A Computed Tomography-Based Fracture Prediction Model With Images of Vertebral Bones and Muscles by Employing Deep Learning: Development and Validation Study.

BACKGROUND: With the progressive increase in aging populations, the use of opportunistic computed tomography (CT) scanning is increasing, which could be a valuable method for acquiring information on both muscles and bones of aging populations. OBJECTIVE: The aim of this study was to develop and externally validate opportunistic CT-based fracture prediction models by using images of vertebral bones and paravertebral muscles. METHODS: The models were developed based on a retrospective longitudinal cohort study of 1214 patients with abdominal CT images between 2010 and 2019. The models were externally validated in 495 patients. The primary outcome of this study was defined as the predictive accuracy for identifying vertebral fracture events within a 5-year follow-up. The image models were developed using an attention convolutional neural network-recurrent neural network model from images of the vertebral bone and paravertebral muscles. RESULTS: The mean ages of the patients in the development and validation sets were 73 years and 68 years, and 69.1% (839/1214) and 78.8% (390/495) of them were females, respectively. The areas under the receiver operator curve (AUROCs) for predicting vertebral fractures were superior in images of the vertebral bone and paravertebral muscles than those in the bone-only images in the external validation cohort (0.827, 95% CI 0.821-0.833 vs 0.815, 95% CI 0.806-0.824, respectively; P<.001). The AUROCs of these image models were higher than those of the fracture risk assessment models (0.810 for major osteoporotic risk, 0.780 for hip fracture risk). For the clinical model using age, sex, BMI, use of steroids, smoking, possible secondary osteoporosis, type 2 diabetes mellitus, HIV, hepatitis C, and renal failure, the AUROC value in the external validation cohort was 0.749 (95% CI 0.736-0.762), which was lower than that of the image model using vertebral bones and muscles (P<.001). CONCLUSIONS: The model using the images of the vertebral bone and paravertebral muscle showed better performance than that using the images of the bone-only or clinical variables. Opportunistic CT screening may contribute to identifying patients with a high fracture risk in the future.

Neonatal dysregulation of 2-arachidonoylglycerol induces impaired brain function in adult mice.

The endocannabinoid system (ECS) regulates neurotransmission linked to synaptic plasticity, cognition, and emotion. While it has been demonstrated that dysregulation of the ECS in adulthood is relevant not only to central nervous system (CNS) disorders such as autism spectrum disorder, cognitive dysfunction, and depression but also to brain function, there are few studies on how dysregulation of the ECS in the neonatal period affects the manifestation and pathophysiology of CNS disorders later in life. In this study, DO34, a diacylglycerol lipase alpha (DAGLα) inhibitor affecting endocannabinoid 2-AG production, was injected into C57BL/6N male mice from postnatal day (PND) 7 to PND 10, inducing dysregulation of the ECS in the neonatal period. Subsequently, we examined whether it affects neuronal function in adulthood through electrophysiological and behavioral evaluation. DO34-injected mice showed significantly decreased cognitive functions, attributed to impairment of hippocampal synaptic plasticity. The findings suggest that regulation of ECS activity in the neonatal period may induce enduring effects on adult brain function.

A novel electrochemical strategy to detect hydrogen peroxide by utilizing peroxidase-mimicking activity of cerium oxide/graphene oxide nanocomposites.

We herein describe a novel electrochemical strategy to detect hydrogen peroxide (H2O2) by utilizing the peroxidase-mimicking activity of cerium oxide nanoparticles (CeO2 NP) and reduced graphene oxide (rGO). Particularly, CeO2 NP/rGO nanocomposites were deposited on the commercial electrode by a very convenient and direct electrochemical reduction of graphene oxide. Due to the peroxidase-mimicking activity of CeO2 NP and the outstanding electrochemical properties of reduced graphene oxide, the reduction current of H2O2 was greatly enhanced. Based on this strategy, we reliably determined H2O2 down to 1.67 µM with excellent specificity and further validated its practical capabilities by robustly detecting H2O2 present in heterogeneous human serum samples. We believe that this work could serve as a new facile platform for H2O2 detection.

Protein Signatures of Parathyroid Adenoma according to Tumor Volume and Functionality.

BACKGRUOUND: Parathyroid adenoma (PA) is a common endocrine disease linked to multiple complications, but the pathophysiology of the disease remains incompletely understood. The study aimed to identify the key regulator proteins and pathways of PA according to functionality and volume through quantitative proteomic analyses. METHODS: We conducted a retrospective study of 15 formalin-fixed, paraffin-embedded PA samples from tertiary hospitals in South Korea. Proteins were extracted, digested, and the resulting peptides were analyzed using liquid chromatography-tandem mass spectrometry. Pearson correlation analysis was employed to identify proteins significantly correlated with clinical variables. Canonical pathways and transcription factors were analyzed using Ingenuity Pathway Analysis. RESULTS: The median age of the participants was 52 years, and 60.0% were female. Among the 8,153 protein groups analyzed, 496 showed significant positive correlations with adenoma volume, while 431 proteins were significantly correlated with parathyroid hormone (PTH) levels. The proteins SLC12A9, LGALS3, and CARM1 were positively correlated with adenoma volume, while HSP90AB2P, HLA-DRA, and SCD5 showed negative correlations. DCPS, IRF2BPL, and FAM98A were the main proteins that exhibited positive correlations with PTH levels, and SLITRK4, LAP3, and AP4E1 had negative correlations. Canonical pathway analysis demonstrated that the RAN and sirtuin signaling pathways were positively correlated with both PTH levels and adenoma volume, while epithelial adherence junction pathways had negative correlations. CONCLUSION: Our study identified pivotal proteins and pathways associated with PA, offering potential therapeutic targets. These findings accentuate the importance of proteomics in understanding disease pathophysiology and the need for further research.

Amoxicillin-Induced Drug Reaction With Eosinophilia and Systemic Symptoms (DRESS) Syndrome With Acute Onset of Diffuse Rash and Acute Kidney Injury (AKI).

Drug reaction with eosinophilia and systemic symptoms (DRESS) syndrome is an uncommon and potentially fatal adverse drug reaction that can affect individuals with immunosuppression, viral reactivation, pharmacogenetic susceptibility, and recent exposures to new medications. Due to the ambiguous symptomology of DRESS syndrome along with a lack of diagnosis and treatment criteria, there can be delays in diagnosis and management. Here, we present a case of a 60-year-old female with an uncommon presentation of DRESS syndrome due to a less commonly implicated drug. We aim to bring awareness to the various presentations associated with DRESS syndrome and inform readers about current diagnostic and treatment modalities used today. In addition, this case serves to provide insights that further evidence is needed to have standardized guidelines in place to effectively diagnose and manage affected patients.

A CT-based Deep Learning Model for Predicting Subsequent Fracture Risk in Patients with Hip Fracture.

Background Patients have the highest risk of subsequent fractures in the first few years after an initial fracture, yet models to predict short-term subsequent risk have not been developed. Purpose To develop and validate a deep learning prediction model for subsequent fracture risk using digitally reconstructed radiographs from hip CT in patients with recent hip fractures. Materials and Methods This retrospective study included adult patients who underwent three-dimensional hip CT due to a fracture from January 2004 to December 2020. Two-dimensional frontal, lateral, and axial digitally reconstructed radiographs were generated and assembled to construct an ensemble model. DenseNet modules were used to calculate risk probability based on extracted image features and fracture-free probability plots were output. Model performance was assessed using the C index and area under the receiver operating characteristic curve (AUC) and compared with other models using the paired t test. Results The training and validation set included 1012 patients (mean age, 74.5 years ± 13.3 [SD]; 706 female, 113 subsequent fracture) and the test set included 468 patients (mean age, 75.9 years ± 14.0; 335 female, 22 subsequent fractures). In the test set, the ensemble model had a higher C index (0.73) for predicting subsequent fractures than that of other image-based models (C index range, 0.59-0.70 for five of six models; P value range, < .001 to < .05). The ensemble model achieved AUCs of 0.74, 0.74, and 0.73 at the 2-, 3-, and 5-year follow-ups, respectively; higher than that of most other image-based models at 2 years (AUC range, 0.57-0.71 for five of six models; P value range, < .001 to < .05) and 3 years (AUC range, 0.55-0.72 for four of six models; P value range, < .001 to < .05). Moreover, the AUCs achieved by the ensemble model were higher than that of a clinical model that included known risk factors (2-, 3-, and 5-year AUCs of 0.58, 0.64, and 0.70, respectively; P < .001 for all). Conclusion In patients with recent hip fractures, the ensemble deep learning model using digital reconstructed radiographs from hip CT showed good performance for predicting subsequent fractures in the short term. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Li and Jaremko in this issue.

Second Skin as Self-Protection Against γ-Hydroxybutyrate.

γ-Hydroxybutyrate (GHB), a date-rape drug, causes certain symptoms, such as amnesia, confusion, ataxia, and unconsciousness, when dissolved in beverages and consumed by a victim. Commonly, assailants use GHB in secret for the crime of drug-facilitated sexual assault because it is tasteless, odorless, and colorless when dissolved in beverages. Generally, GHB detection methods are difficult to use promptly and secretly in situ and in real life because of the necessary detection equipment and low selectivity. To overcome this problem, we have developed a fast, simple, and easy-to-use second skin platform as a confidential self-protection platform that can detect GHB in situ or in real life without equipment. The second skin platform for naked-eye detection of GHB is fabricated with poly(vinyl alcohol) (PVA), polyurethane (PU), and polyacrylonitrile (PAN) included in the chemical receptor 2-(3-bromo-4-hydroxystyryl)-3-ethylbenzothiazol-3-ium iodide (BHEI). PAN conjugated with BHEI nanofibers (PB NFs) has various characteristics, such as ease of use, high sensitivity, and fast color change. PB NFs rapidly detected GHB at 0.01 mg/mL. Furthermore, the second-skin platform attached to the fingertip and wrist detected both 1 and 0.1 mg/mL GHB in solution within 50 s. The color changes caused by the interaction of GHB and the second skin platform cannot be stopped due to strong chemical reactions. In addition, a second skin platform can be secretly utilized in real life because it can recognize fingerprints and object temperatures. Therefore, the second skin platform can be used to aid daily life and prevent drug-facilitated sexual assault crime when attached to the skin because it can be exposed anytime and anywhere.

Recombinant protein embedded liposome on gold nanoparticle based on LSPR method to detect Corona virus.

Antibody sensor to detect viruses has been widely used but has problems such as the difficulty of right direction control of the receptor site on solid substrate, and long time and high cost for design and production of antibodies to new emerging viruses. The virus detection sensor with a recombinant protein embedded liposome (R/Li) was newly developed to solve the above problems, in which R/Li was assembled on AuNPs (Au@R/Li) to increase the sensitivity using localized surface plasmon resonance (LSPR) method. Recombinant angiotensin-converting enzyme-2 (ACE2) was used as host receptors of SARS-CoV and SARS-CoV-2, and the direction of enzyme active site for virus attachment could be controlled by the integration with liposome. The recombinant protein embedded liposomes were assembled on AuNPs, and LSPR method was used for detection. With the sensor platform S1 protein of both viruses was detected with detection limit of 10 pg/ml and SARS-CoV-2 in clinical samples was detected with 10 ~ 35 Ct values. In the selectivity test, MERS-CoV did not show a signal due to no binding with Au@R/Li. The proposed sensor platform can be used as promising detection method with high sensitivity and selectivity for the early and simple diagnosis of new emerging viruses.

Aß dissociation by pectolinarin may counteract against Aß-induced synaptic dysfunction and memory impairment.

Alzheimer's disease (AD) is a degenerative brain disorder characterised by various neurological symptoms, including memory impairment and mood disorders, associated with the abnormal accumulation of amyloid b(Aß) and tau proteins in the brain. There is still no definitive treatment available for AD, and the Aß antibody drugs, which are expected to be approved by the FDA, have many limitations. Therefore, there is an urgent need to develop low-molecular-weight therapeutic agents for the management of AD. In this study, we investigated whether pectolinarin, a flavonoid, regulates Aß aggregation and Aß-induced toxicity. Pectolinarin demonstrated concentration-dependent inhibition of Aß aggregation and had the ability to break down pre-formed Aß aggregates, thereby reducing their neurotoxicity. Furthermore, pectolinarin suppressed Aß aggregates-induced reduction in long-term potentiation (LTP) in the hippocampus. Oral administration of pectolinarin in experimental animals inhibited memory impairment and LTP deficits induced by Aß injection in the hippocampus. These results indicate that pectolinarin may reduce toxic Aß species and Aß-induced memory impairments and synaptic dysfunction.

Effect of Trap Behavior on the Reliability Instability of Metamorphic Buffer in InAlAs/InGaAs MHEMT on GaAs.

Our investigation focused on assessing the influence of the metamorphic buffer in metamorphic high-electron-mobility transistors (MHEMT) that were grown on GaAs substrates. While an MHEMT exhibited elevated off-state current levels, its direct current (DC) and radio frequency (RF) traits were found to be comparable to those of InP-based lattice-matched high-electron-mobility transistors (LM-HEMTs). However, the Pulsed I-V measurement results confirmed the presence of the fast transient charging effect, leading to a more substantial degradation in drain current observed in MHEMT. In addition, through the low-frequency noise characteristics, it was confirmed that the dominant trapping location was located in the bulk site. The slope of the 1/f noise measurement indicated that the primary trapping site was in proximity to the bulk traps. The carrier-number-fluctuation (CNF) model was employed to extract the bulk trap density (Nt). For the LM-HEMTs, the value was at 3.27 × 1016 eV-1·cm-3, while for the MHEMT, it was 3.56 × 1017 eV-1·cm-3.

Dysregulation of the Wnt/ß-catenin signaling pathway via Rnf146 upregulation in a VPA-induced mouse model of autism spectrum disorder.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder associated with impaired social behavior and communication, repetitive behaviors, and restricted interests. In addition to genetic factors, environmental factors such as prenatal drug exposure contribute to the development of ASD. However, how those prenatal factors induce behavioral deficits in the adult stage is not clear. To elucidate ASD pathogenesis at the molecular level, we performed a high-resolution mass spectrometry-based quantitative proteomic analysis on the prefrontal cortex (PFC) of mice exposed to valproic acid (VPA) in utero, a widely used animal model of ASD. Differentially expressed proteins (DEPs) in VPA-exposed mice showed significant overlap with ASD risk genes, including differentially expressed genes from the postmortem cortex of ASD patients. Functional annotations of the DEPs revealed significant enrichment in the Wnt/ß-catenin signaling pathway, which is dysregulated by the upregulation of Rnf146 in VPA-exposed mice. Consistently, overexpressing Rnf146 in the PFC impaired social behaviors and altered the Wnt signaling pathway in adult mice. Furthermore, Rnf146-overexpressing PFC neurons showed increased excitatory synaptic transmission, which may underlie impaired social behavior. These results demonstrate that Rnf146 is critical for social behavior and that dysregulation of Rnf146 underlies social deficits in VPA-exposed mice.

Correlation between immune-related genes and depression-like features in an animal model and in humans.

A growing body of evidence suggests that immune-related genes play pivotal roles in the pathophysiology of depression. In the present study, we investigated a plausible connection between gene expression, DNA methylation, and brain structural changes in the pathophysiology of depression using a combined approach of murine and human studies. We ranked the immobility behaviors of 30 outbred Crl:CD1 (ICR) mice in the forced swim test (FST) and harvested their prefrontal cortices for RNA sequencing. Of the 24,532 analyzed genes, 141 showed significant correlations with FST immobility time, as determined through linear regression analysis with p ≤ 0.01. The identified genes were mostly involved in immune responses, especially interferon signaling pathways. Moreover, induction of virus-like neuroinflammation in the brains of two separate mouse cohorts (n = 30 each) using intracerebroventricular polyinosinic:polycytidylic acid injection resulted in increased immobility during FST and similar expression of top immobility-correlated genes. In human blood samples, candidate gene (top 5%) expression profiling using DNA methylation analysis found the interferon-related USP18 (cg25484698, p = 7.04 × 10-11, Δß = 1.57 × 10-2; cg02518889, p = 2.92 × 10-3, Δß =  - 8.20 × 10-3) and IFI44 (cg07107453, p = 3.76 × 10-3, Δß =  - 4.94 × 10-3) genes to be differentially methylated between patients with major depressive disorder (n = 350) and healthy controls (n = 161). Furthermore, cortical thickness analyses using T1-weighted images revealed that the DNA methylation scores for USP18 were negatively correlated with the thicknesses of several cortical regions, including the prefrontal cortex. Our results reveal the important role of the interferon pathway in depression and suggest USP18 as a potential candidate target. The results of the correlation analysis between transcriptomic data and animal behavior carried out in this study provide insights that could enhance our understanding of depression in humans.

Ethyl pyruvate prevents long-term stress-induced cognitive decline and modulates Akt/GSK-3ß signaling.

Stress is an inevitable part of life and, simultaneously, a stimulus that can trigger various neuropsychiatric disorders. Therefore, proper stress management is essential for maintaining a healthy life. In this study, we investigated the suppression of stress-induced cognitive deficit by controlling changes in synaptic plasticity caused by stress and confirmed that ethyl pyruvate (EP) has such an effect. Corticosterone, a stress hormone, suppresses long-term potentiation (LTP) in mouse acute hippocampal slices. EP blocked the LTP inhibitory effect of corticosterone by regulating GSK-3ß function. Restraint stress for 2 weeks increased the anxiety levels and caused the cognitive decline in the experimental animals. Administration of EP for 14 days did not affect the increase in anxiety caused by stress but improved cognitive decline caused by stress. In addition, the decrease in neurogenesis and synaptic function deficits in the hippocampus, which cause of cognitive decline due to stress, were improved by EP administration. These effects appear via regulation of Akt/GSK-3ß signaling, as in in vitro studies. These results suggest that EP prevents stress-induced cognitive decline through the modulation of Akt/GSK-3ß-mediated synaptic regulation.

Development and validation of common data model-based fracture prediction model using machine learning algorithm.

The need for an accurate country-specific real-world-based fracture prediction model is increasing. Thus, we developed scoring systems for osteoporotic fractures from hospital-based cohorts and validated them in an independent cohort in Korea. The model includes history of fracture, age, lumbar spine and total hip T-score, and cardiovascular disease. PURPOSE: Osteoporotic fractures are substantial health and economic burden. Therefore, the need for an accurate real-world-based fracture prediction model is increasing. We aimed to develop and validate an accurate and user-friendly model to predict major osteoporotic and hip fractures using a common data model database. METHODS: The study included 20,107 and 13,353 participants aged ≥ 50 years with data on bone mineral density using dual-energy X-ray absorptiometry from the CDM database between 2008 and 2011 from the discovery and validation cohort, respectively. The main outcomes were major osteoporotic and hip fracture events. DeepHit and Cox proportional hazard models were used to identify predictors of fractures and to build scoring systems, respectively. RESULTS: The mean age was 64.5 years, and 84.3% were women. During a mean of 7.6 years of follow-up, 1990 major osteoporotic and 309 hip fracture events were observed. In the final scoring model, history of fracture, age, lumbar spine T-score, total hip T-score, and cardiovascular disease were selected as predictors for major osteoporotic fractures. For hip fractures, history of fracture, age, total hip T-score, cerebrovascular disease, and diabetes mellitus were selected. Harrell's C-index for osteoporotic and hip fractures were 0.789 and 0.860 in the discovery cohort and 0.762 and 0.773 in the validation cohort, respectively. The estimated 10-year risks of major osteoporotic and hip fractures were 2.0%, 0.2% at score 0 and 68.8%, 18.8% at their maximum scores, respectively. CONCLUSION: We developed scoring systems for osteoporotic fractures from hospital-based cohorts and validated them in an independent cohort. These simple scoring models may help predict fracture risks in real-world practice.

Reusable Electronic Tongue Based on Transient Receptor Potential Vanilloid 1 Nanodisc-Conjugated Graphene Field-Effect Transistor for a Spiciness-Related Pain Evaluation.

The sense of spiciness is related to the stimulation of vanilloid compounds contained in the foods. Although, the spiciness is commonly considered as the part of taste, it is more classified to the sense of pain stimulated on a tongue, namely, pungency, which is described as a tingling or burning on the tongue. Herein, first, a reusable electronic tongue based on a transient receptor potential vanilloid 1 (TRPV1) nanodisc conjugated graphene field-effect transistor is fabricated and spiciness-related pain evaluation with reusable electrode is demonstrated. The pungent compound reactive receptor TRPV1 is synthesized in the form of nanodiscs to maintain stability and reusability. The newly developed platform shows highly selective and sensitive performance toward each spiciness related vanilloid compound repeatably: 1 aM capsaicin, 10 aM dihydrocapsaicin, 1 fM piperine, 10 nM allicin, and 1 pM AITC. The binding mechanism is also examined by simulation. Furthermore, the elimination of the burning sensation on the tongue after eating spicy foods is not investigated. Based on the synthesis of micelles composed of casein protein (which is contained in skim milk) that remove pungent compounds bound to TRPV1 nanodisc, the deactivation of TRPV1 is investigated, and the electrode is reusable that mimics electronic tongue.

Caspase Cleavage of Receptor Tyrosine Kinases in the Dependence Receptor Family.

Dependence receptors are a group of receptor proteins with shared characteristics of transducing two different signals within cells. They can transduce a positive signal of survival and differentiation in the presence of ligands. On the other hand, dependence receptors can transduce an apoptosis signal in the absence of ligands. The function of these receptors depends on the availability of their ligands. Several receptor tyrosine kinases (RTKs) have been reported as dependence receptors. When cells undergo apoptosis by dependence receptors, the intracellular domain of some RTKs is cleaved by the caspases. Among the RTKs that belong to dependence receptors, we focused on eight RTKs (RET, HER2, MET, ALK, TrkC, EphA4, EphB3, and c-KIT) that are cleaved by caspases. In this review, we describe the features of the receptors, their cleavage sites, and the fate of the cleaved products, as well as recent implications on them being used as potential therapeutics for cancer treatment.

Phyllodulcin improves hippocampal long-term potentiation in 5XFAD mice.

Alzheimer's disease (AD) is a well-known neurodegenerative brain disease, and no curative treatment has yet been developed. The main symptoms include various brain lesions, caused by amyloid ß (Aß) aggregation, and cognitive decline. Therefore, it is believed that substances that control Aß will inhibit the onset of Alzheimer's disease and slow its progression. In this study, the effect of phyllodulcin, a major component of hydrangea, on Aß aggregation and brain pathology in an animal model of AD was studied. Phyllodulcin inhibited the aggregation of Aß and decomposed the pre-aggregated Aß in a concentration-dependent manner. In addition, it inhibited the cytotoxicity of Aß aggregates. Oral administration of phyllodulcin improved Aß-induced memory impairments in normal mice, reduced Aß deposition in the hippocampus, inhibited the activation of microglia and astrocytes, and improved synaptic plasticity in 5XFAD mice. These results suggest that phyllodulcin may be a candidate for the treatment of AD.

In-depth proteomic signature of parathyroid carcinoma.

OBJECTIVE: Diagnosing parathyroid carcinoma (PC) is complicated and controversial that early diagnosis and intervention are often difficult. Therefore, we aimed to elucidate the protein signatures of PC through quantitative proteomic analyses to aid in the early and accurate diagnosis of PC. DESIGN: We conducted a retrospective cohort study. METHODS: We performed liquid chromatography with tandem mass spectrometry using formalin-fixed paraffin-embedded samples. For the analyses, 23 PC and 15 parathyroid adenoma (PA) tissues were collected from 6 tertiary hospitals in South Korea. RESULTS: The mean age of the patients was 52 years, and 63% were women. Proteomic expression profiling revealed 304 differentially expressed proteins (DEPs) with a cut-off of P < .05 and fold change >1.5. Among DEPs, we identified a set of 5 proteins that can discriminate PC from PA: carbonic anhydrase 4 (CA4), alpha/beta hydrolase domain-containing protein 14B (ABHD14B), laminin subunit beta-2 (LAMB2), CD44 antigen (CD44), and alpha-1-acid glycoprotein 1 (ORM1) that exhibited the highest area under the curve of 0.991 in neural network model. The nuclear percentage of CA4 and LAMB2 in immunohistochemistry was significantly lower in PC tissue than in the PA (CA4: 2.77 ± 1.96%, 26.2 ± 3.45%, P < .001; LAMB2: 6.86 ± 3.46%, 38.54 ± 4.13%, P < .001). The most enriched canonical pathways in PC included glycoprotein-6 signaling and mammalian target of rapamycin (mTOR). CONCLUSIONS: We identified key proteins differentially expressed between PC and PA using proteomic analyses of parathyroid neoplasms. These findings may help to diagnose PC accurately and elucidate potential therapeutic targets.

Investigation of Phospholipid Differences in Valproic Acid-Induced Autistic Mouse Model Brain Using Mass Spectrometry Imaging.

Autism is a neurodevelopmental disorder for which the cause and treatment have yet not been determined. The polyunsaturated fatty acid (PUFA) levels change rapidly in the blood or cerebrospinal fluid of autistic children and PUFAs are closely related to autism spectrum disorder (ASD). This finding suggests that changes in lipid metabolism are associated with ASD and result in an altered distribution of phospholipids in cell membranes. To further understand ASD, it is necessary to analyze phospholipids in organs consisting of nerve cells, such as the brain. In this study, we investigated the phospholipid distribution in the brain tissue of valproic acid-induced autistic mice using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). Phospholipids including phosphatidylcholine, phosphatidylethanolamine, and phosphatidylserine were identified in each brain region and exhibited differences between the ASD and control groups. These phospholipids contain docosahexaenoic acid and arachidonic acid, which are important PUFAs for cell signaling and brain growth. We expect that the differences in phospholipids identified in the brain tissue of the ASD model with MALDI-MSI, in conjunction with conventional biological fluid analysis, will help to better understand changes in lipid metabolism in ASD.