Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography.

Many COVID-19 patients infected by SARS-CoV-2 virus develop pneumonia (called novel coronavirus pneumonia, NCP) and rapidly progress to respiratory failure. However, rapid diagnosis and identification of high-risk patients for early intervention are challenging. Using a large computed tomography (CT) database from 3,777 patients, we developed an AI system that can diagnose NCP and differentiate it from other common pneumonia and normal controls. The AI system can assist radiologists and physicians in performing a quick diagnosis especially when the health system is overloaded. Significantly, our AI system identified important clinical markers that correlated with the NCP lesion properties. Together with the clinical data, our AI system was able to provide accurate clinical prognosis that can aid clinicians to consider appropriate early clinical management and allocate resources appropriately. We have made this AI system available globally to assist the clinicians to combat COVID-19.

Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning.

The implementation of clinical-decision support algorithms for medical imaging faces challenges with reliability and interpretability. Here, we establish a diagnostic tool based on a deep-learning framework for the screening of patients with common treatable blinding retinal diseases. Our framework utilizes transfer learning, which trains a neural network with a fraction of the data of conventional approaches. Applying this approach to a dataset of optical coherence tomography images, we demonstrate performance comparable to that of human experts in classifying age-related macular degeneration and diabetic macular edema. We also provide a more transparent and interpretable diagnosis by highlighting the regions recognized by the neural network. We further demonstrate the general applicability of our AI system for diagnosis of pediatric pneumonia using chest X-ray images. This tool may ultimately aid in expediting the diagnosis and referral of these treatable conditions, thereby facilitating earlier treatment, resulting in improved clinical outcomes. VIDEO ABSTRACT.

Direct conversion of fibroblasts to neurons by reprogramming PTB-regulated microRNA circuits.

The induction of pluripotency or trans-differentiation of one cell type to another can be accomplished with cell-lineage-specific transcription factors. Here, we report that repression of a single RNA binding polypyrimidine-tract-binding (PTB) protein, which occurs during normal brain development via the action of miR-124, is sufficient to induce trans-differentiation of fibroblasts into functional neurons. Besides its traditional role in regulated splicing, we show that PTB has a previously undocumented function in the regulation of microRNA functions, suppressing or enhancing microRNA targeting by competitive binding on target mRNA or altering local RNA secondary structure. A key event during neuronal induction is the relief of PTB-mediated blockage of microRNA action on multiple components of the REST complex, thereby derepressing a large array of neuronal genes, including miR-124 and multiple neuronal-specific transcription factors, in nonneuronal cells. This converts a negative feedback loop to a positive one to elicit cellular reprogramming to the neuronal lineage.

Accurate estimation of biological age and its application in disease prediction using a multimodal image Transformer system.

Aging in an individual refers to the temporal change, mostly decline, in the body's ability to meet physiological demands. Biological age (BA) is a biomarker of chronological aging and can be used to stratify populations to predict certain age-related chronic diseases. BA can be predicted from biomedical features such as brain MRI, retinal, or facial images, but the inherent heterogeneity in the aging process limits the usefulness of BA predicted from individual body systems. In this paper, we developed a multimodal Transformer-based architecture with cross-attention which was able to combine facial, tongue, and retinal images to estimate BA. We trained our model using facial, tongue, and retinal images from 11,223 healthy subjects and demonstrated that using a fusion of the three image modalities achieved the most accurate BA predictions. We validated our approach on a test population of 2,840 individuals with six chronic diseases and obtained significant difference between chronological age and BA (AgeDiff) than that of healthy subjects. We showed that AgeDiff has the potential to be utilized as a standalone biomarker or conjunctively alongside other known factors for risk stratification and progression prediction of chronic diseases. Our results therefore highlight the feasibility of using multimodal images to estimate and interrogate the aging process.

The lack of negative association between TE load and subgenome dominance in synthesized Brassica allotetraploids.

Polyploidization is important to the evolution of plants. Subgenome dominance is a distinct phenomenon associated with most allopolyploids. A gene on the dominant subgenome tends to express to higher RNA levels in all organs as compared to the expression of its syntenic paralogue (homoeolog). The mechanism that underlies the formation of subgenome dominance remains unknown, but there is evidence for the involvement of transposon/DNA methylation density differences nearby the genes of parents as being causal. The subgenome with lower density of transposon and methylation near genes is positively associated with subgenome dominance. Here, we generated eight generations of allotetraploid progenies from the merging of parental genomes Brassica rapa and Brassica oleracea. We found that transposon/methylation density differ near genes between the parental (rapa:oleracea) existed in the wide hybrid, persisted in the neotetraploids (the synthetic Brassica napus), but these neotetraploids expressed no expected subgenome dominance. This absence of B. rapa vs. B. oleracea subgenome dominance is particularly significant because, while there is no negative relationship between transposon/methylation level and subgenome dominance in the neotetraploids, the more ancient parental subgenomes for all Brassica did show differences in transposon/methylation densities near genes and did express, in the same samples of cells, biased gene expression diagnostic of subgenome dominance. We conclude that subgenome differences in methylated transposon near genes are not sufficient to initiate the biased gene expressions defining subgenome dominance. Our result was unexpected, and we suggest a "nuclear chimera" model to explain our data.

Deep learning can predict subgenome dominance in ancient but not in neo/synthetic polyploidized genomes.

Deep learning offers new approaches to investigate the mechanisms underlying complex biological phenomena, such as subgenome dominance. Subgenome dominance refers to the dominant expression and/or biased fractionation of genes in one subgenome of allopolyploids, which has shaped the evolution of a large group of plants. However, the underlying cause of subgenome dominance remains elusive. Here, we adopt deep learning to construct two convolutional neural network (CNN) models, binary expression model (BEM) and homoeolog contrast model (HCM), to investigate the mechanism underlying subgenome dominance using DNA sequence and methylation sites. We apply these CNN models to analyze three representative polyploidization systems, Brassica, Gossypium, and Cucurbitaceae, each with available ancient and neo/synthetic polyploidized genomes. The BEM shows that DNA sequence of the promoter region can accurately predict whether a gene is expressed or not. More importantly, the HCM shows that the DNA sequence of the promoter region predicts dominant expression status between homoeologous gene pairs retained from ancient polyploidizations, thus predicting subgenome dominance associated with these events. However, HCM fails to predict gene expression dominance between new homoeologous gene pairs arising from the neo/synthetic polyploidizations. These results are consistent across the three plant polyploidization systems, indicating broad applicability of our models. Furthermore, the two models based on methylation sites produce similar results. These results show that subgenome dominance is associated with long-term sequence differentiation between the promoters of homoeologs, suggesting that subgenome expression dominance precedes and is the driving force or even the determining factor for sequence divergence between subgenomes following polyploidization.

Comprehensive assessment of drought resistance and recovery in kiwifruit genotypes using multivariate analysis.

As global climate change persists, ongoing warming exposes plants, including kiwifruit, to repeated cycles of drought stress and rewatering, necessitating the identification of drought-resistant genotypes for breeding purposes. To better understand the physiological mechanisms underlying drought resistance and recovery in kiwifruit, moderate (40-45% field capacity) and severe (25-30% field capacity) drought stresses were applied, followed by rewatering (80-85% field capacity) to eight kiwifruit rootstocks in this study. We then conducted a multivariate analysis of 20 indices for the assessment of drought resistance and recovery capabilities. Additionally, we identified four principal components, each playing a vital role in coping with diverse water conditions. Three optimal indicator groups were pinpointed, enhancing precision in kiwifruit drought resistance and recovery assessment and simplifying the evaluation system. Finally, MX-1 and HW were identified as representative rootstocks for future research on kiwifruit's responses to moderate and severe drought stresses. This study not only enhances our understanding of the response mechanisms of kiwifruit rootstocks to progressive drought stress and recovery but also provides theoretical guidance for reliable screening of drought-adaptive kiwifruit genotypes.

Cryptochrome 1b represses gibberellin signaling to enhance lodging resistance in maize.

Maize (Zea mays L.) is one of the most important crops worldwide. Photoperiod, light quality, and light intensity in the environment can affect the growth, development, yield, and quality of maize. In Arabidopsis (Arabidopsis thaliana), cryptochromes are blue-light receptors that mediate the photocontrol of stem elongation, leaf expansion, shade tolerance, and photoperiodic flowering. However, the function of maize cryptochrome ZmCRY in maize architecture and photomorphogenic development remains largely elusive. The ZmCRY1b transgene product can activate the light signaling pathway in Arabidopsis and complement the etiolation phenotype of the cry1-304 mutant. Our findings show that the loss-of-function mutant of ZmCRY1b in maize exhibits more etiolation phenotypes under low blue light and appears slender in the field compared with wild-type plants. Under blue and white light, overexpression of ZmCRY1b in maize substantially inhibits seedling etiolation and shade response by enhancing protein accumulation of the bZIP transcription factors ELONGATED HYPOCOTYL 5 (ZmHY5) and ELONGATED HYPOCOTYL 5-LIKE (ZmHY5L), which directly upregulate the expression of genes encoding gibberellin (GA) 2-oxidase to deactivate GA and repress plant height. More interestingly, ZmCRY1b enhances lodging resistance by reducing plant and ear heights and promoting root growth in both inbred lines and hybrids. In conclusion, ZmCRY1b contributes blue-light signaling upon seedling de-etiolation and integrates light signals with the GA metabolic pathway in maize, resulting in lodging resistance and providing information for improving maize varieties.

Regional Active Transcription Associates with Homoeologous Exchange Breakpoints in Synthetic Brassica Tetraploids.

Polyploidization plays a crucial role in plant evolution and is becoming increasingly important in breeding. Structural variations and epigenomic repatterning have been observed in synthetic polyploidizations. However, the mechanisms underlying the occurrence and their effects on gene expression and phenotype remain unknown. Here, we investigated genome-wide large deletion/duplication regions (DelDups) and genomic methylation dynamics in leaf organs of progeny from the first eight generations of synthetic tetraploids derived from Chinese cabbage (Brassica rapa L. ssp. pekinensis) and cabbage (Brassica oleracea L. var. capitata). One- or two-copy DelDups, with a mean size of 5.70 Mb (400 kb - 65.85 Mb), occurred from the first generation of selfing and thereafter. The duplication of a fragment in one subgenome consistently coincided with the deletion of its syntenic fragment in the other subgenome, and vice versa, indicating that these DelDups were generated by homoeologous exchanges (HEs). Interestingly, the larger the genomic syntenic region, the higher the frequency of DelDups, further suggesting that the pairing of large homoeologous fragments is crucial for HEs. Moreover, we found that the active transcription of continuously distributed genes in local regions is positively associated with the occurrence of HE breakpoints. In addition, the expression of genes within DelDups exhibited a dosage effect, and plants with extra parental genomic fragments generally displayed phenotypes biased towards the corresponding parent. Genome-wide methylation fluctuated remarkably, which did not clearly affect gene expression on a large scale. Our findings provide insights into the early evolution of polyploid genomes, offering valuable knowledge for polyploidization-based breeding.

The alleviating effect of Phillygenin on the regulation of respiratory microbiota and its metabolites in IBV-infected broilers by inhibiting the TLR7/MyD88/NF-κB axis.

Phillygenin (PHI) is an active ingredient derived from the leaf of Forsythia suspensa that has been found to alleviate inflammation and peroxidation response. Avian infectious bronchitis (IB) is a major threat to poultry industry viral respiratory tract disease that infected with infectious bronchitis virus (IBV). This study investigated the protection of PHI to CEK cell and broiler's tracheal injury triggered by avian infectious bronchitis virus (IBV). The results showed that IBV infection did not cause serious clinical symptoms and slowing-body weight in PHI-treated broilers. The expression of virus loads, pro-inflammation factors (IL-6, TNF-α, and IL-1ß) in CEK cell, and tracheas were decreased compared to the IBV group, exhibiting its potent anti-inflammation. Mechanistically, the study demonstrated that the inhibition of TLR7/MyD88/NF-κB pathway was mainly involved in the protection effect of PHI to inflammation injury. Interestingly, a higher abundance of Firmicutes and Lactobacillus in respiratory tract was observed in PHI-treated broilers than in the IBV group. Significant differences were observed between the IBV group and PHI-treated group in the Ferroptosis, Tryptophan metabolism, and Glutathione metabolism pathways. PHI exhibited potent protection effect on IBV infection and alleviated inflammation injury, mainly through inhibiting TLR7/MyD88/NF-κB pathway. The study encourages further development of PHI, paving the way to its clinical use as a new candidate drug to relieve IBV-induced respiratory symptoms.

Exploring the Mechanism of Zilongjin in Treating Lung Adenocarcinoma Based on Network Pharmacology Combined with Experimental Verification.

Zilongjin (ZLJ) is a common traditional Chinese medicine for lung adenocarcinoma (LUAD) treatment. However, its mechanisms of action remain to be elucidated. Network pharmacology was used to explore the underlying mechanisms of ZLJ on LUAD treatment. The disease-related targets were determined from the Gene-Cards and DisGeNET databases. Active compounds and targets of ZLJ were obtained from the HIT, TCMSP, and TCMID databases. Then the protein-protein interaction (PPI) network was built by the STRING database to identify core-hub targets of ZLJ in LUAD. Next, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were employed to analyze the enriched regulatory pathways of targets. Molecular docking analysis was used to evaluate interactions between potential targets and active compounds. Finally, qRT-PCR was used to further verify the results of network pharmacology. A total of 124 LUAD-related targets of ZLJ and 5 active compounds of ZLJ from the relevant databases were screened out. Among these target proteins, JUN, CDH1, PPARG, and FOS were core hub-genes in the PPI network. GO and KEGG pathway enrichment analysis indicated that these targets might regulate the PPAR signaling pathway in LUAD. JUN, PPARG, and FOS levels were upregulated, while CDH1 level was downregulated in LUAD cells. This study discerned that ZLJ may target genes such as JUN, FOS, PPARG, and CDH1 via the PPAR signaling pathway in LUAD, offering foundational insights for further exploration of ZLJ in clinical applications.

Long-distance facilitation of coastal ecosystem structure and resilience.

Biotic interactions that hierarchically organize ecosystems by driving ecological and evolutionary processes across spatial scales are ubiquitous in our biosphere. Biotic interactions have been extensively studied at local and global scales, but how long-distance, cross-ecosystem interactions at intermediate landscape scales influence the structure, function, and resilience of ecological systems remains poorly understood. We used remote sensing, modeling, and field data to test the hypothesis that the long-distance impact of an invasive species dramatically affects one of the largest tidal flat ecosystems in East Asia. We found that the invasion of exotic cordgrass Spartina alterniflora can produce long-distance effects on native species up to 10 km away, driving decadal coastal ecosystem transitions. The invasive cordgrass at low elevations facilitated the expansion of the native reed Phragmites australis at high elevations, leading to the massive loss and reduced resilience of the iconic Suaeda salsa "Red Beach" marshes at intermediate elevations, largely as a consequence of reduced soil salinity across the landscape. Our results illustrate the complex role that long-distance interactions can play in shaping landscape structure and ecosystem resilience and in bridging the gap between local and global biotic interactions.

The meso-octoploid Heliophila variabilis genome sheds a new light on the impact of polyploidization and diploidization on the diversity of the Cape flora.

Although the South African Cape flora is one of the most remarkable biodiversity hotspots, its high diversity has not been associated with polyploidy. Here, we report the chromosome-scale genome assembly of an ephemeral cruciferous species Heliophila variabilis (~334 Mb, n = 11) adapted to South African semiarid biomes. Two pairs of differently fractionated subgenomes suggest an allo-octoploid origin of the genome at least 12 million years ago. The ancestral octoploid Heliophila genome (2n = 8x = ~60) has probably originated through hybridization between two allotetraploids (2n = 4x = ~30) formed by distant, intertribal, hybridization. Rediploidization of the ancestral genome was marked by extensive reorganization of parental subgenomes, genome downsizing, and speciation events in the genus Heliophila. We found evidence for loss-of-function changes in genes associated with leaf development and early flowering, and over-retention and sub/neofunctionalization of genes involved in pathogen response and chemical defense. The genomic resources of H. variabilis will help elucidate the role of polyploidization and genome diploidization in plant adaptation to hot arid environments and origin of the Cape flora. The sequenced H. variabilis represents the first chromosome-scale genome assembly of a meso-octoploid representative of the mustard family.

Gradient Interphase Engineering Enabled by Anionic Redox for High-Voltage and Long-Life Li-Ion Batteries.

Intelligent utilization of the anionic redox reaction (ARR) in Li-rich cathodes is an advanced strategy for the practical implementation of next-generation high-energy-density rechargeable batteries. However, due to the intrinsic complexity of ARR (e.g., nucleophilic attacks), the instability of the cathode-electrolyte interphase (CEI) on a Li-rich cathode presents more challenges than typical high-voltage cathodes. Here, we manipulate CEI interfacial engineering by introducing an all-fluorinated electrolyte and exploiting its interaction with the nucleophilic attack to construct a gradient CEI containing a pair of fluorinated layers on a Li-rich cathode, delivering enhanced interfacial stability. Negative/detrimental nucleophilic electrolyte decomposition has been efficiently evolved to further reinforce CEI fabrication, resulting in the construction of LiF-based indurated outer shield and fluorinated polymer-based flexible inner sheaths. Gradient interphase engineering dramatically improved the capacity retention of the Li-rich cathode from 43 to 71% after 800 cycles and achieved superior cycling stability in anode-free and pouch-type full cells (98.8% capacity retention, 220 cycles), respectively.

Accelerating Discovery of Water Stable Metal-Organic Frameworks by Machine Learning.

Metal-organic frameworks (MOFs) provide an extensive design landscape for nanoporous materials that drive innovation across energy and environmental fields. However, their practical applications are often hindered by water stability challenges. In this study, a machine learning (ML) approach is proposed to accelerate the discovery of water stable MOFs and validated through experimental test. First, the largest database currently available that contains water stability information of 1133 synthesized MOFs is constructed and categorized according to experimental stability. Then, structural and chemical descriptors are applied at various fragmental levels to develop ML classifiers for predicting the water stability of MOFs. The ML classifiers achieve high prediction accuracy and excellent transferability on out-of-sample validation. Next, two MOFs are experimentally synthesized with their water stability tested to validate ML predictions. Finally, the ML classifiers are applied to discover water stable MOFs in the ab initio REPEAT charge MOF (ARC-MOF) database. Among ≈280 000 candidates, ≈130 000 (47%) MOFs are predicted to be water stable; furthermore, through multi-stability analysis, 461 (0.16%) MOFs are identified as not only water stable but also thermal and activation stable. The ML approach is anticipated to serve as a prerequisite filtering tool to streamline the exploration of water stable MOFs for important practical applications.

Diversification of freshwater crabs on the sky islands in the Hengduan Mountains Region, China.

The numerous naturally-fragmented sky islands (SIs) in the Hengduan Mountains Region (HMR) of southwestern China constitute discontinuous landscapes where montane habitats are isolated by dry-hot valleys which have fostered exceptional species diversification and endemicity. However, studies documenting the crucial role of SI on the speciation dynamics of native freshwater organisms are scarce. Here we used a novel set of comprehensive genetic markers (24 nuclear DNA sequences and complete mitogenomes), morphological characters, and biogeographical information to reveal the evolutionary history and speciation mechanisms of a group of small-bodied montane potamids in the genus Tenuipotamon. Our results provide a robustly supported phylogeny, and suggest that the vicariance events of these montane crabs correlate well with the emergence of SIs due to the uplift of the HMR during the Late Oligocene. Furthermore, ancestrally, mountain ridges provided corridors for the dispersal of these montane crabs that led to the colonization of moist montane-specific habitats, aided by past climatic conditions that were the crucial determinants of their evolutionary history. The present results illustrated that the mechanisms isolating SIs are reinforced by the harsh-dry isolating climatic features of dry-hot valleys separating SIs and continue to affect local diversification. This offers insights into the causes of the high biodiversity and endemism shown by the freshwater crabs of the HMR-SIs in southwestern China.

Effect of vitrification on protein O-GlcNAcylation in mouse metaphase II oocytes.

In brief: Oocyte vitrification leads to DNA hypomethylation, which results in defect in early embryo development. This study reveals that oocyte vitrification impairs the DNA methylation pattern by influencing protein O-GlcNAcylation. Abstract: Oocyte vitrification leads to decreased DNA methylation levels, which impairs the quality and the developmental potential of oocytes. However, the underlying molecular mechanism still need to be further revealed. In this study, mouse metaphase II (M II) oocytes were frozen by vitrification technology, while fresh oocytes were used as the control group. The effect of oocyte vitrification on protein O-GlcNAcylation and its impact on the developmental potential of oocytes were elucidated. We found that the protein O-GlcNAcylation levels were significantly increased in vitrified oocytes. Increase of protein O-GlcNAcylation levels in control oocytes by PUGNAc (an O-GlcNAcase inhibitor) decreases blastocyst rate after parthenogenetic activation (20.82% in PUGNAc-treated group; 53.82% in control group, P < 0.05). We also discovered that DNA methylation was disrupted in two-cell embryos derived from vitrified oocytes, resulting in decreased 5mC and increased 5hmC, showing similar phenotypes to that derived from PUGNAc-treated oocytes. In vitrified and PUGNAc-treated oocytes, O-GlcNAcylated TET3 was significantly increased. Notably, by inhibiting protein O-GlcNAcylation in vitrified oocytes using OSMI1 (an O-GlcNAc transferase inhibitor) we restored the DNA methylation in two-cell embryos and ameliorated the developmental defects in early embryo. Thus, elevated protein O-GlcNAcylation in vitrified oocytes is an essential contributor to their declining embryonic developmental potential. Modulation of protein O-GlcNAcylation improves the developmental potential of vitrified oocytes.

Loss-tailoring single-mode high-power supersymmetric lasers.

Diode lasers with high beam quality and high power have many promising applications. However, high beam quality is always in conflict with high power. In this Letter, we theoretically and experimentally confirm the mode instability property of supersymmetric structures at higher operating currents. Meanwhile, we propose a loss-tailoring diode laser based on a supersymmetric structure, which enables the higher-order lateral modes to obtain higher losses, raises the excitation threshold of the higher-order lateral modes, and achieves a stable fundamental-lateral-mode output at higher current operation. The device obtained a quasi-single-lobe lateral far-field distribution with the full width at half maximum (FWHM) of 7.58° at 350 mA under room temperature, which is a 65% reduction compared to the traditional Fabry-Perot (FP) diode lasers. Moreover, the M2 of 2.181@350 mA has an improvement of about 37% over traditional FP and supersymmetric structure lasers.

Crystal Structure of the Monocarborane Magnesium(II) Acetylide and Its Use in the Synthesis of α,ß-Unsaturated Ketones.

We report the first crystal structure of heteroleptic Grignard reagent 2 based on the carborane endo/exo dianion [CB11H11-12-C≡C]2-. Full characterization reveals a rare coordination pattern and affirms the bimetallic nature. Navigating the reactivity landscape, we unlock the potential of 2 in nucleophilic addition with ketones to afford propargylic alcohols 3, renowned for their synthetic versatility and potential biological activities, and unveil the Meyer-Schuster rearrangement, yielding α,ß-unsaturated carbonyl compounds 4. This narrative of synthesis, characterization, and reactivity opens new horizons for carborane chemistry, offering avenues for innovation and facile functionalization of carborane scaffolds.