Plausible Model Research Articles

On the importance of fundamental computational fluid dynamics toward a robust and reliable model of left atrial flows.

Computational fluid dynamics (CFD) studies of left atrial flows have reached a sophisticated level, for example, revealing plausible relationships between hemodynamics and stresses with atrial fibrillation. However, little focus has been on fundamental fluid modeling of LA flows. The purpose of this study was to investigate the spatiotemporal convergence, along with the differences between high- (HR) versus normal-resolution/accuracy (NR) solution strategies, respectively. Rigid wall CFD simulations were conducted on 12 patient-specific left atrial geometries obtained from computed tomography scans, utilizing a second-order accurate and space/time-centered solver. The convergence studies showed an average variability of around 30% and 55% for time averaged wall shear stress (WSS), oscillatory shear index (OSI), relative residence time (RRT), and endothelial cell activation potential (ECAP), even between intermediate spatial and temporal resolutions, in the left atrium (LA) and left atrial appendage (LAA), respectively. The comparison between HR and NR simulations showed good correlation in the LA for WSS, RRT, and ECAP ( ), but not for OSI ( ). However, there were poor correlations in the LAA especially for OSI, RRT, and ECAP ( .55, .63, and .61, respectively), except for WSS ( ). The errors are comparable to differences previously reported with disease correlations. To robustly predict atrial hemodynamics and stresses, numerical resolutions of 10 M elements (i.e., .5 mm) and 10 k time-steps per cycle seem necessary (i.e., one order of magnitude higher than normally used in both space and time). In conclusion, attention to fundamental numerical aspects is essential toward establishing a plausible, robust, and reliable model of LA flows.

Dynamic Gain Decomposition Reveals Functional Effects of Dendrites, Ion Channels, and Input Statistics in Population Coding.

Modern, high-density neuronal recordings reveal at ever higher precision how information is represented by neural populations. Still, we lack the tools to understand these processes bottom-up, emerging from the biophysical properties of neurons, synapses, and network structure. The concept of the dynamic gain function, a spectrally resolved approximation of a population's coding capability, has the potential to link cell-level properties to network-level performance. However, the concept is not only useful but also very complex because the dynamic gain's shape is co-determined by axonal and somato-dendritic parameters and the population's operating regime. Previously, this complexity precluded an understanding of any individual parameter's impact. Here, we decomposed the dynamic gain function into three components corresponding to separate signal transformations. This allowed attribution of network-level encoding features to specific cell-level parameters. Applying the method to data from real neurons and biophysically plausible models, we found: (1) The encoding bandwidth of real neurons, approximately 400 Hz, is constrained by the voltage dependence of axonal currents during early action potential initiation. (2) State-of-the-art models only achieve encoding bandwidths around 100 Hz and are limited mainly by subthreshold processes instead. (3) Large dendrites and low-threshold potassium currents modulate the bandwidth by shaping the subthreshold stimulus-to-voltage transformation. Our decomposition provides physiological interpretations when the dynamic gain curve changes, for instance during spectrinopathies and neurodegeneration. By pinpointing shortcomings of current models, it also guides inference of neuron models best suited for large-scale network simulations.

A disinhibitory circuit mechanism explains a general principle of peak performance during mid-level arousal

Perceptual decision-making is highly dependent on the momentary arousal state of the brain, which fluctuates over time on a scale of hours, minutes, and even seconds. The textbook relationship between momentary arousal and task performance is captured by an inverted U-shape, as put forward in the Yerkes-Dodson law. This law suggests optimal performance at moderate levels of arousal and impaired performance at low or high arousal levels. However, despite its popularity, the evidence for this relationship in humans is mixed at best. Here, we use pupil-indexed arousal and performance data from various perceptual decision-making tasks to provide converging evidence for the inverted U-shaped relationship between spontaneous arousal fluctuations and performance across different decision types (discrimination, detection) and sensory modalities (visual, auditory). To further understand this relationship, we built a neurobiologically plausible mechanistic model and show that it is possible to reproduce our findings by incorporating two types of interneurons that are both modulated by an arousal signal. The model architecture produces two dynamical regimes under the influence of arousal: one regime in which performance increases with arousal and another regime in which performance decreases with arousal, together forming an inverted U-shaped arousal-performance relationship. We conclude that the inverted U-shaped arousal-performance relationship is a general and robust property of sensory processing. It might be brought about by the influence of arousal on two types of interneurons that together act as a disinhibitory pathway for the neural populations that encode the available sensory evidence used for the decision.

The Impact of Obesity on Diabetes Onset and Neovascularization in Mouse Models of Metabolic Stress.

Animal models of metabolic disorders are essential to studying pathogenic mechanisms and developing therapies for diabetes, but the induction protocols vary, and sexual dimorphism often exists. In a chronic diabetic model of diet-induced obesity (DIO) and low-dose streptozotocin (STZ)-induced hyperglycemia, blood glucose and lipid profiles were measured. The high-fat (HF) diet damaged insulin sensitivity and increased triglycerides, total cholesterol, LDL-cholesterol, HDL-cholesterol, and liver lipid deposition. STZ increased blood glucose and liver fibrosis with less effects on blood lipids or liver lipid deposition. The combination of DIO and STZ treatments led to significant liver lipid deposition and fibrosis. Female mice showed delayed body weight gain on HF diet and resisted STZ-induced hyperglycemia. However, once they developed DIO, which occurs around 26 weeks of HF diet, the female mice were prone to STZ-induced hyperglycemia. In hindlimb ischemia, male mice in the DIO-STZ group showed significantly worse neovascularization compared with DIO or STZ groups. The DIO-STZ females showed significantly worse recovery than the DIO-STZ males. Our observations suggest that DIO-STZ is a plausible model for studying metabolic and cardiovascular disorders in obesity and diabetes. Moreover, the findings in female animals stress the need to assess sexual dimorphism and investigate the underlying mechanisms that contribute to the worse vasculopathy manifestations in females in metabolic models.

Hydrogen recombination continuum as the radiative model for stellar optical flares

ABSTRACT The study of stellar flares has increased with new observations from CoRoT, Kepler, and TESS satellites, revealing the broad-band visible emission from these events. Typically, stellar flares have been modelled as 104 K blackbody plasma to obtain estimates of their total energy. In the Sun, white-light flares (WLFs) are much fainter than their stellar counterparts, and normally can only be detected via spatially resolved observations. Identifying the radiation mechanism for the formation of the visible spectrum from solar and stellar flares is crucial to understand the energy transfer processes during these events, but spectral data for WLFs are relatively rare, and insufficient to remove the ambiguity of their origin: photospheric blackbody radiation and/or Paschen continuum from hydrogen recombination in the chromosphere. We employed an analytical solution for the recombination continuum of hydrogen instead of the typically assumed 104 K blackbody spectrum to study the energy of stellar flares and infer their fractional area coverage. We investigated 37 events from Kepler-411 and five events from Kepler-396, using both radiation mechanisms. We find that estimates for the total flare energy from the H recombination spectrum are about an order of magnitude lower than the values obtained from the blackbody radiation. Given the known energy transfer processes in flares, we argue that the former is a physically more plausible model than the latter to explain the origin of the broad-band optical emission from flares.

Specification and formation process of enriched portions in Au veins in an epithermal deposit via clustering and geostatistical approaches

Even though epithermal vein-type deposits are the main sources of Au and Ag worldwide, accurate three-dimensional modeling of vein structures and the extraction of high-grade zones are still difficult because of geologic structure heterogeneities and the scarcity of available data, mostly obtained via drilling. Accordingly, by selecting a low-sulfidation epithermal Au–Ag deposit in the Philippine archipelago, we develop an efficient and reliable workflow for determining the spatial distribution of Au-rich veins in detail and the transport of hydrothermal fluids. The studied deposit is mostly hosted in open fractures and breccias with a relatively large tonnage of low Au+Ag grades and/or a small tonnage of high Au+Ag grades. The whole-rock geochemical data (1877 core samples) and lithological data (56 drilling sites) are processed using hierarchical clustering analysis (HCA) and two geostatistical simulations: turning bands simulation for the Au grade distribution and interpretation of mineralization process and truncated Gaussian simulation for the spatial distribution of clusters with similar Au–Ag grade features as classified by HCA. The general correlation between the Au and Ag grades, with a linear correlation coefficient of ≈ 0.69, is based on the HCA application, and the clusters were likely formed by three-stage mineralization processes. A plausible three-dimensional geologic model is then constructed, delineating in detail hydrothermally mineralized and altered zones with Au enrichment and vein system structures in the study area.

A Kinetic Model of Furfural Hydrogenation to 2-Methylfuran on Nanoparticles of Nickel Supported on Sulfuric Acid-Modified Biochar Catalyst

Lignocellulosic biomass can uptake CO2 during growth, which can then be pyrolysed into three major products, biochar (BC), syngas, and bio-oil. Due to the presence of oxygenated organic compounds, the produced bio-oil is not suitable for direct use as a fuel and requires upgrading via hydrodeoxygenation (HDO) and hydrogenation. This is typically carried out over a supported metal catalyst. Regarding circular economy and sustainability, the BC from the pyrolysis step can potentially be activated and used as a novel catalyst support, as reported here. A 15 wt% Ni/BC catalyst was developed by chemically modifying BC with sulfuric acid to improve mesoporous structure and surface area. When compared to the pristine Ni/BC catalyst, sulfuric activated Ni/BC catalyst has excellent mesopores and a high surface area, which increases the dispersion of Ni nanoparticles and hence improves the adsorptive effect and thus catalytic performance. A liquid phase hydrogenation of furfural to 2-methylfuran was performed over the developed 15 wt% Ni/BC catalyst. Langmuir–Hinshelwood–Hougen–Watson (LHHW) kinetic type models for adsorption of dissociative H2 were screened based on an R2 value greater than 99%, demonstrating that the experimental data satisfactorily fit to three plausible models: competitive (Model I), competitive at only one type of adsorption site (Model II), and non-competitive with two types of adsorption sites (Model III). With a correlation coefficient greater than 99% between the experimental rates and the predicted rate, Model III, which is a dual-site adsorption mechanism involving furfural adsorption and hydrogen dissociative adsorption and surface reaction, is the best fit. The Ni/BC catalyst demonstrated comparative performance and significant cost savings over previous catalysts; a value of 24.39 kJ mol−1 was estimated for activation energy, −11.43 kJ mol−1 for the enthalpy of adsorption for H2, and −5.86 kJ mol−1 for furfural. The developed Ni/BC catalyst demonstrated excellent stability in terms of conversion of furfural (96%) and yield of 2-methylfuran (54%) at the fourth successive experiments. Based on furfural conversion and yield of products, it appears that pores are constructed slowly during sulfuric acid activation of the biochar.

Does information reduce interpersonal violence? Evidence from prisons

Abstract Why does interpersonal violence erupt? A key source is conflict over resources and a little-studied mechanism for solving such cases concerns the availability of credible information about individuals’ abilities and willingness to use force. Its core prediction is that when such credible information abounds, the outcome of a potential struggle can be anticipated and thus there is no need to fight. I test this prediction using a nationally representative survey of male prisoners (Ninmates = 10,768, Nfacilities = 207) incarcerated in US state correctional facilities. I also make two methodologically orientated contributions. First, recent research highlights the important consequences that data analysis choices can have in determining quantitative findings. To overcome this, I draw on multiverse analysis and specification curve analysis to map out the key analytical decisions I make and run 262,144 plausible regression models. By doing so, I classify associations that are robust, mixed, or entirely frail according to analytic decisions and find partial support for the informational mechanism of interpersonal violence. Second, in contrast to much quantitative prison research, which uses only official or institutionally punished assaults data, I compare self-recognized fights to self-reported institutionally punished fights and highlight key differences.

The spinal cord facilitates cerebellar upper limb motor learning and control; inputs from neuromusculoskeletal simulation.

Complex interactions between brain regions and the spinal cord (SC) govern body motion, which is ultimately driven by muscle activation. Motor planning or learning are mainly conducted at higher brain regions, whilst the SC acts as a brain-muscle gateway and as a motor control centre providing fast reflexes and muscle activity regulation. Thus, higher brain areas need to cope with the SC as an inherent and evolutionary older part of the body dynamics. Here, we address the question of how SC dynamics affects motor learning within the cerebellum; in particular, does the SC facilitate cerebellar motor learning or constitute a biological constraint? We provide an exploratory framework by integrating biologically plausible cerebellar and SC computational models in a musculoskeletal upper limb control loop. The cerebellar model, equipped with the main form of cerebellar plasticity, provides motor adaptation; whilst the SC model implements stretch reflex and reciprocal inhibition between antagonist muscles. The resulting spino-cerebellar model is tested performing a set of upper limb motor tasks, including external perturbation studies. A cerebellar model, lacking the implemented SC model and directly controlling the simulated muscles, was also tested in the same. The performances of the spino-cerebellar and cerebellar models were then compared, thus allowing directly addressing the SC influence on cerebellar motor adaptation and learning, and on handling external motor perturbations. Performance was assessed in both joint and muscle space, and compared with kinematic and EMG recordings from healthy participants. The differences in cerebellar synaptic adaptation between both models were also studied. We conclude that the SC facilitates cerebellar motor learning; when the SC circuits are in the loop, faster convergence in motor learning is achieved with simpler cerebellar synaptic weight distributions. The SC is also found to improve robustness against external perturbations, by better reproducing and modulating muscle cocontraction patterns.

Five questions on the cell-to-cell movement of Orthotospoviruses

Plant viruses employ Movement proteins (MP) for their cell to cell spread through plasmodesmata (PD). MP modifies the PD and increases its size exclusion limit (SEL). However, the mechanism by which MPs are targeted to the PD is still unresolved and there is a lack of consensus owing to limited studies on their biochemical and structural characters. The non structural protein m (NSm) functions as the MP in Orthotospoviruses. Tospoviral NSm associate with ER membrane. They also form tubules in protoplasts. Groundnut bud necrosis virus (GBNV), a tospovirus, infects several crop plants throughout India and is economically very important. GBNV NSm associates with the membrane strongly via the C-terminal coiled-coil domain, modifies the membrane and causes vesicle fusion in vitro and remodels the ER network into vesicles in vivo. These vesicles are in contrast to the tubules formed by other related tospovirus in cells lacking cell wall. In this review, five important questions on the cell-to-cell movement of tospoviruses have been addressed and based on the various reports, a plausible model on the cell-to-cell movement of Orthotospoviruses is presented.

First-principles theory of the nitrogen interstitial in hBN: a plausible model for the blue emitter.

Color centers in hexagonal boron nitride (hBN) have attracted considerable attention due to their remarkable optical properties enabling robust room temperature photonics and quantum optics applications in the visible spectral range. On the other hand, identification of the microscopic origin of color centers in hBN has turned out to be a great challenge that hinders the in-depth theoretical characterization, on-demand fabrication, and development of integrated photonic devices. This is also true for the blue emitter, which is a result of irradiation damage in hBN, emitting at 436 nm wavelength with desirable properties. Here, we propose the negatively charged nitrogen split interstitial defect in hBN as a plausible microscopic model for the blue emitter. To this end, we carried out a comprehensive first-principles theoretical study of the nitrogen interstitial. We carefully analyzed the accuracy of first-principles methods and showed that the commonly used HSE hybrid exchange-correlation functional fails to describe the electronic structure of this defect. Using the generalized Koopman's theorem, we fine-tuned the functional and obtained a zero-phonon photoluminescence (ZPL) energy in the blue spectral range. We showed that the defect exhibits a high emission rate in the ZPL line and features a characteristic phonon side band that resembles the blue emitter's spectrum. Furthermore, we studied the electric field dependence of the ZPL and numerically showed that the defect exhibits a quadratic Stark shift that is perpendicular to plane electric fields, making the emitter insensitive to electric field fluctuations in the first order. Our work emphasizes the need for assessing the accuracy of common first-principles methods in hBN and exemplifies a workaround methodology. Furthermore, our work is a step towards understanding the structure of the blue emitter and utilizing it in photonics applications.

Characterization of minimal network structures modeling stochastic processes

Identifying the underlying structure of a network from observed data is an important problem across various disciplines. Given the general ill-posed nature of the problem, since in many cases, multiple plausible network models can explain the data, this article concentrates on characterizing classes of models providing possible explanations. Specifically, we explore linear models that can account for observed data in the form of wide-sense stationary processes accommodating the potential presence of feedback loops and direct feedthroughs. To achieve this, we leverage key insights from the theory of graphical models. In particular, we extensively employ Pearl-Verma Theorem in causal discovery which allows one to recover all minimal network structures compatible with the observed data. We adapt such a result to deal with stochastic processes and reinterpret it as a Gram-Schmidt orthogonalization procedure in a suitable Hilbert space. This reinterpretation allows us to characterize all minimal networks explaining a set of data, which have the property of not having any algebraic loops.

Decentralized Neural Circuits of Multisensory Information Integration in the Brain.

The brain combines multisensory inputs together to obtain a complete and reliable description of the world. Recent experiments suggest that several interconnected multisensory brain areas are simultaneously involved to integrate multisensory information. It was unknown how these mutually connected multisensory areas achieve multisensory integration. To answer this question, using biologically plausible neural circuit models we developed a decentralized system for information integration that comprises multiple interconnected multisensory brain areas. Through studying an example of integrating visual and vestibular cues to infer heading direction, we show that such a decentralized system is well consistent with experimental observations. In particular, we demonstrate that this decentralized system can optimally integrate information by implementing sampling-based Bayesian inference. The Poisson variability of spike generation provides appropriate variability to drive sampling, and the interconnections between multisensory areas store the correlation prior between multisensory stimuli. The decentralized system predicts that optimally integrated information emerges locally from the dynamics of the communication between brain areas and sheds new light on the interpretation of the connectivity between multisensory brain areas.

Visibility Evaluation in Microfacet Theory.

Reflectance models capture many types of visual appearances. The most plausible reflectance models follow the Microfacet theory, which is specifically based on statistical representations, with an analytic visibility term. This visibility term has a significant impact on appearance. Visibility computed with the masking term proposed by Smith[1], and revisited by Ashikhmin et al.[2], is nowadays considered as the most plausible in the literature. It is simple and efficient to evaluate for statistical distributions, but it relies on assumptions that are not necessarily respected by real surfaces. This paper proposes an in-depth study of masking for meshed height-field surfaces, generated either from measured real-world materials or from functions derived from distributions of surface normals. We experimentally estimate the masking (and shadowing) of surfaces using a ray-casting technique, and compare their measurements with the theoretical model from Smith and Ashikhmin et al. We show that their assumptions are too restrictive for a majority of real-world surfaces. We propose a model capable of predicting how close the theoretical masking term can be from the masking term estimated by a ray-casting approach. Although most surfaces break their assumptions, our results show that the term from Smith and Ashikhmin et al. can still be reasonably employed for a fraction in a set of more than 400 measured surfaces, with low errors compared to a ray-casting masking estimation, much lower computation times, and very similar visual appearances. Our model can be used to predict the incurred error on a physically-based rendering simulation with a microfacet-based BRDF created from real-world surfaces, instead of explicitly calculating the masking term from its height field.

Conceptual Framework of Equity Sensitivity, Training and Promotion on Specialist Doctors Retention in Malaysia: Moderated by Organizational Trust

Purpose: This paper presents a conceptual framework to ameliorate the retention of specialist doctors in the Ministry of Health (MoH) Malaysia, facilities underpinned by social exchange theory (SET) and equity sensitivity theory.
 Design/Methodology/Approach: The study establishes the issues of specialist attrition from MoH facilities thru analysis of current reports and developments. Followed by an investigation of past literature to develop relationships and hypothesize based on SET tenets of reciprocity.
 Findings: The framework establishes relationship and guidance for the development of specialist doctors’ retention in MoH facilities in Malaysia. From the findings of the study, the framework suggests that equity sensitivity, availability of training and opportunities for promotion have a significant impact on employee retention of specialist doctors in Malaysia. Organizational trust acts as a capable moderator of the relationship between availability of training, opportunities for promotion and employee retention in the framework.
 Implications/Originality/Value: The paper presents a plausible model if validated can provide an invaluable insight in understanding the needs and expectations of specialist doctors’ retention in public hospitals. The framework also addresses the theoretical concerns put forth by previous studies concerning the ambiguities of the broad concepts of SET. Finally, the paper presents the context specific nature of employee retention among a scarcely studied occupation group, i.e., specialist doctors in the Malaysian public sector cultural setting.

Relevance, recovery and recuperation: A prelude to ring withdrawal

In this paper, we introduce recuperative withdrawals, belief change operators that satisfy recuperation, a postulate weaker than recovery, all the AGM postulates for contraction except recovery and another postulate which is a slightly stronger condition than conjunctive inclusion. Furthermore, we present a constructive definition for a class of operators —named ring withdrawals— which are such that the outcome of a ring withdrawal of a belief set K by a sentence α is obtained by adding to the set of most plausible models ‖K‖ all the worlds which are as close to ‖K‖ as its closest ¬α-worlds. Ring withdrawals satisfy the Lindström and Rabinowicz's interpolation thesis. We show that the classes of recuperative withdrawals and of ring withdrawals are identical. Additionally we show that the class of ring withdrawals is not contained in and does not contain the class of AGM contractions or the class of severe withdrawals. Finally we present methods for defining an operator of ring withdrawal by means of a severe withdrawal operator and by means of an AGM contraction operator, and vice-versa.

From the detection of monitoring anomalies to the probabilistic forecast of the evolution of volcanic unrest: an entropy-based approach

Owing to the current lack of plausible and exhaustive physical pre-eruptive models, often volcanologists rely on the observation of monitoring anomalies to track the evolution of volcanic unrest episodes. Taking advantage from the work made in the development of Bayesian Event Trees (BET), here we formalize an entropy-based model to translate the observation of anomalies into probability of a specific volcanic event of interest. The model is quite general and it could be used as a stand-alone eruption forecasting tool or to set up conditional probabilities for methodologies like the BET and of the Bayesian Belief Network (BBN). The proposed model has some important features worth noting: (i) it is rooted in a coherent logic, which gives a physical sense to the heuristic information of volcanologists in terms of entropy; (ii) it is fully transparent and can be established in advance of a crisis, making the results reproducible and revisable, providing a transparent audit trail that reduces the overall degree of subjectivity in communication with civil authorities; (iii) it can be embedded in a unified probabilistic framework, which provides an univocal taxonomy of different kinds of uncertainty affecting the forecast and handles these uncertainties in a formal way. Finally, for the sake of example, we apply the procedure to track the evolution of the 1982–1984 phase of unrest at Campi Flegrei.

A Novel Smartphone App for Self-Monitoring of Neonatal Jaundice Among Postpartum Mothers: Qualitative Research Study.

Neonatal jaundice (NNJ) or hyperbilirubinemia is a ubiquitous condition in newborn infants. Currently, the transcutaneous bilirubinometer is used to screen for NNJ in health care facilities, where neonates need to be physically present (ie, a centralized model of care for NNJ screening). Mobile health (mHealth) apps present a low-cost, home-based, and noninvasive system that could facilitate self-monitoring of NNJ and could allow mothers the convenience of screening for NNJ remotely. However, end users' acceptability of such mHealth apps is of fundamental importance before the incorporation of such apps into clinical practice. The study aimed to explore the perception of postpartum mothers toward self-monitoring of NNJ using a novel mHealth app. Mothers attending video consultations for early postpartum care at 2 Singapore primary care clinics watched an instructional video for a hyperbilirubinemia-screening mHealth app (HSMA). An independent researcher used a semistructured topic guide to conduct in-depth interviews with 25 mothers, assessing their views on HSMAs. All interviews were audio recorded, transcribed verbatim, and checked for accuracy before data analysis. Two researchers independently analyzed the transcripts via thematic analysis. Data were managed using NVivo qualitative data management software. The identified themes were grouped under perceived usability and utility. Mothers valued the convenience and utility of HSMAs for remote monitoring of NNJ. They appreciated the objectivity the app readings provided compared to visual inspection. However, they perceived that the app's applicability would be restricted to severe jaundice, were concerned about its accuracy and restriction to the English language, and lacked confidence in using it. Nevertheless, they were willing to use it once its accuracy was proven and when they received adequate guidance from health care professionals. They also suggested including an action plan for the measured readings and clinical signs within the app. Mothers proposed pairing teleconsultations with HSMAs to boost their confidence and enhance adoption. Mothers were receptive to using HSMAs but had concerns. Multiple languages, proof of accuracy, and resources to guide users should be incorporated into the app in the next phase to increase its successful adoption. Complementing such apps with a teleconsultation service presents a plausible and pragmatic NNJ care delivery model in general practice.

FORGING COMMUNITY–ACADEMIC PARTNERSHIPS FOR HEALTHY AGING: A COMMUNITY-LED TOOLKIT TO COMBAT AGEISM

Abstract There is growing recognition that community-engaged research approaches are essential for bridging the evidence-to-practice gap, especially for minoritized communities underrepresented among academic researchers. Such approaches often adopt a consultative model in which community members provide insights, perspectives, and feedback to support academic-driven projects. This strategy can be mutually beneficial when paired with cultural sensitivity and humility; however, there is a pressing need to form community-academic partnerships that flip this consultative relationship—placing university researchers as advisers on community-led projects that reflect local needs, priorities, and values. Here, we highlight the work of one such community-academic partnership led by the Center for Healthy Aging and Innovation’s (CHAI’s) Community Advisory Board with support from University of Minnesota faculty, staff, and graduate students. First, we describe the vision and formation of our Community Advisory Board (CAB), along with recruitment of its diverse membership representing eight cultural communities of the Twin Cities. We then outline the collaborative needs assessment process by which the CAB identified and prioritized action areas to advance healthy aging and health equity. Finally, we present preliminary results and early lessons learned from the CAB’s first project initiative—creation of a community-led, culturally responsive toolkit to address and reframe community-based sources of age-related stigma and discrimination. Findings from this project: 1) offer a plausible model and process for community-academic engagement which may be adapted and refined to fit local contexts; 2) underscore the value of community-led academic partnerships for addressing age-related stigma and other social factors associated with poor aging outcomes.

Transcriptomic meta-analysis reveals ERRα-mediated oxidative phosphorylation is downregulated in Fuchs' endothelial corneal dystrophy.

Late-onset Fuchs' endothelial corneal dystrophy (FECD) is a degenerative disease of cornea and the leading indication for corneal transplantation. Genetically, FECD patients can be categorized as with (RE+) or without (RE-) the CTG trinucleotide repeat expansion in the transcription factor 4 gene. The molecular mechanisms underlying FECD remain unclear, though there are plausible pathogenic models proposed for RE+ FECD. In this study, we performed a meta-analysis on RNA sequencing datasets of FECD corneal endothelium including 3 RE+ datasets and 2 RE- datasets, aiming to compare the transcriptomic profiles of RE+ and RE- FECD. Gene differential expression analysis, co-expression networks analysis, and pathway analysis were conducted. There was a striking similarity between RE+ and RE- transcriptomes. There were 1,184 genes significantly upregulated and 1,018 genes significantly downregulated in both RE+ and RE- cases. Pathway analysis identified multiple biological processes significantly enriched in both-mitochondrial functions, energy-related processes, ER-nucleus signaling pathway, demethylation, and RNA splicing were negatively enriched, whereas small GTPase mediated signaling, actin-filament processes, extracellular matrix organization, stem cell differentiation, and neutrophil mediated immunity were positively enriched. The translational initiation process was downregulated in the RE+ transcriptomes. Gene co-expression analysis identified modules with relatively distinct biological processes enriched including downregulation of mitochondrial respiratory chain complex assembly. The majority of oxidative phosphorylation (OXPHOS) subunit genes, as well as their upstream regulator gene estrogen-related receptor alpha (ESRRA), encoding ERRα, were downregulated in both RE+ and RE- cases, and the expression level of ESRRA was correlated with that of OXPHOS subunit genes. Meta-analysis increased the power of detecting differentially expressed genes. Integrating differential expression analysis with co-expression analysis helped understand the underlying molecular mechanisms. FECD RE+ and RE- transcriptomic profiles are much alike with the hallmark of downregulation of genes in pathways related to ERRα-mediated OXPHOS.