Response Of Complex System Research Articles

Closing the geologic carbon cycle

Estimates of sedimentary organic carbon burial fluxes based on inventory and isotope mass balance methods have been divergent. A new calculation of the isotope mass balance using a revised assessment of the inputs to the ocean-atmosphere system resolves the apparent discrepancy. Inputs include weathering of carbonate and old kerogen, geogenic methane oxidation, and volcanic and metamorphic degassing. Volcanic and metamorphic degassing comprise ≈23% of the total C input. Inputs from isotopically light OCpetro and CH4-geo drive the mean δ13C of the input to =-8.0 ± 1.9‰, notably lower than the commonly assumed volcanic degassing value. The isotope mass balance model yields a modern burial flux =15.9 ± 6.6 Tmol y-1. The impact of the mid-Miocene Climatic Optimum isotope anomaly is an integrated excess deposition ≈ 4.3 × 106 Tmol between 18 and 11 Ma, which is both longer and larger than estimates for the total degassing by the Columbia River Basalt eruptions, implying a complex carbon system response to large eruptive events. Monte Carlo evaluation finds that late Cenozoic net growth of the carbonate reservoir is very likely while net growth of the Corg reservoir is less certain but more likely than not. At present, subduction does not appear to keep up with net sedimentation and the overall masses of sedimentary carbonate and organic carbon are likely increasing. Growth in the sedimentary Corg reservoir implies oxidation of the surface environment and likely increases in atmospheric pO2.

The transcriptional integration of environmental cues with root cell type development.

Plant roots navigate the soil ecosystem with each cell type uniquely responding to environmental stimuli. Below ground, the plant's response to its surroundings is orchestrated at the cellular level, including morphological and molecular adaptations that shape root system architecture as well as tissue and organ functionality. Our understanding of the transcriptional responses at cell type resolution has been profoundly enhanced by studies of the model plant Arabidopsis thaliana. However, both a comprehensive view of the transcriptional basis of these cellular responses to single and combinatorial environmental cues in diverse plant species remains elusive. In this review, we highlight the ability of root cell types to undergo specific anatomical or morphological changes in response to abiotic and biotic stresses or cues and how they collectively contribute to the plant's overall physiology. We further explore interconnections between stress and the temporal nature of developmental pathways and discuss examples of how this transcriptional reprogramming influences cell type identity and function. Finally, we highlight the power of single-cell and spatial transcriptomic approaches to refine our understanding of how environmental factors fine tune root spatiotemporal development. These complex root system responses underscore the importance of spatiotemporal transcriptional mapping, with significant implications for enhanced agricultural resilience.

Nonparametric identification of multi-degree-of-freedom nonlinear systems from partially measured responses under uncertain dynamic excitations

With the rapid advent of new materials and novel structures, it becomes difficult, if not impossible, to accurately model and simulate the nonlinear response of complex systems under uncertain dynamic excitations based on close-formed nonlinear functions and parametric identification. In this study, a two-step structural nonlinearity localization and identification approach for multi-degree-of-freedom (MDOF) nonlinear systems under uncertain dynamic excitations is developed by integrating an extended Kalman filter with unknown inputs into the equivalent linearized systems. In the first step, unmeasured responses and excitations are estimated as well as unknown structural parameters and nonlinearity locations are identified by fusing acceleration with displacement time histories at the observed degrees of freedom (DOFs). In the second step, the nonlinear restoring force of the detected nonlinear structural members is identified nonparametrically using three polynomial models, including a power series polynomial model (PSPM), a double Chebyshev polynomial model (DCPM), and a Legendre polynomial model (LPM). Linear multi-story shear frames controlled by nonlinear magnetorheological (MR) dampers are modelled computationally to demonstrate the generality of the proposed methodology. The multi-source uncertainties considered in these representative examples include the location and the type of nonlinearities represented by a Bingham model and a modified Dahl model of the dampers, the location of response measurements, the location and intensity of dynamic excitations, the level of measurement noise, and the initial assignment of structural parameters. The acceleration, velocity, and displacement time histories of structures can be evaluated accurately with a maximum error of 2.62% even with the presence of 8% measurement noise, while the external excitations can be estimated within an error of 1.77%. The location of nonlinear elements can be detected correctly. The structural parameters, the NRFs provided by MR dampers and the corresponding energy dissipation can be identified with a maximum error of 2.08%, 1.19% and 0.39%, respectively, even 8% measurement noise and very rough initial assignment of structure parameters (−70%) are considered. Moreover, the numerical results change little (<0.20%) even the initial assignment of structural parameters varies from 50% to 30% of their original values, no matter which nonparametric model is employed. Results indicate that the presented algorithm can effectively identify unmeasured dynamic responses, structural parameters, unknown excitations, nonlinear locations, and NRF of nonlinear elements in a nonparametric way.

Influence of Local Thermodynamic Non-Equilibrium to Photothermally Induced Acoustic Response of Complex Systems

In this paper, the time-resolved model of the photoacoustic signal for samples with a complex inner structure is derived including local non-equilibrium of structural elements with multiple degrees of freedom, i.e., structural entropy of the system. The local non-equilibrium is taken into account through the fractional operator. By analyzing the model for two types of time-dependent excitation, a very short pulse and a very long pulse, it is shown that the rates of non-equilibrium relaxations in complex samples can be measured by applying the derived model and time-domain measurements. Limitations of the model and further directions of its development are discussed.

Selectively cross-linked hydrogel-based cocktail drug delivery micro-chip for colon cancer combinatorial drug screening using AI-CSR platform for precision medicine.

Cancer, ranked as the second leading cause of global mortality with a prevalence of 1 in 6 deaths, necessitates innovative approaches for effective treatment. Combinatorial drug therapy for cancer treatment targets several key pathways simultaneously and potentially enhances anti-cancer efficacy without intolerable side effects. However, it demands precise and accurate control of drug-dose combinations and their release. In this study, we demonstrated a selectively cross-linked hydrogel-based platform that can quantify and release drugs simultaneously for in-parallel cocktail drug screening. PDMS was used as the flow channel substrate and the poly (ethylene glycol) diacrylate (PEGDA) hydrogel array was formed by UV exposure using the photomask. Employing our platform, cocktails of anticancer drugs are precisely loaded and simultaneously released in-parallel into HCT-116 colon cancer cells, facilitating combinatorial drug screening. The integration of an artificial intelligence-based complex system response (AI-CSR) platform successfully identifies optimal drug-dose combinations from a pool of ten approved drugs. Notably, our cocktail drug chip demonstrates exceptional efficiency, screening 155 drug-dose combinations within a brief two and a half hours, a marked improvement over traditional methods. Furthermore, the device exhibits low drug consumption, requiring a mere 1 μL per patch of chip. Thus, our developed PDMS drug-loaded hydrogel platform presents a novel and expedited approach to quantifying drug concentrations, promising to be a faster, efficient and more precise approach for conducting cocktail drug screening experiments.

Vibro-Acoustic Responses and Pressure Signal Analysis for Early Surge Detection in a Turbocharger Compressor

Abstract High-speed centrifugal compressors may be exploited to pressurize fuel cell systems. Nonetheless, due to fuel cells significant interposed volumes, compressor behavior can lead to severe vibrations related to fluid-dynamic instabilities during part load operating conditions. In particular, surge strongly limits centrifugal compressors stable operating region when moving toward low mass flow rates due to a change in system working point. Therefore, compressor dynamic response must be adequately characterized for early surge detection. To this aim, a dedicated experimental activity was conducted on a vaneless diffuser turbocharger coupled to a solid oxide fuel cell emulator plant; compressor evolution toward surge was investigated. Several signal processing techniques were applied to pressure signals as well as vibro-acoustic responses to better predict compressor behavior and classify its status as stable or unstable. Cepstrum, cross-correlation, and wavelet transform have been identified as suitable techniques to define precursors able to early detect surge. By means of cross-correlation function, propagation phenomena in the ducts can be investigated to assess how they interact near compressor low-mass flowrate unstable conditions. Cepstrum provides a convenient way to determine pressure signal spectrum distortion in terms of further periodic components onset. These harmonic components are due to complex system responses generated by transient phenomena; indeed, cepstrum allows to identify hidden anomalous contributions in system response spectra which may arise in incipient surge conditions. Wavelet transform was performed on both structural and pressure response signals to observe their dominant energy contents temporal evolution; indeed, such spectral pattern time-dependent variation can detect the rise of unstable conditions. By exploiting all these techniques, a complete system identification is performed which allows a deeper investigation of the physical phenomena involved; moreover, a more complete set of surge precursors extracted from different probes' physical signals were defined. The results obtained provide original diagnostic insights for monitoring systems suited to perform early surge detection. Compressor instability prevention can extend its operating range, performance, and reliability to allow better integration with other plant components. Finally, cepstrum application for compressor instability identification can be regarded as a novel method in the fluid machinery field.

QuDPy: A Python-based tool for computing ultrafast non-linear optical responses

Nonlinear Optical Spectroscopy is a well-developed field with theoretical and experimental advances that have benefited multiple disciplines, including chemistry, biology, and physics. However, for the accurate interpretation of the corresponding multi-dimensional spectra, there is a need for precise quantum dynamical simulations based on model Hamiltonians. In this article, we present the initial release of our code, QuDPy (Quantum Dynamics in Python), which provides a robust numerical platform for performing quantum dynamics simulations based on model systems, including open quantum systems. A distinguishing feature of our approach is the ability to specify various high-order optical response pathways in the form of double-sided Feynman diagrams through a straightforward input syntax. This syntax outlines the time-ordering of ket-sided or bra-sided optical interactions acting on the time-evolving density matrix of the system. We utilize the quantum dynamics capabilities of QuTip to simulate the spectral response of complex systems, allowing us to compute virtually any n-th order optical response of the model system. To illustrate the utility of our approach, we provide a series of example calculations. Program summaryProgram Title:QuDPyCPC Library link to program files:https://doi.org/10.17632/5xm9pm24cz.1Developer's repository link:https://github.com/sa-shah/QuDPyLicensing provisions: MIT LicenseProgramming language: Python (v3.7)Supplementary material: Available as Google Colab Files.Example 1: https://tinyurl.com/y3j5jmmrExample 2: https://tinyurl.com/37vwntn5External packages:•QuTip (v.4.7) and dependencies i.e. Numpy, Matplotlib (https://qutip.org/)•UFSS Automatic Diagram Generator (https://github.com/peterarose/ufss)Nature of problem: Accurate quantum simulations of complex systems are required in order to understand and interpret multi-dimensional ultrafast spectroscopic signals. This code provides an open-source/multi-platform method that facilitates the generation of higher-order non-linear optical responses for an arbitrary molecular or material system given a model input Hamiltonian and bath model.Solution method: We use the double-sided Feynman diagram method [1, 2] to generate (symbolically) a set of response functions corresponding to the nth order non-linear response of the system to a series of laser pulses using the UFSS package [3] We then perform a series of accurate quantum dynamics calculations using the QuTip package [4] to generate the numerical response and spectra which correspond to specific experimental conditions.

Predicting the response of complex systems for coastal management

Predicting the response of complex systems for coastal management

723 Provincial Burn Mass Casualty Incident Planning: Preliminary Results

Abstract Introduction Burn mass casualty incident (BMCI) response planning includes involving relevant stakeholders, assessing regional burn care capacity, and addressing the specialized needs of burn patients. An essential component of these processes is an evaluation of existing resources and plans. In this study, a province with three important elements—a singular health authority to plan for, two burn centres, and updated health technology—was selected for evaluation. Aim What are the current policies, protocols, and practices that address a provincial response to a BMCI? Methods In this ethics approved case study, qualitative description methodology was used for data analysis. Data were gathered from documents outlining the health system response to a mass casualty incident from the health system internal emergency response plans. Health care professionals directly involved in the response were recruited for interviews. Participants were recruited from prehospital emergency management services, hospital emergency departments, inpatient burn units, and a provincial patient transport department. Interviews were conducted online, recorded, and transcribed. Qualitative description was used to code common themes across documents and transcripts. Results Thirteen documents and nine participant interviews were included. Only two documents included burn-specific considerations. Current policies and protocols were limited to all-hazards mass casualty incident planning and did not address specialized needs of burn care. Current plans were based on assumptions that all burn patients would be triaged and transported to burn centres and that surge capacity would be adequate to accommodate for increased demands. Prehospital participants (n=3) felt that existing plans would adequately manage a BMCI. Six participants stated the current plans were not sufficient to manage a BMCI. A comprehensive description of the complex health system response to a potential BMCI was obtained. Some major deficiencies identified included a lack of strategies to bolster burn care staffing capacity such as just-in-time training resources for non-burn trained staff or utilization of outpatient burn clinic staff. Considerations for increased operating room and wound care resources were absent. Conclusions Current provincial all hazards response plans are not sufficient to support adequate response to a BMCI and need to be amended to address the specialized needs of burn patients. Strategies for expanding capacity such as care of burn patients at non burn facilities and utilization of outpatient clinics must be integrated into future plans. Applicability of Research to Practice The provincial health authority needs to support BMCI response planning efforts to better address this unique hazard prior to an incident occurring for best patient outcomes.

Intervention of Kusuma Milk-Shake Drink on Cervical Dilatation and Duration of Labor: Experience from Bengkulu, Indonesia

Background: Labor processes require energy consumption regulated by a complex nervous system and hormonal response. Thus, the intensity of maternal nutritional intake since pregnancy should be highly considered for physiological delivery. Nutrients that are high in energy and provide fast-decomposing glucose intake should be chosen by the mothers. Kusuma is a kind of drink made from dates, milk, and honey. This study aimed to analyze the effect of Kusuma milk-shake drink implementations on cervical dilatation and duration of labor.Methods: An experimental study was conducted by post-test only with a controlled group design, including 34 mothers with term pregnancy, which was intervention groups and controls. A completely randomized design in two different places was conducted. Data were analyzed using Shapiro-wilk, independent sample T-test, and Mann-Whitney. Results: There was a significant effect of Kusuma milk-shake implementation on cervical dilatation (p=0.000). The dilatation process was found to be 5.5 times faster, and the duration of labor (p=0.000) was observed to be 9.7 hours faster than the control group.Conclusions: Implementation of the Kusuma milk-shake has a significant effect on the acceleration of cervical dilation and the duration of labor. This research is expected to improve the quality of midwifery services as an effort to realize the concept of a Continuum of Obstetric Care.

Biodiversity transformations in the global ocean: A climate change and conservation management perspective.

Understanding the biological diversity of different communities and evaluating the risks to biological sustainability in a time of rapid environmental change is a key challenge for providing an adapting management approach for biodiversity transformations in the ocean linked to human well-being. (Photo credit: Andrea Belgrano).

Porphyrin Functionalized Carbon Quantum Dots for Enhanced Electrochemiluminescence and Sensitive Detection of Cu2.

Porphyrin (TMPyP) functionalized carbon quantum dots (CQDs-TMPyP), a novel and efficient carbon nanocomposite material, were developed as a novel luminescent material, which could be very useful for the sensitive detection of copper ions in the Cu2+ quenching luminescence of functionalized carbon quantum dots. Therefore, we constructed a sensitive "signal off" ECL biosensor for the detection of Cu2+. This sensor can sensitively respond to copper ions in the range of 10 nM to 10 μM, and the detection limit is 2.78 nM. At the same time, it has good selectivity and stability and a benign response in complex systems. With excellent properties, this proposed ECL biosensor provides an efficient and ultrasensitive method for Cu2+ detection.

Novel epidemiological model of gastrointestinal nematode infection to assess grazing cattle resilience by integrating host growth, parasite, grass and environmental dynamics

Gastrointestinal nematode (GIN) infections are ubiquitous and often cause morbidity and reduced performance in livestock. Emerging anthelmintic resistance and increasing change in climate patterns require evaluation of alternatives to traditional treatment and management practices. Mathematical models of parasite transmission between hosts and the environment have contributed towards the design of appropriate control strategies in ruminants, but have yet to account for relationships between climate, infection pressure, immunity, resources, and growth. Here, we develop a new epidemiological model of GIN transmission in a herd of grazing cattle, including host tolerance (body weight and feed intake), parasite burden and acquisition of immunity, together with weather-dependent development of parasite free-living stages, and the influence of grass availability on parasite transmission. Dynamic host, parasite and environmental factors drive a variable rate of transmission. Using literature sources, the model was parametrised for Ostertagia ostertagi, the prevailing pathogenic GIN in grazing cattle populations in temperate climates. Model outputs were validated on published empirical studies from first season grazing cattle in northern Europe. These results show satisfactory qualitative and quantitative performance of the model; they also indicate the model may approximate the dynamics of grazing systems under co-infection by O. ostertagi and Cooperia oncophora, a second GIN species common in cattle. In addition, model behaviour was explored under illustrative anthelmintic treatment strategies, considering impacts on parasitological and performance variables. The model has potential for extension to explore altered infection dynamics as a result of management and climate change, and to optimise treatment strategies accordingly. As the first known mechanistic model to combine parasitic and free-living stages of GIN with host feed-intake and growth, it is well suited to predict complex system responses under non-stationary conditions. We discuss the implications, limitations and extensions of the model, and its potential to assist in the development of sustainable parasite control strategies.

Classification of Terrestrial Lidar Data Directly From Digitized Echo Waveforms

Information derived from full-waveform (FW) data collected by FW laser scanning systems has already been shown to be relevant for point cloud analysis tasks. Relevant waveform attributes to populate the corresponding point’s feature vector are typically provided through a post-processing FW analysis (FWA) technique based on fitting the echo waveform with a parametric function describing the shape and location of the echo pulse in the waveform. Samples of the digitized echo are the primary source for any waveform analysis using parametric functions. On the other hand, for some FW laser scanning systems, describing the complex system response model using a simple parametric function seems challenging or impractical. Earlier studies have shown the potential of waveform’s digital samples as relevant waveform attributes, for point cloud classification. The main goal of this study is to extend earlier experiments on direct exploitation of returned waveform signals collected by a FW terrestrial laser scanning (TLS) system in a built environment for point cloud classification, to multi-return waveform signals. Furthermore, the classification performance on feature vectors containing calibrated waveform attributes, derived from a waveform processing approach performed in real-time by the FW TLS system, is evaluated on multiple-echo waveforms and compared with the classification performance derived from the proposed FW data classification technique. Classification performance derived through the proposed technique demonstrates high information content of raw digitized waveform samples. Results show that feature vectors containing samples of digitized echoes carry more information about physical properties of the target than those containing calibrated waveform attributes.

Identification of COVID-19-Specific Immune Markers Using a Machine Learning Method.

Notably, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a tight relationship with the immune system. Human resistance to COVID-19 infection comprises two stages. The first stage is immune defense, while the second stage is extensive inflammation. This process is further divided into innate and adaptive immunity during the immune defense phase. These two stages involve various immune cells, including CD4+ T cells, CD8+ T cells, monocytes, dendritic cells, B cells, and natural killer cells. Various immune cells are involved and make up the complex and unique immune system response to COVID-19, providing characteristics that set it apart from other respiratory infectious diseases. In the present study, we identified cell markers for differentiating COVID-19 from common inflammatory responses, non-COVID-19 severe respiratory diseases, and healthy populations based on single-cell profiling of the gene expression of six immune cell types by using Boruta and mRMR feature selection methods. Some features such as IFI44L in B cells, S100A8 in monocytes, and NCR2 in natural killer cells are involved in the innate immune response of COVID-19. Other features such as ZFP36L2 in CD4+ T cells can regulate the inflammatory process of COVID-19. Subsequently, the IFS method was used to determine the best feature subsets and classifiers in the six immune cell types for two classification algorithms. Furthermore, we established the quantitative rules used to distinguish the disease status. The results of this study can provide theoretical support for a more in-depth investigation of COVID-19 pathogenesis and intervention strategies.

Right ventricular strain related to pulmonary artery pressure predicts clinical outcome in patients with pulmonary arterial hypertension.

In pulmonary arterial hypertension (PAH), the right ventricle (RV) is exposed to an increased afterload. In response, RV mechanics are altered. Markers which would relate RV function and afterload could therefore aid to understand this complex response system and could be of prognostic value. The aim of our study was to (i) assess the RV-arterial coupling using ratio between RV strain and systolic pulmonary artery pressure (sPAP), in patients with PAH, and (ii) investigate the prognostic value of this new parameter over other echocardiographic parameters. Echocardiograms of 65 pre-capillary PAH patients (45 females, age 61 ± 15 years) were retrospectively analysed. Fractional area change (FAC), sPAP, tricuspid annular plane systolic excursion, and RV free-wall (FW) longitudinal strain (LS) were measured. A primary endpoint of death or heart/lung transplantation described clinical endpoint. Patients who reached a clinical endpoint had worse functional capacity (New York Heart Association), reduced RV function, and higher sPAP. Left ventricle function was similar in both groups. Only RVFW LS/sPAP ratio was found as an independent predictor of clinical endpoint in multivariable analysis (hazard ratio 8.3, 95% confidence interval 3.2-21.6, P < 0.001). The RWFW LS/sPAP (cut-off 0.19) demonstrated a good accuracy for the prediction of reaching the clinical endpoint, with a sensitivity of 92% and specificity of 82.5%. RVFW LS/sPAP ratio significantly predicts all-cause mortality and heart-lung transplantation, and was superior to other well-established parameters, in patients with pre-capillary PAH. We therefore propose RVFW LS/sPAP as a new prognostic echocardiographic marker.

The Nutritional Intervention of Resveratrol Can Effectively Alleviate the Intestinal Inflammation Associated With Celiac Disease Induced by Wheat Gluten.

Background and AimsWheat gluten is a critical trigger for celiac disease, often causing inflammatory lesions and oxidative stress damage in the intestines of patients. In daily life, it is difficult for celiac disease patients to strictly avoid the dietary intake of gluten, which makes complementary preventive therapy particularly urgent. As such, we investigated the alleviating effects of resveratrol in vivo and in vitro models of celiac disease.MethodsWe established in vivo and in vitro models of gluten protein-induced celiac disease. The intervention effect of resveratrol was defined well based on relevant indicators of inflammation, immunity and oxidative stress, and its possible involvement in signaling pathways and genes were also identified.ResultsResveratrol was effective in reducing intestinal oxidative stress and inflammatory damage induced by wheat gluten in both cell and mouse models for celiac disease. We identified correlations between the genes (Fgf15, Nr0b2, Aire and Ubd) and signaling pathways (PPAR, AMPK and FoxO) in which resveratrol performed critical roles.ConclusionsResveratrol contributed to regulate development of autoimmunity through up-regulation of Aire and Ubd genes and promote nutrient absorption in intestine through down-regulation of Fgf15 and Nr0b2 genes, as well as played a role in regulating complex response system of oxidative stress, inflammatory response and immune response in intestine by activating PPAR, AMPK and FoxO signaling pathways, thus effectively alleviating the intestinal symptoms of celiac disease.

Ferrofluidic Couette flow in time-varying magnetic field

Despite time-dependent boundary conditions being ubiquitous in natural and industrial flows, to date the influence of such temporal modulations (e.g. with driving frequency ΩH) has been given minor attention. The present problem addresses ferrofluidic Couette flow in between counter-rotating cylinders in a spatially homogeneous magnetic field subject to time-periodic modulation. Such a modulation can lead to a significant inner Reynolds number (Rei) enhancement for both, either helical and toroidal flow structures. Using a modified Niklas approximation, the effect of low- and high-frequency modulation onto the primary instabilities, stability boundaries as well as on the non-linear oscillations that may occur is investigated. Focusing on bi-stable co-existing solutions, around their stability thresholds quite complex non-linear system response and flow dynamics is detected. For the system remaining supercritical always a single solution is selected by ΩH, while crossing the bifurcation thresholds within a modulation period the triggered system response is more complex, reaching from alternation between different solutions towards the appearance of intermittent behavior.

Cell specific peripheral immune responses predict survival in critical COVID-19 patients

SARS-CoV-2 triggers a complex systemic immune response in circulating blood mononuclear cells. The relationship between immune cell activation of the peripheral compartment and survival in critical COVID-19 remains to be established. Here we use single-cell RNA sequencing and Cellular Indexing of Transcriptomes and Epitomes by sequence mapping to elucidate cell type specific transcriptional signatures that associate with and predict survival in critical COVID-19. Patients who survive infection display activation of antibody processing, early activation response, and cell cycle regulation pathways most prominent within B-, T-, and NK-cell subsets. We further leverage cell specific differential gene expression and machine learning to predict mortality using single cell transcriptomes. We identify interferon signaling and antigen presentation pathways within cDC2 cells, CD14 monocytes, and CD16 monocytes as predictors of mortality with 90% accuracy. Finally, we validate our findings in an independent transcriptomics dataset and provide a framework to elucidate mechanisms that promote survival in critically ill COVID-19 patients. Identifying prognostic indicators among critical COVID-19 patients holds tremendous value in risk stratification and clinical management.

Vespakinin-M, a natural peptide from Vespa magnifica, promotes functional recovery in stroke mice

Acute ischemic stroke triggers complex systemic pathological responses for which the exploration of drug resources remains a challenge. Wasp venom extracted from Vespa magnifica (Smith, 1852) is most commonly used to treat rheumatoid arthritis as well as neurological disorders. Vespakinin-M (VK), a natural peptide from wasp venom, has remained largely unexplored for stroke. Herein, we first confirmed the structure, stability, toxicity and distribution of VK as well as its penetration into the blood–brain barrier. VK (150 and 300 µg/kg, i.p.) was administered to improve stroke constructed by middle cerebral artery occlusion in mice. Our results indicate that VK promote functional recovery in mice after ischemia stroke, including an improvement of neurological impairment, reduction of infarct volume, maintenance of blood-brain barrier integrity, and an obstruction of the inflammatory response and oxidative stress. In addition, VK treatment led to reduced neuroinflammation and apoptosis associated with the activation of PI3K–AKT and inhibition of IκBα–NF-κB signaling pathways. Simultaneously, we confirmed that VK can combine with bradykinin receptor 2 (B2R) as detected by molecular docking, the B2R antagonist HOE140 could counteract the neuro-protective effects of VK on stroke in mice. Overall, targeting the VK–B2R interaction can be considered as a practical strategy for stroke therapy.