, and invasion but decreased apoptosis of HCC cells, particularly promoted mitochondrial fission. Compared with the control group, the tumors in the circ_0098823 knockdown mice were significantly smaller and lighter. Circ_0098823 silencing suppressed DNM1L expression, a key molecule for fission, which enhanced proliferation, migration and invasion, and inhibited apoptosis of HCC cell. IGF2BP3 was a binding protein of circ_0098823. The expression and mRNA stability of DNM1L were down-regulated by IGF2BP3 knockdown. IGF2BP3 knockdown significantly alleviated the excessive migration, invasion and apoptosis of HCC cells caused by circ_0098823 overexpression. This study uncovered a novel circ_0098823 with tumor-promoting effect, and the mechanism by which circ_0098823 participates in HCC progression through IGF2BP3-guided DNM1L. Our study broadens molecular understanding of HCC progression.

Reaction-Modulated Surface-Enhanced Raman Scattering Strategy for Stereoselective Differentiation and Identification of Amino Acids.

Surface-enhanced Raman scattering (SERS) sensing of racemates is a remarkably fascinating yet very sophisticated objective because of similar physicochemical features of enantiomers. Inspired by the enantiomeric selectivity of nucleophilic addition reaction (NAR) toward amino acids, we herein propose highly effective, robust SERS discrimination of d- and l-valine by synergizing asymmetric gold nanorods-embedded ZIF-8 nanoparticles (AGNZ) with NAR to engender stereoselective molecular fingerprint. Experimental and chemometric analyses disclose that enantioselectivity lies in dual aspects: (i) abundant interfacial cavities and 3D hot-spots in AGNZ offer necessary confined asymmetrical surroundings to trigger enantiospecific molecular adsorption and interaction affinity, and (ii) the specified NAR drags the racemates adjacent to the interfacial area of AGNZ for maximum analytes-substrate interaction. This strategy is universal and can be utilized for the recognition of different amino acid enantiomers. Importantly, multiple quantifications of the racemic ratio can be realized with superior prognostic performances. This synergizing strategy therefore provides a significant paradigm shift from traditional methods to realize highly effective SERS discrimination of racemates.

DeepION: A Deep Learning-Based Low-Dimensional Representation Model of Ion Images for Mass Spectrometry Imaging.

Mass spectrometry imaging (MSI) is a high-throughput imaging technique capable of the qualitative and quantitative in situ detection of thousands of ions in biological samples. Ion image representation is a technique that produces a low-dimensional vector embedded with significant spectral and spatial information on an ion image, which further facilitates the distance-based similarity measurement for the identification of colocalized ions. However, given the low signal-to-noise ratios inherent in MSI data coupled with the scarcity of annotated data sets, achieving an effective ion image representation for each ion image remains a challenge. In this study, we propose DeepION, a novel deep learning-based method designed specifically for ion image representation, which is applied to the identification of colocalized ions and isotope ions. In DeepION, contrastive learning is introduced to ensure that the model can generate the ion image representation in a self-supervised manner without manual annotation. Since data augmentation is a crucial step in contrastive learning, a unique data augmentation strategy is designed by considering the characteristics of MSI data, such as the Poisson distribution of ion abundance and a random pattern of missing values, to generate plentiful ion image pairs for DeepION model training. Experimental results of rat brain tissue MSI show that DeepION outperforms other methods for both colocalized ion and isotope ion identification, demonstrating the effectiveness of ion image representation. The proposed model could serve as a crucial tool in the biomarker discovery and drug development of the MSI technique.

Abundance of Modifications in Mature miRNAs Revealed by LC-MS/MS Method Coupled with a Two-Step Hybridization Purification Strategy.

Accurate detection of endogenous miRNA modifications, such as N6-methyladenosine (m6A), 7-methylguanosine (m7G), and 5-methylcytidine (m5C), poses significant challenges, resulting in considerable uncertainty regarding their presence in mature miRNAs. In this study, we demonstrate for the first time that liquid chromatography coupled with a tandem mass spectrometry (LC-MS/MS) nucleoside analysis method is a practical tool for quantitatively analyzing human miRNA modifications. The newly designed liquid-solid two-step hybridization (LSTH) strategy enhances specificity for miRNA purification, while LC-MS/MS offers robust capability in recognizing modifications and sufficient sensitivity with detection limits ranging from attomoles to low femtomoles. Therefore, it provides a more reliable approach compared to existing techniques for revealing modifications in endogenous miRNAs. With this approach, we characterized m6A, m7G, and m5C modifications in miR-21-5p, Let-7a/e-5p, and miR-10a-5p isolated from cultured cells and observed unexpectedly low abundance (<1% at each site) of these modifications.

Scalable Dual In Situ Synthesis of Polyester Nanocomposites for High-Energy Storage.

Incorporating ultralow loading of nanoparticles into polymers has realized increases in dielectric constant and breakdown strength for excellent energy storage. However, there are still a series of tough issues to be dealt with, such as organic solvent uses, which face enormous challenges in scalable preparation. Here, a new strategy of dual in situ synthesis is proposed, namely polymerization of polyethylene terephthalate (PET) synchronizes with growth of calcium borate nanoparticles, making polyester nanocomposites from monomers directly. Importantly, this route is free of organic solvents and surface modification of nanoparticles, which is readily accessible to scalable synthesis of polyester nanocomposites. Meanwhile, uniform dispersion of as ultralow as 0.1 wt% nanoparticles and intense bonding at interfaces have been observed. Furthermore, the PET-based nanocomposite displays obvious increases in both dielectric constant and breakdown strength as compared to the neat PET. Its maximum discharged energy density reaches 15 J cm-3 at 690 MV m-1 and power density attains 218 MW cm-3 under 150 Ω resistance at 300 MV m-1, which is far superior to the current dielectric polymers that can be produced at large scales. This work presents a scalable, safe, low-cost, and environment-friendly route toward polymer nanocomposites with superior capacitive performance.

Advancements in the study of synaptic plasticity and mitochondrial autophagy relationship.

Synapses serve as the points of communication between neurons, consisting primarily of three components: the presynaptic membrane, synaptic cleft, and postsynaptic membrane. They transmit signals through the release and reception of neurotransmitters. Synaptic plasticity, the ability of synapses to undergo structural and functional changes, is influenced by proteins such as growth-associated proteins, synaptic vesicle proteins, postsynaptic density proteins, and neurotrophic growth factors. Furthermore, maintaining synaptic plasticity consumes more than half of the brain's energy, with a significant portion of this energy originating from ATP generated through mitochondrial energy metabolism. Consequently, the quantity, distribution, transport, and function of mitochondria impact the stability of brain energy metabolism, thereby participating in the regulation of fundamental processes in synaptic plasticity, including neuronal differentiation, neurite outgrowth, synapse formation, and neurotransmitter release. This article provides a comprehensive overview of the proteins associated with presynaptic plasticity, postsynaptic plasticity, and common factors between the two, as well as the relationship between mitochondrial energy metabolism and synaptic plasticity.

Communication between alveolar macrophages and fibroblasts via the TNFSF12-TNFRSF12A pathway promotes pulmonary fibrosis in severe COVID-19 patients.

BACKGROUND: Severe COVID-19 infection has been associated with the development of pulmonary fibrosis, a condition that significantly affects patient prognosis. Understanding the underlying cellular communication mechanisms contributing to this fibrotic process is crucial. OBJECTIVE: In this study, we aimed to investigate the role of the TNFSF12-TNFRSF12A pathway in mediating communication between alveolar macrophages and fibroblasts, and its implications for the development of pulmonary fibrosis in severe COVID-19 patients. METHODS: We conducted single-cell RNA sequencing (scRNA-seq) analysis using lung tissue samples from severe COVID-19 patients and healthy controls. The data was processed, analyzed, and cell types were annotated. We focused on the communication between alveolar macrophages and fibroblasts and identified key signaling pathways. In vitro experiments were performed to validate our findings, including the impact of TNFRSF12A silencing on fibrosis reversal. RESULTS: Our analysis revealed that in severe COVID-19 patients, alveolar macrophages communicate with fibroblasts primarily through the TNFSF12-TNFRSF12A pathway. This communication pathway promotes fibroblast proliferation and expression of fibrotic factors. Importantly, silencing TNFRSF12A effectively reversed the pro-proliferative and pro-fibrotic effects of alveolar macrophages. CONCLUSION: The TNFSF12-TNFRSF12A pathway plays a central role in alveolar macrophage-fibroblast communication and contributes to pulmonary fibrosis in severe COVID-19 patients. Silencing TNFRSF12A represents a potential therapeutic strategy for mitigating fibrosis in severe COVID-19 lung disease.

Reconfigurable all-optical pattern recognition for PSK and QAM signals in high-speed optoelectronic firewalls.

In the fifth generation fixed networks (F5G) era, full-fiber-connected optical networks support emerging bandwidth-hungry services. However, optical networks are vulnerable to attack by tapping or other methods, which has been paid more and more attention in modern optical infrastructure. Therefore, high-speed optoelectronic firewalls appear as one of the promising technologies to guarantee security. The most significant and challenging component of a high-speed optoelectronic firewall is all-optical pattern recognition, especially for more advanced high-order modulation formats such as phase shift keying (PSK) or quadrature amplitude modulation (QAM) to satisfy efficient enhanced fixed broadband in F5G. In this paper, what we believe to be a novel reconfigurable all-optical pattern recognition system for PSK and QAM signals is proposed with two implementation architectures. The proposed system mainly consists of a generalized XNOR (GXNOR) and a recirculating loop. The two implementation architectures are precisely two realization methods of the GXNOR part. One employs two cascaded IQ Mach-Zehnder modulators and the other is implemented by the four-wave mixing. The numerical simulation results demonstrate that the two implementation architectures can both achieve all-optical pattern recognition for the reconfigurable high-order modulation formats of QPSK, 8PSK, and 16QAM with the recorded baud rate of 260GBaud.