Termination of convulsion seizures by destabilizing and perturbing seizure memory engrams.

Epileptogenesis, arising from alterations in synaptic strength, shares mechanistic and phenotypic parallels with memory formation. However, direct evidence supporting the existence of seizure memory remains scarce. Leveraging a conditioned seizure memory (CSM) paradigm, we found that CSM enabled the environmental cue to trigger seizure repetitively, and activating cue-responding engram cells could generate CSM artificially. Moreover, cue exposure initiated an analogous process of memory reconsolidation driven by mammalian target of rapamycin-brain-derived neurotrophic factor signaling. Pharmacological targeting of the mammalian target of rapamycin pathway within a limited time window reduced seizures in animals and interictal epileptiform discharges in patients with refractory seizures. Our findings reveal a causal link between seizure memory engrams and seizures, which leads us to a deeper understanding of epileptogenesis and points to a promising direction for epilepsy treatment.

Miniaturized microarray-format digital ELISA enabled by lithographic protein patterning.

The search for reliable protein biomarker candidates is critical for early disease detection and treatment. However, current immunoassay technologies are failing to meet increasing demands for sensitivity and multiplexing. Here, the authors have created a highly sensitive protein microarray using the principle of single-molecule counting for signal amplification, capable of simultaneously detecting a panel of cancer biomarkers at sub-pg/mL levels. To enable this amplification strategy, the authors introduce a novel method of protein patterning using photolithography to subdivide addressable arrays of capture antibody spots into hundreds of thousands of individual microwells. This allows for the total sensor area to be miniaturized, increasing the total possible multiplex capacity. With the immunoassay realized on a standard 75x25 mm form factor glass substrate, sample volume consumption is minimized to <10 µL, making the technology highly efficient and cost-effective. Additionally, the authors demonstrate the power of their technology by measuring six secretory factors related to glioma tumor progression in a cohort of mice. This highly sensitive, sample-sparing multiplex immunoassay paves the way for researchers to track changes in protein profiles over time, leading to earlier disease detection and discovery of more effective treatment using animal models.

A tissue chip with integrated digital immunosensors: In situ brain endothelial barrier cytokine secretion monitoring.

Organ-on-a-chip platforms have potential to offer more cost-effective, ethical, and human-resembling models than animal models for disease study and drug discovery. Particularly, the Blood-Brain-Barrier-on-a-chip (BBB-oC) has emerged as a promising tool to investigate several neurological disorders since it promises to provide a model of the multifunctional tissue working as an important node to control pathogen entry, drug delivery and neuroinflammation. A comprehensive understanding of the multiple physiological functions of the tissue model requires biosensors detecting several tissue-secreted substances in a BBB-oC system. However, current sensor-integrated BBB-oC platforms are only available for tissue membrane integrity characterization based on permeability measurement. Protein secretory pathways are closely associated with the tissue's various diseased conditions. At present, no biosensor-integrated BBB-oC platform exists that permits in situ tissue protein secretion analysis over time, which prohibits researchers from fully understanding the time-evolving pathology of a tissue barrier. Herein, the authors present a platform named "Digital Tissue-BArrier-CytoKine-counting-on-a-chip (DigiTACK)," which integrates digital immunosensors into a tissue chip system and demonstrates on-chip multiplexed, ultrasensitive, longitudinal cytokine secretion profiling of cultured brain endothelial barrier tissues. The integrated digital sensors utilize a novel beadless microwell format to perform an ultrafast "digital fingerprinting" of the analytes while achieving a low limit of detection (LoD) around 100-500 fg/mL for mouse MCP1 (CCL2), IL-6 and KC (CXCL1). The DigiTACK platform is extensively applicable to profile temporal cytokine secretion of other barrier-related organ-on-a-chip systems and can provide new insight into the secretory dynamics of the BBB by sequentially controlled experiments.

Ultrathin Two-Dimensional Bimetal-Organic Framework Nanosheets as High-Performance Electrocatalysts for Benzyl Alcohol Oxidation.

Ultrathin two-dimensional metal-organic frameworks (2D MOFs) have the potential to improve the oxidation of benzyl alcohol (BA) with a large surface area and open catalytic active sites. To achieve high-efficiency electrocatalysts for the oxidation of benzyl alcohol, a moderate solvothermal method was evolved to synthesize a series of 2D MOFs on nickel foam (Ni-MOF/NF, NiCo-61-MOF/NF, NiCo-21-MOF/NF). As the electrocatalyst used for the oxidation of benzyl alcohol, NiCo-61-MOF/NF presented a lower overpotential and superior chemical durability than other electrocatalysts; it only required a potential of ∼1.52 V (vs RHE) to reach 338.16 mA cm-2, with an oxidation efficiency of more than 86%. Besides, after continuous electrocatalysis for 20 000 s at 1.42 V (vs RHE), the current density of NiCo-61-MOF/NF nanosheets was still 38.67 mA cm-2 with 77.34% retention. This demonstrated that NiCo-61-MOF/NF nanosheet electrocatalysts had great potential for benzyl alcohol oxidation. From both the experimental and theoretical studies, it was discovered that NiCo-61-MOF/NF nanosheets have the highest electrocatalytic activity due to their distinctive ultrathin 2D structure, optimized electron structure, and more accessible active sites. This finding would pave a brand-new thought for the design of electrocatalysts with electrocatalytic activity for benzyl alcohol oxidation (EBO).

Determination of meloxicam in human plasma by ultra-high-performance liquid chromatography-tandem mass spectrometry and its application in a pharmacokinetic study.

A rapid, selective and sensitive ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method was developed to detect meloxicam in human plasma. A triple quadrupole tandem mass spectrometer equipped with an electrospray ionization source was used in positive ion mode. Protein precipitation with acetonitrile was used for sample preparation. Meloxicam and 13 C6 -meloxicam internal standard were analyzed on an Acquity CSH C18 column with a mobile phase of acetonitrile and water in 0.1% formic acid using a gradient program for separation. The retention time of meloxicam was 1.1 min and the total run time was only 2.0 min. Detection was performed in multiple reaction monitoring mode using an electrospray ionization source with optimized mass spectrometry parameters. The calibration curves were linear in the range 10.0-3.00 × 103 ng/ml (r ≥ 0.99). The within-run and between-run RSDs were ≤14.8%. The within-run and between-run REs ranged from -4.6 to 10.7%. There was no significant matrix effect, and the recovery rate was high. This method was fully validated, including reinjection reproducibility in human plasma. The method was applied to the pharmacokinetic study. All of the incurred sample reanalysis methods met the criteria.

Machine-Learning-Assisted Microfluidic Nanoplasmonic Digital Immunoassay for Cytokine Storm Profiling in COVID-19 Patients.

Cytokine storm, known as an exaggerated hyperactive immune response characterized by elevated release of cytokines, has been described as a feature associated with life-threatening complications in COVID-19 patients. A critical evaluation of a cytokine storm and its mechanistic linkage to COVID-19 requires innovative immunoassay technology capable of rapid, sensitive, selective detection of multiple cytokines across a wide dynamic range at high-throughput. In this study, we report a machine-learning-assisted microfluidic nanoplasmonic digital immunoassay to meet the rising demand for cytokine storm monitoring in COVID-19 patients. Specifically, the assay was carried out using a facile one-step sandwich immunoassay format with three notable features: (i) a microfluidic microarray patterning technique for high-throughput, multiantibody-arrayed biosensing chip fabrication; (ii) an ultrasensitive nanoplasmonic digital imaging technology utilizing 100 nm silver nanocubes (AgNCs) for signal transduction; (iii) a rapid and accurate machine-learning-based image processing method for digital signal analysis. The developed immunoassay allows simultaneous detection of six cytokines in a single run with wide working ranges of 1-10,000 pg mL-1 and ultralow detection limits down to 0.46-1.36 pg mL-1 using a minimum of 3 µL serum samples. The whole chip can afford a 6-plex assay of 8 different samples with 6 repeats in each sample for a total of 288 sensing spots in less than 100 min. The image processing method enhanced by convolutional neural network (CNN) dramatically shortens the processing time ∼6,000 fold with a much simpler procedure while maintaining high statistical accuracy compared to the conventional manual counting approach. The immunoassay was validated by the gold-standard enzyme-linked immunosorbent assay (ELISA) and utilized for serum cytokine profiling of COVID-19 positive patients. Our results demonstrate the nanoplasmonic digital immunoassay as a promising practical tool for comprehensive characterization of cytokine storm in patients that holds great promise as an intelligent immunoassay for next generation immune monitoring.

Ocean acidification exacerbates copper toxicity in both juvenile and adult stages of the green tide alga Ulva linza.

The toxicity of heavy metals to coastal organisms can be modulated by changes in pH due to progressive ocean acidification (OA). We investigated the combined impacts of copper and OA on different stages of the green macroalga Ulva linza, which is widely distributed in coastal waters, by growing the alga under the addition of Cu (control, 0.125 (medium, MCu), and 0.25 (high) µM, HCu) and elevated pCO2 of 1,000 µatm, predicted in the context of global change. The relative growth rates decreased significantly in both juvenile and adult thalli at HCu under OA conditions. The net photosynthetic and respiration rates, as well as the relative electron transfer rates for the adult thalli, also decreased under the combined impacts of HCu and OA, although no significant changes in the contents of photosynthetic pigments were detected. Our results suggest that Cu and OA act synergistically to reduce the growth and photosynthetic performance of U. linza, potentially prolonging its life cycle.

Ultrasensitive Multiparameter Phenotyping of Rare Cells Using an Integrated Digital-Molecular-Counting Microfluidic Well Plate.

Integrated microfluidic cellular phenotyping platforms provide a promising means of studying a variety of inflammatory diseases mediated by cell-secreted cytokines. However, immunosensors integrated in previous microfluidic platforms lack the sensitivity to detect small signals in the cellular secretion of proinflammatory cytokines with high precision. This limitation prohibits researchers from studying cells secreting cytokines at low abundance or existing at a small population. Herein, the authors present an integrated platform named the "digital Phenoplate (dPP)," which integrates digital immunosensors into a microfluidic chip with on-chip cell assay chambers, and demonstrates ultrasensitive cellular cytokine secretory profile measurement. The integrated sensors yield a limit of detection as small as 0.25 pg mL-1 for mouse tumor necrosis factor alpha (TNF-α). Each on-chip cell assay chamber confines cells whose population ranges from ≈20 to 600 in arrayed single-cell trapping microwells. Together, these microfluidic features of the dPP simultaneously permit precise counting and image-based cytometry of individual cells while performing parallel measurements of TNF-α released from rare cells under multiple stimulant conditions for multiple samples. The dPP platform is broadly applicable to the characterization of cellular phenotypes demanding high precision and high throughput.

Machine learning-based cytokine microarray digital immunoassay analysis.

Serial measurement of a large panel of protein biomarkers near the bedside could provide a promising pathway to transform the critical care of acutely ill patients. However, attaining the combination of high sensitivity and multiplexity with a short assay turnaround poses a formidable technological challenge. Here, the authors develop a rapid, accurate, and highly multiplexed microfluidic digital immunoassay by incorporating machine learning-based autonomous image analysis. The assay has achieved 12-plexed biomarker detection in sample volume <15 µL at concentrations < 5 pg/mL while only requiring a 5-min assay incubation, allowing for all processes from sampling to result to be completed within 40 min. The assay procedure applies both a spatial-spectral microfluidic encoding scheme and an image data analysis algorithm based on machine learning with a convolutional neural network (CNN) for pre-equilibrated single-molecule protein digital counting. This unique approach remarkably reduces errors facing the high-capacity multiplexing of digital immunoassay at low protein concentrations. Longitudinal data obtained for a panel of 12 serum cytokines in human patients receiving chimeric antigen receptor-T (CAR-T) cell therapy reveals the powerful biomarker profiling capability. The assay could also be deployed for near-real-time immune status monitoring of critically ill COVID-19 patients developing cytokine storm syndrome.

Early prediction of mortality risk among patients with severe COVID-19, using machine learning.

BACKGROUND: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 infection, has been spreading globally. We aimed to develop a clinical model to predict the outcome of patients with severe COVID-19 infection early. METHODS: Demographic, clinical and first laboratory findings after admission of 183 patients with severe COVID-19 infection (115 survivors and 68 non-survivors from the Sino-French New City Branch of Tongji Hospital, Wuhan) were used to develop the predictive models. Machine learning approaches were used to select the features and predict the patients' outcomes. The area under the receiver operating characteristic curve (AUROC) was applied to compare the models' performance. A total of 64 with severe COVID-19 infection from the Optical Valley Branch of Tongji Hospital, Wuhan, were used to externally validate the final predictive model. RESULTS: The baseline characteristics and laboratory tests were significantly different between the survivors and non-survivors. Four variables (age, high-sensitivity C-reactive protein level, lymphocyte count and d-dimer level) were selected by all five models. Given the similar performance among the models, the logistic regression model was selected as the final predictive model because of its simplicity and interpretability. The AUROCs of the external validation sets were 0.881. The sensitivity and specificity were 0.839 and 0.794 for the validation set, when using a probability of death of 50% as the cutoff. Risk score based on the selected variables can be used to assess the mortality risk. The predictive model is available at [https://phenomics.fudan.edu.cn/risk_scores/]. CONCLUSIONS: Age, high-sensitivity C-reactive protein level, lymphocyte count and d-dimer level of COVID-19 patients at admission are informative for the patients' outcomes.

A digital protein microarray for COVID-19 cytokine storm monitoring.

Despite widespread concern regarding cytokine storms leading to severe morbidity in COVID-19, rapid cytokine assays are not routinely available for monitoring critically ill patients. We report the clinical application of a digital protein microarray platform for rapid multiplex quantification of cytokines from critically ill COVID-19 patients admitted to the intensive care unit (ICU) at the University of Michigan Hospital. The platform comprises two low-cost modules: (i) a semi-automated fluidic dispensing/mixing module that can be operated inside a biosafety cabinet to minimize the exposure of the technician to the virus infection and (ii) a 12-12-15 inch compact fluorescence optical scanner for the potential near-bedside readout. The platform enabled daily cytokine analysis in clinical practice with high sensitivity (<0.4 pg mL-1), inter-assay repeatability (∼10% CV), and rapid operation providing feedback on the progress of therapy within 4 hours. This test allowed us to perform serial monitoring of two critically ill patients with respiratory failure and to support immunomodulatory therapy using the selective cytopheretic device (SCD). We also observed clear interleukin-6 (IL-6) elevations after receiving tocilizumab (IL-6 inhibitor) while significant cytokine profile variability exists across all critically ill COVID-19 patients and to discover a weak correlation between IL-6 to clinical biomarkers, such as ferritin and C-reactive protein (CRP). Our data revealed large subject-to-subject variability in patients' response to COVID-19, reaffirming the need for a personalized strategy guided by rapid cytokine assays.

Rapid single-molecule digital detection of protein biomarkers for continuous monitoring of systemic immune disorders.

Digital protein assays have great potential to advance immunodiagnostics because of their single-molecule sensitivity, high precision, and robust measurements. However, translating digital protein assays to acute clinical care has been challenging because it requires deployment of these assays with a rapid turnaround. Herein, we present a technology platform for ultrafast digital protein biomarker detection by using single-molecule counting of immune-complex formation events at an early, pre-equilibrium state. This method, which we term "pre-equilibrium digital enzyme-linked immunosorbent assay" (PEdELISA), can quantify a multiplexed panel of protein biomarkers in 10 µL of serum within an unprecedented assay incubation time of 15 to 300 seconds over a 104 dynamic range. PEdELISA allowed us to perform rapid monitoring of protein biomarkers in patients manifesting post-chimeric antigen receptor T-cell therapy cytokine release syndrome, with ∼30-minute sample-to-answer time and a sub-picograms per mL limit of detection. The rapid, sensitive, and low-input volume biomarker quantification enabled by PEdELISA is broadly applicable to timely monitoring of acute disease, potentially enabling more personalized treatment.

Treatment of Cytokine Storm in COVID-19 Patients With Immunomodulatory Therapy.

Observational evidence suggests that excessive inflammation with cytokine storm may play a critical role in development of acute respiratory distress syndrome (ARDS) in COVID-19. We report the emergency use of immunomodulatory therapy utilizing an extracorporeal selective cytopheretic device (SCD) in two patients with elevated serum interleukin (IL)-6 levels and refractory COVID-19 ARDS requiring extracorporeal membrane oxygenation (ECMO). The two patients were selected based on clinical criteria and elevated levels of IL-6 (>100 pg/ml) as a biomarker of inflammation. Once identified, emergency/expanded use permission for SCD treatment was obtained and patient consented. Six COVID-19 patients (four on ECMO) with severe ARDS were also screened with IL-6 levels less than 100 pg/ml and were not treated with SCD. The two enrolled patients' PaO2/FiO2 ratios increased from 55 and 58 to 200 and 192 at 52 and 50 hours, respectively. Inflammatory indices also declined with IL-6 falling from 231 and 598 pg/ml to 3.32 and 116 pg/ml, respectively. IL-6/IL-10 ratios also decreased from 11.8 and 18 to 0.7 and 0.62, respectively. The two patients were successfully weaned off ECMO after 17 and 16 days of SCD therapy, respectively. The results observed with SCD therapy on these two critically ill COVID-19 patients with severe ARDS and elevated IL-6 is encouraging. A multicenter clinical trial is underway with an FDA-approved investigational device exemption to evaluate the potential of SCD therapy to effectively treat COVID-19 intensive care unit patients.

A Digital Protein Microarray for COVID-19 Cytokine Storm Monitoring.

Despite widespread concern for cytokine storms leading to severe morbidity in COVID-19, rapid cytokine assays are not routinely available for monitoring critically ill patients. We report the clinical application of a machine learning-based digital protein microarray platform for rapid multiplex quantification of cytokines from critically ill COVID-19 patients admitted to the intensive care unit (ICU) at the University of Michigan Hospital. The platform comprises two low-cost modules: (i) a semi-automated fluidic dispensing/mixing module that can be operated inside a biosafety cabinet to minimize the exposure of technician to the virus infection and (ii) a 12-12-15 inch compact fluorescence optical scanner for the potential near-bedside readout. The platform enabled daily cytokine analysis in clinical practice with high sensitivity (<0.4pg/mL), inter-assay repeatability (~10% CV), and near-real-time operation with a 10 min assay incubation. A cytokine profiling test with the platform allowed us to observe clear interleukin-6 (IL-6) elevations after receiving tocilizumab (IL-6 inhibitor) while significant cytokine profile variability exists across all critically ill COVID-19 patients and to discover a weak correlation between IL-6 to clinical biomarkers, such as Ferritin and CRP. Our data revealed large subject-to-subject variability in a patient's response to anti-inflammatory treatment for COVID-19, reaffirming the need for a personalized strategy guided by rapid cytokine assays.

An Integrated Plasmo-Photoelectronic Nanostructure Biosensor Detects an Infection Biomarker Accompanying Cell Death in Neutrophils.

Bacterial infections leading to sepsis are a major cause of deaths in the intensive care unit. Unfortunately, no effective methods are available to capture the early onset of infectious sepsis near the patient with both speed and sensitivity required for timely clinical treatment. To fill the gap, the authors develop a highly miniaturized (2.5 × 2.5 µm2 ) plasmo-photoelectronic nanostructure device that detected citrullinated histone H3 (CitH3), a biomarker released to the blood circulatory system by neutrophils. Rapidly detecting CitH3 with high sensitivity has the great potential to prevent infections from developing life-threatening septic shock. To this end, the author's device incorporates structurally engineered arrayed hemispherical gold nanoparticles that are functionalized with high-affinity antibodies. A nanoplasmonic resonance shift induces a photoconduction increase in a few-layer molybdenum disulfide (MoS2 ) channel, and it provides the sensor signal. The device achieves label-free detection of serum CitH3 with a 5-log dynamic range from 10-4 to 101 ng mL and a sample-to-answer time <20 min. Using this biosensor, the authors longitudinally measure the dynamic CitH3 profiles of individual living mice in a sepsis model at high resolution over 12 hours. The developed biosensor may be poised for future translation to personalized management of systemic bacterial infections.

Mass-producible microporous silicon membranes for specific leukocyte subset isolation, immunophenotyping, and personalized immunomodulatory drug screening in vitro.

Widespread commercial and clinical adaptation of biomedical microfluidic technology has been limited in large part due to the lack of mass producibility of polydimethylsiloxane (PDMS) and glass-based devices commonly as reported in the literature. Here, we present a batch-fabricated, robust, and mass-producible immunophenotyping microfluidic device using silicon micromachining processes. Our Si and glass-based microfluidic device, named the silicon microfluidic immunophenotyping assay (SiMIPA), consists of a highly porous (∼40%) silicon membrane that can selectively separate microparticles below a certain size threshold. The device is capable of isolating and stimulating specific leukocyte populations, and allows for measuring their secretion of cell signaling proteins by means of a no-wash homogeneous chemiluminescence-based immunoassay. The high manufacturing throughput (∼170 devices per wafer) makes a large quantity of SiMIPA chips readily available for clinically relevant applications, which normally require large dataset acquisitions for statistical accuracy. With 30 SiMIPA chips, we performed in vitro immunomodulatory drug screening on isolated leukocyte subsets, yielding 5 data points at 6 drug concentrations. Furthermore, the excellent structural integrity of the device allowed for samples and reagents to be loaded using a micropipette, greatly simplifying the experimental protocol.

Cyclewise Operation of Printed MoS2 Transistor Biosensors for Rapid Biomolecule Quantification at Femtomolar Levels.

Field-effect transistors made from MoS2 and other emerging layered semiconductors have been demonstrated to be able to serve as ultrasensitive biosensors. However, such nanoelectronic sensors still suffer seriously from a series of challenges associated with the poor compatibility between electronic structures and liquid analytes. These challenges hinder the practical biosensing applications that demand rapid, low-noise, highly specific biomolecule quantification at femtomolar levels. To address such challenges, we study a cyclewise process for operating MoS2 transistor biosensors, in which a series of reagent fluids are delivered to the sensor in a time-sequenced manner and periodically set the sensor into four assay-cycle stages, including incubation, flushing, drying, and electrical measurement. Running multiple cycles of such an assay can acquire a time-dependent sensor response signal quantifying the reaction kinetics of analyte-receptor binding. This cyclewise detection approach can avoid the liquid-solution-induced electrochemical damage, screening, and nonspecific adsorption to the sensor and therefore improves the transistor sensor's durability, sensitivity, specificity, and signal-to-noise ratio. These advantages in combination with the inherent high sensitivity of MoS2 biosensors allow for rapid biomolecule quantification at femtomolar levels. We have demonstrated the cyclewise quantification of Interleukin-1ß in pure and complex solutions (e.g., serum and saliva) with a detection limit of ∼1 fM and a total detection time ∼23 min. This work leverages the superior properties of layered semiconductors for biosensing applications and advances the techniques toward realizing fast real-time immunoassay for low-abundance biomolecule detection.

Biotunable Nanoplasmonic Filter on Few-Layer MoS2 for Rapid and Highly Sensitive Cytokine Optoelectronic Immunosensing.

Monitoring of the time-varying immune status of a diseased host often requires rapid and sensitive detection of cytokines. Metallic nanoparticle-based localized surface plasmon resonance (LSPR) biosensors hold promise to meet this clinical need by permitting label-free detection of target biomolecules. These biosensors, however, continue to suffer from relatively low sensitivity as compared to conventional immunoassay methods that involve labeling processes. Their response speeds also need to be further improved to enable rapid cytokine quantification for critical care in a timely manner. In this paper, we report an immunobiosensing device integrating a biotunable nanoplasmonic optical filter and a highly sensitive few-layer molybdenum disulfide (MoS2) photoconductive component, which can serve as a generic device platform to meet the need of rapid cytokine detection with high sensitivity. The nanoplasmonic filter consists of anticytokine antibody-conjugated gold nanoparticles on a SiO2 thin layer that is placed 170 µm above a few-layer MoS2 photoconductive flake device. The principle of the biosensor operation is based on tuning the delivery of incident light to the few-layer MoS2 photoconductive flake thorough the nanoplasmonic filter by means of biomolecular surface binding-induced LSPR shifts. The tuning is dependent on cytokine concentration on the nanoplasmonic filter and optoelectronically detected by the few-layer MoS2 device. Using the developed optoelectronic biosensor, we have demonstrated label-free detection of IL-1ß, a pro-inflammatory cytokine, with a detection limit as low as 250 fg/mL (14 fM), a large dynamic range of 106, and a short assay time of 10 min. The presented biosensing approach could be further developed and generalized for point-of-care diagnosis, wearable bio/chemical sensing, and environmental monitoring.

AC Electroosmosis-Enhanced Nanoplasmofluidic Detection of Ultralow-Concentration Cytokine.

Label-free, nanoparticle-based plasmonic optical biosensing, combined with device miniaturization and microarray integration, has emerged as a promising approach for rapid, multiplexed biomolecular analysis. However, limited sensitivity prevents the wide use of such integrated label-free nanoplasmonic biosensors in clinical and life science applications where low-abundance biomolecule detection is needed. Here, we present a nanoplasmofluidic device integrated with microelectrodes for rapid, label-free analysis of a low-abundance cell signaling protein, detected by AC electroosmosis-enhanced localized surface plasmon resonance (ACE-LSPR) biofunctional nanoparticle imaging. The ACE-LSPR device is constructed using both bottom-up and top-down sensor fabrication methods, allowing the seamless integration of antibody-conjugated gold nanorod (AuNR) biosensor arrays with microelectrodes on the same microfluidic platform. Applying an AC voltage to microelectrodes while scanning the scattering light intensity variation of the AuNR biosensors results in significantly enhanced biosensing performance. The AC electroosmosis (ACEO) based enhancement of the biosensor performance enables rapid (5-15 min) quantification of IL-1ß, a pro-inflammatory cytokine biomarker, with a sensitivity down to 158.5 fg/mL (9.1 fM) for spiked samples in PBS and 1 pg/mL (58 fM) for diluted human serum. Together with the optimized detection sensitivity and speed, our study presents the first critical step toward the application of nanoplasmonic biosensing technology to immune status monitoring guided by low-abundance cytokine measurement.