Activator Sequence Research Articles

Establishing a Common Design Language and Process for Unit Development using Miro Template

Our Faculty has embarked on an ambitious multi-year project aimed at taking advantage of lessons learned during emergency COVID online learning and teaching, to develop a set of Faculty principles and implement a transformation of unit offerings into a suite of integrated hybrid experiences supporting and connecting students both on campus and online. The challenge we faced was around the traditional way of delivering content and building knowledge as well as how we assess students. To support the transformation process, the teaching staff and the design staff involved, we have developed and continue to refine a collaborative and non-linear design process template in Miro. The template is designed to guide conversations with academic staff about proposed changes to the unit design. It allows entry into the design process at any point that suits the academic and supports an iterative design thinking approach. Additionally, it enables rapid ‘paper’ prototyping of ideas and establishes a common design language amongst teaching and design staff. This template helps rapidly explain current development thinking to others. The fundamental difference of this template and commonly used design processes is the visualisation of connections between learning outcomes, assessments and sequencing of learning activities. This approach to learning design uses digital mediating artefact in facilitating unit design. The template currently shows the design of a unit from its place within a course or courses, all the way down to the finer details of lesson planning. At every turn, it unobtrusively buttresses the design process with reference to selected design and educational theory, and university policy, subtly reinforcing good teaching practice. The following are currently included in the template, and there are plans to incorporate frames that support the development of assessment rubrics, lesson plans and the conceptual development of new units and courses. Curriculum Mapping - places the unit within its course context. Course and unit learning outcomes are mapped to unit assessments. Enables a simple and clear visualisation of unit place in multiple courses where applicable. Unit Delivery Mode - enables integration of face-to-face and remote learning activities, enables visualisation of connections between activities, and helps track unit student workload. Assessment Design - links assessment design to assessment theory - assessment by, for and of learning (Voinea, 2018), enables visualisation of connections between assessments and sequencing of learning activities, marking and feedback. It tracks student workload in assessment preparation. Refining Learning & Defining Content - links to Blooms and Solo and University learning outcome writing guide to guide crafting of unit learning outcomes if they need to change Class Lesson Plan - Enables the visualisation of in-class plans and implementation of University active learning guidelines (4As) (Vella & Ashworth, 2007) Semester Map - lays the entire unit out across a semester timeline. It enables a bird-eye view of the sequence of all unit-related activities. It can be used to compare student learning experience and workload over multiple units in any given semester timeframe.

Time of Use tariffs, childcare and everyday temporalities in the US and China: Evidence from time-use and sequence-network analysis

Time of Use (ToU) tariffs that aim to shift people’s energy use away from peaks have been key demand-side management measures. Yet, their effectiveness has often been below expectations. In this paper we empirically test arguments based on social practice theory that this underperformance is not the result of people making ill-informed or economically questionable decisions but reflects the complexities of social synchronization. Using sequence-network analysis, we visualize and comparatively analyze time-use data from the US and China to capture everyday temporalities of a particular time-inflexible group – child caregivers. Findings show that timing and sequencing of peak activities for caregivers in both countries were largely structured by institutional and family rhythms, though with considerable differences in extent and timing of influences due to diverging childcare cultures. The necessity to follow these rhythms leaves caregivers little room to adjust their peak activities to ToU tariffs, turning this well-intended measure into an inequitable financial burden on the group. We argue that policymakers should deploy time-varying tariffs in ways that align with everyday temporalities of population groups. Cutting critical and daily peaks in ways that work with people’s temporal (in)flexibilities in everyday practices could be a key to the effectiveness of energy measures.

Crystal structure of transcription factor TGA7 from Arabidopsis

TGA family of transcription factors play important roles in the systemic acquired resistance (SAR) in plants. In SAR, TGA7 binds to the activation sequence-1 (as-1) in the promoter region of SAR related genes and regulates their expressions in an NPR1 dependent manner. Despite its important roles in plant immunity, the molecular mechanism for DNA binding of TGA7 remains unclear. In the present work, we resolved the crystal structure of TGA7 dimers at a resolution of 2.06 Å, in which each monomer binds one molecule of palmitate. Further biochemical studies revealed that TGA7 specifically binds to the TGACG boxes of as-1 DNA in the form of homodimers, and it has specific requirements for the relative spacing and orientation of the two TGACG boxes. Moreover, we built a TGA7-DNA complex model and confirmed by site-directed mutagenesis that amino acid residue R109 in the DNA binding domain (DBD) of TGA7 is a key residue responsible for DNA recognition. Our work offers a good example for structural and functional studies of TGA proteins, and provides key clues to understand the DNA binding mechanism of TGA proteins in the SAR.

Lessons From Implementing Virtual Simulations: A Multi-Program Evaluation

BackgroundThe use of virtual simulation increased significantly during the recent pandemic. This required a rapid shift for many nursing programs, and also provided the opportunity to evaluate a common virtual simulation experience. MethodThis mixed methods study included three different nursing programs from a Western Canadian province. Each program was delivered in either French or English, and did not have a shared curriculum. The Simulation Effectivenes Tool-Modified (SET-M) was used, with n = 88 students responding. Open-ended qualitative responses, and qualitative responses from a faculty debriefing session were analyzed and included in the results. ResultsPrebriefing and debriefing were ranked as being most important in conducting virtual simulation. Sequencing of simulation activities needs to be considered, as does the need for synchronous debriefing. ConclusionThis study highlights the importance of the facilitators’ role in virtual simulation, specifically prebriefing, preparation, and debriefing, and that simulation effectiveness is not based on specific virtual simulation products.

Fe‐based catalyst with diphenylphosphite as donor for stereopolymerization of butadiene, isoprene, and myrcene

AbstractIron catalyst has been encountered with low activity and stereoselectivity sensitive to the operational conditions for diene polymerization. In this study, diphenylphosphite has been proved as an efficient donor in iron‐based tertiary catalyst for butadiene, isoprene and myrcene stereopolymerizations. Thermal robustness of active species has been demonstrated as the high activity and 1,2 stereoselectivity are survived in a wide temperature scope ranging from 5°C to 80°C. The resultant polybutadienes are found to have 1,2 incorporation up to 92.8% with syndiotactic conformation (rrrr: 95.1%), and more than 65% of irregular 3,4 enchainments are generated for polyisoprene and polymyrcene. The active species are formed preferably following addition sequence of iron compound, donor and activator in the presence of monomer. The development of this highly active and stable catalyst combining cost‐efficient components and mild operation parameters could provide accessible catalyst recipe to produce new types of polydienes.

Genome-wide prediction of activating regulatory elements in rice by combining STARR-seq with FACS.

Self-transcribing active regulatory region sequencing (STARR-seq) is widely used to identify enhancers at the whole-genome level. However, whether STARR-seq works as efficiently in plants as in animal systems remains unclear. Here, we determined that the traditional STARR-seq method can be directly applied to rice (Oryza sativa) protoplasts to identify enhancers, though with limited efficiency. Intriguingly, we identified not only enhancers but also constitutive promoters with this technique. To increase the performance of STARR-seq in plants, we optimized two procedures. We coupled fluorescence activating cell sorting (FACS) with STARR-seq to alleviate the effect of background noise, and we minimized PCR cycles and retained duplicates during prediction, which significantly increased the positive rate for activating regulatory elements (AREs). Using this method, we determined that AREs are associated with AT-rich regions and are enriched for a motif that the AP2/ERF family can recognize. Based on GC content preferences, AREs are clustered into two groups corresponding to promoters and enhancers. Either AT- or GC-rich regions within AREs could boost transcription. Additionally, disruption of AREs resulted in abnormal expression of both proximal and distal genes, which suggests that STARR-seq-revealed elements function as enhancers invivo. In summary, our work provides a promising method to identify AREs in plants.

Hybridization of reinforcement learning and agent-based modeling to optimize construction planning and scheduling

Decision-making in construction planning and scheduling is complex because of budget and resource constraints, uncertainty, and the dynamic nature of construction environments. A knowledge gap in the construction literature exists regarding decision-making frameworks with the ability to learn and propose an optimal set of solutions for construction scheduling problems, such as activity sequencing and work breakdown structure formulations under uncertainty. The objective of this paper is to propose a hybrid reinforcement learning–graph embedding network model that 1) simulates complex construction planning environments using agent-based modeling and 2) minimizes computational burdens in establishing activity sequences and work breakdown formations. Three case studies with practical construction scheduling problems were used to demonstrate applicability of the developed model. This paper contributes to the body of knowledge by proposing the hybridization of reinforcement learning and simulation approaches to optimize project durations with resource constraints and support construction practitioners in making project planning decision-making.

Development and characterization of anti-HPV16 monoclonal antibodies for assembly of an HPV16 detection kit.

Quality control is very important during the development of 3-valent (16/18/58), 9-valent (6/11/16/18/31/33/45/52/58), and 15-valent human papillomavirus (HPV) vaccines (6/11/16/18/31/33/35/39/45/52/56/58/59/68). All 3-valent, 9-valent, and 15-valent HPV vaccines contain the HPV16 antigen; therefore, a detection method that can specifically identify HPV16 in vaccines is urgently required. This study aimed to develop and characterize monoclonal antibodies to assemble a highly specific HPV16 detection kit. The HPV16 L1 pentameric protein developed as an immunogen was used to prepare monoclonal antibodies. From the pool of prepared monoclonal antibodies, we selected 4G12 and 5A6 to screen and evaluate their subtypes, specificity, neutralizing activity, serum competition, binding affinity, and gene sequencing. After these characterizations, an enzyme-linked immunosorbent assay kit for these monoclonal antibodies was developed, and excellent quality was demonstrated in the assessment of linearity, repeatability, and specificity. The developed detection kit has great potential for wide use in clinical testing and quality control in vaccine production processes.

Functional characterization of novel variants found in patients with suspected Fabry disease

The deficiency or absence of the lysosomal hydrolase α-Galactosidase A results in Fabry disease (FD), a rare and underdiagnosed X-linked disorder. The symptoms caused by FD have a direct relation with the variant present in the gene coding α-Galactosidase A (GLA) and enzyme residual activity, and it can vary drastically between men and women of the same family. Here, we present four novel variants found in patients with suspicion of FD. The patients were screened for FD by enzymatic activity and/or DNA sequencing, which showed four novel GLA missense variants. To confirm the potential pathogenicity of these variants, we employed site-directed mutagenesis. GLA wild-type and mutant plasmids were transfected into mammalian cells; RNA and proteins were extracted for expression and enzymatic activity analysis. The patients presented the variants p.Ile133Asn, p.Lys140Thr, p.Lys168Gln and p.Pro323Thr in the GLA. In vitro analysis showed pathogenic potential of three variants and one tolerated variant. The variants p.Ile133Asn and p.Lys168Gln showed no residual activity and, therefore, leading to classical phenotype, and the variant p.Lys140Thr, which presented 22% of residual activity, was considered a mild variant leading to non-classical phenotype. The variant p.Pro323Thr presented 66.7% of residual activity and alone, it is not enough to cause FD.

ATAC-STARR-seq reveals transcription factor-bound activators and silencers within chromatin-accessible regions of the human genome.

Massively parallel reporter assays (MPRAs) test the capacity of putative gene regulatory elements to drive transcription on a genome-wide scale. Most gene regulatory activity occurs within accessible chromatin, and recently described methods have combined assays that capture these regions—such as assay for transposase-accessible chromatin using sequencing (ATAC-seq)—with self-transcribing active regulatory region sequencing (STARR-seq) to selectively assay the regulatory potential of accessible DNA (ATAC-STARR-seq). Here, we report an integrated approach that quantifies activating and silencing regulatory activity, chromatin accessibility, and transcription factor (TF) occupancy with one assay using ATAC-STARR-seq. Our strategy, including important updates to the ATAC-STARR-seq assay and workflow, enabled high-resolution testing of ∼50 million unique DNA fragments tiling ∼101,000 accessible chromatin regions in human lymphoblastoid cells. We discovered that 30% of all accessible regions contain an activator, a silencer, or both. Although few MPRA studies have explored silencing activity, we demonstrate that silencers occur at similar frequencies to activators, and they represent a distinct functional group enriched for unique TF motifs and repressive histone modifications. We further show that Tn5 cut-site frequencies are retained in the ATAC-STARR plasmid library compared to standard ATAC-seq, enabling TF occupancy to be ascertained from ATAC-STARR data. With this approach, we found that activators and silencers cluster by distinct TF footprint combinations, and these groups of activity represent different gene regulatory networks of immune cell function. Altogether, these data highlight the multilayered capabilities of ATAC-STARR-seq to comprehensively investigate the regulatory landscape of the human genome all from a single DNA fragment source.

‘But I don’t know if I want to talk to you’: strategies to foster conversational receptiveness across the United States’ political divide

ABSTRACT This study explores the conversational receptiveness strategies that are intentionally embedded in the Braver Angels organization’s Red/Blue Workshops. These workshops facilitate difficult conversations across the political divide in the United States, especially communication between Republicans and Democrats. Workshop training materials and workshop recordings were analyzed to identify how moderators were trained to encourage conversational receptiveness through structured dialogue. Results identified trained facilitator strategies (greeting behaviors, acknowledging power differences, setting up structures for safety of outgroup conversations, active listening, and showing appreciation for participant input), structured conversational receptiveness practices (limiting assumptions through perspective-taking and locating shared interests), and the strategic sequencing of training activities all contributed to creating dialogic moments. The conversational work done in these workshops around sharing one’s own perspective and invoking the perspectives of others, holds potential implications for helping to create communities of dialogue where people can develop conversational receptiveness, both within these workshops and beyond.

Genome-wide identification of functional enhancers and their potential roles in pig breeding

BackgroundThe pig is an economically important livestock species and is a widely applied large animal model in medical research. Enhancers are critical regulatory elements that have fundamental functions in evolution, development and disease. Genome-wide quantification of functional enhancers in the pig is needed.ResultsWe performed self-transcribing active regulatory region sequencing (STARR-seq) in the porcine kidney epithelial PK15 and testicular ST cell lines, and reliably identified 2576 functional enhancers. Most of these enhancers were located in repetitive sequences and were enriched within silent and lowly expressed genes. Enhancers poorly overlapped with chromatin accessibility regions and were highly enriched in chromatin with the repressive histone modification H3K9me3, which is different from predicted pig enhancers detected using ChIP-seq for H3K27ac or/and H3K4me1 modified histones. This suggests that most pig enhancers identified with STARR-seq are endogenously repressed at the chromatin level and may function during cell type-specific development or at specific developmental stages. Additionally, the PPP3CA gene is associated with the loin muscle area trait and the QKI gene is associated with alkaline phosphatase activity that may be regulated by distal functional enhancers.ConclusionsIn summary, we generated the first functional enhancer map in PK15 and ST cells for the pig genome and highlight its potential roles in pig breeding.

Ocimum sanctum, OscWRKY1, regulates phenylpropanoid pathway genes and promotes resistance to pathogen infection in Arabidopsis.

OscWRKY1 from Ocimum sanctum positively regulates phenylpropanoid pathway genes and rosmarinic acid content. OscWRKY1 overexpression promotes resistance against bacterial pathogen in Arabidopsis. WRKY transcription factor (TF) family regulates various developmental and physiological functions in plants. PAL genes encode enzymes which are involved in plant defense responses, but the direct regulation of PAL genes and phenylpropanoid pathway through WRKY TF's is not well characterized. In the present study, we have characterized an OscWRKY1 gene from Ocimum sanctum which shows induced expression by methyl jasmonate (MeJA), salicylic acid (SA), and wounding. The recombinant OscWRKY1 protein binds to the DIG-labeled (Digoxigenin) W-box cis-element TTGAC[C/T] and activates the LacZ reporter gene in yeast. Overexpression of OscWRKY1 enhances Arabidopsis resistance towards Pseudomonas syringae pv. tomato Pst DC3000. Upstream activator sequences of PAL and C4H have been identified to contain the conserved W-box cis-element (TTGACC) in both O. sanctum and Arabidopsis. OscWRKY1 was found to interact with W-box cis-element present in the PAL and C4H promoters. Silencing of OscWRKY1 using VIGS resulted in reduced expression of PAL, C4H, COMT, F5H and 4CL transcripts. OscWRKY1 silenced plants exhibit reduced PAL activity, whereas, the overexpression lines of OscWRKY1 in Arabidopsis exhibit increased PAL activity. Furthermore, the metabolite analysis of OscWRKY1 silenced plants showed reduced rosmarinic acid content. These results revealed that OscWRKY1 positively regulates the phenylpropanoid pathway genes leading to the alteration of rosmarinic acid content and enhances the resistance against bacterial pathogen in Arabidopsis.

Constraint Sampling Reinforcement Learning: Incorporating Expertise for Faster Learning

Online reinforcement learning (RL) algorithms are often difficult to deploy in complex human-facing applications as they may learn slowly and have poor early performance. To address this, we introduce a practical algorithm for incorporating human insight to speed learning. Our algorithm, Constraint Sampling Reinforcement Learning (CSRL), incorporates prior domain knowledge as constraints/restrictions on the RL policy. It takes in multiple potential policy constraints to maintain robustness to misspecification of individual constraints while leveraging helpful ones to learn quickly. Given a base RL learning algorithm (ex. UCRL, DQN, Rainbow) we propose an upper confidence with elimination scheme that leverages the relationship between the constraints, and their observed performance, to adaptively switch among them. We instantiate our algorithm with DQN-type algorithms and UCRL as base algorithms, and evaluate our algorithm in four environments, including three simulators based on real data: recommendations, educational activity sequencing, and HIV treatment sequencing. In all cases, CSRL learns a good policy faster than baselines.

Deep Learning, Mining, and Collaborative Clustering to Identify Flexible Daily Activities Patterns.

The monitoring of the daily life activities routine is beneficial, especially in old age. It can provide relevant information on the person’s health state and wellbeing and can help identify deviations that signal care deterioration or incidents that require intervention. Existing approaches consider the daily routine as a rather strict sequence of activities which is not usually the case. In this paper, we propose a solution to identify flexible daily routines of older adults considering variations related to the order of activities and activities timespan. It combines the Gap-BIDE algorithm with a collaborative clustering technique. The Gap-BIDE algorithm is used to identify the most common patterns of behavior considering the elements of variations in activities sequence and the period of the day (i.e., night, morning, afternoon, and evening) for increased pattern mining flexibility. K-means and Hierarchical Clustering Agglomerative algorithms are collaboratively used to address the time-related elements of variability in daily routine like activities timespan vectors. A prototype was developed to monitor and detect the daily living activities based on smartwatch data using a deep learning architecture and the InceptionTime model, for which the highest accuracy was obtained. The results obtained are showing that the proposed solution can successfully identify the routines considering the aspects of flexibility such as activity sequences, optional and compulsory activities, timespan, and start and end time. The best results were obtained for the collaborative clustering solution that considers flexibility aspects in routine identification, providing coverage of monitored data of 89.63%.

Functional Definition of Thyroid Hormone Response Elements Based on a Synthetic STARR-seq Screen.

When bound to thyroid hormone, the nuclear receptor TRα1 activates the transcription of a number of genes in many cell types. It mainly acts by binding DNA as a heterodimer with retinoid X receptors at specific response elements related to the DR4 consensus sequence. However, the number of DR4-like elements in the genome exceed by far the number of occupied sites, indicating that minor variations in nucleotides composition deeply influence the DNA-binding capacity and transactivation activity of TRα1. An improved protocol of synthetic self-transcribing active regulatory region sequencing was used to quantitatively assess the transcriptional activity of thousands of synthetic sites in parallel. This functional screen highlights a strong correlation between the affinity of the heterodimers for DNA and their capacity to mediate the thyroid hormone response.

Nonlinear dynamical modeling of neural activity using volterra series with GA-enhanced particle swarm optimization algorithm.

In order to improve the modeling performance of Volterra sequence for nonlinear neural activity, in this paper, a new optimization algorithm is proposed to identify Volterra sequence parameters. Algorithm combines the advantages of particle swarm optimization (PSO) and genetic algorithm (GA) improve the performance of the identification of nonlinear model parameters from rapidity and accuracy. In the modeling experiments of neural signal data generated by the neural computing model and clinical neural data set in this paper, the proposed algorithm shows its excellent potential in nonlinear neural activity modeling. Compared with PSO and GA, the algorithm can achieve less identification error, and better balance the convergence speed and identification error. Further, we explore the influence of algorithm parameters on identification efficiency, which provides possible guiding significance for parameter setting in practical application of the algorithm.

Process optimization for post disaster reconstruction project based on industrial design structure matrix (DSM)

Post-disaster reconstruction projects face tighter time constraints and are in a more complex environment, making the implementation process of conventional projects unable to meet new requirements. This study decomposes the construction process and then determines the feed-forward and feedback relationship between activities in the post-disaster reconstruction environment. An information relationship diagram is established, and the relationship is transformed into a design structure matrix (DSM). Through DSM manipulation, a partitioned DSM is formed to express the activity process that is more suitable for reconstruction. This research shows that the activities sequence and content need to be changed to adapt to the reconstruction scenario, and some activities may even be canceled. Some suggestions can help construct the project faster, including closer cooperation between design and construction. The bidding scope includes design and construction and the use of more integrated project delivery methods. Finally, a reconstruction case in China illustrates the operability of analyzing and adjusting the implementation process through this framework.

Compatibility rules of human enhancer and promoter sequences.

Gene regulation in the human genome is controlled by distal enhancers that activate specific nearby promoters1. A proposed model for this specificity is that promoters have sequence-encoded preferences for certain enhancers, for example, mediated by interacting sets of transcription factors or cofactors2. This 'biochemical compatibility' model has been supported by observations at individual human promoters and by genome-wide measurements in Drosophila3-9. However, the degree to which human enhancers and promoters are intrinsically compatible has not yet been systematically measured, and how their activities combine to control RNA expression remains unclear. Here we design a high-throughput reporter assay called enhancer × promoter self-transcribing active regulatory region sequencing (ExP STARR-seq) and applied it to examine the combinatorial compatibilities of 1,000 enhancer and 1,000 promoter sequences in human K562 cells. We identify simple rules for enhancer-promoter compatibility, whereby most enhancers activate all promoters by similar amounts, and intrinsic enhancer and promoter activities multiplicatively combine to determine RNA output (R2 = 0.82). In addition, two classes of enhancers and promoters show subtle preferential effects. Promoters of housekeeping genes contain built-in activating motifs for factors such as GABPA and YY1, which decrease the responsiveness of promoters to distal enhancers. Promoters of variably expressed genes lack these motifs and show stronger responsiveness to enhancers. Together, this systematic assessment of enhancer-promoter compatibility suggests a multiplicative model tuned by enhancer and promoter class to control gene transcription in the human genome.

Development of HPV58 type-specific antibodies and detection kit

Currently, human papillomavirus (HPV) vaccines are in short supply, so the development of HPV vaccines has a broad market prospect. The 3-, 9-, and 15-valent HPV vaccines developed by ourselves all contain HPV58-derived antigen components. It is important to detect HPV 58 during vaccine production. Here, we introduced a development process of HPV58 type-specific antibodies and a detection kit. Briefly, HPV58 L1-Virus Like Particles (VLPs) were used as antigens to immunize mice, followed by extraction of the ascites to prepare hybridoma cells. After culturing, the supernatants containing secreted antibodies were harvested, purified, and screened to obtain monoclonal antibodies (mAbs). In the pool of attained monoclonal antibodies, we selected 2F7 and 2G7 to evaluate their subtypes, specificity, neutralizing activity, serum competition, binding affinity and gene sequencing. Finally, an enzyme-linked immunosorbent assay (ELISA) detection kit was assembled with 2F7 and 2G7 mAbs which possessed high specificity to HPV58 L1-VLPs. The detection kit developed by 2F7 and 2G7 could be adopted to specifically detect HPV58 L1 protein with good linearity and detection range, which could be widely used in clinical testing and quality control in the production of HPV vaccines. Abbreviations: BSA: Bovine serum albumin; CDRs: Complementarity-determining regions; CV: Coefficient of variation; DTT: Dithiothreitol; ELISA: Enzyme-linked immunosorbent assay; HAT: Hypoxanthine-aminopterin-thymidine; HPV: Human Papillomavirus; IC50: 50% inhibition rate; IC90: 90% inhibition rate; mAbs: Monoclonal antibodies; VLP: Virus-like particle