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Myocardial injury triggers intense oxidative stress, inflammatory response, and cytokine release, which are essential for myocardial repair and remodeling. Excess reactive oxygen species (ROS) scavenging and inflammation elimination have long been considered to reverse myocardial injuries. However, the efficacy of traditional treatments (antioxidant, anti-inflammatory drugs and natural enzymes) is still poor due to their intrinsic defects such as unfavorable pharmacokinetics and bioavailability, low biological stability, and potential side effects. Nanozyme represents a candidate to effectively modulate redox homeostasis for the treatment of ROS related inflammation diseases. We develop an integrated bimetallic nanozyme derived from metal-organic framework (MOF) to eliminate ROS and alleviate inflammation. The bimetallic nanozyme (Cu-TCPP-Mn) is synthesized by embedding manganese and copper into the porphyrin followed by sonication, which could mimic the cascade activities of superoxide dismutase (SOD) and catalase (CAT) to transform oxygen radicals to hydrogen peroxide, followed by the catalysis of hydrogen peroxide into oxygen and water. Enzyme kinetic analysis and oxygen-production velocities analysis were performed to evaluate the enzymatic activities of Cu-TCPP-Mn. We also established myocardial infarction (MI) and myocardial ischemia-reperfusion (I/R) injury animal models to verify the ROS scavenging and anti-inflammation effect of Cu-TCPP-Mn. As demonstrated by kinetic analysis and oxygen-production velocities analysis, Cu-TCPP-Mn nanozyme possesses good performance in both SOD- and CAT-like activities to achieve synergistic ROS scavenging effect and provide protection for myocardial injury. In both MI and I/R injury animal models, this bimetallic nanozyme represents a promising and reliable technology to protect the heart tissue from oxidative stress and inflammation-induced injury, and enables the myocardial function to recover from otherwise severe damage. This research provides a facile and applicable method to develop a bimetallic MOF nanozyme, which represents a promising alternative to the treatment of myocardial injuries.

Accurately labeling large datasets is important for biomedical machine learning yet challenging while modern data augmentation methods may generate noise in the training data, which may deteriorate machine learning model performance. Existing approaches addressing noisy training data typically rely on strict modeling assumptions, classification models and well-curated dataset. To address these, we propose a novel reliability-based training-data-cleaning method employing inductive conformal prediction (ICP). This method uses a small set of well-curated training data and leverages ICP-calculated reliability metrics to selectively correct mislabeled data and outliers within vast quantities of noisy training data. The efficacy is validated across three classification tasks with distinct modalities: filtering drug-induced-liver-injury (DILI) literature with free-text title and abstract, predicting ICU admission of COVID-19 patients through CT radiomics and electronic health records, and subtyping breast cancer using RNA-sequencing data. Varying levels of noise to the training labels were introduced via label permutation. Our training-data-cleaning method significantly enhanced the downstream classification performance (paired t-tests, p  ≤ 0 . 05 among 30 random train/test partitions): significant accuracy enhancement in 86 out of 96 DILI experiments (up to 11.4% increase from 0.812 to 0.905), significant AUROC and AUPRC enhancements in all 48 COVID-19 experiments (up to 23.8% increase from 0.597 to 0.739 for AUROC, and 69.8% increase from 0.183 to 0.311 for AUPRC), and significant accuracy and macro-average F1-score improvements in 47 out of 48 RNA-sequencing experiments (up to 74.6% increase from 0.351 to 0.613 for accuracy, and 89.0% increase from 0.267 to 0.505 for F1-score). The improvement can be both statistically and clinically significant for information retrieval, disease diagnosis and prognosis. The method offers the potential to substantially boost classification performance in biomedical machine learning tasks without necessitating an excessive volume of well-curated training data or strong data distribution and modeling assumptions in existing semi-supervised learning methods.

•GGE-GTCS possessed an extended principal gradient, suggesting an excessive functional segregation.•GGE-GTCS showed an altered principal gradient score in both transmodal and unimodal systems.•Both principal and secondary connectome gradients were associated with clinical features.•The main results were reproduced using multiple processing configurations and were validated using an independent sample. Genetic generalized epilepsy is a network disorder typically involving distributed areas identified by classical neuroanatomy. However, the finer topological relationships in terms of continuous spatial arrangement between these systems are still ambiguous. Connectome gradients provide the topological representations of human macroscale hierarchy in an abstract low-dimensional space by embedding the functional connectome into a set of axes. Leveraging connectome gradients, we systematically scrutinized abnormalities of functional connectome gradient in patients with genetic generalized epilepsy with tonic-clonic seizure (GGE-GTCS, n = 78) compared to healthy controls (HC, n = 85), and further examined the reproducibility across multiple processing configurations and in an independent validation sample (patients with GGE-GTCS, n = 28; HC, n = 31). Our findings demonstrated an extended principal gradient at different spatial scales, network-level and vertex-level, in patients with GGE-GTCS. We found consistent results across processing parameters and in validation sample. The extended principal gradient revealed the excessive functional segregation between unimodal and transmodal systems associated with duration of epilepsy and age at seizure onset in patients. Furthermore, the connectivity profile of regions with abnormal principal gradients verified the disrupted functional hierarchy revealed by gradients. Together, our findings provided a novel view of functional system hierarchy alterations, which facilitated a continuous spatial arrangement of macroscale networks, to increase our understanding of the functional connectome hierarchy in generalized epilepsy.

The success of radiotherapy relies on tumor-specific delivery of radiosensitizers to attenuate hypoxia resistance. Here we report an ammonia-assisted hot water etching strategy for the generic synthesis of a library of small-sized (sub-50 nm) hollow mesoporous organosilica nanoparticles (HMONs) with mono, double, triple, and even quadruple framework hybridization of diverse organic moieties by changing only the introduced bissilylated organosilica precursors. The biodegradable thioether-hybridized HMONs are chosen for efficient co-delivery of tert -butyl hydroperoxide (TBHP) and iron pentacarbonyl (Fe(CO) 5 ). Distinct from conventional RT, radiodynamic therapy (RDT) is developed by taking advantage of X-ray-activated peroxy bond cleavage within TBHP to generate •OH, which can further attack Fe(CO) 5 to release CO molecules for gas therapy. Detailed in vitro and in vivo studies reveal the X-ray-activated cascaded release of •OH and CO molecules from TBHP/Fe(CO) 5 co-loaded PEGylated HMONs without reliance on oxygen, which brings about remarkable destructive effects against both normoxic and hypoxic cancers. A common failure of many cancer treatments is attributed to the resistance imparted by tumour hypoxia. Here, the authors report on the generic synthesis of small-sized hollow mesoporous organosilica nanoparticles which are designed for oxygen-independent X-ray-activated synergistic therapy.

The ultrahigh flexibility and elasticity achieved in freestanding single-crystalline ferroelectric oxide membranes have attracted much attention recently. However, for antiferroelectric oxides, the flexibility limit and fundamental mechanism in their freestanding membranes are still not explored clearly. Here, we successfully fabricate freestanding single-crystalline PbZrO 3 membranes by a water-soluble sacrificial layer technique. They exhibit good antiferroelectricity and have a commensurate/incommensurate modulated microstructure. Moreover, they also have good shape recoverability when bending with a small radius of curvature (about 2.4 μm for the thickness of 120 nm), corresponding to a bending strain of 2.5%. They could tolerate a maximum bending strain as large as 3.5%, far beyond their bulk counterpart. Our atomistic simulations reveal that this remarkable flexibility originates from the antiferroelectric-ferroelectric phase transition with the aid of polarization rotation. This study not only suggests the mechanism of antiferroelectric oxides to achieve high flexibility but also paves the way for potential applications in flexible electronics. Authors find that freestanding single crystalline antiferroelectric PbZrO 3 membranes exhibit remarkable flexibility that can endure a maximum bending strain of 3.5%, with the assistance of mechanical-induced antiferroelectric-ferroelectric phase transition.

The functional architecture of the human brain has been extensively described in terms of functional connectivity networks, detected from the low-frequency coherent neuronal fluctuations that can be observed in a resting state condition. Little is known, so far, about the changes in functional connectivity and in the topological properties of functional networks, associated with different brain diseases. In this study, we investigated alterations related to mesial temporal lobe epilepsy (mTLE), using resting state functional magnetic resonance imaging on 18 mTLE patients and 27 healthy controls. Functional connectivity among 90 cortical and subcortical regions was measured by temporal correlation. The related values were analyzed to construct a set of undirected graphs. Compared to controls, mTLE patients showed significantly increased connectivity within the medial temporal lobes, but also significantly decreased connectivity within the frontal and parietal lobes, and between frontal and parietal lobes. Our findings demonstrated that a large number of areas in the default-mode network of mTLE patients showed a significantly decreased number of connections to other regions. Furthermore, we observed altered small-world properties in patients, along with smaller degree of connectivity, increased n-to-1 connectivity, smaller absolute clustering coefficients and shorter absolute path length. We suggest that the mTLE alterations observed in functional connectivity and topological properties may be used to define tentative disease markers.

RNA domains within viral IRESs are crucial for initiating cap-independent translation of the genome in many positive-sense RNA viruses. However, the structures and mechanisms of these IRES domains remain unclear. Here, we present the 3 Å resolution crystal structure of the coxsackievirus B3 (CVB3) IRES domain V (dV) as a model for type I IRESs. The crystal structure revealed an elongated architecture of dV, with two sets of coaxially stacked stems forming an H-type four-way junction (4WJ) organized by an A-rich motif. Despite sequence dissimilarities, this dV from a type I IRES exhibits remarkable structural similarity to the analogous tertiary structures of the encephalomyocarditis virus (EMCV) JK domain and the hepatitis A virus (HAV) dV, which are typical domains in the type II and III IRESs, respectively. While SAXS studies indicate a similar RNA fold of dV in solution, structure-guided binding, computational modeling, and X-ray footprinting studies with and without the HEAT1 domain of eIF4G, compared to the analogous type II (EMCV JK) and III (HAV dV) domains, suggest that various IRESs maintain a common mechanism of eIF4G binding interactions during viral genome translation. Despite sequence variability, this structural conservation across IRES types may offer unique opportunities to develop universal antivirals targeting these structures. The structure of a type I viral IRES RNA that binds human eIF4G shares a common topology with related RNAs from type II and III IRESs, despite sequence variations, offering a prospect of developing universal antiviral drugs targeting these structures.

Background In this study, we tested whether a combination of radiomic features extracted from baseline pre-immunotherapy computed tomography (CT) images and clinicopathological characteristics could be used as novel noninvasive biomarkers for predicting the clinical benefits of non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs). Methods The data from 92 consecutive patients with lung cancer who had been treated with ICIs were retrospectively analyzed. In total, 88 radiomic features were selected from the pretreatment CT images for the construction of a random forest model. Radiomics model 1 was constructed based on the Rad-score. Using multivariate logistic regression analysis, the Rad-score and significant predictors were integrated into a single predictive model (radiomics nomogram model 1) to predict the durable clinical benefit (DCB) of ICIs. Radiomics model 2 was developed based on the same Rad-score as radiomics model 1.Using multivariate Cox proportional hazards regression analysis, the Rad-score, and independent risk factors, radiomics nomogram model 2 was constructed to predict the progression-free survival (PFS). Results The models successfully predicted the patients who would benefit from ICIs. For radiomics model 1, the area under the receiver operating characteristic curve values for the training and validation cohorts were 0.848 and 0.795, respectively, whereas for radiomics nomogram model 1, the values were 0.902 and 0.877, respectively. For the PFS prediction, the Harrell’s concordance indexes for the training and validation cohorts were 0.717 and 0.760, respectively, using radiomics model 2, whereas they were 0.749 and 0.791, respectively, using radiomics nomogram model 2. Conclusions CT-based radiomic features and clinicopathological factors can be used prior to the initiation of immunotherapy for identifying NSCLC patients who are the most likely to benefit from the therapy. This could guide the individualized treatment strategy for advanced NSCLC.

Background Tumor phototherapy especially photodynamic therapy (PDT) or photothermal therapy (PTT), has been considered as an attractive strategy to elicit significant immunogenic cell death (ICD) at an optimal tumor retention of PDT/PTT agents. Heptamethine cyanine dye (IR-780), a promising PDT/PTT agent, which can be used for near-infrared (NIR) fluorescence/photoacoustic (PA) imaging guided tumor phototherapy, however, the strong hydrophobicity, short circulation time, and potential toxicity in vivo hinder its biomedical applications. To address this challenge, we developed mesoporous polydopamine nanoparticles (MPDA) with excellent biocompatibility, PTT efficacy, and PA imaging ability, facilitating an efficient loading and protection of hydrophobic IR-780. Results The IR-780 loaded MPDA (IR-780@MPDA) exhibited high loading capacity of IR-780 (49.7 wt%), good physiological solubility and stability, and reduced toxicity. In vivo NIR fluorescence and PA imaging revealed high tumor accumulation of IR-780@MPDA. Furthermore, the combined PDT/PTT of IR-780@MPDA could induce ICD, triggered immunotherapeutic response to breast tumor by the activation of cytotoxic T cells, resulting in significant suppression of tumor growth in vivo. Conclusion This study demonstrated that the as-developed compact and biocompatible platform could induce combined PDT/PTT and accelerate immune activation via excellent tumor accumulation ability, offering multimodal tumor theranostics with negligible systemic toxicity. Graphical Abstract

Positive (+) sense RNA viruses include many important pathogens that exploit noncanonical translation mechanisms to express their genomes within the host cells. Unlike DNA or negative (−) sense RNA viruses, (+) sense RNA viruses can directly function as mRNAs, even though they lack typical features of host mRNAs, such as the 5′ cap structure required for canonical translation initiation. Instead, they exploit structured RNA elements to recruit host translational machinery without the 5′ cap, bypassing the canonical translation initiation mechanism. Prominent examples include internal ribosome entry sites (IRESs) and 3′ cap-independent translation enhancers (3′ CITEs). These RNA modules facilitate translation initiation by recruiting the ribosomal subunits, either directly or through initiation factors, and mediating long-range RNA-RNA interactions. Other regulatory motifs, such as frameshifting signals, allow the ribosome to shift reading frames to regulate protein output. All these RNA elements function through RNA-protein interactions and often utilize host and virus-encoded proteins to hijack the host’s translational apparatus. Over the past several years, various structural biology approaches, including biochemical and enzymatic probing, X-ray crystallography, nuclear magnetic resonance (NMR) spectroscopy, and cryogenic electron microscopy (cryo-EM), have revealed the unique structural roles of these viral RNA elements and their protein complexes. Although a few structures of IRES and CITE domains have been solved through these methods, the structures of these RNA elements and their structure-function relationship have remained largely unknown. This review discusses the current understanding of translation-related RNA structures in (+) sense RNA viruses, the critical RNA-protein interactions they mediate, and various structural biology approaches used to study them. Since the genome of these viruses serves as a template for two mutually exclusive virological processes, namely genome translation and replication, the review also discusses how viruses can utilize RNA structure-based strategies to regulate the switch between genome translation and replication, highlighting future directions for exploring these fundamental virological processes to develop antiviral therapeutics able to combat diseases caused by these pathogens.