Using artificial intelligence to document the hidden RNA virosphere.

Current metagenomic tools can fail to identify highly divergent RNA viruses. We developed a deep learning algorithm, termed LucaProt, to discover highly divergent RNA-dependent RNA polymerase (RdRP) sequences in 10,487 metatranscriptomes generated from diverse global ecosystems. LucaProt integrates both sequence and predicted structural information, enabling the accurate detection of RdRP sequences. Using this approach, we identified 161,979 potential RNA virus species and 180 RNA virus supergroups, including many previously poorly studied groups, as well as RNA virus genomes of exceptional length (up to 47,250 nucleotides) and genomic complexity. A subset of these novel RNA viruses was confirmed by RT-PCR and RNA/DNA sequencing. Newly discovered RNA viruses were present in diverse environments, including air, hot springs, and hydrothermal vents, with virus diversity and abundance varying substantially among ecosystems. This study advances virus discovery, highlights the scale of the virosphere, and provides computational tools to better document the global RNA virome.

Borna disease virus 1 induces ferroptosis, contributing to lethal encephalitis.

Borna disease virus 1 (BoDV-1) is a neurotropic RNA virus that has been linked to fatal BoDV-1 encephalitis (BVE) in humans. Ferroptosis represents a newly recognized kind of programmed cell death that marked by iron overload and lipid peroxidation. Various viral infections are closely related to ferroptosis. However, the link between BoDV-1 infection and ferroptosis, as well as its role in BVE pathogenesis, remains inadequately understood. Herein, we used primary rat cortical neurons, human microglial HMC3 cells, and Sprague‒Dawley rats as models. BoDV-1 infection induced ferroptosis, as ferroptosis characteristics were detected (iron overload, reactive oxygen species buildup, decreased antioxidant capacity, lipid peroxidation, and mitochondrial damage). Analysis via qRT-PCR and Western blot demonstrated that BoDV-1-induced ferroptosis was mediated through Nrf2/HO-1/SLC7a11/GPX4 antioxidant pathway suppression. Nrf2 downregulation was due to BoDV-1 infection promoting Nrf2 ubiquitination and degradation. Following BoDV-1-induced ferroptosis, the PTGS2/PGE2 signaling pathway was activated, and various intracellular lipid peroxidation products and damage-associated molecular patterns were released, contributing to BVE occurrence and progression. More importantly, inhibiting ferroptosis or the ubiquitin‒proteasome system effectively alleviated BVE. Collectively, these findings demonstrate the interaction between BoDV-1 infection and ferroptosis and reveal BoDV-1-induced ferroptosis as an underlying pathogenic mechanism of BVE.

Discovery, recognized antigenic structures, and evolution of cross-serotype broadly neutralizing antibodies from porcine B-cell repertoires against foot-and-mouth disease virus.

It is a great challenge to isolate the broadly neutralizing antibodies (bnAbs) against foot-and-mouth disease virus (FMDV) due to its existence as seven distinct serotypes without cross-protection. Here, by vaccination of pig with FMDV serotype O and A whole virus antigens, we obtained 10 bnAbs against serotypes O, A and/or Asia1 by dissecting 216 common clonotypes of two serotype O and A specific porcine B-cell receptor (BCR) gene repertoires containing total 12720 B cell clones, indicating the induction of cross-serotype bnAbs after sequential vaccination with serotypes O and A antigens. The majority of porcine bnAbs (9/10) were derived from terminally differentiated B cells of different clonal lineages, which convergently targeted the conserved "RGDL" motif on structural protein VP1 of FMDV by mimicking receptor recognition to inhibit viral attachment to cells. Cryo-EM complex structures revealed that the other bnAb pOA-2 specifically targets a novel inter-pentamer antigen structure surrounding the viral three-fold axis, with a highly conserved determinant at residue 68 on VP2. This unique binding pattern enabled cross-serotype neutralization by destabilizing the viral particle. The evolutionary analysis of pOA-2 demonstrated its origin from an intermediate B-cell, emphasizing the crucial role of somatic hypermutations (SHMs) in balancing the breadth and potency of neutralization. However, excessive SHMs may deviate from the trajectory of broad neutralization. This study provides a strategy to uncover bnAbs against highly mutable pathogens and the cross-serotype antigenic structures to explore broadly protective FMDV vaccine.

Clinical Management in NSCLC Patients With EGFR Mutation After Osimertinib Progression With Unknown Resistance Mechanisms.

BACKGROUND: Osimertinib is approved as a standard treatment for non-small cell lung cancer (NSCLC) patients with epidermal growth factor receptor (EGFR) mutation by FDA. However, the mechanisms of resistance for nearly half of patients after osimertinib progression are still unknown, and the optimal therapies for these patients are still controversial. In this retrospective study, we compared efficacy and safety between immunotherapy + chemotherapy, chemotherapy alone, and osimertinib + bevacizumab in NSCLC patients after osimertinib progression with unknown resistance mechanisms. METHODS: Advanced NSCLC patients with unknown resistance mechanisms after osimertinib progression were retrospectively reviewed and divided into immunotherapy + chemotherapy, chemotherapy alone, and osimertinib + bevacizumab treatment groups according to the treatment they received after osimertinib progression. Clinicopathological features, objective response rate (ORR), progression-free survival (PFS), and overall survival (OS) were compared between groups. RESULTS: A total of 121 patients were enrolled in this study, 22 in the immunotherapy + chemotherapy group, 72 in the chemotherapy group, and 27 in the osimertinib + bevacizumab group. The ORR was much higher in the immunotherapy + chemotherapy group compared with chemotherapy or osimertinib + bevacizumab group (55.56% vs. 14.81% vs. 0% in patients after progression on 1st line osimertinib treatment; 30.77% vs. 6.67% vs. 13.33% in patients after progression on 2nd/3rd line osimertinib treatment). Median PFS was also significantly longer in the immunotherapy + chemotherapy group compared with other groups (8.2 months vs. 4.0 months vs. 6.0 months in all patients, p = 0.0066). The median OS did not reach remarkable difference among groups, although osimertinib + bevacizumab group had a numerically longer median OS (37.0 months vs. 37.0 months vs. 47.6 months in all patients, p = 0.6357). Compared with immunotherapy + chemotherapy and chemotherapy, treatment-related adverse events (AEs) of osimertinib + bevacizumab were milder, especially in AEs related to gastrointestinal and bone marrow suppression. CONCLUSION: Our study provides clinical evidence that NSCLC patients after osimertinib progression with unknown resistance mechanisms may benefit from immunotherapy + chemotherapy, with higher ORR and longer PFS compared with osimertinib + bevacizumab or chemotherapy groups. Osimertinib + bevacizumab treatment was also an optional option for patients because OS was numerically longer and safer in this group.

Automatic kidney stone identification: an adaptive feature-weighted LSTM model based on urine and blood routine analysis.

Kidney stones are the most common urinary system diseases, and early identification is of great significance. The purpose of this study was to use routine urine and blood detection indices to build a deep learning (DL) model to identify the presence of kidney stones in the early stage. A retrospective analysis was conducted on patients with kidney stones who were treated at West China Hospital of Sichuan University from January 2020 to June 2023. A total of 1130 individuals presenting with kidney stones and 1230 healthy subjects were enrolled. The first blood and urine laboratory data of participants at our hospital were collected, and the data were divided into a training dataset (80%) and a verification dataset (20%). Additionally, a long short-term memory (LSTM)-based adaptive feature weighting model was trained for the early identification of kidney stones, and the results were compared with those of other models. The performance of the model was evaluated by the area under the subject working characteristic curve (AUC). The important predictive factors are determined by ranking the characteristic importance of the predictive factors. A total of 17 variables were screened; among the top 4 characteristics according to the weight coefficient in this model, urine WBC, urine occult blood, qualitative urinary protein, and microcyte percentage had high predictive value for kidney stones in patients. The accuracy of the kidney stone (KS-LSTM) learning model was 89.5%, and the AUC was 0.95. Compared with other models, it has better performance. The results show that the KS-LSTM model based on routine urine and blood tests can accurately identify the presence of kidney stones. And provide valuable assistance for clinicians to identify kidney stones in the early stage.

Role of ticagrelor in the peri-thrombolytic phase for patients with ST-segment elevation myocardial infarction: a comprehensive review.

Recent years have seen ticagrelor, a potent P2Y12 inhibitor, emerge as a significant advancement in the peri-thrombolytic management of patients with ST-segment elevation myocardial infarction (STEMI), offering a promising alternative to traditional antiplatelet drugs like clopidogrel. This review critically examines the efficacy and safety of ticagrelor during the peri-thrombolytic phase in STEMI patients, drawing on evidence from key clinical trials such as TREAT and MIRTOS, as well as other relevant studies. These investigations underscore ticagrelor's superior platelet inhibition capabilities, which are crucial for minimizing thrombotic complications post-thrombolysis without increasing bleeding risks. Despite its potential, clopidogrel remains the guideline-recommended choice for such patients, leaving the appropriateness of ticagrelor in this context open to debate. By summarizing the current evidence and identifying gaps in our understanding, this study advocates for targeted research to clarify the long-term benefits and optimal deployment of ticagrelor, highlighting its evolving significance in cardiovascular care.

Removal-Free and Multicellular Suspension Bath-Based 3D Bioprinting.

Suspension bath-based 3D bioprinting (SUB3BP) is effective in creating engineered vascular structures. The transfer of oxygen and nutrients via engineered vascular networks is necessary for tissue or organ survival and integration following transplantation. Existing SUB3BP techniques face challenges in fabricating hierarchical structures with multicellular organization, including issues related to suspension bath removal, restricted material choices, and low accuracy. A next-generation SUB3BP technique that is removal-free and multicellular is presented. A simple, storable, stable, and scalable starch hydrogel design leverages the diverse spectrum of hydrogels available for use in SUB3BP. Starch granules (8.1 µm) create vascular structures with minimal surface roughness (2.5 µm) that simulate more natural vessel walls compared to prior research. The development of cells and organoids, as well as the bioprinting of multicellular skin models with vasculature, demonstrates that starch suspension baths eliminate the removal process and have the potential for fabricating artificial tissue with a hierarchical structure and multicellular distribution.

3D Bioprinting of Liquid High-Cell-Proportion Bioinks in Liquid Granular Bath.

Embedded 3D bioprinting techniques have emerged as a powerful method to fabricate 3D engineered constructs using low strength bioinks; however, there are challenges in simultaneously satisfying the requirements of high-cell-activity, high-cell-proportion, and low-viscosity bioinks. In particular, the printing capacity of embedded 3D bioprinting is limited as two main challenges: spreading and diffusion, especially for liquid, high-cell-activity bioinks that can facilitate high-cell-proportion. Here, a liquid-in-liquid 3D bioprinting (LL3DBP) strategy is developed, which used a liquid granular bath to prevent the spreading of liquid bioinks during 3D printing, and electrostatic interaction between the liquid bioinks and liquid granular baths is found to effectively prevent the diffusion of liquid bioinks. As an example, the printing of positively charged 5% w/v gelatin methacryloyl (GelMA) in a liquid granular bath prepared with negatively charged κ-carrageenan is proved to be achievable. By LL3DBP, printing capacity is greatly advanced and bioinks with over 90% v/v cell can be printed, and printed structures with high-cell-proportion exhibit excellent bioactivity.

Association between serum estradiol levels and abdominal aortic calcification in postmenopausal woman: a cross-sectional study.

Background: The association between Estradiol (E2) levels and abdominal aortic calcification (AAC) in postmenopausal women remains unclear. Methods: 614 postmenopausal women from the 2013-2014 NHANES survey cycle were included in this study. The study population was divided into 3 groups according to E2 tertiles: Tertile1 (2.12-3.57pg/mL), Tertile2 (3.60-7.04pg/mL), and Tertile3 (7.06-38.4pg/mL). Estrogen concentration data were natural logarithmically transformed. A Kauppila score > 5 was regarded as prominent arterial calcification and was used to define (EAAC). Logistic regression models were used to assess the association between E2 levels and EAAC prevalence. Subgroup analyses were performed to test whether the association between E2 levels and EAAC prevalence was consistent in different groups. Sensitivity analyses tested the stability of the model in women older than 45 years. Results: EAAC prevalence was significantly higher in Tertile1 (16.6%) than in Tertile2 (9.8%) and Tertile3 (8.3%). On a continuous scale, the adjusted model showed a 58% [OR (95%CI), 1.58 (1.02, 2.54)] increase in the risk of EAAC prevalence for per unit decrease in ln(E2). On a categorical scale, the adjusted model showed that Tertile1 and Tertile2 were 2.55 [OR (95%CI), 2.55 (1.10, 5.92)] and 1.31[OR (95%CI), 1.31(1.03, 2.57)] times higher risk of suffering from EAAC than Tertile3, respectively. Conclusion: This study found that a higher prevalence of AAC in postmenopausal women is closely associated with lower serum E2 levels. Our research further underscores the importance of E2 in maintaining cardiovascular health in postmenopausal women and suggests that monitoring E2 levels may aid in the early prevention and management of AAC and related cardiovascular diseases.

Optimizing the management of aerobic composting for antibiotic resistance genes elimination: A review of future strategy for livestock manure resource utilization.

Aerobic composting technology is an efficient, safe and practical method to reduce the residues of antibiotics and antibiotic resistance genes (ARGs) due to unreasonable disposal of livestock manure. Nowadays, it remains unclear how aerobic composting works to minimize the level of remaining antibiotics and ARGs in manure. Moreover, aerobic composting techniques even have the potential to enhance ARGs level. Therefore, this study conducted a literature review on ARGs variation during the composting process to assess the fate, migration, and risk features of antibiotics and ARGs in different livestock manure and compost. The relationship between ARGs reduction and crucial factors (temperature, heavy metal, and microbial community structures) in the composting process was discussed. The merits and limitations of different technologies used in compost was summarized. The effects on ARGs reduction in the aerobic composting process with various strategies was examined. We attempt to provide a fresh and novel viewpoint on the advancement of global aerobic composting technology.

Comparison of the effects of contrast medium and low-molecular-weight dextran on coronary optical coherence tomographic imaging in relatively complex coronary lesions.

Background: Optical coherence tomography (OCT) has gained increasing popularity in coronary artery intervention due to its high resolution and excellent tissue correlation as a novel intravascular imaging modality. However, the current use of OCT requires contrast agent injection for imaging, and excessive use of contrast agents may adversely affect renal function, exacerbate cardiac burden, and even lead to contrast agent-induced nephropathy and heart failure. In recent years, several researchers have proposed the use of low molecular weight dextran (LMWD) as a substitute for contrast agents in OCT imaging because of its low toxicity, low cost, and wide availability. However, the inclusion of lesions in these studies is relatively simple, and the image quality criteria remain to be optimized. Methods: This study included 26 patients with coronary artery disease who were scheduled for OCT imaging in a real-world clinical practice involving various complex lesions. All patients underwent two OCT examinations at the same vascular site, one each using contrast agent and LMWD. Both contrast media and LMWDs were infused by an autoinjector. The primary endpoint of the study was the average image quality score. Secondary endpoints included clear image length, clear image segments, minimum lumen area, average lumen area, and contrast-induced nephropathy, among others. Results: In terms of image clarity, the average image quality score was similar when comparing contrast media with LMWD (3.912 ± 0.175 vs. 3.769 ± 0.392, P = 0.071). The lengths of the clear images and the segments of the clear images were also similar between the two groups (50.97 ± 16.25 mm vs. 49.12 ± 18.15 mm, P = 0.110; 255.5 ± 81.29 vs. 250.5 ± 89.83, P = 0.095). Additionally, strong correlations were noted between the two flushing solutions regarding the minimum lumen area and mean lumen area. During their hospital stay, none of the patient exhibited deterioration in renal function, and no patient experienced any major adverse cardiovascular events. Conclusions: The quality of coronary artery OCT imaging using LMWD may be comparable to that achieved with traditional contrast agents, even in real-world clinical practice involving various complex lesions. For high-risk patients, LMWD may serve as an excellent substitute for contrast agents in OCT examinations.

Meta-analysis of GHG emissions stimulated by crop residue return in paddy fields: Strategies for mitigation.

The stimulating impact of crop residue return on greenhouse gas (GHG) emissions from paddy fields have been widely accepted, while the influence of site environmental and human factors on the simulating degree remains unclear. Here, we performed a meta-analysis to assess the GHG emissions affected by residue return, and its mitigation potential combined with key factors in paddy fields. Drawing upon 1047 observation sets of CH4 and N2O emissions from 155 peer-reviewed publications we found that residue return to paddy fields caused an average increase of 73% CH4 emissions and 14% in N2O emissions. Utilizing meta-analytical models, we identified pH as the most significant driver modulating GHG emissions, followed by soil organic matter (SOC) and total nitrogen. In alkaline soils, combining straw return with intermittent irrigation (285.2%) or mid-season drainage (118.9%) significantly reduced CH4 emissions compared to continuous flooding (1201.9%). Additionally, pairing straw return with higher nitrogen inputs (above 150 kg N ha-1) improved soil N2O uptake by -11.5%. In acid and neutral soils, straw carbonization achieved soil CH4 negative emissions (from -2.9% to -39.3%), but the long-term effects remained unclear. Reduced drainage frequency mitigates N2O emissions but may increase CH4 emissions. To efficiently mitigate GHG emissions, we proposed low-carbon schemes for acid or neutral soils based on specific SOC content: For soils with SOC content <10 g kg-1, prioritize nitrogen input control with rates not exceeding 174 kg N ha-1. For soils with SOC content >10 g kg-1, prioritize adjusting the type of straw. Our study underscores the significance of site-specific factors in modulating GHG emissions. Efficient GHG mitigation can be achieved by combining residue return with other agronomic measures tailored to different soil conditions.

Effects of transgenic modification on the bacterial communities in different niches of maize under glyphosate toxicity.

Transgenic glyphosate-resistant maize has emerged as a way to expand the use of glyphosate for weed control. Studying the microbiome in the tissues and rhizosphere soil of transgenic plants is vital for understanding the glyphosate-resistant mechanism and optimizing the transgenic design of crops. In our study, the expression of a mutant cp4epsps gene in transgenic maize, which confers tolerance to glyphosate, was performed using the maize variety Xianyu 335 as the genetically modified acceptor line. This transgenic modification did not affect the initial bacterial community in the leaf, stem, or root of maize, but promoted a differential bacterial community in the rhizosphere soil. Under glyphosate application, the abundance of beneficial bacteria involved in N fixation and P solubilization in plant tissues and the rhizosphere soil of glyphosate-resistance maize were higher than those in the glyphosate-sensitive maize. In contrast, the abundance of pathogens had the opposite trend, suggesting that the enhanced health of transgenic maize prevented microbiome deterioration under glyphosate. The re-inoculation of bacterial strains isolated from glyphosate-resistance maize into the leaf and rhizosphere soil of glyphosate-sensitive maize resulted in an enhanced photosynthetic capacity in response to glyphosate, demonstrating the vital role of specific bacteria for glyphosate resistance. Our study provides important evidence of how transgenic maize tolerance to herbicides affects the bacterial communities across the maize niches under glyphosate toxicity.

Functional network modules overlap and are linked to interindividual connectome differences during human brain development.

The modular structure of functional connectomes in the human brain undergoes substantial reorganization during development. However, previous studies have implicitly assumed that each region participates in one single module, ignoring the potential spatial overlap between modules. How the overlapping functional modules develop and whether this development is related to gray and white matter features remain unknown. Using longitudinal multimodal structural, functional, and diffusion MRI data from 305 children (aged 6 to 14 years), we investigated the maturation of overlapping modules of functional networks and further revealed their structural associations. An edge-centric network model was used to identify the overlapping modules, and the nodal overlap in module affiliations was quantified using the entropy measure. We showed a regionally heterogeneous spatial topography of the overlapping extent of brain nodes in module affiliations in children, with higher entropy (i.e., more module involvement) in the ventral attention, somatomotor, and subcortical regions and lower entropy (i.e., less module involvement) in the visual and default-mode regions. The overlapping modules developed in a linear, spatially dissociable manner, with decreased entropy (i.e., decreased module involvement) in the dorsomedial prefrontal cortex, ventral prefrontal cortex, and putamen and increased entropy (i.e., increased module involvement) in the parietal lobules and lateral prefrontal cortex. The overlapping modular patterns captured individual brain maturity as characterized by chronological age and were predicted by integrating gray matter morphology and white matter microstructural properties. Our findings highlight the maturation of overlapping functional modules and their structural substrates, thereby advancing our understanding of the principles of connectome development.

3D Printing of Tough Hydrogel Scaffolds with Functional Surface Structures for Tissue Regeneration.

Hydrogel scaffolds have numerous potential applications in the tissue engineering field. However, tough hydrogel scaffolds implanted in vivo are seldom reported because it is difficult to balance biocompatibility and high mechanical properties. Inspired by Chinese ramen, we propose a universal fabricating method (printing-P, training-T, cross-linking-C, PTC & PCT) for tough hydrogel scaffolds to fill this gap. First, 3D printing fabricates a hydrogel scaffold with desired structures (P). Then, the scaffold could have extraordinarily high mechanical properties and functional surface structure by cycle mechanical training with salting-out assistance (T). Finally, the training results are fixed by photo-cross-linking processing (C). The tough gelatin hydrogel scaffolds exhibit excellent tensile strength of 6.66 MPa (622-fold untreated) and have excellent biocompatibility. Furthermore, this scaffold possesses functional surface structures from nanometer to micron to millimeter, which can efficiently induce directional cell growth. Interestingly, this strategy can produce bionic human tissue with mechanical properties of 10 kPa-10 MPa by changing the type of salt, and many hydrogels, such as gelatin and silk, could be improved with PTC or PCT strategies. Animal experiments show that this scaffold can effectively promote the new generation of muscle fibers, blood vessels, and nerves within 4 weeks, prompting the rapid regeneration of large-volume muscle loss injuries.

A Deep Learning Model for Cervical Optical Coherence Tomography Image Classification.

Objectives: Optical coherence tomography (OCT) has recently been used in gynecology to detect cervical lesions in vivo and proven more effective than colposcopy in clinical trials. However, most gynecologists are unfamiliar with this new imaging technique, requiring intelligent computer-aided diagnosis approaches to help them interpret cervical OCT images efficiently. This study aims to (1) develop a clinically-usable deep learning (DL)-based classification model of 3D OCT volumes from cervical tissue and (2) validate the DL model's effectiveness in detecting high-risk cervical lesions, including high-grade squamous intraepithelial lesions and cervical cancer. Method: The proposed DL model, designed based on the convolutional neural network architecture, combines a feature pyramid network (FPN) with texture encoding and deep supervision. We extracted, represent, and fused four-scale texture features to improve classification performance on high-risk local lesions. We also designed an auxiliary classification mechanism based on deep supervision to adjust the weight of each scale in FPN adaptively, enabling low-cost training of the whole model. Results: In the binary classification task detecting positive subjects with high-risk cervical lesions, our DL model achieved an 81.55% (95% CI, 72.70-88.51%) F1-score with 82.35% (95% CI, 69.13-91.60%) sensitivity and 81.48% (95% CI, 68.57-90.75%) specificity on the Renmin dataset, outperforming five experienced medical experts. It also achieved an 84.34% (95% CI, 74.71-91.39%) F1-score with 87.50% (95% CI, 73.20-95.81%) sensitivity and 90.59% (95% CI, 82.29-95.85%) specificity on the Huaxi dataset, comparable to the overall level of the best investigator. Moreover, our DL model provides visual diagnostic evidence of histomorphological and texture features learned in OCT images to assist gynecologists in making clinical decisions quickly. Conclusions: Our DL model holds great promise to be used in cervical lesion screening with OCT efficiently and effectively.