Graphical User Interface

The open-source console MaRCoS, which stands for "Magnetic Resonance Control System", combines hardware, firmware and software elements for integral control of Magnetic Resonance Imaging (MRI) scanners. Previous developments have focused on making the system robust and reliable, rather than on users, who have been somewhat overlooked. This work describes a Graphical User Interface (GUI) designed for intuitive control of MaRCoS, as well as compatibility with clinical environments. The GUI is based on an arrangement of tabs and a renewed Application Program Interface (API)...

Transcriptomic analyses across large scales of evolutionary distance have great potential to shed light on regulatory evolution but are complicated by difficulties in establishing orthology and limited availability of accessible software. We introduce here a method and a graphical user interface wrapper, called Annotator-RNAtor, for performing interspecies transcriptomic analysis and studying intragenus evolution. The pipeline uses third-party software to infer homologous genes in various species and highlight differences in the expression of the core-genes...

UNLABELLED: Segmentation of neural somata is a crucial and usually the most time-consuming step in the analysis of optical functional imaging of neuronal microcircuits. In recent years, multiple auto-segmentation tools have been developed to improve the speed and consistency of the segmentation process, mostly, using deep learning approaches. Current segmentation tools, while advanced, still encounter challenges in producing accurate segmentation results, especially in datasets with a low signal-to-noise ratio...

Nasopalatine duct cysts are difficult to detect on panoramic radiographs due to obstructive shadows and are often overlooked. Therefore, sensitive detection using panoramic radiography is clinically important. This study aimed to create a trained model to detect nasopalatine duct cysts from panoramic radiographs in a graphical user interface-based environment. This study was conducted on panoramic radiographs and CT images of 115 patients with nasopalatine duct cysts. As controls, 230 age- and sex-matched patients without cysts were selected from the same database...

Recent advancements in contact map-based protein three-dimensional (3D) structure prediction have been driven by the evolution of deep learning algorithms. However, the gap in accessible software tools for novices in this domain remains a significant challenge. This study introduces GoFold, a novel, standalone graphical user interface (GUI) designed for beginners to perform contact map overlap (CMO) problems for better template selection. Unlike existing tools that cater more to research needs or assume foundational knowledge, GoFold offers an intuitive, user-friendly platform with comprehensive tutorials...

Analysis of local field potentials (LFPs) is important for understanding how ensemble neurons function as a network in a specific region of the brain. Despite the availability of tools for analyzing LFP data, there are some missing features such as analysis of high frequency oscillations (HFOs) and spatial properties. In addition, accessibility of most tools is restricted due to closed source code and/or high costs. To overcome these issues, we have developed two freely available tools that make temporal and spatial analysis of LFP data easily accessible...

As a natural adsorbent material, bentonite is widely used in the field of heavy metal adsorption. The heavy metal adsorption capacity of bentonite varies significantly in studies due to the differences in the properties of bentonite, solution, and heavy metal. To achieve accurate predictions of bentonite's heavy metal adsorption capacity, this study employed six machine learning (ML) regression algorithms to investigate the adsorption characteristics of bentonite. Finally, an eXtreme Gradient Boosting Regression (XGB) model with outstanding predictive performance was constructed...

Hemolytic peptides can trigger hemolysis by rupturing red blood cells' membranes and triggering cell disruption. Due to the labor-intensive and time-consuming in-lab identification process, accurate, high-throughput hemolytic peptide prediction is crucial for the growth of peptide sequence data in proteomics and peptidomics. In this study, we offer the HemoDL ensemble learning model, which learns the distinct distribution of sequence characteristics for predicting the hemolytic activity of peptides using a double LightGBM framework...

Although previous studies have acknowledged the potential of geographic information systems (GIS) and social media data (SMD) in assessment of exposure to various environmental risks, none has presented a simple, effective and user-friendly tool. This study introduces a conceptual model that integrates individual mobility patterns extracted from social media, with the geographic footprints of infectious diseases and other environmental agents utilizing GIS. The efficacy of the model was independently evaluated for selected case studies involving lead in the ground; particulate matter in the air; and an infectious, viral disease (COVID- 19)...

Asparagine (Asn) deamidation and aspartic acid (Asp) isomerization are common degradation pathways that affect the stability of therapeutic antibodies. These modifications can pose a significant challenge in the development of biopharmaceuticals. As such, the early engineering and selection of chemically stable monoclonal antibodies (mAbs) can substantially mitigate the risk of subsequent failure. In this study, we introduce a novel in silico approach for predicting deamidation and isomerization sites in therapeutic antibodies by analyzing the structural environment surrounding asparagine and aspartate residues...

Chromotherapy rooms (CRs) are physical spaces with colored lights able to enhance an individual's mood, well-being, and, in the long term, their health. Virtual reality technology can be used to implement CR (VRCRs) and provide higher flexibility at lower costs. However, existing VRCRs are limited to a few use cases, and they do not fully explore the potential and pitfalls of the technology. This work contributes by comparing three VRCR designs: empty, static, and dynamic. Empty is just a void but a blue-colored environment...

Deep learning methods have emerged as powerful tools for analyzing histopathological images, but current methods are often specialized for specific domains and software environments, and few open-source options exist for deploying models in an interactive interface. Experimenting with different deep learning approaches typically requires switching software libraries and reprocessing data, reducing the feasibility and practicality of experimenting with new architectures. We developed a flexible deep learning library for histopathology called Slideflow, a package which supports a broad array of deep learning methods for digital pathology and includes a fast whole-slide interface for deploying trained models...

Curation of biomedical knowledge into systems biology diagrammatic or computational models is essential for studying complex biological processes. However, systems-level curation is a laborious manual process, especially when facing ever-increasing growth of domain literature. New findings demonstrating elaborate relationships between multiple molecules, pathways and cells have to be represented in a format suitable for systems biology applications. Importantly, curation should capture the complexity of molecular interactions in such a format together with annotations of the involved elements and support stable identifiers and versioning...

The vast amount of genome sequence data that is available, and that is predicted to drastically increase in the near future, can only be efficiently dealt with by building automated pipelines. Indeed, the Earth Biogenome Project will produce high-quality reference genome sequences for all 1.8 million named living eukaryote species, providing unprecedented insight into the evolution of genes and gene families, and thus on biological issues. Here, new modules for gene annotation, further BLAST search algorithms, further multiple sequence alignment methods, the adding of reference sequences, further tree rooting methods, the estimation of rates of synonymous and nonsynonymous substitutions, and the identification of positively selected amino acid sites, have been added to auto-phylo (version 2), a recently developed software to address biological problems using phylogenetic inferences...

This article examines the choices between sitting and standing in virtual reality (VR) experiences, addressing conflicts, challenges, and opportunities. It explores issues such as the risk of motion sickness in stationary users and virtual rotations, the formation of mental models, consistent authoring, affordances, and the integration of embodied interfaces for enhanced interactions. Furthermore, it delves into the significance of multisensory integration and the impact of postural mismatches on immersion and acceptance in VR...

Recent advances in iterative neural network analyses (e.g., AlphaFold2 and RoseTTA fold) have been revolutionary for protein 3D structure prediction, especially for difficult-to-manipulate α-helical/β-barrel integral membrane proteins. These model structures are calculated based on the coevolution of amino acids within the protein of interest and similarities to existing protein structures; the local effects of the membrane on folding and stability of the calculated model structures are not considered...

BACKGROUND: The dramatic increase of drug-resistant bacteria necessitates urgent development of platforms to simultaneously detect and inactivate bacteria causing wound infections, but are confronted with various challenges. Delta amino levulinic acid (ALA) induced protoporphyrin IX (PpIX) can be a promising modality for simultaneous bioburden diagnostics and therapeutics. Herein, we report utility of ALA induced protoporphyrin (PpIX) based simultaneous bioburden detection, photoinactivation and therapeutic outcome assessment in methicillin resistant Staphylococcus aureus (MRSA) infected wounds of mice...

Background: The scarcity of medical resources and personnel has worsened due to COVID-19. Telemedicine faces challenges in assessing wounds without physical examination. Evaluating pressure injuries is time consuming, energy intensive, and inconsistent. Most of today's telemedicine platforms utilize graphical user interfaces with complex operational procedures and limited channels for information dissemination. The study aims to establish a smart telemedicine diagnosis system based on YOLOv7 and large language model...

Droplet generation technology has become increasingly important in a wide range of applications, including biotechnology and chemical synthesis. T-junction channels are commonly used for droplet generation due to their integration capability of a larger number of droplet generators in a compact space. In this study, a finite element analysis (FEA) approach is employed to simulate droplet production and its dynamic regimes in a T-junction configuration and collect data for post-processing analysis. Next, image analysis was performed to calculate the droplet length and determine the droplet generation regime...

BACKGROUND: The eCOVID19 Recommendations Map & Gateway to Contextualization (RecMap) website was developed to identify all COVID-19 guidelines, assess the credibility and trustworthiness of the guidelines, and make recommendations understandable to various stakeholder groups. To date, little has been done to understand and explore parents' experiences when accessing and using the RecMap website for COVID-19 health decision-making. OBJECTIVE: To explore (1) where parents look for COVID-19 health information and why, (2) parents' user experience when accessing and using the RecMap website to make health decisions, and (3) what knowledge mobilization activities are needed to increase parents' awareness, use, and engagement with the RecMap website...