Laser-responsive erastin-loaded chondroitin sulfate nanomedicine targeting CD44 and system xc- in liver cancer: A non-ferroptotic approach.

Erastin, a ferroptosis-inducing system xc- inhibitor, faces clinical challenges due to suboptimal physicochemical and pharmacokinetic properties, as well as relatively low potency and off-target toxicity. Addressing these, we developed ECINs, a novel laser-responsive erastin-loaded nanomedicine utilizing indocyanine green (ICG)-grafted chondroitin sulfate A (CSA) derivatives. Our aim was to improve erastin's tumor targeting via CSA-CD44 interactions and enhance its antitumor efficacy through ICG's photothermal and photodynamic effects in the laser-on state while minimizing off-target effects in the laser-off state. ECINs, with their nanoscale size of 186.7 ± 1.1 nm and high erastin encapsulation efficiency of 93.0 ± 0.8%, showed excellent colloidal stability and sustained drug release up to 120 h. In vitro, ECINs demonstrated a mechanism of cancer cell inhibition via G1-phase cell cycle arrest, indicating a non-ferroptotic action. In vivo biodistribution studies in SK-HEP-1 xenograft mice revealed that ECINs significantly enhanced tumor distribution of erastin (1.9-fold greater than free erastin) while substantially reducing off-target accumulation in the lungs and spleen by 203-fold and 19.1-fold, respectively. Combined with laser irradiation, ECINs significantly decreased tumor size (2.6-fold, compared to free erastin; 2.4-fold, compared to ECINs without laser irradiation) with minimal systemic toxicity. This study highlights ECINs as a dual-modality approach for liver cancer treatment, demonstrating significant efficacy against tumors overexpressing CD44 and system xc-.

Blockade of STING activation alleviates microglial dysfunction and a broad spectrum of Alzheimer's disease pathologies.

Abnormal glial activation promotes neurodegeneration in Alzheimer's disease (AD), the most common cause of dementia. Stimulation of the cGAS-STING pathway induces microglial dysfunction and sterile inflammation, which exacerbates AD. We showed that inhibiting STING activation can control microglia and ameliorate a wide spectrum of AD symptoms. The cGAS-STING pathway is required for the detection of ectopic DNA and the subsequent immune response. Amyloid-ß (Aß) and tau induce mitochondrial stress, which causes DNA to be released into the cytoplasm of microglia. cGAS and STING are highly expressed in Aß plaque-associated microglia, and neuronal STING is upregulated in the brains of AD model animals. The presence of the APOE ε4 allele, an AD risk factor, also upregulated both proteins. STING activation was necessary for microglial NLRP3 activation, proinflammatory responses, and type-I-interferon responses. Pharmacological STING inhibition reduced a wide range of AD pathogenic features in AppNL-G-F/hTau double-knock-in mice. An unanticipated transcriptome shift in microglia reduced gliosis and cerebral inflammation. Significant reductions in the Aß load, tau phosphorylation, and microglial synapse engulfment prevented memory loss. To summarize, our study describes the pathogenic mechanism of STING activation as well as its potential as a therapeutic target in AD.

Multimodal Model for Predicting Fetal Acidosis in Delivery Room.

In the delivery room, fetal well-being is evaluated through laboratory tests, biosignals like cardiotocography, and imaging techniques such as fetal echocardiography. We have developed a multimodal machine learning model that integrates medical records, biosignals, and imaging data to predict fetal acidosis, using a dataset from a tertiary hospital's delivery room (n=2,266). To achieve this, features were extracted from unstructured data sources, including biosignals and imaging, and then merged with structured data from medical records. The concatenated vectors formed the basis for training a classifier to predict post-delivery fetal acidosis. Our model achieved an Area Under the Receiver Operating Characteristic curve (AUROC) of 0.752 on the test dataset, demonstrating the potential of multimodal models in predicting various fetal outcomes.

Microglia Gravitate toward Amyloid Plaques Surrounded by Externalized Phosphatidylserine via TREM2.

Microglia play a crucial role in synaptic elimination by engulfing dystrophic neurons via triggering receptors expressed on myeloid cells 2 (TREM2). They are also involved in the clearance of beta-amyloid (Aß) plaques in Alzheimer's disease (AD); nonetheless, the driving force behind TREM2-mediated phagocytosis of beta-amyloid (Aß) plaques remains unknown. Here, using advanced 2D/3D/4D co-culture systems with loss-of-function mutations in TREM2 (a frameshift mutation engineered in exon 2) brain organoids/microglia/assembloids, it is identified that the clearance of Aß via TREM2 is accelerated by externalized phosphatidylserine (ePtdSer) generated from dystrophic neurons surrounding the Aß plaques. Moreover, it is investigated whether microglia from both sporadic (CRISPR-Cas9-based APOE4 lines) and familial (APPNL-G-F/MAPT double knock-in mice) AD models show reduced levels of TREM2 and lack of phagocytic activity toward ePtdSer-positive Aß plaques. Herein new insight is provided into TREM2-dependent microglial phagocytosis of Aß plaques in the context of the presence of ePtdSer during AD progression.

Improving Rebar Twist Prediction Exploiting Unified-Channel Attention-Based Image Restoration and Regression Techniques.

Recent research has made significant progress in automated unmanned systems utilizing Artificial Intelligence (AI)-based image processing to optimize the rebar manufacturing process and minimize defects such as twisting during production. Despite various studies, including those employing data augmentation through Generative Adversarial Networks (GANs), the performance of rebar twist prediction has been limited due to image quality degradation caused by environmental noise, such as insufficient image quality and inconsistent lighting conditions in rebar processing environments. To address these challenges, we propose a novel approach for real-time rebar twist prediction in manufacturing processes. Our method involves restoring low-quality grayscale images to high resolution and employing an object detection model to identify and track rebar endpoints. We then apply regression analysis to the coordinates obtained from the bounding boxes to estimate the error rate of the rebar endpoint positions, thereby determining the occurrence of twisting. To achieve this, we first developed a Unified-Channel Attention (UCA) module that is robust to changes in intensity and contrast for grayscale images. The UCA can be integrated into image restoration models to more accurately detect rebar endpoint characteristics in object detection models. Furthermore, we introduce a method for predicting the future positions of rebar endpoints using various linear and non-linear regression models. The predicted positions are used to calculate the error rate in rebar endpoint locations, determined by the distance between the actual and predicted positions, which is then used to classify the presence of rebar twisting. Our experimental results demonstrate that integrating the UCA module with our image restoration model significantly improved existing models in Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) metrics. Moreover, employing regression models to predict future rebar endpoint positions enhances the F1 score for twist prediction. As a result, our approach offers a practical solution for rapid defect detection in rebar manufacturing processes.

Electrophysiological insights with brain organoid models: a brief review.

Brain organoid is a three-dimensional (3D) tissue derived from stem cells such as induced pluripotent stem cells (iPSCs) embryonic stem cells (ESCs) that reflect real human brain structure. It replicates the complexity and development of the human brain, enabling studies of the human brain in vitro. With emerging technologies, its application is various, including disease modeling and drug screening. A variety of experimental methods have been used to study structural and molecular characteristics of brain organoids. However, electrophysiological analysis is necessary to understand their functional characteristics and complexity. Although electrophysiological approaches have rapidly advanced for monolayered cells, there are some limitations in studying electrophysiological and neural network characteristics due to the lack of 3D characteristics. Herein, electrophysiological measurement and analytical methods related to neural complexity and 3D characteristics of brain organoids are reviewed. Overall, electrophysiological understanding of brain organoids allows us to overcome limitations of monolayer in vitro cell culture models, providing deep insights into the neural network complex of the real human brain and new ways of disease modeling. [BMB Reports 2024; 57(7): 311-317].

Guidelines for Manufacturing and Application of Organoids: Brain.

This study offers a comprehensive overview of brain organoids for researchers. It combines expert opinions with technical summaries on organoid definitions, characteristics, culture methods, and quality control. This approach aims to enhance the utilization of brain organoids in research. Brain organoids, as three-dimensional human cell models mimicking the nervous system, hold immense promise for studying the human brain. They offer advantages over traditional methods, replicating anatomical structures, physiological features, and complex neuronal networks. Additionally, brain organoids can model nervous system development and interactions between cell types and the microenvironment. By providing a foundation for utilizing the most human-relevant tissue models, this work empowers researchers to overcome limitations of two-dimensional cultures and conduct advanced disease modeling research.

Direct interrogation of context-dependent GPCR activity with a universal biosensor platform.

G protein-coupled receptors (GPCRs) are the largest family of druggable proteins encoded in the human genome, but progress in understanding and targeting them is hindered by the lack of tools to reliably measure their nuanced behavior in physiologically relevant contexts. Here, we developed a collection of compact ONE vector G-protein Optical (ONE-GO) biosensor constructs as a scalable platform that can be conveniently deployed to measure G-protein activation by virtually any GPCR with high fidelity even when expressed endogenously in primary cells. By characterizing dozens of GPCRs across many cell types like primary cardiovascular cells or neurons, we revealed insights into the molecular basis for G-protein coupling selectivity of GPCRs, pharmacogenomic profiles of anti-psychotics on naturally occurring GPCR variants, and G-protein subtype signaling bias by endogenous GPCRs depending on cell type or upon inducing disease-like states. In summary, this open-source platform makes the direct interrogation of context-dependent GPCR activity broadly accessible.

Direct interrogation of context-dependent GPCR activity with a universal biosensor platform.

G protein-coupled receptors (GPCRs) are the largest family of druggable proteins in the human genome, but progress in understanding and targeting them is hindered by the lack of tools to reliably measure their nuanced behavior in physiologically-relevant contexts. Here, we developed a collection of compact ONE vector G-protein Optical (ONE-GO) biosensor constructs as a scalable platform that can be conveniently deployed to measure G-protein activation by virtually any GPCR with high fidelity even when expressed endogenously in primary cells. By characterizing dozens of GPCRs across many cell types like primary cardiovascular cells or neurons, we revealed new insights into the molecular basis for G-protein coupling selectivity of GPCRs, pharmacogenomic profiles of anti-psychotics on naturally-occurring GPCR variants, and G-protein subtype signaling bias by endogenous GPCRs depending on cell type or upon inducing disease-like states. In summary, this open-source platform makes the direct interrogation of context-dependent GPCR activity broadly accessible.

Caffeine Produced in Rice Plants Provides Tolerance to Water-Deficit Stress.

Exogenous or endogenous caffeine application confers resistance to diverse biotic stresses in plants. In this study, we demonstrate that endogenous caffeine in caffeine-producing rice (CPR) increases tolerance even to abiotic stresses such as water deficit. Caffeine produced by CPR plants influences the cytosolic Ca2+ ion concentration gradient. We focused on examining the expression of Ca2+-dependent protein kinase genes, a subset of the numerous proteins engaged in abiotic stress signaling. Under normal conditions, CPR plants exhibited increased expressions of seven OsCPKs (OsCPK10, OsCPK12, OsCPK21, OsCPK25, OsCPK26, OsCPK30, and OsCPK31) and biochemical modifications, including antioxidant enzyme (superoxide dismutase, catalase, peroxidase, and ascorbate peroxidase) activity and non-enzymatic antioxidant (ascorbic acid) content. CPR plants exhibited more pronounced gene expression changes and biochemical alterations in response to water-deficit stress. CPR plants revealed increased expressions of 16 OsCPKs (OsCPK1, OsCPK2, OsCPK3, OsCPK4, OsCPK5, OsCPK6, OsCPK9, OsCPK10, OsCPK11, OsCPK12, OsCPK14, OsCPK16, OsCPK18, OsCPK22, OsCPK24, and OsCPK25) and 8 genes (OsbZIP72, OsLEA25, OsNHX1, OsRab16d, OsDREB2B, OsNAC45, OsP5CS, and OsRSUS1) encoding factors related to abiotic stress tolerance. The activity of antioxidant enzymes increased, and non-enzymatic antioxidants accumulated. In addition, a decrease in reactive oxygen species, an accumulation of malondialdehyde, and physiological alterations such as the inhibition of chlorophyll degradation and the protection of photosynthetic machinery were observed. Our results suggest that caffeine is a natural chemical that increases the potential ability of rice to cope with water-deficit stress and provides robust resistance by activating a rapid and comprehensive resistance mechanism in the case of water-deficit stress. The discovery, furthermore, presents a new approach for enhancing crop tolerance to abiotic stress, including water deficit, via the utilization of a specific natural agent.

Enhancement of the therapeutic efficacy of the MAP regimen using thiamine pyrophosphate-decorated albumin nanoclusters in osteosarcoma treatment.

Recent studies on osteosarcoma regimens have mainly focused on modifying the combination of antineoplastic agents rather than enhancing the therapeutic efficacy of each component. Here, an albumin nanocluster (NC)-assisted methotrexate (MTX), doxorubicin (DOX), and cisplatin (MAP) regimen with improved antitumor efficacy is presented. Human serum albumin (HSA) is decorated with thiamine pyrophosphate (TPP) to increase the affinity to the bone tumor microenvironment (TME). MTX or DOX (hydrophobic MAP components) is adsorbed to HSA-TPP via hydrophobic interactions. MTX- or DOX-adsorbed HSA-TPP NCs exhibit 20.8- and 1.64-fold higher binding affinity to hydroxyapatite, respectively, than corresponding HSA NCs, suggesting improved targeting ability to the bone TME via TPP decoration. A modified MAP regimen consisting of MTX- or DOX-adsorbed HSA-TPP NCs and free cisplatin displays a higher synergistic anticancer effect in HOS/MNNG human osteosarcoma cells than conventional MAP. TPP-decorated NCs show 1.53-fold higher tumor accumulation than unmodified NCs in an orthotopic osteosarcoma mouse model, indicating increased bone tumor distribution. As a result, the modified regimen more significantly suppresses tumor growth in vivo than solution-based conventional MAP, suggesting that HSA-TPP NC-assisted MAP may be a promising strategy for osteosarcoma treatment.

The QPLEX™ Plus Assay Kit for the Early Clinical Diagnosis of Alzheimer's Disease.

We recently developed a multiplex diagnostic kit, QPLEX™ Alz plus assay kit, which captures amyloid-ß1-40, galectin-3 binding protein, angiotensin-converting enzyme, and periostin simultaneously using microliters of peripheral blood and utilizes an optimized algorithm for screening Alzheimer's disease (AD) by correlating with cerebral amyloid deposition. Owing to the demand for early AD detection, we investigate the potential of our kit for the early clinical diagnosis of AD. A total of 1395 participants were recruited, and their blood samples were analyzed with the QPLEX™ kit. The average of QPLEX™ algorithm values in each group increased gradually in the order of the clinical progression continuum of AD: cognitively normal (0.382 ± 0.150), subjective cognitive decline (0.452 ± 0.130), mild cognitive impairment (0.484 ± 0.129), and AD (0.513 ± 0.136). The algorithm values between each group showed statistically significant differences among groups divided by Mini-Mental State Examination and Clinical Dementia Rating. The QPLEX™ algorithm values could be used to distinguish the clinical continuum of AD or cognitive function. Because blood-based diagnosis is more accessible, convenient, and cost- and time-effective than cerebral spinal fluid or positron emission tomography imaging-based diagnosis, the QPLEX™ kit can potentially be used for health checkups and the early clinical diagnosis of AD.

Detecting GPCR Signals With Optical Biosensors of Gα-GTP in Cell Lines and Primary Cell Cultures.

G protein-coupled receptors (GPCRs) are the largest class of transmembrane receptors and mediate a wide variety of physiological processes. GPCRs respond to a plethora of extracellular ligands and initiate signaling pathways inside cells via heterotrimeric G proteins (Gαßγ). Because of the critical role GPCRs play in regulating biological processes and as pharmacological targets, the availability of tools to measure their signaling activity are of high interest. Live-cell biosensors that detect the activity of G proteins in response to GPCR stimulation have emerged as a powerful approach to investigate GPCR/G protein signaling. Here, we detail methods to monitor G protein activity through direct measurement of GTP-bound Gα subunits using optical biosensors based on bioluminescence resonance energy transfer (BRET). More specifically, this article describes the use of two types of complementary biosensors. The first protocol explains how to use a multicomponent BRET biosensor that relies on expression of exogenous G proteins in cell lines. This protocol yields robust responses that are compatible with endpoint measurements of dose-dependent ligand effects or with kinetic measurements of subsecond resolution. The second protocol describes the implementation of unimolecular biosensors that detect the activation of endogenous G proteins in cell lines expressing exogenous GPCRs or in primary cells upon stimulation of endogenous GPCRs. Overall, using the biosensors as described in this article will help users characterize the mechanisms of action of many pharmacological agents and natural ligands that modulate GPCR and G protein signaling with high precision. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Using bimolecular BRET biosensors to monitor Gα-GTP formation of tagged Gα in live cells Alternate Protocol 1: Measuring GPCR dose-dependent Gα-GTP responses in endpoint format Basic Protocol 2: Using unimolecular BRET biosensors to study endogenous G protein activity Alternate Protocol 2: Using unimolecular BRET biosensors to study endogenous G protein activity in mouse cortical neurons.

Fine-tuning GPCR-mediated neuromodulation by biasing signaling through different G protein subunits.

G-protein-coupled receptors (GPCRs) mediate neuromodulation through the activation of heterotrimeric G proteins (Gαßγ). Classical models depict that G protein activation leads to a one-to-one formation of Gα-GTP and Gßγ species. Each of these species propagates signaling by independently acting on effectors, but the mechanisms by which response fidelity is ensured by coordinating Gα and Gßγ responses remain unknown. Here, we reveal a paradigm of G protein regulation whereby the neuronal protein GINIP (Gα inhibitory interacting protein) biases inhibitory GPCR responses to favor Gßγ over Gα signaling. Tight binding of GINIP to Gαi-GTP precludes its association with effectors (adenylyl cyclase) and, simultaneously, with regulator-of-G-protein-signaling (RGS) proteins that accelerate deactivation. As a consequence, Gαi-GTP signaling is dampened, whereas Gßγ signaling is enhanced. We show that this mechanism is essential to prevent the imbalances of neurotransmission that underlie increased seizure susceptibility in mice. Our findings reveal an additional layer of regulation within a quintessential mechanism of signal transduction that sets the tone of neurotransmission.

Small-molecule targeting of GPCR-independent noncanonical G-protein signaling in cancer.

Activation of heterotrimeric G-proteins (Gαßγ) by G-protein-coupled receptors (GPCRs) is a quintessential mechanism of cell signaling widely targeted by clinically approved drugs. However, it has become evident that heterotrimeric G-proteins can also be activated via GPCR-independent mechanisms that remain untapped as pharmacological targets. GIV/Girdin has emerged as a prototypical non-GPCR activator of G proteins that promotes cancer metastasis. Here, we introduce IGGi-11, a first-in-class small-molecule inhibitor of noncanonical activation of heterotrimeric G-protein signaling. IGGi-11 binding to G-protein α-subunits (Gαi) specifically disrupted their engagement with GIV/Girdin, thereby blocking noncanonical G-protein signaling in tumor cells and inhibiting proinvasive traits of metastatic cancer cells. In contrast, IGGi-11 did not interfere with canonical G-protein signaling mechanisms triggered by GPCRs. By revealing that small molecules can selectively disable noncanonical mechanisms of G-protein activation dysregulated in disease, these findings warrant the exploration of therapeutic modalities in G-protein signaling that go beyond targeting GPCRs.

Sex differences in the progression of glucose metabolism dysfunction in Alzheimer's disease.

Alzheimer's disease (AD) is a common neurodegenerative disease characterized by amyloid plaques and impaired brain metabolism. Because women have a higher prevalence of AD than men, sex differences are of great interest. Using cross-sectional and longitudinal data, we showed sex-dependent metabolic dysregulations in the brains of AD patients. Cohort 1 (South Korean, n = 181) underwent Pittsburgh compound B-PET, fluorodeoxyglucose-PET, magnetic resonance imaging, and blood biomarker (plasma tau and beta-amyloid 42 and 40) measurements at baseline and two-year follow-ups. Transcriptome analysis of data from Cohorts 2 and 3 (European, n = 78; Singaporean, n = 18) revealed sex differences in AD-related alterations in brain metabolism. In women (but not in men), all imaging indicators displayed consistent correlation curves with AD progression. At the two-year follow-up, clear brain metabolic impairment was revealed only in women, and the plasma beta-amyloid 42/40 ratio was a possible biomarker for brain metabolism in women. Furthermore, our transcriptome analysis revealed sex differences in transcriptomes and metabolism in the brains of AD patients as well as a molecular network of 25 female-specific glucose metabolic genes (FGGs). We discovered four key-attractor FGG genes (ALDOA, ENO2, PRKACB, and PPP2R5D) that were associated with amyloid/tau-related genes (APP, MAPT, BACE1, and BACE2). Furthermore, these genes successfully distinguished amyloid positivity in women. Understanding sex differences in the pathogenesis of AD and considering these differences will improve development of effective diagnostics and therapeutic treatments for AD.

Small-molecule targeting of GPCR-independent non-canonical G protein signaling inhibits cancer progression.

Activation of heterotrimeric G-proteins (Gαßγ) by G-protein-coupled receptors (GPCRs) is a quintessential mechanism of cell signaling widely targeted by clinically-approved drugs. However, it has become evident that heterotrimeric G-proteins can also be activated via GPCR-independent mechanisms that remain untapped as pharmacological targets. GIV/Girdin has emerged as a prototypical non-GPCR activator of G proteins that promotes cancer metastasis. Here, we introduce IGGi-11, a first-in-class smallmolecule inhibitor of non-canonical activation of heterotrimeric G-protein signaling. IGGi-11 binding to G-protein α-subunits (Gαi) specifically disrupted their engagement with GIV/Girdin, thereby blocking non-canonical G-protein signaling in tumor cells, and inhibiting pro-invasive traits of metastatic cancer cells in vitro and in mice. In contrast, IGGi-11 did not interfere with canonical G-protein signaling mechanisms triggered by GPCRs. By revealing that small molecules can selectively disable non-canonical mechanisms of G-protein activation dysregulated in disease, these findings warrant the exploration of therapeutic modalities in G-protein signaling that go beyond targeting GPCRs.

Association of B cell profile and receptor repertoire with the progression of Alzheimer's disease.

Alzheimer's disease (AD) is the most prevalent type of dementia. Reports have revealed that the peripheral immune system is linked to neuropathology; however, little is known about the contribution of B lymphocytes in AD. For this longitudinal study, 133 participants are included at baseline and second-year follow-up. Also, we analyze B cell receptor (BCR) repertoire data generated from a public dataset of three normal and 10 AD samples and perform BCR repertoire profiling and pairwise sharing analysis. As a result, longitudinal increase in B lymphocytes is associated with increased cerebral amyloid deposition and hyperactivates induced pluripotent stem cell-derived microglia with loss-of-function for beta-amyloid clearance. Patients with AD share similar class-switched BCR sequences with identical isotypes, despite the high somatic hypermutation rate. Thus, BCR repertoire profiling can lead to the development of individualized immune-based therapeutics and treatment. We provide evidence of both quantitative and qualitative changes in B lymphocytes during AD pathogenesis.

Multi-Omics-Based Autophagy-Related Untypical Subtypes in Patients with Cerebral Amyloid Pathology.

Recent multi-omics analyses paved the way for a comprehensive understanding of pathological processes. However, only few studies have explored Alzheimer's disease (AD) despite the possibility of biological subtypes within these patients. For this study, unsupervised classification of four datasets (genetics, miRNA transcriptomics, proteomics, and blood-based biomarkers) using Multi-Omics Factor Analysis+ (MOFA+), along with systems-biological approaches following various downstream analyses are performed. New subgroups within 170 patients with cerebral amyloid pathology (Aß+) are revealed and the features of them are identified based on the top-rated targets constructing multi-omics factors of both whole (M-TPAD) and immune-focused models (M-IPAD). The authors explored the characteristics of subtypes and possible key-drivers for AD pathogenesis. Further in-depth studies showed that these subtypes are associated with longitudinal brain changes and autophagy pathways are main contributors. The significance of autophagy or clustering tendency is validated in peripheral blood mononuclear cells (PBMCs; n = 120 including 30 Aß- and 90 Aß+), induced pluripotent stem cell-derived human brain organoids/microglia (n = 12 including 5 Aß-, 5 Aß+, and CRISPR-Cas9 apolipoprotein isogenic lines), and human brain transcriptome (n = 78). Collectively, this study provides a strategy for precision medicine therapy and drug development for AD using integrative multi-omics analysis and network modelling.

Neurotoxicity of phenylalanine on human iPSC-derived cerebral organoids.

Phenylketonuria (PKU) is a common genetic metabolic disorder that causes phenylalanine accumulation in the blood. The most serious symptoms are related to the brain, as intellectual disability, seizure, and microcephaly are commonly found in poorly treated PKU patients and the babies of maternal PKU. However, the mechanism of hyperphenylalaninemia on human neurodevelopment is still unclear. Here we utilized human induced pluripotent stem cell (iPSC)-derived cerebral organoids to investigate the neurotoxicity of hyperphenylalaninemia. Cerebral organoids at days 40 or 100 were treated with different concentrations of phenylalanine for 5 days. After phenylalanine treatments, the cerebral organoids displayed alterations in organoid size, induction of apoptosis, and depletion of neural progenitor cells. However, phenylalanine did not have an impact on neurons and glia, including astrocytes, immature oligodendrocytes, and mature oligodendrocytes. Remarkably, a reduction in the thickness of the cortical rosettes and a decrease in myelination at the intermediate zone were inspected with the elevated phenylalanine concentrations. RNA-seq of phenylalanine-treated organoids revealed that gene sets related to apoptosis, p53 signaling pathway, and TNF signaling pathway via NF-kB were enriched in upregulated genes, while those related to cell cycle and amino acid metabolism were enriched in downregulated genes. In addition, there were several microcephaly disease genes, such as ASPM, LMNB1, and CENPE, ranked at the top of the downregulated genes. These findings indicate that phenylalanine exposure may contribute to microcephaly, abnormal cortical expansion, and myelination lesions in the developing human brain.