Increased Mast Cell Counts and Degranulation in Microscopic Colitis

Objectives: Microscopic colitis (MC) is characterized by chronic diarrhea, normal colonoscopy findings, and mucosal inflammation in colonic biopsies and can be classified as collagenous colitis (CC) or lymphocytic colitis (LC). However, the pathogenesis of MC is largely unknown. In this study, we aimed to study mast cell counts and activation in MC. Methods: We investigated 64 biopsy samples from the surgical pathology database of Indiana University Health, which met the diagnostic criteria for CC or LC along with 20 control samples collected from 2014 to 2015. The specimens were used for the quantification of mast cells by examining the presence of intracellular and extracellular tryptase by immunohistochemistry. Results: In the lamina propria, the mast cell count was higher in both CC and LC groups than the control (mean highest count, 39/high-power field (HPF) vs. 30/HPF vs. 23/HPF; P < 0.01). Extracellular tryptase was present in 10% of control subjects as compared to 41% of CC (P < 0.01). Extracellular tryptase was present in 10% of control subjects as compared to 41% of CC (P < 0.01). Extracellular tryptase was present in 10% of control subjects as compared to 41% of CC (. Conclusions: The increased mast cell count and degranulation are identified in MC, suggesting that mast cell activation might be involved in the pathogenesis of MC

Moisture susceptibility of warm mix asphalt (WMA) with an organic wax additive based on X-ray computed tomography (CT) technology

The warm mix asphalt was fabricated with different moisture contents (0%, 1%, 2%, and 3%) of limestone aggregates using the Superpave gyratory compactor. The moisture susceptibility of asphalt mixtures with an organic wax additive RH was studied. The samples were compacted and tested using the modified Lottman test AASHTO T283, and the X-ray computed tomography technology was used to capture the internal structure images before and after the freeze-thaw cycles. The test results show that the air voids were distributed in the size range of 0–5 mm3 and 5–10 mm3. The number of air voids decreased with the increase of air void size and increased after freeze-thaw cycles. The air void content can be influenced by the residual moisture in aggregates. The higher the moisture content of aggregates is, the larger the air void content is. So, the air void content is likely to be sensitive to moisture damage. The increase ratio of the air void and moisture content of aggregates had good correlation with the indirect tensile strength and tensile strength ratio of the samples. The indirect tensile strength and tensile strength ratio of the samples decreased linearly, and the samples were sensitive to the moisture damage with the increases of increase ratio of the air void/moisture content in aggregates

Mitochondrial EF4 links respiratory dysfunction and cytoplasmic translation in Caenorhabditis elegans

AbstractHow animals coordinate cellular bioenergetics in response to stress conditions is an essential question related to aging, obesity and cancer. Elongation factor 4 (EF4/LEPA) is a highly conserved protein that promotes protein synthesis under stress conditions, whereas its function in metazoans remains unknown. Here, we show that, in Caenorhabditis elegans, the mitochondria-localized CeEF4 (referred to as mtEF4) affects mitochondrial functions, especially at low temperature (15°C). At worms' optimum growing temperature (20°C), mtef4 deletion leads to self-brood size reduction, growth delay and mitochondrial dysfunction. Transcriptomic analyses show that mtef4 deletion induces retrograde pathways, including mitochondrial biogenesis and cytoplasmic translation reorganization. At low temperature (15°C), mtef4 deletion reduces mitochondrial translation and disrupts the assembly of respiratory chain supercomplexes containing complex IV. These observations are indicative of the important roles of mtEF4 in mitochondrial functions and adaptation to stressful conditions

Fault Tolerant Free Gait and Footstep Planning for Hexapod Robot Based on Monte-Carlo Tree

Legged robots can pass through complex field environments by selecting gaits and discrete footholds carefully. Traditional methods plan gait and foothold separately and treat them as the single-step optimal process. However, such processing causes its poor passability in a sparse foothold environment. This paper novelly proposes a coordinative planning method for hexapod robots that regards the planning of gait and foothold as a sequence optimization problem with the consideration of dealing with the harshness of the environment as leg fault. The Monte Carlo tree search algorithm(MCTS) is used to optimize the entire sequence. Two methods, FastMCTS, and SlidingMCTS are proposed to solve some defeats of the standard MCTS applicating in the field of legged robot planning. The proposed planning algorithm combines the fault-tolerant gait method to improve the passability of the algorithm. Finally, compared with other planning methods, experiments on terrains with different densities of footholds and artificially-designed challenging terrain are carried out to verify our methods. All results show that the proposed method dramatically improves the hexapod robot's ability to pass through sparse footholds environment

Non-homology-based prediction of gene functions in maize (\u3ci\u3eZea mays\u3c/i\u3e ssp. \u3ci\u3emays\u3c/i\u3e)

Advances in genome sequencing and annotation have eased the difficulty of identifying new gene sequences. Predicting the functions of these newly identified genes remains challenging. Genes descended from a common ancestral sequence are likely to have common functions.As a result, homology is widely used for gene function prediction. This means functional annotation errors also propagate from one species to another. Several approaches based on machine learning classification algorithms were evaluated for their ability to accurately predict gene function from non-homology gene features. Among the eight supervised classification algorithms evaluated, random forest-based prediction consistently provided the most accurate gene function prediction. Non-homology-based functional annotation provides complementary strengths to homology-based annotation, with higher average performance in Biological Process GO terms, the domain where homology-based functional annotation performs the worst, and weaker performance in Molecular Function GO terms, the domain where the accuracy of homology-based functional annotation is highest. GO prediction models trained with homology-based annotations were able to successfully predict annotations from a manually curated “gold standard” GO annotation set. Non-homology-based functional annotation based on machine learning may ultimately prove useful both as a method to assign predicted functions to orphan genes which lack functionally characterized homologs, and to identify and correct functional annotation errors which were propagated through homology-based functional annotations

Conventional and hyperspectral time-series imaging of maize lines widely used in field trials

Background: Maize (Zea mays ssp. mays) is 1 of 3 crops, along with rice and wheat, responsible for more than one-half of all calories consumed around the world. Increasing the yield and stress tolerance of these crops is essential to meet the growing need for food. The cost and speed of plant phenotyping are currently the largest constraints on plant breeding efforts. Datasets linking new types of high-throughput phenotyping data collected from plants to the performance of the same genotypes under agronomic conditions across a wide range of environments are essential for developing new statistical approaches and computer vision–based tools. Findings A set of maize inbreds—primarily recently off patent lines—were phenotyped using a high-throughput platform at University of Nebraska-Lincoln. These lines have been previously subjected to high-density genotyping and scored for a core set of 13 phenotypes in field trials across 13 North American states in 2 years by the Genomes 2 Fields Consortium. A total of 485 GB of image data including RGB, hyperspectral, fluorescence, and thermal infrared photos has been released. Conclusions Correlations between image-based measurements and manual measurements demonstrated the feasibility of quantifying variation in plant architecture using image data. However, naive approaches to measuring traits such as biomass can introduce nonrandom measurement errors confounded with genotype variation. Analysis of hyperspectral image data demonstrated unique signatures from stem tissue. Integrating heritable phenotypes from high-throughput phenotyping data with field data from different environments can reveal previously unknown factors that influence yield plasticity

Right upper lobe segmentectomy and subsegmentectomy guided by classification pattern of peripheral segmental veins

BackgroundStudies have analyzed the simplified branching pattern of peripheral segmental veins and developed a standardized approach for intersegmental vein identification in the right upper lobe (RUL). However, the identification approach of intersubsegmental veins has not been reported. This study aimed to supplement the identification approach of intersubsegmental veins and the classification pattern of peripheral segmental veins by using three-dimensional computed tomography bronchography and angiography (3D-CTBA).Materials and methodsA total of 600 patients with ground glass opacity (GGO) who had undergone 3D-CTBA preoperatively at Hebei General Hospital between September 2020 and September 2022 were used for the retrospective study. We reviewed the anatomical variations of RUL veins in these patients using 3D-CTBA images.ResultsAccording to the anatomical position, the peripheral segmental veins structures of RUL were classified into five categories: “Iab type of anterior with central vein” (256/600, 42.7%), “Ib type of anterior with central vein” (166/600, 27.7%), “Central vein type” (38/600, 6.3%), “Anterior vein type” (81/600, 13.5%), “Right top pulmonary vein type” (57/600, 9.5%). The approach for intersegmental vein and intersubsegmental veins identification was divided into five types: anterior approach, posterobronchial approach, central vein approach, V2t approach, and intermediate bronchus posterior surface approach.ConclusionsThe classification pattern of peripheral segmental veins should find wide application. Further, approaches identifying intersegmental veins and intersubsegmental veins may help thoracic surgeons perform safe and accurate RUL segmentectomy

ModelScope-Agent: Building Your Customizable Agent System with Open-source Large Language Models

Large language models (LLMs) have recently demonstrated remarkable capabilities to comprehend human intentions, engage in reasoning, and design planning-like behavior. To further unleash the power of LLMs to accomplish complex tasks, there is a growing trend to build agent framework that equips LLMs, such as ChatGPT, with tool-use abilities to connect with massive external APIs. In this work, we introduce ModelScope-Agent, a general and customizable agent framework for real-world applications, based on open-source LLMs as controllers. It provides a user-friendly system library, with customizable engine design to support model training on multiple open-source LLMs, while also enabling seamless integration with both model APIs and common APIs in a unified way. To equip the LLMs with tool-use abilities, a comprehensive framework has been proposed spanning over tool-use data collection, tool retrieval, tool registration, memory control, customized model training, and evaluation for practical real-world applications. Finally, we showcase ModelScopeGPT, a real-world intelligent assistant of ModelScope Community based on the ModelScope-Agent framework, which is able to connect open-source LLMs with more than 1000 public AI models and localized community knowledge in ModelScope. The ModelScope-Agent library\footnote{https://github.com/modelscope/modelscope-agent} and online demo\footnote{https://modelscope.cn/studios/damo/ModelScopeGPT/summary} are now publicly available