Messenger RNAs (mRNAs) encode information in both their primary sequence and their higher order structure. The independent contributions of factors like codon usage and secondary structure to ...regulating protein expression are difficult to establish as they are often highly correlated in endogenous sequences. Here, we used 2 approaches, global inclusion of modified nucleotides and rational sequence design of exogenously delivered constructs, to understand the role of mRNA secondary structure independent from codon usage. Unexpectedly, highly expressed mRNAs contained a highly structured coding sequence (CDS). Modified nucleotides that stabilize mRNA secondary structure enabled high expression across a wide variety of primary sequences. Using a set of eGFP mRNAs with independently altered codon usage and CDS structure, we find that the structure of the CDS regulates protein expression through changes in functional mRNA half-life (i.e., mRNA being actively translated). This work highlights an underappreciated role of mRNA secondary structure in the regulation of mRNA stability.
Effective genetic diagnosis requires the correlation of genetic variant data with detailed phenotypic information. However, manual encoding of clinical data into machine-readable forms is laborious ...and subject to observer bias. Natural language processing (NLP) of electronic health records has great potential to enhance reproducibility at scale but suffers from idiosyncrasies in physician notes and other medical records. We developed methods to optimize NLP outputs for automated diagnosis. We filtered NLP-extracted Human Phenotype Ontology (HPO) terms to more closely resemble manually extracted terms and identified filter parameters across a three-dimensional space for optimal gene prioritization. We then developed a tiered pipeline that reduces manual effort by prioritizing smaller subsets of genes to consider for genetic diagnosis. Our filtering pipeline enabled NLP-based extraction of HPO terms to serve as a sufficient replacement for manual extraction in 92% of prospectively evaluated cases. In 75% of cases, the correct causal gene was ranked higher with our applied filters than without any filters. We describe a framework that can maximize the utility of NLP-based phenotype extraction for gene prioritization and diagnosis. The framework is implemented within a cloud-based modular architecture that can be deployed across health and research institutions.
Natural language processing (NLP) holds promise for automating the phenotyping process and generating machine-readable lists of codes that describe a patient’s condition. We describe a generalizable framework of sequential filtration steps that can be applied across any electronic health records system, NLP platform, and molecular diagnostic aid to improve the diagnostic utility of NLP-derived phenotypic code lists.
Hypophosphatasia (HPP) is a rare metabolic disorder characterized by low tissue‐nonspecific alkaline phosphatase (TNSALP) typically caused by ALPL gene mutations. HPP is heterogeneous, with clinical ...presentation correlating with residual TNSALP activity and/or dominant‐negative effects (DNE). We measured residual activity and DNE for 155 ALPL variants by transient transfection and TNSALP enzymatic activity measurement. Ninety variants showed low residual activity and 24 showed DNE. These results encompass all missense variants with carrier frequencies above 1/25,000 from the Genome Aggregation Database. We used resulting data as a reference to develop a new computational algorithm that scores ALPL missense variants and predicts high/low TNSALP enzymatic activity. Our approach measures the effects of amino acid changes on TNSALP dimer stability with a physics‐based implicit solvent energy model. We predict mutation deleteriousness with high specificity, achieving a true‐positive rate of 0.63 with false‐positive rate of 0, with an area under receiver operating curve (AUC) of 0.9, better than all in silico predictors tested. Combining this algorithm with other in silico approaches can further increase performance, reaching an AUC of 0.94. This study expands our understanding of HPP heterogeneity and genotype/phenotype relationships with the aim of improving clinical ALPL variant interpretation.
By informing timely targeted treatments, rapid whole-genome sequencing can improve the outcomes of seriously ill children with genetic diseases, particularly infants in neonatal and pediatric ...intensive care units (ICUs). The need for highly qualified professionals to decipher results, however, precludes widespread implementation. We describe a platform for population-scale, provisional diagnosis of genetic diseases with automated phenotyping and interpretation. Genome sequencing was expedited by bead-based genome library preparation directly from blood samples and sequencing of paired 100-nt reads in 15.5 hours. Clinical natural language processing (CNLP) automatically extracted children's deep phenomes from electronic health records with 80% precision and 93% recall. In 101 children with 105 genetic diseases, a mean of 4.3 CNLP-extracted phenotypic features matched the expected phenotypic features of those diseases, compared with a match of 0.9 phenotypic features used in manual interpretation. We automated provisional diagnosis by combining the ranking of the similarity of a patient's CNLP phenome with respect to the expected phenotypic features of all genetic diseases, together with the ranking of the pathogenicity of all of the patient's genomic variants. Automated, retrospective diagnoses concurred well with expert manual interpretation (97% recall and 99% precision in 95 children with 97 genetic diseases). Prospectively, our platform correctly diagnosed three of seven seriously ill ICU infants (100% precision and recall) with a mean time saving of 22:19 hours. In each case, the diagnosis affected treatment. Genome sequencing with automated phenotyping and interpretation in a median of 20:10 hours may increase adoption in ICUs and, thereby, timely implementation of precise treatments.
While many genetic diseases have effective treatments, they frequently progress rapidly to severe morbidity or mortality if those treatments are not implemented immediately. Since front-line ...physicians frequently lack familiarity with these diseases, timely molecular diagnosis may not improve outcomes. Herein we describe Genome-to-Treatment, an automated, virtual system for genetic disease diagnosis and acute management guidance. Diagnosis is achieved in 13.5 h by expedited whole genome sequencing, with superior analytic performance for structural and copy number variants. An expert panel adjudicated the indications, contraindications, efficacy, and evidence-of-efficacy of 9911 drug, device, dietary, and surgical interventions for 563 severe, childhood, genetic diseases. The 421 (75%) diseases and 1527 (15%) effective interventions retained are integrated with 13 genetic disease information resources and appended to diagnostic reports ( https://gtrx.radygenomiclab.com ). This system provided correct diagnoses in four retrospectively and two prospectively tested infants. The Genome-to-Treatment system facilitates optimal outcomes in children with rapidly progressive genetic diseases.
Lysosomal acid lipase (LAL) deficiency is an autosomal recessive disorder caused by LIPA gene mutations that disrupt LAL activity. We performed in vitro functional testing of 149
LIPA variants to ...increase the understanding of the variant effects on LAL deficiency and to improve disease prevalence estimates. Chosen variants had been reported in literature or population databases. Functional testing was done by plasmid transient transfection and LAL activity assessment. We assembled a set of 165 published LAL deficient patient genotypes to evaluate this assay's effectiveness to recapitulate genotype/phenotype relationships. Rapidly progressive LAL deficient patients showed negligible enzymatic activity (<1%), whereas patients with childhood/adult LAL deficiency typically have 1–7% average activity. We benchmarked six in silico variant effect prediction algorithms with these functional data. PolyPhen‐2 was shown to have a superior area under the receiver operating curve performance. We used functional data along with Genome Aggregation Database (gnomAD) allele frequencies to estimate LAL deficiency birth prevalence, yielding a range of 3.45–5.97 cases per million births in European‐ancestry populations. The low estimate only considers functionally assayed variants in gnomAD. The high estimate computes allele frequencies for variants absent in gnomAD, and uses in silico scores for unassayed variants. Prevalence estimates are lower than previously published, underscoring LAL deficiency's rarity.
With the financialization of a major segment of the world economy, the built environment has, in turn, experienced a new level of commodification. For the super rich, residential real estate promises ...strong return on investment, safe sheltering of funds outside the home country, and in most cases, a view. In Manhattan this development has recently taken physical form in the very tall slender tower. With extraordinary values predicated on location, views, and exclusivity, these buildings are shaped by careful manipulation of zoning and building codes, supported by innovative structural solutions, presented in enticing renderings, all to maximize profit potential. Application of new building technologies allows designers to create buildings with very high floor areas (FAR) on very small sites while maximizing height and, consequently, unit prices. This thesis explores this phenomenon as a built manifestation of global processes and local influences based on current developments in New York City. It transfers its findings to Seattle, which is growing in prominence in the international real estate market, as a physical location in which to explore the potential opportunities allowed by local building and zoning code that could shape a new typology of ultra-luxury real estate in the city. Projecting into the near future, this project manifests itself as a slender residential tower that embodies and embraces both the legal and physical gymnastics undertaken in its design.
There are many data communications titles covering design, installation, etc., but almost none that specifically focus on industrial networks, which are an essential part of the day-to-day work of ...industrial control systems engineers, and the main focus of an increasingly large group of network specialists.
The focus of this book makes it uniquely relevant to control engineers and network designers working in this area. The industrial application of networking is explored in terms of design, installation and troubleshooting, building the skills required to identify, prevent and fix common industrial data communications problems, both at the design stage and in the maintenance phase.
The focus of this book is 'outside the box'. The emphasis goes beyond typical communications issues and theory to provide the necessary toolkit of knowledge to solve industrial communications problems covering RS-232, RS-485, Modbus, Fieldbus, DeviceNet, Ethernet and TCP/IP. The idea of the book is that in reading it you should be able to walk onto your plant, or facility, and troubleshoot and fix communications problems as quickly as possible.
Process skills such as problem solving, critical thinking, information processing, teamwork, and communication are important for student success in their coursework and eventually the workplace, but ...these skills are not always explicitly taught or assessed in undergraduate courses. These skills should be assessed in order to identify areas for student improvement and because assessment practices can provide clear goals to students. However, my analysis of the current literature suggests that instructors do not have the tools necessary to effectively assess and provide feedback on these skills, particularly in science, technology, engineering, and mathematics (STEM) undergraduate courses. To meet this need of assessing and providing feedback to students, rubrics and other instructional resources have been developed to assess process skills as part of the Enhancing Learning by Improving Process Skills in STEM (ELIPSS) Project. Surveys and interview data indicated that the rubrics were practical for instructors to use to provide feedback to students, represented all relevant aspects of the skills, measured the processes that students used when completing tasks, and could be reliably used by multiple raters. During rubric development, the resources were propagated to the STEM instructor community, and the effectiveness of the propagation methods were examined. The highest rates of adoption resulted from hearing about the rubrics from a colleague or attending a presentation about the rubrics. Additionally, running the ELIPSS workshops and creating the ELIPSS website that people found from searching the internet each led to moderate adoption rates. These results support the idea that a multifaceted propagation strategy may be most effective for researchers who are developing assessment tools. When studying the ways in which STEM instructors were implementing the ELIPSS rubrics, it was found that the instructors each developed different strategies that suited their intended learning outcomes and instructional environments by assessing and providing feedback to students in a variety of ways. Instructors with different class sizes, course levels, online course management systems, and access to teaching assistants all adapted the rubric implementation strategy to fit their unique classroom environments. Multiple instructors reported that they were better able to articulate professional skill expectations to their students through the use of the rubrics. Additionally, they were more aware of how their students interacted with one another in groups after using the interaction rubrics. These results indicate that ELIPSS rubrics can encourage more reflective practice in undergraduate instructors by providing them with more information about their students that can be used to modify their teaching methods. Further work was done to examine how students developed process skills in a first-year chemistry laboratory course. Students in a first-year chemistry laboratory course used the ELIPSS rubrics to assess their own process skills, and they were also assessed by a teaching assistant. Additionally, students reported their understanding of process skills and their perceived improvements over the course of the semester. The results suggest that students understand interpersonal process skills such as teamwork and communication better than they understand cognitive process skills such as critical thinking and information processing. While the evidence further suggests that students improved their process skills, and students reported that they improved their process skills, the students showed inconsistent abilities to self-assess and provide justification for their assessment using rubrics.
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