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PubMed Journals Articles About "Should Start Biotechnology Companies Manage Learning Generate Necessary" RSS

06:28 EDT 5th April 2020 | BioPortfolio

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Showing "Should Start Biotechnology Companies Manage Learning Generate Necessary" PubMed Articles 1–25 of 8,700+

Can biotechnology strategies effectively manage environmental (micro)plastics?

With the convenience of plastic products to daily life, the negative sides of the plastic-age have gradually emerged. Like other pollutants, complex environmental factors result in the ubiquitous presence of (micro)plastics worldwide, raising potential risks to the ecological systems. However, due to the limitation of traditional technologies in treating these materials, new strategies should be developed. More recently, researchers have showed that biotechnology strategies could be promising approaches to ...


Dental trauma learning facilitators for medical doctors: a viewpoint.

It is important for medical doctors to be equipped with the requisite knowledge and skills to manage dental trauma cases when patients present to them in an emergency. The aim of this paper is to identify facilitators (factors that enhance learning) that may impact on the ability and competency of medical doctors, who are expected to treat traumatic dental injuries (TDI), to appropriately treat and manage such cases. A change in medical curricula that is more inclusive of dental education and TDI management...

Relationships Between Dry-land Resistance Training and Swim Start Performance and Effects of Such Training on the Swim Start: A Systematic Review.

The swim start requires an explosive muscular response of the lower body musculature to effectively initiate movement off the starting blocks. There are currently key gaps in the literature evaluating the relationship between dry-land resistance training and swim start performance and the effects of this training on swim start performance, as assessed by the time to 5, 10 or 15 m.


An Analysis of the Learning Health System in Its First Decade in Practice: Scoping Review.

In the past decade, Lynn Etheredge presented a vision for the Learning Health System (LHS) as an opportunity for increasing the value of health care via rapid learning from data and immediate translation to practice and policy. An LHS is defined in the literature as a system that seeks to continuously generate and apply evidence, innovation, quality, and value in health care.

Implementation of Urgent Start Peritoneal Dialysis Reduces Hemodialysis Catheter Use and Hospital Stay in Patients with Unplanned Dialysis Start.

Unplanned start of renal replacement therapy is common in patients with end-stage renal disease and often accomplished by hemodialysis (HD) using a central venous catheter (CVC). Urgent start using peritoneal dialysis (PD) could be an alternative for some of the patients; however, this requires a hospital-based PD center that offers a structured urgent start PD (usPD) program.

Microbes in food biotechnology: An annotated selection of World Wide Web sites relevant to the topics in microbial biotechnology.

Off to a Good Start: A Behaviorally Based Model for Teaching Children With Down Syndrome; Book 1: Foundations for Learning.

Machine learning applications in systems metabolic engineering.

Systems metabolic engineering allows efficient development of high performing microbial strains for the sustainable production of chemicals and materials. In recent years, increasing availability of bio big data, for example, omics data, has led to active application of machine learning techniques across various stages of systems metabolic engineering, including host strain selection, metabolic pathway reconstruction, metabolic flux optimization, and fermentation. In this paper, recent contributions of mach...

Bio-Inspired Representation Learning for Visual Attention Prediction.

Visual attention prediction (VAP) is a significant and imperative issue in the field of computer vision. Most of the existing VAP methods are based on deep learning. However, they do not fully take advantage of the low-level contrast features while generating the visual attention map. In this article, a novel VAP method is proposed to generate the visual attention map via bio-inspired representation learning. The bio-inspired representation learning combines both low-level contrast and high-level semantic f...

Twelve tips for facilitating medical students prescribing learning on clinical placement.

Prescribing is a complex clinical skill requiring mastery by the end of basic medical training. Prescribing errors are common in newly qualified doctors, aligned with expressed anxiety about prescribing, particularly with high-risk medications. Learning about prescribing needs to start early in medical training, underpinned by regular opportunities for reflective practice. Authentic learning within the clinical work environment is more effective than lecture based learning and allows potential immediate fee...

Trends in Biotechnology at the Turn of the Millennium.

The concept of biotechnology has gained wide popularity by the time. There is of course some anecdotal evidence as to what topics are currently considered the most prominent and how they compare to the common perception of which research topics were considered "trendy" years ago.

The Sustainability and Life Cycle Assessments of Industrial Biotechnology: An Introduction.

Industrial biotechnology (IB) uses biological and biochemical processes in industrial production and is often regarded as an emerging key technology revolutionizing the production of many products while protecting resources and the environment and fostering economic development. This contribution describes the background and sketches the content of the volume 'Sustainability and Life Cycle Assessment of Industrial Biotechnology' in the Springer series 'Advances in Biochemical Engineering/Biotechnology'. The...

Incorporating biological structure into machine learning models in biomedicine.

In biomedical applications of machine learning, relevant information often has a rich structure that is not easily encoded as real-valued predictors. Examples of such data include DNA or RNA sequences, gene sets or pathways, gene interaction or coexpression networks, ontologies, and phylogenetic trees. We highlight recent examples of machine learning models that use structure to constrain model architecture or incorporate structured data into model training. For machine learning in biomedicine, where sample...

Navigating Institutional Challenges: Design to Enable Community Participation in Social Learning for Freshwater Planning.

Social learning is a process suited to developing understanding and concerted action to tackle complex resource dilemmas, such as freshwater management. Research has begun to recognise that in practice social learning encounters a variety of institutional challenges from the shared habits and routines of stakeholders (organised by rules, norms and strategies) that are embedded in organisational structures and norms of professional behaviour. These institutional habits and routines influence the degree of wi...

The effect of start-up on energy recovery and compositional changes in brewery wastewater in bioelectrochemical systems.

Start-up of bioelectrochemical systems (BESs) fed with brewery wastewater was compared at different adjusted anode potentials (-200 and 0 mV vs. Ag/AgCl) and external resistances (50 and 1000 Ω). Current generation stabilized faster with the external resistances (9 ± 3 and 1.70 ± 0.04 A/m with 50 and 1000 Ω, respectively), whilst significantly higher current densities of 76 ± 39 and 44 ± 9 A/m were obtained with the adjusted anode potentials of -200 and 0 mV vs. Ag/AgCl, respectively. Af...

Machine learning with multiparametric magnetic resonance imaging of the breast for early prediction of response to neoadjuvant chemotherapy.

In patients with locally advanced breast cancer undergoing neoadjuvant chemotherapy (NAC), some patients achieve a complete pathologic response (pCR), some achieve a partial response, and some do not respond at all or even progress. Accurate prediction of treatment response has the potential to improve patient care by improving prognostication, enabling de-escalation of toxic treatment that has little benefit, facilitating upfront use of novel targeted therapies, and avoiding delays to surgery. Visual inspe...

The learning curve of one anastomosis gastric bypass and its impact as a preceding procedure to Roux-en Y gastric bypass: initial experience of one hundred and five consecutive cases.

The aim of this study was to assess the learning curve of one anastomosis gastric bypass (OAGB-MGB) at the start of a low volume bariatric unit and analyze its impact as a preceding procedure to Roux-en Y gastric bypass (RYGB).

Predictive Modeling of Outcomes After Traumatic and Nontraumatic Spinal Cord Injury Using Machine Learning: Review of Current Progress and Future Directions.

Machine learning represents a promising frontier in epidemiological research on spine surgery. It consists of a series of algorithms that determines relationships between data. Machine learning maintains numerous advantages over conventional regression techniques, such as a reduced requirement for a priori knowledge on predictors and better ability to manage large datasets. Current studies have made extensive strides in employing machine learning to a greater capacity in spinal cord injury (SCI). Analyses u...

Collaborating constructively for sustainable biotechnology.

Tackling the pressing sustainability needs of society will require the development and application of new technologies. Biotechnology, emboldened by recent advances in synthetic biology, offers to generate sustainable biologically-based routes to chemicals and materials as alternatives to fossil-derived incumbents. Yet, the sustainability potential of biotechnology is not without trade-offs. Here, we probe this capacity for sustainability for the case of bio-based nylon using both deliberative and analytica...

Usability of Learning Moment: Features of an E-learning Tool That Maximize Adoption by Students.

E-learning is widely used in medical education. To maximize the potential of E-learning tools, every effort should be made to encourage adoption by optimizing usability. We created Learning Moment (LM), a web-based application that integrates principles of asynchronous learning and learning portfolios into a platform on which students can document and share learning experiences that occur during clinical work. We sought to evaluate the usability of LM and identify features that optimize adoption by users.

Interpretability and Class Imbalance in Prediction Models for Pain Volatility in Manage My Pain App Users: Analysis Using Feature Selection and Majority Voting Methods.

Pain volatility is an important factor in chronic pain experience and adaptation. Previously, we employed machine-learning methods to define and predict pain volatility levels from users of the Manage My Pain app. Reducing the number of features is important to help increase interpretability of such prediction models. Prediction results also need to be consolidated from multiple random subsamples to address the class imbalance issue.

Effect of Public Deliberation on Patient Attitudes Regarding Consent and Data Use in a Learning Health Care System for Oncology.

We sought to generate informed and considered opinions regarding acceptable secondary uses of deidentified health information and consent models for oncology learning health care systems.

Peritoneal Dialysis as an Urgent-Start Option for Incident Patients on Chronic Renal Replacement Therapy: World Experience and Review of Literature.

Chronic kidney disease is a significant problem of public health worldwide, and up to 60% of patients start dialysis in an unplanned manner without a definitive dialysis access. Recently, peritoneal dialysis (PD) has emerged as an alternative to unplanned chronic dialytic method, and the world collective experience shows that PD can be an efficient, safe, and cost-effective alternative with comparable outcomes to the planned PD and urgent-start hemodialysis (HD). More importantly, as compared to urgent-star...

Achieving Rapid Blood Pressure Control With Digital Therapeutics: Retrospective Cohort and Machine Learning Study.

Behavioral therapies, such as electronic counseling and self-monitoring dispensed through mobile apps, have been shown to improve blood pressure, but the results vary and long-term engagement is a challenge. Machine learning is a rapidly advancing discipline that can be used to generate predictive and responsive models for the management and treatment of chronic conditions and shows potential for meaningfully improving outcomes.

Dynamic Metabolomics for Engineering Biology: Accelerating Learning Cycles for Bioproduction.

Metabolomics is a powerful tool to rationally guide the metabolic engineering of synthetic bioproduction pathways. Current reports indicate great potential to further develop metabolomics-directed synthetic bioproduction. Advanced mass metabolomics methods including isotope flux analysis, untargeted metabolomics, and system-wide approaches are assisting the characterization of metabolic pathways and enabling the biosynthesis of more complex products. More importantly, a design, build, test, and learn (DBTL)...


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