A Lightweight Deep Learning Framework for Automatic MRI Data Sorting and Artifacts Detection.

The purpose of this study is to develop a lightweight and easily deployable deep learning system for fully automated content-based brain MRI sorting and artifacts detection. 22092 MRI volumes from 4076 patients between 2017 and 2021 were involved in this retrospective study. The dataset mainly contains 4 common contrast (T1-weighted (T1w), contrast-enhanced T1-weighted (T1c), T2-weighted (T2w), fluid-attenuated inversion recovery (FLAIR)) in three perspectives (axial, coronal, and sagittal), and magnetic resonance angiography (MRA), as well as three typical artifacts (motion, aliasing, and metal artifacts).

A mitochondrial EglN1-AMPKα axis drives breast cancer progression by enhancing metabolic adaptation to hypoxic stress.

Mitochondria play essential roles in cancer cell adaptation to hypoxia, but the underlying mechanisms remain elusive. Through mitochondrial proteomic profiling, we here find that the prolyl hydroxylase EglN1 (PHD2) accumulates on mitochondria under hypoxia. EglN1 substrate-binding region in the β2β3 loop is responsible for its mitochondrial translocation and contributes to breast tumor growth.

FDXR drives primary and endocrine-resistant tumor cell growth in ER+ breast cancer via CPT1A-mediated fatty acid oxidation.

Background: The majority of breast cancers (BCs) expressing estrogen receptor (ER) have shown endocrine resistance. Our previous study demonstrated that ferredoxin reductase (FDXR) promoted mitochondrial function and ER+ breast tumorigenesis. But the underlying mechanism is not clear.

Unsupervised anomaly detection in brain MRI: Learning abstract distribution from massive healthy brains.

Purpose: To develop a general unsupervised anomaly detection method based only on MR images of normal brains to automatically detect various brain abnormalities.

Materials And Methods: In this study, a novel method based on three-dimensional deep autoencoder network is proposed to automatically detect and segment various brain abnormalities without being trained on any abnormal samples. A total of 578 normal T2w MR volumes without obvious abnormalities were used for model training and validation.

Mechanical and medical imaging properties of 3D-printed materials as tissue equivalent materials.

Three materials of polylactic acid (PLA), polyamide 12 (PA12), and light curing resin (LCR) were used to construct phantom using 3D printing technology. The mechanical and medical imaging properties of the three materials, such as elastic modulus, density, effective atomic number, X-ray attenuation coefficient, computed tomography (CT) number, and acoustic properties, were investigated. The results showed that the elastic modulus for PLA was 1.

Macrotrabecular-massive hepatocellular carcinoma: imaging identification and prediction based on gadoxetic acid-enhanced magnetic resonance imaging.

Objectives: To identify image features of macrotrabecular-massive (MTM) hepatocellular carcinoma (HCC) and to determine its role in predicting MTM-HCC.

Methods: Patients who underwent preoperative gadoxetic acid-enhanced MRI and with surgery proven HCC were retrospectively included. Imaging features were assessed according to Liver Imaging Reporting and Data System.

FGF21 Enhances Therapeutic Efficacy and Reduces Side Effects of Dexamethasone in Treatment of Rheumatoid Arthritis.

In order to investigate efficacy of FGF21 combine dexamethasone (Dex) on rheumatoid arthritis (RA) meanwhile reduce side effects of dexamethasone. We used combination therapy (Dex 15 mg/kg + FGF21 0.25 mg/kg, Dex 15 mg/kg + FGF21 0.

Liver fibrosis staging with diffusion-weighted imaging: a systematic review and meta-analysis.

Purpose: A meta-analysis was performed to assess the diagnostic performance of diffusion-weighted imaging (DWI) in liver fibrosis (LF) staging.

Methods: We conducted a comprehensive literature search to identify relevant articles. Diagnostic data were extracted for each METAVIR fibrosis stage (F0-F4).

Preoperative evaluation of the histological grade of hepatocellular carcinoma with diffusion-weighted imaging: a meta-analysis.

Objective: To evaluate the diagnostic performance of diffusion-weighted imaging (DWI) in the preoperative prediction of the histological grade of hepatocellular carcinoma (HCC).

Materials And Methods: A comprehensive literature search was performed in several authoritative databases to identify relevant articles. QUADAS-2 was used to assess the quality of included studies.

Relative specificity of acupuncture reinforcing and reducing methods.

Objective: To probe the effects of acupuncture reinforcing and reducing methods on the human body.

Methods: Studied acupuncture reinforcing and reducing actions in the ancient literature, based on modern clinical and experimental studies, in combination with experience of acupuncture teaching and clinical treatment.

Results: The key to the generation of reinforcing and reducing actions is not the acupuncture reinforcing and reducing methods themselves, but instead the functional state of the patient during the acupuncture.