ABSTRACT
OBJECTIVES: Previous studies have shown that microstructural alterations in white matter (WM) could contribute to the symptom manifestation and support the dysconnectivity hypothesis in schizophrenia patients. These alterations were pervasive, non-specific, and reported inconsistently across the literature. This study aimed to specifically investigate the microstructure alterations of the posterior limb of the internal capsule (PLIC) in first-episode, drug-naive schizophrenia patients. Utilizing a multicompartmental biophysical model, we further explored the correlation between these alterations and syndrome scale scores. METHODS: Thirty-two individuals with first-episode, drug-naive schizophrenia (FES) and thirty demographically matched healthy controls were enrolled. High-resolution multi-shell diffusion MRI data were collected, followed by the application of a three-compartment Neurite Orientation Dispersion and Density Imaging (NODDI) model to scrutinize the alterations in white matter microstructure. Changes in sensory and motor fibers within the PLIC were specifically focused on. Additionally, the correlation between these pathological changes and scores on the Positive and Negative Syndrome Scale (PANSS) was investigated. RESULTS: The Neurite density index (NDI) in the left PLIC was significantly lower in FES patients compared to healthy individuals, and positively correlated with PANSS positive syndrome scores (r = 0.0379, p = 0.046). In the sensory component (left superior thalamic radiation within PLIC, STR_P), the NDI was significantly elevated (p < 0.0001). Conversely, the NDI in the motor component (left corticospinal tract within PLIC, CST_P) was reduced (p = 0.007) in FES patients compared to healthy individuals, and strongly correlated with PANSS positive syndrome scores (p < 0.020) and PANSS total scores (p < 0.045). Moreover, the NDI deviation of STR from total PLIC (fSTR_P) and NDI deviation in STR_P and CST_P compared to PLIC region (fPLIC) were significantly higher in FES patients than in healthy controls (p < 0.00001), with an area under the curve (AUC) of fPLIC reaching 0.872. CONCLUSION: The study's findings provided new insights into the discrepancy of white matter microstructure changes associated with the sensory and motor fibers in the PLIC region in FES patients. These results contribute to the growing body of evidence suggesting that WM microstructural alterations play a critical role in schizophrenia pathophysiology.
Subject(s)
Internal Capsule , Schizophrenia , White Matter , Humans , Schizophrenia/pathology , Schizophrenia/diagnostic imaging , Internal Capsule/pathology , Internal Capsule/diagnostic imaging , White Matter/diagnostic imaging , White Matter/pathology , Female , Male , Adult , Young Adult , Diffusion Magnetic Resonance Imaging/methods , Diffusion Tensor Imaging/methodsABSTRACT
CONTEXT: Computational drug repurposing methods have been continuously developed in recent years to alleviate the high costs associated with drug development. As drug targets or the products of disease-related genes, proteins play an important role in drug repurposing. Although the potential has been demonstrated, heterogeneous graphs with proteins as independent nodes have yet to be studied, where extracting high-quality protein features from heterogeneous graphs poses a significant challenge. A novel drug repurposing model based on the feature construction of multi-layer ensemble (DRML-Ensemble) is proposed in this study. The performance of DRML-Ensemble, as evaluated on publicly available datasets, achieves an AUPR value of 0.93 and an AUROC value of 0.92, surpassing those of existing state-of-the-art methods. Additionally, DRML-Ensemble demonstrates its notable ability for drug repurposing in Alzheimer's disease. METHODS: DRML-Ensemble is primarily composed of multiple layers of heterogeneous graph feature construction (HGFC). Each HGFC can extract protein features by leveraging the relationships between drugs, diseases, and proteins. These protein features are then utilized in subsequent layers to build drug and disease features, facilitating drug repurposing. By stacking multiple layers, optimal protein features can be obtained from the heterogeneous graph, consequently improving the accuracy of drug repurposing. However, an excessive· stacking of layers usually affect the model's training process, for example, causing problems such as overfitting; a multi-layer ensemble prediction module is designed to further improve the model's performance.
Subject(s)
Drug Repositioning , Drug Repositioning/methods , Humans , Proteins/chemistry , Computational Biology/methods , Algorithms , Alzheimer Disease/drug therapyABSTRACT
Microglia, the resident immune cells of the central nervous system (CNS), play a dual role in neurotoxicity by releasing the NLR Family Pyrin Domain Containing 3 (NLRP3) inflammasome and brain-derived neurotrophic factor (BDNF) in response to environmental stress. Suppression of BDNF is implicated in learning and memory impairment induced by exposure to manganese (Mn) or lead (Pb) individually. Methyl CpG Binding Protein 2 (MeCp2) and its phosphorylation status are related to BDNF suppression. Protein phosphatase2A (PP2A), a member of the serine/threonine phosphatases family, dephosphorylates substrates based on the methylation state of its catalytic C subunit (PP2Ac). However, the specific impairment patterns and molecular mechanisms resulting from co-exposure to Mn and Pb remain unclear. Therefore, the purpose of this study was to explore the effects of Mn and Pb exposure, alone and in combination, on inducing neurotoxicity in the hippocampus of mice and BV2 cells, and to determine whether simultaneous exposure to both metals exacerbate their toxicity. Our findings reveal that co-exposure to Mn and Pb leads to severe learning and memory impairment in mice, which correlates with the accumulation of metals in the hippocampus and synergistic suppression of BDNF. This suppression is accompanied by up-regulation of the epigenetic repressor MeCp2 and its phosphorylation status, as well as demethylation of PP2Ac. Furthermore, inhibition of PP2Ac demethylation using ABL127, an inhibitor for its protein phosphatase methylesterase1 (PME1), or knockdown of MeCp2 via siRNA transfection in vitro effectively increases BDNF expression and mitigates BV2 cell damage induced by Mn and Pb co-exposure. We also observe abnormal activation of microglia characterized by enhanced release of the NLRP3 inflammasome, Casepase-1 and pro-inflammatory cytokines IL-1ß, in the hippocampus of mice and BV2 cells. In summary, our experiments demonstrate that simultaneous exposure to Mn and Pb results in more severe hippocampus-dependent learning and memory impairment, which is attributed to epigenetic suppression of BDNF mediated by PP2A regulation.
Subject(s)
Brain-Derived Neurotrophic Factor , Epigenesis, Genetic , Hippocampus , Lead , Manganese , Memory Disorders , Animals , Brain-Derived Neurotrophic Factor/metabolism , Mice , Epigenesis, Genetic/drug effects , Manganese/toxicity , Lead/toxicity , Hippocampus/drug effects , Hippocampus/metabolism , Memory Disorders/chemically induced , Male , Mice, Inbred C57BL , Microglia/drug effects , Methyl-CpG-Binding Protein 2/metabolism , Methyl-CpG-Binding Protein 2/genetics , Protein Phosphatase 2/metabolism , Learning/drug effectsABSTRACT
Drug repurposing is an effective method to reduce the time and cost of drug development. Computational drug repurposing can quickly screen out the most likely associations from large biological databases to achieve effective drug repurposing. However, building a comprehensive model that integrates drugs, proteins, and diseases for drug repurposing remains challenging. This study proposes a drug repurposing method based on the ternary heterogeneous graph attention network (DRTerHGAT). DRTerHGAT designs a novel protein feature extraction process consisting of a large-scale protein language model and a multi-task autoencoder, so that protein features can be extracted accurately and efficiently from amino acid sequences. The ternary heterogeneous graph of drug-protein-disease comprehensively considering the relationships among the three types of nodes, including three homogeneous and three heterogeneous relationships. Based on the graph and the extracted protein features, the deep features of the drugs and the diseases are extracted by graph convolutional networks (GCN) and heterogeneous graph node attention networks (HGNA). In the experiments, DRTerHGAT is proven superior to existing advanced methods and DRTerHGAT variants. DRTerHGAT's powerful ability for drug repurposing is also demonstrated in Alzheimer's disease.
Subject(s)
Drug Repositioning , Drug Repositioning/methods , Humans , Proteins/chemistry , Algorithms , Alzheimer Disease/drug therapy , Neural Networks, Computer , Computational Biology/methods , SoftwareABSTRACT
Real-time tracking of intracellular carbohydrates remains challenging. While click chemistry allows bio-orthogonal tagging with fluorescent probes, the reaction permanently alters the target molecule and only allows a single snapshot. Here, we demonstrate click-free mid-infrared photothermal (MIP) imaging of azide-tagged carbohydrates in live cells. Leveraging the micromolar detection sensitivity for 6-azido-trehalose (TreAz) and the 300-nm spatial resolution of MIP imaging, the trehalose recycling pathway in single mycobacteria, from cytoplasmic uptake to membrane localization, is directly visualized. A peak shift of azide in MIP spectrum further uncovers interactions between TreAz and intracellular protein. MIP mapping of unreacted azide after click reaction reveals click chemistry heterogeneity within a bacterium. Broader applications of azido photothermal probes to visualize the initial steps of the Leloir pathway in yeasts and the newly synthesized glycans in mammalian cells are demonstrated.
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Targeting immunosuppressive metastatic cancer cells is a key challenge in therapy. We recently have shown that a rigid-rod aromatic, pBP-NBD, that responds to enzymes and kill immunosuppressive metastatic osteosarcoma (mOS) and castration resistant prostate cancer (CRPC) cells in mimetic bone microenvironment. However, pBP-NBD demonstrated moderate efficacy against CRPC cells. To enhance activity, we incorporated the unnatural amino acid L- or D-4,4'-biphenylalanine (L- or D-BiP) into pBP-NBD, drastically increasing cellular uptake and CRPC inhibition. Specifically, we inserted BiP into pBP-NBD to target mOS (Saos2 and SJSA1) and CRPC (VCaP and PC3) cells with overexpressed phosphatases. Our results show that the D-peptide backbone with an aspartate methyl diester at the C-terminal offers the highest activity against these immunosuppressive mOS and CRPC cells. Importantly, imaging shows that the peptide assemblies almost instantly enter the cells and accumulate primarily within the endoplasmic reticulum of Saos2, SJSA1, and PC3 cells and at the lysosomes of VCaP cells. By using BiP to boost cellular uptake and self-assembly within cancer cells, this work illustrates an unnatural hydrophobic amino acid as a versatile and effective residue to boost endocytosis of synthetic peptides for intracellular self-assembly.
Subject(s)
Amino Acids , Humans , Cell Line, Tumor , Amino Acids/chemistry , Osteosarcoma/drug therapy , Osteosarcoma/metabolism , Osteosarcoma/pathology , Male , Antineoplastic Agents/pharmacology , Antineoplastic Agents/chemistry , Endocytosis/drug effects , Peptides/chemistry , Peptides/pharmacology , Prostatic Neoplasms/drug therapy , Prostatic Neoplasms/metabolism , Prostatic Neoplasms/pathologyABSTRACT
Simultaneous spatial mapping of the activity of multiple enzymes in a living system can elucidate their functions in health and disease. However, methods based on monitoring fluorescent substrates are limited. Here, we report the development of nitrile (C≡N)-tagged enzyme activity reporters, named nitrile chameleons, for the peak shift between substrate and product. To image these reporters in real time, we developed a laser-scanning mid-infrared photothermal imaging system capable of imaging the enzymatic substrates and products at a resolution of 300 nm. We show that when combined, these tools can map the activity distribution of different enzymes and measure their relative catalytic efficiency in living systems such as cancer cells, Caenorhabditis elegans, and brain tissues, and can be used to directly visualize caspase-phosphatase interactions during apoptosis. Our method is generally applicable to a broad category of enzymes and will enable new analyses of enzymes in their native context.
Subject(s)
Diagnostic Imaging , Nitriles , Coloring AgentsABSTRACT
Although the formation of peptide assemblies catalyzed by alkaline phosphatase (ALP) has received increasing attention in inhibiting cancer cells, the detailed enzyme kinetics of the dephosphorylation of the corresponding phosphopeptide assemblies have yet to be determined. We recently discovered that assemblies from a phosphopentapeptide can form intracellular nanoribbons that kill induced pluripotent stem cells or osteosarcoma cells, but the kinetics of enzymatic dephosphorylation remain unknown. Thus, we chose to examine the enzyme kinetics of the dephosphorylation of the phosphopentapeptide [NBD-LLLLpY (1)] from concentrations below to above its critical micelle concentration (CMC). Our results show that the phosphopeptide exhibits a CMC of 75 µM in phosphate saline buffer, and the apparent Vmax and Km values of alkaline phosphatase catalyzed dephosphorylation are approximately 0.24 µM/s and 5.67 mM, respectively. Despite dephosphorylation remaining incomplete at 60 min in all the concentrations tested, dephosphorylation of the phosphopeptide at concentrations of 200 µM or above mainly results in nanoribbons, dephosphorylation at concentrations of CMC largely produces nanofibers, and dephosphorylation below the CMC largely generates nanoparticles. Moreover, the formation of nanoribbons correlates with the intranuclear accumulation of the pentapeptide. By providing the first examination of the enzymatic kinetics of phosphopeptide assemblies, this work further supports the notion that the assemblies of phosphopentapeptides can act as a new functional entity for controlling cell fates.
Subject(s)
Nanotubes, Carbon , Phosphopeptides , Alkaline Phosphatase/metabolism , KineticsABSTRACT
In order to enhance the retrieval accuracy of cloud top height (CTH) from MODIS data, neural network models were employed based on Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data. Three types of methods were established using MODIS inputs: cloud parameters, calibrated radiance, and a combination of both. From a statistical standpoint, models with combination inputs demonstrated the best performance, followed by models with calibrated radiance inputs, while models relying solely on calibrated radiance had poorer applicability. This work found that cloud top pressure (CTP) and cloud top temperature played a crucial role in CTH retrieval from MODIS data. However, within the same type of models, there were slight differences in the retrieved results, and these differences were not dependent on the quantity of input parameters. Therefore, the model with fewer inputs using cloud parameters and calibrated radiance was recommended and employed for individual case studies. This model produced results closest to the actual cloud top structure of the typhoon and exhibited similar cloud distribution patterns when compared with the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) CTHs from a climatic statistical perspective. This suggests that the recommended model has good applicability and credibility in CTH retrieval from MODIS images. This work provides a method to improve accurate CTHs from MODIS data for better utilization.
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PURPOSE: This study aims to develop a high-efficiency and high-resolution 3D imaging approach for simultaneous mapping of multiple key tissue parameters for routine brain imaging, including T1 , T2 , proton density (PD), ADC, and fractional anisotropy (FA). The proposed method is intended for pushing routine clinical brain imaging from weighted imaging to quantitative imaging and can also be particularly useful for diffusion-relaxometry studies, which typically suffer from lengthy acquisition time. METHODS: To address challenges associated with diffusion weighting, such as shot-to-shot phase variation and low SNR, we integrated several innovative data acquisition and reconstruction techniques. Specifically, we used M1-compensated diffusion gradients, cardiac gating, and navigators to mitigate phase variations caused by cardiac motion. We also introduced a data-driven pre-pulse gradient to cancel out eddy currents induced by diffusion gradients. Additionally, to enhance image quality within a limited acquisition time, we proposed a data-sharing joint reconstruction approach coupled with a corresponding sequence design. RESULTS: The phantom and in vivo studies indicated that the T1 and T2 values measured by the proposed method are consistent with a conventional MR fingerprinting sequence and the diffusion results (including diffusivity, ADC, and FA) are consistent with the spin-echo EPI DWI sequence. CONCLUSION: The proposed method can achieve whole-brain T1 , T2 , diffusivity, ADC, and FA maps at 1-mm isotropic resolution within 10 min, providing a powerful tool for investigating the microstructural properties of brain tissue, with potential applications in clinical and research settings.
Subject(s)
Brain , Magnetic Resonance Imaging , Humans , Brain/diagnostic imaging , Magnetic Resonance Imaging/methods , Phantoms, Imaging , Mathematical ConceptsABSTRACT
PURPOSE: This study aims to develop a high-resolution whole-brain multi-parametric quantitative MRI approach for simultaneous mapping of myelin-water fraction (MWF), T1, T2, and proton-density (PD), all within a clinically feasible scan time. METHODS: We developed 3D visualization of short transverse relaxation time component (ViSTa)-MRF, which combined ViSTa technique with MR fingerprinting (MRF), to achieve high-fidelity whole-brain MWF and T1/T2/PD mapping on a clinical 3T scanner. To achieve fast acquisition and memory-efficient reconstruction, the ViSTa-MRF sequence leverages an optimized 3D tiny-golden-angle-shuffling spiral-projection acquisition and joint spatial-temporal subspace reconstruction with optimized preconditioning algorithm. With the proposed ViSTa-MRF approach, high-fidelity direct MWF mapping was achieved without a need for multicompartment fitting that could introduce bias and/or noise from additional assumptions or priors. RESULTS: The in vivo results demonstrate the effectiveness of the proposed acquisition and reconstruction framework to provide fast multi-parametric mapping with high SNR and good quality. The in vivo results of 1 mm- and 0.66 mm-isotropic resolution datasets indicate that the MWF values measured by the proposed method are consistent with standard ViSTa results that are 30× slower with lower SNR. Furthermore, we applied the proposed method to enable 5-min whole-brain 1 mm-iso assessment of MWF and T1/T2/PD mappings for infant brain development and for post-mortem brain samples. CONCLUSIONS: In this work, we have developed a 3D ViSTa-MRF technique that enables the acquisition of whole-brain MWF, quantitative T1, T2, and PD maps at 1 and 0.66 mm isotropic resolution in 5 and 15 min, respectively. This advancement allows for quantitative investigations of myelination changes in the brain.
Subject(s)
Myelin Sheath , Water , Humans , Magnetic Resonance Imaging/methods , Brain/diagnostic imaging , Brain Mapping/methods , Phantoms, Imaging , Image Processing, Computer-Assisted/methodsABSTRACT
The interaction of multiple drugs could lead to severe events, which cause medical injuries and expenses. Accurate prediction of drug-drug interaction (DDI) events can help clinicians make effective decisions and establish appropriate therapy programs. However, there exist two issues worthy of further consideration. (i) The global features of drug molecules should be paid attention to, rather than just their local characteristics. (ii) The fusion of multi-source features should also be studied to capture the comprehensive features of the drug. This study designs a Multi-Source Feature Fusion framework with Multiple Attention blocks named MSFF-MA-DDI that utilizes multimodal data for DDI event prediction. MSFF-MA-DDI can (i) encode global correlations between long-distance atoms in drug molecular sequences by a self-attention layer based on a position embedding block and (ii) fuse drug sequence features and heterogeneous features (chemical substructure, target, and enzyme) through a multi-head attention block to better represent the features of drugs. Experiments on real-world datasets show that MSFF-MA-DDI can achieve performance that is close to or even better than state-of-the-art models. Especially in cold start scenarios, the model can achieve the best performance. The effectiveness of the model is also supported by the case study on nervous system drugs. The source codes and data are available at https://github.com/BioCenter-SHU/MSFF-MA-DDI.
Subject(s)
Software , Drug InteractionsABSTRACT
The understanding on how short peptide assemblies transit from disorder to order remains limited due to the lack of atomistic structures. Here we report cryo-EM structure of the nanofibers short intrinsically disordered peptides (IDPs). Upon lowering pH or adding calcium ions, the IDP transitions from individual nanoparticles to nanofibers containing an aromatic core and a disordered periphery comprised of 2 to 5 amino acids. Protonating the phosphate or adding more metal ions further assembles the nanofibers into filament bundles. The assemblies of the IDP analogs with controlled chemistry, such as phosphorylation site, hydrophobic interactions, and sequences indicate that metal ions interact with the flexible periphery of the nanoparticles of the IDPs to form fibrils and enhance the interfibrillar interactions to form filament bundles. Illustrating that an IDP self-assembles from disorder to order, this work offers atomistic molecular insights to understand assemblies of short peptides driven by noncovalent interactions.
ABSTRACT
White matter of the human brain is influenced by common genetic variations and shaped by neural activity-dependent experiences. Variations in microstructure of cerebral white matter across individuals and even across fiber tracts might underlie differences in cognitive capacity and vulnerabilities to mental disorders. The frontoparietal and cingulo-opercular networks of the brain constitute the central system supporting cognitive functions, and functional connectivity of these networks has been used to distinguish individuals known as "functional fingerprinting." The frontal aslant tract (FAT) that passes through the two networks has been implicated in executive functions. However, whether FAT can be used as a "structural fingerprint" to distinguish individuals and predict an individual's cognitive function and dysfunction is unknown. Here we investigated the fingerprinting property of FAT microstructural profiles using three independent diffusion MRI datasets with repeated scans on human participants including both females and males. We found that diffusion and geometric profiles of FAT can be used to distinguish individuals with a high accuracy. Next, we demonstrated that fractional anisotropy in different FAT segments predicted distinct cognitive functions, including working memory, inhibitory control, and relational reasoning. Finally, we assessed the contribution of altered FAT microstructural profiles to cognitive dysfunction in unmedicated patients with obsessive-compulsive disorders. We found that the altered microstructure in FAT was associated with the severity of obsessive-compulsive symptoms. Collectively, our findings suggest that the microstructural profiles of FAT can identify individuals with a high accuracy and may serve as an imaging marker for predicting an individual's cognitive capacity and disease severity.SIGNIFICANCE STATEMENT The frontoparietal network and cingulo-opercular network of the brain constitute a dual-network architecture for human cognitive functions, and functional connectivity of these two networks can be used as a "functional fingerprint" to distinguish individuals. However, the structural underpinnings of these networks subserving individual heterogeneities in their functional connectivity and cognitive ability remain unknown. We show here that the frontal aslant tract (FAT) that passes through the two networks distinguishes individuals with a high accuracy. Further, we demonstrate that the diffusion profiles of FAT predict distinct cognitive functions in healthy subjects and are associated with the clinical symptoms in patients with obsessive-compulsive disorders. Our findings suggest that the FAT may serve as a unique structural fingerprint underlying individual cognitive capability.
Subject(s)
Brain , Obsessive-Compulsive Disorder , Male , Female , Humans , Diffusion Magnetic Resonance Imaging , Cognition , Executive Function , Obsessive-Compulsive Disorder/diagnosis , Magnetic Resonance ImagingABSTRACT
Background: Whole brain radiation therapy (WBRT) can cause cognitive dysfunctions in lung cancer patients with brain metastasis (BM). Diffusion kurtosis imaging (DKI) can detect brain microstructural alterations sensitivly. We aimed to identify the potential of DKI parameters for early radiation-induced brain injury and investigate the association between microstructure changes and neurocognitive function (NCF) decline. Methods: Lung cancer patients with BM (n=35) who underwent WBRT in a single center in Zhejiang, China, were consecutively and prospectively enrolled between June 24th, 2020 and December 22nd, 2021, and the median follow-up time was 6.0 months (3.6-6.6 months). DKI and T1-weighted (T1W) MRI scans were acquired prior to and following WBRT. Diffusivity-based (mean diffusivity, MD; fractional anisotropy, FA) and kurtosis-based (mean kurtosis, MK; axial kurtosis, AK) parameters were calculated within the automated anatomical labeling (AAL) atlas-based regions. Reliable change indices practice effects (RCI-PE) scores of the Mini-Mental State Examination (MMSE) were calculated to determine significant neurocognitive decline by a one-sample t-test from baseline to 2-6 months post-WBRT. To assess the subacute induced effects within the whole brain, percentage changes of DKI parameters were evaluated at 170 atlas-based regions by a one-sample t-test. Linear regression analyses were used to evaluate the association between DKI parameter changes and RCI-PE scores. Results: Finally, the study included 19 patients in the longitudinal follow-up. RCI-PE scores declined at 2-6 months post-WBRT (mean RCI-PE =-0.842, 95% CI, -0.376 to -1.310; P=0.002). With the atlas-based analysis of subacute effects after post-WBRT, a total of 28 regions changed in at least one diffusion parameter, revealing region-wise microstructural alterations in the brain. Significant correlations of at least one diffusion parameters with RCI-PEs were observed in 9 regions, such as the right orbital part of the inferior frontal gyrus [right IFGorb, r(AK) =0.47, P=0.03] and left middle temporal gyrus [left MTG, r(MK) =-0.49, P=0.03]. Conclusions: DKI parameters can be used to detect early microstructure changes and represent important imaging predictors for cognitive decline. The reported 9 regions are more particularly vulnerable to neurocognitive radiation-induced impairment for lung cancer patients with BM, representing potential dose-avoidance targets for cognitive function preservation.
ABSTRACT
Rapid cellular uptake of synthetic molecules remains a challenge, and the motif frequently employed to generate prodrugs, succinic ester, unfortunately lowers the efficacy of the desired drugs due to their slow ester hydrolysis and low cell entry. Here we show that succinic ester-containing diglycine drastically boosts the cellular uptake of supramolecular assemblies or prodrugs. Specifically, autohydrolysis of the diglycine-activated succinic esters turns the nanofibers of the conjugates of succinic ester and self-assembling motif into nanoparticles for fast cellular uptake. The autohydrolysis of diglycine-activated succinic esters and drug conjugates also restores the efficacy of the drugs. 2D nuclear magnetic resonance (NMR) suggests that a "U-turn" of diglycine favors intramolecular hydrolysis of diglycine-activated succinic esters to promote autohydrolysis. As an example of rapid autohydrolysis of diglycine-activated succinic esters for instant cellular uptake, this work illustrates a nonenzymatic bond cleavage approach to develop effective therapeutics for intracellular targeting.
Subject(s)
Prodrugs , Prodrugs/pharmacology , Prodrugs/chemistry , Esters/chemistry , Glycylglycine , Biological Transport , HydrolysisABSTRACT
Cancer is a major public health concern requiring novel treatment approaches. Enzyme-instructed self-assembly (EISA) provides a unique approach for selectively inhibiting cancer cells. However, the structure and activity correlation of EISA remains to be explored. This study investigates new EISA substrates of alkaline phosphatase (ALP) to hinder ovarian cancer cells. Analogues 2-8 were synthesized by modifying the amino acid residues of a potent EISA substrate 1 that effectively inhibits the growth of OVSAHO, a high-grade serous ovarian cancer (HGSOC) cell line. The efficacy of 2-8 against OVSAHO was assessed, along with the combination of substrate 1 with clinically used drugs. The results reveal that substrate 1 displays the highest cytotoxicity against OVSAHO cells, with an IC50 of around 8 µM. However, there was limited synergism observed between substrate 1 and the tested clinically used drugs. These findings indicate that EISA likely operates through a distinct mechanism that necessitates further elucidation.
Subject(s)
Alkaline Phosphatase , Ovarian Neoplasms , Female , Humans , Alkaline Phosphatase/metabolism , Peptides/pharmacology , Peptides/chemistry , Ovarian Neoplasms/drug therapy , Cell Line , Cell Line, TumorABSTRACT
Introduction: The ventral tegmental area (VTA) is less affected compared to substantia nigra pars compacta (SNc) in Parkinson's disease (PD). This study aimed to quantitatively evaluate iron content in the VTA across different stages of PD in order to help explain the selective loss of dopamine neurons in PD. Methods: Quantitative susceptibility mapping (QSM) data were obtained from 101 PD patients, 35 idiopathic rapid eye movement sleep behavior disorder (RBD) patients, and 62 healthy controls (HCs). The mean QSM values in the VTA and SNc were calculated and compared among the groups. Results: Both RBD and PD patients had increased iron values in the bilateral SNc compared with HCs. RBD and PD patients in the Hoehn-Yahr (H & Y) stage 1 did not show elevated iron values in the VTA, while PD patients with more than 1.5 H & Y staging had increased iron values in bilateral VTA compared to HCs. Discussion: This study shows that there is no increased iron accumulation in the VTA during the prodromal and early clinical stages of PD, but iron deposition increases significantly as the disease becomes more severe.
ABSTRACT
Speech comprehension is a complex process involving multiple stages, such as decoding of phonetic units, recognizing words, and understanding sentences and passages. In this study, we identify cortical networks beyond basic phonetic processing using a novel passage learning paradigm. Participants learn to comprehend a story composed of syllables of their native language, but containing unfamiliar vocabulary and syntax. Three learning methods are employed, each resulting in some degree of learning within a 12-min learning session. Functional magnetic resonance imaging results reveal that, when listening to the same story, the classic temporal-frontal language network is significantly enhanced by learning. Critically, activation of the left anterior and posterior temporal lobe correlates with the learning outcome that is assessed behaviorally through, e.g. word recognition and passage comprehension tests. This study demonstrates that a brief learning session is sufficient to induce neural plasticity in the left temporal lobe, which underlies the transformation from phonetic units to the units of meaning, such as words and sentences.