Novel Angiotensin-Converting Enzyme-Inhibitory Peptides Obtained from Trichiurus lepturus: Preparation, Identification and Potential Antihypertensive Mechanism.

Peptides possessing antihypertensive attributes via inhibiting the angiotensin-converting enzyme (ACE) were derived through the enzymatic degradation of Trichiurus lepturus (ribbonfish) using alkaline protease. The resulting mixture underwent filtration using centrifugation, ultrafiltration tubes, and Sephadex G-25 gels. Peptides exhibiting ACE-inhibitory properties and DPPH free-radical-scavenging abilities were isolated and subsequently purified via LC/MS-MS, leading to the identification of over 100 peptide components. In silico screening yielded five ACE inhibitory peptides: FAGDDAPR, QGPIGPR, IFPRNPP, AGFAGDDAPR, and GPTGPAGPR. Among these, IFPRNPP and AGFAGDDAPR were found to be allergenic, while FAGDDAPRR, QGPIGPR, and GPTGPAGP showed good ACE-inhibitory effects. IC50 values for the latter peptides were obtained from HUVEC cells: FAGDDAPRR (IC50 = 262.98 µM), QGPIGPR (IC50 = 81.09 µM), and GPTGPAGP (IC50 = 168.11 µM). Peptide constituents derived from ribbonfish proteins effectively modulated ACE activity, thus underscoring their therapeutic potential. Molecular docking and modeling corroborated these findings, emphasizing the utility of functional foods as a promising avenue for the treatment and prevention of hypertension, with potential ancillary health benefits and applications as substitutes for synthetic drugs.

Vitamin D deficiency increases the risk of diabetic peripheral neuropathy in elderly type 2 diabetes mellitus patients by predominantly increasing large-fiber lesions.

AIMS: This study explores the link between Vitamin D deficiency (VDD) and diabetic peripheral neuropathy (DPN) in elderly type 2 diabetes mellitus (T2DM) patients. METHODS: Involving 257 elderly T2DM patients, the study utilized propensity score matching to balance age, sex, and diabetes duration. VDD was defined as serum 25-hydroxyvitamin D [25(OH)D] levels below 20 ng/ml. Large nerve fiber lesions were evaluated by electromyogram, while small nerve fiber lesions were assessed by measuring skin conductance. RESULTS: DPN patients had notably lower serum 25(OH)D levels than non-DPN patients [15.05 vs. 18.4 ng/ml, P = 0.018]. VDD was identified as an independent risk factor for DPN (odds ratio = 2.488, P = 0.008) in multivariate logistic regression analysis. Spearman's correlation showed negative correlations between serum 25(OH)D levels and specific nerve latencies, and positive correlations with specific nerve velocities and amplitudes. The VDD group exhibited longer median sensory nerve latencies and motor evoked potential latencies compared to the vitamin D-sufficient group. Further, VDD is associated with the prolongation of the median motor nerve latency (odds ratio = 1.362, P = 0.038). CONCLUSIONS: VDD is independently associated with a higher risk of DPN. VDD may promote the development of DPN by affecting large nerve fibers.

Metal-organic-framework derived NiS2/C hollow structures for enhanced polysulfide redox kinetics in lithium-sulfur batteries.

To cope with the shuttling of soluble lithium polysulfides in lithium-sulfur batteries, confinement tactics, such as trapping of sulfur within porous carbon structures, have been extensively studied. Although performance has improved a bit, the slow polysulfide conversion inducing fast capacity decay remains a big challenge. Herein, a NiS2/carbon (NiS2/C) composite with NiS2 nanoparticles embedded in a thin layer of carbon over the surface of micro-sized hollow structures has been prepared from Ni-metal-organic frameworks. These unique structures can physically entrap sulfur species and also influence their redox conversion kinetics. By improving the reaction kinetics of polysulfides, the NiS2/carbon@sulfur (NiS2/C@S) composite cathode with a suppressed shuttle effect shows a high columbic efficiency and decent rate performance. An initial capacity of 900 mAh g-1 at the rate of 1 C (1 C = 1675 mA g-1) and a low-capacity decline rate of 0.132% per cycle after 500 cycles are obtained, suggesting that this work provides a rational design of a sulfur cathode.

Sema4D as a biomarker for Predicting rheumatoid arthritis disease activity.

OBJECTIVE: The semaphorins are membrane or secreted proteins first identified in neural development. Semaphorin 4D (Sema4D) is the first family member found to have immune properties. We evaluated the potential of Sema4D as a marker for rheumatoid arthritis (RA) disease activity, singly and in combination with other known biomarkers including rheumatoid factor (RF) and C-reactive protein (CRP). METHODS: Three hundred and eleven RA patients were enrolled. The patients were divided into three groups based on their disease activity in 28 joints (DAS28): mild, moderate, and severe. The healthy group included 40 healthy individuals. SerumSema4D was measured by quantitative ELISA and the specificity and sensitivity of biomarkers were evaluated by generating a receiver operating characteristic (ROC) curve to analyze their diagnostic accuracy. RESULTS: Serum Sema4D levels in the moderate and severe RA groups were elevated significantly above those of the controls (P < 0.01), while levels in the mild RA and control groups did not differ significantly (P > 0.05). The Sema4D cutoff threshold was 15.7 ng/ml when the DAS28 was applied as a reference. Compared to the erythrocyte sedimentation rate (ESR and CRP, Sema4D had the highest specificity (96.8%) and area under the curve (0.80) for diagnosing RA activity. The highest specificity (100%) for the biomarker combinations was obtained when Sema4D was combined with CRP and anti-CCP, the combination of the Sema4D combined with ESR and anti-CCP had the highest sensitivity (99.35%). According to this result, a new model for jointly calculating RA activity of Sema4D,anti-CCP and CRP was constructed. Meanwhile another model is established by using the method of multivariate analysis.Model comparison results showed the the multiple regression algorithm method fitted the patients' disease activity better. CONCLUSION: The serum Sema 4D level effectively reflects moderate to severe RA activity. Sema4D levels can be used together with conventional RA biomarkers to increase the diagnostic power of RA activity. The multiple regression algorithm method is promising in disease activity calculation.

Scaling of Algorithmic Bias in Pulse Oximetry with Signal-to-Noise Ratio.

Recent work has noted a skin-color bias in existing pulse oximetry systems in their estimation of arterial oxygen saturation. Frequently, the algorithm used by these systems estimate a "ratio-of-ratios", called the "R-value", on their way to estimating the oxygen saturation. In this work, we focus on an "SNR-related" bias that is due to noise in measurements. We derive expressions for the SNR-related bias in R-value estimation, and observe how it scales with the signal-to-noise ratio (SNR). We show that the bias can arise at two steps of R-value estimation: in estimating the max and min of a pulsatile signal, and, additionally in taking ratios to estimate the R-value. We assess the bias resulting from the combination of the two steps, but also separate out contributions of each step. By doing so, we deduce that the bias induced in max and min estimation is likely to dominate. Because the SNR tends to get worse with higher melanin concentration, our result provides a sense of scaling of this bias with melanin concentration.

The Development and Synthesis of a CdZnS @Metal-Organic Framework ZIF-8 for the Highly Efficient Photocatalytic Degradation of Organic Dyes.

The development of photocatalysts for organic degradation is a hot research topic. In this study, CdZnS was selected as the carrier, and ZIF-8 was combined with it to explore the photocatalytic performance of the composite. In addition, the compound material, CdZnS@ZIF-8, was used as a photocatalyst for the decomposition of methylene blue dye, and the performance of pure CdZnS and pure ZIF-8 was compared. The photocatalytic efficiency of CdZnS@ZIF-8 was significantly higher than that of the other two. In the experimental reaction, the amount of catalyst was 0.04 g, the pH value was 7, the initial concentration of methylene blue aqueous solution was 20 mg/L, and the degradation of methylene blue in 50 mL aqueous solution could reach 99.5% under visible light irradiation for 90 min, showing excellent photocatalytic efficiency in the visible light range. It demonstrated excellent photocatalytic function in the visible light region, and the electron transfer phenomenon at the interface occurred in the het-junction and the separation of the photo-generating electron-hole as an electron acceptor of ZIF-8 further promoted the photocatalytic effect.

Comprehensive analysis of thirteen-gene panel with prognosis value in Multiple Myeloma.

BACKGROUND: Although there are many treatments for Multiple myeloma (MM), patients with MM still unable to escape the recurrence and aggravation of the disease. OBJECTIVE: We constructed a risk model based on genes closely associated with MM prognosis to predict its prognostic value. METHODS: Gene function enrichment and signal pathway enrichment analysis, Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis, univariate and multivariate Cox regression analysis, Kaplan-Meier (KM) survival analysis and Receiver Operating Characteristic (ROC) analysis were used to identify the prognostic gene signature for MM. Finally, the prognostic gene signature was validated using the Gene Expression Omnibus (GEO) database. RESULTS: Thirteen prognostic genes were screened by univariate Cox analysis and LASSO regression analysis. Multivariate Cox analysis revealed risk score to be an independent prognostic factor for patients with MM [Hazard Ratio (HR) = 2.564, 95% Confidence Interval (CI) = 2.223-2.958, P< 0.001]. The risk score had a high level of predictive value according to ROC analysis, with an area under the curve (AUC) of 0.744. CONCLUSIONS: The potential prognostic signature of thirteen genes were assessed and a risk model was constructed that significantly correlated with prognosis in MM patients.

A Stabilized Li-Metal Anode with a Ti-Based Metal-Organic Framework Electronic Shield.

The insufficient cyclic efficiency and poor safety have prohibited the commercial applications of the lithium-metal anode because of its uncontrolled dendrite growth at the surface. A mechanically stable and highly ionic conductive solid electrolyte interphase (SEI) holds great promise to address the issues. Herein, a viable surface engineering approach is proposed for stabilizing the Li anode via a scalable artificial method. The surface of Li metal is functionalized by constructing a mechanically tough and electron-insulating metal-organic framework (MOF) of the MIL-125(Ti) layer. In-situ optical microscopy reveals its crucial role in inhibiting dendritic Li growth. Because of the intrinsic insulativity and highly ordered micropores of MIL-125(Ti), the Li+ ions acquire electrons under the coating layer, resulting in a uniform and dense Li deposition behavior. The symmetric cell of the MOF-modified Li electrode delivers a long life span of 2000 h with an overpotential of less than 20 mV at 0.5 mA cm-2. When paired with the same MOF-derived sulfur cathode, decent cycling retention is available as well. This work demonstrates a feasible strategy for the development of a stable Li-metal anode with alleviative dendritic growth.

A model of neurovascular coupling and its application to cortical spreading depolarization.

Cortical spreading depolarization (CSD) is a neuropathological condition involving propagating waves of neuronal silence, and is related to multiple diseases, such as migraine aura, traumatic brain injury (TBI), stroke, and cardiac arrest, as well as poor outcome of patients. While CSDs of different severity share similar roots on the ion exchange level, they can lead to different vascular responses (namely spreading hyperemia and spreading ischemia). In this paper, we propose a mathematical model relating neuronal activities to predict vascular changes as measured with near-infrared spectroscopy (NIRS) and fMRI recordings, and apply it to the extreme case of CSD, where sustained near-complete neuronal depolarization is seen. We utilize three serially connected models (namely, ion exchange, neurovascular coupling, and hemodynamic model) which are described by differential equations. Propagating waves of ion concentrations, as well as the associated vasodynamics and hemodynamics, are simulated by solving these equations. Our proposed model predicts vasodynamics and hemodynamics that agree both qualitatively and quantitatively with experimental literature. Mathematical modeling and simulation offer a powerful tool to help understand the underlying mechanisms of CSD and help interpret the data. In addition, it helps develop novel monitoring techniques prior to data collection. Our simulated results strongly suggest that fMRI is unable to reliably distinguish between spreading hyperemia and spreading ischemia, while NIRS signals are substantially distinct in the two cases.

Evaluating feasibility of functional near-infrared spectroscopy in dolphins.

Significance: Using functional near-infrared spectroscopy (fNIRS) in bottlenose dolphins (Tursiops truncatus) could help to understand how echolocating animals perceive their environment and how they focus on specific auditory objects, such as fish, in noisy marine settings. Aim: To test the feasibility of near-infrared spectroscopy (NIRS) in medium-sized marine mammals, such as dolphins, we modeled the light propagation with computational tools to determine the wavelengths, optode locations, and separation distances that maximize sensitivity to brain tissue. Approach: Using frequency-domain NIRS, we measured the absorption and reduced scattering coefficient of dolphin sculp. We assigned muscle, bone, and brain optical properties from the literature and modeled light propagation in a spatially accurate and biologically relevant model of a dolphin head, using finite-element modeling. We assessed tissue sensitivities for a range of wavelengths (600 to 1700 nm), source-detector distances (50 to 120 mm), and animal sizes (juvenile model 25% smaller than adult). Results: We found that the wavelengths most suitable for imaging the brain fell into two ranges: 700 to 900 nm and 1100 to 1150 nm. The optimal location for brain sensing positioned the center point between source and detector 30 to 50 mm caudal of the blowhole and at an angle 45 deg to 90 deg lateral off the midsagittal plane. Brain tissue sensitivity comparable to human measurements appears achievable only for smaller animals, such as juvenile bottlenose dolphins or smaller species of cetaceans, such as porpoises, or with source-detector separations ≫100 mm in adult dolphins. Conclusions: Brain measurements in juvenile or subadult dolphins, or smaller dolphin species, may be possible using specialized fNIRS devices that support optode separations of >100 mm. We speculate that many measurement repetitions will be required to overcome hemodynamic signals originating predominantly from the muscle layer above the skull. NIRS measurements of muscle tissue are feasible today with source-detector separations of 50 mm, or even less.

Diffuse optical tomography spatial prior for EEG source localization in human visual cortex.

Electroencephalography (EEG) and diffuse optical tomography (DOT) are imaging methods which are widely used for neuroimaging. While the temporal resolution of EEG is high, the spatial resolution is typically limited. DOT, on the other hand, has high spatial resolution, but the temporal resolution is inherently limited by the slow hemodynamics it measures. In our previous work, we showed using computer simulations that when using the results of DOT reconstruction as the spatial prior for EEG source reconstruction, high spatio-temporal resolution could be achieved. In this work, we experimentally validate the algorithm by alternatingly flashing two visual stimuli at a speed that is faster than the temporal resolution of DOT. We show that the joint reconstruction using both EEG and DOT clearly resolves the two stimuli temporally, and the spatial confinement is drastically improved in comparison to reconstruction using EEG alone.

Prognostic value of an eighteen-genes panel in acute myeloid leukemia by analyzing TARGET and TCGA databases.

BACKGROUND: Acute myeloid leukemia (AML) has a poor prognosis, and the current 5-year survival rate is less than 30%. OBJECTIVE: The present study was designed to identify the significant genes closely related to AML prognosis and predict the prognostic value by constructing a risk model based on their expression. METHODS: Using bioinformatics (Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, univariate and multivariate Cox regression analysis, Kaplan-Meier survival analysis, and receiver operating characteristic (ROC) analysis) to identify a prognostic gene signature for AML. Finally, The Cancer Genome Atlas (TCGA) database was used to validate this prognostic signature. RESULTS: Based on univariate and multivariate Cox regression analysis, eighteen prognostic genes were identified, and the gene signature and risk score model were constructed. Multivariate Cox analysis showed that the risk score was an independent prognostic factor [hazard ratio (HR) = 1.122, 95% confidence interval (CI) = 1.067-1.180, P< 0.001]. ROC analysis showed a high predictive value of the risk model with an area under the curve (AUC) of 0.705. CONCLUSIONS: This study evaluated a potential prognostic signature with eighteen genes and constructed a risk model significantly related to the prognosis of AML patients.

Novel gene signature reveals prognostic model in acute lymphoblastic leukemia.

Acute lymphoblastic leukemia (ALL) is a type of hematological malignancy and has a poor prognosis. In our study, we aimed to construct a prognostic model of ALL by identifying important genes closely related to ALL prognosis. We obtained transcriptome data (RNA-seq) of ALL samples from the GDC TARGET database and identified differentially expressed genes (DEGs) using the "DESeq" package of R software. We used univariate and multivariate cox regression analyses to screen out the prognostic genes of ALL. In our results, the risk score can be used as an independent prognostic factor to predict the prognosis of ALL patients [hazard ratio (HR) = 2.782, 95% CI = 1.903-4.068, p < 0.001]. Risk score in clinical parameters has high diagnostic sensitivity and specificity for predicting overall survival of ALL patients, and the area under curve (AUC) is 0.864 in the receiver operating characteristic (ROC) analysis results. Our study evaluated a potential prognostic signature with six genes and constructed a risk model significantly related to the prognosis of ALL patients. The results of this study can help clinicians to adjust the treatment plan and distinguish patients with good and poor prognosis for targeted treatment.

Non-Invasive Spectroscopy for Measuring Cerebral Tissue Oxygenation and Metabolism as a Function of Cerebral Perfusion Pressure.

Near-infrared spectroscopy (NIRS) and diffuse correlation spectroscopy (DCS) measure cerebral hemodynamics, which in turn can be used to assess the cerebral metabolic rate of oxygen (CMRO2) and cerebral autoregulation (CA). However, current mathematical models for CMRO2 estimation make assumptions that break down for cerebral perfusion pressure (CPP)-induced changes in CA. Here, we performed preclinical experiments with controlled changes in CPP while simultaneously measuring NIRS and DCS at rest. We observed changes in arterial oxygen saturation (~10%) and arterial blood volume (~50%) with CPP, two variables often assumed to be constant in CMRO2 estimations. Hence, we propose a general mathematical model that accounts for these variations when estimating CMRO2 and validate its use for CA monitoring on our experimental data. We observed significant changes in the various oxygenation parameters, including the coupling ratio (CMRO2/blood flow) between regions of autoregulation and dysregulation. Our work provides an appropriate model and preliminary experimental evidence for the use of NIRS- and DCS-based tissue oxygenation and metabolism metrics for non-invasive diagnosis of CA health in CPP-altering neuropathologies.

Injectable cartilage matrix hydrogel loaded with cartilage endplate stem cells engineered to release exosomes for non-invasive treatment of intervertebral disc degeneration.

Low back pain, mainly caused by intervertebral disc degeneration (IVDD), is a common health problem; however, current surgical treatments are less than satisfactory. Thus, it is essential to develop novel non-invasive surgical methods for IVDD treatment. Here, we describe a therapeutic strategy to inhibit IVDD by injecting hydrogels modified with the extracellular matrix of costal cartilage (ECM-Gels) that are loaded with cartilage endplate stem cells (CESCs). After loaded with CESCs overexpressing Sphk2 (Lenti-Sphk2-CESCs) and injected near the cartilage endplate (CEP) of rats in vivo, ECM-Gels produced Sphk2-engineered exosomes (Lenti-Sphk2-Exos). These exosomes penetrated the annulus fibrosus (AF) and transported Sphk2 into the nucleus pulposus cells (NPCs). Sphk2 activated the phosphatidylinositol 3-kinase (PI3K)/p-AKT pathway as well as the intracellular autophagy of NPCs, ultimately ameliorating IVDD. This study provides a novel and efficient non-invasive combinational strategy for IVDD treatment using injectable ECM-Gels loaded with CESCs that express Sphk2 with sustained release of functional exosomes.

Enhanced spatiotemporal resolution imaging of neuronal activity using joint electroencephalography and diffuse optical tomography.

Significance: Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) are both commonly used methodologies for neuronal source reconstruction. While EEG has high temporal resolution (millisecond-scale), its spatial resolution is on the order of centimeters. On the other hand, in comparison to EEG, fNIRS, or diffuse optical tomography (DOT), when used for source reconstruction, can achieve relatively high spatial resolution (millimeter-scale), but its temporal resolution is poor because the hemodynamics that it measures evolve on the order of several seconds. This has important neuroscientific implications: e.g., if two spatially close neuronal sources are activated sequentially with only a small temporal separation, single-modal measurements using either EEG or DOT alone would fail to resolve them correctly. Aim: We attempt to address this issue by performing joint EEG and DOT neuronal source reconstruction. Approach: We propose an algorithm that utilizes DOT reconstruction as the spatial prior of EEG reconstruction, and demonstrate the improvements using simulations based on the ICBM152 brain atlas. Results: We show that neuronal sources can be reconstructed with higher spatiotemporal resolution using our algorithm than using either modality individually. Further, we study how the performance of the proposed algorithm can be affected by the locations of the neuronal sources, and how the performance can be enhanced by improving the placement of EEG electrodes and DOT optodes. Conclusions: We demonstrate using simulations that two sources separated by 2.3-3.3 cm and 50 ms can be recovered accurately using the proposed algorithm by suitably combining EEG and DOT, but not by either in isolation. We also show that the performance can be enhanced by optimizing the electrode and optode placement according to the locations of the neuronal sources.

Giant aneurysm of the bilateral vertebrobasilar junction treated by pipeline and coils: A case report and literature review.

Giant aneurysm of the posterior circulation is associated with a higher risk of rupture compared with that of the anterior circulation. Furthermore, surgical clipping and interventional embolization for giant aneurysm of the posterior circulation are more difficult and complex to perform. The present study reported on the case of a 26-year-old female who exhibited a giant spherical aneurysm of the vertebrobasilar junction (VBJ) with a maximum diameter of ~35 mm that caused cervical discomfort. In addition, the patient experienced symptoms including left-sided walking and hoarseness caused by the compression of the brainstem and the posterior cranial nerves. The risks associated with performing surgery in this area are high and the prognosis is mainly poor. The patient of the present study was treated using the Pipeline Flex device with coil embolization. As a giant aneurysm of the VBJ simultaneously affects the bilateral vertebral arteries (VAs) and basilar artery, it is a unique condition and the treatment strategy must be personalized. Based on an analysis of the hemodynamic influence on the aneurysm in the present case, the Pipeline was placed through the left VA, the coils were packed through the right VA, and finally, the right VA was proximally occluded. At 7 months after embolization, the patient's modified Rankin scale score was 1 point. Upon analysis of the hemodynamic influence on the aneurysm of the VBJ, the VA with the larger shear force on the wall of the aneurysm was selected for occlusion to simplify the treatment of the aneurysm and to maximize the probability to achieve recovery.

Improving the measuring length accuracy of articulated arm coordinate measuring machine using artificial neural network.

A new method for further improving the measuring length accuracy of the articulated arm coordinate measuring machine (AACMM) is proposed. The detailed procedure of the proposed method involves kinematic error calibration with the Levenberg-Marquardt algorithm and then non-kinematic error (such as link deflection, thermal errors, and error motions of the rotation shaft) compensation with a back-propagation neural network optimized by the mind evolutionary algorithm. In order to verify the effectiveness and correctness of the proposed method, the simulation and experiment were carried out on an AACMM. The simulated and experimental results demonstrate that the measuring length accuracy of the AACMM is improved significantly after kinematic error calibration and non-kinematic error compensation, confirming the effectiveness and correctness of the proposed method.

Antibody development and property analysis of RhBST2 for accurate cell biological and viral research.

BST2 is a single-pass type II transmembrane (TM) protein, which has a cytoplasmic domain, a transmembrane domain, and an extracellular domain, each domain is important for biologic function of BST2. BST2 is a host restriction factor that can effectively inhibit retrovirus release. Rhesus monkeys are considered as relevant natural animal models for studying AIDS in humans. In order to recognize rhesus BST2 (RhBST2) protein and detect its function accurately, we prepared a polyclonal antibody (pAb) especially for RhBST2. Meanwhile, we constructed RhBST2 proteins with the addition of an HA-tag at the N-terminus (RhBST2-NHA) or inside of the ectodomain (RhBST2-IHA) to compare the recognition ability of rabbit anti-RhBST2 pAb and anti-HA mAb. The results showed that the anti-HA mAb and rabbit anti-RhBST2 pAb had the same ability to identify RhBST2. RhBST2 demonstrated antiviral activity and the ability to activate NF-κB. Moreover, the N-glycosylation states, cell surface level and intracellular localization of RhBST2 were detected. However, HA tags relatively changed part of the biological function of RhBST2. These results show that the RhBST2 polyclonal antibody is more suitable for analyzing the properties and functions of RhBST2, and the natural domain of RhBST2 is very important for its function.

Identification of geraldol as an inhibitor of aquaporin­4 binding by NMO­IgG.

Neuromyelitis optica (NMO) is a severe neurological demyelinating autoimmune disease that affects the optic nerves and spinal cord. There is currently no effective cure or therapy. Aquaporin­4 (AQP4) is a known target of the autoimmune antibody NMO­IgG. Therefore, binding of NMO­IgG to AQP4, and subsequent activation of antibody­mediated and complement­dependent cytotoxicity (CDC), are thought to underlie the pathogenesis of NMO. In the present study, a cell­based high­throughput screening approach was developed to identify molecular inhibitors of NMO­IgG binding to AQP4. Using this approach, extracts from the herb Petroselinum crispum were shown to have inhibitory effects on NMO­IgG binding to AQP4, and the natural compound geraldol was purified from the herb extracts. Analytical high performance liquid chromatography, electrospray ionization­mass spectrometry and nuclear magnetic resonance analyses confirmed the identity of the isolated compound as geraldol, a flavonoid. Geraldol effectively blocked binding of NMO­IgG to AQP4 in immunofluorescence assays and decreased CDC in NMO­IgG/complement­treated FRTL­AQP4 cells and primary astrocytes. Geraldol exhibited low cytotoxicity, with no effect on proliferation or apoptosis of FRTL­AQP4 cells and primary astrocytes. Permeability assays indicated that geraldol did not alter the water transport function of AQP4 in either cell system. The present study suggests the potential therapeutic value of geraldol for NMO drug development.