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At least 523 records · Page 29

Brain expression of the vascular endothelial growth factor gene family in cognitive aging and alzheimer’s disease

Vascular endothelial growth factor (VEGF) is associated with the clinical manifestation of Alzheimer’s disease (AD). However, the role of the VEGF gene family in neuroprotection is complex due to the number of biological pathways they regulate. This study explored associations between brain expression of VEGF genes with cognitive performance and AD pathology. Genetic, cognitive, and neuropathology data were acquired from the Religious Orders Study and Rush Memory and Aging Project. Expression of ten VEGF ligand and receptor genes was quantified using RNA sequencing of prefrontal cortex tissue. Global cognitive composite scores were calculated from 17 neuropsychological tests. β-amyloid and tau burden were measured at autopsy. Participants (n = 531) included individuals with normal cognition (n = 180), mild cognitive impairment (n = 148), or AD dementia (n = 203). Mean age at death was 89 years and 37% were male. Higher prefrontal cortex expression of VEGFB, FLT4, FLT1, and PGF was associated with worse cognitive trajectories (p ≤ 0.01). Increased expression of VEGFB and FLT4 was also associated with lower cognition scores at the last visit before death (p ≤ 0.01). VEGFB, FLT4, and FLT1 were upregulated among AD dementia compared with normal cognition participants (p ≤ 0.03). All four genes associated with cognition related to elevated β-amyloid (p ≤ 0.01) and/or tau burden (p ≤ 0.03). VEGF ligand and receptor genes, specifically genes relevant to FLT4 and FLT1 receptor signaling, are associated with cognition, longitudinal cognitive decline, and AD neuropathology. Future work should confirm these observations at the protein level to better understand how changes in VEGF transcription and translation relate to neurodegenerative disease.

60 APPLIED LIFE SCIENCES↗

CryoET reveals organelle phenotypes in huntington disease patient iPSC-derived and mouse primary neurons

Huntington’s disease (HD) is caused by an expanded CAG repeat in the huntingtin gene, yielding a Huntingtin protein with an expanded polyglutamine tract. While experiments with patient-derived induced pluripotent stem cells (iPSCs) can help understand disease, defining pathological biomarkers remains challenging. Here, we used cryogenic electron tomography to visualize neurites in HD patient iPSC-derived neurons with varying CAG repeats, and primary cortical neurons from BACHD, deltaN17-BACHD, and wild-type mice. In HD models, we discovered sheet aggregates in double membrane-bound organelles, and mitochondria with distorted cristae and enlarged granules, likely mitochondrial RNA granules. We used artificial intelligence to quantify mitochondrial granules, and proteomics experiments reveal differential protein content in isolated HD mitochondria. Knockdown of Protein Inhibitor of Activated STAT1 ameliorated aberrant phenotypes in iPSC- and BACHD neurons. We show that integrated ultrastructural and proteomic approaches may uncover early HD phenotypes to accelerate diagnostics and the development of targeted therapeutics for HD.

59 BASIC BIOLOGICAL SCIENCES↗

How short peptides disassemble tau fibrils in Alzheimer’s disease

Reducing fibrous aggregates of the protein tau is a possible strategy for halting the progression of Alzheimer’s disease (AD). Previously, we found that in vitro, the d-enantiomeric peptide (D-peptide) D-TLKIVWC disassembles ultra-stable tau fibrils extracted from the autopsied brains of individuals with AD (hereafter, these tau fibrils are referred to as AD-tau) into benign segments, with no energy source other than ambient thermal agitation. To consider D-peptide-mediated disassembly as a potential route to therapeutics for AD, it is essential to understand the mechanism and energy source of the disassembly action. Here, in this work, we show that the assembly of D-peptides into amyloid-like (‘mock-amyloid’) fibrils is essential for AD-tau disassembly. These mock-amyloid fibrils have a right-handed twist but are constrained to adopt a left-handed twist when templated in complex with AD-tau. The release of strain that accompanies the conversion of left-twisted to right-twisted, relaxed mock-amyloid produces a torque that is sufficient to break the local hydrogen bonding between tau molecules, and leads to the fragmentation of AD-tau. This strain-relief mechanism seems to operate in other examples of amyloid fibril disassembly, and could inform the development of first-in-class therapeutics for amyloid diseases.

Alzheimer's disease↗

The cardiac molecular setting of metabolic syndrome in pigs reveals disease susceptibility and suggests mechanisms that exacerbate COVID-19 outcomes in patients

Abstract Although metabolic syndrome (MetS) is linked to an elevated risk of cardiovascular disease (CVD), the cardiac-specific risk mechanism is unknown. Obesity, hypertension, and diabetes (all MetS components) are the most common form of CVD and represent risk factors for worse COVID-19 outcomes compared to their non MetS peers. Here, we use obese Yorkshire pigs as a highly relevant animal model of human MetS, where pigs develop the hallmarks of human MetS and reproducibly mimics the myocardial pathophysiology in patients. Myocardium-specific mass spectroscopy-derived metabolomics, proteomics, and transcriptomics enabled the identity and quality of proteins and metabolites to be investigated in the myocardium to greater depth. Myocardium-specific deregulation of pro-inflammatory markers, propensity for arterial thrombosis, and platelet aggregation was revealed by computational analysis of differentially enriched pathways between MetS and control animals. While key components of the complement pathway and the immune response to viruses are under expressed, key N6-methyladenosin RNA methylation enzymes are largely overexpressed in MetS. Blood tests do not capture the entirety of metabolic changes that the myocardium undergoes, making this analysis of greater value than blood component analysis alone. Our findings create data associations to further characterize the MetS myocardium and disease vulnerability, emphasize the need for a multimodal therapeutic approach, and suggests a mechanism for observed worse outcomes in MetS patients with COVID-19 comorbidity.

60 APPLIED LIFE SCIENCES↗

Preparing for the next pandemic via transfer learning from existing diseases with hierarchical multi-modal BERT: a study on COVID-19 outcome prediction

Abstract Developing prediction models for emerging infectious diseases from relatively small numbers of cases is a critical need for improving pandemic preparedness. Using COVID-19 as an exemplar, we propose a transfer learning methodology for developing predictive models from multi-modal electronic healthcare records by leveraging information from more prevalent diseases with shared clinical characteristics. Our novel hierarchical, multi-modal model ( $${\textsc {TransMED}}$$ T R A N S MED ) integrates baseline risk factors from the natural language processing of clinical notes at admission, time-series measurements of biomarkers obtained from laboratory tests, and discrete diagnostic, procedure and drug codes. We demonstrate the alignment of $${\textsc {TransMED}}$$ T R A N S MED ’s predictions with well-established clinical knowledge about COVID-19 through univariate and multivariate risk factor driven sub-cohort analysis. $${\textsc {TransMED}}$$ T R A N S MED ’s superior performance over state-of-the-art methods shows that leveraging patient data across modalities and transferring prior knowledge from similar disorders is critical for accurate prediction of patient outcomes, and this approach may serve as an important tool in the early response to future pandemics.

59 BASIC BIOLOGICAL SCIENCES↗

Prediction of chronic kidney disease progression using recurrent neural network and electronic health records

Chronic kidney disease (CKD) is a progressive loss in kidney function. Early detection of patients who will progress to late-stage CKD is of paramount importance for patient care. To address this, we develop a pipeline to process longitudinal electronic heath records (EHRs) and construct recurrent neural network (RNN) models to predict CKD progression from stages II/III to stages IV/V. The RNN model generates predictions based on time-series records of patients, including repeated lab tests and other clinical variables. Our investigation reveals that using a single variable, the recorded estimated glomerular filtration rate (eGFR) over time, the RNN model achieves an average area under the receiver operating characteristic curve (AUROC) of 0.957 for predicting future CKD progression. When additional clinical variables, such as demographics, vital information, lab test results, and health behaviors, are incorporated, the average AUROC increases to 0.967. In both scenarios, the standard deviation of the AUROC across cross-validation trials is less than 0.01, indicating a stable and high prediction accuracy. Our analysis results demonstrate the proposed RNN model outperforms existing standard approaches, including static and dynamic Cox proportional hazards models, random forest, and LightGBM. The utilization of the RNN model and the time-series data of previous eGFR measurements underscores its potential as a straightforward and effective tool for assessing the clinical risk of CKD patients concerning their disease progression.

60 APPLIED LIFE SCIENCES↗

Identification of an adhesive interface for the non-clustered δ1 protocadherin-1 involved in respiratory diseases

Cadherins form a large family of calcium-dependent adhesive proteins involved in morphogenesis, cell differentiation, and neuronal connectivity. Non-clustered δ1 protocadherins form a cadherin subgroup of proteins with seven extracellular cadherin (EC) repeats and cytoplasmic domains distinct from those of classical cadherins. Non-clustered δ1 protocadherins mediate homophilic adhesion and have been implicated in various diseases including asthma, autism, and cancer. Here we present X-ray crystal structures of human Protocadherin-1 (PCDH1), a δ1-protocadherin member essential for New World Hantavirus infection that is typically expressed in the brain, airway epithelium, skin keratinocytes, and lungs. The structures suggest a binding mode that involves antiparallel overlap of repeats EC1 to EC4. Mutagenesis combined with binding assays and biochemical experiments validated this mode of adhesion. Overall, these results reveal the molecular mechanism underlying adhesiveness of PCDH1 and δ1-protocadherins, also shedding light on PCDH1’s role in maintaining airway epithelial integrity, the loss of which causes respiratory diseases.

59 BASIC BIOLOGICAL SCIENCES↗

Personalized whole-brain neural mass models reveal combined Aβ and tau hyperexcitable influences in Alzheimer's disease.

Neuronal dysfunction and cognitive deterioration in Alzheimer's disease (AD) are likely caused by multiple pathophysiological factors. However, mechanistic evidence in humans remains scarce, requiring improved non-invasive techniques and integrative models. We introduce personalized AD computational models built on whole-brain Wilson-Cowan oscillators and incorporating resting-state functional MRI, amyloid-β (Aβ) and tau-PET from 132 individuals in the AD spectrum to evaluate the direct impact of toxic protein deposition on neuronal activity. This subject-specific approach uncovers key patho-mechanistic interactions, including synergistic Aβ and tau effects on cognitive impairment and neuronal excitability increases with disease progression. The data-derived neuronal excitability values strongly predict clinically relevant AD plasma biomarker concentrations (p-tau217, p-tau231, p-tau181, GFAP) and grey matter atrophy obtained through voxel-based morphometry. Furthermore, reconstructed EEG proxy quantities show the hallmark AD electrophysiological alterations (theta band activity enhancement and alpha reductions) which occur with Aβ-positivity and after limbic tau involvement. Microglial activation influences on neuronal activity are less definitive, potentially due to neuroimaging limitations in mapping neuroprotective vs detrimental activation phenotypes. Mechanistic brain activity models can further clarify intricate neurodegenerative processes and accelerate preventive/treatment interventions.

60 APPLIED LIFE SCIENCES↗

Iron and aluminum interaction with amyloid-beta peptides associated with Alzheimer’s disease

An elevation in the concentration of heavy metal ions in Alzheimer’s disease (AD) brain has been demonstrated in many studies. Aβ precipitation and toxicity in AD brains seem to be caused by abnormal interactions with neocortical metal ions, especially iron, copper, zinc, and aluminum [1–3]. There is increasing evidence that iron and aluminum ions are involved in the mechanisms that underlie the neurodegenerative diseases [4,5]. However, evidence was brought to demonstrate that some Aβ fragments, at physiological pH, are not able to form binary complexes with Fe(III) ions of sufficient stability to compete with metal hydroxide precipitation [6]. On the contrary, multiple metal ions are known to interact with Aβ peptides [7]. Consequently, we investigated here the interaction of Fe(II/III) and Al(III) ions with some amyloid-β peptides and fragments that results in peptide aggregation and fibrillation [8,9]. Infrared spectroscopy, atomic force microscopy, scanning electron microscopy, electrophoresis and mass spectrometry demonstrated conformational changes of peptides in the presence of such metals.

60 APPLIED LIFE SCIENCES↗

Multispectral medical image fusion in Contourlet domain for computer based diagnosis of Alzheimer’s disease

Computer based diagnosis of Alzheimer’s disease can be performed by dint of the analysis of the functional and structural changes in the brain. Multispectral image fusion deliberates upon fusion of the complementary information while discarding the surplus information to achieve a solitary image which encloses both spatial and spectral details. This paper presents a Non-Sub-sampled Contourlet Transform (NSCT) based multispectral image fusion model for computer-aided diagnosis of Alzheimer’s disease. The proposed fusion methodology involves color transformation of the input multispectral image. The multispectral image in YIQ color space is decomposed using NSCT followed by dimensionality reduction using modified Principal Component Analysis algorithm on the low frequency coefficients. Further, the high frequency coefficients are enhanced using non-linear enhancement function. Two different fusion rules are then applied to the low-pass and high-pass sub-bands: Phase congruency is applied to low frequency coefficients and a combination of directive contrast and normalized Shannon entropy is applied to high frequency coefficients. The superiority of the fusion response is depicted by the comparisons made with the other state-of-the-art fusion approaches (in terms of various fusion metrics).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Structure of the Newcastle disease virus hemagglutinin-neuraminidase (HN) ectodomain reveals a four-helix bundle stalk

The paramyxovirus hemagglutinin-neuraminidase (HN) protein plays multiple roles in viral entry and egress, including binding to sialic acid receptors, activating the fusion (F) protein to activate membrane fusion and viral entry, and cleaving sialic acid from carbohydrate chains. HN is an oligomeric integral membrane protein consisting of an N-terminal transmembrane domain, a stalk region, and an enzymatically active neuraminidase (NA) domain. Structures of the HN NA domains have been solved previously; however, the structure of the stalk region has remained elusive. The stalk region contains specificity determinants for F interactions and activation, underlying the requirement for homotypic F and HN interactions in viral entry. Mutations of the Newcastle disease virus HN stalk region have been shown to affect both F activation and NA activities, but a structural basis for understanding these dual affects on HN functions has been lacking. Here, we report the structure of the Newcastle disease virus HN ectodomain, revealing dimers of NA domain dimers flanking the N-terminal stalk domain. The stalk forms a parallel tetrameric coiled-coil bundle (4HB) that allows classification of extensive mutational data, providing insight into the functional roles of the stalk region. Mutations that affect both F activation and NA activities map predominantly to the 4HB hydrophobic core, whereas mutations that affect only F-protein activation map primarily to the 4HB surface. Two of four NA domains interact with the 4HB stalk, and residues at this interface in both the stalk and NA domain have been implicated in HN function.

59 BASIC BIOLOGICAL SCIENCES↗

Broad and potent neutralizing human antibodies to tick-borne flaviviruses protect mice from disease

Tick-borne encephalitis virus (TBEV) is an emerging human pathogen that causes potentially fatal disease with no specific treatment. Mouse monoclonal antibodies are protective against TBEV, but little is known about the human antibody response to infection. Here, we report on the human neutralizing antibody response to TBEV in a cohort of infected and vaccinated individuals. Expanded clones of memory B cells expressed closely related anti-envelope domain III (EDIII) antibodies in both groups of volunteers. However, the most potent neutralizing antibodies, with IC50s below 1 ng/ml, were found only in individuals who recovered from natural infection. These antibodies also neutralized other tick-borne flaviviruses, including Langat, louping ill, Omsk hemorrhagic fever, Kyasanur forest disease, and Powassan viruses. Structural analysis revealed a conserved epitope near the lateral ridge of EDIII adjoining the EDI–EDIII hinge region. Prophylactic or early therapeutic antibody administration was effective at low doses in mice that were lethally infected with TBEV.

60 APPLIED LIFE SCIENCES↗

Including frameworks of public health ethics in computational modelling of infectious disease interventions

Decisions on public health interventions to control infectious diseases are often informed by computational models. Interpreting the predicted outcomes of a public health decision requires not only high-quality modelling but also an ethical framework for assessing the benefits and harms associated with different options. The design and specification of ethical frameworks matured independently of computational modelling, so many values recognized as important for ethical decision-making are missing from computational models. We demonstrate a proof-of-concept approach to incorporate multiple public health values into the evaluation of a simple computational model for vaccination against a pathogen such as SARS-CoV-2. By examining a bounded space of alternative prioritizations of three values relevant to public health ethics (aggregate clinical burden, equity in clinical burden, equity in adverse effects from vaccination), we identify value trade-offs, where the outcomes of optimal strategies differ depending on the ethical framework. This work demonstrates an approach to incorporating diverse values into decision criteria used to evaluate outcomes of models of infectious disease interventions.

"Mathematical Biology"↗

Ethical considerations in infectious disease modelling for public health policy: the case of school closures

Mathematical models of infectious diseases are frequently used as a tool to support public health policy and decisions around the implementation of interventions such as school closures. However, most publications on policy-relevant modelling lack an ethical framework and do not explicitly consider the ethical implications of the work. This creates a risk that the unintended consequences of interventions are overlooked or that models are used to justify decisions that are inconsistent with public health ethics. In this article, we focus on the case study of school closures as a commonly modelled intervention against pandemic influenza, COVID-19 and other infectious disease threats. We briefly review some of the key concepts in public health ethics and describe approaches to modelling the effects of school closures. We then identify a series of ethical considerations involved in modelling school closures. These include accounting for population heterogeneity and inequalities; including a diversity of viewpoints and expertise in model design; considering the distribution of benefits and harms; and model transparency and contextualization. Furthermore, we conclude with some recommendations to ensure that policy-relevant modelling is consistent with some key ethics values.

97 MATHEMATICS AND COMPUTING↗

Ferrous iron formation following the co-aggregation of ferric iron and the Alzheimer's disease peptide β-amyloid (1–42)

For decades, a link between increased levels of iron and areas of Alzheimer’s disease (AD) pathology has been recognized, including AD lesions comprised of the peptide b-amyloid (Ab). Despite many observations of this association, the relationship between Ab and iron is poorly understood. Using X-ray microspectroscopy, X-ray absorption spectroscopy, electron microscopy and spectrophotometric iron(II) quantification techniques, we examine the interaction between Ab(1–42) and synthetic iron(III), reminiscent of ferric iron stores in the brain. We report Ab to be capable of accumulating iron(III) within amyloid aggregates, with this process resulting in Ab-mediated reduction of iron(III) to a redox-active iron(II) phase. Additionally, we show that the presence of aluminium increases the reductive capacity of Ab, enabling the redox cycling of the iron. These results demonstrate the ability of Ab to accumulate iron, offering an explanation for previously observed local increases in iron concentration associated with AD lesions. Furthermore, the ability of iron to form redox-active iron phases from ferric precursors provides an origin both for the redox-active iron previously witnessed in AD tissue, and the increased levels of oxidative stress characteristic of AD. These interactions between Ab and iron deliver valuable insights into the process of AD progression, which may ultimately provide targets for disease therapies.

redox↗

Climate, environmental and socio-economic change: weighing up the balance in vector-borne disease transmission

Arguably one of the most important effects of climate change is the potential impact on human health. While this is likely to take many forms, the implications for future transmission of vector-borne diseases (VBDs), given their ongoing contribution to global disease burden, are both extremely important and highly uncertain. In part, this is due not only to data limitations and methodological challenges when integrating climate-driven VBD models and climate change projections, but, perhaps most crucially, the multitude of epidemiological, ecological, and socioeconomic factors that drive VBD transmission, and this complexity has generated considerable debate over the last 10-15 years. In this article, and Theme Issue, we seek to elucidate current knowledge around this topic, identify key themes and uncertainties, evaluate ongoing challenges and open research questions, and, crucially, offer some solutions for the field moving forwards. Although many of these challenges are ubiquitous across multiple VBDs, more specific issues also arise in different vector-pathogen systems. This Theme Issue seeks to cover both, reflected in the breadth and depth of the topics and VBD-systems considered, itself strongly indicative of the challenging, but necessary, multidisciplinary nature of this research field.

54 ENVIRONMENTAL SCIENCES↗

FOXO3 targets are reprogrammed as Huntington's disease neural cells and striatal neurons face senescence with p16 INK4a increase

Neurodegenerative diseases (ND) have been linked to the critical process in aging-cellular senescence. However, the temporal dynamics of cellular senescence in ND conditions is unresolved. Here, we show senescence features develop in human Huntington's disease (HD) neural stem cells (NSCs) and medium spiny neurons (MSNs), including the increase of p16 INK4a , a key inducer of cellular senescence. We found that HD NSCs reprogram the transcriptional targets of FOXO3, a major cell survival factor able to repress cell senescence, antagonizing p16 INK4a expression via the FOXO3 repression of the transcriptional modulator ETS2. Additionally, p16 INK4a promotes cellular senescence features in human HD NSCs and MSNs. These findings suggest that cellular senescence may develop during neuronal differentiation in HD and that the FOXO3-ETS2-p16 INK4a axis may be part of molecular responses aimed at mitigating this phenomenon. Our studies identify neuronal differentiation with accelerated aging of neural progenitors and neurons as an alteration that could be linked to NDs.

59 BASIC BIOLOGICAL SCIENCES↗

A chromosome-scale reference genome of trifoliate orange ( Poncirus trifoliata ) provides insights into disease resistance, cold tolerance and genome evolution in Citrus

Trifoliate orange (Poncirus trifoliata), a deciduous close relative of evergreen Citrus, has important traits for citrus production, including tolerance/resistance to citrus greening disease (Huanglongbing, HLB) and other major diseases, and cold tolerance. It has been one of the most important rootstocks, and one of the most valuable sources of resistance and tolerance genes for citrus. Here we present a high-quality, chromosomescale genome assembly of P. trifoliata. The 264.9-Mb assembly contains nine chromosomal pseudomolecules with 25 538 protein-coding genes, covering 97.2% of the estimated gene space. Comparative analyses of P. trifoliata and nine Citrus genomes revealed 605 species-specific genes and six rapidly evolving gene families in the P. trifoliata genome. Poncirus trifoliata has evolved specific adaptation in the C-repeat/ DREB binding factor (CBF)-dependent and CBF-independent cold signaling pathways to tolerate cold. We identified candidate genes within quantitative trait loci for HLB tolerance, and at the loci for resistance to citrus tristeza virus and citrus nematode. Genetic diversity analysis of Poncirus accessions and Poncirus/ Citrus hybrids shows a narrow genetic base in the US germplasm collection, and points to the importance of collecting and preserving more natural genetic variation. Two phenotypically divergent Poncirus accessions are found to be clonally related, supporting a previous conjecture that dwarf Flying Dragon originated as a mutant of a non-dwarfing type. The high-quality genome reveals features and evolutionary insights of Poncirus, and it will serve as a valuable resource for genetic, genomic and molecular research and manipulation in citrus.

54 ENVIRONMENTAL SCIENCES↗