31 Search Results

Abstract Apidaecin 1b (Api), the first characterized Type II Proline-rich antimicrobial peptide (PrAMP), is encoded in the honey bee genome. It inhibits bacterial growth by binding in the nascent peptide exit tunnel of the ribosome after the release of the completed protein and trapping the release factors. By genome mining, we have identified 71 PrAMPs encoded in insect genomes as pre-pro-polyproteins. Having chemically synthesized and tested the activity of 26 peptides, we demonstrate that despite significant sequence variation in the N-terminal sequence, the majority of the PrAMPs that retain the conserved C-terminal sequence of Api are able to trap the ribosome at the stop codons and induce stop codon readthrough—all hallmarks of Type II PrAMP mode of action. Some of the characterized PrAMPs exhibit superior antibacterial activity in comparison with Api. The newly solved crystallographic structures of the ribosome complexed with Api and with the more active peptide Fva1 from the stingless bee demonstrate the universal placement of the PrAMPs’ C-terminal pharmacophore in the post-release ribosome despite variations in their N-terminal sequence.

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Traditional control sequences for HVAC systems in large commercial buildings have historically led to poor energy efficiency. To overcome this issue, ASHRAE has recently published Guideline 36 (G36), a collection of high-performance control sequences aimed at reducing energy consumption and cost for building owners. While these sequences are effective in increasing energy efficiency, their influence on a building's capacity to deliver demand flexibility remains uncertain. Prior research suggests a potential trade-off between energy efficiency and demand flexibility because permanently reducing energy use negatively impacts the available amount of load that can be reduced when responding to grid signals. To investigate this hypothesis, we created Modelica simulation models for an air handling unit with a G36 trim-and-respond sequence, calibrated these models to a fully instrumented experimental building testbed X1A in FLEXLAB, and simulated different demand flexibility scenarios. Counter to expectations, results show that, during a “shed event” with prior pre-cooling, G36 reduces demand by around 3.1 W/m2 more than the traditional control sequences, at the cost of a reduction in comfort (1.5 °C-hour/day) across five different cities across the United States. Our results provide encouraging evidence that, under the tested conditions, G36 does not decrease demand flexibility. This study should increase the confidence of building owners, designers, and operators who are looking to take advantage of demand flexibility programs while complying with increasingly stringent building energy efficiency standards.

As electrification and decarbonization goals become more commonplace across the country, the need for integrating thermal energy storage (TES) with HVAC to provide flexibility and load shifting is growing. Although there has been recent work related to the modeling and design of TES-integrated heat pump (HP) systems, investigation of generalized sizing and control methods for these systems remain limited. This paper details the development of generalized controls and sizing strategies applicable across different TES-integrated designs, two of which are discussed in this study. We demonstrate how model-based design enables an informed sizing and controls design process using the control-oriented Modelica language to generate high-fidelity models that accurately represent real-world behavior. We detail our development and testing of both heuristic and model predictive control (MPC) algorithms to determine the optimal charge and discharge schedule with dynamic varying utility prices. Experimental results show MPC provides operating costs reduction of nearly 20% for a minimum TES sizing scenario. In addition, we provide a generalized and intuitive control algorithm with near-optimal performance to control HP + TES systems and test its performance in simulation. This generalized control algorithm is also used to drive the results of our cost analysis, providing insights for engineers designing new TES-integrated HVAC systems. The cost analysis demonstrates the tradeoff between higher initial hardware costs from larger equipment and the resulting operational cost benefits, and enables a cost-effective sizing method which is applicable to any system. The paper concludes with design recommendations for new integrated HP-TES control systems in buildings.

Control and analytics retrofits in commercial buildings provide owners and operators with tools for improved maintenance and operations, and are an effective strategy for advancing the ambitious carbon reduction objectives mandated by state and federal governments. However, current retrofit processes are labor-intensive, error-prone, and expensive, thereby limiting scalability. There are two primary issues. First, control sequences are: a) typically manually specified in English language using non-standard terminology; b) often not tested prior to installation; and c) more complex when they aim for higher performance (greater efficiency, grid-flexibility). Second, naming conventions used to label the data are often inconsistent, and may vary by practitioner and project. These problems result in significant manual labor and increased cost, lead to malfunctioning operation, and limit scaled deployment of new, high performance control sequences such as needed for heat pump plants with energy storage. This paper presents recent progress towards digitization of these processes, facilitated by two new ASHRAE standards that underwent first public review in 2024. Standard 231P facilitates vendor-neutral, machine-readable representations of control sequences, enabling creation of vendor-agnostic libraries of high performance control sequences that can be translated digitally to building automation systems. Standard 223P facilitates interoperability between controls/analytics and building systems by enabling semi-automatic configuration using semantic models. We first provide a preliminary glimpse into the content of these new standards. Second, we describe their relationships with the established ASHRAE Standard 135 (BACnet communication protocol) and Guideline 36 (high-performance control sequences), and suggest how new automated techniques can be integrated with current human-centric practices. Finally, we discuss how the proposed workflows could impact different industry stakeholders, including owners, designers, control vendors, installers, commissioning agents, and facilities managers. These standards and guidelines enable new workflows that can significantly reduce deployment efforts and costs, and provide a path for scaled deployment of new sequences such as needed for combined chiller and heat pump plants.

The software package in question is a collection of simulation models in the Modelica language, representing a variety of mechanical system designs and envelope conditions related to LBL's FLEXLAB facility. The collection of models also features multiple controls sequences that can be simulated with the FLEXLAB model to simulate different demand flexibility scenarios. Additionally, this package will feature datasets from 3 experimental tests, used for calibration, validation and comparison against the Modelica models, this includes weather data that can be used to replicate different scenarios in simulation across the same weather conditions experienced in real experiments. Given FLEXLAB high level of instrumentation and available data, the models are calibrated across multiple measurement points, and thus results from the extension of this model to other climate zones or control sequences, would provide high level of confidence.

Control applications that facilitate Demand Flexibility (DF) are difficult to deploy at scale in existing buildings. The heterogeneity of systems and non-standard naming conventions for metadata describing data points in building automation systems often lead to ad-hoc and building-specific applications. In recent years, several researchers investigated semantic models to describe the meaning of building data. They suggest that these models can enhance the deployment of building applications, enabling data exchanges among heterogeneous sources and their portability across different buildings. However, the studies in question fail to explore these capabilities in the context of controls. This paper proposes a novel semantics-driven framework for developing and deploying portable DF control applications. The design of the framework leverages an iterative design science research methodology, evolving from evidence gathered through simulation and field demonstrations. The framework aims to decouple control applications from specific buildings and control platforms, enabling these control applications to be configured semi-automatically. This allows application developers and researchers to streamline the onboarding of new applications that could otherwise be time-consuming and resource-intensive. The framework has been validated for its capability to facilitate the deployment of control applications sharing the same codebase across diverse virtual and real buildings. The demonstration successfully tested two controls for load shifting and shedding in four virtual buildings using the Building Optimization Testing Framework (BOPTEST) and in one real building using the control platform VOLTTRON. Insights into the current limitations, benefits, and challenges of generalizable controls and semantic models are derived from the deployment efforts and outcomes to guide future research in this field.

DFLEXLIBS is a library/repository of HVAC-based demand flexibility control applications developed using Python. The library is based on portable control applications that exclusively contain control logic and are abstract to building details, such as point names and communication protocols. The library leverages semantic models and control platform-oriented interfaces to configure and run the controls in specific buildings. To date, the library contains two applications and two interfaces (for BOPTEST and VOLTTRON) and has been demonstrated in five heterogeneous buildings.

Brown rot fungi are primary decomposers of wood and litter in northern forests. Relative to other microbes, these fungi have evolved distinct mechanisms that rapidly depolymerize and metabolize cellulose and hemicellulose without digesting the more recalcitrant lignin. Its efficient degradative system has therefore attracted considerable attention for the development of sustainable biomass conversion technologies. However, there has been a significant lack of genetic tools in brown rot species by which to manipulate genes for both mechanistic studies and engineering applications. To advance brown rot genetic studies, we provided a gene-reporting system that can facilitate genetic manipulations in a model fungus Gloeophyllum trabeum. We first optimized a transformation procedure in G. trabeum, and then transformed the fungus into a constitutive laccase producer with a well-studied white rot laccases gene (from Trametes versicolor). With this, we built a gene reporting system based on laccase gene’s expression and its rapid assay using an 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) indicator dye. The laccase reporter system was validated robust enough to allow us to test the effects of donor DNA’s formats, protoplast viability, and gene regulatory elements on transformation efficiencies. Going forward, we anticipate the toolset provided in this work would expedite phenotyping studies and genetic engineering of brown rot species.

An increasing number of studies have elucidated the essential roles of long noncoding RNAs (lncRNAs) in tumor development. LncRNAs are also closely associated with bladder cancer (BCa) progression. In the present study, we screened out a novel lncRNA CALML3-AS1 with increased expression value in BCa tissues. Particularly, we showed that CALML3-AS1 overexpression correlates with advanced staging and an unsatisfactory prognosis. Functional experiments illustrated that CALML3-AS1 knockdown suppressed BCa cell proliferation, arrested cell-cycle progression and impaired migration and invasion while promoting apoptosis. Mechanistic investigation revealed that CALML3-AS1 directly interacts with miR-4316 and inhibits its availability in BCa cells, leading to elevated expression of ZBTB2. Consequently, ZBTB2 promotes BCa tumorigenesis through repressing p21 and facilitating PDK4 transcription. In conclusion, our findings demonstrate a novel CALML3-AS1-mediated process involved in BCa progression and indicate it might be a promising therapeutic target.