Real-Time Direct Monitoring of Chirality Fixation and Recognition at the Single-Molecule Level.

Chirality, a fundamental attribute of nature, significantly influences a wide range of phenomena related to physical properties, chemical reactions, biological pharmacology, and so on. As a pivotal aspect of chirality research, chirality recognition contributes to the synthesis of complex chiral products from simple chiral compounds and exhibits intricate interplay between chiral materials. However, macroscopic detection technologies cannot unveil the dynamic process and intrinsic mechanisms of single-molecule chirality recognition. Herein, we present a single-molecule detection platform based on graphene-molecule-graphene single-molecule junctions to measure the chirality recognition involving interactions between amines and chiral alcohols. This approach leads to the realization of in situ and real-time direct observation of chirality recognition at the single-molecule level, demonstrating that chiral alcohols exhibit compelling potential to induce the formation of the corresponding chiral configuration of molecules. The amalgamation of theoretical analyses with experimental findings reveals a synergistic action between electrostatic interactions and steric hindrance effects in the chirality recognition process, thus substantiating the microscopic mechanism governing the chiral structure-activity relationship. These studies open up a pathway for exploring novel chiral phenomena from the fundamental limits of chemistry, such as chiral origin and chiral amplification, and offer important insights into the precise synthesis of chiral materials.

Network enrichment significance testing in brain-phenotype association studies.

Functional networks often guide our interpretation of spatial maps of brain-phenotype associations. However, methods for assessing enrichment of associations within networks of interest have varied in terms of both scientific rigor and underlying assumptions. While some approaches have relied on subjective interpretations, others have made unrealistic assumptions about spatial properties of imaging data, leading to inflated false positive rates. We seek to address this gap in existing methodology by borrowing insight from a method widely used in genetics research for testing enrichment of associations between a set of genes and a phenotype of interest. We propose network enrichment significance testing (NEST), a flexible framework for testing the specificity of brain-phenotype associations to functional networks or other sub-regions of the brain. We apply NEST to study enrichment of associations with structural and functional brain imaging data from a large-scale neurodevelopmental cohort study.

Spatial Single-cell Analysis Decodes Cortical Layer and Area Specification.

The human cerebral cortex, pivotal for advanced cognitive functions, is composed of six distinct layers and dozens of functionally specialized areas 1,2 . The layers and areas are distinguished both molecularly, by diverse neuronal and glial cell subtypes, and structurally, through intricate spatial organization 3,4 . While single-cell transcriptomics studies have advanced molecular characterization of human cortical development, a critical gap exists due to the loss of spatial context during cell dissociation 5,6,7,8 . Here, we utilized multiplexed error-robust fluorescence in situ hybridization (MERFISH) 9 , augmented with deep-learning-based cell segmentation, to examine the molecular, cellular, and cytoarchitectural development of human fetal cortex with spatially resolved single-cell resolution. Our extensive spatial atlas, encompassing 16 million single cells, spans eight cortical areas across four time points in the second and third trimesters. We uncovered an early establishment of the six-layer structure, identifiable in the laminar distribution of excitatory neuronal subtypes by mid-gestation, long before the emergence of cytoarchitectural layers. Notably, while anterior-posterior gradients of neuronal subtypes were generally observed in most cortical areas, a striking exception was the sharp molecular border between primary (V1) and secondary visual cortices (V2) at gestational week 20. Here we discovered an abrupt binary shift in neuronal subtype specification at the earliest stages, challenging the notion that continuous morphogen gradients dictate mid-gestation cortical arealization 6,10 . Moreover, integrating single-nuclei RNA-sequencing and in situ whole transcriptomics revealed an early upregulation of synaptogenesis in V1-specific Layer 4 neurons, suggesting a role of synaptogenesis in this discrete border formation. Collectively, our findings underscore the crucial role of spatial relationships in determining the molecular specification of cortical layers and areas. This work not only provides a valuable resource for the field, but also establishes a spatially resolved single-cell analysis paradigm that paves the way for a comprehensive developmental atlas of the human brain.

Understanding Emergent Complexity from a Single-Molecule Perspective.

Molecules, with structural, scaling, and interaction diversities, are crucial for the emergence of complex behaviors. Interactions are essential prerequisites for complex systems to exhibit emergent properties that surpass the sum of individual component characteristics. Tracing the origin of complex molecular behaviors from interactions is critical to understanding ensemble emergence, and requires insights at the single-molecule level. Electrical signals from single-molecule junctions enable the observation of individual molecular behaviors, as well as intramolecular and intermolecular interactions. This technique provides a foundation for bottom-up explorations of emergent complexity. This Perspective highlights investigations of various interactions via single-molecule junctions, including intramolecular orbital and weak intermolecular interactions and interactions in chemical reactions. It also provides potential directions for future single-molecule junctions in complex system research.

The 3D Revolution in Cancer Discovery.

SUMMARY: The transition from 2D to 3D spatial profiling marks a revolutionary era in cancer research, offering unprecedented potential to enhance cancer diagnosis and treatment. This commentary outlines the experimental and computational advancements and challenges in 3D spatial molecular profiling, underscoring the innovation needed in imaging tools, software, artificial intelligence, and machine learning to overcome implementation hurdles and harness the full potential of 3D analysis in the field.

ADAMTS7 Promotes Smooth Muscle Cell Foam Cell Expansion in Atherosclerosis.

Human genetic studies have repeatedly associated SNPs near the gene ADAMTS7 with atherosclerotic cardiovascular disease. Subsequent investigations in mice demonstrated that ADAMTS7 is proatherogenic, induced in response to vascular injury, and alters smooth muscle cell function. However, the mechanisms governing this function and its relationship to atherosclerosis remain unclear. Here, we report the first conditional Adamts7 transgenic mouse in which the gene can be conditionally overexpressed in smooth muscle cells, mimicking its induction in atherosclerosis. We observed that smooth muscle cell Adamts7 overexpression results in a 3.5-fold increase in peripheral atherosclerosis, coinciding with an expansion of smooth muscle foam cells. RNA sequencing of Adamts7 overexpressed primary smooth muscle cells revealed an upregulation in the expression of lipid uptake genes. Subsequent experiments in primary smooth muscle cells demonstrated that increased Spi1 and Cd36 expression leads to increased smooth muscle cell oxLDL uptake. To uncover ADAMTS7 expression in human disease, we have interrogated the largest scRNA-seq dataset of human carotid atherosclerosis. This analysis discovered that endothelial cells had the highest expression level of ADAMTS7 with lesser expression in smooth muscle cells, fibroblasts, and mast cells. Subsequent conditional knockout studies in smooth muscle cells surprisingly showed no change in atherosclerosis, suggesting redundant expression of this secreted factor in the vessel wall. Finally, mice overexpressing Adamts7 in endothelial cells also exhibit increased atherosclerosis, suggesting that multiple vascular cell types can contribute to ADAMTS7-mediated foam cell expansion. In summary, Adamts7 is expressed by multiple vascular cell types in atherosclerosis, and ADAMTS7 promotes oxLDL uptake in smooth muscle cells, increasing smooth muscle foam cell formation and peripheral atherosclerosis in mice.

An atlas of epithelial cell states and plasticity in lung adenocarcinoma.

Understanding the cellular processes that underlie early lung adenocarcinoma (LUAD) development is needed to devise intervention strategies1. Here we studied 246,102 single epithelial cells from 16 early-stage LUADs and 47 matched normal lung samples. Epithelial cells comprised diverse normal and cancer cell states, and diversity among cancer cells was strongly linked to LUAD-specific oncogenic drivers. KRAS mutant cancer cells showed distinct transcriptional features, reduced differentiation and low levels of aneuploidy. Non-malignant areas surrounding human LUAD samples were enriched with alveolar intermediate cells that displayed elevated KRT8 expression (termed KRT8+ alveolar intermediate cells (KACs) here), reduced differentiation, increased plasticity and driver KRAS mutations. Expression profiles of KACs were enriched in lung precancer cells and in LUAD cells and signified poor survival. In mice exposed to tobacco carcinogen, KACs emerged before lung tumours and persisted for months after cessation of carcinogen exposure. Moreover, they acquired Kras mutations and conveyed sensitivity to targeted KRAS inhibition in KAC-enriched organoids derived from alveolar type 2 (AT2) cells. Last, lineage-labelling of AT2 cells or KRT8+ cells following carcinogen exposure showed that KACs are possible intermediates in AT2-to-tumour cell transformation. This study provides new insights into epithelial cell states at the root of LUAD development, and such states could harbour potential targets for prevention or intervention.

High-Dimensional Single-Cell Multimodal Landscape of Human Carotid Atherosclerosis.

BACKGROUND: Atherosclerotic plaques are complex tissues composed of a heterogeneous mixture of cells. However, our understanding of the comprehensive transcriptional and phenotypic landscape of the cells within these lesions is limited. METHODS: To characterize the landscape of human carotid atherosclerosis in greater detail, we combined cellular indexing of transcriptomes and epitopes by sequencing and single-cell RNA sequencing to classify all cell types within lesions (n=21; 13 symptomatic) to achieve a comprehensive multimodal understanding of the cellular identities of atherosclerosis and their association with clinical pathophysiology. RESULTS: We identified 25 cell populations, each with a unique multiomic signature, including macrophages, T cells, NK (natural killer) cells, mast cells, B cells, plasma cells, neutrophils, dendritic cells, endothelial cells, fibroblasts, and smooth muscle cells (SMCs). Among the macrophages, we identified 2 proinflammatory subsets enriched in IL-1B (interleukin-1B) or C1Q expression, 2 TREM2-positive foam cells (1 expressing inflammatory genes), and subpopulations with a proliferative gene signature and SMC-specific gene signature with fibrotic pathways upregulated. Further characterization revealed various subsets of SMCs and fibroblasts, including SMC-derived foam cells. These foamy SMCs were localized in the deep intima of coronary atherosclerotic lesions. Utilizing cellular indexing of transcriptomes and epitopes by sequencing data, we developed a flow cytometry panel, using cell surface proteins CD29, CD142, and CD90, to isolate SMC-derived cells from lesions. Lastly, we observed reduced proportions of efferocytotic macrophages, classically activated endothelial cells, and contractile and modulated SMC-derived cells, while inflammatory SMCs were enriched in plaques of clinically symptomatic versus asymptomatic patients. CONCLUSIONS: Our multimodal atlas of cell populations within atherosclerosis provides novel insights into the diversity, phenotype, location, isolation, and clinical relevance of the unique cellular composition of human carotid atherosclerosis. These findings facilitate both the mapping of cardiovascular disease susceptibility loci to specific cell types and the identification of novel molecular and cellular therapeutic targets for the treatment of the disease.

Spatially Exploring RNA Biology in Archival Formalin-Fixed Paraffin-Embedded Tissues.

Spatial transcriptomics has emerged as a powerful tool for dissecting spatial cellular heterogeneity but as of today is largely limited to gene expression analysis. Yet, the life of RNA molecules is multifaceted and dynamic, requiring spatial profiling of different RNA species throughout the life cycle to delve into the intricate RNA biology in complex tissues. Human disease-relevant tissues are commonly preserved as formalin-fixed and paraffin-embedded (FFPE) blocks, representing an important resource for human tissue specimens. The capability to spatially explore RNA biology in FFPE tissues holds transformative potential for human biology research and clinical histopathology. Here, we present Patho-DBiT combining in situ polyadenylation and deterministic barcoding for spatial full coverage transcriptome sequencing, tailored for probing the diverse landscape of RNA species even in clinically archived FFPE samples. It permits spatial co-profiling of gene expression and RNA processing, unveiling region-specific splicing isoforms, and high-sensitivity transcriptomic mapping of clinical tumor FFPE tissues stored for five years. Furthermore, genome-wide single nucleotide RNA variants can be captured to distinguish different malignant clones from non-malignant cells in human lymphomas. Patho-DBiT also maps microRNA-mRNA regulatory networks and RNA splicing dynamics, decoding their roles in spatial tumorigenesis trajectory. High resolution Patho-DBiT at the cellular level reveals a spatial neighborhood and traces the spatiotemporal kinetics driving tumor progression. Patho-DBiT stands poised as a valuable platform to unravel rich RNA biology in FFPE tissues to study human tissue biology and aid in clinical pathology evaluation.

Inferring super-resolution tissue architecture by integrating spatial transcriptomics with histology.

Spatial transcriptomics (ST) has demonstrated enormous potential for generating intricate molecular maps of cells within tissues. Here we present iStar, a method based on hierarchical image feature extraction that integrates ST data and high-resolution histology images to predict spatial gene expression with super-resolution. Our method enhances gene expression resolution to near-single-cell levels in ST and enables gene expression prediction in tissue sections where only histology images are available.

Asian Cohort for Alzheimer's Disease (ACAD) pilot study on genetic and non-genetic risk factors for Alzheimer's disease among Asian Americans and Canadians.

INTRODUCTION: Clinical research in Alzheimer's disease (AD) lacks cohort diversity despite being a global health crisis. The Asian Cohort for Alzheimer's Disease (ACAD) was formed to address underrepresentation of Asians in research, and limited understanding of how genetics and non-genetic/lifestyle factors impact this multi-ethnic population. METHODS: The ACAD started fully recruiting in October 2021 with one central coordination site, eight recruitment sites, and two analysis sites. We developed a comprehensive study protocol for outreach and recruitment, an extensive data collection packet, and a centralized data management system, in English, Chinese, Korean, and Vietnamese. RESULTS: ACAD has recruited 606 participants with an additional 900 expressing interest in enrollment since program inception. DISCUSSION: ACAD's traction indicates the feasibility of recruiting Asians for clinical research to enhance understanding of AD risk factors. ACAD will recruit > 5000 participants to identify genetic and non-genetic/lifestyle AD risk factors, establish blood biomarker levels for AD diagnosis, and facilitate clinical trial readiness. HIGHLIGHTS: The Asian Cohort for Alzheimer's Disease (ACAD) promotes awareness of under-investment in clinical research for Asians. We are recruiting Asian Americans and Canadians for novel insights into Alzheimer's disease. We describe culturally appropriate recruitment strategies and data collection protocol. ACAD addresses challenges of recruitment from heterogeneous Asian subcommunities. We aim to implement a successful recruitment program that enrolls across three Asian subcommunities.

Mirrorless MEMS imaging: a nonlinear vibrational approach utilizing aerosol-jetted PZT-actuated fiber MEMS scanner for microscale illumination.

This study introduces a novel image capture and lighting techniques using a cutting-edge hybrid MEMS scanner system designed for compact microscopic imaging. The scanner comprises a tapered optical fiber waveguide and innovative aerosol-jet printed PZT (lead zirconate titanate) bimorph push-pull actuators on a stainless-steel substrate, effectively addressing issues that are commonly associated with PZT on silicon substrates such as fracture and layer separation. By leveraging nonlinear vibration, the scanner achieves a spiral scan pattern from a single signal input, in addition to the expected two-dimensional scanning and target illumination from two phase-shifted inputs. This capability is further enhanced by a novel process to taper the optical fiber, which reduces illumination scattering and tunes the fiber to the resonant frequencies of the scanner. The precisely tapered tip enables large fields of view while maintaining independent 2-axis scanning through one-degree-of-freedom actuation. Experimental validation showcases the successful generation of a spiral scan pattern with a 60 µm diameter scan area and a 10 Hz frame rate, effectively reconstructing scanned images of 5 µm lines, cross patterns (15 µm in length with a 5 µm gap), and structures of a Psychodidae wing.

Patterns of Gene Expression, Splicing, and Allele-Specific Expression Vary among Macular Tissues and Clinical Stages of Age-Related Macular Degeneration.

Age-related macular degeneration (AMD) is a leading cause of blindness, and elucidating its underlying disease mechanisms is vital to the development of appropriate therapeutics. We identified differentially expressed genes (DEGs) and differentially spliced genes (DSGs) across the clinical stages of AMD in disease-affected tissue, the macular retina pigment epithelium (RPE)/choroid and the macular neural retina within the same eye. We utilized 27 deeply phenotyped donor eyes (recovered within a 6 h postmortem interval time) from Caucasian donors (60-94 years) using a standardized published protocol. Significant findings were then validated in an independent set of well-characterized donor eyes (n = 85). There was limited overlap between DEGs and DSGs, suggesting distinct mechanisms at play in AMD pathophysiology. A greater number of previously reported AMD loci overlapped with DSGs compared to DEGs between disease states, and no DEG overlap with previously reported loci was found in the macular retina between disease states. Additionally, we explored allele-specific expression (ASE) in coding regions of previously reported AMD risk loci, uncovering a significant imbalance in C3 rs2230199 and CFH rs1061170 in the macular RPE/choroid for normal eyes and intermediate AMD (iAMD), and for CFH rs1061147 in the macular RPE/choroid for normal eyes and iAMD, and separately neovascular AMD (NEO). Only significant DEGs/DSGs from the macular RPE/choroid were found to overlap between disease states. STAT1, validated between the iAMD vs. normal comparison, and AGTPBP1, BBS5, CERKL, FGFBP2, KIFC3, RORα, and ZNF292, validated between the NEO vs. normal comparison, revealed an intricate regulatory network with transcription factors and miRNAs identifying potential upstream and downstream regulators. Findings regarding the complement genes C3 and CFH suggest that coding variants at these loci may influence AMD development via an imbalance of gene expression in a tissue-specific manner. Our study provides crucial insights into the multifaceted genomic underpinnings of AMD (i.e., tissue-specific gene expression changes, potential splice variation, and allelic imbalance), which may open new avenues for AMD diagnostics and therapies specific to iAMD and NEO.

Pueraria thomsonii Radix Water Extract Alleviate Type 2 Diabetes Mellitus in db/db Mice through Comprehensive Regulation of Metabolism and Gut Microbiota.

Type 2 diabetes mellitus (T2DM) is an increasingly prevalent and serious health problem. Its onset is typically associated with metabolic disorders and disturbances in the gut microbiota. Previous studies have reported the anti-T2DM effects of Pueraria thomsonii Radix as a functional food. However, the mechanism of action is still unknown. In this study, rich polyphenols and polysaccharides from Pueraria Thomsonii Radix water extract (PTR) were quantitatively determined, and then the effects of PTR on db/db mice were evaluated by pharmacology, metabolomics, and 16S rRNA gene sequencing. The results showed that PTR could alleviate pancreatic tissue damage, significantly decrease fasting blood glucose (FBG), fasting serum insulin (FINS), homeostasis model assessment insulin resistance (HOMA-IR), urinary glucose (UGLU), and urinary albumin/creatinine ratio (UACR). Metabolomics showed that the Diabetes Control (DM) group produced 109 differential metabolites, of which 74 could be regulated by PTR. In addition, 16S rRNA sequencing was performed in fecal samples and results showed that PTR could reduce the Firmicutes/Bacteroidetes(F/B) ratio and regulate three beneficial bacteria and one harmful bacterium. In conclusion, the results showed that PTR could ameliorate the T2DM symptoms, metabolic disorder, and gut microbiota imbalance of db/db mice, and it was superior to metformin in some aspects. We suggested for the first time that γ-aminobutyric acid (GABA) may be involved in the regulation of the microbiota-gut-brain axis (MGB) and thus affects the metabolic disorders associated with T2DM. This study will provide a scientific basis for the development of functional food with PTR.

Network Enrichment Significance Testing in Brain-Phenotype Association Studies.

Functional networks often guide our interpretation of spatial maps of brain-phenotype associations. However, methods for assessing enrichment of associations within networks of interest have varied in terms of both scientific rigor and underlying assumptions. While some approaches have relied on subjective interpretations, others have made unrealistic assumptions about the spatial structure of imaging data, leading to inflated false positive rates. We seek to address this gap in existing methodology by borrowing insight from a method widely used in genomics research for testing enrichment of associations between a set of genes and a phenotype of interest. We propose Network Enrichment Significance Testing (NEST), a flexible framework for testing the specificity of brain-phenotype associations to functional networks or other sub-regions of the brain. We apply NEST to study phenotype associations with structural and functional brain imaging data from a large-scale neurodevelopmental cohort study.

Surgical Outcome of Proximal Isolated Subclavian Artery Aneurysms: A Single-Center Retrospective Observational Study.

OBJECTIVE: The objective of this study was to introduce our institutional experience of treatment strategies (cervical subclavian artery reconstruction, thoracotomy subclavian artery reconstruction and endovascular treatment) for proximal isolated subclavian artery aneurysms (PISAAs). METHODS: we retrospectively analyzed 15 consecutive patients with PISAAs treated by different treatment strategies (cervical reconstruction, thoracotomy reconstruction and endovascular treatment) in our institution from May 2016 to May 2022. Baseline data, surgery-related data, postoperative information and long-term follow-up were assessed. RESULTS: A total of 17 PISAAs in 15 consecutive patients were treated in our institution. The success rates of subclavian artery reconstruction in the cervical reconstruction, the thoracotomy reconstruction and the endovascular treatment were 100%, 100 and 83.33%, respectively. About the involved vertebral artery, the reconstruction rates in the cervical reconstruction, the thoracotomy reconstruction, and the endovascular treatment were 80%, 75%, and 0, respectively. The intraoperative blood loss in the thoracotomy reconstruction was significantly higher than that in the cervical reconstruction and the endovascular treatment (p<0.05). The total operation time of the thoracotomy reconstruction was significantly longer than that of the cervical reconstruction and the endovascular treatment (p<0.05). In terms of postoperative ventilator use time, total postoperative drainage fluid, total postoperative drainage time, and ICU duration, both the thoracotomy reconstruction and the cervical reconstruction were significantly more than the endovascular treatment (p<0.05). During the follow-up, one patient in the endovascular treatment underwent re-intervention 22 months after surgery due to in-stent occlusion. CONCLUSIONS: For patients with PISAAs, different treatment strategies are recommended depending on the size of the aneurysms and whether the involved vertebral arteries require reconstruction. CLINICAL IMPACT: This article is the largest study on the treatment strategies of PISAAs. By comparing the prognosis and complications of endovascular treatment with those of open surgery, it provides a certain reference basis for the choice of treatment for patients with PISAAs. For patients with aneurysms' diameter of >50 mm, the thoracotomy subclavian artery reconstruction is recommended; for patients with aneurysms' diameter of <30 mm requiring reconstruction of the involved vertebral arteries, the cervical subclavian artery reconstruction is recommended; for patients with aneurysms' diameter of <30 mm not requiring reconstruction of the involved vertebral arteries, the endovascular treatment is recommended.

Benchmarking algorithms for joint integration of unpaired and paired single-cell RNA-seq and ATAC-seq data.

BACKGROUND: Single-cell RNA-sequencing (scRNA-seq) measures gene expression in single cells, while single-nucleus ATAC-sequencing (snATAC-seq) quantifies chromatin accessibility in single nuclei. These two data types provide complementary information for deciphering cell types and states. However, when analyzed individually, they sometimes produce conflicting results regarding cell type/state assignment. The power is compromised since the two modalities reflect the same underlying biology. Recently, it has become possible to measure both gene expression and chromatin accessibility from the same nucleus. Such paired data enable the direct modeling of the relationships between the two modalities. Given the availability of the vast amount of single-modality data, it is desirable to integrate the paired and unpaired single-modality datasets to gain a comprehensive view of the cellular complexity. RESULTS: We benchmark nine existing single-cell multi-omic data integration methods. Specifically, we evaluate to what extent the multiome data provide additional guidance for analyzing the existing single-modality data, and whether these methods uncover peak-gene associations from single-modality data. Our results indicate that multiome data are helpful for annotating single-modality data. However, we emphasize that the availability of an adequate number of nuclei in the multiome dataset is crucial for achieving accurate cell type annotation. Insufficient representation of nuclei may compromise the reliability of the annotations. Additionally, when generating a multiome dataset, the number of cells is more important than sequencing depth for cell type annotation. CONCLUSIONS: Seurat v4 is the best currently available platform for integrating scRNA-seq, snATAC-seq, and multiome data even in the presence of complex batch effects.