Seasonal patterns of nonstructural carbohydrate storage and mobilization in two tree species with distinct life-history traits.

Nonstructural carbohydrates (NSC) are essential for tree growth and adaptation, yet our understanding of the seasonal storage and mobilization dynamics of whole-tree NSC is still limited, especially when tree functional types are involved. Here, Quercus acutissima Carruth. and Pinus massoniana Lamb. with distinct life-history traits (i.e., a deciduous broadleaf species vs. an evergreen coniferous species) were studied to assess the size and seasonal fluctuations of organ and whole-tree NSC pools with a focus on comparing differences in carbon resource mobilization patterns between the two species. We sampled the organs (leaf, branch, stem, and root) of the target trees repeatedly over four seasons of the year. Then, NSC concentrations in each organ were paired with biomass estimates from the allometric model to generate whole-tree NSC pools. The seasonal dynamics of the whole-tree NSC of Q. acutissima and P. massoniana reached the peak in autumn and summer, respectively. The starch pools of the two species were supplemented in the growing season while the soluble sugar pools were the largest in the dormant season. Seasonal dynamics of organ-level NSC concentrations and pools were affected by organ type and tree species, with above-ground organs generally increasing during the growing season and P. massoniana roots decreasing during the growing season. In addition, the whole-tree NSC pools of P. massoniana were larger but Q. acutissima showed larger seasonal fluctuations, indicating that larger storage was not associated with more pronounced seasonal fluctuations. We also found that the branch and root were the most dynamic organs of Q. acutissima and P. massoniana, respectively, and were the major suppliers of NSC to support tree growth activities. These results provide fundamental insights into the dynamics and mobilization patterns of NSC at the whole-tree level, and have important implications for investigating environmental adaptions of different tree functional types.

Fish ubiquitin-specific protease 8 (USP8) inhibits IFN production through autophagy-lysosomal dependent degradation of IRF7.

Interferon regulatory factor 7 (IRF7) is considered the master regulator of virus-induced interferon (IFN) production. However, to avoid an autoimmune response, the expression of IRF7 must be tightly controlled. In this study, we report that zebrafish ubiquitin-specific protease 8 (USP8) promotes IRF7 degradation through an autophagy-lysosome-dependent pathway to inhibit IFN production. First, zebrafish usp8 is induced upon spring viremia of carp virus (SVCV) infection and polyinosinic/polycytidylic acid (poly I:C) stimulation. Second, overexpression of USP8 suppresses SVCV or poly I:C-mediated IFN expression. Mechanistically, USP8 interacts with IRF7 and promotes its degradation via an autophagy-lysosome-dependent pathway. Finally, USP8 significantly suppresses cellular antiviral responses and enhances SVCV proliferation. In summary, our discoveries offer a perspective on the role of zebrafish USP8 and provide additional understanding of the regulation of IRF7 in host antiviral immune response.

Gibberellin-Mediated Sensitivity of Rice Roots to Aluminum Stress.

Aluminum toxicity poses a significant constraint on crop production in acidic soils. While phytohormones are recognized for their pivotal role in mediating plant responses to aluminum stress, the specific involvement of gibberellin (GA) in regulating aluminum tolerance remains unexplored. In this study, we demonstrate that external GA exacerbates the inhibitory impact of aluminum stress on root growth of rice seedlings, concurrently promoting reactive oxygen species (ROS) accumulation. Furthermore, rice plants overexpressing the GA synthesis gene SD1 exhibit enhanced sensitivity to aluminum stress. In contrast, the slr1 gain-of-function mutant, characterized by impeded GA signaling, displays enhanced tolerance to aluminum stress, suggesting the negative regulatory role of GA in rice resistance to aluminum-induced toxicity. We also reveal that GA application suppresses the expression of crucial aluminum tolerance genes in rice, including Al resistance transcription factor 1 (ART1), Nramp aluminum transporter 1 (OsNramp4), and Sensitive to Aluminum 1 (SAL1). Conversely, the slr1 mutant exhibits up-regulated expression of these genes compared to the wild type. In summary, our results shed light on the inhibitory effect of GA in rice resistance to aluminum stress, contributing to a theoretical foundation for unraveling the intricate mechanisms of plant hormones in regulating aluminum tolerance.

MicroRNA-encoded regulatory peptides modulate cadmium tolerance and accumulation in rice.

MicroRNAs (miRNAs) are small noncoding RNAs that play a vital role in plant responses to abiotic and biotic stresses. Recently, it has been discovered that some primary miRNAs (pri-miRNAs) encode regulatory short peptides called miPEPs. However, the presence of miPEPs in rice, and their functions in response to abiotic stresses, particularly stress induced by heavy metals, remain poorly understood. Here, we identified a functional small peptide (miPEP156e) encoded by pri-miR156e that regulates the expression of miR156 and its target SPL genes, thereby affecting miR156-mediated cadmium (Cd) tolerance in rice. Overexpression of miPEP156e led to decreased uptake and accumulation of Cd and reactive oxygen species (ROS) levels in plants under Cd stress, resulting in improved rice Cd tolerance, as observed in miR156-overexpressing lines. Conversely, miPEP156e mutants displayed sensitivity to Cd stress due to the elevated accumulation of Cd and ROS. Transcriptome analysis further revealed that miPEP156e improved rice Cd tolerance by modulating Cd transporter genes and ROS scavenging genes. Our study provides insights into the regulatory mechanism of miPEP156e in rice response to Cd stress and demonstrates the potential of miPEPs as an effective tool for improving crop abiotic stress tolerance.

Temporal dynamics of stomatal regulation and carbon- and water-related traits for a native tree species in low subtropical China.

Stomata are pivotal in modulating water and carbon processes within plants. However, our understanding of the temporal dynamics of water- and carbon-related traits, as influenced by stomatal behavior, remains limited. Here, we explore how stomatal regulation behavior and water- and carbon-related traits vary with changing environments by examining the seasonal variations in these traits of the native tree species Schima superba in low subtropical China. In February, April, and July of 2022, a series of water- and carbon-related traits were measured in the leaves and stems. The results showed that S. superba exhibited isohydric behavior in February when the soil dried out and vapor pressure deficit (VPD) was lower but anisohydric behavior in April and July when the soil was wetter and VPD was higher. In February, NSC and their components increased, and a relatively large contribution of soluble sugars to the change in NSC was observed. In the branches and phloem, NSC and their components displayed a relatively high monthly variability, suggesting their role in maintaining carbon balance within the trees. Conversely, the NSC in the leaves demonstrated minimal monthly variability. The specific leaf area, as well as the concentration of nitrogen (N) and phosphorus (P) per unit mass in leaves and the cumulative stem water release, exhibited a decrease with a reduction in soil water potential. Interestingly, the hydraulic conductivity remained consistent throughout this process. Furthermore, the relatively low monthly growth rate observed in February could suggest a carbon sink limitation. In conclusion, the increased NSC and decreased water status of S. superba under relatively stressed soil conditions indicated a trade-off between water and carbon storage. Our findings enhance our comprehension of the dynamics and regulation of water and carbon status in forests, thereby advancing the development of plant carbon and water process models under climate change scenarios.

Aorta Dilatation in Unrepaired Tetralogy of Fallot.

Background Aortic root dilation is an increasingly recognized feature in repaired tetralogy of Fallot (TOF) patients. However, the dilation at the aortic root and ascending aorta in unrepaired TOF is rarely studied. This study aims to confirm whether aortic dilation is a common feature in unrepaired TOF and investigate the factors attributed to aortic dilation. Methodology Patients with an echocardiographic diagnosis of TOF undergoing computed tomography angiography were retrospectively studied. Diameters and z scores of aortic annular (Ao1), aortic sinotubular junction (Ao2), ascending aorta (Ao3), and distal transverse aortic arch (Ao4) were measured. Preoperative body surface area (BSA), hemoglobin (Hb), hematocrit (HCT), arterial oxygen saturation (SaO2), and platelet (PLT) count were recorded. Results A total of 101 TOF patients aged 6.8 ± 9.5 years were included in this study, whose mean BSA (m2), Hb (g/L), HCT, SaO2 (%), and PLT (109/L) were 0.7 ± 0.4, 162.1 ± 3.8, 0.5 ± 0.1, 85.1 ± 9.3, and 238.1 ± 101.1, respectively. The mean z score of Ao1, Ao2, Ao3, and Ao4 were 10.3 ± 3.5, 4.7 ± 2.9, 4.0 ± 2.7, and 4.1 ± 2.4, respectively. Age and BSA were positively correlated with the z scores of Ao1 and Ao2. Preoperative Hb and HCT were positively correlated with the z scores of Ao1, Ao2, Ao3, and Ao4. Preoperative SaO2 and PLT were negatively correlated with the z scores of Ao1, Ao2, Ao3, and Ao4. Conclusions Aortic dilation is common in unrepaired TOF patients. The dilation of different levels of the aorta was correlated with age, BSA, preoperative Hb, HCT, SaO2, and PLT.

Global analysis of seed transcriptomes reveals a novel PLATZ regulator for seed size and weight control in soybean.

Seed size and weight are important factors that influence soybean yield. Combining the weighted gene co-expression network analysis (WGCNA) of 45 soybean accessions and gene dynamic changes in seeds at seven developmental stages, we identified candidate genes that may control the seed size/weight. Among these, a PLATZ-type regulator overlapping with 10 seed weight QTLs was further investigated. This zinc-finger transcriptional regulator, named as GmPLATZ, is required for the promotion of seed size and weight in soybean. The GmPLATZ may exert its functions through direct binding to the promoters and activation of the expression of cyclin genes and GmGA20OX for cell proliferation. Overexpression of the GmGA20OX enhanced seed size/weight in soybean. We further found that the GmPLATZ binds to a 32-bp sequence containing a core palindromic element AATGCGCATT. Spacing of the flanking sequences beyond the core element facilitated GmPLATZ binding. An elite haplotype Hap3 was also identified to have higher promoter activity and correlated with higher gene expression and higher seed weight. Orthologues of the GmPLATZ from rice and Arabidopsis play similar roles in seeds. Our study reveals a novel module of GmPLATZ-GmGA20OX/cyclins in regulating seed size and weight and provides valuable targets for breeding of crops with desirable agronomic traits.

Zebrafish TMEM47 is an effective blocker of IFN production during RNA and DNA virus infection.

IMPORTANCE: Mitochondrial antiviral signaling protein (MAVS) and stimulator of interferon (IFN) genes (STING) are key adaptor proteins required for innate immune responses to RNA and DNA virus infection. Here, we show that zebrafish transmembrane protein 47 (TMEM47) plays a critical role in regulating MAVS- and STING-triggered IFN production in a negative feedback manner. TMEM47 interacted with MAVS and STING for autophagic degradation, and ATG5 was essential for this process. These findings suggest the inhibitory function of TMEM47 on MAVS- and STING-mediated signaling responses during RNA and DNA virus infection.

Integration of transcriptome and metabolome analyses reveals the role of OsSPL10 in rice defense against brown planthopper.

KEY MESSAGE: OsSPL10 is a negative regulator of rice defense against BPH, knockout of OsSPL10 enhances BPH resistance through upregulation of defense-related genes and accumulation of secondary metabolites. Rice (Oryza sativa L.), one of the most important staple foods worldwide, is frequently attacked by various herbivores, including brown planthopper (BPH, Nilaparvata lugens). BPH is a typical monophagous, phloem-sucking herbivore that has been a substantial threat to rice production and global food security. Understanding the regulatory mechanism of defense responses to BPH is essential for improving BPH resistance in rice. In this study, a SQUAMOSA PROMOTER-BINDING PROTEIN-LIKE 10 (OsSPL10) transcription factor was found to play a negative role in the defenses of rice against BPH. To gain insights into the molecular and biochemical mechanisms of OsSPL10, we performed combined analyses of transcriptome and metabolome, and revealed that knockout of OsSPL10 gene improved rice resistance against BPH by enhancing the direct and indirect defenses. Genes involved in plant hormone signal transduction, MAPK signaling pathway, phenylpropanoid biosynthesis, and plant-pathogen interaction pathway were significantly upregulated in spl10 mutant. Moreover, spl10 mutant exhibited increased accumulation of defense-related secondary metabolites in the phenylpropanoid and terpenoid pathways. Our findings reveal a novel role for OsSPL10 gene in regulating the rice defense responses, which can be used as a potential target for genetic improvement of BPH resistance in rice.

MRI-based brain age prediction model for children under 3 years old using deep residual network.

Early identification and intervention of abnormal brain development individual subjects are of great significance, especially during the earliest and most active stage of brain development in children aged under 3. Neuroimage-based brain's biological age has been associated with health, ability, and remaining life. However, the existing brain age prediction models based on neuroimage are predominantly adult-oriented. Here, we collected 658 T1-weighted MRI scans from 0 to 3 years old healthy controls and developed an accurate brain age prediction model for young children using deep learning techniques with high accuracy in capturing age-related changes. The performance of the deep learning-based model is comparable to that of the SVR-based model, showcasing remarkable precision and yielding a noteworthy correlation of 91% between the predicted brain age and the chronological age. Our results demonstrate the accuracy of convolutional neural network (CNN) brain-predicted age using raw T1-weighted MRI data with minimum preprocessing necessary. We also applied our model to children with low birth weight, premature delivery history, autism, and ADHD, and discovered that the brain age was delayed in children with extremely low birth weight (less than 1000 g) while ADHD may cause accelerated aging of the brain. Our child-specific brain age prediction model can be a valuable quantitative tool to detect abnormal brain development and can be helpful in the early identification and intervention of age-related brain disorders.

Platelet extracellular vesicles are efficient delivery vehicles of doxorubicin, an anti-cancer drug: preparation and in vitro characterization.

Platelet extracellular vesicles (PEVs) are an emerging delivery vehi for anticancer drugs due to their ability to target and remain in the tumor microenvironment. However, there is still a lack of understanding regarding yields, safety, drug loading efficiencies, and efficacy of PEVs. In this study, various methods were compared to generate PEVs from clinical-grade platelets, and their properties were examined as vehicles for doxorubicin (DOX). Sonication and extrusion produced the most PEVs, with means of 496 and 493 PEVs per platelet (PLT), respectively, compared to 145 and 33 by freeze/thaw and incubation, respectively. The PEVs were loaded with DOX through incubation and purified by chromatography. The size and concentration of the PEVs and PEV-DOX were analyzed using dynamic light scattering and nanoparticle tracking analysis. The results showed that the population sizes and concentrations of PEVs and PEV-DOX were in the ranges of 120-150 nm and 1.2-6.2 × 1011 particles/mL for all preparations. The loading of DOX determined using fluorospectrometry was found to be 2.1 × 106, 1.7 × 106, and 0.9 × 106 molecules/EV using freeze/thaw, extrusion, and sonication, respectively. The internalization of PEVs was determined to occur through clathrin-mediated endocytosis. PEV-DOX were more efficiently taken up by MDA-MB-231 breast cancer cells compared to MCF7/ADR breast cancer cells and NIH/3T3 cells. DOX-PEVs showed higher anticancer activity against MDA-MB-231 cells than against MCF7/ADR or NIH/3T3 cells and better than acommercial liposomal DOX formulation. In conclusion, this study demonstrates that PEVs generated by PLTs using extrusion, freeze/thaw, or sonication can efficiently load DOX and kill breast cancer cells, providing a promising strategy for further evaluation in preclinical animal models. The study findings suggest that sonication and extrusion are the most efficient methods to generate PEVs and that PEVs loaded with DOX exhibit significant anticancer activity against MDA-MB-231 breast cancer cells.

What is the context?● Current synthetic drug delivery systems can have limitations and side effects.● Platelet extracellular vesicles (PEVs) are a natural and potentially safer alternative for delivering cancer drugs to tumors.● However, there is still a lack of understanding about how to produce PEVs and how effective they are in delivering drugs.What is new?● We compared different methods for producing PEVs from clinical-grade platelets and found that sonication and extrusion were the most effective methods.● The PEVs were loaded with a cancer drug called doxorubicin (DOX) and tested their ability to kill breast cancer cells.What is the impact?● PEVs loaded with DOX were effective at killing cancer cells, especially MDA-MB-231 breast cancer cells.● This study demonstrates that PEVs are a promising strategy for delivering cancer drugs to tumors and that sonication and extrusion are the most efficient methods for producing PEVs.● The results suggest that further evaluation of PEVs in preclinical animal models is warranted to determine their potential as a cancer drug delivery system.Abbreviations: ADP: adenosine diphosphate; bFGF: basic fibroblast growth factor; BSA: bovine serum albumin; CD41: platelet glycoprotein IIb; CD62P: P-selectin; CFDASE: 5-(and-6)-carboxyfluorescein diacetate: succinimidyl ester; CPLT: cryopreserved platelet; CPZ: chlorpromazine hydrochloride; CTC: circulating tumor cell; DMSO: dimethyl sulfoxide; DDS: drug delivery system; DOX: doxorubicin; EPR: enhanced permeability and retention; EV: extracellular vesicle; FBS: fetal bovine serum; GMP: good manufacturing practice; GF: growth factor; HER2: human epidermal growth factor receptor 2; HGF: hepatocyte growth factor; Lipo-DOX: liposomal doxorubicin; MDR: multi-drug resistance; MMP-2: matrix metalloproteinase-2; MP: microparticle; MSC: mesenchymal stromal cell; NP: nanoparticle; NTA: nanoparticle tracking analysis; PAR-1: protease activated receptor-1; PAS: platelet additive solution; PBS: phosphate-buffered saline; PC: platelet concentrate; PEG: polyethylene glycol; PEV: platelet-derived extracellular vesicle; DOX-PEV: doxorubicin-loaded platelet-derived extracellular vesicle-encapsulated; PFA: paraformaldehyde; PF4: platelet factor 4; P-gp: P-glycoprotein; PLT: platelet; PS: phosphatidylserine; SDS-PAGE: sodium dodecylsulfate polyacrylamide gel electrophoresis; SEM: scanning electron microscopy; TCIPA: tumor cell-induced PLT aggregation; TDDS: targeted drug delivery system; TEG: thromboelastography; TF: tissue factor; TF-EV: extracellular vesicle expressing tissue factor; TME: tumor microenvironment; TNBC: triple-negative breast cancer; TXA2: thromboxane-A2; VEGF: vascular endothelial growth factor; WHO: World Health Organization.

A multicenter study on two-stage transfer learning model for duct-dependent CHDs screening in fetal echocardiography.

Duct-dependent congenital heart diseases (CHDs) are a serious form of CHD with a low detection rate, especially in underdeveloped countries and areas. Although existing studies have developed models for fetal heart structure identification, there is a lack of comprehensive evaluation of the long axis of the aorta. In this study, a total of 6698 images and 48 videos are collected to develop and test a two-stage deep transfer learning model named DDCHD-DenseNet for screening critical duct-dependent CHDs. The model achieves a sensitivity of 0.973, 0.843, 0.769, and 0.759, and a specificity of 0.985, 0.967, 0.956, and 0.759, respectively, on the four multicenter test sets. It is expected to be employed as a potential automatic screening tool for hierarchical care and computer-aided diagnosis. Our two-stage strategy effectively improves the robustness of the model and can be extended to screen for other fetal heart development defects.

An Innovative Three-Stage Model for Prenatal Genetic Disorder Detection Based on Region-of-Interest in Fetal Ultrasound.

A global survey has revealed that genetic syndromes affect approximately 8% of the population, but most genetic diagnoses are typically made after birth. Facial deformities are commonly associated with chromosomal disorders. Prenatal diagnosis through ultrasound imaging is vital for identifying abnormal fetal facial features. However, this approach faces challenges such as inconsistent diagnostic criteria and limited coverage. To address this gap, we have developed FGDS, a three-stage model that utilizes fetal ultrasound images to detect genetic disorders. Our model was trained on a dataset of 2554 images. Specifically, FGDS employs object detection technology to extract key regions and integrates disease information from each region through ensemble learning. Experimental results demonstrate that FGDS accurately recognizes the anatomical structure of the fetal face, achieving an average precision of 0.988 across all classes. In the internal test set, FGDS achieves a sensitivity of 0.753 and a specificity of 0.889. Moreover, in the external test set, FGDS outperforms mainstream deep learning models with a sensitivity of 0.768 and a specificity of 0.837. This study highlights the potential of our proposed three-stage ensemble learning model for screening fetal genetic disorders. It showcases the model's ability to enhance detection rates in clinical practice and alleviate the burden on medical professionals.

A computer-aided diagnosis system for brain tumors based on artificial intelligence algorithms.

The choice of treatment and prognosis evaluation depend on the accurate early diagnosis of brain tumors. Many brain tumors go undiagnosed or are overlooked by clinicians as a result of the challenges associated with manually evaluating magnetic resonance imaging (MRI) images in clinical practice. In this study, we built a computer-aided diagnosis (CAD) system for glioma detection, grading, segmentation, and knowledge discovery based on artificial intelligence algorithms. Neuroimages are specifically represented using a type of visual feature known as the histogram of gradients (HOG). Then, through a two-level classification framework, the HOG features are employed to distinguish between healthy controls and patients, or between different glioma grades. This CAD system also offers tumor visualization using a semi-automatic segmentation tool for better patient management and treatment monitoring. Finally, a knowledge base is created to offer additional advice for the diagnosis of brain tumors. Based on our proposed two-level classification framework, we train models for glioma detection and grading, achieving area under curve (AUC) of 0.921 and 0.806, respectively. Different from other systems, we integrate these diagnostic tools with a web-based interface, which provides the flexibility for system deployment.

Personalized cancer avatars for patients with thymic malignancies: A pilot study with circulating tumor cell-derived organoids.

BACKGROUND: Systemic therapy is the primary treatment for advanced thymic malignancies. However, there is an urgent need to improve clinical outcome. Personalized treatment based on predictive biomarkers is a potential approach to address this requirement. In this study, we aimed to show the correlation between drug sensitivity tests on CTCs-derived organoids and clinical response in patients with thymic malignancies. This approach carries the potential to create personalized cancer avatars and improve treatment outcome for patients. METHODS: We previously reported potential treatment outcome prediction with patient-derived organoids (cancer avatars) in patients with pancreatic ductal adenocarcinoma. To further investigate the feasibility of this approach in advanced thymic malignancies, we conducted a study in which 12 patients were enrolled and 21 liquid biopsies were performed. RESULTS: Cancer avatars were successfully derived in 16 out of 21 samples (success rate 76.2%). We found a sensitivity of 1.0 and specificity of 0.6 for drug sensitivity tests on the cancer avatars, and a two-tailed Fisher's exact test revealed a significant correlation between drug sensitivity tests and clinical responses (p = 0.0275). CONCLUSION: This study supports the potential of circulating tumor cell-derived organoids to inform personalized treatment for advanced thymic malignancies. Further validation of this proof of concept finding is ongoing.

Prediction of Diagnosis-Related Groups for Appendectomy Patients Using C4.5 and Neural Network.

Due to the increasing cost of health insurance, for decades, many countries have endeavored to constrain the cost of insurance by utilizing a DRG payment system. In most cases, under the DRG payment system, hospitals cannot exactly know which DRG code inpatients are until they are discharged. This paper focuses on the prediction of what DRG code appendectomy patients will be classified with when they are admitted to hospital. We utilize two models (or classifiers) constructed using the C4.5 algorithm and back-propagation neural network (BPN). We conducted experiments with the data collected from two hospitals. The results show that the accuracies of these two classification models can be up to 97.84% and 98.70%, respectively. According to the predicted DRG code, hospitals can effectively arrange medical resources with certainty, then, in turn, improve the quality of the medical care patients receive.

A Meta-analysis Assessing the Efficacy of Balloon Pulmonary Angioplasty in Resolving Chronic Thromboembolic Pulmonary Hypertension.

Background and Purpose: Chronic thromboembolic pulmonary hypertension (CTEPH) is the fourth most common form of pulmonary hypertension (PH), representing a pre-capillary manifestation of the disorder. This meta-analysis aims to evaluate the role of balloon pulmonary angioplasty (BPA) in the treatment of CTEPH. Methods: Our investigation was conducted using PubMed, Embase, Cochrane Library, and Web of Science platforms. Results: This meta-analysis includes the analysis of seven studies. BPA demonstrated a significant reduction in pulmonary arterial pressure in CTEPH patients (Mean difference (MD) = -9.80, 95% CI: -1.10 to -8.59, P < .00001). BPA also resulted in a decrease in pulmonary vascular resistance in CTEPH patients (MD = -4.70, 95% CI: -7.17 to -2.22, P = .0002). Moreover, BPA was associated with improved 6-minute walk distance of CTEPH patients (MD = 43.86, 95% CI: 26.19 to 61.53, P < .00001). Additionally, BPA led to a reduction in NT-proBNP levels in CTEPH patients (MD = -3.46, 95% CI: -10.63 to 3.71, p-value = 0.34). BPA also resulted in an improvement in the WHO functional class of CTEPH patients, with an increase in class I-II (MD = 0.28, 95% CI: 0.22 to 0.35, P < .00001) and a decrease in class III-IV (MD = 0.16, 95% CI: 0.10 to 0.26, P < .00001). Conclusion: These findings support the effectiveness of BPA as an alternative treatment option for CTEPH patients, leading to improvements in prognostic factors such as hemodynamics, functional ability, and biomarkers. BPA may offer enhanced therapeutic benefits and potentially serve as an alternative treatment for select CTEPH patients.

Zebrafish MAP2K7 Simultaneously Enhances Host IRF7 Stability and Degrades Spring Viremia of Carp Virus P Protein via Ubiquitination Pathway.

During viral infection, host defensive proteins either enhance the host immune response or antagonize viral components directly. In this study, we report on the following two mechanisms employed by zebrafish mitogen-activated protein kinase kinase 7 (MAP2K7) to protect the host during spring viremia of carp virus (SVCV) infection: stabilization of host IRF7 and degradation of SVCV P protein. In vivo, map2k7+/- (map2k7-/- is a lethal mutation) zebrafish showed a higher lethality, more pronounced tissue damage, and more viral proteins in major immune organs than the controls. At the cellular level, overexpression of map2k7 significantly enhanced host cell antiviral capacity, and viral replication and proliferation were significantly suppressed. Additionally, MAP2K7 interacted with the C terminus of IRF7 and stabilized IRF7 by increasing K63-linked polyubiquitination. On the other hand, during MAP2K7 overexpression, SVCV P proteins were significantly decreased. Further analysis demonstrated that SVCV P protein was degraded by the ubiquitin-proteasome pathway, as the attenuation of K63-linked polyubiquitination was mediated by MAP2K7. Furthermore, the deubiquitinase USP7 was indispensable in P protein degradation. These results confirm the dual functions of MAP2K7 during viral infection. IMPORTANCE Normally, during viral infection, host antiviral factors individually modulate the host immune response or antagonize viral components to defense infection. In the present study, we report that zebrafish MAP2K7 plays a crucial positive role in the host antiviral process. According to the weaker antiviral capacity of map2k7+/- zebrafish than that of the control, we find that MAP2K7 reduces host lethality through two pathways, as follows: enhancing K63-linked polyubiquitination to promote host IRF7 stability and attenuating K63-mediated polyubiquitination to degrade the SVCV P protein. These two mechanisms of MAP2K7 reveal a special antiviral response in lower vertebrates.