Advancing Myocarditis Research: Evaluating Animal Models for Enhanced Pathophysiological Insights.

Purpose Of Review: This review aims to assess the current landscape of animal models used in myocarditis research, with a focus on understanding their utility in uncovering the pathophysiology of the disease. The goal is to evaluate these models' strengths and weaknesses and propose optimizations to make them more relevant and reliable for both mechanistic studies and therapeutic interventions in myocarditis.

Recent Findings: Recent studies have primarily utilized animal models, particularly viral and autoimmune myocarditis models, to study disease mechanisms.

Hypoglycemic Effects and Quality Marker Screening of Lindl. at Different Growth Years.

(1) Background: The effect of Lindl. () on hyperglycemic syndrome has only been recently known for several years. Materials of were always collected from the plants cultivated in various growth ages.

The cumulative effects of cascade reservoirs control nitrogen and phosphorus flux: Base on biogeochemical processes.

The reservoir serves as a water source, a flood control structure, a navigational aid, and also impacts the downstream ecosystem as well as the reservoir zone. However, debate exists about effectiveness of cascade reservoirs in controlling the transportation of nutrients, particularly in the Yangtze River basin, which has been significantly affected by reservoir development. This research develops a new model X-NPSEM (X with Nitrogen and Phosphorus Steady-state Reservoir Model) based on biogeochemical processes of nitrogen and phosphorus reaction for investigating the dynamic storage capacity of cascade reservoirs at both reservoir- and watershed scales.

PPARα is one of the key targets for dendrobine to improve hepatic steatosis in NAFLD.

Ethnopharmacological Relevance: Dendrobium nobile Lindl. (DNL) is a traditional Chinese ethnobotanical herb. Dendrobine (DNE) has been designated as a quality indicator for DNL in the Chinese Pharmacopoeia.

BlobCUT: A Contrastive Learning Method to Support Small Blob Detection in Medical Imaging.

Medical imaging-based biomarkers derived from small objects (e.g., cell nuclei) play a crucial role in medical applications.

Use of novel structural features to identify urinary biomarkers during acute kidney injury that predict progression to chronic kidney disease.

Background: A significant barrier to biomarker development in the field of acute kidney injury (AKI) is the use of kidney function to identify candidates. Progress in imaging technology makes it possible to detect early structural changes prior to a decline in kidney function. Early identification of those who will advance to chronic kidney disease (CKD) would allow for the initiation of interventions to halt progression.

Microbiological Quality and Safety of Pizza Held Out of Temperature Control in University Dining Halls.

Pizza is a popular food consumed around the world every day. Hot food temperatures were obtained from 19,754 nonpizza samples and 1,336 pizza temperatures were taken from dining facilities operated by Rutgers University between 2001 and 2020. These data showed that pizza was more frequently out of temperature control than many other foods.

New method for scaling nonpoint source pollution by integrating the SWAT model and IHA-based indicators.

Nonpoint source (NPS) pollution shows spatial scaling effects because it is affected by topography, river networks, and many other factors. Currently, the lack of an integrated methodology for quantifying the scaling effect has become a crucial barrier in evaluating NPS pollution. In this study, a new method was proposed for scaling NPS pollution by integrating hydrological model and hydrological alteration indicators.

Image analysis techniques to map pyramids, pyramid structure, glomerular distribution, and pathology in the intact human kidney from 3-D MRI.

Kidney pathologies are often highly heterogeneous. To comprehensively understand kidney structure and pathology, it is critical to develop tools to map tissue microstructure in the context of the whole, intact organ. Magnetic resonance imaging (MRI) can provide a unique, three-dimensional view of the kidney and allows for measurements of multiple pathological features.

Impacted molar upright with self-made helical spring.

With a case of mesial impaction of maxillary first and second molar, the mechanical analysis and clinical applications of a self-made helical spring for the uprighting treatment of mesial impacted molars was introduced.

Small Blob Detector Using Bi-Threshold Constrained Adaptive Scales.

Recent advances in medical imaging technology bring great promises for medicine practices. Imaging biomarkers are discovered to inform disease diagnosis, prognosis, and treatment assessment. Detecting and segmenting objects from images are often the first steps in quantitative measurement of these biomarkers.

Magnetic resonance imaging accurately tracks kidney pathology and heterogeneity in the transition from acute kidney injury to chronic kidney disease.

Acute kidney injury (AKI) increases the risk for chronic kidney disease (CKD). However, there are few tools to detect microstructural changes after AKI. Here, cationic ferritin-enhanced magnetic resonance imaging (CFE-MRI) was applied to examine the heterogeneity of kidney pathology in the transition from AKI to CKD.

AD-NET: Age-adjust neural network for improved MCI to AD conversion prediction.

The prediction of Mild Cognitive Impairment (MCI) patients who are at higher risk converting to Alzheimer's Disease (AD) is critical for effective intervention and patient selection in clinical trials. Different biomarkers including neuroimaging have been developed to serve the purpose. With extensive methodology development efforts on neuroimaging, an emerging field is deep learning research.

Improved small blob detection in 3D images using jointly constrained deep learning and Hessian analysis.

Imaging biomarkers are being rapidly developed for early diagnosis and staging of disease. The development of these biomarkers requires advances in both image acquisition and analysis. Detecting and segmenting objects from images are often the first steps in quantitative measurement of these biomarkers.

Integration of machine learning and mechanistic models accurately predicts variation in cell density of glioblastoma using multiparametric MRI.

Glioblastoma (GBM) is a heterogeneous and lethal brain cancer. These tumors are followed using magnetic resonance imaging (MRI), which is unable to precisely identify tumor cell invasion, impairing effective surgery and radiation planning. We present a novel hybrid model, based on multiparametric intensities, which combines machine learning (ML) with a mechanistic model of tumor growth to provide spatially resolved tumor cell density predictions.

Deep Residual Inception Encoder-Decoder Network for Medical Imaging Synthesis.

Image synthesis is a novel solution in precision medicine for scenarios where important medical imaging is not otherwise available. The convolutional neural network (CNN) is an ideal model for this task because of its powerful learning capabilities through the large number of layers and trainable parameters. In this research, we propose a new architecture of residual inception encoder-decoder neural network (RIED-Net) to learn the nonlinear mapping between the input images and targeting output images.

In situ immobilization of cadmium in soil by stabilized biochar-supported iron phosphate nanoparticles.

The potential for nanoscale phosphate amendments to remediate heavy metal contamination has been widely investigated, but the strong tendency of nanoparticles to form aggregates limits the application of this technique in soil. This study synthesized a composite of biochar-supported iron phosphate nanoparticle (BC@Fe3(PO4)2) stabilized by a sodium carboxymethyl cellulose to improve the stability and mobility of the amendment in soil. The sedimentation test and column test demonstrated that BC@Fe3(PO4)2 exhibited better stability and mobility than iron phosphate nanoparticles.

[The mechanics analysis and clinical application of molar distalization with micro-implant combining with utility arch].

Combined with a case, the mechanical analysis and clinical application of micro-implant combining with utility arch were introduced in this paper.

NBS1 rs1805794G>C polymorphism is associated with decreased risk of acute myeloid leukemia in a Chinese population.

As a key encoding protein gene of MRN (MRE11-RAD50-NBS1) complex, NBS1 plays a crucial role in maintaining genomic stability and preventing cell apoptosis, inflammation and tumorgenesis. Single nucleotide polymorphisms (rs2735383 and rs1805794) in NBS1 have been frequently studied in some cancers with discordant results in previous case-control studies. However, the relationship between these two functional polymorphisms and the susceptibility to acute myeloid leukemia (AML) in Chinese population has not been investigated.