Multi-organ proteomic landscape of COVID-19 autopsies.

The molecular pathology of multi-organ injuries in COVID-19 patients remains unclear, preventing effective therapeutics development. Here, we report a proteomic analysis of 144 autopsy samples from seven organs in 19 COVID-19 patients. We quantified 11,394 proteins in these samples, in which 5,336 were perturbed in the COVID-19 patients compared to controls. Our data showed that cathepsin L1, rather than ACE2, was significantly upregulated in the lung from the COVID-19 patients. Systemic hyperinflammation and dysregulation of glucose and fatty acid metabolism were detected in multiple organs. We also observed dysregulation of key factors involved in hypoxia, angiogenesis, blood coagulation, and fibrosis in multiple organs from the COVID-19 patients. Evidence for testicular injuries includes reduced Leydig cells, suppressed cholesterol biosynthesis, and sperm mobility. In summary, this study depicts a multi-organ proteomic landscape of COVID-19 autopsies that furthers our understanding of the biological basis of COVID-19 pathology.

A code for RanGDP binding in ankyrin repeats defines a nuclear import pathway.

Regulation of nuclear import is fundamental to eukaryotic biology. The majority of nuclear import pathways are mediated by importin-cargo interactions. Yet not all nuclear proteins interact with importins, necessitating the identification of a general importin-independent nuclear import pathway. Here, we identify a code that determines importin-independent nuclear import of ankyrin repeats (ARs), a structural motif found in over 250 human proteins with diverse functions. AR-containing proteins (ARPs) with a hydrophobic residue at the 13th position of two consecutive ARs bind RanGDP efficiently, and consequently enter the nucleus. This code, experimentally tested in 17 ARPs, predicts the nuclear-cytoplasmic localization of over 150 annotated human ARPs with high accuracy and is acquired by the most common familial melanoma-associated CDKN2A mutation, leading to nuclear accumulation of mutant p16ink4a. The RaDAR (RanGDP/AR) pathway represents a general importin-independent nuclear import pathway and is frequently used by AR-containing transcriptional regulators, especially those regulating NF-κB/p53.

Deficiency of factor-inhibiting HIF creates a tumor-promoting immune microenvironment.

Hypoxia signaling influences tumor development through both cell-intrinsic and -extrinsic pathways. Inhibiting hypoxia-inducible factor (HIF) function has recently been approved as a cancer treatment strategy. Hence, it is important to understand how regulators of HIF may affect tumor growth under physiological conditions. Here we report that in aging mice factor-inhibiting HIF (FIH), one of the most studied negative regulators of HIF, is a haploinsufficient suppressor of spontaneous B cell lymphomas, particular pulmonary B cell lymphomas. FIH deficiency alters immune composition in aged mice and creates a tumor-supportive immune environment demonstrated in syngeneic mouse tumor models. Mechanistically, FIH-defective myeloid cells acquire tumor-supportive properties in response to signals secreted by cancer cells or produced in the tumor microenvironment with enhanced arginase expression and cytokine-directed migration. Together, these data demonstrate that under physiological conditions, FIH plays a key role in maintaining immune homeostasis and can suppress tumorigenesis through a cell-extrinsic pathway.

dCCA: detecting differential covariation patterns between two types of high-throughput omics data.

MOTIVATION: The advent of multimodal omics data has provided an unprecedented opportunity to systematically investigate underlying biological mechanisms from distinct yet complementary angles. However, the joint analysis of multi-omics data remains challenging because it requires modeling interactions between multiple sets of high-throughput variables. Furthermore, these interaction patterns may vary across different clinical groups, reflecting disease-related biological processes. RESULTS: We propose a novel approach called Differential Canonical Correlation Analysis (dCCA) to capture differential covariation patterns between two multivariate vectors across clinical groups. Unlike classical Canonical Correlation Analysis, which maximizes the correlation between two multivariate vectors, dCCA aims to maximally recover differentially expressed multivariate-to-multivariate covariation patterns between groups. We have developed computational algorithms and a toolkit to sparsely select paired subsets of variables from two sets of multivariate variables while maximizing the differential covariation. Extensive simulation analyses demonstrate the superior performance of dCCA in selecting variables of interest and recovering differential correlations. We applied dCCA to the Pan-Kidney cohort from the Cancer Genome Atlas Program database and identified differentially expressed covariations between noncoding RNAs and gene expressions. AVAILABILITY AND IMPLEMENTATION: The R package that implements dCCA is available at https://github.com/hwiyoungstat/dCCA.

A hypothalamic novelty signal modulates hippocampal memory.

The ability to recognize information that is incongruous with previous experience is critical for survival. Novelty signals have therefore evolved in the mammalian brain to enhance attention, perception and memory1,2. Although the importance of regions such as the ventral tegmental area3,4 and locus coeruleus5 in broadly signalling novelty is well-established, these diffuse monoaminergic transmitters have yet to be shown to convey specific information on the type of stimuli that drive them. Whether distinct types of novelty, such as contextual and social novelty, are differently processed and routed in the brain is unknown. Here we identify the supramammillary nucleus (SuM) as a novelty hub in the hypothalamus6. The SuM region is unique in that it not only responds broadly to novel stimuli, but also segregates and selectively routes different types of information to discrete cortical targets-the dentate gyrus and CA2 fields of the hippocampus-for the modulation of mnemonic processing. Using a new transgenic mouse line, SuM-Cre, we found that SuM neurons that project to the dentate gyrus are activated by contextual novelty, whereas the SuM-CA2 circuit is preferentially activated by novel social encounters. Circuit-based manipulation showed that divergent novelty channelling in these projections modifies hippocampal contextual or social memory. This content-specific routing of novelty signals represents a previously unknown mechanism that enables the hypothalamus to flexibly modulate select components of cognition.

Proteomics-Derived Biomarker Panel Facilitates Distinguishing Primary Lung Adenocarcinomas With Intestinal or Mucinous Differentiation From Lung Metastatic Colorectal Cancer.

The diagnosis of primary lung adenocarcinomas with intestinal or mucinous differentiation (PAIM) remains challenging due to the overlapping histomorphological, immunohistochemical (IHC), and genetic characteristics with lung metastatic colorectal cancer (lmCRC). This study aimed to explore the protein biomarkers that could distinguish between PAIM and lmCRC. To uncover differences between the two diseases, we used tandem mass tagging-based shotgun proteomics to characterize proteomes of formalin-fixed, paraffin-embedded tumor samples of PAIM (n = 22) and lmCRC (n = 17).Then three machine learning algorithms, namely support vector machine (SVM), random forest, and the Least Absolute Shrinkage and Selection Operator, were utilized to select protein features with diagnostic significance. These candidate proteins were further validated in an independent cohort (PAIM, n = 11; lmCRC, n = 19) by IHC to confirm their diagnostic performance. In total, 105 proteins out of 7871 proteins were significantly dysregulated between PAIM and lmCRC samples and well-separated two groups by Uniform Manifold Approximation and Projection. The upregulated proteins in PAIM were involved in actin cytoskeleton organization, platelet degranulation, and regulation of leukocyte chemotaxis, while downregulated ones were involved in mitochondrial transmembrane transport, vasculature development, and stem cell proliferation. A set of ten candidate proteins (high-level expression in lmCRC: CDH17, ATP1B3, GLB1, OXNAD1, LYST, FABP1; high-level expression in PAIM: CK7 (an established marker), NARR, MLPH, S100A14) was ultimately selected to distinguish PAIM from lmCRC by machine learning algorithms. We further confirmed using IHC that the five protein biomarkers including CDH17, CK7, MLPH, FABP1 and NARR were effective biomarkers for distinguishing PAIM from lmCRC. Our study depicts PAIM-specific proteomic characteristics and demonstrates the potential utility of new protein biomarkers for the differential diagnosis of PAIM and lmCRC. These findings may contribute to improving the diagnostic accuracy and guide appropriate treatments for these patients.

Electroregulation of graphene-nanofluid interactions to coenhance water permeation and ion rejection in vertical graphene membranes.

Graphene oxide (GO) membranes with nanoconfined interlayer channels theoretically enable anomalous nanofluid transport for ultrahigh filtration performance. However, it is still a significant challenge for current GO laminar membranes to achieve ultrafast water permeation and high ion rejection simultaneously, because of the contradictory effect that exists between the water-membrane hydrogen-bond interaction and the ion-membrane electrostatic interaction. Here, we report a vertically aligned reduced GO (VARGO) membrane and propose an electropolarization strategy for regulating the interfacial hydrogen-bond and electrostatic interactions to concurrently enhance water permeation and ion rejection. The membrane with an electro-assistance of 2.5 V exhibited an ultrahigh water permeance of 684.9 L m-2 h-1 bar-1, which is 1-2 orders of magnitude higher than those of reported GO-based laminar membranes. Meanwhile, the rejection rate of the membrane for NaCl was as high as 88.7%, outperforming most reported graphene-based membranes (typically 10 to 50%). Molecular dynamics simulations and density-function theory calculations revealed that the electropolarized VARGO nanochannels induced the well-ordered arrangement of nanoconfined water molecules, increasing the water transport efficiency, and thereby resulting in improved water permeation. Moreover, the electropolarization effect enhanced the surface electron density of the VARGO nanochannels and reinforced the interfacial attractive interactions between the cations in water and the oxygen groups and π-electrons on the VARGO surface, strengthening the ion-partitioning and Donnan effect for the electrostatic exclusion of ions. This finding offers an electroregulation strategy for membranes to achieve both high water permeability and high ion rejection performance.

Identifying covariate-related subnetworks for whole-brain connectome analysis.

Whole-brain connectome data characterize the connections among distributed neural populations as a set of edges in a large network, and neuroscience research aims to systematically investigate associations between brain connectome and clinical or experimental conditions as covariates. A covariate is often related to a number of edges connecting multiple brain areas in an organized structure. However, in practice, neither the covariate-related edges nor the structure is known. Therefore, the understanding of underlying neural mechanisms relies on statistical methods that are capable of simultaneously identifying covariate-related connections and recognizing their network topological structures. The task can be challenging because of false-positive noise and almost infinite possibilities of edges combining into subnetworks. To address these challenges, we propose a new statistical approach to handle multivariate edge variables as outcomes and output covariate-related subnetworks. We first study the graph properties of covariate-related subnetworks from a graph and combinatorics perspective and accordingly bridge the inference for individual connectome edges and covariate-related subnetworks. Next, we develop efficient algorithms to exact covariate-related subnetworks from the whole-brain connectome data with an $\ell_0$ norm penalty. We validate the proposed methods based on an extensive simulation study, and we benchmark our performance against existing methods. Using our proposed method, we analyze two separate resting-state functional magnetic resonance imaging data sets for schizophrenia research and obtain highly replicable disease-related subnetworks.

Selective targeting of parallel G-quadruplex structure using L-RNA aptamer.

G-quadruplexes (G4) are special nucleic acid structures with diverse conformational polymorphisms. Selective targeting of G-quadruplex conformations and regulating their biological functions provide promising therapeutic intervention. Despite the large repertoire of G4-binding tools, only a limited number of them can specifically target a particular G4 conformation. Here, we introduce a novel method, G4-SELEX-Seq and report the development of the first L-RNA aptamer, L-Apt12-6, with high binding selectivity to parallel G4 over other nucleic acid structures. Using parallel dG4 c-kit 1 as an example, we demonstrate the strong binding affinity between L-Apt12-6 and c-kit 1 dG4 in vitro and in cells, and notably report the applications of L-Apt12-6 in controlling DNA replication and gene expression. Our results suggest that L-Apt12-6 is a valuable tool for targeting parallel G-quadruplex conformation and regulating G4-mediated biological processes. Furthermore, G4-SELEX-Seq can be used as a general platform for G4-targeting L-RNA aptamers selection and should be applicable to other nucleic acid structures.

KIRREL promotes the proliferation of gastric cancer cells and angiogenesis through the PI3K/AKT/mTOR pathway.

Anti-angiogenesis is a promising therapeutic strategy for delaying tumour progression that offers, new hope for gastric cancer targeted therapy. The purpose of this study was to investigate the precise mechanism by which Kin of IRRE-like protein 1 (KIRREL) contributes to the development of gastric cancer, particularly in terms of tumour angiogenesis. Differential expression of KIRREL in tissues and cells was detected using quantitative real-time polymerase chain reaction, western blotting and immunohistochemistry. A bioinformatics analysis was conducted to screen for the function and pathway enrichment of KIRREL in gastric cancer. Lentivirus-induced KIRREL silencing in SNU-5 cells and lentivirus-induced KIRREL overexpression in AGS cells were used to study the effect of KIRREL on the proliferation, cell cycle and angiogenesis of gastric cancer cells. Moreover, the expressions of PI3K, P-PI3K, AKT, P-AKT, mTOR, P-mTOR, HIF-1α and VEGF were also detected. Gastric cancer tissues and cells had high levels of KIRREL expression, which is associated with the proliferation, cell cycle and angiogenesis of gastric cancer cells. After silencing and overexpressing KIRREL in SNU-5 and AGS cells, respectively, the proliferation and angiogenesis of SNU-5 cells were inhibited, while the proliferation and angiogenesis of AGS cells were promoted. According to a bioinformatics analysis of the KIRREL gene, angiogenesis regulation and the PI3K/AKT pathway were highly connected. The PI3K/AKT/mTOR pathway was repressed and stimulated by KIRREL silencing and overexpression, respectively. IGF-1, an AKT agonist, and LY294002, an inhibitor, reversed the effects of KIRREL silencing and overexpression on the PI3K/AKT/mTOR pathway and on gastric cancer cell proliferation and angiogenesis. KIRREL may mediate the proliferation and angiogenesis of gastric cancer cells through the PI3K/AKT/mTOR signalling pathway. These findings could help in the further development of potential anti-angiogenesis targets.

Piceatannol protects against myocardial ischemia/reperfusion injury by inhibiting ferroptosis via Nrf-2 signaling-mediated iron metabolism.

Myocardial tissue ischemia damages myocardial cells. Although reperfusion is an effective technique to rescue myocardial cell damage, it may also exacerbate myocardial cell damage. Ferroptosis, an iron-dependent cell death, occurs following myocardial ischemia-reperfusion (I/R). Piceatannol (PCT) is a natural stilbene compound with excellent antioxidant properties that protect against I/R injury and exerts protective effects against ferroptosis-induced cardiomyocytes following I/R injury; however, the exact mechanism remains to be elucidated. PURPOSE: This study aims to investigate the protective effect and mechanism of PCT on myocardial ischemia-reperfusion injury. METHODS: An ischemia-reperfusion model was established via ligation of the left anterior descending branch of mice's hearts and hypoxia-reoxygenation (H/R) of cardiomyocytes. RESULTS: During ischemia-reperfusion, Nuclear factor E2-related factor 2 (Nrf-2) expression was downregulated, the left ventricular function was impaired, intracellular iron and lipid peroxidation product levels were elevated, and cardiomyocytes underwent ferroptosis. Furthermore, ferroptosis was enhanced following treatment with an Nrf-2 inhibitor. After PCT treatment, Nrf-2 expression significantly increased, intracellular ferrous ions and lipid peroxidation products significantly reduced, Ferroportin1 (FPN1) expression increased, and transferrin receptor-1 (TfR-1) expression was inhibited. CONCLUSIONS: PCT regulates iron metabolism through Nrf-2 to protect against myocardial cell ferroptosis induced by myocardial I/R injury.

Ror2-mediated non-canonical Wnt signaling regulates Cdc42 and cell proliferation during tooth root development.

The control of size and shape is an important part of regulatory process during organogenesis. Tooth formation is a highly complex process that fine-tunes the size and shape of the tooth, which are crucial for its physiological functions. Each tooth consists of a crown and one or more roots. Despite comprehensive knowledge of the mechanism that regulates early tooth crown development, we have limited understanding of the mechanism regulating root patterning and size during development. Here, we show that Ror2-mediated non-canonical Wnt signaling in the dental mesenchyme plays a crucial role in cell proliferation, and thereby regulates root development size in mouse molars. Furthermore, Cdc42 acts as a potential downstream mediator of Ror2 signaling in root formation. Importantly, activation of Cdc42 can restore cell proliferation and partially rescue the root development size defects in Ror2 mutant mice. Collectively, our findings provide novel insights into the function of Ror2-mediated non-canonical Wnt signaling in regulating tooth morphogenesis, and suggest potential avenues for dental tissue engineering.

Arid1a regulates cell cycle exit of transit-amplifying cells by inhibiting the Aurka-Cdk1 axis in mouse incisor.

Stem cells self-renew or give rise to transit-amplifying cells (TACs) that differentiate into specific functional cell types. The fate determination of stem cells to TACs and their transition to fully differentiated progeny is precisely regulated to maintain tissue homeostasis. Arid1a, a core component of the switch/sucrose nonfermentable complex, performs epigenetic regulation of stage- and tissue-specific genes that is indispensable for stem cell homeostasis and differentiation. However, the functional mechanism of Arid1a in the fate commitment of mesenchymal stem cells (MSCs) and their progeny is not clear. Using the continuously growing adult mouse incisor model, we show that Arid1a maintains tissue homeostasis through limiting proliferation, promoting cell cycle exit and differentiation of TACs by inhibiting the Aurka-Cdk1 axis. Loss of Arid1a overactivates the Aurka-Cdk1 axis, leading to expansion of the mitotic TAC population but compromising their differentiation ability. Furthermore, the defective homeostasis after loss of Arid1a ultimately leads to reduction of the MSC population. These findings reveal the functional significance of Arid1a in regulating the fate of TACs and their interaction with MSCs to maintain tissue homeostasis.

The Contact Interface Electronic Coupling of Cobalt and Zirconia Enables Stable and Highly Efficient 4e- Oxygen Reduction Reaction Catalysis.

Cobalt (Co) is an efficient oxygen reduction reaction (ORR) catalyst but suffers from issues of easy deactivation and instability. Here, it shows that ZrO2 can stabilize Co through interface electron coupling and enables highly efficient 4e- ORR catalysis. Porous carbon nanofibers loaded with dispersed Co-nanodots (≈10 nm, 9.63 wt%) and ZrO2 nanoparticles are synthesized as the catalyst. The electron transfer from the metallic Co to ZrO2 causes interface-oriented electron enrichment that promotes the activation and conversion of O2, improving the efficiency of 4e- transfer. Moreover, the simulation results show that ZrO2 acts like an electron reservoir to store electrons from Co and slowly release them to the interface, solving the easy deactivation problem of Co. The catalyst exhibits a high half-wave potential (E1/2) of 0.84 V, which only decreases by 3.6 mV after 10 000 cycles, showing great stability. Particularly, the enhanced spin polarization of Co in a magnetic field reinforces the interface electron coupling that increases the E1/2 to 0.864 V and decreases the energy barrier of ORR from 0.81 to 0.63 eV, confirming that the proposed strategy is effective for constructing efficient and stable ORR catalysts.

Surface-Ligand Tuned Reversible Transformations in Aqueous Environments Between CdSe Magic-Size Clusters and Their Precursor Compounds.

That magic-size clusters (MSCs) have their counterpart precursor compounds (PCs) has not been generally accepted by expertise circles. Here, experimental evidence to support this new concept is presented. With aqueous-phase CdSe MSCs as a model system, it is shown that when the MSCs are dispersed in water containing a certain amount of L-cysteine (Cys), the MSCs disappear slowly. Upon the addition of CdCl2 , the MSCs recover. It is proposed that after dispersing, the MSCs transform to their quasi-isomeric, non-absorbing PCs upon Cys addition. In the presence of CdCl2 , the PCs transform back to the MSCs due to Cys elimination. The surface ligand Cys of the MSCs plays a significant role in the reversible transformations. The present study provides compelling evidence that absorbing MSCs have their non-absorbing PCs. The study findings suggest that the transformation between two MSCs that display absorption spectral shifts in a stepwise pattern is assisted by their PCs.

Suppressing Deep-Level Trap Toward Over 13% Efficient Solution-Processed Kesterite Solar Cell.

Cu2ZnSn (S,Se)4 (CZTSSe), a promising absorption material for thin-film solar cells, still falls short of reaching the balance limit efficiency due to the presence of various defects and high defect concentration in the thin film. During the high-temperature selenization process of CZTSSe, the diffusion of various elements and chemical reactions significantly influence defect formation. In this study, a NaOH-Se intermediate layer introduced at the back interface can optimize Cu2ZnSnS4 (CZTS)precursor films and subsequently adjust the Se and alkali metal content to favor grain growth during selenization. Through this back interface engineering, issues such as non-uniform grain arrangement on the surface, voids in bulk regions, and poor contact at the back interface of absorber layers are effectively addressed. This method not only optimizes morphology but also suppresses deep-level defect formation, thereby promoting carrier transport at both interfaces and bulk regions of the absorber layer. Consequently, CZTSSe devices with a NaOH-Se intermediate layer improved fill factor, open-circuit voltage, and efficiency by 13.3%. This work initiates from precursor thin films via back interface engineering to fabricate high-quality absorber layers while advancing the understanding regarding the role played by intermediate layers at the back interface of kesterite solar cells.

Electron Transport Layer Engineering Induced Carrier Dynamics Optimization for Efficient Cd-Free Sb2 Se3 Thin-Film Solar Cells.

Antimony selenide (Sb2 Se3 ) is a highly promising photovoltaic material thanks to its outstanding optoelectronic properties, as well as its cost-effective and eco-friendly merits. However, toxic CdS is widely used as an electron transport layer (ETL) in efficient Sb2 Se3 solar cells, which largely limit their development toward market commercialization. Herein, an effective green Cd-free ETL of SnOx is introduced and deposited by atomic layer deposition method. Additionally, an important post-annealing treatment is designed to further optimize the functional layers and the heterojunction interface properties. Such engineering strategy can optimize SnOx ETL with higher nano-crystallinity, higher carrier density, and less defect groups, modify Sb2 Se3 /SnOx heterojunction with better interface performance and much desirable "spike-like" band alignment, and also improve the Sb2 Se3 light absorber layer quality with passivated bulk defects and prolonged carrier lifetime, and therefore to enhance carrier separation and transport while suppressing non-radiative recombination. Finally, the as-fabricated Cd-free Mo/Sb2 Se3 /SnOx /ITO/Ag thin-film solar cell exhibits a stimulating efficiency of 7.39%, contributing a record value for Cd-free substrate structured Sb2 Se3 solar cells reported to date. This work provides a viable strategy for developing and broadening practical applications of environmental-friendly Sb2 Se3 photovoltaic devices.

(Bi,Sb)2 Se3 Alloy Thin Film for Short-Wavelength Infrared Photodetector and TFT Monolithic-Integrated Matrix Imaging.

Short-wavelength infrared photodetectors play a significant role in various fields such as autonomous driving, military security, and biological medicine. However, state-of-the-art short-wavelength infrared photodetectors, such as InGaAs, require high-temperature fabrication and heterogenous integration with complementary metal-oxide-semiconductor (CMOS) readout circuits (ROIC), resulting in a high cost and low imaging resolution. Herein, for the first time, a low-cost, high-performance, high-stable, and thin-film transistor (TFT) ROIC monolithic-integrated (Bi,Sb)2 Se3 alloy thin-film short-wavelength infrared photodetector is reported. The (Bi,Sb)2 Se3 alloy thin-film short-wavelength infrared photodetectors demonstrate a high external quantum efficiency (EQE) of 21.1% (light intensity of 0.76 µW cm-2 ) and a fast response time (3.24 µs). The highest EQE is about two magnitudes than that of the extrinsic photoconduction of Sb2 Se3 (0.051%). In addition, the unpackaged devices demonstrate high electric and thermal stability (almost no attenuation at 120 °C for 312 h), showing potential for in-vehicle applications that may experient such a high temperature. Finally, both the (Bi,Sb)2 Se3 alloy thin film and n-type CdSe buffer layer are directly deposited on the TFT ROIC (with a 64 × 64-pixel array) with a low-temperature process and the material identification and imaging applications are presented. This work is a significant breakthrough in ROIC monolithic-integrated short-wavelength infrared imaging chips.

Prognostic and predictive value of super-enhancer-derived signatures for survival and lung metastasis in osteosarcoma.

BACKGROUND: Risk stratification and personalized care are crucial in managing osteosarcoma due to its complexity and heterogeneity. However, current prognostic prediction using clinical variables has limited accuracy. Thus, this study aimed to explore potential molecular biomarkers to improve prognostic assessment. METHODS: High-throughput inhibitor screening of 150 compounds with broad targeting properties was performed and indicated a direction towards super-enhancers (SEs). Bulk RNA-seq, scRNA-seq, and immunohistochemistry (IHC) were used to investigate SE-associated gene expression profiles in osteosarcoma cells and patient tissue specimens. Data of 212 osteosarcoma patients who received standard treatment were collected and randomized into training and validation groups for retrospective analysis. Prognostic signatures and nomograms for overall survival (OS) and lung metastasis-free survival (LMFS) were developed using Cox regression analyses. The discriminatory power, calibration, and clinical value of nomograms were evaluated. RESULTS: High-throughput inhibitor screening showed that SEs significantly contribute to the oncogenic transcriptional output in osteosarcoma. Based on this finding, focus was given to 10 SE-associated genes with distinct characteristics and potential oncogenic function. With multi-omics approaches, the hyperexpression of these genes was observed in tumor cell subclusters of patient specimens, which were consistently correlated with poor outcomes and rapid metastasis, and the majority of these identified SE-associated genes were confirmed as independent risk factors for poor outcomes. Two molecular signatures were then developed to predict survival and occurrence of lung metastasis: the SE-derived OS-signature (comprising LACTB, CEP55, SRSF3, TCF7L2, and FOXP1) and the SE-derived LMFS-signature (comprising SRSF3, TCF7L2, FOXP1, and APOLD1). Both signatures significantly improved prognostic accuracy beyond conventional clinical factors. CONCLUSIONS: Oncogenic transcription driven by SEs exhibit strong associations with osteosarcoma outcomes. The SE-derived signatures developed in this study hold promise as prognostic biomarkers for predicting OS and LMFS in patients undergoing standard treatments. Integrative prognostic models that combine conventional clinical factors with these SE-derived signatures demonstrate substantially improved accuracy, and have the potential to facilitate patient counseling and individualized management.

Hybrid Cross-Linking to Construct Functional Elastomers.

ConspectusElastomers have been extensively used in diverse industrial sectors such as footwear, seals, tires, and cable jacketing and have attracted more and more attention in emerging fields such as regenerative medicine, soft robotics, and stretchable electronics. Global consumption of natural and synthetic elastomers amounted to nearly 27 million metric tons in 2020. In addition, to further enhance the common properties of elastomers, it is highly desired to endow elastomers with functionalities such as reprocessability, biomimetic mechanical properties, self-healing ability, bioactivity, and electrical conductivity, which will significantly broaden their applications. The covalent or noncovalent cross-linked structure is the essential factor for the elasticity of elastomers. Traditional elastomers usually comprise a single type of cross-linked molecular network, for which it is difficult to modulate the properties and introduce functionalities. Inspired by the simultaneous existence of multiple cross-linked structures in proteins, researchers have employed a hybrid cross-linking strategy to construct elastomers. Various noncovalent interactions (e.g., hydrogen bonds, metal-ligand coordination, ionic interactions, and chain folding) and dynamic covalent bonds (e.g., disulfide bonds, oxime-urethane bonds, and urea bonds) have been integrated in elastomers. Accordingly, the properties and functionalities of elastomers can be tuned by regulating the types, ratios, and distributions of cross-links. The hybrid cross-linking strategy provides a versatile and effective way to construct diverse functional elastomers for broad applications in various important fields.In this Account, we present our recent progress on functional elastomers constructed by a hybrid cross-linking strategy, including their design, preparation, properties, and diverse applications. First, we provide a brief introduction of the basic concept of functional elastomers and outline general strategies and mechanics for functional elastomers constructed by hybrid cross-linking. Then, we classify hybrid cross-linked elastomers by their design strategies, including multiple cross-linking, topological design, chemical coupling, and multiple networks. The relationships between the functionalities and hybrid cross-linked structures are summarized. At the same time, we also introduce diverse applications of these hybrid cross-linked elastomers in biomedicine, flexible electronics, soft robotics, 3D printing, and so on. Finally, we discuss our perspective on open challenges and future development trends of this rapidly evolving field. This Account highlighting the diverse hybrid cross-linked elastomers not only provides insights into strategies for elastomer functionalization but also provides new ideas for material design and inspires a variety of new applications.