The tumor-derived cytokine Chi3l1 induces neutrophil extracellular traps that promote T cell exclusion in triple-negative breast cancer.

In triple-negative breast cancer (TNBC), stromal restriction of CD8+ T cells associates with poor clinical outcomes and lack of responsiveness to immune-checkpoint blockade (ICB). To identify mediators of T cell stromal restriction, we profiled murine breast tumors lacking the transcription factor Stat3, which is commonly hyperactive in breast cancers and promotes an immunosuppressive tumor microenvironment. Expression of the cytokine Chi3l1 was decreased in Stat3-/- tumors. CHI3L1 expression was elevated in human TNBCs and other solid tumors exhibiting T cell stromal restriction. Chi3l1 ablation in the polyoma virus middle T (PyMT) breast cancer model generated an anti-tumor immune response and delayed mammary tumor onset. These effects were associated with increased T cell tumor infiltration and improved response to ICB. Mechanistically, Chi3l1 promoted neutrophil recruitment and neutrophil extracellular trap formation, which blocked T cell infiltration. Our findings provide insight into the mechanism underlying stromal restriction of CD8+ T cells and suggest that targeting Chi3l1 may promote anti-tumor immunity in various tumor types.

A whole-slide foundation model for digital pathology from real-world data.

Digital pathology poses unique computational challenges, as a standard gigapixel slide may comprise tens of thousands of image tiles1-3. Prior models have often resorted to subsampling a small portion of tiles for each slide, thus missing the important slide-level context4. Here we present Prov-GigaPath, a whole-slide pathology foundation model pretrained on 1.3 billion 256 × 256 pathology image tiles in 171,189 whole slides from Providence, a large US health network comprising 28 cancer centres. The slides originated from more than 30,000 patients covering 31 major tissue types. To pretrain Prov-GigaPath, we propose GigaPath, a novel vision transformer architecture for pretraining gigapixel pathology slides. To scale GigaPath for slide-level learning with tens of thousands of image tiles, GigaPath adapts the newly developed LongNet5 method to digital pathology. To evaluate Prov-GigaPath, we construct a digital pathology benchmark comprising 9 cancer subtyping tasks and 17 pathomics tasks, using both Providence and TCGA data6. With large-scale pretraining and ultra-large-context modelling, Prov-GigaPath attains state-of-the-art performance on 25 out of 26 tasks, with significant improvement over the second-best method on 18 tasks. We further demonstrate the potential of Prov-GigaPath on vision-language pretraining for pathology7,8 by incorporating the pathology reports. In sum, Prov-GigaPath is an open-weight foundation model that achieves state-of-the-art performance on various digital pathology tasks, demonstrating the importance of real-world data and whole-slide modelling.

The menin inhibitor revumenib in KMT2A-rearranged or NPM1-mutant leukaemia.

Targeting critical epigenetic regulators reverses aberrant transcription in cancer, thereby restoring normal tissue function1-3. The interaction of menin with lysine methyltransferase 2A (KMT2A), an epigenetic regulator, is a dependence in acute leukaemia caused by either rearrangement of KMT2A or mutation of the nucleophosmin 1 gene (NPM1)4-6. KMT2A rearrangements occur in up to 10% of acute leukaemias and have an adverse prognosis, whereas NPM1 mutations occur in up to 30%, forming the most common genetic alteration in acute myeloid leukaemia7,8. Here, we describe the results of the first-in-human phase 1 clinical trial investigating revumenib (SNDX-5613), a potent and selective oral inhibitor of the menin-KMT2A interaction, in patients with relapsed or refractory acute leukaemia (ClinicalTrials.gov, NCT04065399). We show that therapy with revumenib was associated with a low frequency of grade 3 or higher treatment-related adverse events and a 30% rate of complete remission or complete remission with partial haematologic recovery (CR/CRh) in the efficacy analysis population. Asymptomatic prolongation of the QT interval on electrocardiography was identified as the only dose-limiting toxicity. Remissions occurred in leukaemias refractory to multiple previous lines of therapy. We demonstrate clearance of residual disease using sensitive clinical assays and identify hallmarks of differentiation into normal haematopoietic cells, including differentiation syndrome. These data establish menin inhibition as a therapeutic strategy for susceptible acute leukaemia subtypes.

An extra-erythrocyte role of haemoglobin body in chondrocyte hypoxia adaption.

Although haemoglobin is a known carrier of oxygen in erythrocytes that functions to transport oxygen over a long range, its physiological roles outside erythrocytes are largely elusive1,2. Here we found that chondrocytes produced massive amounts of haemoglobin to form eosin-positive bodies in their cytoplasm. The haemoglobin body (Hedy) is a membraneless condensate characterized by phase separation. Production of haemoglobin in chondrocytes is controlled by hypoxia and is dependent on KLF1 rather than the HIF1/2α pathway. Deletion of haemoglobin in chondrocytes leads to Hedy loss along with severe hypoxia, enhanced glycolysis and extensive cell death in the centre of cartilaginous tissue, which is attributed to the loss of the Hedy-controlled oxygen supply under hypoxic conditions. These results demonstrate an extra-erythrocyte role of haemoglobin in chondrocytes, and uncover a heretofore unrecognized mechanism in which chondrocytes survive a hypoxic environment through Hedy.

Prior knowledge-guided multilevel graph neural network for tumor risk prediction and interpretation via multi-omics data integration.

The interrelation and complementary nature of multi-omics data can provide valuable insights into the intricate molecular mechanisms underlying diseases. However, challenges such as limited sample size, high data dimensionality and differences in omics modalities pose significant obstacles to fully harnessing the potential of these data. The prior knowledge such as gene regulatory network and pathway information harbors useful gene-gene interaction and gene functional module information. To effectively integrate multi-omics data and make full use of the prior knowledge, here, we propose a Multilevel-graph neural network (GNN): a hierarchically designed deep learning algorithm that sequentially leverages multi-omics data, gene regulatory networks and pathway information to extract features and enhance accuracy in predicting survival risk. Our method achieved better accuracy compared with existing methods. Furthermore, key factors nonlinearly associated with the tumor pathogenesis are prioritized by employing two interpretation algorithms (i.e. GNN-Explainer and IGscore) for neural networks, at gene and pathway level, respectively. The top genes and pathways exhibit strong associations with disease in survival analyses, many of which such as SEC61G and CYP27B1 are previously reported in the literature.

Deep learning-based quantification and transcriptomic profiling reveal a methyl jasmonate-mediated glandular trichome formation pathway in Cannabis sativa.

Cannabis glandular trichomes (GTs) are economically and biotechnologically important structures that have a remarkable morphology and capacity to produce, store, and secrete diverse classes of secondary metabolites. However, our understanding of the developmental changes and the underlying molecular processes involved in cannabis GT development is limited. In this study, we developed Cannabis Glandular Trichome Detection Model (CGTDM), a deep learning-based model capable of differentiating and quantifying three types of cannabis GTs with a high degree of efficiency and accuracy. By profiling at eight different time points, we captured dynamic changes in gene expression, phenotypes, and metabolic processes associated with GT development. By integrating weighted gene co-expression network analysis with CGTDM measurements, we established correlations between phenotypic variations in GT traits and the global transcriptome profiles across the developmental gradient. Notably, we identified a module containing methyl jasmonate (MeJA)-responsive genes that significantly correlated with stalked GT density and cannabinoid content during development, suggesting the existence of a MeJA-mediated GT formation pathway. Our findings were further supported by the successful promotion of GT development in cannabis through exogenous MeJA treatment. Importantly, we have identified CsMYC4 as a key transcription factor that positively regulates GT formation via MeJA signaling in cannabis. These findings provide novel tools for GT detection and counting, as well as valuable information for understanding the molecular regulatory mechanism of GT formation, which has the potential to facilitate the molecular breeding, targeted engineering, informed harvest timing, and manipulation of cannabinoid production.

Illuminating bunyavirus entry into host cells with fluorescence.

Bunyavirales constitute the largest order of enveloped RNA viruses, many members of which cause severe diseases in humans and domestic animals. In recent decades, innovative fluorescence-based methods have paved the way to visualize and track single fluorescent bunyaviral particles in fixed and live cells. This technological breakthrough has enabled imaging of the early stages of infection and the quantification of every step in the bunyavirus cell entry process. Here, we describe the latest procedures for rendering bunyaviral particles fluorescent and discuss the advantages and disadvantages of each approach in light of the most recent advances in fluorescence detection and monitoring of bunyavirus entry. In this mini-review, we also illustrate how fluorescent viral particles are a powerful tool for deciphering the cellular entry process of bunyaviruses, the vast majority of which have not yet been analyzed.

Effectiveness of Covid-19 Vaccines over a 9-Month Period in North Carolina.

BACKGROUND: The duration of protection afforded by coronavirus disease 2019 (Covid-19) vaccines in the United States is unclear. Whether the increase in postvaccination infections during the summer of 2021 was caused by declining immunity over time, the emergence of the B.1.617.2 (delta) variant, or both is unknown. METHODS: We extracted data regarding Covid-19-related vaccination and outcomes during a 9-month period (December 11, 2020, to September 8, 2021) for approximately 10.6 million North Carolina residents by linking data from the North Carolina Covid-19 Surveillance System and the Covid-19 Vaccine Management System. We used a Cox regression model to estimate the effectiveness of the BNT162b2 (Pfizer-BioNTech), mRNA-1273 (Moderna), and Ad26.COV2.S (Johnson & Johnson-Janssen) vaccines in reducing the current risks of Covid-19, hospitalization, and death, as a function of time elapsed since vaccination. RESULTS: For the two-dose regimens of messenger RNA (mRNA) vaccines BNT162b2 (30 µg per dose) and mRNA-1273 (100 µg per dose), vaccine effectiveness against Covid-19 was 94.5% (95% confidence interval [CI], 94.1 to 94.9) and 95.9% (95% CI, 95.5 to 96.2), respectively, at 2 months after the first dose and decreased to 66.6% (95% CI, 65.2 to 67.8) and 80.3% (95% CI, 79.3 to 81.2), respectively, at 7 months. Among early recipients of BNT162b2 and mRNA-1273, effectiveness decreased by approximately 15 and 10 percentage points, respectively, from mid-June to mid-July, when the delta variant became dominant. For the one-dose regimen of Ad26.COV2.S (5 × 1010 viral particles), effectiveness against Covid-19 was 74.8% (95% CI, 72.5 to 76.9) at 1 month and decreased to 59.4% (95% CI, 57.2 to 61.5) at 5 months. All three vaccines maintained better effectiveness in preventing hospitalization and death than in preventing infection over time, although the two mRNA vaccines provided higher levels of protection than Ad26.COV2.S. CONCLUSIONS: All three Covid-19 vaccines had durable effectiveness in reducing the risks of hospitalization and death. Waning protection against infection over time was due to both declining immunity and the emergence of the delta variant. (Funded by a Dennis Gillings Distinguished Professorship and the National Institutes of Health.).

scAnno: a deconvolution strategy-based automatic cell type annotation tool for single-cell RNA-sequencing data sets.

Undoubtedly, single-cell RNA sequencing (scRNA-seq) has changed the research landscape by providing insights into heterogeneous, complex and rare cell populations. Given that more such data sets will become available in the near future, their accurate assessment with compatible and robust models for cell type annotation is a prerequisite. Considering this, herein, we developed scAnno (scRNA-seq data annotation), an automated annotation tool for scRNA-seq data sets primarily based on the single-cell cluster levels, using a joint deconvolution strategy and logistic regression. We explicitly constructed a reference profile for human (30 cell types and 50 human tissues) and a reference profile for mouse (26 cell types and 50 mouse tissues) to support this novel methodology (scAnno). scAnno offers a possibility to obtain genes with high expression and specificity in a given cell type as cell type-specific genes (marker genes) by combining co-expression genes with seed genes as a core. Of importance, scAnno can accurately identify cell type-specific genes based on cell type reference expression profiles without any prior information. Particularly, in the peripheral blood mononuclear cell data set, the marker genes identified by scAnno showed cell type-specific expression, and the majority of marker genes matched exactly with those included in the CellMarker database. Besides validating the flexibility and interpretability of scAnno in identifying marker genes, we also proved its superiority in cell type annotation over other cell type annotation tools (SingleR, scPred, CHETAH and scmap-cluster) through internal validation of data sets (average annotation accuracy: 99.05%) and cross-platform data sets (average annotation accuracy: 95.56%). Taken together, we established the first novel methodology that utilizes a deconvolution strategy for automated cell typing and is capable of being a significant application in broader scRNA-seq analysis. scAnno is available at https://github.com/liuhong-jia/scAnno.

Glucosylceramide in bunyavirus particles is essential for virus binding to host cells.

Hexosylceramides (HexCer) are implicated in the infection process of various pathogens. However, the molecular and cellular functions of HexCer in infectious cycles are poorly understood. Investigating the enveloped virus Uukuniemi (UUKV), a bunyavirus of the Phenuiviridae family, we performed a lipidomic analysis with mass spectrometry and determined the lipidome of both infected cells and derived virions. We found that UUKV alters the processing of HexCer to glycosphingolipids (GSL) in infected cells. The infection resulted in the overexpression of glucosylceramide (GlcCer) synthase (UGCG) and the specific accumulation of GlcCer and its subsequent incorporation into viral progeny. UUKV and several pathogenic bunyaviruses relied on GlcCer in the viral envelope for binding to various host cell types. Overall, our results indicate that GlcCer is a structural determinant of virions crucial for bunyavirus infectivity. This study also highlights the importance of glycolipids on virions in facilitating interactions with host cell receptors and infectious entry of enveloped viruses.

Carbon-Extraction-Induced Biaxial Strain Tuning of Carbon-Intercalated Iridium Metallene for Hydrogen Evolution Catalysis.

Metallene materials with atomic thicknesses are receiving increasing attention in electrocatalysis due to ultrahigh surface areas and distinctive surface strain. However, the continuous strain regulation of metallene remains a grand challenge. Herein, taking advantage of autocatalytic reduction of Cu2+ on biaxially strained, carbon-intercalated Ir metallene, we achieve control over the carbon extraction kinetics, enabling fine regulation of carbon intercalation concentration and continuous tuning of (111) in-plane (-2.0%-2.6%) and interplanar (3.5%-8.8%) strains over unprecedentedly wide ranges. Electrocatalysis measurements reveal the strain-dependent activity toward hydrogen evolution reaction (HER), where weakly strained Ir metallene (w-Ir metallene) with the smallest lattice constant presents the highest mass activity of 2.89 A mg-1Ir at -0.02 V vs reversible hydrogen electrode (RHE). Theoretical calculations validated the pivotal role of lattice compression in optimizing H binding on carbon-intercalated Ir metallene surfaces by downshifting the d-band center, further highlighting the significance of strain engineering for boosted electrocatalysis.

Natural and synthetic 5-(3'-indolyl)oxazoles: Biological activity, chemical synthesis and advanced molecules.

5-(3'-Indolyl)oxazole moiety is a privileged heterocyclic scaffold, embedded in many biologically interesting natural products and potential therapeutic agents. Compounds containing this scaffold, whether from natural sources or synthesized, have demonstrated a wide array of biological activities. This has piqued the interest of synthetic chemists, leading to a large number of reported synthetic approaches to 5-(3'-indolyl)oxazole scaffold in recent years. In this review, we comprehensively overviewed the different biological activities and chemical synthetic methods for the 5-(3'-indolyl)oxazole scaffold reported in the literatures from 1963 to 2024. The focus of this study is to highlight the significance of 5-(3'-indolyl)oxazole derivatives as the lead compounds for the lead discovery of anticancer, pesticidal, antimicrobial, antiviral, antioxidant and anti-inflammatory agents, to summarize the synthetic methods for the 5-(3'-indolyl)oxazole scaffold. In addition, the reported mechanism of action of 5-(3'-indolyl)oxazoles and advanced molecules studied in animal models are also reviewed. Furthermore, this review offers perspectives on how 5-(3'-indolyl)oxazole scaffold as a privileged structure might be exploited in the future.

Cell cycle-dependent kinase inhibitor GhKRP6, a direct target of GhBES1.4, participates in BR regulation of cell expansion in cotton.

The steroidal hormone brassinosteroid (BR) has been shown to positively regulate cell expansion in plants. However, the specific mechanism by which BR controls this process has not been fully understood. In this study, RNA-seq and DAP-seq analysis of GhBES1.4 (a core transcription factor in BR signaling) were used to identify a cotton cell cycle-dependent kinase inhibitor called GhKRP6. The study found that GhKRP6 was significantly induced by the BR hormone and that GhBES1.4 directly promoted the expression of GhKRP6 by binding to the CACGTG motif in its promoter region. GhKRP6-silenced cotton plants had smaller leaves with more cells and reduced cell size. Furthermore, endoreduplication was inhibited, which affected cell expansion and ultimately decreased fiber length and seed size in GhKRP6-silenced plants compared with the control. The KEGG enrichment results of control and VIGS-GhKRP6 plants revealed differential expression of genes related to cell wall biosynthesis, MAPK, and plant hormone transduction pathways - all of which are related to cell expansion. Additionally, some cyclin-dependent kinase (CDK) genes were upregulated in the plants with silenced GhKRP6. Our study also found that GhKRP6 could interact directly with a cell cycle-dependent kinase called GhCDKG. Taken together, these results suggest that BR signaling influences cell expansion by directly modulating the expression of cell cycle-dependent kinase inhibitor GhKRP6 via GhBES1.4.

N6 -Methyladenosine mRNA modification regulates transcripts stability associated with cotton fiber elongation.

N6 -Methyladenosine (m6 A) is the most abundant methylation modification in eukaryotic mRNA. The discovery of the dynamic and reversible regulatory mechanism of m6 A has greatly promoted the development of m6 A-led epitranscriptomics. However, the characterization of m6 A in cotton fiber is still unknown. Here, we reveal the potential link between m6 A modification and cotton fiber elongation by parallel m6 A-immunoprecipitation-sequencing (m6 A-seq) and RNA-seq analysis of fibers from the short fiber mutants Ligonliness-2 (Li2 ) and wild-type (WT). This study demonstrated a higher level of m6 A in the Li2 mutant, with the enrichment of m6 A modifications in the stop codon, 3'-untranslated region and coding sequence regions than in WT cotton. In the correlation analysis between genes containing differential m6 A modifications and differentially expressed genes, we identified several genes that could potentially regulate fiber elongation, including cytoskeleton, microtubule binding, cell wall and transcription factors (TFs). We further confirmed that the methylation of m6 A affected the mRNA stability of these fiber elongation-related genes including the TF GhMYB44, which showed the highest expression level in the RNA-seq data and m6 A methylation in the m6 A-seq data. Next, the overexpression of GhMYB44 reduces fiber elongation, whereas the silencing of GhMYB44 produces longer fibers. In summary, these results uncover that m6 A methylation regulated the expression of genes related to fiber development by affecting mRNA's stability, ultimately affecting cotton fiber elongation.

An Ultrastable Low-Temperature Na Metal Battery Enabled by Synergy between Weakly Solvating Solvents.

The low ionic conductivity and high desolvation barrier are the main challenges for organic electrolytes in rechargeable metal batteries, especially at low temperatures. The general strategy is to couple strong-solvation and weak-solvation solvents to give balanced physicochemical properties. However, the two challenges described above cannot be overcome at the same time. Herein, we combine two different kinds of weakly solvating solvents with a very low desolvation energy. Interestingly, the synergy between the weak-solvation solvents can break the locally ordered structure at a low temperature to enable higher ionic conductivity compared to those with individual solvents. Thus, facile desolvation and high ionic conductivity are achieved simultaneously, significantly improving the reversibility of electrode reactions at low temperatures. The Na metal anode can be stably cycled at 2 mA cm-2 at -40 °C for 1000 h. The Na||Na3V2(PO4)3 cell shows the reversible capacity of 64 mAh g-1 at 0.3 C after 300 cycles at -40 °C, and the capacity retention is 86%. This strategy is applicable to other sets of weak-solvation solvents, providing guidance for the development of electrolytes for low-temperature rechargeable metal batteries.

Precise Tuning of the D-Band Center of Dual-Atomic Enzymes for Catalytic Therapy.

Single-atom nanozyme-based catalytic therapy is of great interest in the field of tumor catalytic therapy; however, their development suffers from the low affinity of nanozymes to the substrates (H2O2 or O2), leading to deficient catalytic activity in the tumor microenvironment. Herein, we report a new strategy for precisely tuning the d-band center of dual-atomic sites to enhance the affinity of metal atomic sites and substrates on a class of edge-rich N-doped porous carbon dual-atomic sites Fe-Mn (Fe1Mn1-NCe) for greatly boosting multiple-enzyme-like catalytic activities. The as-made Fe1Mn1-NCe achieved a much higher catalytic efficiency (Kcat/Km = 4.01 × 105 S-1·M-1) than Fe1-NCe (Kcat/Km = 2.41 × 104 S-1·M-1) with an outstanding stability of over 90% activity retention after 1 year, which is the best among the reported dual-atom nanozymes. Theoretical calculations reveal that the synergetic effect of Mn upshifts the d-band center of Fe from -1.113 to -0.564 eV and enhances the adsorption capacity for the substrate, thus accelerating the dissociation of H2O2 and weakening the O-O bond on O2. We further demonstrated that the superior enzyme-like catalytic activity of Fe1Mn1-NCe combined with photothermal therapy could effectively inhibit tumor growth in vivo, with an inhibition rate of up to 95.74%, which is the highest value among the dual-atom artificial enzyme therapies reported so far.

Flavin-Dependent Monooxygenase Kmy13 Mediates Formation of the Carbocyclic ansa System during Kendomycin B Biosynthesis.

Kendomycin B is distinguished from other ansamycins by its unique, fully carbogenic ansa scaffold. We show here that FAD-dependent monooxygenase Kmy13 is solely responsible for installing the rare ansa structural framework; in vivo gene disruption/complementation experiments and in vitro enzymatic assays are described in detail. Moreover, the compound with a ß-keto ester, kendolactone A (2), was confirmed as the natural substrate of Kmy13 and a bona fide biosynthetic intermediate en route to kendomycin B. Further structural prediction and biochemical assays have provided significant insights into the catalytic mechanism of Kmy13.

High-Volumetric Density Atomic Cobalt on Multishell ZnxCd1-xS Boosts Photocatalytic CO2 Reduction.

The volumetric density of the metal atomic site is decisive to the operating efficiency of the photosynthetic nanoreactor, yet its rational design and synthesis remain a grand challenge. Herein, we report a shell-regulating approach to enhance the volumetric density of Co atomic sites onto/into multishell ZnxCd1-xS for greatly improving CO2 photoreduction activity. We first establish a quantitative relation between the number of shell layers, specific surface areas, and volumetric density of atomic sites on multishell ZnxCd1-xS and conclude a positive relation between photosynthetic performance and the number of shell layers. The triple-shell ZnxCd1-xS-Co1 achieves the highest CO yield rate of 7629.7 µmol g-1 h-1, superior to those of the double-shell ZnxCd1-xS-Co1 (5882.2 µmol g-1 h-1) and single-shell ZnxCd1-xS-Co1 (4724.2 µmol g-1 h-1). Density functional theory calculations suggest that high-density Co atomic sites can promote the mobility of photogenerated electrons and enhance the adsorption of Co(bpy)32+ to increase CO2 activation (CO2 → CO2* → COOH* → CO* → CO) via the S-Co-bpy interaction, thereby enhancing the efficiency of photocatalytic CO2 reduction.

Strong d-π Orbital Coupling of Co-C4 Atomic Sites on Graphdiyne Boosts Potassium-Sulfur Battery Electrocatalysis.

Potassium-sulfur (K-S) batteries are severely limited by the sluggish kinetics of the solid-phase conversion of K2S3/K2S2 to K2S, the rate-determining and performance-governing step, which urgently requires a cathode with facilitated sulfur accommodation and improved catalytic efficiency. To this end, we leverage the orbital-coupling approach and herein report a strong d-π coupling catalytic configuration of single-atom Co anchored between two alkynyls of graphdiyne (Co-GDY). The d-π orbital coupling of the Co-C4 moiety fully redistributes electrons two-dimensionally across the GDY, and as a result, drastically accelerates the solid-phase K2S3/K2S2 to K2S conversion and enhances the adsorption of sulfur species. Applied as the cathode, the S/Co-GDY delivered a record-high rate performance of 496.0 mAh g-1 at 5 A g-1 in K-S batteries. In situ and ex situ characterizations coupling density functional theory (DFT) calculations rationalize how the strong d-π orbital coupling of Co-C4 configuration promotes the reversible solid-state transformation kinetics of potassium polysulfide for high-performance K-S batteries.