algorithms

Conventional B-mode ultrasound imaging has difficulty in delineating homogeneous soft tissues with similar acoustic impedances, as the reflectivity depends on the acoustic impedance at the interface. As a quantitative imaging biomarker sensitive to alteration of biomechanical properties, speed-of-sound (SoS) holds promising potential for tissue and disease differentiation such as delineation of different breast tissue types with similar acoustic impedance. Compared to two-dimensional (2D) SoS images, three-dimensional (3D) volumetric SoS images achieved through a full-angle ultrasound scan can reveal more intricate morphological structures of tissues; however, they generally require a ring transducer...

An efficient algorithm for compressing a given many-body potential energy surface (PES) of molecular systems into a grid-based matrix product operator (MPO) is proposed. The PES is once represented by a full-dimensional or truncated many-body expansion form, which is obtained by ab initio calculations at each grid mesh point, and then all terms in the expansion are compressed and merged into a single MPO while maintaining the bond dimension of the MPO as small as possible. It was shown that the ab initio PES of the H2 CO was compressed by more than 2 orders of magnitude in the size of the site operators without loss of accuracy...

Transcription factor RBPJ is the central component in Notch signal transduction and directly forms a coactivator complex together with the Notch intracellular domain (NICD). While RBPJ protein levels remain constant in most tissues, dynamic expression of Notch target genes varies depending on the given cell-type and the Notch activity state. To elucidate dynamic RBPJ binding genome-wide, we investigated RBPJ occupancy by ChIP-Seq. Surprisingly, only a small set of the total RBPJ sites show a dynamic binding behavior in response to Notch signaling...

BACKGROUND AND AIMS: High-power-short-duration (HPSD) ablation is an effective treatment for atrial fibrillation but poses risks of thermal injuries to the oesophagus and vagus nerve. This study investigates incidence and predictors of thermal injuries, employing machine learning. METHODS: A prospective observational study was conducted at Leipzig Heart Centre, Germany, excluding patients with multiple prior ablations. All patients received Ablation Index guided HPSD ablation and subsequent oesophagogastroduodenoscopy...

OBJECTIVES: To assess whether meal or water intake may affect the measurement of the ultrasound (US) attenuation coefficient (AC) imaging, a parameter that is directly related to liver fat content. METHODS: The study was performed in two centers (Italy and USA). AC was obtained using the ATI algorithm implemented in the Aplio i-series US systems (Canon Medical Systems, Japan) by one operator at each center. Measurements were performed at baseline and 5, 15, 30, 45 minutes after drinking 500 mL of water (group 1), or 30, 45, 60, 90, 120 minutes after eating a meal of about 600 kcal (group 2)...

Wearable inertial measurement units (IMUs) are used increasingly to estimate biomechanical exposures in lifting-lowering tasks. The objective of the study was to develop and evaluate predictive models for estimating relative hand loads and two other critical biomechanical exposures to gain a comprehensive understanding of work-related musculoskeletal disorders in lifting. We collected 12,480 lifting-lowering phases from 26 subjects (15 men and 11 women) performing manual lifting-lowering tasks with hand loads (0-22...

As living standards rise, more and more people are paying attention to their own health, especially issues such as cerebral thrombosis, cerebral infarction, and other cerebral blood flow problems. An accurate simulation of blood flow within cerebral vessels has emerged as a crucial area of research. In this study, we focus on microcirculatory blood flow in ischemic brain tissue and employ a 0D-1D geometric multi-scale coupled model to characterize this process. Given the intricate nature of human cerebral vessels, we apply a numerical method combining the finite element method and the third-order Runge-Kutta method to resolve the coupled model...

BACKGROUND: Insulin-naive subjects with type 2 diabetes (T2D) start basal insulin titration from a low initial insulin dose (IID), which is adjusted weekly or twice per week based on fasting plasma glucose (FPG) measurement as recommended by the American Diabetes Association (ADA). The procedure to reach the optimal insulin dose (OID) is time-consuming, especially in subjects with high insulin needs (HIN). The aim of this study is to provide a fast and effective, but still safe, insulin titration algorithm in insulin-naive T2D subjects with HIN...

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BACKGROUND: Luteolin, a common dietary flavonoid found in plants, has been shown to have anti-cancer properties. However, its exact mechanisms of action in non-small cell lung cancer (NSCLC) are still not fully understood, particularly its role in regulating broader genomic networks and specific gene targets. In this study, we aimed to elucidate the role of microRNAs (miRNAs) in NSCLC treated with luteolin, using A549 cells as a model system. MATERIALS AND METHODS: miRNA profiling was conducted on luteolin-treated A549 cells using Exiqon microarrays, with validation of selected miRNAs by qRT-PCR...

BACKGROUND: The comprehensive expression level and potential molecular role of Cyclin A2 (CCNA2) in uterine corpus endometrial carcinoma (UCEC) remains undiscovered. METHODS: UCEC and normal endometrium tissues from in-house and public databases were collected for investigating protein and messenger RNA expression of CCNA2. The transcription factors of CCNA2 were identified by the Cistrome database. The prognostic significance of CCNA2 in UCEC was evaluated through univariate and multivariate Cox regression as well as Kaplan-Meier curve analysis...

The initial enthusiasm about computational pathology (CP) and artificial intelligence (AI) was that they will replace pathologists entirely on the way to fully automated diagnostics. It is becoming clear that currently this is not the immediate model to pursue. On top of the legal and regulatory complexities surrounding its implementation, the majority of tested machine learning (ML)-based predictive algorithms do not display the exquisite performance needed to render them unequivocal, standalone decision makers for matters with direct implications to human health...

The field of theranostics is rapidly advancing, driven by the goals of enhancing patient care. Recent breakthroughs in artificial intelligence (AI) and its innovative theranostic applications have marked a critical step forward in nuclear medicine, leading to a significant paradigm shift in precision oncology. For instance, AI-assisted tumor characterization, including automated image interpretation, tumor segmentation, feature identification, and prediction of high-risk lesions, improves diagnostic processes, offering a precise and detailed evaluation...

PURPOSE: To develop a rib and clavicle fracture detection model for chest radiographs in trauma patients using a deep learning (DL) algorithm. MATERIALS AND METHODS: We retrospectively collected 56 145 chest X-rays (CXRs) from trauma patients in a trauma center between August 2008 and December 2016. A rib/clavicle fracture detection DL algorithm was trained using this data set with 991 (1.8%) images labeled by experts with fracture site locations. The algorithm was tested on independently collected 300 CXRs in 2017...

The objective of this observational study was to evaluate the efficacy of a neck-mounted automated activity monitor (AAM) at detecting early postpartum resumed ovarian cyclicity. A total of 192 lactating cows (primiparous = 73 and multiparous = 119) were enrolled in this study. Cows were continuously monitored by a neck-mounted AAM early postpartum (7 to 30 d in milk; DIM). Calving was classified as assisted (forced extraction of a calf) or unassisted (normal calving). Retained fetal membrane, metritis, hyperketonemia, clinical mastitis, and milk production were recorded...

Major histocompatibility complex Class II (MHCII) proteins initiate and regulate immune responses by presentation of antigenic peptides to CD4+ T-cells and self-restriction. The interactions between MHCII and peptides determine the specificity of the immune response and are crucial in immunotherapy and cancer vaccine design. With the ever-increasing amount of MHCII-peptide binding data available, many computational approaches have been developed for MHCII-peptide interaction prediction over the last decade...

Transformer neural networks show promising capabilities, in particular for uses in materials analysis, design, and manufacturing, including their capacity to work effectively with human language, symbols, code, and numerical data. Here, we explore the use of large language models (LLMs) as a tool that can support engineering analysis of materials, applied to retrieving key information about subject areas, developing research hypotheses, discovery of mechanistic relationships across disparate areas of knowledge, and writing and executing simulation codes for active knowledge generation based on physical ground truths...

Traditional pharmaceutical manufacturing processes for solid oral dosage forms can be inefficient and have been known to produce a large amount of undesired product. With the progressing trend of achieving carbon neutrality, there is an impetus to increase the energy efficiency of these manufacturing processes while maintaining the critical quality attributes of the product. One of the important steps in downstream pharmaceutical manufacturing is wet granulation, and within that, twin screw granulation (TSG) is a popular continuous manufacturing technique...

BACKGROUND: The shift towards milder strokes and studies suggesting that stroke symptoms vary by age and sex may challenge the Face-Arm-Speech Time (FAST) coverage. We aimed to study the proportion of stroke cases admitted with FAST symptoms, sex and age differences in FAST presentation and explore any additional advantage of including new item(s) from the National Institute of Health Stroke Scale (NIHSS) to the FAST algorithm. METHODS: This registry-based study included patients admitted with acute stroke to Sahlgrenska University Hospital (November 2014 to June 2019) with NIHSS items at admission...

Organoid Intelligence ushers in a new era by seamlessly integrating cutting-edge organoid technology with the power of artificial intelligence. Organoids, three-dimensional miniature organ-like structures cultivated from stem cells, offer an unparalleled opportunity to simulate complex human organ systems in vitro. Through the convergence of organoid technology and AI, researchers gain the means to accelerate discoveries and insights across various disciplines. Artificial intelligence algorithms enable the comprehensive analysis of intricate organoid behaviors, intricate cellular interactions, and dynamic responses to stimuli...