Constructing and exploring neuroimaging projects: a survey from clinical practice to scientific research.

Over the past decades, numerous large-scale neuroimaging projects that involved the collection and release of multimodal data have been conducted globally. Distinguished initiatives such as the Human Connectome Project, UK Biobank, and Alzheimer's Disease Neuroimaging Initiative, among others, stand as remarkable international collaborations that have significantly advanced our understanding of the brain. With the advancement of big data technology, changes in healthcare models, and continuous development in biomedical research, various types of large-scale projects are being established and promoted worldwide.

Mime: A flexible machine-learning framework to construct and visualize models for clinical characteristics prediction and feature selection.

The widespread use of high-throughput sequencing technologies has revolutionized the understanding of biology and cancer heterogeneity. Recently, several machine-learning models based on transcriptional data have been developed to accurately predict patients' outcome and clinical response. However, an open-source R package covering state-of-the-art machine-learning algorithms for user-friendly access has yet to be developed.

The association between hematologic traits and aneurysm-related subarachnoid hemorrhage: a two-sample mendelian randomization study.

Several hematologic traits have been suggested to potentially contribute to the formation and rupture of intracranial aneurysms (IA). The purpose of this study is to explore the causal association between hematologic traits and the risk of IA. To explore the causal association between hematologic traits and the risk of IA, we employed two-sample Mendelian randomization (MR) analysis.

Pan-cancer evaluation of regulated cell death to predict overall survival and immune checkpoint inhibitor response.

Regulated cell death (RCD) plays a pivotal role in various biological processes, including development, tissue homeostasis, and immune response. However, a comprehensive assessment of RCD status and its associated features at the pan-cancer level remains unexplored. Furthermore, despite significant advancements in immune checkpoint inhibitors (ICI), only a fraction of cancer patients currently benefit from treatments.

Machine learning-based investigation of regulated cell death for predicting prognosis and immunotherapy response in glioma patients.

Glioblastoma is a highly aggressive and malignant type of brain cancer that originates from glial cells in the brain, with a median survival time of 15 months and a 5-year survival rate of less than 5%. Regulated cell death (RCD) is the autonomous and orderly cell death under genetic control, controlled by precise signaling pathways and molecularly defined effector mechanisms, modulated by pharmacological or genetic interventions, and plays a key role in maintaining homeostasis of the internal environment. The comprehensive and systemic landscape of the RCD in glioma is not fully investigated and explored.

Mood swings are causally associated with intracranial aneurysm subarachnoid hemorrhage: A Mendelian randomization study.

Background: Mood swings have been observed in patients with intracranial aneurysm (IA), but it is still unknown whether mood swings can affect IA.

Aim: To explore the causal association between mood swings or experiencing mood swings and IA through a two-sample Mendelian randomization (MR) study.

Methods: Summary-level statistics of mood swings, experiencing mood swings, IA, aneurysm-associated subarachnoid hemorrhage (aSAH), and non-ruptured IA (uIA) were collected from the genome-wide association study.

Transcription factor ZBTB42 is a novel prognostic factor associated with immune cell infiltration in glioma.

ZBTB42 is a transcription factor that belongs to the ZBTB transcript factor family and plays an important role in skeletal muscle development. Dysregulation of ZBTB42 expression can lead to a variety of diseases. However, the function of ZBTB42 in glioma development has not been studied by now.