Profiling of the gut, skin and nasal microbiotas revealed clinically relevant microbial taxa from children with allergies: a pilot study.

Background: A reduction in biodiversity and alterations in the microbiota composition are relevant to allergic diseases. However, combined analyses of the skin, nasal and gut microbiotas are lacking in the literature. In addition, in previous studies, microbiota were detected mainly by V3-V4 sequencing, but other sequences might be missed with this technique.

Machine learning, clinical-radiomics approach with HIM for hemorrhagic transformation prediction after thrombectomy and treatment.

Background: This study aimed to develop a clinical-radiomics model using hyperattenuated imaging markers (HIM), characterized by hyperattenuation on head non-contrast computed tomography immediately after thrombectomy, to predict the risk of hemorrhagic transformation (HT) in patients undergoing endovascular mechanical thrombectomy (MT).

Methods: A total of 159 consecutive patients with HIM were screened immediately after MT for inclusion. The datasets were randomly divided into training and test cohorts at a ratio of 8:2.

Gap-free genome assemblies of two Pyrus bretschneideri cultivars and GWAS analyses identify a CCCH zinc finger protein as a key regulator of stone cell formation in pear fruit.

The Chinese white pear (Pyrus bretschneideri) is an economically significant fruit crop worldwide. Previous versions of the P. bretschneideri genome assembly contain numerous gaps and unanchored genetic regions.

Opportunities and challenges in the application of single-cell transcriptomics in plant tissue research.

Single-cell transcriptomics overcomes the limitations of conventional transcriptome methods by isolating and sequencing RNA from individual cells, thus capturing unique expression values for each cell. This technology allows unprecedented precision in observing the stochasticity and heterogeneity of gene expression within cells. However, single-cell RNA sequencing (scRNA-seq) experiments often fail to capture all cells and genes comprehensively, and single-modality data is insufficient to explain cell states and systemic changes.

Do LLMs Have Visualization Literacy? An Evaluation on Modified Visualizations to Test Generalization in Data Interpretation.

In this paper, we assess the visualization literacy of two prominent Large Language Models (LLMs): OpenAI's Generative Pretrained Transformers (GPT), the backend of ChatGPT, and Google's Gemini, previously known as Bard, to establish benchmarks for assessing their visualization capabilities. While LLMs have shown promise in generating chart descriptions, captions, and design suggestions, their potential for evaluating visualizations remains under-explored. Collecting data from humans for evaluations has been a bottleneck for visualization research in terms of both time and money, and if LLMs were able to serve, even in some limited role, as evaluators, they could be a significant resource.

Deep Learning-Assisted Diagnosis of Malignant Cerebral Edema Following Endovascular Thrombectomy.

Background: Malignant cerebral edema (MCE) is a significant complication following endovascular thrombectomy (EVT) in the treatment of acute ischemic stroke. This study aimed to develop and validate a deep learning-assisted diagnosis model based on the hyperattenuated imaging marker (HIM), characterized by hyperattenuation on head non-contrast computed tomography immediately after thrombectomy, to facilitate radiologists in predicting MCE in patients receiving EVT.

Methods: This study included 271 patients, with 168 in the training cohort, 43 in the validation cohort, and 60 in the prospective internal test cohort.

Gastrointestinal bleeding after pancreatoduodenectomy: Report of four cases.

Background: Postpancreatectomy hemorrhage is one of the most severe and life-threatening complications after pancreaticoduodenectomy. We present four cases of gastrointestinal bleeding patients to clarify its appropriate treatment and prevention.

Case Summary: The main symptoms included black stool, hematochezia, haematemesis, blood in the nasogastric tube, and hemorrhagic shock.

gene integration into regulatory networks via interaction with conserved genes in peach.

genes can evolve "from scratch" from noncoding sequences, acquiring novel functions in organisms and integrating into regulatory networks during evolution to drive innovations in important phenotypes and traits. However, identifying genes is challenging, as it requires high-quality genomes from closely related species. According to the comparison with nine closely related genomes, we determined at least 178 genes in "baifeng".

Large-scale calcium imaging reveals a systematic V4 map for encoding natural scenes.

Biological visual systems have evolved to process natural scenes. A full understanding of visual cortical functions requires a comprehensive characterization of how neuronal populations in each visual area encode natural scenes. Here, we utilized widefield calcium imaging to record V4 cortical response to tens of thousands of natural images in male macaques.

A Survey of Designs for Combined 2D+3D Visual Representations.

We examine visual representations of data that make use of combinations of both 2D and 3D data mappings. Combining 2D and 3D representations is a common technique that allows viewers to understand multiple facets of the data with which they are interacting. While 3D representations focus on the spatial character of the data or the dedicated 3D data mapping, 2D representations often show abstract data properties and take advantage of the unique benefits of mapping to a plane.

The blood routine test holds screening values for influenza A in 2023: a retrospective study.

Background: Influenza A is the most common viral pathogen isolated from pediatric clinics during influenza seasons. Some young patients with influenza manifest rapid progression with high fever and severe sequelae, such as pneumonia and meningitis. Therefore, early diagnosis and prompt treatment are highly important.

Transcription factor PbMYB80 regulates lignification of stone cells and undergoes RING finger protein PbRHY1-mediated degradation in pear fruit.

The Chinese white pear (Pyrus bretschneideri) fruit carries a high proportion of stone cells, adversely affecting fruit quality. Lignin is a main component of stone cells in pear fruit. In this study, we discovered that a pear MYB transcription factor, PbMYB80, binds to the promoters of key lignin biosynthesis genes and inhibits their expression.

Visualizing and Comparing Machine Learning Predictions to Improve Human-AI Teaming on the Example of Cell Lineage.

We visualize the predictions of multiple machine learning models to help biologists as they interactively make decisions about cell lineage-the development of a (plant) embryo from a single ovum cell. Based on a confocal microscopy dataset, traditionally biologists manually constructed the cell lineage, starting from this observation and reasoning backward in time to establish their inheritance. To speed up this tedious process, we make use of machine learning (ML) models trained on a database of manually established cell lineages to assist the biologist in cell assignment.