Showing papers by "University of Virginia published in 2022"

Replicability, Robustness, and Reproducibility in Psychological Science

Abstract: Replication-an important, uncommon, and misunderstood practice-is gaining appreciation in psychology. Achieving replicability is important for making research progress. If findings are not replicable, then prediction and theory development are stifled. If findings are replicable, then interrogation of their meaning and validity can advance knowledge. Assessing replicability can be productive for generating and testing hypotheses by actively confronting current understandings to identify weaknesses and spur innovation. For psychology, the 2010s might be characterized as a decade of active confrontation. Systematic and multi-site replication projects assessed current understandings and observed surprising failures to replicate many published findings. Replication efforts highlighted sociocultural challenges such as disincentives to conduct replications and a tendency to frame replication as a personal attack rather than a healthy scientific practice, and they raised awareness that replication contributes to self-correction. Nevertheless, innovation in doing and understanding replication and its cousins, reproducibility and robustness, has positioned psychology to improve research practices and accelerate progress. Expected final online publication date for the Annual Review of Psychology, Volume 73 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Nitrogen defects/boron dopants engineered tubular carbon nitride for efficient tetracycline hydrochloride photodegradation and hydrogen evolution

Abstract: Polymeric carbon nitride (g-C3N4) exhibits only mediocre catalytic activity in photocatalytic environmental remediation and energy conversion because of its limited light absorption and sluggish charge transfer. Herein, we assembled novel, tubular carbon nitride (D-TCN450) with nitrogen defects/boron dopants via a self-supramolecular reaction and NaBH4 thermal reduction approach. Advanced characterization results suggested that introducing the nitrogen defects/boron dopants can effectively promote light trapping, charge separation, and valance-band downshift. Density functional theory and electron spin resonance results further proved that the fusion of cyano groups (nitrogen defects) into the framework of D-TCN450 can facilitate oxygen adsorption to form superoxide radicals. As a result, D-TCN450 exhibited dramatically improved photocatalytic hydrogen evolution and photodegradation of tetracycline hydrochloride at a 4- and 9-fold enhancement compared to pristine g-C3N4, respectively. This integrated engineering strategy might provide a unique paradigm for the rational design of novel photocatalysts for sustainable remediation and energy innovation.

A SARS-CoV-2 ferritin nanoparticle vaccine elicits protective immune responses in nonhuman primates

Abstract: The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants stresses the continued need for next-generation vaccines that confer broad protection against coronavirus disease 2019. We developed and evaluated an adjuvanted SARS-CoV-2 spike ferritin nanoparticle (SpFN) vaccine in nonhuman primates. High-dose (50-μg) SpFN vaccine, given twice 28 days apart, induced a T helper cell 1 (T H 1)–biased CD4 T H response and elicited neutralizing antibodies against SARS-CoV-2 wild type and variants of concern, as well as against SARS-CoV-1. These potent humoral and cell-mediated immune responses translated into rapid elimination of replicating virus in the upper and lower airways and lung parenchyma of nonhuman primates after high-dose SARS-CoV-2 respiratory challenge. The immune response elicited by SpFN vaccination and resulting efficacy in nonhuman primates support the utility of SpFN as a vaccine candidate for SARS-causing betacoronaviruses.

Carbon dots based photocatalysis for environmental applications

Abstract: Carbon quantum dots (CQDs) have attracted intensive interest in the scientific community attributed to their quantum effect, non-toxicity, fluorescence, photoluminescence, and up-conversion properties, and have been extensively applied in sensing, biomedical, optoelectronic and catalysis fields. Especially, CQDs can act as photocatalysts and be used in energy and environmental areas, such as wastewater remediation and solar energy conversion to fuels and green chemicals. This review will briefly introduce the unique physicochemical properties of CQDs, such as light absorption, photoluminescence, and up-conversion luminescence. The advanced fabrication methods and modification strategies of CQDs will also be summarized. Finally, we will show the broad applications of CQDs in photocatalytic pollutant removal and hydrogen/hydrogen-peroxide production, discussing the structure-activity relationship of CQDs and their complexes in the field of catalysis. Lastly, the key issues and perspectives for future energy and environmental applications are presented. This comprehensive review will provide new insight and inspiration in the synthesis, improvement, and photocatalytic application of CQDs.

Molecular architecture of the human caveolin-1 complex

Abstract: Membrane-sculpting proteins shape the morphology of cell membranes and facilitate remodeling in response to physiological and environmental cues. Complexes of the monotopic membrane protein caveolin function as essential curvature-generating components of caveolae, flask-shaped invaginations that sense and respond to plasma membrane tension. However, the structural basis for caveolin’s membrane remodeling activity is currently unknown. Here, we show that, using cryo–electron microscopy, the human caveolin-1 complex is composed of 11 protomers organized into a tightly packed disc with a flat membrane-embedded surface. The structural insights suggest a previously unrecognized mechanism for how membrane-sculpting proteins interact with membranes and reveal how key regions of caveolin-1, including its scaffolding, oligomerization, and intramembrane domains, contribute to its function.

Phase classification of multi-principal element alloys via interpretable machine learning

Abstract: There is intense interest in uncovering design rules that govern the formation of various structural phases as a function of chemical composition in multi-principal element alloys (MPEAs). In this paper, we develop a machine learning (ML) approach built on the foundations of ensemble learning, post hoc model interpretability of black-box models and clustering analysis to establish a quantitative relationship between the chemical composition and experimentally observed phases of MPEAs. The novelty of our work stems from performing instance-level (or local) variable attribution analysis of ML predictions based on the breakdown method, and then identifying similar instances based on k-means clustering analysis of the breakdown results. We also complement the breakdown analysis with Ceteris Paribus profiles that showcase how the model response changes as a function of a single variable, when the values of all other variables are fixed. Results from local model interpretability analysis uncover key insights into variables that govern the formation of each phase. Our developed approach is generic, model-agnostic, and valuable to explain the insights learned by the black-box models. An interactive web application is developed to facilitate model sharing and accelerate the design of novel MPEAs with targeted properties

Evolution of Low-Noise Avalanche Photodetectors

Abstract: This paper reviews materials and structural approaches that have been developed to reduce the excess noise in avalanche photodiodes and increase the gain-bandwidth product.

Extension and torsion of rubber-like hollow and solid circular cylinders for incompressible isotropic hyperelastic materials with limiting chain extensibility

Abstract: In this paper we demonstrate the application of a newly proposed generalised neo-Hookean strain energy function within the family of limiting chain extensibility models to the problem of torsion in incompressible isotropic rubber-like tubes and solid circular cylinders. We consider a general deformation involving extension and torsion in tubes, and subsequently specialise to the simple torsion of solid cylinders. Expressions for the twisting moment M , axial load N and the inflation pressure P are derived and presented for all the considered deformations. Using the proposed model, solutions are obtained for the critical axial stretch λ c z beyond which the specimens exhibit the reversal of the Poynting-type effect upon twisting for both stretched tubes and solid cylinders. The model is then applied to various existing experimental datasets involving torsion in tubes and cylinders. By simultaneous fitting of the model to the considered datasets, it is shown that the model favourably captures the torsional deformation of rubber-like materials. Furthermore, it will be demonstrated that the response function of the model is compatible with Penn and Kearsley's scaling law in torsion and can be directly derived from the ensuing experimental data. While the problem of torsion in elastic tubes and cylinders has been well-studied, this work provides a contribution to nuanced aspects of this problem including the prediction of the critical axial stretch λ c z at which Poynting-type effects reverse in stretched specimens, demonstration of compatibility with the scaling law and favourable simultaneous fits to a variety of experimental datasets involving the torsion of tubes and solid cylinders.

Assessment of spatiotemporal trend of precipitation indices and meteorological drought characteristics in the Mahi River basin, India

Abstract: • Spatial and temporal trend of precipitation extremes calculated using ClimPact2 tool during 1970–2019. • IMD grids are divided into three agro-climatic zones over the Mahi River basin. • Asymmetry in rainfall indicates the presence of interannual variability in the basin. • Characteristics of drought events over agroclimatic zones will reduce the prolonged risk during cropping. • Maximum drought duration and severity were observed in the agroclimatic zone of the western plateau and hills of the Mahi basin. Understanding the trend and variability in hydroclimatic extremes as well as drought characteristics in the context of changing climate is of paramount importance in the management of watershed and rain-fed farming systems. This study focuses on understanding the variations in rainfall patterns & drought types with 3 regions of the agro-climatic zone, in the Mahi River basin, India. The basin is surrounded by three states i.e. Rajasthan, Madhya Pradesh, and Gujarat which is known for its substantial drought occurrences. Very limited studies have been carried out using agroclimatic indices. A 50 years of daily rainfall data (gridded, 0.25°×0.25° spatial resolution) from 1970 to 2019 has been taken from India Meteorological Department (IMD) to compute extreme precipitation indices using ClimPACT2 package and time series trend was tested by Mann-Kendall. Further, 51 grid points are divided into three regions (region 1, region 2, and region 3) as per the agro-climatic zones over the Mahi River basin. The region-wise agroclimatic rainfall variability has been analyzed using monthly standard deviation and anomaly index. The run theory was applied for the characterization of drought assessment. Standardized precipitation index (SPI) was performed for 3, 6, 12, and 24-months. The result found a Consecutive dry day (CDD) with increasing trend significantly and Consecutive wet days (CWD) with decreasing trend may cause a possible impact on agriculture. Findings revealed that region 2 recorded consequent frequent and maximum droughts events over the basin. Hence, the regional topography and moisture availability perform a major role in regional precipitation variability. The output of the current study would be utilized in a better understanding of the drought condition and give a better climate change indication at a regional-basin level. This finding may be valuable for researchers to find out the crucial agro-climatic regions in the basin for preparedness for effective management and planning of water resources.

Coupling of protein condensates to ordered lipid domains determines functional membrane organization

Abstract: ABSTRACT During T-cell activation, the transmembrane adaptor Linker of Activation of T-cells (LAT) forms biomolecular condensates with Grb2 and Sos1, facilitating signaling. LAT has also been associated with cholesterol-rich condensed lipid domains. However, the potential coupling between protein condensation and lipid phase separation and its role in organizing T-cell signaling were unknown. Here, we report that LAT/Grb2/Sos1 condensates reconstituted on model membranes can induce and template lipid domains, indicating strong coupling between lipid- and protein-based phase separation. Correspondingly, activation of T-cells induces protein condensates that associate with and stabilize raft-like membrane domains. Inversely, lipid domains nucleate and stabilize LAT protein condensates in both reconstituted and living systems. This coupling of lipid and protein assembly is functionally important, since uncoupling of lipid domains from cytoplasmic protein condensates abrogates T-cell activation. Thus, thermodynamic coupling between protein condensates and ordered lipid domains regulates the functional organization of living membranes. SUMMARY Membrane-associated protein condensates couple to ordered membrane domains to determine the functional organization of T-cell plasma membranes

Integrating Human and Nonhuman Primate Data to Estimate Human Tolerances for Traumatic Brain Injury

Abstract: Traumatic brain injury (TBI) contributes to a significant portion of the injuries resulting from motor vehicle crashes, falls, and sports collisions. The development of advanced countermeasures to mitigate these injuries requires a complete understanding of the tolerance of the human brain to injury. In this study, we developed a new method to establish human injury tolerance levels using an integrated database of reconstructed football impacts, subinjurious human volunteer data, and nonhuman primate data. The human tolerance levels were analyzed using tissue-level metrics determined using harmonized species-specific finite element (FE) brain models. Kinematics-based metrics involving complete characterization of angular motion (e.g., diffuse axonal multi-axial general evaluation (DAMAGE)) showed better power of predicting tissue-level deformation in a variety of impact conditions and were subsequently used to characterize injury tolerance. The proposed human brain tolerances for mild and severe TBI were estimated and presented in the form of injury risk curves based on selected tissue-level and kinematics-based injury metrics. The application of the estimated injury tolerances was finally demonstrated using real-world automotive crash data.

Evidence for oligodendrocyte progenitor cell heterogeneity in the adult mouse brain

Abstract: Abstract Oligodendrocyte progenitor cells (OPCs) account for approximately 5% of the adult brain and have been historically studied for their role in myelination. In the adult brain, OPCs maintain their proliferative capacity and ability to differentiate into oligodendrocytes throughout adulthood, even though relatively few mature oligodendrocytes are produced post-developmental myelination. Recent work has begun to demonstrate that OPCs likely perform multiple functions in both homeostasis and disease and can significantly impact behavioral phenotypes such as food intake and depressive symptoms. However, the exact mechanisms through which OPCs might influence brain function remain unclear. The first step in further exploration of OPC function is to profile the transcriptional repertoire and assess the heterogeneity of adult OPCs. In this work, we demonstrate that adult OPCs are transcriptionally diverse and separate into two distinct populations in the homeostatic brain. These two groups show distinct transcriptional signatures and enrichment of biological processes unique to individual OPC populations. We have validated these OPC populations using multiple methods, including multiplex RNA in situ hybridization and RNA flow cytometry. This study provides an important resource that profiles the transcriptome of adult OPCs and will provide a toolbox for further investigation into novel OPC functions.