An improved low-rank plus sparse unrolling network method for dynamic magnetic resonance imaging.

Background: Recent advances in deep learning have sparked new research interests in dynamic magnetic resonance imaging (MRI) reconstruction. However, existing deep learning-based approaches suffer from insufficient reconstruction efficiency and accuracy due to the lack of time correlation modeling during the reconstruction procedure.

Purpose: Inappropriate tensor processing steps and deep learning models may lead to not only a lack of modeling in the time dimension but also an increase in the overall size of the network.

Gold-grafted melamine sponge as surface-enhanced Raman spectroscopy substrate for enzyme-linked immunoassay of mycotoxins in cereal samples.

Gold-grafted melamine sponge (AuSp) was fabricated and applied as surface-enhanced Raman spectroscopy (SERS) substrate for enzyme-linked immunoassay of 2 typical mycotoxins, zearalenone (ZEN) and T-2 toxin. The gold nanoparticles were in situ grown on the sponge, and the product showed good effect in enhancing Raman signal and good stability. COMSOL and Gaussian simulations were used to analyze the enhancing effect.

Recent progress of chiral metal-organic frameworks in enantioselective separation and detection.

Chiral compounds are abundantly distributed in both the natural world and biological systems. It is crucial to identify and detect chiral compounds in living systems or to separate and determine them in the natural environment. Many researchers have developed a range of chiral materials with different functionalizations to separate and detect chiral substances.

Effects of a reminiscence therapy-involved program on anxiety, depression, and the quality of life in cancer patients: a meta-analysis of randomized controlled trials.

Objective: Reminiscence therapy is increasingly being utilized for cancer patients to address psychological pressure and enhance their quality of life. This meta-analysis aimed to comprehensively evaluate the effect of a reminiscence therapy-involved program (RTIP) on anxiety, depression, and quality of life in cancer patients.

Methods: A systematic literature search was conducted in the Web of Science, PubMed, Embase, and Cochrane Library databases until December 2023 to screen randomized control trials (RCTs) comparing the effect of RTIP and control care.

A hybrid, nonlinear programming approach for optimizing passive shimming in MRI.

Background: In magnetic resonance imaging (MRI), maintaining a highly uniform main magnetic field (B) is essential for producing detailed images of human anatomy. Passive shimming (PS) is a technique used to enhance B uniformity by strategically arranging shimming iron pieces inside the magnet bore. Traditionally, PS optimization has been implemented using linear programming (LP), posing challenges in balancing field quality with the quantity of iron used for shimming.

A self-driven microfluidic immunosensor for rapid separation, enrichment, and detection of biomarkers in serum.

Biomarkers and their concentration levels are critical indicators of metabolomics for clinical applications. Rapid and sensitive analysis methods are essential for realizing timely and efficient quantitation of those significant biomarkers. In this work, a self-driven microfluidic immunosensor was developed for rapid all-in-one separation, enrichment, and detection of biomarkers.

Critical steps in the restoration of coal mine soils: Microbial-accelerated soil reconstruction.

Soil reconstruction is a critical step in the restoration of environments affected by mining activities. This paper provides a comprehensive review of the significant role that microbial processes play in expediting soil structure formation, particularly within the context of mining environment restoration. Coal gangue and flotation tailings, despite their low carbon content and large production volumes, present potential substrates for soil reclamation.

Recent progress of porous cage materials in sample preparation, chromatographic separation, and detection.

Porous cage materials with certain dimensions, sizes, shapes, and functions have been regarded as promising materials for sample preparation, chromatographic separation, and detection process. In contrast to infinite frameworks such as metal-organic frameworks or covalent organic frameworks, porous cage materials are constructed from discrete molecules containing at least one internal cavity. The well-defined cavities in porous cage materials provide opportunities for non-covalent interactions.

Far-Red Aggregation-Induced Emission Hydrogel-Reinforced Tissue Clearing for 3D Vasculature Imaging of Whole Lung and Whole Tumor.

Understanding the vascular formation and distribution in metastatic lung tumors is a significant challenge due to autofluorescence, antibody/dye diffusion in dense tumor, and fluorophore stability when exposed to solvent-based clearing agents. Here, an approach is presented that redefines 3D vasculature imaging within metastatic tumor, peritumoral lung tissue, and normal lung. Specifically, a far-red aggregation-induced emission nanoparticle with surface amino groups (termed as TSCN nanoparticle, TSCNNP) is designed for in situ formation of hydrogel (TSCNNP@Gel) inside vasculatures to provide structural support and enhance the fluorescence in solvent-based tissue clearing method.

White matter microstructure alterations of the posterior limb of internal capsule in first-episode drug naive schizophrenia patients.

Objectives: Previous studies have shown that microstructural alterations in white matter (WM) could contribute to the symptom manifestation and support the dysconnectivity hypothesis in schizophrenia patients. These alterations were pervasive, non-specific, and reported inconsistently across the literature. This study aimed to specifically investigate the microstructure alterations of the posterior limb of the internal capsule (PLIC) in first-episode, drug-naive schizophrenia patients.

On-Chip Capture, Raman-Silent Polymer Labeling, and Digital Mapping Analysis of O157:H7 in Beverages All-in-One.

O157:H7 is one of the most susceptible foodborne pathogens, easily causing food poisoning and other health risks. It is of great significance to establish a quantitative method with higher sensitivity and less time consumption for foodborne pathogens analysis. The Raman-silent signal has a good performance for avoiding interference from the food matrix so as to achieve accurate signal differentiation.

Arrhythmia classification based on multi-feature multi-path parallel deep convolutional neural networks and improved focal loss.

Early diagnosis of abnormal electrocardiogram (ECG) signals can provide useful information for the prevention and detection of arrhythmia diseases. Due to the similarities in Normal beat (N) and Supraventricular Premature Beat (S) categories and imbalance of ECG categories, arrhythmia classification cannot achieve satisfactory classification results under the inter-patient assessment paradigm. In this paper, a multi-path parallel deep convolutional neural network was proposed for arrhythmia classification.

Response of bacterial ecological and functional properties to anthropogenic interventions during maturation of mine sand soil.

Soil formation is a complex process that starts from the biological development. The ecological principles and biological function in soil are of great importance, whereas their response to anthropogenic intervention has been poorly understood. In this study, a 150-day microcosmic experiment was conducted with the addition of sludge and/or fermented wood chips (FWC) to promote the soil maturation.

IRE1α determines ferroptosis sensitivity through regulation of glutathione synthesis.

Cellular sensitivity to ferroptosis is primarily regulated by mechanisms mediating lipid hydroperoxide detoxification. We show that inositol-requiring enzyme 1 (IRE1α), an endoplasmic reticulum (ER) resident protein critical for the unfolded protein response (UPR), also determines cellular sensitivity to ferroptosis. Cancer and normal cells depleted of IRE1α gain resistance to ferroptosis, while enhanced IRE1α expression promotes sensitivity to ferroptosis.

Myocardial infarction detection method based on the continuous T-wave area feature and multi-lead-fusion deep features.

Myocardial infarction (MI) is one of the most threatening cardiovascular diseases. This paper aims to explore a method for using an algorithm to autonomously classify MI based on the electrocardiogram (ECG).A detection method of MI that fuses continuous T-wave area (C_TWA) feature and ECG deep features is proposed.