Biology subjects

Hatch, A.

Publications and source records attributed to Hatch, A..

4 recordsLinked to original sources

bioRxiv2024

Building Brains for Robots: A Hands-On Approach to Learning Neuroscience in the Classroom

As the relevance of neuroscience in education grows, effective methods for teaching this complex subject in high school classrooms remain elusive. Integrating classroom experiments with brain-based robots offers a promising solution. This paper presents a structured curriculum designed around the use of camera-equipped mobile robots which enables students to construct and explore artificial neural networks. Through this hands-on approach, students engage directly with core concepts in neuroscience, learning to model spiking neural networks, decision-making processes in the basal ganglia, and principles of learning and memory. The curriculum not only makes challenging neuroscience concepts accessible and engaging but also demonstrates significant improvements in students understanding and self-efficacy. By detailing the curriculums development, implementation, and educational outcomes, this study outlines a scalable model for incorporating advanced scientific topics into secondary education, paving the way for a deeper student understanding of both theoretical neuroscience and its practical applications.

scientific communication and education↗

bioRxiv2020

A clinically validated human capillary blood transcriptome test for global systems biology studies

Chronic diseases are the leading cause of morbidity and mortality globally. Yet, the majority of them have unknown etiologies, and genetic contribution is weak. In addition, many of the chronic diseases go through the cycles of relapse and remission, during which the genomic DNA does not change. This strongly suggests that human gene expression is the main driver of chronic disease onset and relapses. To identify the etiology of chronic diseases and develop more effective preventative measures, a comprehensive gene expression analysis of the human body is needed. Blood tissue is easy to access and contains a large number of expressed genes involved in many fundamental aspects of our physiology. We report here the development of a whole blood transcriptome clinical test that is high throughput, automated, inexpensive, and clinically validated. The test requires only 50 microliters of blood from a finger prick, enabling access by diverse populations that have been traditionally under-represented in clinical research. The transcripts in the samples are preserved at the time of collection and can be stored and/or transported at ambient temperatures for up to 28 days. The sample preservative protects integrity, while also inactivating all pathogens (bacteria, fungi, and viruses), enabling safe transportation globally. Given its unique set of usability features and clinical performance, this test should be integrated into longitudinal, population-scale, systems biology studies.

systems biology↗

bioRxiv2020

A Precision Medicine Approach to Stress Testing Using Metabolomics and MicroRibonucleic Acids

BackgroundAcute coronary syndrome (ACS) is a growing global health problem, and precision medicine techniques hold promise for the development of diagnostic indicators of ACS. In this pilot, we sought to assess the utility of an integrated analysis of metabolomic and microRNA data in peripheral blood to distinguish patients with abnormal cardiac stress testing from matched controls. MethodsWe used prospectively collected samples from emergency department (ED) patients placed in an ED-based observation unit who underwent stress testing for ACS. We isolated microRNA and quantified metabolites from plasma collected before and after stress testing in patients with myocardial ischemia on stress testing versus those with normal stress tests. The combined metabolomic and microRNA data were analyzed jointly for case (ischemia) and 1:1 matched control patients in a supervised, dimension-reducing discriminant analysis. Two integrative models were implemented: a baseline model utilizing data collected prior to stress-testing (T0) and a stress-delta model, which included the difference between post-stress test (T1) and pre-stress test (T0). ResultsSeven case patients with myocardial ischemia on ED cardiac stress testing (6 females, 85% Caucasian, mean Thrombolysis In Myocardial Infarction Score=3, 4 patients ultimately received percutaneous coronary intervention) were 1:1 age and sex-matched to controls. Several metabolites and microRNAs were differentially expressed between cases and controls. Integrative analysis of the baseline levels of metabolites and microRNA expression showed modest performance for distinguishing cases from controls with an overall error rate of 0.143. The stress-delta model showed worse performance for distinguishing cases from controls, with an overall error rate of 0.500. ConclusionsGiven our small sample size, results are hypothesis-generating. However, this pilot study shows a potential method for a precision medicine approach to cardiac stress testing in patients undergoing workup for ACS.

physiology↗

bioRxiv2019

A robust metatranscriptomic technology for population-scale studies of diet, gut microbiome, and human health

A functional readout of the gut microbiome is necessary to enable precise control of the gut microbiomes functions, which support human health and prevent or minimize a wide range of chronic diseases. Stool metatranscriptomic analysis offers a comprehensive functional view of the gut microbiome, but despite its usefulness, it has rarely been used in clinical studies due to its complexity, cost, and bioinformatic challenges. This method has also received criticism due to potential intra-sample variability, rapid changes, and RNA degradation. Here, we describe a robust and automated stool metatranscriptomic method, called Viomega, which was specifically developed for population-scale studies. Viomega includes sample collection, ambient temperature sample preservation, total RNA extraction, physical removal of ribosomal RNAs (rRNAs), preparation of directional Illumina libraries, Illumina sequencing, taxonomic classification based on a database of >110,000 microbial genomes, and quantitative microbial gene expression analysis using a database of ~100 million microbial genes. We applied this method to 10,000 human stool samples, and performed several small-scale studies to demonstrate sample stability and consistency. In summary, Viomega is an inexpensive, high throughput, automated, and accurate sample-to-result stool metatranscriptomic technology platform for large-scale studies and a wide range of applications.

systems biology↗