Unfolding the genotype-to-phenotype black box of cardiovascular diseases through cross-scale modeling

Clinicopathologic and Genomic Characteristics of Minute Pulmonary Meningothelial-like Nodules

Minute pulmonary meningothelial-like nodules (MPMNs) are benign lung lesions with histologic characteristics similar to meningeal epithelium. MPMNs often lead to misdiagnosis for their similar radiologic characteristics to malignant nodules. The pathogenesis of MPMNs remains unclear, and this research primarily focused on mutations in a limited number of genes, lacking a comprehensive analysis of their mutational landscape. We collected 134 MPMNs from 88 patients with pathologic examinations at Peking Union Medical College Hospital in the past 5 years. We performed whole-exome sequencing on 12 MPMNs and 7 adenocarcinoma lesions from 6 patients. In our PUMCH-MPMN cohort, we provided clinical, pathologic, radiologic, and follow-up characteristics of patients with MPMNs. Our study demonstrated the pathologic diagnostic value of 3 classic MPMN diagnostic markers (epithelial membrane antigen, progesterone receptor, and vimentin) and the novel marker somatostatin receptor 2. It also suggested the preoperative differential diagnostic value of positron emission tomography/computed tomography. We also classified MPMNs into 4 types based on different discovery methods and verified the diagnostic value of traditional and novel immunohistochemical markers. We performed whole-exome sequencing and revealed that MPMNs harbor mutations enriched in cell cycle and cytoskeleton assembly pathways. On the other hand, classical meningioma-related mutations, such as NF2 mutations, were not detected. These findings provide new evidence for the hypothesis that MPMNs arise from reactive proliferation rather than share a common origin with meningiomas, contributing to a better understanding of MPMNs among clinicians and pathologists, reducing misdiagnosis, and improving patient care.

scTML: a pan-cancer single-cell landscape of multiple mutation types

Investigating mutations, including single nucleotide variations (SNVs), gene fusions, alternative splicing and copy number variations (CNVs), is fundamental to cancer study. Recent computational methods and biological research have demonstrated the reliability and biological significance of detecting mutations from single-cell transcriptomic data. However, there is a lack of a single-cell-level database containing comprehensive mutation information in all types of cancer. Establishing a single-cell mutation landscape from the huge emerging single-cell transcriptomic data can provide a critical resource for elucidating the mechanisms of tumorigenesis and evolution. Here, we developed scTML (http://sctml.xglab.tech/), the first database offering a pan-cancer single-cell landscape of multiple mutation types. It includes SNVs, insertions/deletions, gene fusions, alternative splicing and CNVs, along with gene expression, cell states and other phenotype information. The data are from 74 datasets with 2 582 633 cells, including 35 full-length (Smart-seq2) transcriptomic single-cell datasets (all publicly available data with raw sequencing files), 23 datasets from 10X technology and 16 spatial transcriptomic datasets. scTML enables users to interactively explore multiple mutation landscapes across tumors or cell types, analyze single-cell-level mutation-phenotype associations and detect cell subclusters of interest. scTML is an important resource that will significantly advance deciphering intra-tumor and inter-tumor heterogeneity, and how mutations shape cell phenotypes.

Cutting-edge microneedle innovations: Transforming the landscape of cardiovascular and metabolic disease management

Cardiovascular diseases (CVDs) and metabolic disorders (MDs) have surfaced as formidable challenges to global health, significantly imperiling human well-being. Recently, microneedles (MNs) have garnered substantial interest within the realms of CVD and MD research. Offering a departure from conventional diagnostic and therapeutic methodologies, MNs present a non-invasive, safe, and user-friendly modality for both monitoring and treatment, thereby marking substantial strides and attaining pivotal achievements in this avant-garde domain, while also unfurling promising avenues for future inquiry. This thorough review encapsulates the latest developments in employing MNs for both the surveillance and management of CVDs and MDs. Initially, it succinctly outlines the foundational principles and approaches of MNs in disease surveillance and therapy. Subsequently, it delves into the pioneering utilizations of MNs in the surveillance and management of CVDs and MDs. Ultimately, this discourse synthesizes and concludes the primary findings of this investigation, additionally prognosticating on the trajectory of MN technology.