Solid-state nanopore sequencing, a key third-generation sequencing technology, offers considerable potential for genomics and diagnostics due to its long read lengths, real-time detection, and amplification-free operation. The technology identifies DNA sequences by measuring characteristic changes in ionic current as single-stranded DNA translocates through a nanoscale pore. However, its practical development faces challenges including limited spatiotemporal resolution, pore clogging from nonspecific adsorption, and significant electrical noise. This review systematically examines strategies developed to address these limitations. We discuss the use of ultrathin two-dimensional materials such as graphene and molybdenum disulfide to improve spatial resolution, and methods to modulate DNA translocation through optimized solution conditions, pore geometry, surface charge engineering, and bio-solid hybrid pore designs. Furthermore, we detail noise suppression strategies targeting key sources like thermal noise, 1/f noise, and dielectric noise. These approaches encompass careful material selection, surface coatings, innovations in chip and amplifier design, and machine learning–based signal processing. The review also outlines surface functionalization techniques that reduce clogging and enhance analytical specificity. While challenges remain, continued convergence of materials science, nanofabrication, and data science is advancing solid-state nanopore technology toward reliable, high-precision sequencing platforms, promising to significantly impact personalized medicine and biological research.

The liver coordinately maintains cholesterol, triglyceride, and glucose homeostasis by integrating the synthesis, storage, utilization, and inter-conversion of these metabolic programs, and their dysregulation contributes to metabolic-associated steatotic liver disease (MASLD), hepatocellular carcinoma (HCC), type 2 diabetes mellitus (T2DM), and gestational diabetes mellitus (GDM). Long non-coding RNAs (lncRNAs), which are not translated into proteins, regulate gene expression through interactions with DNA, RNA, and proteins at transcriptional, post-transcriptional, and epigenetic levels, and have emerged as central determinants of hepatic metabolic balance. This review systematically summarizes how lncRNAs govern cholesterol biosynthesis and efflux, triglyceride synthesis and lipolysis, glycogen turnover, gluconeogenesis, and glycolysis in hepatocytes. Unlike pathway-by-pathway descriptions, we highlight that these programs are coupled through shared signaling networks, including PI3K/AKT/mechanistic target of rapamycin complex 1 (mTORC1), 5′-AMP-activated protein kinase (AMPK), SREBP, PPAR, and FoxO1, and that pleiotropic lncRNAs coordinate lipid and glucose outputs rather than controlling a single isolated process. We further examine how lncRNA dysregulation drives MASLD, HCC, T2DM, and GDM, and evaluate their potential as diagnostic biomarkers and therapeutic targets. Finally, we outline current limitations, including incomplete molecular characterization, low cross-species conservation, heterogeneous experimental validation, and unresolved delivery challenges, which must be addressed before lncRNA-based strategies reach clinical application.