High-throughput profiling of chemical-induced gene expression across 93,644 perturbations.

In this Resource, we present an extensive dataset of chemical-induced gene signatures (CIGS), encompassing expression patterns of 3,407 genes regulating key biological processes in 2 human cell lines exposed to 13,221 compounds across 93,664 perturbations. This dataset encompasses 319,045,108 gene expression events, generated through 2 high-throughput technologies: the previously documented high-throughput sequencing-based high-throughput screening (HTS) and the newly developed highly multiplexed and parallel sequencing (HiMAP-seq). Our results show that HiMAP-seq is comparable to RNA sequencing, but can profile the expression of thousands of genes across thousands of samples in one single test by utilizing a pooled-sample strategy.

Natural small molecule bergapten ameliorates rheumatoid arthritis by targeting STAT3.

Rheumatoid arthritis (RA) is a severe and chronic inflammatory disease that currently has almost no cure. Here, we report a natural small molecule bergapten (BG) as a promising treatment for RA. Firstly, our results show BG treatment significantly inhibits RA in collagen-induced arthritis (CIA) rats.

Global burden of chronic kidney disease and its attributable risk factors (1990-2021): an analysis based on the global burden of disease study.

Background: Chronic kidney disease is a global health challenge, especially in resource-limited regions. Understanding its burden and key risk factors is crucial for effective interventions.

Methods: Data from the Global Burden of Disease Study (1990-2021) covering 204 countries were analyzed to assess trends in prevalence, mortality, and disability-adjusted life years for chronic kidney disease, alongside geographic, age, sex, and risk factor patterns.

Chemical Proteomics Identifies RBBP7 as a New E3 Ligase Supporting Targeted Protein Degradation.

Targeted protein degradation (TPD) has been recognized as a powerful therapeutic strategy for the treatment of a wide range of diseases. However, the application of existing degraders is constrained by their dependence on a limited number of E3 ubiquitin ligases, such as CRBN and VHL. To address this limitation, we developed a suite of novel small-molecule degraders by integrating an ynamide electrophile into protein-targeting ligands.

Interpretable Dynamic Brain Network Analysis with Functional and Structural Priors.

The dynamic functional brain network (DFBN) inherently captures topological changes in brain connectivity pattern during activity, attracting increasing attention for detecting brain disorders. However, most current DFBN analysis methods rely on data-driven modeling and ignore crucial prior knowledge of brain structure and function, resulting in weak interpretability of models. Furthermore, effectively extracting dynamic topological features from DFBN is still a challenging issue, due to its intricate spatio-temporal features coupling.

Azoacetylene Electrophiles for Proteome-wide Ligand and Target Discovery: Supporting Targeted Protein Degradation.

Covalent probes integrated with chemical proteomics have been an efficient method for disclosing new druggable targets and E3 ubiquitin ligases supporting targeted protein degradation. However, a large fraction of the proteome including E3 ligases remains inaccessible with existing electrophiles. In this work, we developed a new reactive warhead, terminal azoacetylene, which can be generated by in situ desilylation for proteome profiling under cellular conditions.

Gene signature-guided isolation identifies cucurbitacins as STAT3 inhibitors from Picria fel-terrae Lour.

Background: The transcription activator factor signal transducer and activator of transcription 3 (STAT3) diseases, such as triple-negative breast cancer (TNBC), making the need to identify new inhibitors crucial for effective treatment. In this regard, plants used in traditional Chinese medicine, including Picria fel-terrae Lour. (PFL), represent a rich source of bioactive compounds for identifying STAT3 inhibitors.

Proteome-Wide Ligand and Target Discovery by Using β-Nitrostyrene Electrophiles: Supporting Targeted Protein Degradation.

Bioconjugation chemistry has been a powerful avenue in expanding the repertoire of druggable proteome, as well as in identifying new E3 ligases to support targeted protein degradation (TPD). However, a large fraction of proteome remains inaccessible with existing covalent probes. Herein, we incorporated various electron-withdrawing groups into styrene derivatives and identified β-nitrostyrene as a cysteine-targeting reversible covalent warhead for target discovery.

Enhancing Neurodegenerative Disease Diagnosis Through Confidence-Driven Dynamic Spatio-Temporal Convolutional Network.

Dynamic brain networks are more effective than static networks in characterizing the evolving patterns of brain functional connectivity, making them a more promising tool for diagnosing neurodegenerative diseases. However, existing classification methods for dynamic brain networks often rely on sliding windows to extract multi-window features, leading to suboptimal performance due to the spatio-temporal coupling on these windows and limited ability to effectively integrate complex topological features. To address these limitations, we propose a novel method called Confidence-Driven Dynamic Spatio-Temporal Convolutional Network (CD-DSTCN).

High-temperature deuterium tracks the thermal stability of hydroxyl in epidote and zoisite.

Studying the thermal stability of the -OH groups in epidote-group minerals is of significant importance for understanding the deep-water cycle of the Earth. Epidote group minerals are among the common silicate minerals in the mafic oceanic crust of subducting lithospheric plates and are important water carriers in the deep mantle as well as in the Earth's deep-water cycle. Deuteration reactions offer significant advantages in tracing the thermal stability of the -OH groups in minerals, allowing for the labeling of hydrogen without affecting the mineral structure.

Multimodal fusion model for diagnosing mild cognitive impairment in unilateral middle cerebral artery steno-occlusive disease.

Objectives: To propose a multimodal functional brain network (FBN) and structural brain network (SBN) topological feature fusion technique based on resting-state functional magnetic resonance imaging (rs-fMRI), diffusion tensor imaging (DTI), 3D-T1-weighted imaging (3D-T1WI), and demographic characteristics to diagnose mild cognitive impairment (MCI) in patients with unilateral middle cerebral artery (MCA) steno-occlusive disease.

Methods: The performances of different algorithms on the MCI dataset were evaluated using 5-fold cross-validation. The diagnostic results of the multimodal performance were evaluated using t-distributed stochastic neighbor embedding (t-SNE) analysis.

Targeting CDK4/6 suppresses colorectal cancer by destabilizing YAP1.

Colorectal cancer (CRC) is among the most prevalent and deadly cancers worldwide. The Yes-associated protein 1 (YAP1) is frequently dysregulated in cancers, contributing to cancer stemness, chemoresistance, and cancer-related death. However, strategies directly targeting YAP1 have not yet been successful because of the lack of active binding pockets and unregulated toxicity.

Multi-channel spatio-temporal graph attention contrastive network for brain disease diagnosis.

Dynamic brain networks (DBNs) can capture the intricate connections and temporal evolution among brain regions, becoming increasingly crucial in the diagnosis of neurological disorders. However, most existing researches tend to focus on isolated brain network sequence segmented by sliding windows, and they are difficult to effectively uncover the higher-order spatio-temporal topological pattern in DBNs. Meantime, it remains a challenge to utilize the structure connectivity prior in the DBNs analysis.

Cell-Active, Arginine-Targeting Irreversible Covalent Inhibitors for Non-Kinases and Kinases.

Targeted covalent inhibitors (TCIs) play an essential role in the fields of kinase research and drug discovery. TCI strategies to target more common amino acid side-chains have yet to be demonstrated. Targeting other amino acids would also expand the pharmaceutical industry's toolbox for targeting other tough-to-drug proteins.

Identification of chemical inhibitors targeting long noncoding RNA through gene signature-based high throughput screening.

Scalable methods for functionally high-throughput screening of RNA-targeting small molecules are currently limited. Here, an RNA knockdown gene signature and high-throughput sequencing-based high-throughput screening (HTS) were integrated to identify RNA-targeting compounds. We first generated a gene signature characterizing the knockdown of the long non-coding RNA LINC00973.

Multifaceted roles of cGAS-STING pathway in the lung cancer: from mechanisms to translation.

Lung cancer (LC) remains one of the most prevalent and lethal malignancies globally, with a 5-year survival rate for advanced cases persistently below 10%. Despite the significant advancements in immunotherapy, a substantial proportion of patients with advanced LC fail to respond effectively to these treatments, highlighting an urgent need for novel immunotherapeutic targets. The cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) pathway has gained prominence as a potential target for improving LC immunotherapy due to its pivotal role in enhancing anti-tumor immune responses, augmenting tumor antigen presentation, and promoting T cell infiltration.

Pharmacological targeting of casein kinase 1δ suppresses oncogenic NRAS-driven melanoma.

Activating mutations in NRAS account for 15-20% of melanoma, yet effective anti-NRAS therapies are still lacking. In this study, we unveil the casein kinase 1δ (CK1δ) as an uncharacterized regulator of oncogenic NRAS mutations, specifically Q61R and Q61K, which are the most prevalent NRAS mutations in melanoma. The genetic ablation or pharmacological inhibition of CK1δ markedly destabilizes NRAS mutants and suppresses their oncogenic functions.

Global Profiling Lysine Reactivity and Ligandability with Oxidant-Triggered Bioconjugation Chemistry.

Due to the high abundance and diverse functions of lysine residues, both in the interior and on the surface of proteins, the development of new methods to characterize their reactivity and ligandability could significantly expand the pool of druggable targets. To date, only a limited number of aminophilic electrophiles have been assessed for interactions with the lysine proteome, resulting in a substantial fraction remaining inaccessible to current probes. Here, to the best of our knowledge, we report the first oxidant-triggered bioconjugation platform for in-depth profiling of lysines.

Static and Dynamic Functional Network Connectivity in Parkinson's Disease Patients With Postural Instability and Gait Disorder.

Aims: The exact cause of the parkinsonism gait remains uncertain. We first focus on understanding the underlying neurological reasons for these symptoms through the examination of both static functional network connectivity (SFNC) and dynamic functional network connectivity (DFNC).

Methods: We recruited 64 postural instability and gait disorder-dominated Parkinson's disease (PIGD-PD) patients, 31 non-PIGD-PD (nPIGD-PD) patients, and 54 healthy controls (HC) from Nanjing Brain Hospital.

Targeting EGFR degradation by autophagosome degraders.

Several generations of epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors have been developed for the treatment of non-small cell lung cancer (NSCLC) in clinic. However, emerging drug resistance mediated by new EGFR mutations or activations by pass, leads to malignant progression of NSCLC. Proteolysis targeting chimeras (PROTACs) have been utilized to overcome the drug resistance acquired by mutant EGFR, newly potent and selective degraders are still need to be developed for clinical applications.

Catalyst-free late-stage functionalization to assemble α-acyloxyenamide electrophiles for selectively profiling conserved lysine residues.

Covalent probes coupled with chemical proteomics represent a powerful method for investigating small molecule and protein interactions. However, the creation of a reactive warhead within various ligands to form covalent probes has been a major obstacle. Herein, we report a convenient and robust process to assemble a unique electrophile, an α-acyloxyenamide, through a one-step late-stage coupling reaction.

Spatio-Temporal Graph Hubness Propagation Model for Dynamic Brain Network Classification.

Dynamic brain network has the advantage over static brain network in characterizing the variation pattern of functional brain connectivity, and it has attracted increasing attention in brain disease diagnosis. However, most of the existing dynamic brain networks analysis methods rely on extracting features from independent brain networks divided by sliding windows, making them hard to reveal the high-order dynamic evolution laws of functional brain networks. Additionally, they cannot effectively extract the spatio-temporal topology features in dynamic brain networks.

3D hierarchic interfacial assembly of Au nanocage@Au along with IS-AgMNPs for simultaneous, ultrasensitive, reliable, and quantitative SERS detection of colorectal cancer related miRNAs.

Simultaneous, reliable, and ultra-sensitive analysis of promising miRNA biomarkers of colorectal cancer (CRC) in serum is critical for early diagnosis and prognosis of CRC. In this work, we proposed a novel 3D hierarchic assembly clusters-based SERS strategy with dual enrichment and enhancement designed for the ultrasensitive and quantitative analysis of two upregulated CRC-related miRNAs (miR-21 and miR-31). The biosensor contains the following: (1) SERS probe, Au nanocage@Au nanoparticles (AuNC@Au NPs) labeled with Raman reporters (RaRs).

Comprehensive pan-cancer analysis unveils the significant prognostic value and potential role in immune microenvironment modulation of TRIB3.

TRIB3, a pseudokinase, was previously studied within only some specific cancer types, leaving its comprehensive functions in pan-cancer contexts largely unexplored. Here, we performed an integrated analysis of expression, prognosis, genetic alterations, functional enrichment and tumor immune-related characteristics in 33 cancer types. Our results showed that exhibits high expression levels across 24 different cancer types and correlates closely with unfavorable prognoses.