MACNet: A Multidimensional Attention-Based Convolutional Neural Network for Lower-Limb Motor Imagery Classification.

Decoding lower-limb motor imagery (MI) is highly important in brain-computer interfaces (BCIs) and rehabilitation engineering. However, it is challenging to classify lower-limb MI from electroencephalogram (EEG) signals, because lower-limb motions (LLMs) including MI are excessively close to physiological representations in the human brain and generate low-quality EEG signals. To address this challenge, this paper proposes a multidimensional attention-based convolutional neural network (CNN), termed MACNet, which is specifically designed for lower-limb MI classification.

FDCN-C: A deep learning model based on frequency enhancement, deformable convolution network, and crop module for electroencephalography motor imagery classification.

Motor imagery (MI)-electroencephalography (EEG) decoding plays an important role in brain-computer interface (BCI), which enables motor-disabled patients to communicate with external world via manipulating smart equipment. Currently, deep learning (DL)-based methods are popular for EEG decoding. Whereas the utilization efficiency of EEG features in frequency and temporal domain is not sufficient, which results in poor MI classification performance.

Human-in-the-Loop Trajectory Optimization Based on sEMG Biofeedback for Lower-Limb Exoskeleton.

Lower-limb exoskeletons (LLEs) can provide rehabilitation training and walking assistance for individuals with lower-limb dysfunction or those in need of functionality enhancement. Adapting and personalizing the LLEs is crucial for them to form an intelligent human-machine system (HMS). However, numerous LLEs lack thorough consideration of individual differences in motion planning, leading to subpar human performance.

Development and validation of a Radiopathomics model based on CT scans and whole slide images for discriminating between Stage I-II and Stage III gastric cancer.

Objective: This study aimed to develop and validate an artificial intelligence radiopathological model using preoperative CT scans and postoperative hematoxylin and eosin (HE) stained slides to predict the pathological staging of gastric cancer (stage I-II and stage III).

Methods: This study included a total of 202 gastric cancer patients with confirmed pathological staging (training cohort: n = 141; validation cohort: n = 61). Pathological histological features were extracted from HE slides, and pathological models were constructed using logistic regression (LR), support vector machine (SVM), and NaiveBayes.

A comprehensive radiopathological nomogram for the prediction of pathological staging in gastric cancer using CT-derived and WSI-based features.

Objective: This study aims to develop and validate an innovative radiopathomics model that combines radiomics and pathomics features to effectively differentiate between stages I-II and stage III gastric cancer (pathological staging).

Methods: Our study included 200 patients with well-defined stages of gastric cancer divided into a training cohort (n = 140) and a test cohort (n = 60). Radiomics features were extracted from contrast-enhanced CT images using PyRadiomics, while pathomics features were obtained from whole slide images of pathological specimens through a fine-tuned deep learning model (ResNet-18).

A radiomics model based on magnetic resonance imaging to predict cytokeratin 7/19 expression and liver fluke infection of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer. HCC with liver fluke infection could harbor unique biological behaviors. This study was aimed at investigating radiomics features of HCC with liver fluke infection and establishing a model to predict the expression of cytokeratin 7 (CK7) and cytokeratin 19 (CK19) as well as prognosis at the same time.

Radiomics and nomogram of magnetic resonance imaging for preoperative prediction of microvascular invasion in small hepatocellular carcinoma.

Background: Microvascular invasion (MVI) of small hepatocellular carcinoma (sHCC) (≤ 3.0 cm) is an independent prognostic factor for poor progression-free and overall survival. Radiomics can help extract imaging information associated with tumor pathophysiology.

Medical Therapy of Hearing Impairment and Tinnitus with Chinese Medicine: An Overview.

The current review gives a comprehensive overview of the recent development in Chinese medicine (CM) for treating several kinds of acquired nerve deafness and tinnitus, as well as links the traditional principle to well-established pharmacological mechanisms for future research. To date, about 24 herbal species and 40 related ingredients used in CM to treat hearing loss and tinnitus are reported for the treatment of endocochlear potential, endolymph growth, lowering toxic and provocative substance aggregation, inhibiting sensory cell death, and retaining sensory transfer. However, there are a few herbal species that can be used for medicinal purposes.

Comparison of 10- and 20-min hepatobiliary phase images on Gd-EOB-DTPA-enhanced MRI T1 mapping for liver function assessment in clinic.

Purpose: To compare hepatobiliary phase (HBP) images obtained 10 and 20 min after Gd-EOB-DTPA-enhanced MRI for liver function assessment in clinic on 3.0 T MR imaging.

Methods: 103 patients were separated into four groups: 38 patients for the normal liver function (NLF) group, 33 patients for the liver cirrhosis with Child-Pugh A (LCA) group, 21 patients for the liver cirrhosis with Child-Pugh B group, and 11 patients for a liver cirrhosis with Child-Pugh C group.

Evaluating segmental liver function using T1 mapping on Gd-EOB-DTPA-enhanced MRI with a 3.0 Tesla.

Background: Assessing the liver function provides valuable information to evaluate surgical risk and plan accordingly. Current studies focus on whole liver function evaluation. However, assessment of segmental liver function is equally important in the clinical practice.

Gd-EOB-DTPA-enhanced MRI T1 mapping for assessment of liver function in rabbit fibrosis model: comparison of hepatobiliary phase images obtained at 10 and 20 min.

Objectives: To compare hepatobiliary phase (HBP) images obtained at 10 and 20 min after Gd-EOB-DTPA-enhanced MRI for assessment of liver function in rabbit fibrosis model on 3.0 T MR imaging.

Methods: 34 animals were separated into three groups: 5 for a control group, 14 for a mild fibrosis group, and 15 for a severe fibrosis group based on pathological proof.

Conventional MRI techniques combined with MR sialography on T2-3D-DRIVE in Sjögren syndrome.

Aim: To investigate the value of conventional MRI techniques combined with MR sialography on T2-3D-DRIVE in the diagnosis of Sjögren syndrome (SS).

Methods: 107 patients were divided into SS group and non-SS group. Conventional MRI techniques, such as T1WI, T2WI, and STIR images were used for changes of fat signal in the parotid gland, while the MR sialography were used for ducts dilation of the parotid gland.

Vulnerability of welders to manganese exposure--a neuroimaging study.

Increased manganese (Mn) exposure is known to cause cognitive, psychiatric and motor deficits. Mn exposure occurs in different occupational settings, where the airborne Mn level and the size of respirable particulates may vary considerably. Recently the importance of the role of the cerebral cortex in Mn toxicity has been highlighted, especially in Mn-induced neuropsychological effects.

Thalamic GABA predicts fine motor performance in manganese-exposed smelter workers.

Overexposure to manganese (Mn) may lead to parkinsonian symptoms including motor deficits. The main inhibitory neurotransmitter gamma-aminobutyric acid (GABA) is known to play a pivotal role in the regulation and performance of movement. Therefore this study was aimed at testing the hypothesis that an alteration of GABA following Mn exposure may be associated with fine motor performance in occupationally exposed workers and may underlie the mechanism of Mn-induced motor deficits.

In vivo measurement of brain GABA concentrations by magnetic resonance spectroscopy in smelters occupationally exposed to manganese.

Background: Exposure to excessive levels of manganese (Mn) is known to induce psychiatric and motor disorders, including parkinsonian symptoms. Therefore, finding a reliable means for early detection of Mn neurotoxicity is desirable.

Objectives: Our goal was to determine whether in vivo brain levels of γ-aminobutyric acid (GABA), N-acetylaspartate (NAA), and other brain metabolites in male smelters were altered as a consequence of Mn exposure.

[Variations of brain magnetic resonance imaging among manganese-exposed workers].

Objective: Variations of the signal intensities in the magnetic resonance (MR) T(1)-weighted image (T(1)WI) of globus pallidus among manganese(Mn)-exposed workers were explored to provide a scientific basis for exposed biomarker of manganese-injured central nervous system (CNS).

Methods: The brain MR T(1) and T(2) WI in eighteen male asymptomatic Mn-exposed, eight manganism and nine healthy control workers were examined routinely by adopting a 1.5 Tesla signal superconducting system.

Relationship between changes in brain MRI and (1)H-MRS, severity of chronic liver damage, and recovery after liver transplantation.

Magnetic resonance imaging (MRI) and (1)H magnetic resonance spectroscopy ((1)H-MRS) have been used in clinics for diagnosis of chronic liver diseases. This study was designed to investigate the relationship between MRI/MRS outcomes and the severity of liver damage. Of 50 patients examined, the MRI signal intensity in the globus pallidus as determined by pallidus index (PI) increased as the disease severity (scored by Child Pugh ranking) worsened (r = 0.

Evidence for altered hippocampal volume and brain metabolites in workers occupationally exposed to lead: a study by magnetic resonance imaging and (1)H magnetic resonance spectroscopy.

Environmental and occupational exposure to lead (Pb) remains to be a major public health issue. The purpose of this cross-sectional study was to use non-invasive magnetic resonance imaging (MRI) and proton magnetic resonance spectroscopy ((1)H MRS) techniques to investigate whether chronic exposure to Pb in an occupational setting altered brain structure and function of Pb-exposed workers. The Pb-exposed group consisted of 15 workers recruited from either a Pb-smelting factory or a Pb-battery manufacturer.