ChatRadio-Valuer: A Chat Large Language Model for Generalizable Radiology Impression Generation on Multi-institution and Multi-system Data.

Achieving clinical level performance and widespread deployment for generating radiology impressions encounters a giant challenge for conventional artificial intelligence models tailored to specific diseases and organs. Concurrent with the increasing accessibility of radiology reports and advancements in modern general AI techniques, the emergence and potential of deployable radiology AI exploration have been bolstered. Here, we present ChatRadio-Valuer, the first general radiology diagnosis large language model for localized deployment within hospitals and being close to clinical use for multi-institution and multi-system diseases.

Magnetic resonance imaging of cruciate ligament disorders: current updates.

While conventional structural magnetic resonance imaging (MRI) can detect cruciate ligament anatomy and injuries, it has inherent limitations. Recently, novel MRI technologies such as quantitative MRI and artificial intelligence (AI) have emerged to mitigate these shortcomings, providing critical quantitative insights beyond gross morphological imaging and poised to expand current knowledge in assessing cruciate ligament injuries and to facilitate clinical decision making. Quantitative MRI serves as a noninvasive histological and quantification tool, which significantly improves the evaluation of degeneration and repair processes.

Associations among neuropsychological performance, brain structural alterations, and glymphatic function in patients with minimal hepatic encephalopathy.

Brain anatomical alterations in gray matter(GM), white matter(WM), and glymphatic system(GS) in patients with hepatitis B cirrhosis(HBC) with minimal hepatic encephalopathy(MHE) remain to be clarified. A total of 33 healthy controls and 37 patients with treatment-native primary HBC (further subdivided into HBC in MHE group[MHE] and HBC in non-MHE group[NMHE]) participated in neuroimaging study with three-dimensional T1 and a half q-space Cartesian grid diffusion model. Group differences in regional GM volume(GMV) were assessed using voxel-based morphometry(VBM) analysis.

Unveiling causal relationships between tobacco use phenotypes and neuroimaging: Insights from bidirectional Mendelian randomization and bibliometric analysis.

Smoking is considered the most common addictive behavior worldwid. However, it is not systematically investigated whether there are bidirectional causal associations between tobacco use and neuroimaging, which might provide potential neural biomarkers or therapeutic neuro-targets for tobacco abuse or rehabilitation. In this study, using Mendelian randomization (MR), we explored both forward and reverse causal relationships between 4 tobacco use phenotypes (including Cigarettes per day, Smoking initiation, Age of initiation and Smoking cessation) and 209 neuroimaging features involving brain function and structure.

Distinct insula subdivisions of resting-state functional connectivity in individuals with opioid and methamphetamine use disorders.

Different addictive drugs can impact the function and morphology of the brain in diverse ways. The insula cortex, an important brain node involved in craving and reward neural circuits in individuals with substance use disorders (including damage to the insula cortex), has been reported to reduce addictive behaviors. However, less is known about whether there is a functional difference between individuals with opioid and methamphetamine use disorders, especially regarding the function of the insula cortex.

The causal effects of gut microbiota on quantitative susceptibility mapping (QSM) and T2* imaging-derived phenotypes: insights from a Mendelian randomization study.

Background: Gut microbiota are associated with brain imaging-derived phenotypes (IDPs); however, the specific causal relationship between the gut microbiota and brain iron-related IDPs remains unclear. Thus, we sought to analyze the potential causal effects of gut microbiota on brain iron-related IDPs using Mendelian randomization (MR).

Methods: We obtained the data of 196 gut microbiota from a genome-wide association study (GWAS) from the MiBioGen database, as well as the data of 18 quantitative susceptibility mapping (QSM) IDPs and 10 T2* IDPs from the United Kingdom Biobank (UKB).

Hereditary and cortical morphological biomarker of sensitivity to reward in short-term withdrawal methamphetamine abusers.

Higher sensitivity to reward (SR) and weaker sensitivity to punishment (SP) construct the fundamental craving characteristics of methamphetamine abuse. However, few studies have appraised relationships between SR/SP (SR or SP) and cortical morphological alterations in methamphetamine abusers and whether hereditary factors take effects on SR/SP is unclear. Based on surface-based morphometric analysis, cortical discrepancy was investigated between 38 methamphetamine abusers and 37 healthy controls.

Altered orientation dispersion index of white matter in individuals with insomnia during the COVID-19 pandemic: A study combining neuroimaging technique and Mendelian randomization.

Study Objectives: Coronavirus disease 2019 (COVID-19) can lead to insomnia. However, associations between COVID-19-caused insomnia and white matter (WM) changes are unclear.

Methods: All subjects had ever been infected with COVID-19.

Connectome-based predictive modelling can predict follow-up craving after abstinence in individuals with opioid use disorders.

Background: Individual differences have been detected in individuals with opioid use disorders (OUD) in rehabilitation following protracted abstinence. Recent studies suggested that prediction models were effective for individual-level prognosis based on neuroimage data in substance use disorders (SUD).

Aims: This prospective cohort study aimed to assess neuroimaging biomarkers for individual response to protracted abstinence in opioid users using connectome-based predictive modelling (CPM).

Identifying Minimal Hepatic Encephalopathy: A New Perspective from Magnetic Resonance Imaging.

Type C hepatic encephalopathy (HE) is a condition characterized by brain dysfunction caused by liver insufficiency and/or portal-systemic blood shunting, which manifests as a broad spectrum of neurological or psychiatric abnormalities, ranging from minimal HE (MHE), detectable only by neuropsychological or neurophysiological assessment, to coma. Though MHE is the subclinical phase of HE, it is highly prevalent in cirrhotic patients and strongly associated with poor quality of life, high risk of overt HE, and mortality. It is, therefore, critical to identify MHE at the earliest and timely intervene, thereby minimizing the subsequent complications and costs.

Gray Matter Thickness and Subcortical Nuclear Volume in Men After SARS-CoV-2 Omicron Infection.

Importance: The clinical manifestations and effects on the brain of the SARS-CoV-2 Omicron variant in the acute postinfection phase remain unclear.

Objective: To investigate the pathophysiological mechanisms underlying clinical symptoms and changes to gray matter and subcortical nuclei among male patients after Omicron infection and to provide an imaging basis for early detection and intervention.

Design, Setting, And Participants: In this cohort study, a total of 207 men underwent health screening magnetic resonance imaging scans between August 28 and September 18, 2022; among them, 98 provided complete imaging and neuropsychiatric data.

Diagnostic efficiency among Eu-/C-/ACR-TIRADS and S-Detect for thyroid nodules: a systematic review and network meta-analysis.

Background: The performance in evaluating thyroid nodules on ultrasound varies across different risk stratification systems, leading to inconsistency and uncertainty regarding diagnostic sensitivity, specificity, and accuracy.

Objective: Comparing diagnostic performance of detecting thyroid cancer among distinct ultrasound risk stratification systems proposed in the last five years.

Evidence Acquisition: Systematic search was conducted on PubMed, EMBASE, and Web of Science databases to find relevant research up to December 8, 2022, whose study contents contained elucidation of diagnostic performance of any one of the above ultrasound risk stratification systems (European Thyroid Imaging Reporting and Data System[Eu-TIRADS]; American College of Radiology TIRADS [ACR TIRADS]; Chinese version of TIRADS [C-TIRADS]; Computer-aided diagnosis system based on deep learning [S-Detect]).

Identification of NOX4 as a New Biomarker in Hepatocellular Carcinoma and Its Effect on Sorafenib Therapy.

To improve the survival of patients with hepatocellular carcinoma (HCC), new biomarkers and therapeutic targets are urgently needed. In this study, the GEO and TCGA dataset were used to explore the differential co-expressed genes and their prognostic correlation between HCC and normal samples. The mRNA levels of these genes were validated by qRT-PCR in 20 paired fresh HCC samples.

Causal Associations between Functional/Structural Connectivity and Stroke: A Bidirectional Mendelian Randomization Study.

Disruption of brain resting-state networks (RSNs) is known to be related to stroke exposure, but determining causality can be difficult in epidemiological studies. We used data on genetic variants associated with the levels of functional (FC) and structural connectivity (SC) within 7 RSNs identified from a genome-wide association study (GWAS) meta-analysis among 24,336 European ancestries. The data for stroke and its subtypes were obtained from the MEGASTROKE consortium, including up to 520,000 participants.

The genetic susceptibility analysis of TAAR1 rs8192620 to methamphetamine and heroin abuse and its role in impulsivity.

Abnormal genetic polymorphism of trace amine-associated receptor 1 (TAAR1) rs8192620 site has been confirmed to induce methamphetamine (MA) use and drug craving. However, the genetic susceptibility difference between MA addicts and heroin addicts is unknown. This study evaluated genetic heterogeneity of TAAR1 rs8192620 between MA and heroin addicts and elucidated whether rs8192620 genotypes associated with discrepancy in emotional impulsivity, which would help to instruct individualized treatment in addiction via acting on TAAR1 and evaluate risk of varied drug addiction.

Machine learning with neuroimaging biomarkers: Application in the diagnosis and prediction of drug addiction.

Drug abuse is a serious problem worldwide. Owing to intermittent intake of certain substances and the early inconspicuous clinical symptoms, this brings huge challenges for timely diagnosing addiction status and preventing substance use disorders (SUDs). As a non-invasive technique, neuroimaging can capture neurobiological signatures of abnormality in multiple brain regions caused by drug consumption in each clinical stage, like parenchymal morphology alteration as well as aberrant functional activity and connectivity of cerebral areas, making it realizable to diagnosis, prediction and even preemptive therapy of addiction.

Posttranslational Modifications of Smurfs: Emerging Regulation in Cancer.

Smad ubiquitination regulatory factors (Smurfs) belong to the Nedd4 subfamily of HECT-type E3 ubiquitin ligases. Under normal situations, Smurfs are exactly managed by upstream regulators, and thereby strictly control tumor biological processes, including cell growth, differentiation, apoptosis, polarization, epithelial mesenchymal transition (EMT), and invasion. Disruption of Smurf activity has been implicated in cancer progression, and Smurf activity is controlled by a series of posttranslational modifications (PTMs), including phosphorylation, ubiquitination, neddylation, sumoylation, and methylation.

Unraveling the molecular mechanisms between inflammation and tumor angiogenesis.

Inflammatory mediators in tumor microenvironment influence cancer occurrence, growth and metastasis through complex signaling networks. Excessive inflammation is closely associated with elevated cancer risk and mortality, in part through inflammation-induced angiogenesis. Mechanistically, multiple tumor-associated inflammatory cells increase the release and accumulation of various inflammatory products in cancerous sites.

The Clearance of High-Risk Human Papillomavirus is Sooner After Thin Loop Electrosurgical Excision Procedure (t-LEEP).

: To investigate high-risk human papillomavirus (HPV) infection clearance following thin loop electrosurgical excision procedure (t-LEEP) among patients with cervical benign lesion. : This retrospective study analyzed clinical data from patients with cervical benign lesion and HPV infection, who had undergone t-LEEP (T-Group), compared with patients with HPV infection undergone no treatment (NT-Group). Both groups attended regular follow-up between January 2008 and January 2012.

AKIP1 promotes angiogenesis and tumor growth by upregulating CXC-chemokines in cervical cancer cells.

Upregulation of A-kinase-interacting protein 1 (AKIP1) has been observed in breast and esophageal cancers, indicating that AKIP1 may be a potent oncogenic protein. However, the role of AKIP1 in cervical cancer still remains unknown. This study aimed to explore the role of AKIP1 in cervical cancer and to investigate the underlying mechanism of AKIP1 in tumor growth.

Identification of a microRNA signature associated with survivability in cervical squamous cell carcinoma.

Background: The aim of this study is to find the potential miRNA expression signature capable of predicting survival time for cervical squamous cell carcinoma (CSCC) patients.

Methods: The expression of 332 miRNAs was measured in 131 (Training cohort) and 130 (Validation cohort) patients with CSCC in the Cancer Genome Atlas (TCGA) data portal. The miRNA expression signature was identified by Cox Proportion Hazard regression model to the Training data set, and subsequently validated in an independent Validation set.

Molecular mechanisms underlying endometriosis pathogenesis revealed by bioinformatics analysis of microarray data.

Objective: To identify differentially expressed genes (DEGs) in endometriosis and further analyze molecular mechanisms implicated in disease pathogenesis.

Materials And Methods: Gene expression data (ID: GSE7846) of human endometrial endothelial cells (HEECs) collected from eutopic endometria tissue of patients with and without endometriosis were downloaded from Gene Expression Omnibus. DEGs were screened using Limma package, followed by enrichment analysis using clusterProfiler package in R.