Characterization of a novel conditional knockout mouse model to assess efficacy of mRNA therapy in the context of severe OTC deficiency.

Ornithine transcarbamylase deficiency (OTCD) is the most common urea-cycle disorder, characterized by hyperammonemia and accompanied by a high unmet patient need. mRNA therapies have been shown to be efficacious in hypomorphic Sparse-fur abnormal skin and hair (Spf-ash) mice, a model of late-onset disease. However, studying the efficacy of ornithine transcarbamylase (OTC) mRNA therapy in traditional knockout mice, a model for severe early-onset OTCD, is hampered by the rapid lethality of the model and poor lipid nanoparticle (LNP) uptake into neonatal mouse liver.

DV-DETR: Improved UAV Aerial Small Target Detection Algorithm Based on RT-DETR.

For drone-based detection tasks, accurately identifying small-scale targets like people, bicycles, and pedestrians remains a key challenge. In this paper, we propose DV-DETR, an improved detection model based on the Real-Time Detection Transformer (RT-DETR), specifically optimized for small target detection in high-density scenes. To achieve this, we introduce three main enhancements: (1) ResNet18 as the backbone network to improve feature extraction and reduce model complexity; (2) the integration of recalibration attention units and deformable attention mechanisms in the neck network to enhance multi-scale feature fusion and improve localization accuracy; and (3) the use of the Focaler-IoU loss function to better handle the imbalanced distribution of target scales and focus on challenging samples.

Micromechanical characteristics of titanium alloy (Ti-6Al-4V) made by laser powder bed fusion using an in-situ SEM micropillar compression technique.

While titanium alloy (Ti-6Al-4V) made by laser powder bed fusion (L-PBF) exhibits complex deformation behaviors, its important micromechanical properties in relation to loading directions are not fully understood. This research aims to investigate the micromechanical behaviors of printed L-PBF Ti-6Al-4V alloys under vertical (i.e.

Association between dietary vitamin B6 intake and endometriosis risk: evidence from the national health and nutrition examination survey.

Background: Endometriosis is a multifaceted disorder with genetic, immune, inflammatory, and multifactorial origins. Vitamin B6 serves as a pivotal coenzyme in various metabolic pathways involving lipids, hemes, nucleic acids, proteins, and carbohydrates. Dysregulation or deficiency of vitamin B6 can perturb human physiology.

AFM-YOLOv8s: An Accurate, Fast, and Highly Robust Model for Detection of Sporangia of with Various Morphological Variants.

Monitoring spores is crucial for predicting and preventing fungal- or oomycete-induced diseases like grapevine downy mildew. However, manual spore or sporangium detection using microscopes is time-consuming and labor-intensive, often resulting in low accuracy and slow processing speed. Emerging deep learning models like YOLOv8 aim to rapidly detect objects accurately but struggle with efficiency and accuracy when identifying various sporangia formations amidst complex backgrounds.

Downregulation of SSR2 Enhances Hepatocellular Carcinoma Cisplatin Sensitivity via the Hippo Pathway.

Background: Chemotherapy resistance is an obstacle to promoting the survival of patients with hepatocellular carcinoma (HCC). Thus, finding promising therapeutic targets to enhance HCC chemotherapy is necessary.

Methods: Signal sequence receptor subunit (SSR2) expression analysis was performed using quantitative real time polymerase chain reaction (qPCR) and Western blotting assays.

Enhancing practicality of deep learning for crop disease identification under field conditions: insights from model evaluation and crop-specific approaches.

Background: Crop diseases can lead to significant yield losses and food shortages if not promptly identified and managed by farmers. With the advancements in convolutional neural networks (CNN) and the widespread availability of smartphones, automated and accurate identification of crop diseases has become feasible. However, although previous studies have achieved high accuracy (>95%) under laboratory conditions (Lab) using mixed data sets of multiple crops, these models often falter when deployed under field conditions (Field).

Characterizing the mechanism of action for mRNA therapeutics for the treatment of propionic acidemia, methylmalonic acidemia, and phenylketonuria.

Messenger RNA (mRNA) therapeutics delivered via lipid nanoparticles hold the potential to treat metabolic diseases caused by protein deficiency, including propionic acidemia (PA), methylmalonic acidemia (MMA), and phenylketonuria (PKU). Herein we report results from multiple independent preclinical studies of mRNA-3927 (an investigational treatment for PA), mRNA-3705 (an investigational treatment for MMA), and mRNA-3210 (an investigational treatment for PKU) in murine models of each disease. All 3 mRNA therapeutics exhibited pharmacokinetic/pharmacodynamic (PK/PD) responses in their respective murine model by driving mRNA, protein, and/or protein activity responses, as well as by decreasing levels of the relevant biomarker(s) when compared to control-treated animals.

Fatigue Crack Growth Rates and Crack Tip Opening Loads in CT Specimens Made of SDSS and Manufactured Using WAAM.

Additive manufacturing offers greater flexibility in the design and fabrication of structural components with complex shapes. However, the use of additively manufactured parts for load-bearing structural applications, specifically involving cyclic loading, requires a thorough investigation of material fatigue properties. These properties can be affected by many factors, including residual stresses and crack tip shielding mechanisms, which can be very different from those of conventionally manufactured materials.

Calculating Volume of Pig Point Cloud Based on Improved Poisson Reconstruction.

Pig point cloud data can be used to digitally reconstruct surface features, calculate pig body volume and estimate pig body weight. Volume, as a pig novel phenotype feature, has the following functions: (a) It can be used to estimate livestock weight based on its high correlation with body weight. (b) The volume proportion of various body parts (such as head, legs, etc.

A deep learning-based approach for fully automated segmentation and quantitative analysis of muscle fibers in pig skeletal muscle.

Muscle fiber properties exert a significant influence on pork quality, with cross-sectional area (CSA) being a crucial parameter closely associated with various meat quality indicators, such as shear force. Effectively identifying and segmenting muscle fibers in a robust manner constitutes a vital initial step in determining CSA. This step is highly intricate and time-consuming, necessitating an accurate and automated analytical approach.

Unraveling varying spatiotemporal patterns of dengue and associated exposure-response relationships with environmental variables in Southeast Asian countries before and during COVID-19.

The enforcement of COVID-19 interventions by diverse governmental bodies, coupled with the indirect impact of COVID-19 on short-term environmental changes (e.g. plant shutdowns lead to lower greenhouse gas emissions), influences the dengue vector.

Inhibition of IGF2BP1 attenuates the progression of endometriosis through PTBP1.

Introduction: Endometriosis (EMs), manifested by pain and infertility, is a chronic inflammatory disease. The precise pathophysiology of this disease remains uncertain. Insulin-like growth factor-2 mRNA-binding protein 1 (IGF2BP1) and polypyrimidine tract-binding protein 1 (PTBP1) have both been found to regulate proliferation, apoptosis, and invasion.

MOFs@POMs-derived bimetallic oxide Fe(MoO) nanoparticles for sensitive colorimetric detection of salicylic acid in aspirin.

A colorimetric sensing method for salicylic acid (SA) was developed by designing and fabricating bimetallic oxide nanozymes. Firstly, by calcinating MIL-100(Fe)@PMo (MOFs@POMs) at different temperature, Fe(MoO)-Ts (T = 400℃, 500℃, 600℃, 700℃) nanoparticles (NPs) were successfully prepared. Secondly, by evaluating the peroxidase-like activities, Fe(MoO)-600 NPs shows the best peroxidase-like activity attributed to the Fenton-like effect and the synergistic coupling interaction between Mo and Fe.

Hu-Qi-Zheng-Xiao Decoction Inhibits the Metastasis of Hepatocellular Carcinoma Cells by Suppressing the HIF-1α Signaling Pathway to Inhibit EMT, LCSC, and Angiogenic Process.

Background: Hepatocellular carcinoma (HCC) is a common clinical malignant tumor of the digestive system. Hu-Qi-Zheng-Xiao (HQZX) decoction has been clinically found to prolong the survival of patients with hepatocellular carcinoma and improve the quality of patients' survival, but its antitumor biological mechanism is still unclear.

Methods: A nude mouse hollow fiber hepatocellular carcinoma model was constructed to analyze the in vivo efficacy of HQZX decoction against 7 different hepatocellular carcinoma cells.

Generating synthetic population for simulating the spatiotemporal dynamics of epidemics.

Agent-based models have gained traction in exploring the intricate processes governing the spread of infectious diseases, particularly due to their proficiency in capturing nonlinear interaction dynamics. The fidelity of agent-based models in replicating real-world epidemic scenarios hinges on the accurate portrayal of both population-wide and individual-level interactions. In situations where comprehensive population data are lacking, synthetic populations serve as a vital input to agent-based models, approximating real-world demographic structures.