Global Analysis Research Articles

Global Invasion of Thrips parvispinus (Karny) (Thysanoptera: Thripidae) Across Three Continents Associated With Its One Haplotype

ABSTRACTThrips parvispinus (Karny) is an exotic pest that has invaded many regions around the world in the last three decades. It was first detected in Florida in 2020 on ornamental plants (Hoya and Anthurium) in greenhouses and subsequently on ornamental plants in residential landscapes (Gardenia) in 2021. However, its first report on open vegetable field crops (Capsicum) in Florida was in 2022. We conducted field surveys and genetic analysis to answer three questions: (1) Is the population of T. parvispinus that invaded Florida the same as the one that has spread globally in the last few decades? (2) Is the host expansion to Capsicum in Florida a new population or the extension of the existing population reported on ornamental plants? and (3) What are the native and invaded distribution ranges of T. parvispinus? We analysed the genetic variation in the mitochondrial gene cytochrome oxidase I (COI) to address these questions. The global genetic diversity analysis of T. parvispinus revealed 18 haplotypes (populations) worldwide based on available data, but only one population (Hap1) invaded three continents: Africa, Europe, and North America. Based on available data, the highest haplotype diversity was observed in India, suggesting India may be part of the presumed native range (South and Southeast Asian countries) of T. parvispinus. Our survey of retail plant stores across 10 Florida counties indicated that plant trade is the source of T. parvispinus in open vegetable field crops and ornamental landscape plants. The outcome of this study will assist with regulatory and management decisions of T. parvispinus in Florida and elsewhere.

Probing effective operators in single top quark production in association with a lepton-neutrino pair

We study single top quark production in association with a lepton-neutrino pair at the LHC within the framework of the Standard Model effective field theory (SMEFT). We focus on relevant two-quark-two-lepton operators (Olq3, Olequ1, and Olequ3). It is known that these operators have tiny effects on the inclusive cross section of standard model tW production and are thus typically ignored in the SMEFT searches. However, we show that by employing smart observables, such as mT2, the pp→tℓν process is significantly sensitive to these operators. We set the most stringent limit on the coupling strength of the Olq3 operator by reinterpreting the results of a search for new phenomena with two opposite-charge leptons, jets and missing transverse momentum at s=13 TeV performed by the ATLAS collaboration. The limits derived on the Olequ1 and Olequ3 operators are comparable to those obtained from probing EFT effects in pp→tt¯ℓν and pp→tt¯ℓℓ processes at the LHC. Consequently, we propose to include the effects of these three operators on the pp→tℓν process in future global SMEFT analyses to increase the sensitivity and to reduce possible degeneracies. Published by the American Physical Society 2024

Famine and food security: new trends and systems or politics as usual? An introduction.

Over the past decade, famine and food insecurity have increased, yet there have been few articles with a critical analysis of their social and political dynamics. This special issue of Disasters aims to revive such analysis and to provide new insights. The special issue contains eight articles, with topics ranging from the role of global politics and neoliberal strategies, to sanctions, war, settler-colonialism, elite capture and inequalities, actions of resistance and resilience, and the challenges of famine prevention in today's global political context. The papers provide both global and local analysis, with the latter covering Kashmir, South Africa, South Sudan, Sudan, and Syria.

Climate change and lethal violence: a global analysis

Purpose The study aims to uncover the relationship between rising temperatures, increased greenhouse gas emissions and the prevalence of lethal violence, encompassing suicides and homicides. It also sought to identify how climate change affects different economic strata in countries, notably in high and middle-income nations, and across Asia and Africa. Design/methodology/approach This study rigorously explored the link between global climate change and lethal violence across 201 countries from 1970 to 2020. Climate change was measured using annual surface temperature fluctuations and greenhouse gas emissions, while lethal violence was estimated using data on suicides and homicides. Findings The analysis revealed significant positive associations between escalating temperatures, heightened greenhouse gas emissions and lethal violence. These connections were evident across different economic levels and geographic regions in Asia and Africa. Originality/value This study emphasizes the urgent need for comprehensive interventions to combat human-induced climate change and mitigate its extensive negative impacts on society, particularly its association with increased violent behavior.

Global Profiling and Analysis of 5' Monophosphorylated mRNA Decay Intermediates.

During RNA turnover, the action of endo- and exo-ribonucleases can yield RNA decay intermediates with specific 5' ends. These RNA decay intermediates have been demonstrated to be the outcome of decapping, microRNA-directed endo-cleavage, or the protected fragments of ribosomes and exon-junction complexes. Therefore, global analysis of RNA decay intermediates can facilitate studies of many RNA decay pathways. In this chapter, we describe a high-throughput sequencing protocol named parallel analysis of RNA ends (PARE), which allows genome-wide profiling of 5' monophosphorylated mRNA decay intermediates from plants or other eukaryotes. Also, we present the tools and scripts necessary for the proper analysis of RNA degradome data obtained from the PARE method. Details and modifications of library construction procedures and bioinformatic analyses to optimize sequencing quality and cope with emerging sequencing platforms and findings are highlighted.

Global reliability sensitivity analysis of cradle-type double rotary table

The rotary table is a crucial component of the machine tool, and its accuracy and reliability have an important impact on the machining accuracy and machining efficiency of the machine tool. In this paper, a global reliability sensitivity analysis method of the rotary table is proposed considering the random uncertainty for material parameters of each component. Firstly, the mechanical model of the rotary table is established based on the finite element method. Subsequently, the functional relationship between the parameters of each component and the deformation of the rotary table is reconstructed using the adaptive Kriging surrogate model. Finally, a global reliability sensitivity analysis of the rotary table is performed based on the Bayesian formulation. The results show that the proposed global reliability sensitivity analysis method of the rotary table demonstrates satisfactory efficiency and can provide theoretical guidance for the design and optimization of the rotary table.

Abstract PR010: High purity CTC RNA sequencing identifies poor prognosis lineage states in castrate resistant prostate cancer

Abstract Background: Metastatic prostate cancer is an androgen receptor (AR) driven disease for which multiple AR targeted therapies are FDA approved, leading to improvements in patient outcomes. However, development of treatment resistance remains universal, driven by AR alterations as well as lineage state transitions that bypass AR signaling and culminate in neuroendocrine prostate cancer (NEPC) with poor prognosis. Liquid biopsies could enable longitudinal molecular analysis to identify such lineage transitions, but bulk RNA sequencing of circulating tumor cells (CTCs) has been limited by the challenge of isolating sufficiently pure samples for global signaling pathway analysis. We developed a novel approach to CTC purification that results in purity comparable to tissue biopsies and performed the first large-scale CTC RNA-seq study in a multi-institutional cohort of patients with metastatic prostate cancer. Using this approach, we identified multiple prostate cancer lineage states associated with prognosis. Methods: 273 blood samples were collected from 117 patients with histologically confirmed metastatic prostate cancer treated at the University of Wisconsin Carbone Cancer Center, William S. Middleton Memorial Veterans Hospital, UC San Diego Moores Cancer Center and Dana Farber Cancer Institute. CTCs were isolated with our automated microfluidic technology integrating negative and positive selection for CTC enrichment. CTCs were captured immunomagnetically followed by RNA isolation on chip and RNA sequencing. A modification of the ESTIMATE algorithm was used to infer sample tumor purity, and CIBERSORTx was used to infer immune content. Overall survival (OS) was defined as date of death or last contact relative to first CTC sample collection. Results: 146 samples from 70 patients met our >50% purity threshold for gene expression pathway analysis. Single sample pathway analysis identified four CTC transcriptional phenotypes: luminal A (high AR signaling, intermediate proliferation), luminal B (high AR signaling, high proliferation), low proliferation, and neuroendocrine. Compared to patients with low CTC burden/low tumor purity (median OS NR, n=63), patients with luminal A (n=21) and low proliferation (n=12) phenotypes had similar survival, while patients with luminal B (n=18) and NE (n=3) had markedly shorter survival (LumB: median OS 6 months, HR 9.1, log rank p<0.0001, NE: median OS 3.7 months, HR 11.8, log rank p=0.0019). Conclusion: We report the largest CTC RNA sequencing cohort of patients with metastatic prostate cancer and demonstrate that CTC RNA-seq identifies prostate cancer lineage states mirroring those described in tissue profiling. In addition to an NE phenotype concordant with tissue histology and associated with markedly inferior overall survival, we identified a more common luminal B CTC subtype defined by persistent AR signaling and high proliferation and associated with poor prognosis comparable to NEPC. Citation Format: Marina N Sharifi, Jamie M Sperger, Amy K Taylor, Katharine E Tippins, Shannon R Reese, Viridiana Carreno, Katherine R Kaufmann, Alex H Chang, Luke A Nunamaker, Charlotte Linebarger, Kyle T Helzer, Matthew Bootsma, Grace C Blitzer, John Floberg, David Kosoff, Rana R McKay, Xiao X Wei, Shuang G Zhao, Joshua M Lang. High purity CTC RNA sequencing identifies poor prognosis lineage states in castrate resistant prostate cancer [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr PR010.

Variable resolution machine learning optimization of antennas using global sensitivity analysis.

The significance of rigorous optimization techniques in antenna engineering has grown significantly in recent years. For many design tasks, parameter tuning must be conducted globally, presenting a challenge due to associated computational costs. The popular bio-inspired routines often necessitate thousands of merit function calls to converge, generating prohibitive expenses whenever the design process relies on electromagnetic (EM) simulation models. Surrogate-assisted methods offer acceleration, yet constructing reliable metamodels is hindered in higher-dimensional spaces and systems with highly nonlinear characteristics. This work suggests an innovative technique for global antenna optimization embedded within a machine-learning framework. It involves iteratively refined kriging surrogates and particle swarm optimization for generating infill points. The search process operates within a reduced-dimensionality region established through fast global sensitivity analysis. Domain confinement enables the creation of accurate behavioral models using limited training data, resulting in low CPU costs for optimization. Additional savings are realized by employing variable-resolution EM simulations, where low-fidelity models are utilized during the global search stage (including sensitivity analysis), and high-fidelity ones are reserved for final (gradient-based) tuning of antenna parameters. Comprehensive verification demonstrates the consistent performance of the proposed procedure, its superiority over benchmark techniques, and the relevance of the mechanisms embedded into the algorithm for enhancing search process reliability, design quality, and computational efficiency.

A sensitivity analysis of the Earth for all model: Getting the giant leap scenario with fewer policies

AbstractIntegrated assessment models (IAMs) are popular tools used to predict the evolution of human society, a challenging question that science has long tried to address. The World3 model is a popular IAM, designed in the seventies by several scientists convened by the Club of Rome and mostly known for its usage to analyze the so‐called limits to growth. The recent Earth for all (E4A) model has been initiated by one of the major co‐authors of the World3 model, Jørgen Randers. It is substantially more complicated than the relatively simple World3 model, and it has been used to compare two different and opposite world development scenarios: the too little too late scenario, in which current policies are assumed to continue, and the giant leap (GL) scenario, in which 21 policies related to five turnarounds are identified to produce significant improvements in six indicators of human well‐being. By using global and local sensitivity analyses of the E4A model, we suggest that the evolution of the six indicators in the GL scenario can be approximately reached by focusing on just six policies and three turnarounds (namely, the energy, the inequality, and the poverty turnarounds). The evolution of the six indicators can be even improved by investing “reasonably” more on three of these six policies and by keeping unchanged the remaining three. From a methodological point of view, we exploit both global (Sobol) and local sensitivity analyses to identify the policies that most influence the six indicators, and we subsequently execute a scenario analysis of the identified policies to confirm that they can produce a similar (or even a better) evolution of the indicators themselves.

Abstract 4125992: Eicosapentaenoic Acid (EPA) Increases Expression of Nrf2-mediated Antioxidant Response Element and Heme Oxygenase-1 in Cytokine-Activated Endothelial Cells

Background: Endothelial cell (EC) nuclear factor erythroid 2-related factor (Nrf2) translocates to the nucleus during inflammation to mediate transcription of genes in the antioxidant response elements (ARE). An ARE regulates mRNA encoding HMOX-1, thioredoxin (TXN), and NAD(P)H quinone oxidoreductase-1 (NQO1), among others. Parkinson disease protein 7 (PARK7) and p62 work independently to prevent Keap1-mediated degradation of Nrf2 during oxidative stress. Eicosapentaenoic acid (EPA) administered as icosapent ethyl reduced CV events (REDUCE-IT). We tested the effects of EPA on ARE protein expression in ECs from multiple tissues during cytokine challenge. Methods: Human brain, pulmonary and vascular ECs were treated with IL-6 (12 ng/mL) for 2 hours and then incubated with EPA (40 µM) for 24 h. Global proteomic analysis performed by LC-MS measured relative protein expression. Significant (p<0.05) changes between treatment groups >1-fold were analyzed by differential enrichment analysis of proteomics data (DEP) and included in gene set enrichment analyses (GSEA). Significantly modulated pathways within the Gene Ontology (GO) database were identified as those with an adjusted-p value <0.05. Results: Proteomic analysis revealed that EPA significantly modulated ≥600 proteins in ECs distinct from IL-6 challenge alone. In EC, EPA significantly modulated the “cellular response to oxidative stress” pathway (GO: 0034599) relative to IL-6 alone. Within this GO pathway, EPA increased levels of catalase (1.2-fold, 1.1-fold, 1.1-fold) and mitochondrial glutathione reductase (1.1-fold, 1.1-fold, 1.1-fold) in brain, pulmonary, and vascular ECs, respectively. We also observed a consistent increase in brain, pulmonary, and vascular ECs of p62 (1.3-fold, 1.2-fold, and 1.2-fold, respectively), and ARE members HMOX-1 (1.5-fold, 1.7-fold, and 2.1-fold, respectively), and NQO1 (1.1-fold, 1.2-fold, and 1.3-fold, respectively). TXN was increased in pulmonary and vascular ECs (1.1-fold and 1.2-fold, respectively) with EPA. Mitochondrial TXN (also called TXN2) increased in brain ECs with EPA 1.1-fold. EPA also significantly increased levels of PARK7 1.1-fold. Conclusions: During inflammation, EPA enhanced expression of cytoprotective proteins in the ARE, notably HMOX-1, along with its regulators, in ECs from multiple tissues. Augmented endogenous antioxidant pathways may contribute to EPA’s clinical benefits.

Retraction: Social and economic factors responsible for environmental performance: A global analysis.

Retraction: Social and economic factors responsible for environmental performance: A global analysis.

Exploration and Development of Quantum Computing Algorithms for Optimization, Cryptography, and Machine Learning Applications

Quantum computing, with its potential to revolutionize computation, relies fundamentally on the development of efficient algorithms to leverage its unparalleled processing capabilities. This research delves into the creation, exploration, and refinement of quantum computing algorithms, focusing on their applications in optimization, cryptography, and machine learning. Quantum algorithms such as Shor's and Grover's have demonstrated remarkable advantages in factorization and search problems, while more recent innovations are tackling complex challenges in global optimization and data analysis. By integrating principles of quantum mechanics—such as superposition, entanglement, and interference—these algorithms promise exponential speed-ups over classical counterparts in specific domains. This study critically analyzes existing quantum algorithms, proposes advancements in hybrid quantum-classical frameworks, and explores their implications for practical problem-solving. Through simulations and theoretical evaluations, it aims to bridge the gap between quantum theory and real-world applications, contributing to the evolution of quantum computing as a transformative technology.

The effect of CHINA RAILWAY Express on alleviating the Red Sea Waterway Crisis: A GTAP model-based study

In November 2023, the Red Sea Waterway Crisis broke out, which caused the goods originally shipped to Europe via the Red Sea-Suez Canal Route to be transported around the Cape of Good Hope in Africa, thus increasing the shipping cost and shipping time. Firstly, this paper uses the Supply Chain Network Model and the Optimization Model to theoretically analyze the impact of this incident. Secondly, the Global Trade Analysis Project (GTAP) Model is employed to analyze the impact of the crisis on China. At the same time, it also explains whether the impact of the incident can be alleviated by using CHINA RAILWAY Express (CR Express). Finally, this paper compares the upward pressure changes of domestic commodity prices in China, Germany, France, Netherlands and Italy before and after the adoption of CR Express. The results of the study are as follows. (1) The outbreak of the Red Sea Waterway Crisis has a great negative impact on China's macro economy. When China switches to the use of CR Express, the impact on China's GDP and terms of trade is reduced. (2) The outbreak of the Red Sea Waterway Crisis has a greater impact on China's import trade than on its export trade. (3) The outbreak of the Red Sea Waterway Crisis has a great negative impact on China's textile and clothing industry and electronic equipment industry. (4) CR Express can ease the upward pressure of domestic commodity prices. Taken together, the above results can provide reference for China and other countries to cope with similar impact events.

Phospholipase D2 downregulates interleukin-1β secretion from tumor-associated macrophages to suppress bladder cancer progression.

The tumor microenvironment (TME) modulates therapeutic response and prognosis in patients with bladder cancer (BC). The roles of two phospholipase D (PLD) isoforms, PLD1 and PLD2 (hydrolysis of phosphatidylcholine to phosphatidic acid), in cancer cells have been well-studied in numerous cancer types, but their roles in the TME remain unclear. We used a mouse BC Pld2-KO carcinogenesis model and global transcriptomic analysis to reveal that PLD2 was significantly involved in BC progression through immunosuppressive pathways in the TME. We therefore focused on PLD2 and tumor-associated macrophages (TAMs), which were increased in Pld2-KO mice and further associated with poor prognoses in BC patients. Invitro, we found that Pld2-KO mouse TAMs had significantly enhanced proliferation, correlating closely with increased interleukin-1β (IL-1β) production. These results indicate that PLD2 suppresses BC progression by regulation of IL-1β secretion from TAMs in the TME, suggesting that PLD2 could serve as a potential therapeutic target for modifying the TME in BC.

Integrated Profiling Identifies Long-Term Molecular Consequences of Prenatal Dexamethasone Treatment in the Rat Brain-Potential Triggers of Depressive Phenotype and Cognitive Impairment.

Prenatal excess of glucocorticoids (GCs) is considered to be one of the highly impacting factors contributing to depression development. Although GCs are crucial for normal fetal development and their administration (mainly dexamethasone, DEX) is a life-saving procedure for those at risk of preterm delivery, exposure to excess levels of GCs during pregnancy can yield detrimental consequences. Therefore, we aimed to systematically investigate the brain molecular alterations triggered by prenatal DEX administration. We used a rat model of depression based on prenatal exposure to DEX and performed integrative multi-level methylomic, transcriptomic, and proteomic analyses of adult rats' brains (i.e., frontal cortex (FCx) and hippocampus (Hp)) to identify the outcomes of DEX action. Each of the investigated levels was significantly affected by DEX in the long-term manner. Particularly, we found 200 CpG islands to be differentially methylated in the FCx and 200 in the Hp of prenatally DEX-treated rats. Global transcriptomic analysis uncovered differential expression of transcripts mostly in FCx (271) and 1 in Hp, while proteomic study identified 146 differentially expressed proteins in FCx and 123 in Hp. Among the identified enriched molecular networks, we found altered pathways involved in synaptic plasticity (i.e., cAMP, calcium, and Wnt signaling pathways or tight junctions and adhesion molecules), which may contribute to cognitive impairment, observed in DEX-treated animals. Moreover, in the FCx, DEX administration in the prenatal period downregulates the expression of ribosome protein genes associated both with large and small ribosomal subunit assembly which can lead to a global decrease in translation and protein synthesis processes and, indirectly, alterations in the neurotransmission process.

The status quo of psychology research on refugees, asylum-seekers and displaced people: a global bibliometric analysis

The status quo of psychology research on refugees, asylum-seekers and displaced people: a global bibliometric analysis

INNV-35. DATA-DRIVEN MODELING OF EMERGING TRENDS AND COLLABORATIVE NETWORKS ACROSS BRAIN METASTASES RESEARCH: THE PAST DECADE OF INNOVATION

Abstract With recent significant growth in brain metastases literature output, more comprehensive research is necessary to understand emerging trends and novel methods of diagnosis and treatment. We aimed to address this by providing a contemporary systematic global analysis of emerging brain metastases research in the last decade while visually depicting the international collaborative environment among its researchers. Data mining was performed on all brain metastases publications across the last decade indexed in Elsevier’s Scopus database. Our Scopus search revealed 6,362 publications from 1,184 sources from 2013-2022. Of those, 252 were identified as high-impact articles with an annual citation rate (CR) > 10. The compounded annual growth rate (CAGR) of brain metastases publications was 7.2% per year since 2013. There was an acceleration of scientific production, from 5.9% CAGR across 2013-2018 to 9.6% across 2019-2022. Authors per document increased from 7.2% to 8.5% while international co-authorships increased from 16.6% to 18.3% in the same periods, respectively. Recent trending topics were noted to be artificial intelligence, understanding the brain microenvironment, exosomes, novel mechanisms of diagnosis (such as circulating tumor cells), and targeted treatments. High-impact articles tended to revolve around specific therapies or biomarkers as opposed to general synopses. Clustering analysis revealed three separate pivotal collaborative communities centered around Brown PD/Sahgal A, Ahluwalia MS, and Wang Y, with Brown PD as most notable for high impact research. While the top institutional collaborative group centered around Mayo Clinic, the highest impact research centered around the Dana-Farber Cancer Institute. Sub-analyses revealed that studies involving multiple countries tended to have a higher impact. The median overall survival of brain metastases, by primary source, was illustrated across the last five decades. Overall, significant growth in scientific production is driven by the integration of novel technologies (such as artificial intelligence), interdisciplinary approaches, and collaboration across global communities.

Drug resistance biomarkers in ovarian cancer: a bibliometric study from 2017 to 2022

BackgroundLate diagnosis and patient relapse, mainly due to chemoresistance, are the key reasons for the high mortality rate of ovarian cancer patients. Hence, the search for biomarkers of high predictive value within the phenomenon of chemoresistance is vital. This study performs a bibliometric analysis of the scientific literature concerning biomarkers of drug resistance in ovarian cancer, considering the period from 2017 to 2022.MethodsThe terms “drug resistance biomarker” and “ovarian cancer” were linked by the Boolean operator “AND”. The search was done in PubMed, selecting documents published over the last 5 years (2017-2022), which were analyzed with the open-source tool Bibliometrix developed in the R package. The language of the publications was restricted to English. Several types of papers such as case reports, clinical trials, comparative studies, and original articles were considered.ResultsA total of 335 scientific articles were analyzed. The United States and China were the leading contributors and established the largest number of scientific collaborations. The Huazhong University of Science and Technology and the University of Texas MD Anderson Cancer Center were the most influential institutions. The Journal of Ovarian Research, International Journal of Molecular Science, and Scientific Reports are among the most relevant journals. The study identified high-profile, relevant thematic niches and important descriptors that indicate topics of interest, including studies on women, cell lines, solid tumors, and gene expression regulation. As well as studies involving middle-aged and adult participants, and those focusing on prognosis evaluation. Descriptors such as “drug resistance,” “neoplasm,” “genetics,” “biomarker,” “gene expression profile,” and “drug therapy” would indicate new research trends. In addition, we propose that BCL-2, CHRF, SNAIL, miR-363, iASPP, ALDH1, Fzd7, and EZH2 are potential biomarkers of drug resistance.ConclusionsThis paper contributes to the global analysis of the scientific investigation related to drug resistance biomarkers in ovarian cancer to facilitate further studies and collaborative networks, which may lead to future improvements in therapy for this lethal disease.

Impact of the Prey Refuge Parameter in the Presence of Fear Effect on the Fuzzy Two-Prey–One Predator Model with Switching Effect

It has been thought of as a class of models where a generalist predator feeds on two distinct prey species. We wish to examine how prey refuge factors affect prey–predator models when fear effects are present. In order to achieve this, a two-prey–one predator model with prey refuge has been taken into consideration in the presence of the predator’s fear effect on two prey species. Both prey species engage in intra-specific competition. We enhance our model by including a switching mechanism in predation. In order to account for the inherent imperfection of environmental conditions, some parameters have been taken as fuzzy numbers. Analytical and numerical results on the system have been examined in fuzzy sense. The system’s positivity, boundedness, and permanence are examined. The system’s local and global stability analyses have been investigated. Hopf bifurcation analysis around the positive interior equilibrium point has been explored. The stability of the limit cycle of our suggested fuzzy system has been discussed. The system’s numerical simulations have been investigated with pertinent tables and graphical illustrations. When the prey refuge parameter and fear parameter exceed the critical value, the system experiences Hopf bifurcation at the positive interior equilibrium point.

Proteome modulation triggers potent antiviral response in Japanese Encephalitis Virus infected human macrophages.

Japanese encephalitis virus (JEV) is a mosquito-borne neurotropic virus that claims thousands of children's lives globally every year, causing neuropsychiatric sequelae. While neuronal cell pathogenesis is a terminal consequence of JEV infection, the virus hijacks macrophages during initial replication and propagation, making macrophages critical cells of host immune defense that dictate the outcomes of infection. Though a plethora of studies have been reported using various neuronal and immune cells, a global response of human macrophages to JEV infection is yet to be explored. In this study, we assessed the kinetics of global proteome dysregulation employing an in vitro JEV infection model using human monocyte-derived macrophages (THP-1). A comparative assessment of the proteome of the infected THP-1 cells revealed differential regulation of 428 proteins at 24h post-infection (hpi), which was later increased to 443 by 48h post-infection. Global gene ontology analysis of the differentially expressed proteins highlighted several critical pathways related to immune and metabolic processes that are known to play either proviral or antiviral effects during infection. Notably, several antiviral proteins, including STAT2, OAS1, MX1, MX2, RIG-I, ISG15, and ISG20, were significantly upregulated at both time points post-infection. In contrast, a considerable downregulation of BCL-2, an anti-apoptotic protein at 48hpi indicates the activation of cell death pathways. Further, gene set enrichment analysis identified the type I interferon signaling pathway as one of the top upregulated pathways following JEV infection in human macrophages. Altogether, this study demonstrates human macrophage responses to JEV infection at the proteome level for the first time, highlighting several critical and novel antiviral proteins and pathways that not only advance our understanding of anti-JEV immunity but also aid in developing strategies to control this acute global public health menace.