Human learning

BACKGROUND: Motif finding in Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) data is essential to reveal the intricacies of transcription factor binding sites (TFBSs) and their pivotal roles in gene regulation. Deep learning technologies including convolutional neural networks (CNNs) and graph neural networks (GNNs), have achieved success in finding ATAC-seq motifs. However, CNN-based methods are limited by the fixed width of the convolutional kernel, which makes it difficult to find multiple transcription factor binding sites with different lengths...

Central fatigue is a common pathological state characterized by psychological loss of drive, lack of appetite, drowsiness, and decreased psychic alertness. The mechanism underlying central fatigue is still unclear, and there is no widely accepted successful animal model that fully represents human characteristics. We aimed to construct a more clinically relevant and comprehensive animal model of central fatigue. In this study, we utilized the Modified Multiple Platform Method (MMPM) combined with alternate-day fasting (ADF) to create the animal model...

Virtual fencing technology provides an opportunity to rethink the management of intensive grazing systems in general, yet most studies have used products developed and applied to more extensive livestock systems. This research aimed to assess the application of a virtual fencing technology developed for the intensive pastoral dairy industry. The Halter system uses 2 primary cues, sound and vibration, and one aversive secondary cue, a low energy electrical pulse, to confine cows to a pasture allocation and remotely herd cows...

RATIONALE AND OBJECTIVE: Avoidance of opioid withdrawal plays a key role in human opioid addiction. Here, we present a procedure for studying operant negative reinforcement in rats that was inspired by primate procedures where opioid-dependent subjects lever-press to prevent naloxone infusions. METHODS: In Experiment 1, we trained rats (n = 30, 15 females) to lever-press to escape and then avoid mild footshocks (0.13-0.27 mA) for 35 days (30 trials/d)...

Virtual reality (VR) has increasingly been used in several disciplines, including nursing, a profession in high demand that is now facing a shortage. This study investigated the effectiveness and efficacy of VR hybrid training over traditional training (TR) methods. Sixteen college students were recruited and randomly assigned to get 100% TR or 50% TR and 50% VR (VR50). Participants attended a three-day program with a registered nurse, consisting of lectures and practical lab sessions. Participants' performance, training time, cognitive development, physical development, mental workload, user experience, Students' Satisfaction and Self-Confidence, and team learning were evaluated...

Microscopy is integral to medical research, facilitating the exploration of various biological questions, notably cell quantification. However, this process's time-consuming and error-prone nature, attributed to human intervention or automated methods usually applied to fluorescent images, presents challenges. In response, machine learning algorithms have been integrated into microscopy, automating tasks and constructing predictive models from vast datasets. These models adeptly learn representations for object detection, image segmentation, and target classification...

While disgust originates in the hard-wired mammalian distaste response, the conscious experience of disgust in humans strongly depends on subjective appraisal and may even extend to socio-moral contexts. Here, in a series of studies, we combined functional magnetic resonance imaging with machine-learning-based predictive modelling to establish a comprehensive neurobiological model of subjective disgust. The developed neurofunctional signature accurately predicted momentary self-reported subjective disgust across discovery (n = 78) and pre-registered validation (n = 30) cohorts and generalized across core disgust (n = 34 and n = 26), gustatory distaste (n = 30) and socio-moral (unfair offers; n = 43) contexts...

OBJECTIVES: ChatGPT is an innovative artificial intelligence designed to enhance human activities and serve as a potent tool for information retrieval. This study aimed to evaluate the performance and limitation of ChatGPT on fourth-year pharmacy student examination. METHODS: This cross-sectional study was conducted on February 2023 at the Faculty of Pharmacy, Chiang Mai University, Thailand. The exam contained 16 multiple-choice questions and 2 short-answer questions, focusing on classification and medical management of shock and electrolyte disorders...

RATIONALE AND OBJECTIVES: To develop and validate a nomogram that combines contrast-enhanced spectral mammography (CESM) deep learning with clinical-pathological features to predict neoadjuvant chemotherapy (NAC) response (either low Miller Payne (MP-L) grades 1-2 or high MP (MP-H) grades 3-5) in patients with ER-positive/HER2-negative breast cancer. MATERIALS AND METHODS: In this retrospective study, 265 breast cancer patients were randomly allocated into training and test sets (used for models training and testing, respectively) at a 4:1 ratio...

Expression is the main method for judging the emotional state and psychological condition of the human body, and the prediction of changes in facial expressions can effectively determine the mental health of a person, thus avoiding serious psychological or psychiatric disorders due to early negligence. From a computer vision perspective, most researchers have focused on studying facial expression analysis, and in some cases, body posture is also considered. However their performance is more limited under unconstrained natural conditions, which requires more information to be used in human emotion analysis...

Ferroptosis is a programmed form of cell death regulated by iron and has been linked to the development of asthma. However, the precise mechanisms driving ferroptosis in asthma remain elusive. To gain deeper insights, we conducted an analysis of nasal epithelial and sputum samples from the GEO database using three machine learning methods. Our investigation identified a pivotal gene, Arachidonate 15-lipoxygenase (ALOX15), associated with ferroptosis in asthma. Through both in vitro and in vivo experiments, we further confirmed the significant role of ALOX15 in ferroptosis in asthma...

Conventional, brightfield-microscopic semen analysis provides important baseline information about sperm quality of an individual; however, it falls short of identifying subtle subcellular and molecular defects in cohorts of "bad", defective human and animal spermatozoa with seemingly normal phenotypes. To bridge this gap, it is desirable to increase the precision of andrological evaluation in humans and livestock animals by pursuing advanced biomarker-based imaging methods. This review, spiced up with occasional classic movie references but seriously scholastic at the same time, focuses mainly on the biomarkers of altered male germ cell proteostasis resulting in post-testicular carryovers of proteins associated with ubiquitin-proteasome system...

PURPOSE: This review provides an overview of the current state of artificial intelligence (AI) technology for automated detection of breast cancer in digital mammography (DM) and digital breast tomosynthesis (DBT). It aims to discuss the technology, available AI systems, and the challenges faced by AI in breast cancer screening. METHODS: The review examines the development of AI technology in breast cancer detection, focusing on deep learning (DL) techniques and their differences from traditional computer-aided detection (CAD) systems...

The detection of tetracycline antibiotics (TCs) in food holds great significance in minimizing their absorption within the human body. Hence, this study aims to develop a rapid, convenient, real-time, and accurate detection method for detecting antibiotics in an authentic market setting. A colorimetric fluorescence sensor was devised for tetracycline detection utilizing PVA aerogels as the substrate. Its operating principle is based on the IFE effect and antenna effect. A detection device is designed to capture fluorescence images while deep learning was employed to aid in the detection process...

Humans learn concepts both from labeled supervision and by unsupervised observation of patterns, a process machines are being taught to mimic by training on large annotated datasets-a method quite different from the human pathway, wherein few examples with no supervision suffice to induce an unfamiliar relational concept. We introduce a computational model designed to emulate human inductive reasoning on abstract reasoning tasks, such as those in IQ tests, using a minimax entropy approach. This method combines identifying the most effective constraints on data via minimum entropy with determining the best combination of them via maximum entropy...

INTRODUCTION: A dental humanoid robot, SIMROID® , is able to replicate the actions characteristic of human beings and enable training for communicating with patients and coping with unexpected situations. This study assessed user experiences via a survey questionnaire following hands-on training on the SIMROID® . MATERIALS AND METHODS: A total of 112 participants, consisting of 50 high school students who visited AUSD (Asahi University School of Dentistry) to participate in open campus events, 42 fourth-year students at AUSD and 20 dental students from Mexico State Autonomy University, University of Siena and Peking University took the survey...

OBJECTIVE: BACKGROUND: The use of endothelial cell cultures has become fundamental to study angiogenesis. Recent advances in artificial intelligences (AI) offer opportunities to develop automated assessment methods in medical research, analyzing larger datasets. OBJECTIVE: OBJECTIVE: The aim of this study was to compare the application of AI with a manual method to morphometrically quantify in vitro angiogenesis. OBJECTIVE: METHODS: Co-cultures of human microvascular endothelial cells and fibroblasts were incubated mimicking endothelial capillary-beds...

Many physician assistant (PA) students first encounter death in the earliest days of their training when working with cadavers in the gross anatomy laboratory. Developing a deep knowledge of human anatomy is fundamental to health profession training programs and modern medical practice. Despite decreased laboratory hours and integration of technology and diagnostic imaging into modern anatomy courses, there remains value in the cadaver dissection experience. Medical learners experience diverse and complex feelings toward cadavers; learning to regulate one's personal responses within the anatomy laboratory is a skill that can be extrapolated to clinical practice...

Human mesh recovery aims to estimate all human meshes within a given image. In this paper, we propose an Instance-aware Multi-person 3D Human Mesh Recovery (InstaHMR) network based on the one-stage framework. Compared to former one-stage methods, instance-aware single person feature is exploited to represent more accurate human mesh. Specifically, we propose the Contextual Instance Guidance (CIG) module which generates instance-aware single person feature by leveraging spatial and channel attention operations...

The crisis of antibiotic resistance has become a significant global threat to human health. Understanding properties of antibiotic resistance genes (ARGs) is the first step to mitigate this issue. Although many methods have been proposed for predicting properties of ARGs, most of these methods focus only on predicting antibiotic classes, while ignoring other properties of ARGs, such as resistance mechanisms and transferability. However, acquiring all of these properties of ARGs can help researchers gain a more comprehensive understanding of the essence of antibiotic resistance, which will facilitate the development of antibiotics...