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Machine learning model reveals hidden structure of human gut microbiome
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This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"The human gut is home to a diverse community of microbes. Variations in the makeup of this community between individuals have been linked to diseases such as inflammatory bowel disease, diabetes, and cancer. Efforts to understand these differences have revealed three community types, or enterotypes, in humans, each representing the dominance of a single microbe. But because microbes co-mingle with many partners, studying the gut microbiome solely in terms of enterotypes misses on the highly nuanced nature of microbial interactions. Researchers recently addressed that shortcoming using a machine learning technique called latent Dirichlet allocation, or LDA. Their goal was to determine whether and how recurring microbial partnerships, or assemblages, are linked to the three enterotypes. Using gut metagenomic data gathered from 861 healthy adults across 12 countries LDA revealed three assemblages corresponding to each enterotype as well as a fourth wild-card assemblage that could be found in any gut..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

Subject:
Biology
Life Science
Material Type:
Diagram/Illustration
Reading
Provider:
Research Square
Provider Set:
Video Bytes
Date Added:
11/03/2020
Meta-analysis of the robustness and universality of gut microbiome-metabolome associations
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This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Increasing evidence of gut microbe-metabolite-host health interactions has prompted increasing research on the human gut microbiome and metabolome. Statistical and machine learning-based methods have been widely used to identify microbial metabolites that can be modulated to improve gut health, but whether the findings of individual studies are applicable across studies remains unclear. In a recent meta-analysis, researchers searched for metabolites whose levels in the human gut could be reliably predicted from microbiome composition, using a machine learning approach with data processed from 1733 samples in 10 independent studies. While the predictability of many metabolites varied considerably among studies, the search identified 97 robustly well-predicted metabolites that were involved in processes such as bile acid transformation and polyamine metabolism..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

Subject:
Biology
Life Science
Material Type:
Diagram/Illustration
Reading
Provider:
Research Square
Provider Set:
Video Bytes
Date Added:
10/13/2021
New machine learning approach helps scientists understand the microorganisms found in activated sludge
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This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"The activated sludge (AS) process is used to treat sewage or industrial wastewater. In this process, pollutants are removed by a diverse group of microorganisms. Because AS is a unique, controllable engineered ecosystem, its attributes make it attractive to ecologists studying microbial community assembly. A recent study reports a new machine learning approach that can distinguish metagenome-assembled genomes (MAGs) of AS bacteria from those of other environments. Using this method, the researchers identified some functional features that are likely viral for AS bacteria to adapt to treatment bioreactors. They found that few microorganisms are shared between different wastewater treatment plants, although some AS MAGs may have been missed due to short sequencing read length or low sequencing depth..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

Subject:
Biology
Life Science
Material Type:
Diagram/Illustration
Reading
Provider:
Research Square
Provider Set:
Video Bytes
Date Added:
04/24/2020
Novel methodology to predict hypoglycaemia rates with basal insulin in real-world populations
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This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"People with diabetes who require basal insulin to achieve blood glucose control can be at risk of hypoglycaemia, where blood glucose levels drop too low. In randomised clinical trials (or RCTs), use of second-generation basal insulin analogues, such as insulin glargine 300 units/mL (known as glargine 300) and insulin degludec, results in similar glycated haemoglobin reductions compared with first-generation basal insulin analogues, such as glargine 100 and insulin detemir, but with less hypoglycaemia. However, it is not known whether these results translate directly to routine clinical practice, as RCTs often apply strict inclusion and exclusion criteria, meaning that they may not be generalisable to real-life situations. Electronic medical records are a source of rich real-world data, but using them to make comparisons between different treatments can be difficult because results might be biased by confounding data, something that the randomisation in RCTs is designed to minimise..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

Subject:
Applied Science
Biology
Health, Medicine and Nursing
Life Science
Material Type:
Diagram/Illustration
Reading
Provider:
Research Square
Provider Set:
Video Bytes
Date Added:
09/23/2019
OpenML: An R Package to Connect to the Machine Learning Platform OpenML
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OpenML is an online machine learning platform where researchers can easily share data, machine learning tasks and experiments as well as organize them online to work and collaborate more efficiently. In this paper, we present an R package to interface with the OpenML platform and illustrate its usage in combination with the machine learning R package mlr (Bischl et al, 2016). We show how the OpenML package allows R users to easily search, download and upload data sets and machine learning tasks. Furthermore, we also show how to upload results of experiments, share them with others and download results from other users. Beyond ensuring reproducibility of results, the OpenML platform automates much of the drudge work, speeds up research, facilitates collaboration and increases the users’ visibility online.

Subject:
Social Science
Material Type:
Reading
Author:
Benjamin Hofner
Bernd Bischl
Dominik Kirchhoff
Heidi Seibold
Jakob Bossek
Joaquin Vanschoren
Michel Lang
Pascal Kerschke
Giuseppe Casalicchio
Date Added:
11/13/2020
Predicted rates of hypoglycemia with Gla-300 versus first-and
second-generation basal insulin analogs: the real-world LIGHTNING study
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This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Hypoglycemia, or low blood glucose, is an important risk factor for people with type 2 diabetes receiving blood glucose-lowering therapies, such as insulin. It can lead to symptoms that interfere with activities of daily living and can sometimes (though rarely) result in debilitating events, including loss of consciousness. Basal insulins are designed to help maintain stable blood glucose levels throughout the day. Data from randomized clinical trials show that newer, second-generation basal insulin analogs (such as insulin glargine 300 units per mL and insulin degludec) have lower hypoglycemia risk than first- generation basal insulin analogs (such as insulin glargine 100 units per mL and insulin detemir), while providing comparable glycemic control. However, these randomized controlled trials may not truly reflect clinical practice, as they applied strict inclusion and exclusion criteria and were conducted under strict oversight dictated by very specific protocols..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

Subject:
Applied Science
Health, Medicine and Nursing
Material Type:
Diagram/Illustration
Reading
Provider:
Research Square
Provider Set:
Video Bytes
Date Added:
10/04/2019
Predicting acute graft-versus-host-disease in allogeneic stem cell transplantation patients
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This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Allogeneic hematopoietic stem cell transplantation (allo-HSCT) is the transplantation of donor derived stem cells and treats a variety of hematologic and non-hematologic disorders. Allo-HSCT patients exhibit changes in their gut microbiota and experience a range of complications post-treatment, including acute graft-versus-host disease (aGvHD). The potential roles or timing of gut microbiota reestablishment and immunological homeostasis after allo-HSCT are not known. It is also not yet known if the microbiota at other body sites plays a role. Recently, researchers ran an integrated host-microbiota analysis of the gut, oral, and nasal microbiota in children undergoing allo-HSCT. The bacterial diversity decreased in all three sites during the first month. Certain microbial taxa were already different in allo-HSCT patients before transplantation compared to healthy children. Onset of acute GvHD after treatment could be predicted from the pre-treatment microbiota composition at all three body sites..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

Subject:
Biology
Life Science
Material Type:
Diagram/Illustration
Reading
Provider:
Research Square
Provider Set:
Video Bytes
Date Added:
10/13/2021
Predicting heart disease-inducing metabolites from patients' gut microbiomes
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This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"The foods we eat, our biological makeup, and the microbes that dwell in our gut share a highly complex relationship. Sometimes, for example, our resident microbes can turn the beneficial nutrients and drugs we take into harmful substances. That’s the case for L-carnitine, a nutrient found in red meat and supplements, which certain bacteria metabolize into trimethylamine-N-oxide (TMAO), a compound linked to cardiovascular disease. To understand how different individuals’ microbial makeup might predispose them to harmful TMAO production researchers tested 56 individuals who received carnitine supplementation for 1 month. High-TMAO producers showed lower levels of active TMAO, likely because bacteria had already begun to break down a sizeable portion of ingested carnitine. The team also observed that TMAO productivity could be enhanced by carnitine supplementation..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

Subject:
Biology
Life Science
Material Type:
Diagram/Illustration
Reading
Provider:
Research Square
Provider Set:
Video Bytes
Date Added:
02/25/2021
Privacy, Data Sharing and Evidence Based Policy Making
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14. Brave New World: Privacy, Data Sharing and Evidence Based Policy Making

The trifecta of globalization, urbanization and digitization have created new opportunities and challenges across our nation, cities, boroughs and urban centers. Cities in particular are in a unique position at the center of commerce and technology becoming hubs for innovation and practical application of emerging technology. In this rapidly changing 24/7 digitized world, governments are leveraging innovation and technology to become more effective, efficient, transparent and to be able to better plan for and anticipate the needs of its citizens, businesses and community organizations. This class will provide the framework for how cities and communities can become smarter and more accessible with technology and more connected.

Subject:
Business and Communication
Management
Material Type:
Lesson
Provider:
CUNY Academic Works
Provider Set:
Medgar Evers College
Author:
Rhonda S. Binda
Date Added:
10/30/2020
Prying open AI’s black box reveals insights into why cancers recur
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This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Artificial intelligence is making rapid advances in medicine. Already, there are machine learning algorithms that can outperform doctors in some medical fields. There’s only one fairly big problem: experts aren’t quite sure how these algorithms work. While designers know full well what goes into the A-I systems they build and what comes out, the learning part in between is often too complex to comprehend. To their users, machine learning algorithms are effectively black boxes. Now, researchers from the RIKEN Center for Advanced Intelligence Project in Japan are lifting the lid. They’ve developed a deep-learning system that can outperform human experts in predicting whether prostate cancer will reoccur within one year. More importantly, the deep learning system they developed can acquire human-understandable features from unannotated pathology images to offer up critical clues that could help humans make better diagnoses themselves..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

Subject:
Applied Science
Health, Medicine and Nursing
Material Type:
Diagram/Illustration
Reading
Provider:
Research Square
Provider Set:
Video Bytes
Date Added:
10/23/2020
Quantum materials pave the path for synthetic neuroscience
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This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Quantum materials are opening up a realm of possibilities in materials research. Among the best known examples are superconductivity and quantum computing. But that’s only the beginning. The same properties that make these materials unique are also enabling researchers to demystify the inner workings of the human brain. So what makes quantum materials well suited for this purpose? Unlike the free-flowing electrons in ordinary conductors or semiconductors, electrons in quantum materials show correlated behavior. That in itself has been the focus of intense physics research. But the upshot for brain research is tunable electronic behavior that can mimic the electronic signaling of neurons and the synapses between them. Most importantly, quantum materials can simulate synaptic plasticity. Plasticity is the biological ability that makes learning and memory formation possible. It’s all about timing. Connections between neurons that fire within a short, milliseconds-long time window grow stronger..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

Subject:
Applied Science
Engineering
Material Type:
Diagram/Illustration
Reading
Provider:
Research Square
Provider Set:
Video Bytes
Date Added:
09/23/2019
The Shallow and the Deep: A biased introduction to neural networks and old school machine learning
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The Shallow and the Deep is a collection of lecture notes that offers an accessible introduction to neural networks and machine learning in general. However, it was clear from the beginning that these notes would not be able to cover this rapidly changing and growing field in its entirety. The focus lies on classical machine learning techniques, with a bias towards classification and regression. Other learning paradigms and many recent developments in, for instance, Deep Learning are not addressed or only briefly touched upon.

Biehl argues that having a solid knowledge of the foundations of the field is essential, especially for anyone who wants to explore the world of machine learning with an ambition that goes beyond the application of some software package to some data set. Therefore, The Shallow and the Deep places emphasis on fundamental concepts and theoretical background. This also involves delving into the history and pre-history of neural networks, where the foundations for most of the recent developments were laid. These notes aim to demystify machine learning and neural networks without losing the appreciation for their impressive power and versatility.

Subject:
Applied Science
Computer Science
Material Type:
Textbook
Provider:
University of Groningen
Author:
Michael Biehl
Date Added:
10/10/2023
Specialized metabolic functions of keystone taxa sustain soil microbiome stability
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This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"The sustainability of the terrestrial ecosystem depends on the stability of its tiniest residents. The terrestrial microbiome controls functions such as organic carbon turnover, nutrient-use efficiency, and productivity, and losing critical keystone functions may cause dramatic shifts in microbiome composition and function. A recent study sought to better understand the relationship between biodiversity and microbiome stability. Researchers inoculated microbial communities differing in phylogenetic diversity into sterilized soil and evaluated the resulting microbiome stability. They found that bacterial communities with higher phylogenetic diversity tended to be more stable throughout a range of pH values. Specialized metabolic functions, including “nitrogen metabolism” and "phosphonate and phosphinate metabolism,” were identified as keystone functions. These critical functions were carried out by specific bacterial taxa, including Nitrospira and Gammatimonas..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

Subject:
Biology
Life Science
Material Type:
Diagram/Illustration
Reading
Provider:
Research Square
Provider Set:
Video Bytes
Date Added:
02/25/2021
Top 10 phage identification tools put to the test
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This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Bacteriophages are everywhere, influencing everything from microbial evolution to biogeochemical cycling. Phages, however, remain among the least understood members of complex microbiomes. Do the tools used to identify phages introduce biases? A recent study compared ten of the most widely used bioinformatics tools designed to detect phages from metagenomics data. Overall, tool performance varied substantially in the analysis of different benchmarking datasets. For a set of artificial RefSeq contigs, PPR Meta and VirSorter2 showed the highest performance. Kraken2 showed the highest accuracy for a mock community benchmark. And generally, k-mer tools performed better than similarity- or gene-based tools. The study offers insight into the biases introduced by different tools, offers guidance into which one is best suited for different use cases, and suggests that rather than relying on any one tool, researchers may do well to combine different ones to suit their research needs..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

Subject:
Biology
Life Science
Material Type:
Diagram/Illustration
Reading
Provider:
Research Square
Provider Set:
Video Bytes
Date Added:
05/01/2023
Using machine learning to predict bioreactor productivity
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This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"As a precursor to biobased chemicals, biomass holds enormous potential for meeting the needs of the circular economy. To get the most out of biomass, a new study proposes borrowing tools from machine learning. During anaerobic fermentation, biomass fuels the growth and proliferation of various microorganisms. These microbes, in turn, form organic molecules that can be processed into specialty chemicals, but the conditions and microbes most conducive to this process aren’t always known. To find out, researchers examined bioreactors designed to form medium-chain carboxylates from xylan and lactate. As expected, reducing the hydraulic retention time, or the average time soluble compounds reside in a bioreactor, boosted the formation of useful medium-chain carboxylates. The key was to identify the organisms responsible for this boost. For that, the team used machine learning models designed to link the change in hydraulic retention time to distinct sequences of microbial DNA..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

Subject:
Biology
Life Science
Material Type:
Diagram/Illustration
Reading
Provider:
Research Square
Provider Set:
Video Bytes
Date Added:
05/18/2022
Using the gut microbiome to differentiate between wild and farmed large yellow croaker
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This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Some commercial fish species have both wild and farmed populations. Distinguishing between them is important for identifying escaped fish, managing food safety risk, and setting appropriate market prices. However, for many species, suitable genetic markers haven’t yet been discovered. To provide an alternative, researchers recently tried to use gut microbiome data to differentiate between wild and farmed large yellow croaker. Compared with those of wild croaker, the rectums of farmed croaker had lower microbial diversity (Shannon index values) and bacterial loads, and different microbiome compositions that were distinguishable despite high inter-batch variability. For example, the wild fish microbiome was dominated by _Psychrobacter_ spp., while the farmed fish microbiome was not. The predicted functions of the gut microbes also differed between wild and farmed croaker, presumably because the populations have divergent diets and thus divergent gut environments..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

Subject:
Biology
Life Science
Material Type:
Diagram/Illustration
Reading
Provider:
Research Square
Provider Set:
Video Bytes
Date Added:
05/17/2022
VIBRANT: Automated recovery, annotation and curation of microbial viruses
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This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Viruses that infect bacteria and archaea are abundant in human and environmental microbiomes. Their roles in manipulating, killing, and recycling microbes makes them key players in environmental processes and human health and disease, including inflammatory bowel diseases. In spite of their importance, the tools available for analyzing viral genomes are limited. Now, a new tool allows researchers to identify viruses and predict their functions using genomic data. VIBRANT (Virus Identification By iteRative ANnoTation), is the first software to use a hybrid machine learning and protein similarity approach. going beyond traditional limitations to maximize the identification of highly diverse viruses. In validation experiments with reference datasets, VIBRANT recovered higher-quality virus sequences and reduced false identification of non-viral genome fragments compared to other identification programs..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

Subject:
Biology
Life Science
Material Type:
Diagram/Illustration
Reading
Provider:
Research Square
Provider Set:
Video Bytes
Date Added:
06/23/2020
The growing role of AI and ML in Data Security
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 The organizations that depend largely on collecting data from various sources or are highly digitized must adopt data security. It is better to fight the risks at the initial stage than to regret the loss of data and face the consequences. If the information can not be kept safe from various attacks then the preference of the organization will decrease eventually. Even if personal information cannot be trusted in the hands of the organization then there will be dissatisfaction among customers. If an organization is unable to keep its customers satisfied then its value can hit rock bottom. Hence, by using Artificial Intelligence and Machine Learning the data security should be made better. These technologies will also help in decreasing the extra effort that has to be put by an organization and its employees.  

Subject:
Computer Science
Information Science
Marketing
Material Type:
Reading
Student Guide
Author:
Amelia Emma
Date Added:
01/09/2020