Block Copolymer Cross-Linked Nanoassemblies Improve Particle Stability and Biocompatibility of Superparamagnetic Iron Oxide Nanoparticles

PURPOSE: To develop cross-linked nanoassemblies (CNAs) as carriers for superparamagnetic iron oxide nanoparticles (IONPs). METHODS: Ferric and ferrous ions were co-precipitated inside core-shell type nanoparticles prepared by cross-linking poly(ethylene glycol)-poly(aspartate) block copolymers to prepare CNAs entrapping Fe(3)O(4) IONPs (CNA-IONPs). Particle stability and biocompatibility of CNA-IONPs were characterized in comparison to citrate-coated Fe(3)O(4) IONPs (Citrate-IONPs). RESULTS: CNA-IONPs, approximately 30 nm in diameter, showed no precipitation in water, PBS, or a cell culture medium after 3 or 30 h, at 22, 37, and 43°C, and 1, 2.5, and 5 mg/mL, whereas Citrate-IONPs agglomerated rapidly (\u3e 400 nm) in all aqueous media tested. No cytotoxicity was observed in a mouse brain endothelial-derived cell line (bEnd.3) exposed to CNA-IONPs up to 10 mg/mL for 30 h. Citrate-IONPs (\u3e 0.05 mg/mL) reduced cell viability after 3 h. CNA-IONPs retained the superparamagnetic properties of entrapped IONPs, enhancing T2-weighted magnetic resonance images (MRI) at 0.02 mg/mL, and generating heat at a mild hyperthermic level (40 ~ 42°C) with an alternating magnetic field (AMF). CONCLUSION: Compared to citric acid coating, CNAs with a cross-linked anionic core improved particle stability and biocompatibility of IONPs, which would be beneficial for future MRI and AMF-induced remote hyperthermia applications

Mucin transiently sustains coronavirus infectivity through heterogenous changes in phase morphology of evaporating aerosol

Respiratory pathogens can be spread though the transmission of aerosolised expiratory secretions in the form of droplets or particulates. Understanding the fundamental aerosol parameters that govern how such pathogens survive whilst airborne is essential to understanding and developing methods of restricting their dissemination. Pathogen viability measurements made using Controlled Electrodynamic Levitation and Extraction of Bioaerosol onto Substrate (CELEBS) in tandem with a comparative kinetics electrodynamic balance (CKEDB) measurements allow for a direct comparison between viral viability and evaporation kinetics of the aerosol with a time resolution of seconds. Here, we report the airborne survival of mouse hepatitis virus (MHV) and determine a comparable loss of infectivity in the aerosol phase to our previous observations of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Through the addition of clinically relevant concentrations of mucin to the bioaerosol, there is a transient mitigation of the loss of viral infectivity at 40% RH. Increased concentrations of mucin promoted heterogenous phase change during aerosol evaporation, characterised as the formation of inclusions within the host droplet. This research demonstrates the role of mucus in the aerosol phase and its influence on short-term airborne viral stability

Pre/pro-B cells generate macrophage populations during homeostasis and inflammation

Most tissue-resident macrophages (Mφs) are believed to be derived prenatally and are assumed to maintain themselves throughout life by self-proliferation. However, in adult mice we identified a progenitor within bone marrow, early pro-B cell/fraction B, that differentiates into tissue Mφs. These Mφ precursors have non-rearranged B-cell receptor genes and coexpress myeloid (GR1, CD11b, and CD16/32) and lymphoid (B220 and CD19) lineage markers. During steady state, these precursors exit bone marrow, losing Gr1, and enter the systemic circulation, seeding the gastrointestinal system as well as pleural and peritoneal cavities but not the brain. While in these tissues, they acquire a transcriptome identical to embryonically derived tissue-resident Mφs. Similarly, these Mφ precursors also enter sites of inflammation, gaining CD115, F4/80, and CD16/32, and become indistinguishable from blood monocyte-derived Mφs. Thus, we have identified a population of cells within the bone marrow early pro-B cell compartment that possess functional plasticity to differentiate into either tissue-resident or inflammatory Mφs, depending on microenvironmental signals. We propose that these precursors represent an additional source of Mφ populations in adult mice during steady state and inflammation

Multi-modality machine learning predicting Parkinson's disease

Personalized medicine promises individualized disease prediction and treatment. The convergence of machine learning (ML) and available multimodal data is key moving forward. We build upon previous work to deliver multimodal predictions of Parkinson's disease (PD) risk and systematically develop a model using GenoML, an automated ML package, to make improved multi-omic predictions of PD, validated in an external cohort. We investigated top features, constructed hypothesis-free disease-relevant networks, and investigated drug-gene interactions. We performed automated ML on multimodal data from the Parkinson's progression marker initiative (PPMI). After selecting the best performing algorithm, all PPMI data was used to tune the selected model. The model was validated in the Parkinson's Disease Biomarker Program (PDBP) dataset. Our initial model showed an area under the curve (AUC) of 89.72% for the diagnosis of PD. The tuned model was then tested for validation on external data (PDBP, AUC 85.03%). Optimizing thresholds for classification increased the diagnosis prediction accuracy and other metrics. Finally, networks were built to identify gene communities specific to PD. Combining data modalities outperforms the single biomarker paradigm. UPSIT and PRS contributed most to the predictive power of the model, but the accuracy of these are supplemented by many smaller effect transcripts and risk SNPs. Our model is best suited to identifying large groups of individuals to monitor within a health registry or biobank to prioritize for further testing. This approach allows complex predictive models to be reproducible and accessible to the community, with the package, code, and results publicly available

SLC37A1 and SLC37A2 Are Phosphate-Linked, Glucose-6-Phosphate Antiporters

Blood glucose homeostasis between meals depends upon production of glucose within the endoplasmic reticulum (ER) of the liver and kidney by hydrolysis of glucose-6-phosphate (G6P) into glucose and phosphate (Pi). This reaction depends on coupling the G6P transporter (G6PT) with glucose-6-phosphatase-α (G6Pase-α). Only one G6PT, also known as SLC37A4, has been characterized, and it acts as a Pi-linked G6P antiporter. The other three SLC37 family members, predicted to be sugar-phosphate:Pi exchangers, have not been characterized functionally. Using reconstituted proteoliposomes, we examine the antiporter activity of the other SLC37 members along with their ability to couple with G6Pase-α. G6PT- and mock-proteoliposomes are used as positive and negative controls, respectively. We show that SLC37A1 and SLC37A2 are ER-associated, Pi-linked antiporters, that can transport G6P. Unlike G6PT, neither is sensitive to chlorogenic acid, a competitive inhibitor of physiological ER G6P transport, and neither couples to G6Pase-α. We conclude that three of the four SLC37 family members are functional sugar-phosphate antiporters. However, only G6PT/SLC37A4 matches the characteristics of the physiological ER G6P transporter, suggesting the other SLC37 proteins have roles independent of blood glucose homeostasis

Abeta42-Induced Neurodegeneration via an Age-Dependent Autophagic-Lysosomal Injury in Drosophila

The mechanism of widespread neuronal death occurring in Alzheimer's disease (AD) remains enigmatic even after extensive investigation during the last two decades. Amyloid beta 42 peptide (Aβ1–42) is believed to play a causative role in the development of AD. Here we expressed human Aβ1–42 and amyloid beta 40 (Aβ1–40) in Drosophila neurons. Aβ1–42 but not Aβ1–40 causes an extensive accumulation of autophagic vesicles that become increasingly dysfunctional with age. Aβ1–42-induced impairment of the degradative function, as well as the structural integrity, of post-lysosomal autophagic vesicles triggers a neurodegenerative cascade that can be enhanced by autophagy activation or partially rescued by autophagy inhibition. Compromise and leakage from post-lysosomal vesicles result in cytosolic acidification, additional damage to membranes and organelles, and erosive destruction of cytoplasm leading to eventual neuron death. Neuronal autophagy initially appears to play a pro-survival role that changes in an age-dependent way to a pro-death role in the context of Aβ1–42 expression. Our in vivo observations provide a mechanistic understanding for the differential neurotoxicity of Aβ1–42 and Aβ1–40, and reveal an Aβ1–42-induced death execution pathway mediated by an age-dependent autophagic-lysosomal injury

Orally Administrated Cinnamon Extract Reduces β-Amyloid Oligomerization and Corrects Cognitive Impairment in Alzheimer's Disease Animal Models

An increasing body of evidence indicates that accumulation of soluble oligomeric assemblies of β-amyloid polypeptide (Aβ) play a key role in Alzheimer's disease (AD) pathology. Specifically, 56 kDa oligomeric species were shown to be correlated with impaired cognitive function in AD model mice. Several reports have documented the inhibition of Aβ plaque formation by compounds from natural sources. Yet, evidence for the ability of common edible elements to modulate Aβ oligomerization remains an unmet challenge. Here we identify a natural substance, based on cinnamon extract (CEppt), which markedly inhibits the formation of toxic Aβ oligomers and prevents the toxicity of Aβ on neuronal PC12 cells. When administered to an AD fly model, CEppt rectified their reduced longevity, fully recovered their locomotion defects and totally abolished tetrameric species of Aβ in their brain. Furthermore, oral administration of CEppt to an aggressive AD transgenic mice model led to marked decrease in 56 kDa Aβ oligomers, reduction of plaques and improvement in cognitive behavior. Our results present a novel prophylactic approach for inhibition of toxic oligomeric Aβ species formation in AD through the utilization of a compound that is currently in use in human diet

Genetic Evidence Implicates the Immune System and Cholesterol Metabolism in the Aetiology of Alzheimer's Disease

Background 1Late Onset Alzheimer's disease (LOAD) is the leading cause of dementia. Recent large genome-wide association studies (GWAS) identified the first strongly supported LOAD susceptibility genes since the discovery of the involvement of APOE in the early 1990s. We have now exploited these GWAS datasets to uncover key LOAD pathophysiological processes. Methodology We applied a recently developed tool for mining GWAS data for biologically meaningful information to a LOAD GWAS dataset. The principal findings were then tested in an independent GWAS dataset. Principal Findings We found a significant overrepresentation of association signals in pathways related to cholesterol metabolism and the immune response in both of the two largest genome-wide association studies for LOAD. Significance Processes related to cholesterol metabolism and the innate immune response have previously been implicated by pathological and epidemiological studies of Alzheimer's disease, but it has been unclear whether those findings reflected primary aetiological events or consequences of the disease process. Our independent evidence from two large studies now demonstrates that these processes are aetiologically relevant, and suggests that they may be suitable targets for novel and existing therapeutic approaches

Convergent genetic and expression data implicate immunity in Alzheimer's disease

Background Late–onset Alzheimer's disease (AD) is heritable with 20 genes showing genome wide association in the International Genomics of Alzheimer's Project (IGAP). To identify the biology underlying the disease we extended these genetic data in a pathway analysis. Methods The ALIGATOR and GSEA algorithms were used in the IGAP data to identify associated functional pathways and correlated gene expression networks in human brain. Results ALIGATOR identified an excess of curated biological pathways showing enrichment of association. Enriched areas of biology included the immune response (p = 3.27×10-12 after multiple testing correction for pathways), regulation of endocytosis (p = 1.31×10-11), cholesterol transport (p = 2.96 × 10-9) and proteasome-ubiquitin activity (p = 1.34×10-6). Correlated gene expression analysis identified four significant network modules, all related to the immune response (corrected p 0.002 – 0.05). Conclusions The immune response, regulation of endocytosis, cholesterol transport and protein ubiquitination represent prime targets for AD therapeutics