Metal-organic framework-based nanoplatforms for synergistic anti-atherosclerosis therapy by regulating the PI3K/AKT/MSR1 pathway in macrophages.

Atherosclerosis is the main pathogenic factor of various cardiovascular diseases. During the pathogenesis of atherosclerosis, macrophages play a major role, mainly by secreting pro-inflammatory cytokines and taking in lipids to form foam cells. Thiamine pyrophosphate (TPP) is an antagonist of the P2Y6 receptor, which is overexpressed on macrophages during atherosclerosis and facilitates the lipid phagocytosis of macrophages.

Current status and prospects of MOFs loaded with HO-related substances for ferroptosis therapy.

Ferroptosis is a programmed cell death mechanism characterized by the accumulation of iron (Fe)-dependent lipid peroxides within cells. Ferroptosis holds excellent promise in tumor therapy. Metal-organic frameworks (MOFs) offer unique advantages in tumor ferroptosis treatment due to their high porosity, excellent stability, high biocompatibility, and targeting capabilities.

Advances in drug delivery-based therapeutic strategies for renal fibrosis treatment.

Renal fibrosis is the result of all chronic kidney diseases and is becoming a major global health hazard. Currently, traditional treatments for renal fibrosis are difficult to meet clinical needs due to shortcomings such as poor efficacy or highly toxic side effects. Therefore, therapeutic strategies that target the kidneys are needed to overcome these shortcomings.

Circular RNAs: Biomarkers of cancer.

Circular RNAs (circRNAs) are a class of single-stranded closed RNAs that are produced by the back splicing of precursor mRNAs. The formation of circRNAs mainly involves intron-pairing-driven circularization, RNA-binding protein (RBP)-driven circularization, and lariat-driven circularization. The vast majority of circRNAs are found in the cytoplasm, and some intron-containing circRNAs are localized in the nucleus.

Treatment of inferior turbinate hypertrophy by plasma turbinate reduction with onepointthreeside way.

Objectives: Nasal congestion is often the main symptom of the patients with non-allergic rhinitis, who have inferior turbinate hypertrophy if getting poor treatment effect. Plasma treatment for inferior turbinate hypertrophy can effectively improve nasal obstruction. Generally, plasma treatment with multiple puncture sites, makes patients intraoperative painful and postoperative bleeding, which let patients often fear of surgery.

Machine learning-based prognostic and metastasis models of kidney cancer.

Background: Kidney cancer originates from the urinary tubule epithelial system of the renal parenchyma, accounting for 20% of all urinary system tumors. Approximately 70% of cases are localized at diagnosis, and 30% are metastatic. Most localized kidney cancers can be cured by surgery, but most metastatic patients relapse after surgery and eventually die of kidney cancer.

A Fast-Response Driving Waveform Design Based on High-Frequency Voltage for Three-Color Electrophoretic Displays.

Three-color electrophoretic displays (EPDs) have the characteristics of colorful display, reflection display, low power consumption, and flexible display. However, due to the addition of red particles, response time of three-color EPDs is increased. In this paper, we proposed a new driving waveform based on high-frequency voltage optimization and electrophoresis theory, which was used to shorten the response time.

Genetic insights, disease mechanisms, and biological therapeutics for Waardenburg syndrome.

Waardenburg syndrome (WS), also known as auditory-pigmentary syndrome, is the most common cause of syndromic hearing loss (HL), which accounts for approximately 2-5% of all patients with congenital hearing loss. WS is classified into four subtypes depending on the clinical phenotypes. Currently, pathogenic mutations of PAX3, MITF, SOX10, EDN3, EDNRB or SNAI2 are associated with different subtypes of WS.

Next-generation sequencing-based mutation analysis of genes associated with enlarged vestibular aqueduct in Chinese families.

Objectives: The identification of gene mutations enables more appropriate genetic counseling and proper medical management for EVA patients. The purpose of this study was to validate the accuracy and sensitivity of our method for comprehensive mutation detection in EVA, and summarize these data to explore a more accurate and convenient genetic diagnosis method.

Methods: A multiplex PCR sequencing panel was designed to capture the exons of three known EVA-associated genes (SLC26A4, KCNJ10, and FOXI1), and NGS was conducted in 17 Chinese families with EVA.

Ultrasmall Au clusters supported on pristine and defected CeO: Structure and stability.

The atomistic simulation of supported metal catalysts has long been challenging due to the increased complexity of dual components. In order to determine the metal/support interface, efficient theoretical tools to map out the potential energy surface (PES) are generally required. This work represents the first attempt to apply the recently developed SSW-NN method, stochastic surface walking (SSW) global optimization based on global neural network potential (G-NN), to explore the PES of a highly controversial supported metal catalyst, Au/CeO, system.

Elmod3 knockout leads to progressive hearing loss and abnormalities in cochlear hair cell stereocilia.

ELMOD3, an ARL2 GTPase-activating protein, is implicated in causing hearing impairment in humans. However, the specific role of ELMOD3 in auditory function is still far from being elucidated. In the present study, we used the CRISPR/Cas9 technology to establish an Elmod3 knockout mice line in the C57BL/6 background (hereinafter referred to as Elmod3-/- mice) and investigated the role of Elmod3 in the cochlea and auditory function.

Atomic structure of boron resolved using machine learning and global sampling.

Boron crystals, despite their simple composition, must rank top for complexity: even the atomic structure of the ground state of β-B remains uncertain after 60 years' study. This makes it difficult to understand the many exotic photoelectric properties of boron. The presence of self-doping atoms in the crystal interstitial sites forms an astronomical configurational space, making the determination of the real configuration virtually impossible using current techniques.

Massively parallelization strategy for material simulation using high-dimensional neural network potential.

The potential energy surface (PES) calculation is the bottleneck for modern material simulation. The high-dimensional neural network (HDNN) technique emerged recently appears to be a problem solver for fast and accurate PES computation. The major cost of the HDNN lies at the computation of the structural descriptors that capture the geometrical environment of atoms.

Revealing isoelectronic size conversion dynamics of metal nanoclusters by a noncrystallization approach.

Atom-by-atom engineering of nanomaterials requires atomic-level knowledge of the size evolution mechanism of nanoparticles, which remains one of the greatest mysteries in nanochemistry. Here we reveal atomic-level dynamics of size evolution reaction of molecular-like nanoparticles, i.e.

Material discovery by combining stochastic surface walking global optimization with a neural network.

While the underlying potential energy surface (PES) determines the structure and other properties of a material, it has been frustrating to predict new materials from theory even with the advent of supercomputing facilities. The accuracy of the PES and the efficiency of PES sampling are two major bottlenecks, not least because of the great complexity of the material PES. This work introduces a "Global-to-Global" approach for material discovery by combining for the first time a global optimization method with neural network (NN) techniques.