Characterizing molecular and synaptic signatures in mouse models of late-onset Alzheimer's disease independent of amyloid and tau pathology.

INTRODUCTION: MODEL-AD (Model Organism Development and Evaluation for Late-Onset Alzheimer's Disease) is creating and distributing novel mouse models with humanized, clinically relevant genetic risk factors to capture the trajectory and progression of late-onset Alzheimer's disease (LOAD) more accurately. METHODS: We created the LOAD2 model by combining apolipoprotein E4 (APOE4), Trem2*R47H, and humanized amyloid-beta (Aß). Mice were subjected to a control diet or a high-fat/high-sugar diet (LOAD2+HFD). We assessed disease-relevant outcome measures in plasma and brain including neuroinflammation, Aß, neurodegeneration, neuroimaging, and multi-omics. RESULTS: By 18 months, LOAD2+HFD mice exhibited sex-specific neuron loss, elevated insoluble brain Aß42, increased plasma neurofilament light chain (NfL), and altered gene/protein expression related to lipid metabolism and synaptic function. Imaging showed reductions in brain volume and neurovascular uncoupling. Deficits in acquiring touchscreen-based cognitive tasks were observed. DISCUSSION: The comprehensive characterization of LOAD2+HFD mice reveals that this model is important for preclinical studies seeking to understand disease trajectory and progression of LOAD prior to or independent of amyloid plaques and tau tangles. HIGHLIGHTS: By 18 months, unlike control mice (e.g., LOAD2 mice fed a control diet, CD), LOAD2+HFD mice presented subtle but significant loss of neurons in the cortex, elevated levels of insoluble Ab42 in the brain, and increased plasma neurofilament light chain (NfL). Transcriptomics and proteomics showed changes in gene/proteins relating to a variety of disease-relevant processes including lipid metabolism and synaptic function. In vivo imaging revealed an age-dependent reduction in brain region volume (MRI) and neurovascular uncoupling (PET/CT). LOAD2+HFD mice also demonstrated deficits in acquisition of touchscreen-based cognitive tasks.

Assessment of neurovascular uncoupling: APOE status is a key driver of early metabolic and vascular dysfunction.

BACKGROUND: Alzheimer's disease (AD) is the most common cause of dementia worldwide, with apolipoprotein Eε4 (APOEε4) being the strongest genetic risk factor. Current clinical diagnostic imaging focuses on amyloid and tau; however, new methods are needed for earlier detection. METHODS: PET imaging was used to assess metabolism-perfusion in both sexes of aging C57BL/6J, and hAPOE mice, and were verified by transcriptomics, and immunopathology. RESULTS: All hAPOE strains showed AD phenotype progression by 8 months, with females exhibiting the regional changes, which correlated with GO-term enrichments for glucose metabolism, perfusion, and immunity. Uncoupling analysis revealed APOEε4/ε4 exhibited significant Type-1 uncoupling (↓ glucose uptake, ↑ perfusion) at 8 and 12 months, while APOEε3/ε4 demonstrated Type-2 uncoupling (↑ glucose uptake, ↓ perfusion), while immunopathology confirmed cell specific contributions. DISCUSSION: This work highlights APOEε4 status in AD progression manifests as neurovascular uncoupling driven by immunological activation, and may serve as an early diagnostic biomarker. HIGHLIGHTS: We developed a novel analytical method to analyze PET imaging of 18F-FDG and 64Cu-PTSM data in both sexes of aging C57BL/6J, and hAPOEε3/ε3, hAPOEε4/ε4, and hAPOEε3/ε4 mice to assess metabolism-perfusion profiles termed neurovascular uncoupling. This analysis revealed APOEε4/ε4 exhibited significant Type-1 uncoupling (decreased glucose uptake, increased perfusion) at 8 and 12 months, while APOEε3/ε4 demonstrated significant Type-2 uncoupling (increased glucose uptake, decreased perfusion) by 8 months which aligns with immunopathology and transcriptomic signatures. This work highlights that there may be different mechanisms underlying age related changes in APOEε4/ε4 compared with APOEε3/ε4. We predict that these changes may be driven by immunological activation and response, and may serve as an early diagnostic biomarker.

Metabolomics profiling reveals distinct, sex-specific signatures in serum and brain metabolomes in mouse models of Alzheimer's disease.

INTRODUCTION: Increasing evidence suggests that metabolic impairments contribute to early Alzheimer's disease (AD) mechanisms and subsequent dementia. Signals in metabolic pathways conserved across species can facilitate translation. METHODS: We investigated differences in serum and brain metabolites between the early-onset 5XFAD and late-onset LOAD1 (APOE4.Trem2*R47H) mouse models of AD to C57BL/6J controls at 6 months of age. RESULTS: We identified sex differences for several classes of metabolites, such as glycerophospholipids, sphingolipids, and amino acids. Metabolic signatures were notably different between brain and serum in both mouse models. The 5XFAD mice exhibited stronger differences in brain metabolites, whereas LOAD1 mice showed more pronounced differences in serum. DISCUSSION: Several of our findings were consistent with results in humans, showing glycerophospholipids reduction in serum of apolipoprotein E (apoE) ε4 carriers and replicating the serum metabolic imprint of the APOE ε4 genotype. Our work thus represents a significant step toward translating metabolic dysregulation from model organisms to human AD. HIGHLIGHTS: This was a metabolomic assessment of two mouse models relevant to Alzheimer's disease. Mouse models exhibit broad sex-specific metabolic differences, similar to human study cohorts. The early-onset 5XFAD mouse model primarily alters brain metabolites while the late-onset LOAD1 model primarily changes serum metabolites. Apolipoprotein E (apoE) ε4 mice recapitulate glycerophospolipid signatures of human APOE ε4 carriers in both brain and serum.

In vivo validation of late-onset Alzheimer's disease genetic risk factors.

INTRODUCTION: Genome-wide association studies have identified over 70 genetic loci associated with late-onset Alzheimer's disease (LOAD), but few candidate polymorphisms have been functionally assessed for disease relevance and mechanism of action. METHODS: Candidate genetic risk variants were informatically prioritized and individually engineered into a LOAD-sensitized mouse model that carries the AD risk variants APOE ε4/ε4 and Trem2*R47H. The potential disease relevance of each model was assessed by comparing brain transcriptomes measured with the Nanostring Mouse AD Panel at 4 and 12 months of age with human study cohorts. RESULTS: We created new models for 11 coding and loss-of-function risk variants. Transcriptomic effects from multiple genetic variants recapitulated a variety of human gene expression patterns observed in LOAD study cohorts. Specific models matched to emerging molecular LOAD subtypes. DISCUSSION: These results provide an initial functionalization of 11 candidate risk variants and identify potential preclinical models for testing targeted therapeutics. HIGHLIGHTS: A novel approach to validate genetic risk factors for late-onset AD (LOAD) is presented. LOAD risk variants were knocked in to conserved mouse loci. Variant effects were assayed by transcriptional analysis. Risk variants in Abca7, Mthfr, Plcg2, and Sorl1 loci modeled molecular signatures of clinical disease. This approach should generate more translationally relevant animal models.

Remote loading in liposome: a review of current strategies and recent developments.

Liposomes have gained prominence as nanocarriers in drug delivery, and the number of products in the market is increasing steadily, particularly in cancer therapeutics. Remote loading of drugs in liposomes is a significant step in the translation and commercialization of the first liposomal product. Low drug loading and drug leakage from liposomes is a translational hurdle that was effectively circumvented by the remote loading process. Remote loading or active loading could load nearly 100% of the drug, which was not possible with the passive loading procedure. A major drawback of conventional remote loading is that only a very small percentage of the drugs are amenable to this method. Therefore, methods for drug loading are still a problem for several drugs. The loading of multiple drugs in liposomes to improve the efficacy and safety of nanomedicine has gained prominence recently with the introduction of a marketed formulation (Vyxeos) that improves overall survival in acute myeloid leukemia. Different strategies for modifying the remote loading process to overcome the drawbacks of the conventional method are discussed here. The review aims to discuss the latest developments in remote loading technology and its implications in liposomal drug delivery.

Assessment of Neurovascular Uncoupling: APOE Status is a Key Driver of Early Metabolic and Vascular Dysfunction.

BACKGROUND: Alzheimer's disease (AD) is the most common cause of dementia worldwide, with apolipoprotein ε4 (APOEε4) being the strongest genetic risk factor. Current clinical diagnostic imaging focuses on amyloid and tau; however, new methods are needed for earlier detection. METHODS: PET imaging was used to assess metabolism-perfusion in both sexes of aging C57BL/6J, and hAPOE mice, and were verified by transcriptomics, and immunopathology. RESULTS: All hAPOE strains showed AD phenotype progression by 8 mo, with females exhibiting the regional changes, which correlated with GO-term enrichments for glucose metabolism, perfusion, and immunity. Uncoupling analysis revealed APOEε4/ε4 exhibited significant Type-1 uncoupling (↓ glucose uptake, ↑ perfusion) at 8 and 12 mo, while APOEε3/ε4 demonstrated Type-2 uncoupling (↑ glucose uptake, ↓ perfusion), while immunopathology confirmed cell specific contributions. DISCUSSION: This work highlights APOEε4 status in AD progression manifest as neurovascular uncoupling driven by immunological activation, and may serve as an early diagnostic biomarker.

Levetiracetam Modulates Brain Metabolic Networks and Transcriptomic Signatures in the 5XFAD Mouse Model of Alzheimer's disease.

INTRODUCTION: Subcritical epileptiform activity is associated with impaired cognitive function and is commonly seen in patients with Alzheimer's disease (AD). The anti-convulsant, levetiracetam (LEV), is currently being evaluated in clinical trials for its ability to reduce epileptiform activity and improve cognitive function in AD. The purpose of the current study was to apply pharmacokinetics (PK), network analysis of medical imaging, gene transcriptomics, and PK/PD modeling to a cohort of amyloidogenic mice to establish how LEV restores or drives alterations in the brain networks of mice in a dose-dependent basis using the rigorous preclinical pipeline of the MODEL-AD Preclinical Testing Core. METHODS: Chronic LEV was administered to 5XFAD mice of both sexes for 3 months based on allometrically scaled clinical dose levels from PK models. Data collection and analysis consisted of a multi-modal approach utilizing 18F-FDG PET/MRI imaging and analysis, transcriptomic analyses, and PK/PD modeling. RESULTS: Pharmacokinetics of LEV showed a sex and dose dependence in Cmax, CL/F, and AUC0-∞, with simulations used to estimate dose regimens. Chronic dosing at 10, 30, and 56 mg/kg, showed 18F-FDG specific regional differences in brain uptake, and in whole brain covariance measures such as clustering coefficient, degree, network density, and connection strength (i.e. positive and negative). In addition, transcriptomic analysis via nanoString showed dose-dependent changes in gene expression in pathways consistent 18F-FDG uptake and network changes, and PK/PD modeling showed a concentration dependence for key genes, but not for network covariance modeling. DISCUSSION: This study represents the first report detailing the relationships of metabolic covariance and transcriptomic network changes resulting from LEV administration in 5XFAD mice. Overall, our results highlight non-linear kinetics based on dose and sex, where gene expression analysis demonstrated LEV dose- and concentration- dependent changes, along with cerebral metabolism, and/or cerebral homeostatic mechanisms relevant to human AD, which aligned closely with network covariance analysis of 18F-FDG images. Collectively, this study show cases the value of a multimodal connectomic, transcriptomic, and pharmacokinetic approach to further investigate dose dependent relationships in preclinical studies, with translational value towards informing clinical study design.

Advancing water treatment sustainability: Investigating electrified Ti3C2Tx composite membranes for minimizing microplastic fouling.

The overuse of plastics has led to a large influx of microplastics (MPs) in water bodies and water/wastewater treatment plants. Coupled with the ongoing water crisis, this poses a threat to freshwater availability as MPs disrupt the operation of these plants. MPs cause severe fouling of low-pressure membrane technologies such as ultrafiltration (UF) due to the strong adhesion between MPs and the membrane surface. An electrified membrane-based technology is suggested as an alternative MP fouling mitigation strategy. In this study, composite membranes of sulfonated polyethersulfone (SPES)/MXene (Ti3C2Tx) were fabricated and evaluated as a promising candidate for mitigating fouling of MPs. The described SPES/Ti3C2Tx composite membrane was designed to improve important physiochemical properties such as conductivity without affecting water flux. The membranes were tested under different electrical potentials to find an optimal strategy to reduce MP fouling. The performance tests showed that the flux increased from 42 L m-2. h-1 at 0 V to 49 L m-2. h-1 at 2 V due to electrostatic repulsion when 5 wt% Ti3C2Tx was used as a result of the applied electric potential. In addition, it was shown that intermittent applied voltage using "30 min ON: 60 min OFF" mode resulted in more stable water flux due to in-situ coagulant formation and cleaning. This study illustrates the potential of MXene-based membranes for mitigating MP fouling and paves the way for future research on membrane materials that can enhance system performance.

3D bioengineered neural tissue generated from patient-derived iPSCs mimics time-dependent phenotypes and transcriptional features of Alzheimer's disease.

Several iPSC-derived three-dimensional (3D) cultures have been generated to model Alzheimer's disease (AD). While some AD-related phenotypes have been identified across these cultures, none of them could recapitulate multiple AD-related hallmarks in one model. To date, the transcriptomic features of these 3D models have not been compared with those of human AD brains. However, these data are crucial to understanding the pertinency of these models for studying AD-related pathomechanisms over time. We developed a 3D bioengineered model of iPSC-derived neural tissue that combines a porous scaffold composed of silk fibroin protein with an intercalated collagen hydrogel to support the growth of neurons and glial cells into complex and functional networks for an extended time, a fundamental requisite for aging studies. Cultures were generated from iPSC lines obtained from two subjects carrying the familial AD (FAD) APP London mutation, two well-studied control lines, and an isogenic control. Cultures were analyzed at 2 and 4.5 months. At both time points, an elevated Aß42/40 ratio was detected in conditioned media from FAD cultures. However, extracellular Aß42 deposition and enhanced neuronal excitability were observed in FAD culture only at 4.5 months, suggesting that extracellular Aß deposition may trigger enhanced network activity. Remarkably, neuronal hyperexcitability has been described in AD patients early in the disease. Transcriptomic analysis revealed the deregulation of multiple gene sets in FAD samples. Such alterations were strikingly similar to those observed in human AD brains. These data provide evidence that our patient-derived FAD model develops time-dependent AD-related phenotypes and establishes a temporal relation among them. Furthermore, FAD iPSC-derived cultures recapitulate transcriptomic features of AD patients. Thus, our bioengineered neural tissue represents a unique tool to model AD in vitro over time.

Surveillance, distribution, and treatment methods of antimicrobial resistance in water: A review.

The World Health Organization (WHO) recognizes antimicrobial resistance (AMR) as a serious threat to human health. Scientists warn that the world is approaching a post-antibiotic era, in which antibiotics will be ineffective, and AMR infections may become a leading cause of death worldwide. Wastewater treatment plants (WWTPs) have been identified as hotspots for the spread and reproduction of AMR. This review focuses on the fate of AMR in WWTPs and advanced water treatment processes, highlighting their removal efficiencies and limitations. Additionally, methods for monitoring AMR in WWTPs and aquatic environments are discussed. Monitoring of AMR in wastewater is crucial for tracking its presence and spread to the environment. Advanced AMR treatment processes such as membrane bioreactors (MBRs), vermifiltration (VF), advanced oxidation processes (AOPs), and membrane filtration processes (MFPs) are discussed and compared.

Differential splicing of neuronal genes in a Trem2*R47H mouse model mimics alterations associated with Alzheimer's disease.

BACKGROUND: Molecular characterization of late-onset Alzheimer's disease (LOAD), the leading cause of age-related dementia, has revealed transcripts, proteins, and pathway alterations associated with disease. Assessing these postmortem signatures of LOAD in experimental model systems can further elucidate their relevance to disease origins and progression. Model organisms engineered with human genetic factors further link these signatures to disease-associated variants, especially when studies are designed to leverage homology across species. Here we assess differential gene splicing patterns in aging mouse models carrying humanized APOE4 and/or the Trem2*R47H variant on a C57BL/6J background. We performed a differential expression of gene (DEG) and differential splicing analyses on whole brain transcriptomes at multiple ages. To better understand the difference between differentially expressed and differentially spliced genes, we evaluated enrichment of KEGG pathways and cell-type specific gene signatures of the adult brain from each alteration type. To determine LOAD relevance, we compared differential splicing results from mouse models with multiple human AD splicing studies. RESULTS: We found that differentially expressed genes in Trem2*R47H mice were significantly enriched in multiple AD-related pathways, including immune response, osteoclast differentiation, and metabolism, whereas differentially spliced genes were enriched for neuronal related functions, including GABAergic synapse and glutamatergic synapse. These results were reinforced by the enrichment of microglial genes in DEGs and neuronal genes in differentially spliced genes in Trem2*R47H mice. We observed significant overlap between differentially spliced genes in Trem2*R47H mice and brains from human AD subjects. These effects were absent in APOE4 mice and suppressed in APOE4.Trem2*R47H double mutant mice relative to Trem2*R47H mice. CONCLUSIONS: The cross-species observation that alternative splicing observed in LOAD are present in Trem2*R47H mouse models suggests a novel link between this candidate risk gene and molecular signatures of LOAD in neurons and demonstrates how deep molecular analysis of new genetic models links molecular disease outcomes to a human candidate gene.

Reduction in GABAB on glia induce Alzheimer's disease related changes.

Alzheimer's Disease (AD) is a neurodegenerative disorder characterized by beta-amyloid plaques (Aß), neurofibrillary tangles (NFT), and neuroinflammation. Data have demonstrated that neuroinflammation contributes to Aß and NFT onset and progression, indicating inflammation and glial signaling is vital to understanding AD. A previous investigation demonstrated a significant decrease of the GABAB receptor (GABABR) in APP/PS1 mice (Salazar et al., 2021). To determine if changes in GABABR restricted to glia serve a role in AD, we developed a mouse model with a reduction of GABABR restricted to macrophages, GAB/CX3ert. This model exhibits changes in gene expression and electrophysiological alterations similar to amyloid mouse models of AD. Crossing the GAB/CX3ert mouse with APP/PS1 resulted in significant increases in Aß pathology. Our data demonstrates that decreased GABABR on macrophages leads to several changes observed in AD mouse models, as well as exacerbation of AD pathology when crossed with existing models. These data suggest a novel mechanism in AD pathogenesis.

Enhanced skin penetration of Finasteride loaded DMSO-liposomes for the treatment of androgenic alopecia: comparison with conventional liposomes.

Long-term treatment with finasteride (FIN) for androgenic alopecia is restricted due to its systemic side effects. To address this problem, DMSO-modified liposomes were prepared in the present study to improve the topical delivery of FIN. DMSO-liposomes were prepared by a modification of the ethanol injection method. It was hypothesized that the permeation-enhancing property of DMSO could promote drug delivery to deeper skin layer where hair follicles are present. Liposomes were optimized by quality by design (QbD) approach and biologically evaluated in a rat model of testosterone-induced alopecia. Optimized DMSO-liposomes were spherical and had mean vesicle size, zeta potential, and entrapment efficiency of 330.1 ± 1.5, -14.52 ± 1.32, and 59.02 ± 1.12%, respectively. Biological evaluation on testosterone-induced alopecia and skin histology shows that follicular density and anagen/telogen (A/T) ratio were increased in rats treated with DMSO-liposomes as compared to FIN-liposomes without DMSO and an alcoholic solution of FIN applied topically. DMSO-liposomes could be promising skin delivery vehicles for FIN or similar drugs.

A novel human tau knock-in mouse model reveals interaction of Abeta and human tau under progressing cerebral amyloidosis in 5xFAD mice.

BACKGROUND: Hyperphosphorylation and intraneuronal aggregation of the microtubule-associated protein tau is a major pathological hallmark of Alzheimer's disease (AD) brain. Of special interest is the effect of cerebral amyloid beta deposition, the second main hallmark of AD, on human tau pathology. Therefore, studying the influence of cerebral amyloidosis on human tau in a novel human tau knock-in (htau-KI) mouse model could help to reveal new details on their interplay. METHODS: We studied the effects of a novel human htau-KI under fast-progressing amyloidosis in 5xFAD mice in terms of correlation of gene expression data with human brain regions, development of Alzheimer's-like pathology, synaptic transmission, and behavior. RESULTS: The main findings are an interaction of human beta-amyloid and human tau in crossbred 5xFADxhtau-KI observed at transcriptional level and corroborated by electrophysiology and histopathology. The comparison of gene expression data of the 5xFADxhtau-KI mouse model to 5xFAD, control mice and to human AD patients revealed conspicuous changes in pathways related to mitochondria biology, extracellular matrix, and immune function. These changes were accompanied by plaque-associated MC1-positive pathological tau that required the htau-KI background. LTP deficits were noted in 5xFAD and htau-KI mice in contrast to signs of rescue in 5xFADxhtau-KI mice. Increased frequencies of miniature EPSCs and miniature IPSCs indicated an upregulated presynaptic function in 5xFADxhtau-KI. CONCLUSION: In summary, the multiple interactions observed between knocked-in human tau and the 5xFAD-driven progressing amyloidosis have important implications for future model development in AD.

Physiological relevance of in-vitro cell-nanoparticle interaction studies as a predictive tool in cancer nanomedicine research.

Cell uptake study is a routine experiment used as a surrogate to predict in vivo response in cancer nanomedicine research. Cell culture conditions should be designed in such a way that it emulates 'real' physiological conditions and avoid artefacts. It is critical to dissect the steps involved in cellular uptake to understand the physical, chemical, and biological factors responsible for particle internalization. The two-dimensional model (2D) of cell culture is overly simplistic to mimic the complexity of cancer tissues that exist in vivo. It cannot simulate the critical tissue-specific properties like cell-cell interaction and cell-extracellular matrix (ECM) interaction and its influences on the temporal and spatial distribution of nanoparticles (NPs). The three dimensional model organization of heterogenous cancer and normal cells with the ECM acts as a formidable barrier to NP penetration and cellular uptake. The three dimensional cell culture (3D) technology is a breakthrough in this direction that can mimic the barrier properties of the tumor microenvironment (TME). Herein, we discuss the physiological factors that should be considered to bridge the translational gap between in and vitro cell culture studies and in-vivo studies in cancer nanomedicine.

Levetiracetam modulates brain metabolic networks and transcriptomic signatures in the 5XFAD mouse model of Alzheimer's disease.

Introduction: Subcritical epileptiform activity is associated with impaired cognitive function and is commonly seen in patients with Alzheimer's disease (AD). The anti-convulsant, levetiracetam (LEV), is currently being evaluated in clinical trials for its ability to reduce epileptiform activity and improve cognitive function in AD. The purpose of the current study was to apply pharmacokinetics (PK), network analysis of medical imaging, gene transcriptomics, and PK/PD modeling to a cohort of amyloidogenic mice to establish how LEV restores or drives alterations in the brain networks of mice in a dose-dependent basis using the rigorous preclinical pipeline of the MODEL-AD Preclinical Testing Core. Methods: Chronic LEV was administered to 5XFAD mice of both sexes for 3 months based on allometrically scaled clinical dose levels from PK models. Data collection and analysis consisted of a multi-modal approach utilizing 18F-FDG PET/MRI imaging and analysis, transcriptomic analyses, and PK/PD modeling. Results: Pharmacokinetics of LEV showed a sex and dose dependence in Cmax, CL/F, and AUC0-∞, with simulations used to estimate dose regimens. Chronic dosing at 10, 30, and 56 mg/kg, showed 18F-FDG specific regional differences in brain uptake, and in whole brain covariance measures such as clustering coefficient, degree, network density, and connection strength (i.e., positive and negative). In addition, transcriptomic analysis via nanoString showed dose-dependent changes in gene expression in pathways consistent 18F-FDG uptake and network changes, and PK/PD modeling showed a concentration dependence for key genes, but not for network covariance modeling. Discussion: This study represents the first report detailing the relationships of metabolic covariance and transcriptomic network changes resulting from LEV administration in 5XFAD mice. Overall, our results highlight non-linear kinetics based on dose and sex, where gene expression analysis demonstrated LEV dose- and concentration-dependent changes, along with cerebral metabolism, and/or cerebral homeostatic mechanisms relevant to human AD, which aligned closely with network covariance analysis of 18F-FDG images. Collectively, this study show cases the value of a multimodal connectomic, transcriptomic, and pharmacokinetic approach to further investigate dose dependent relationships in preclinical studies, with translational value toward informing clinical study design.

In vivo validation of late-onset Alzheimer's disease genetic risk factors.

Introduction: Genome-wide association studies have identified over 70 genetic loci associated with late-onset Alzheimer's disease (LOAD), but few candidate polymorphisms have been functionally assessed for disease relevance and mechanism of action. Methods: Candidate genetic risk variants were informatically prioritized and individually engineered into a LOAD-sensitized mouse model that carries the AD risk variants APOE4 and Trem2*R47H. Potential disease relevance of each model was assessed by comparing brain transcriptomes measured with the Nanostring Mouse AD Panel at 4 and 12 months of age with human study cohorts. Results: We created new models for 11 coding and loss-of-function risk variants. Transcriptomic effects from multiple genetic variants recapitulated a variety of human gene expression patterns observed in LOAD study cohorts. Specific models matched to emerging molecular LOAD subtypes. Discussion: These results provide an initial functionalization of 11 candidate risk variants and identify potential preclinical models for testing targeted therapeutics.

Metabolomics profiling reveals distinct, sex-specific signatures in the serum and brain metabolomes in the mouse models of Alzheimer's disease.

INTRODUCTION: Increasing evidence suggests that metabolic impairments contribute to early Alzheimer's disease (AD) mechanisms and subsequent dementia. Signals in metabolic pathways conserved across species provides a promising entry point for translation. METHODS: We investigated differences of serum and brain metabolites between the early-onset 5XFAD and late-onset LOAD1 (APOE4.Trem2*R47H) mouse models of AD to C57BL/6J controls at six months of age. RESULTS: We identified sex differences for several classes of metabolites, such as glycerophospholipids, sphingolipids, and amino acids. Metabolic signatures were notably different between brain and serum in both mouse models. The 5XFAD mice exhibited stronger differences in brain metabolites, whereas LOAD1 mice showed more pronounced differences in serum. DISCUSSION: Several of our findings were consistent with results in humans, showing glycerophospholipids reduction in serum of APOE4 carriers and replicating the serum metabolic imprint of the APOE4 genotype. Our work thus represents a significant step towards translating metabolic dysregulation from model organisms to human AD.

Characterizing Molecular and Synaptic Signatures in mouse models of Late-Onset Alzheimer's Disease Independent of Amyloid and Tau Pathology.

INTRODUCTION: MODEL-AD is creating and distributing novel mouse models with humanized, clinically relevant genetic risk factors to more accurately mimic LOAD than commonly used transgenic models. METHODS: We created the LOAD2 model by combining APOE4, Trem2*R47H, and humanized amyloid-beta. Mice aged up to 24 months were subjected to either a control diet or a high-fat/high-sugar diet (LOAD2+HFD) from two months of age. We assessed disease-relevant outcomes, including in vivo imaging, biomarkers, multi-omics, neuropathology, and behavior. RESULTS: By 18 months, LOAD2+HFD mice exhibited cortical neuron loss, elevated insoluble brain Aß42, increased plasma NfL, and altered gene/protein expression related to lipid metabolism and synaptic function. In vivo imaging showed age-dependent reductions in brain region volume and neurovascular uncoupling. LOAD2+HFD mice also displayed deficits in acquiring touchscreen-based cognitive tasks. DISCUSSION: Collectively the comprehensive characterization of LOAD2+HFD mice reveal this model as important for preclinical studies that target features of LOAD independent of amyloid and tau.

Sea surface temperature (SST) and SST anomaly (SSTA) datasets over the last four decades (1977-2016) during typhoon season (May to November) in the entire Global Ocean, North Pacific Ocean, Philippine Sea, South China sea, and Eastern China Sea.

The Sea Surface Temperature Anomalies (SSTA) are created for the chosen study period from 1977 to 2016 (40-years) including the base period from 1941 to 1970 (30-years) using the two different raw Sea Surface Temperature (SST) datasets named Optimum Interpolation (OI) SST version 2 and Centennial in situ Observation-Based Estimates (COBE) SST version 2. The SSTA and SST are measured for each month from May to November (typhoon activity months in the North West Pacific) over the entire Global Ocean, especially focusing on the North Pacific Ocean; Philippine Sea; South China Sea; and Eastern China Sea (the marginal Seas of the North West Pacific Ocean). The OI-SST V2 dataset is directly accessed by the online link https://psl.noaa.gov/, which is made available by the Physical Sciences Laboratory (PSL) of the National Oceanic and Atmospheric Administration (NOAA). OI-SST V2 dataset contains monthly-averaged SST data from December 1981 to May 2020. COBE-SST V2 dataset belongs to the Japan Meteorological Agency (JMA) and is also made available by the PSL of NOAA through the online link https://psl.noaa.gov/. COBE-SST V2 dataset contains a very long period of monthly-averaged SST data from January 1850 to December 2019. The SST data in both datasets are on a regular one-degree (1o) grid covering the entire Oceans of the Earth. Both datasets are in the Network Common Data Form (NetCDF)(.nc) and can be opened on any appropriate software platform like ESRI ArcGIS 10.5 for further analysis. All SST data presented in this article merely belong to the typhoon season months (from May to November) of the North West Pacific (NWP) Ocean basin and are thus crucial for typhoon-related research. At First, the SST data for each month from May to November over the whole study and the base periods are extracted for the entire Global Ocean. Then, for each successive 5-year period and 10-year period, the SST data is averaged separately for each month from May to November. Also, for the whole 40 years of the chosen current period and 30 years of the base period, the SST data is averaged separately for each month of the typhoon season. The successive year, 5-year, and 10-year SST data of the chosen current period is averaged for all seven months of typhoon season. Also, for the whole 40 years of the chosen current period and 30 years of the base period, the SST data is averaged over all seven months of typhoon season. Finally, the yearly, 5-yearly, 10-yearly, and monthly Sea Surface Temperature Anomalies (SSTA) are measured using the chosen current and base period data for the entire Global Ocean, North Pacific Ocean, Philippine Sea, South China sea, and Eastern China Sea. Statistical analyses are done, which are significant for global warming, SST, and typhoon-related research. For detailed analysis, explanation, and discussion, the readers are referred to the "Typhoon strength rising in the past four decades" [1].