Role of cyclophilin A in aggravation of myocardial ischemia reperfusion injury via regulation of apoptosis mediated by thioredoxin-interacting protein.

BACKGROUND: The progression and persistence of myocardial ischemia/reperfusion injury (MI/RI) are strongly linked to local inflammatory responses and oxidative stress. Cyclophilin A (CypA), a pro-inflammatory factor, is involved in various cardiovascular diseases. However, the role and mechanism of action of CypA in MI/RI are still not fully understood. METHODS: We used the Gene Expression Omnibus (GEO) database for bioinformatic analysis. We collected blood samples from patients and controls for detecting the levels of serum CypA using enzyme-linked immunosorbent assay (ELISA) kits. We then developed a myocardial ischemia/reperfusion (I/R) injury model in wild-type (WT) mice and Ppia-/- mice. We utilized echocardiography, hemodynamic measurements, hematoxylin and eosin (H&E) staining, immunohistochemistry, enzyme-linked immunosorbent assay, and terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) staining to determine the role of CypA in myocardial I/R injury. Finally, we conducted an in vitrostudy, cell transfection, flow cytometry, RNA interference, and a co-immunoprecipitation assay to clarify the mechanism of CypA in aggravating cardiomyocyte apoptosis. RESULTS: We found that CypA inhibited TXNIP degradation to enhance oxidative stress-induced cardiomyocyte apoptosis during MI/RI. By comparing and analyzing CypA expression in patients with coronary atherosclerotic heart disease and in healthy controls, we found that CypA was upregulated in patients with Coronary Atmospheric Heart Disease, and its expression was positively correlated with Gensini scores. In addition, CypA deficiency decreased cytokine expression, oxidative stress, and cardiomyocyte apoptosis in I/R-treated mice, eventually alleviating cardiac dysfunction. CypA knockdown also reduced H2O2-induced apoptosis in H9c2 cells. Mechanistically, we found that CypA inhibited K48-linked ubiquitination mediated by atrophin-interacting protein 4 (AIP4) and proteasomal degradation of TXNIP, a thioredoxin-binding protein that mediates oxidative stress and induces apoptosis. CONCLUSION: These findings highlight the critical role CypA plays in myocardial injury caused by oxidative stress-induced apoptosis, indicating that CypA can be a viable biomarker and a therapeutic target candidate for MI/RI.

The extracellular cyclophilin A-integrin ß2 complex as a therapeutic target of viral pneumonia.

The acute respiratory virus infection can induce uncontrolled inflammatory responses, such as cytokine storm and viral pneumonia, which are the major causes of death in clinical cases. Cyclophilin A (CypA) is mainly distributed in the cytoplasm of resting cells and released into the extracellular space in response to inflammatory stimuli. Extracellular CypA (eCypA) is upregulated and promotes inflammatory response in severe COVID-19 patients. However, how eCypA promotes virus-induced inflammatory response remains elusive. Here, we observe that eCypA is induced by influenza A and B viruses and SARS-CoV-2 in cells, mice, or patients. Anti-CypA mAb reduces pro-inflammatory cytokines production, leukocytes infiltration, and lung injury in virus-infected mice. Mechanistically, eCypA binding to integrin ß2 triggers integrin activation, thereby facilitating leukocyte trafficking and cytokines production via the focal adhesion kinase (FAK)/GTPase and FAK/ERK/P65 pathways, respectively. These functions are suppressed by the anti-CypA mAb that specifically blocks eCypA-integrin ß2 interaction. Overall, our findings reveal that eCypA-integrin ß2 signaling mediates virus-induced inflammatory response, indicating that eCypA is a potential target for antibody therapy against viral pneumonia.

A community challenge to predict clinical outcomes after immune checkpoint blockade in non-small cell lung cancer.

BACKGROUND: Predictive biomarkers of immune checkpoint inhibitor (ICI) efficacy are currently lacking for non-small cell lung cancer (NSCLC). Here, we describe the results from the Anti-PD-1 Response Prediction DREAM Challenge, a crowdsourced initiative that enabled the assessment of predictive models by using data from two randomized controlled clinical trials (RCTs) of ICIs in first-line metastatic NSCLC. METHODS: Participants developed and trained models using public resources. These were evaluated with data from the CheckMate 026 trial (NCT02041533), according to the model-to-data paradigm to maintain patient confidentiality. The generalizability of the models with the best predictive performance was assessed using data from the CheckMate 227 trial (NCT02477826). Both trials were phase III RCTs with a chemotherapy control arm, which supported the differentiation between predictive and prognostic models. Isolated model containers were evaluated using a bespoke strategy that considered the challenges of handling transcriptome data from clinical trials. RESULTS: A total of 59 teams participated, with 417 models submitted. Multiple predictive models, as opposed to a prognostic model, were generated for predicting overall survival, progression-free survival, and progressive disease status with ICIs. Variables within the models submitted by participants included tumor mutational burden (TMB), programmed death ligand 1 (PD-L1) expression, and gene-expression-based signatures. The best-performing models showed improved predictive power over reference variables, including TMB or PD-L1. CONCLUSIONS: This DREAM Challenge is the first successful attempt to use protected phase III clinical data for a crowdsourced effort towards generating predictive models for ICI clinical outcomes and could serve as a blueprint for similar efforts in other tumor types and disease states, setting a benchmark for future studies aiming to identify biomarkers predictive of ICI efficacy. TRIAL REGISTRATION: CheckMate 026; NCT02041533, registered January 22, 2014. CheckMate 227; NCT02477826, registered June 23, 2015.

Hypothalamic-Pituitary-Adrenal Axis and Epilepsy.

Epilepsy is a recurrent, transient seizure disorder of the nervous system that affects the intellectual development, life and work, and psychological health of patients. People with epilepsy worldwide experience great suffering. Stressful stimuli such as infection, mental stress, and sleep deprivation are important triggers of epilepsy, and chronic stressful stimuli can lead to frequent seizures and comorbidities. The hypothalamic-pituitary-adrenal (HPA) axis is the most important system involved in the body's stress response, and dysfunction thereof is thought to be associated with core epilepsy symptoms and related psychopathology. This article explores the intrinsic relationships of corticotropin-releasing hormone, adrenocorticotropic hormone, and glucocorticoids with epilepsy in order to reveal the role of the HPA axis in the pathogenesis of epilepsy. We hope that this information will yield future possible directions and ideas for fully understanding the pathogenesis of epilepsy and developing antiepileptic drugs.

Cyclophilin A facilitates influenza B virus replication by stabilizing viral proteins.

Influenza B circulates annually and causes substantial disease burden in humans. However, little is known about the infection mechanisms of influenza B virus (IBV). Here, we find that the host factor cyclophilin A (CypA) facilitates IBV replication by targeting IBV non-structural protein 1 (BNS1) and nucleoprotein (BNP). CypA promotes OTUD4-mediated K48-linked BNS1 deubiquitination to stabilize BNS1 by upregulating OTUD4 expression. Meanwhile, CypA and the E3 ligase MIB1 competitively interact with BNP to inhibit its proteasomal degradation. Moreover, cyclosporine A treatment or CypA R55A mutation results in an impaired function of CypA in IBV replication. Notably, BNP hijacks CypA into the nucleus to enhance the activity of viral ribonucleoprotein complexes by enhancing the interaction between BNP and IBV polymerase basic protein 1. Taken together, this study unveils the critical role of CypA in facilitating IBV replication, suggesting that CypA is a promising target for anti-IBV drug.

Enhancing microstructure and device performance of InGaN quantum dot micro-LEDs through substrate off-cut angle modulation.

InGaN quantum dots (QDs) are regarded as a compelling candidate material for the fabrication of high-quality GaN-based micro-LEDs. In this work, to study the impact of a substrate structure on InGaN QDs and QD-based micro-LEDs, GaN-on-sapphire substrates with off-cut angles toward the a-axis of 0.2°, 0.4°, and 0.7° were utilized as templates for the fabrication of InGaN QDs and InGaN QDs-based micro-LEDs. Experimental results show that GaN template with 0.4° off-cut angle exhibits the narrowest terrace width and enables InGaN QDs to be higher and more uniform. The InGaN QD sample grown on 0.4° substrate has a very small wavelength shift of 2.5 nm with temperature increasing and owns the longest photoluminescence peak wavelength implying the highest In content. Furthermore, electroluminescence (EL) spectra demonstrate that QD-based micro-LED array has excellent wavelength stability under various injection currents, and the stability can be improved further on a GaN template with narrower terraces. The results indicate that altering the terrace width of GaN template is a feasible scheme for improving the properties of GaN-based micro-LEDs.

cgMSI: pathogen detection within species from nanopore metagenomic sequencing data.

BACKGROUND: Metagenomic sequencing is an unbiased approach that can potentially detect all the known and unidentified strains in pathogen detection. Recently, nanopore sequencing has been emerging as a highly potential tool for rapid pathogen detection due to its fast turnaround time. However, identifying pathogen within species is nontrivial for nanopore sequencing data due to the high sequencing error rate. RESULTS: We developed the core gene alleles metagenome strain identification (cgMSI) tool, which uses a two-stage maximum a posteriori probability estimation method to detect pathogens at strain level from nanopore metagenomic sequencing data at low computational cost. The cgMSI tool can accurately identify strains and estimate relative abundance at 1× coverage. CONCLUSIONS: We developed cgMSI for nanopore metagenomic pathogen detection within species. cgMSI is available at https://github.com/ZHU-XU-xmu/cgMSI .

NLRC4 promotes the cGAS-STING signaling pathway by facilitating CBL-mediated K63-linked polyubiquitination of TBK1.

TANK-binding kinase 1 (TBK1) is crucial in producing type Ⅰ interferons (IFN-Ⅰ) that play critical functions in antiviral innate immunity. The tight regulation of TBK1, especially its activation, is very important. Here we identify NLRC4 as a positive regulator of TBK1. Ectopic expression of NLRC4 facilitates the activation of the IFN-ß promoter, the mRNA levels of IFN-ß, ISG54, and ISG56, and the nuclear translocation of interferon regulatory factor 3 induced by cGAS and STING. Consistently, under herpes simplex virus-1 (HSV-1) infection, knockdown or knockout of NLRC4 in BJ cells and primary peritoneal macrophages from Nlrc4-deficient (Nlrc4-/- ) mice show attenuated Ifn-ß, Isg54, and Isg56 mRNA transcription, TBK1 phosphorylation, and augmented viral replications. Moreover, Nlrc4-/- mice show higher mortality upon HSV-1 infection. Mechanistically, NLRC4 facilitates the interaction between TBK1 and the E3 ubiquitin ligase CBL to enhance the K63-linked polyubiquitination of TBK1. Our study elucidates a previously uncharacterized function for NLRC4 in upregulating the cGAS-STING signaling pathway and antiviral innate immunity.

PROTAC targeting cyclophilin A controls virus-induced cytokine storm.

Cytokine storms caused by viruses are associated with elevated cytokine levels and uncontrolled inflammatory responses that can lead to acute respiratory distress syndrome. Current antiviral therapies are not sufficient to prevent or treat these complications. Cyclophilin A (CypA) is a key factor that regulates the production of multiple cytokines and could be a potential therapeutic target for cytokine storms. Here, three proteolysis targeting chimeras (PROTACs) targeting CypA were designed. These PROTACs bind to CypA, enhance its ubiquitination, and promote its degradation in both cell lines and mouse organs. During influenza B virus (IBV) infection, PROTAC-mediated CypA depletion reduces P65 phosphorylation and NF-κB-mediated proinflammatory cytokine production in A549 cells. Moreover, Comp-K targeting CypA suppresses excessive secretion of proinflammatory cytokines in bronchoalveolar lavage fluid, reduces lung injury, and enhances survival rates of IBV-infected mice. Collectively, we provide PROTACs targeting CypA, which are potential candidates for the control of cytokine storms.

Investigation on the Optical Properties of Micro-LEDs Based on InGaN Quantum Dots Grown by Molecular Beam Epitaxy.

InGaN quantum dots (QDs) have attracted significant attention as a promising material for high-efficiency micro-LEDs. In this study, plasma-assisted molecular beam epitaxy (PA-MBE) was used to grow self-assembled InGaN QDs for the fabrication of green micro-LEDs. The InGaN QDs exhibited a high density of over 3.0 × 1010 cm-2, along with good dispersion and uniform size distribution. Micro-LEDs based on QDs with side lengths of the square mesa of 4, 8, 10, and 20 µm were prepared. Attributed to the shielding effect of QDs on the polarized field, luminescence tests indicated that InGaN QDs micro-LEDs exhibited excellent wavelength stability with increasing injection current density. The micro-LEDs with a side length of 8 µm showed a shift of 16.9 nm in the peak of emission wavelength as the injection current increased from 1 A/cm2 to 1000 A/cm2. Furthermore, InGaN QDs micro-LEDs maintained good performance stability with decreasing platform size at low current density. The EQE peak of the 8 µm micro-LEDs is 0.42%, which is 91% of the EQE peak of the 20 µm devices. This phenomenon can be attributed to the confinement effect of QDs on carriers, which is significant for the development of full-color micro-LED displays.

Self-powered (In,Ga)N-nanowire-based photodetector with fast response speed for under-seawater detection.

Due to the requirements of oceanography exploration and detection, self-powered photodetectors (PDs) with low-power consumption are essential for the next-generation optoelectronic applications. In this work, we successfully demonstrate a self-powered photoelectrochemical (PEC) PD in seawater based on the (In,Ga)N/GaN core-shell heterojunction nanowires. Compared to those of the PD in pure water, it is found that the upward and downward overshooting features of current can be the key reason contributing to the much faster response speed of the PD in seawater. Thanks to the enhanced response speed, the rise time of PD can be reduced more than 80%, and the fall time remains only 30% by applying in seawater instead of pure water. The key factors of generating these overshooting features should be the instantaneous temperature gradient, carrier accumulation and elimination on the semiconductor/electrolyte interfaces at the moments of light on and off. By the analysis of experimental results, the Na+ and Cl- ions are proposed to be the main factors affecting the PD behavior in seawater, which can enhance the conductivity and accelerate the oxidation-reduction reaction significantly. This work paves an effective way to develop the new self-powered PDs for the wide applications in under-seawater detection and communication.

Use of dual genomic sequencing to screen mitochondrial diseases in pediatrics: a retrospective analysis.

Mitochondrial diseases (MDs) were a large group multisystem disorders, attributable in part to the dual genomic control. The advent of massively sequencing has improved diagnostic rates and speed, and was increasingly being used as a first-line diagnostic test. Paediatric patients (aged < 18 years) who underwent dual genomic sequencing were enrolled in this retrospective multicentre study. We evaluated the mitochondrial disease criteria (MDC) and molecular diagnostic yield of dual genomic sequencing. Causative variants were identified in 177 out of 503 (35.2%) patients using dual genomic sequencing. Forty-six patients (9.1%) had mitochondria-related variants, including 25 patients with nuclear DNA (nDNA) variants, 15 with mitochondrial DNA (mtDNA) variants, and six with dual genomic variants (MT-ND6 and POLG; MT-ND5 and RARS2; MT-TL1 and NARS2; MT-CO2 and NDUFS1; MT-CYB and SMARCA2; and CHRNA4 and MT-CO3). Based on the MDC, 15.2% of the patients with mitochondria-related variants were classified as "unlikely to have mitochondrial disorder". Moreover, 4.5% of the patients with non-mitochondria-related variants and 1.43% with negative genetic tests, were classified as "probably having mitochondrial disorder". Dual genomic sequencing in suspected MDs provided a more comprehensive and accurate diagnosis for pediatric patients, especially for patients with dual genomic variants.

Prioritizing prognostic-associated subpopulations and individualized recurrence risk signatures from single-cell transcriptomes of colorectal cancer.

Colorectal cancer (CRC) is one of the most common gastrointestinal malignancies. There are few recurrence risk signatures for CRC patients. Single-cell RNA-sequencing (scRNA-seq) provides a high-resolution platform for prognostic signature detection. However, scRNA-seq is not practical in large cohorts due to its high cost and most single-cell experiments lack clinical phenotype information. Few studies have been reported to use external bulk transcriptome with survival time to guide the detection of key cell subtypes in scRNA-seq data. We proposed scRankXMBD, a computational framework to prioritize prognostic-associated cell subpopulations based on within-cell relative expression orderings of gene pairs from single-cell transcriptomes. scRankXMBD achieves higher precision and concordance compared with five existing methods. Moreover, we developed single-cell gene pair signatures to predict recurrence risk for patients individually. Our work facilitates the application of the rank-based method in scRNA-seq data for prognostic biomarker discovery and precision oncology. scRankXMBD is available at https://github.com/xmuyulab/scRank-XMBD. (XMBD:Xiamen Big Data, a biomedical open software initiative in the National Institute for Data Science in Health and Medicine, Xiamen University, China.).

The Effect of Periodic Duty Cyclings in Metal-Modulated Epitaxy on GaN:Mg Film.

Metal modulation epitaxy (MME) is a technique in which metal beams (Al, Ga, In, and Mg) are switched on and off in short periods in an RF MBE system while a continuous nitrogen plasma beam is kept on. We systematically studied the effect of periodic duty cycling on the morphology, crystalline quality, Mg doping concentration, and electrical properties of GaN:Mg films grown by MME. When the metal shutter duty cycling is 20 s open/10 s close, the sample has smooth surface with clear steps even with Mg doping concentration higher than 1 × 1020 cm-3. The RMS roughness is about 0.5 nm. The FWHM of (002) XRD rocking curve is 230 arcsec and the FWHM of (102) XRD rocking curve is 260 arcsec. As result, a hole concentration of 5 × 1018 cm-3 and a resistivity of 1.5 Ω·cm have been obtained. The hole concentration increases due to the incorporation of surface accumulated Mg dopants into suitable Ga substitutional sites with minimal formation of compensatory defects.

Detach GaN-Based Film to Realize a Monolithic Bifunctional Device for Both Lighting and Detection.

Due to the emerging requirements of miniaturization and multifunctionality, monolithic devices with both functions of lighting and detection are essential for next-generation optoelectronic devices. In this work, based on freestanding (In,Ga)N films, we demonstrate a monolithic device with two functions of lighting and self-powered detection successfully. The freestanding (In,Ga)N film is detached from the epitaxial silicon (Si) substrate by a cost-effective and fast method of electrochemical etching. Due to the stress release and the lightening of the quantum-confined Stark effect (QCSE), the wavelength blueshift of electroluminescent (EL) peak is very small (<1 nm) when increasing the injection current, leading to quite stable EL spectra. On the other hand, the proposed monolithic bifunctional device can have a high ultraviolet/visible reject ratio (Q = 821) for self-powered detection, leading to the excellent detection selectivity. The main reason can be attributed to the removal of Si by the lift-off process, which can limit the response to visible light. This work paves an effective way to develop new monolithic multifunctional devices for both detection and display.

Psychometric Evaluation of the Cooper-Norcross Inventory of Preferences-Therapist Version.

The Cooper-Norcross Inventory of Preferences (C-NIP) is a commonly used and psychometrically validated measure of client preferences in therapy. However, the C-NIP version for therapists (C-NIP-T) has not yet been validated. This study aimed to develop a Chinese version of the C-NIP-T and test its factor structure, reliability, and concurrent validity. A national sample of 1,054 Chinese mental health professionals completed the C-NIP-T and provided relevant demographic information. Confirmatory factor analysis (CFA) and exploratory structural equation modeling (ESEM) were used to examine the factor structure of the C-NIP-T. ESEM provided stronger evidence than CFA for the hypothesized four-factor model. Internal consistency coefficients (Cronbach's α) of the four subscales ranged between .60 and .76. Full or partial scalar invariance was established across therapists' therapeutic orientations, gender, personal therapy, and clinical experience. There were significant differences in subscale scores among therapists who identified as cognitive/cognitive-behavioral, psychoanalytic/psychodynamic, and humanistic/client-centered, supporting the concurrent validity of the C-NIP-T. The C-NIP-T is a psychometrically sound measure that can be used to assess therapists' preferences about therapy.

Multiplexed imaging mass cytometry reveals distinct tumor-immune microenvironments linked to immunotherapy responses in melanoma.

Background: Single-cell technologies have enabled extensive analysis of complex immune composition, phenotype and interactions within tumor, which is crucial in understanding the mechanisms behind cancer progression and treatment resistance. Unfortunately, knowledge on cell phenotypes and their spatial interactions has only had limited impact on the pathological stratification of patients in the clinic so far. We explore the relationship between different tumor environments (TMEs) and response to immunotherapy by deciphering the composition and spatial relationships of different cell types. Methods: Here we used imaging mass cytometry to simultaneously quantify 35 proteins in a spatially resolved manner on tumor tissues from 26 melanoma patients receiving anti-programmed cell death-1 (anti-PD-1) therapy. Using unsupervised clustering, we profiled 662,266 single cells to identify lymphocytes, myeloid derived monocytes, stromal and tumor cells, and characterized TME of different melanomas. Results: Combined single-cell and spatial analysis reveals highly dynamic TMEs that are characterized with variable tumor and immune cell phenotypes and their spatial organizations in melanomas, and many of these multicellular features are associated with response to anti-PD-1 therapy. We further identify six distinct TME archetypes based on their multicellular compositions, and find that patients with different TME archetypes responded differently to anti-PD-1 therapy. Finally, we find that classifying patients based on the gene expression signature derived from TME archetypes predicts anti-PD-1 therapy response across multiple validation cohorts. Conclusions: Our results demonstrate the utility of multiplex proteomic imaging technologies in studying complex molecular events in a spatially resolved manner for the development of new strategies for patient stratification and treatment outcome prediction.

An artificial neural network model based on autophagy-related genes in childhood systemic lupus erythematosus.

BACKGROUND: Childhood systemic lupus erythematosus (cSLE) is a multisystemic, life-threatening autoimmune disease. Compared to adults, SLE in childhood is more active, can cause multisystem involvement including renal, neurological and hematological, and can cause cumulative damage across systems more rapidly. Autophagy, one of the core functions of cells, is involved in almost every process of the immune response and has been shown to be associated with many autoimmune diseases, being a key factor in the interplay between innate and adaptive immunity. Autophagy influences the onset, progression and severity of SLE. This paper identifies new biomarkers for the diagnosis and treatment of childhood SLE based on an artificial neural network of autophagy-related genes. METHODS: We downloaded dataset GSE100163 from the Gene Expression Omnibus database and used Protein-protein Interaction Network (PPI) and Least Absolute Shrinkage and Selection Operator (LASSO) to screen the signature genes of autophagy-related genes in cSLE. A new artificial neural network model for cSLE diagnosis was constructed using the signature genes. The predictive efficiency of the model was also validated using the dataset GSE65391. Finally, "CIBERSORT" was used to calculate the infiltration of immune cells in cSLE and to analyze the relationship between the signature genes and the infiltration of immune cells. RESULTS: We identified 37 autophagy-related genes that differed in cSLE and normal samples, and finally obtained the seven most relevant signature genes for cSLE (DDIT3, GNB2L1, CTSD, HSPA8, ULK1, DNAJB1, CANX) by PPI and LASOO regression screening, and constructed an artificial neural network diagnostic model for cSLE. Using this model, we plotted the ROC curves for the training and validation group diagnoses with the area under the curve of 0.976 and 0.783, respectively. Finally, we performed immunoassays on cSLE samples, and the results showed that Plasma cells, Macrophages M0, Dendritic cells activated and Neutrophils were significantly infiltrated in cSLE. CONCLUSION: We constructed an artificial neural network diagnostic model of seven autophagy-related genes that can be used for the diagnosis of cSLE. Meanwhile, the characteristic genes affect the immune infiltration of cSLE, which may provide new perspectives for the exploration of cSLE treatment and related mechanisms.

Protocol to estimate cell type proportions from bulk RNA-seq using DAISM-DNNXMBD.

Computational protocols for cell type deconvolution from bulk RNA-seq data have been used to understand cellular heterogeneity in disease-related samples, but their performance can be impacted by batch effect among datasets. Here, we present a DAISM-DNN protocol to achieve robust cell type proportion estimation on the target dataset. We describe the preparation of calibrated samples from human blood samples. We then detail steps to train a dataset-specific deep neural network (DNN) model and cell type proportion estimation using the trained model. For complete details on the use and execution of this protocol, please refer to Lin et al. (2022).