Glucose dissociates DDX21 dimers to regulate mRNA splicing and tissue differentiation.

Glucose is a universal bioenergy source; however, its role in controlling protein interactions is unappreciated, as are its actions during differentiation-associated intracellular glucose elevation. Azido-glucose click chemistry identified glucose binding to a variety of RNA binding proteins (RBPs), including the DDX21 RNA helicase, which was found to be essential for epidermal differentiation. Glucose bound the ATP-binding domain of DDX21, altering protein conformation, inhibiting helicase activity, and dissociating DDX21 dimers. Glucose elevation during differentiation was associated with DDX21 re-localization from the nucleolus to the nucleoplasm where DDX21 assembled into larger protein complexes containing RNA splicing factors. DDX21 localized to specific SCUGSDGC motif in mRNA introns in a glucose-dependent manner and promoted the splicing of key pro-differentiation genes, including GRHL3, KLF4, OVOL1, and RBPJ. These findings uncover a biochemical mechanism of action for glucose in modulating the dimerization and function of an RNA helicase essential for tissue differentiation.

Selective IL-27 production by intestinal regulatory T cells permits gut-specific regulation of TH17 cell immunity.

Regulatory T cells (Treg cells) are instrumental in establishing immunological tolerance. However, the precise effector mechanisms by which Treg cells control a specific type of immune response in a given tissue remains unresolved. By simultaneously studying Treg cells from different tissue origins under systemic autoimmunity, in the present study we show that interleukin (IL)-27 is specifically produced by intestinal Treg cells to regulate helper T17 cell (TH17 cell) immunity. Selectively increased intestinal TH17 cell responses in mice with Treg cell-specific IL-27 ablation led to exacerbated intestinal inflammation and colitis-associated cancer, but also helped protect against enteric bacterial infection. Furthermore, single-cell transcriptomic analysis has identified a CD83+CD62Llo Treg cell subset that is distinct from previously characterized intestinal Treg cell populations as the main IL-27 producers. Collectively, our study uncovers a new Treg cell suppression mechanism crucial for controlling a specific type of immune response in a particular tissue and provides further mechanistic insights into tissue-specific Treg cell-mediated immune regulation.

In Vivo Target Gene Activation via CRISPR/Cas9-Mediated Trans-epigenetic Modulation.

Current genome-editing systems generally rely on inducing DNA double-strand breaks (DSBs). This may limit their utility in clinical therapies, as unwanted mutations caused by DSBs can have deleterious effects. CRISPR/Cas9 system has recently been repurposed to enable target gene activation, allowing regulation of endogenous gene expression without creating DSBs. However, in vivo implementation of this gain-of-function system has proven difficult. Here, we report a robust system for in vivo activation of endogenous target genes through trans-epigenetic remodeling. The system relies on recruitment of Cas9 and transcriptional activation complexes to target loci by modified single guide RNAs. As proof-of-concept, we used this technology to treat mouse models of diabetes, muscular dystrophy, and acute kidney disease. Results demonstrate that CRISPR/Cas9-mediated target gene activation can be achieved in vivo, leading to measurable phenotypes and amelioration of disease symptoms. This establishes new avenues for developing targeted epigenetic therapies against human diseases. VIDEO ABSTRACT.

Allosteric modulation and G-protein selectivity of the Ca2+-sensing receptor.

The calcium-sensing receptor (CaSR) is a family C G-protein-coupled receptor1 (GPCR) that has a central role in regulating systemic calcium homeostasis2,3. Here we use cryo-electron microscopy and functional assays to investigate the activation of human CaSR embedded in lipid nanodiscs and its coupling to functional Gi versus Gq proteins in the presence and absence of the calcimimetic drug cinacalcet. High-resolution structures show that both Gi and Gq drive additional conformational changes in the activated CaSR dimer to stabilize a more extensive asymmetric interface of the seven-transmembrane domain (7TM) that involves key protein-lipid interactions. Selective Gi and Gq coupling by the receptor is achieved through substantial rearrangements of intracellular loop 2 and the C terminus, which contribute differentially towards the binding of the two G-protein subtypes, resulting in distinct CaSR-G-protein interfaces. The structures also reveal that natural polyamines target multiple sites on CaSR to enhance receptor activation by zipping negatively charged regions between two protomers. Furthermore, we find that the amino acid L-tryptophan, a well-known ligand of CaSR extracellular domains, occupies the 7TM bundle of the G-protein-coupled protomer at the same location as cinacalcet and other allosteric modulators. Together, these results provide a framework for G-protein activation and selectivity by CaSR, as well as its allosteric modulation by endogenous and exogenous ligands.

A role for the C. elegans Argonaute protein CSR-1 in small nuclear RNA 3' processing.

The Integrator is a multi-subunit protein complex that catalyzes the maturation of snRNA transcripts via 3' cleavage, a step required for snRNA incorporation with snRNP for spliceosome biogenesis. Here we developed a GFP based in vivo snRNA misprocessing reporter as a readout of Integrator function and performed a genome-wide RNAi screen for Integrator regulators. We found that loss of the Argonaute encoding csr-1 gene resulted in widespread 3' misprocessing of snRNA transcripts that is accompanied by a significant increase in alternative splicing. Loss of the csr-1 gene down-regulates the germline expression of Integrator subunits 4 and 6 and is accompanied by a reduced protein translation efficiency of multiple Integrator catalytic and non-catalytic subunits. Through isoform and motif mutant analysis, we determined that CSR-1's effect on snRNA processing is dependent on its catalytic slicer activity but does not involve the CSR-1a isoform. Moreover, mRNA-sequencing revealed high similarity in the transcriptome profile between csr-1 and Integrator subunit knockdown via RNAi. Together, our findings reveal CSR-1 as a new regulator of the Integrator complex and implicate a novel role of this Argonaute protein in snRNA 3' processing.

B56δ long-disordered arms form a dynamic PP2A regulation interface coupled with global allostery and Jordan's syndrome mutations.

Intrinsically disordered regions (IDR) and short linear motifs (SLiMs) play pivotal roles in the intricate signaling networks governed by phosphatases and kinases. B56δ (encoded by PPP2R5D) is a regulatory subunit of protein phosphatase 2A (PP2A) with long IDRs that harbor a substrate-mimicking SLiM and multiple phosphorylation sites. De novo missense mutations in PPP2R5D cause intellectual disabilities (ID), macrocephaly, Parkinsonism, and a broad range of neurological symptoms. Our single-particle cryo-EM structures of the PP2A-B56δ holoenzyme reveal that the long, disordered arms at the B56δ termini fold against each other and the holoenzyme core. This architecture suppresses both the phosphatase active site and the substrate-binding protein groove, thereby stabilizing the enzyme in a closed latent form with dual autoinhibition. The resulting interface spans over 190 Šand harbors unfavorable contacts, activation phosphorylation sites, and nearly all residues with ID-associated mutations. Our studies suggest that this dynamic interface is coupled to an allosteric network responsive to phosphorylation and altered globally by mutations. Furthermore, we found that ID mutations increase the holoenzyme activity and perturb the phosphorylation rates, and the severe variants significantly increase the mitotic duration and error rates compared to the normal variant.

ChemMORT: an automatic ADMET optimization platform using deep learning and multi-objective particle swarm optimization.

Drug discovery and development constitute a laborious and costly undertaking. The success of a drug hinges not only good efficacy but also acceptable absorption, distribution, metabolism, elimination, and toxicity (ADMET) properties. Overall, up to 50% of drug development failures have been contributed from undesirable ADMET profiles. As a multiple parameter objective, the optimization of the ADMET properties is extremely challenging owing to the vast chemical space and limited human expert knowledge. In this study, a freely available platform called Chemical Molecular Optimization, Representation and Translation (ChemMORT) is developed for the optimization of multiple ADMET endpoints without the loss of potency (https://cadd.nscc-tj.cn/deploy/chemmort/). ChemMORT contains three modules: Simplified Molecular Input Line Entry System (SMILES) Encoder, Descriptor Decoder and Molecular Optimizer. The SMILES Encoder can generate the molecular representation with a 512-dimensional vector, and the Descriptor Decoder is able to translate the above representation to the corresponding molecular structure with high accuracy. Based on reversible molecular representation and particle swarm optimization strategy, the Molecular Optimizer can be used to effectively optimize undesirable ADMET properties without the loss of bioactivity, which essentially accomplishes the design of inverse QSAR. The constrained multi-objective optimization of the poly (ADP-ribose) polymerase-1 inhibitor is provided as the case to explore the utility of ChemMORT.

APLF facilitates interstrand DNA crosslink repair and replication fork protection to confer cisplatin resistance.

Replication stress converts the stalled forks into reversed forks, which is an important protection mechanism to prevent fork degradation and collapse into poisonous DNA double-strand breaks (DSBs). Paradoxically, the mechanism also acts in cancer cells to contribute to chemoresistance against various DNA-damaging agents. PARP1 binds to and is activated by stalled forks to facilitate fork reversal. Aprataxin and polynucleotide kinase/phosphatase-like factor (APLF) binds to PARP1 through the poly(ADP-ribose) zinc finger (PBZ) domain and is known to be involved in non-homologous end joining (NHEJ). Here, we identify a novel function of APLF involved in interstrand DNA crosslink (ICL) repair and fork protection. We demonstrate that PARP1 activity facilitates the APLF recruitment to stalled forks, enabling the FANCD2 recruitment to stalled forks. The depletion of APLF sensitizes cells to cisplatin, impairs ICL repair, reduces the FANCD2 recruitment to stalled forks, and results in nascent DNA degradation by MRE11 nucleases. Additionally, cisplatin-resistant cancer cells show high levels of APLF and homologous recombination-related gene expression. The depletion of APLF sensitizes cells to cisplatin and results in fork instability. Our results reveal the novel function of APLF to facilitate ICL repair and fork protection, thereby contributing to cisplatin-resistant phenotypes of cancer cells.

Secondary organic aerosol reduced by mixture of atmospheric vapours.

Secondary organic aerosol contributes to the atmospheric particle burden with implications for air quality and climate. Biogenic volatile organic compounds such as terpenoids emitted from plants are important secondary organic aerosol precursors with isoprene dominating the emissions of biogenic volatile organic compounds globally. However, the particle mass from isoprene oxidation is generally modest compared to that of other terpenoids. Here we show that isoprene, carbon monoxide and methane can each suppress the instantaneous mass and the overall mass yield derived from monoterpenes in mixtures of atmospheric vapours. We find that isoprene 'scavenges' hydroxyl radicals, preventing their reaction with monoterpenes, and the resulting isoprene peroxy radicals scavenge highly oxygenated monoterpene products. These effects reduce the yield of low-volatility products that would otherwise form secondary organic aerosol. Global model calculations indicate that oxidant and product scavenging can operate effectively in the real atmosphere. Thus highly reactive compounds (such as isoprene) that produce a modest amount of aerosol are not necessarily net producers of secondary organic particle mass and their oxidation in mixtures of atmospheric vapours can suppress both particle number and mass of secondary organic aerosol. We suggest that formation mechanisms of secondary organic aerosol in the atmosphere need to be considered more realistically, accounting for mechanistic interactions between the products of oxidizing precursor molecules (as is recognized to be necessary when modelling ozone production).

Cortical activation and brain network efficiency during dual tasks: An fNIRS study.

OBJECTIVE: Dual task (DT) is a commonly used paradigm indicative of executive functions. Brain activities during DT walking is usually measured by portable functional near infrared spectroscopy (fNIRS). Previous studies focused on cortical activation in prefrontal cortex and overlooked other brain regions such as sensorimotor cortices. This study is aimed at investigating the modulations of cortical activation and brain network efficiency in multiple brain regions from single to dual tasks with different complexities and their relationships with DT performance. METHODS: Forty-two healthy adults [12 males; mean age: 27.7 (SD=6.5) years] participated in this study. Participants performed behavioral tasks with portable fNIRS simultaneous recording. There were three parts of behavioral tasks: cognitive tasks while standing (serial subtraction of 3's and 7's), walking alone and DT (walk while subtraction, including serial subtraction of 3's and 7's). Cognitive cost, walking cost and cost sum (i.e., sum of cognitive and walking costs) were calculated for DT. Cortical activation, local and global network efficiency were calculated for each task. RESULTS: The cognitive cost was greater and the walking cost was less during DT with subtraction 3's compared with 7's (P's = 0.032 and 0.019, respectively). Cortical activation and network efficiency were differentially modulated among single and dual tasks (P's < 0.05). Prefrontal activation during DT was positively correlated with DT costs, while network efficiency was negatively correlated with DT costs (P's < 0.05). CONCLUSIONS: Our results revealed prefrontal over-activation and reduced network efficiency in individuals with poor DT performance. Our findings suggest that reduced network efficiency could be a possible mechanism contributing to poor DT performance, which is accompanied by compensatory prefrontal over-activation.

Defect Compensation and Lattice Stabilization Enables High Voltage Output in Tin Halide Perovskite Solar Cells.

Tin halide perovskite solar cells (PSCs) are regarded as the most promising lead-free alternatives for photovoltaic applications. However, they still suffer from uncompetitive photovoltaic performance because of the facile Sn2+ oxidation and Sn-related defects. Herein, a defect and carrier management strategy by using diaminopyridine (DP) and 4-bromo-2,6-diaminopyridine (4BrDP) as multifunctional additives for tin halide perovskites is reported. Both DP and 4BrDP induced strong interaction with tin perovskites by coordinate bonding and N─H···I hydrogen bonding, which greatly suppresses the micro-strain and Urbach energy of tin halide perovskite films. The strong hydrogen bonding inhibits the formation of I3 - and related defect density. Meanwhile, the electron-donor species of halogen bond in 4BrDP provides higher reactivity of 2 and 6 sites, which indicates stronger passivation ability with tin halide perovskites. These advances enable a champion power conversion efficiency (PCE) of 13.40% in 4BrDP-processed devices with remarkable improvement in both open-circuit voltage (Voc) of 881 mV and fill factor (FF) of 71.26%. The 4BrDP devices retain 91% and 82% of the pristine PCE after 2000 h storage in N2 atmosphere and 1000 h under 85 °C, respectively. Therefore, this work provides new insight into molecular design for high-performance and stable lead-free optoelectronics.

Deep Learning-Based Localization and Detection of Malpositioned Endotracheal Tube on Portable Supine Chest Radiographs in Intensive and Emergency Medicine: A Multicenter Retrospective Study.

OBJECTIVES: We aimed to develop a computer-aided detection (CAD) system to localize and detect the malposition of endotracheal tubes (ETTs) on portable supine chest radiographs (CXRs). DESIGN: This was a retrospective diagnostic study. DeepLabv3+ with ResNeSt50 backbone and DenseNet121 served as the model architecture for segmentation and classification tasks, respectively. SETTING: Multicenter study. PATIENTS: For the training dataset, images meeting the following inclusion criteria were included: 1) patient age greater than or equal to 20 years; 2) portable supine CXR; 3) examination in emergency departments or ICUs; and 4) examination between 2015 and 2019 at National Taiwan University Hospital (NTUH) (NTUH-1519 dataset: 5,767 images). The derived CAD system was tested on images from chronologically (examination during 2020 at NTUH, NTUH-20 dataset: 955 images) or geographically (examination between 2015 and 2020 at NTUH Yunlin Branch [YB], NTUH-YB dataset: 656 images) different datasets. All CXRs were annotated with pixel-level labels of ETT and with image-level labels of ETT presence and malposition. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: For the segmentation model, the Dice coefficients indicated that ETT would be delineated accurately (NTUH-20: 0.854; 95% CI, 0.824-0.881 and NTUH-YB: 0.839; 95% CI, 0.820-0.857). For the classification model, the presence of ETT could be accurately detected with high accuracy (area under the receiver operating characteristic curve [AUC]: NTUH-20, 1.000; 95% CI, 0.999-1.000 and NTUH-YB: 0.994; 95% CI, 0.984-1.000). Furthermore, among those images with ETT, ETT malposition could be detected with high accuracy (AUC: NTUH-20, 0.847; 95% CI, 0.671-0.980 and NTUH-YB, 0.734; 95% CI, 0.630-0.833), especially for endobronchial intubation (AUC: NTUH-20, 0.991; 95% CI, 0.969-1.000 and NTUH-YB, 0.966; 95% CI, 0.933-0.991). CONCLUSIONS: The derived CAD system could localize ETT and detect ETT malposition with excellent performance, especially for endobronchial intubation, and with favorable potential for external generalizability.

A newly evolved rice-specific gene JAUP1 regulates jasmonate biosynthesis and signalling to promote root development and multi-stress tolerance.

Root architecture and function are critical for plants to secure water and nutrient supply from the soil, but environmental stresses alter root development. The phytohormone jasmonic acid (JA) regulates plant growth and responses to wounding and other stresses, but its role in root development for adaptation to environmental challenges had not been well investigated. We discovered a novel JA Upregulated Protein 1 gene (JAUP1) that has recently evolved in rice and is specific to modern rice accessions. JAUP1 regulates a self-perpetuating feed-forward loop to activate the expression of genes involved in JA biosynthesis and signalling that confers tolerance to abiotic stresses and regulates auxin-dependent root development. Ectopic expression of JAUP1 alleviates abscisic acid- and salt-mediated suppression of lateral root (LR) growth. JAUP1 is primarily expressed in the root cap and epidermal cells (EPCs) that protect the meristematic stem cells and emerging LRs. Wound-activated JA/JAUP1 signalling promotes crosstalk between the root cap of LR and parental root EPCs, as well as induces cell wall remodelling in EPCs overlaying the emerging LR, thereby facilitating LR emergence even under ABA-suppressive conditions. Elevated expression of JAUP1 in transgenic rice or natural rice accessions enhances abiotic stress tolerance and reduces grain yield loss under a limited water supply. We reveal a hitherto unappreciated role for wound-induced JA in LR development under abiotic stress and suggest that JAUP1 can be used in biotechnology and as a molecular marker for breeding rice adapted to extreme environmental challenges and for the conservation of water resources.

An End-to-End Platform for Digital Pathology Using Hyperspectral Autofluorescence Microscopy and Deep Learning-Based Virtual Histology.

Conventional histopathology involves expensive and labor-intensive processes that often consume tissue samples, rendering them unavailable for other analyses. We present a novel end-to-end workflow for pathology powered by hyperspectral microscopy and deep learning. First, we developed a custom hyperspectral microscope to nondestructively image the autofluorescence of unstained tissue sections. We then trained a deep learning model to use autofluorescence to generate virtual histologic stains, which avoids the cost and variability of chemical staining procedures and conserves tissue samples. We showed that the virtual images reproduce the histologic features present in the real-stained images using a randomized nonalcoholic steatohepatitis (NASH) scoring comparison study, where both real and virtual stains are scored by pathologists (D.T., A.D.B., R.K.P.). The test showed moderate-to-good concordance between pathologists' scoring on corresponding real and virtual stains. Finally, we developed deep learning-based models for automated NASH Clinical Research Network score prediction. We showed that the end-to-end automated pathology platform is comparable with an independent panel of pathologists for NASH Clinical Research Network scoring when evaluated against the expert pathologist consensus scores. This study provides proof of concept for this virtual staining strategy, which could improve cost, efficiency, and reliability in pathology and enable novel approaches to spatial biology research.

BioNet: a large-scale and heterogeneous biological network model for interaction prediction with graph convolution.

MOTIVATION: Understanding chemical-gene interactions (CGIs) is crucial for screening drugs. Wet experiments are usually costly and laborious, which limits relevant studies to a small scale. On the contrary, computational studies enable efficient in-silico exploration. For the CGI prediction problem, a common method is to perform systematic analyses on a heterogeneous network involving various biomedical entities. Recently, graph neural networks become popular in the field of relation prediction. However, the inherent heterogeneous complexity of biological interaction networks and the massive amount of data pose enormous challenges. This paper aims to develop a data-driven model that is capable of learning latent information from the interaction network and making correct predictions. RESULTS: We developed BioNet, a deep biological networkmodel with a graph encoder-decoder architecture. The graph encoder utilizes graph convolution to learn latent information embedded in complex interactions among chemicals, genes, diseases and biological pathways. The learning process is featured by two consecutive steps. Then, embedded information learnt by the encoder is then employed to make multi-type interaction predictions between chemicals and genes with a tensor decomposition decoder based on the RESCAL algorithm. BioNet includes 79 325 entities as nodes, and 34 005 501 relations as edges. To train such a massive deep graph model, BioNet introduces a parallel training algorithm utilizing multiple Graphics Processing Unit (GPUs). The evaluation experiments indicated that BioNet exhibits outstanding prediction performance with a best area under Receiver Operating Characteristic (ROC) curve of 0.952, which significantly surpasses state-of-theart methods. For further validation, top predicted CGIs of cancer and COVID-19 by BioNet were verified by external curated data and published literature.

ABC-Net: a divide-and-conquer based deep learning architecture for SMILES recognition from molecular images.

Structural information for chemical compounds is often described by pictorial images in most scientific documents, which cannot be easily understood and manipulated by computers. This dilemma makes optical chemical structure recognition (OCSR) an essential tool for automatically mining knowledge from an enormous amount of literature. However, existing OCSR methods fall far short of our expectations for realistic requirements due to their poor recovery accuracy. In this paper, we developed a deep neural network model named ABC-Net (Atom and Bond Center Network) to predict graph structures directly. Based on the divide-and-conquer principle, we propose to model an atom or a bond as a single point in the center. In this way, we can leverage a fully convolutional neural network (CNN) to generate a series of heat-maps to identify these points and predict relevant properties, such as atom types, atom charges, bond types and other properties. Thus, the molecular structure can be recovered by assembling the detected atoms and bonds. Our approach integrates all the detection and property prediction tasks into a single fully CNN, which is scalable and capable of processing molecular images quite efficiently. Experimental results demonstrate that our method could achieve a significant improvement in recognition performance compared with publicly available tools. The proposed method could be considered as a promising solution to OCSR problems and a starting point for the acquisition of molecular information in the literature.

Focused ultrasound-mediated blood-brain barrier opening is safe and feasible with moderately hypofractionated radiotherapy for brainstem diffuse midline glioma.

BACKGROUND: Diffuse midline glioma (DMG) is a pediatric tumor with dismal prognosis. Systemic strategies have been unsuccessful and radiotherapy (RT) remains the standard-of-care. A central impediment to treatment is the blood-brain barrier (BBB), which precludes drug delivery to the central nervous system (CNS). Focused ultrasound (FUS) with microbubbles can transiently and non-invasively disrupt the BBB to enhance drug delivery. This study aimed to determine the feasibility of brainstem FUS in combination with clinical doses of RT. We hypothesized that FUS-mediated BBB-opening (BBBO) is safe and feasible with 39 Gy RT. METHODS: To establish a safety timeline, we administered FUS to the brainstem of non-tumor bearing mice concurrent with or adjuvant to RT; our findings were validated in a syngeneic brainstem murine model of DMG receiving repeated sonication concurrent with RT. The brainstems of male B6 (Cg)-Tyrc-2J/J albino mice were intracranially injected with mouse DMG cells (PDGFB+, H3.3K27M, p53-/-). A clinical RT dose of 39 Gy in 13 fractions (39 Gy/13fx) was delivered using the Small Animal Radiation Research Platform (SARRP) or XRAD-320 irradiator. FUS was administered via a 0.5 MHz transducer, with BBBO and tumor volume monitored by magnetic resonance imaging (MRI). RESULTS: FUS-mediated BBBO did not affect cardiorespiratory rate, motor function, or tissue integrity in non-tumor bearing mice receiving RT. Tumor-bearing mice tolerated repeated brainstem BBBO concurrent with RT. 39 Gy/13fx offered local control, though disease progression occurred 3-4 weeks post-RT. CONCLUSION: Repeated FUS-mediated BBBO is safe and feasible concurrent with RT. In our syngeneic DMG murine model, progression occurs, serving as an ideal model for future combination testing with RT and FUS-mediated drug delivery.

Lower contact force predicts right pulmonary vein carina breakthrough after ablation index-guided pulmonary vein isolation using high-power short-duration.

INTRODUCTION: Carina breakthrough (CB) at the right pulmonary vein (RPV) can occur after circumferential pulmonary vein isolation (PVI) due to epicardial bridging or transient tissue edema. High-power short-duration (HPSD) ablation may increase the incidence of RPV CB. Currently, the surrogate of ablation parameters to predict RPV CB is not well established. This study investigated predictors of RPV CB in patients undergoing ablation index (AI)-guided PVI with HPSD. METHODS: The study included 62 patients with symptomatic atrial fibrillation (AF) who underwent AI-guided PVI using HPSD. Patients were categorized into two groups based on the presence or absence of RPV CB. Lesions adjacent to the RPV carina were assessed, and CB was confirmed through residual voltage, low voltage along the ablation lesions, and activation wavefront propagation. RESULTS: Out of the 62 patients, 21 (33.87%) experienced RPV CB (Group 1), while 41 (66.13%) achieved first-pass RPV isolation (Group 2). Despite similar AI and HPSD, patients with RPV CB had lower contact force (CF) at lesions adjacent to the RPV carina. Receiver operating characteristic (ROC) curve analysis identified CF < 10.5 g as a predictor of RPV CB, with 75.7% sensitivity and 56.2% specificity (area under the curve: 0.714). CONCLUSION: In patients undergoing AI-guided PVI with HPSD, lower CF adjacent to the carina was associated with a higher risk of RPV CB. These findings suggest that maintaining higher CF during ablation in this region may reduce the occurrence of RPV CB.

Murine cytotoxic CD4+ T cells in the tumor microenvironment are at a hyper-maturation stage of Th1 CD4+ T cells sustained by IL-12.

The roles of tumor-infiltrating CD4+Foxp3- T cells are not well characterized due to their plasticity of differentiation, and varying levels of activation or exhaustion. To further clarify this issue, we used a model featuring subcutaneous murine colon cancer and analyzed the dynamic changes of phenotype and function of the tumor-associated CD4+ T-cell response. We found that, even at a late stage of tumor growth, the tumor-infiltrating CD4+Foxp3- T cells still expressed effector molecules, inflammatory cytokines and molecules that are expressed at reduced levels in exhausted cells. We used microarrays to examine the gene-expression profiles of different subsets of CD4+ T cells and revealed that the tumor-infiltrating CD4+Foxp3- T cells expressed not only type 1 helper (Th1) cytokines, but also cytolytic granules such as those encoded by Gzmb and Prf1. In contrast to CD4+ regulatory T cells, these cells exclusively co-expressed natural killer receptor markers and cytolytic molecules as shown by flow-cytometry studies. We used an ex vivo killing assay and proved that they could directly suppress CT26 tumor cells through granzyme B and perforin. Finally, we used pathway analysis and ex vivo stimulation to confirm that the CD4+Foxp3- T cells expressed higher levels of IL12rb1 genes and were activated by the IL-12/IL-27 pathway. In conclusion, this work finds that, in late-stage tumors, the tumor-infiltrating lymphocyte population of CD4+ cells harbored a sustained, hyper-maturated Th1 status with cytotoxic function supported by IL-12.

Age and light damage influence Fzd5 regulation of ocular growth-related genes.

Genetic and environmental factors can independently or coordinatively drive ocular axis growth. Mutations in FRIZZLED5 (FZD5) have been associated with microphthalmia, coloboma, and, more recently, high myopia. The molecular mechanism of how Fzd5 participates in ocular growth remains unknown. In this study, we compiled a list of human genes associated with ocular growth abnormalities based on public databases and a literature search. We identified a set of ocular growth-related genes from the list that was altered in the Fzd5 mutant mice by RNAseq analysis at different time points. The Fzd5 regulation of this set of genes appeared to be impacted by age and light damage. Further bioinformatical analysis indicated that these genes are extracellular matrix (ECM)-related; and meanwhile an altered Wnt signaling was detected. Altogether, the data suggest that Fzd5 may regulate ocular growth through regulating ECM remodeling, hinting at a genetic-environmental interaction in gene regulation of ocular axis control.