(Gesneriaceae), a new species in the karst landforms of Guizhou Province, China.

X.X.Bai & F.

Single-cell RNA-sequencing and spatial transcriptomic analysis reveal a distinct population of APOE cells yielding pathological lymph node metastasis in papillary thyroid cancer.

Background: Thyroid cancer is one of the most common endocrine tumors worldwide, especially among women and the metastatic mechanism of papillary thyroid carcinoma remains poorly understood.

Methods: Thyroid cancer tissue samples were obtained for single-cell RNA-sequencing and spatial transcriptomics, aiming to intratumoral and antimetastatic heterogeneity of advanced PTC. The functions of APOE in PTC cell proliferation and invasion were confirmed through in vivo and in vitro assays.

Effects of population aging on quality of life and disease burden: a population-based study.

Background: As population aging intensifies, it becomes increasingly important to elucidate the casual relationship between aging and changes in population health. Therefore, our study proposed to develop a systematic attribution framework to comprehensively evaluate the health impacts of population aging.

Methods: We used health-adjusted life expectancy (HALE) to measure quality of life and disability-adjusted life years (DALY) to quantify the burden of disease for the population of Guangzhou.

Novel full-thickness biomimetic corneal model for studying pathogenesis and treatment of diabetic keratopathy.

Diabetic keratopathy (DK), a significant complication of diabetes, often leads to corneal damage and vision impairment. Effective models are essential for studying DK pathogenesis and evaluating potential therapeutic interventions. This study developed a novel biomimetic full-thickness corneal model for the first time, incorporating corneal epithelial cells, stromal cells, endothelial cells, and nerves to simulate DK conditions .

Screening of obstructive sleep apnea and diabetes mellitus -related biomarkers based on integrated bioinformatics analysis and machine learning.

Background: The pathophysiology of obstructive sleep apnea (OSA) and diabetes mellitus (DM) is still unknown, despite clinical reports linking the two conditions. After investigating potential roles for DM-related genes in the pathophysiology of OSA, our goal is to investigate the molecular significance of the condition. Machine learning is a useful approach to understanding complex gene expression data to find biomarkers for the diagnosis of OSA.