Betaine & Lung Health 🫁 | Pulmonary Macrophage Pyroptosis Inhibition | #pencis #FOXO1 #LungInjury

INTRODUCTION

Bronchopulmonary dysplasia (BPD) remains one of the most prevalent chronic lung diseases in premature infants, characterized by impaired alveolar development and long-term respiratory complications. Emerging research highlights the importance of inflammatory pathways, particularly NLRP3-mediated macrophage pyroptosis, in the pathogenesis of BPD. Pyroptosis, a pro-inflammatory form of cell death, contributes to excessive inflammation and tissue injury in the immature lung exposed to hyperoxia. In this context, betaine, a naturally occurring compound with well-established anti-inflammatory and antioxidant properties, has attracted scientific interest as a potential therapeutic candidate. By modulating molecular signaling pathways, including FOXO1 phosphorylation, betaine may offer protective effects against hyperoxia-induced lung injury and provide new insights into treatment strategies for BPD.

PATHOGENESIS OF BPD AND NLRP3-MEDIATED PYROPTOSIS

BPD pathogenesis is multifactorial, involving mechanical ventilation, oxygen toxicity, and inflammatory responses that disrupt normal lung development. Among these, macrophage-driven inflammation through NLRP3 inflammasome activation plays a central role. Hyperoxia significantly increases the expression of pyroptosis-associated proteins, leading to alveolar simplification and impaired vascular growth. Pyroptotic macrophages release inflammatory cytokines, which exacerbate pulmonary damage and hinder alveolarization. Therefore, targeting NLRP3-mediated macrophage pyroptosis has emerged as a promising therapeutic strategy to improve outcomes in preterm infants with BPD.

ROLE OF BETAINE IN ANTI-INFLAMMATORY MODULATION

Betaine acts as a methyl donor in metabolic processes and exerts strong anti-inflammatory and antioxidative functions. In the context of BPD, betaine reduces oxidative stress markers and inflammatory mediators while preserving lung tissue integrity. Experimental evidence demonstrates that daily subcutaneous administration of betaine in neonatal mice exposed to hyperoxia significantly reduces macrophage pyroptosis. By attenuating oxidative injury and inflammatory cytokine production, betaine supports both structural and functional lung protection, indicating its therapeutic potential.

FOXO1 PHOSPHORYLATION AND BETAINE INTERVENTION

The transcription factor FOXO1 is closely associated with cell survival, inflammation, and oxidative stress responses. Hyperoxia induces FOXO1 phosphorylation, which in turn promotes NLRP3 activation and pyroptosis in pulmonary macrophages. Betaine has been shown to inhibit the phosphorylation of FOXO1, thereby preventing NLRP3 activation and subsequent pyroptotic cell death. In vitro studies using RAW264.7 macrophages confirmed that betaine suppressed FOXO1 phosphorylation and pyroptosis under hyperoxic conditions, while treatment with okadaic acid, a phosphatase inhibitor, reversed these protective effects.

IMPACT ON LUNG DEVELOPMENT

Hyperoxia-induced injury impairs alveolarization, leading to fewer and larger alveoli typical of BPD. Betaine treatment has been found to restore alveolar structure, reduce inflammatory infiltration, and promote lung development in neonatal mice exposed to hyperoxia. By modulating molecular pathways and reducing macrophage pyroptosis, betaine indirectly supports lung growth and enhances overall pulmonary architecture. This suggests that betaine not only acts as an anti-inflammatory agent but also plays a crucial role in developmental lung protection.

FUTURE RESEARCH DIRECTIONS

The findings on betaine’s protective effects in hyperoxia-induced BPD provide a foundation for translational research. Future studies should focus on dose optimization, timing of administration, and long-term safety in neonatal populations. Investigating the interaction of betaine with other molecular pathways may also reveal synergistic therapeutic benefits. Clinical trials will be necessary to validate preclinical evidence and establish betaine as a viable adjunct therapy for preventing or treating BPD in preterm infants.

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Hashtags

#BronchopulmonaryDysplasia, #BPD, #MacrophagePyroptosis, #NLRP3, #FOXO1, #Betaine, #NeonatalLungDisease, #Hyperoxia, #LungDevelopment, #PulmonaryInflammation, #Pyroptosis, #NeonatalCare, #AntiInflammatory, #OxidativeStress, #LungInjury, #MolecularTherapeutics, #PretermInfants, #RespiratoryResearch, #TranslationalMedicine, #LungHealth

Outbreak Dates of Viruses Could Be Predicted by Their Protein Sequence 🧬 | Pencis Insights #VirusPrediction #ProteinSequence #pencis

INTRODUCTION

Emerging infectious diseases such as monkeypox, smallpox, and coronavirus have posed repeated global health threats since 1970. Understanding the outbreak dynamics of these viral pathogens is critical for preparedness and prevention. Traditional epidemiological surveillance often lags behind viral evolution, leaving populations vulnerable to sudden epidemics. Recent advances in computational biology and protein sequence analysis have enabled researchers to explore whether viral outbreak dates can be predicted by examining one-dimensional protein sequences. This research aims to establish a mathematical correlation between outbreak timing and antigenic properties of viral proteins, providing a novel perspective on pandemic forecasting.

METHODS OF OUTBREAK DATA COLLECTION

To develop a predictive model, outbreak dates for monkeypox, smallpox, and coronavirus were systematically collected and compared against a reference strain, SARS-CoV-2 D614. By calculating the outbreak time interval, denoted as z, researchers were able to quantify temporal differences between strains. Simultaneously, the one-dimensional antigenic amino acid sequences of each strain were extracted to identify super-antigens. These sequences provided a foundation for calculating antigenic precision and amino acid features relevant to outbreak prediction.

PROTEIN SEQUENCE ANALYSIS AND SUPER-ANTIGEN DETECTION

Protein sequences play a vital role in immune recognition and viral pathogenicity. In this study, super-antigens were detected within the one-dimensional amino acid sequences, serving as indicators of potential immune evasion strategies. The increase in antigen precision, represented as x, was calculated for each strain. Additionally, the number of tryptophan residues (W), represented as y, was determined. These molecular variables provided the basis for developing a regression model capable of linking protein structure to outbreak intervals.

STATISTICAL MODELING AND REGRESSION EQUATION

A regression equation was established to correlate the outbreak interval (z) with antigen precision increase (x) and tryptophan count (y). The final model, expressed as z = 13.762x² − 109.376x − 63.290y + 221.197, demonstrated a perfect correlation coefficient (R = 1.0000000). Rigorous statistical testing confirmed the robustness of the model, with a low probability of type I error (P = 0.008). This result indicates a strong predictive relationship between protein sequence features and outbreak dates.

IMPLICATIONS FOR PANDEMIC PREDICTION

The model offers a powerful tool for forecasting outbreaks of viral diseases by analyzing protein sequences. Unlike conventional epidemiological models that rely on real-time surveillance, this approach provides predictive power before outbreaks occur. This could allow for earlier interventions, targeted vaccine development, and enhanced global preparedness against emerging pathogens. The methodology highlights the potential of computational biology and protein analytics in reshaping infectious disease prediction.

CONCLUSION AND FUTURE RESEARCH

This research demonstrates that outbreak dates for pathogens such as monkeypox, smallpox, and coronavirus can be predicted through one-dimensional protein sequence analysis. The high accuracy of the regression model underscores the feasibility of linking molecular data with epidemiological outcomes. Future research should expand the dataset to include additional viral families, refine antigen detection algorithms, and integrate machine learning approaches for broader predictive applications. Ultimately, this strategy could revolutionize outbreak forecasting, offering a scientific framework to anticipate and mitigate global health crises.

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Hashtags

#VirusPrediction, #ProteinSequence, #EpidemiologyResearch, #OutbreakForecasting, #MonkeypoxResearch, #SmallpoxStudy, #CoronavirusAnalysis, #PandemicModeling, #SuperAntigen, #AminoAcidSequence, #ComputationalBiology, #ViralEvolution, #PublicHealthPreparedness, #InfectiousDiseases, #Bioinformatics, #StatisticalModeling, #PandemicPrediction, #VaccineResearch, #OneHealth, #GlobalHealth

Spatial Epidemiology of COVID-19 in Africa 🌍 | Insights & Analysis #pencis

INTRODUCTION

The COVID-19 pandemic has significantly altered global health dynamics, with Africa presenting unique challenges and insights due to its diverse geographic, socioeconomic, and healthcare contexts. Unlike many other regions, African countries experienced heterogeneous patterns of disease transmission and vaccination coverage, influenced by both internal factors and external pressures from neighboring countries. This study highlights the role of spatial epidemiology in understanding the spread of COVID-19 and the disparities in vaccination uptake across the continent. By integrating spatial econometric modeling approaches such as the Spatial Lag Model (SLM), Spatial Lagged X Model (SLX), and Spatial Error Model (SEM), the research seeks to capture not only the country-level factors but also the interconnected nature of African nations in shaping pandemic outcomes.

SPATIAL DISTRIBUTION AND HOTSPOT ANALYSIS

COVID-19 in Africa demonstrated strong spatial clustering, with hotspot regions emerging in the North and South. Countries such as South Africa, Egypt, and Morocco recorded the highest infection rates, while much of Central and Western Africa experienced lower, though still significant, caseloads. Identifying these hotspots is crucial for designing effective health strategies, as it allows for targeted allocation of resources and the implementation of containment measures. Spatial epidemiology provides insights into how geographic proximity influences disease spread, underlining the necessity of regional cooperation in pandemic response.

VACCINATION COVERAGE AND INEQUITY

Vaccination efforts across Africa varied widely, reflecting inequities in health infrastructure, logistics, and public acceptance. While Seychelles achieved vaccination rates exceeding 70%, countries like South Sudan lagged behind with less than 10% coverage by 2022. These disparities demonstrate how vaccine availability alone does not guarantee uptake. Socioeconomic conditions, trust in public health systems, and population demographics all played key roles in determining coverage. Spatial econometric analysis helps uncover these inequalities, offering policymakers actionable insights into addressing barriers that hinder vaccination success.

SOCIOECONOMIC DETERMINANTS OF COVID-19 SPREAD

The analysis reveals that socioeconomic indicators such as Human Development Index (HDI), GDP per capita, and population density strongly influenced both case numbers and vaccination rates. Higher urbanization and population density facilitated virus transmission, while wealthier nations had relatively better access to vaccines and healthcare infrastructure. However, socioeconomic advantage did not always translate into equitable coverage, emphasizing the complex interplay between development and health outcomes. These findings highlight the need for policies that address socioeconomic vulnerabilities in pandemic preparedness.

DEMOGRAPHIC AND HEALTH-RELATED INFLUENCES

Demographic structures and pre-existing health conditions also shaped COVID-19 outcomes across Africa. Countries with a higher proportion of older adults or elevated prevalence of non-communicable diseases such as diabetes experienced greater risks of severe cases and fatalities. These health and demographic factors interact with spatial patterns of disease distribution, underscoring the need for integrating population-specific health risk assessments into pandemic planning. A spatially informed understanding of these factors enables the creation of interventions tailored to vulnerable subgroups.

POLICY IMPLICATIONS AND FUTURE DIRECTIONS

The findings of this study highlight the importance of spatial epidemiology in designing effective and equitable public health strategies. African policymakers must consider geographic clustering, cross-border interdependencies, and socioeconomic and demographic disparities when implementing future pandemic responses. Regional collaborations and data-driven allocation of vaccines can mitigate the uneven impacts observed during COVID-19. Strengthening healthcare infrastructure, improving health equity, and adopting spatial econometric insights can better prepare the continent for future pandemics, ensuring that interventions are context-sensitive and equitable.

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Hashtags

#COVID19Africa, #SpatialEpidemiology, #VaccineEquity, #PublicHealthAfrica, #COVID19Research, #PandemicResponse, #HealthInequalities, #AfricaVaccination, #SocioeconomicFactors, #Epidemiology, #GlobalHealth, #DiseaseMapping, #HealthInfrastructure, #PolicyImplications, #SpatialAnalysis, #HealthEquity, #VaccinationCoverage, #PandemicPreparedness, #InfectiousDiseases, #HealthcareAfrica,

Accounting for the Geometry of the Respiratory Tract in Viral Infections 🧬 | Advanced Insights #RespiratoryHealth #ViralInfections #Pencis

INTRODUCTION

The study of viral infection dynamics has long relied on both computational models and experimental systems that simplify host tissues into flat, uniform surfaces. While this framework has been useful for capturing broad infection behaviors, it overlooks the reality that respiratory tract tissues are not flat but geometrically complex. The respiratory tract is shaped by tubular, branching structures, with spatial heterogeneity that fundamentally alters infection progression and immune responses. By integrating more realistic tissue architecture into computational models, researchers are now uncovering new insights into viral lineage dynamics and regional variations in infection severity. This shift represents a significant advance in bridging experimental virology with computational biology.

RESPIRATORY TRACT GEOMETRY AND ITS BIOLOGICAL IMPORTANCE

The respiratory tract consists of a branching tubular structure where each generation of airways narrows progressively, leading to the deep alveolar regions. This geometry plays a central role in viral infections because viral particles experience distinct deposition patterns across airway generations. Narrower airways in deeper lung regions are not only harder for the immune system to access but are also associated with severe infection outcomes. Thus, the anatomical design of the respiratory tract is more than structural—it directly influences the spatial and temporal spread of viral infections. Recognizing this has important implications for both experimental systems and computational modelling.

LIMITATIONS OF FLAT TISSUE MODELS

Flat, wide tissue models commonly used in computational and in vitro studies fail to capture the complexity of infection dynamics in the respiratory system. While such models allow for controlled environments, they neglect the tubular branching that drives non-uniform viral spread. As a result, these simplified models may underestimate viral heterogeneity, immune response variability, and lineage evolution. This limitation has hindered translation of in vitro findings to in vivo infection outcomes, particularly in respiratory diseases such as influenza, SARS-CoV-2, and other emerging viral pathogens.

MULTICELLULAR MODELLING WITH REALISTIC GEOMETRY

To address these limitations, researchers are extending multicellular models of viral dynamics by incorporating features of the respiratory tract’s architecture. Such models capture both the tubular nature of airways and the branching structure of airway generations. This realistic approach allows simulation of how infection dynamics differ between upper and lower airways, how viral load changes along the tract, and how immune responses adapt to spatial heterogeneity. Importantly, the models help to explain why deeper infections are often more severe and resistant to immune clearance.

VIRAL LINEAGE DYNAMICS AND IMMUNE HETEROGENEITY

One major advantage of incorporating respiratory tract geometry into models is the ability to study viral lineage dynamics. Infections in deeper lung regions may foster distinct viral subpopulations due to reduced immune surveillance and spatial compartmentalization. Moreover, immune responses are not evenly distributed across the tract, meaning that infection control is highly variable. These factors contribute to within-host viral diversity, potentially influencing transmission, disease severity, and treatment outcomes. Such heterogeneity cannot be fully appreciated using flat in vitro systems.

IMPLICATIONS FOR FUTURE EXPERIMENTAL SYSTEMS

This new modelling framework highlights the need to design experimental systems that better represent the branching architecture of the respiratory tract. Bioreactors, organoids, and microfluidic airway-on-a-chip devices could incorporate tubular and branching geometries to better mimic in vivo conditions. Doing so will enable more accurate evaluation of antiviral drugs, vaccines, and immune therapies in the context of realistic tissue structures. Ultimately, integrating geometry into infection research bridges a key gap between experimental virology and clinical reality, offering new opportunities for translational science.

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Hashtags

#RespiratoryTract, #ViralInfections, #InfectionDynamics, #ComputationalModels, #RespiratoryGeometry, #BranchingAirways, #TissueModelling, #ImmuneResponse, #ViralLineages, #LungInfections, #SystemsBiology, #InVitroModels, #ExperimentalVirology, #SpatialHeterogeneity, #HostPathogen, #AirwayStructure, #MulticellularModels, #InfectionBiology, #RespiratoryResearch, #VirologyInnovation

🌍 Strategy and Mechanism of One Health Governance: Case Study of China | #OneHealth #Pencis

INTRODUCTION

One Health governance in China represents a multidimensional framework that integrates human health, animal health, and environmental sustainability to address shared risks of emerging infectious diseases, food safety threats, and ecological challenges. This study critically evaluates China’s current One Health system, highlighting its strategic approach and operational mechanisms. By focusing on governance as the central theme, the research aims to explore both progress and persistent gaps within political, institutional, and societal levels. Understanding these interlinked factors provides an evidence-based foundation for strengthening governance structures, improving intersectoral coordination, and ensuring alignment with global standards of One Health implementation.

POLITICAL COMMITMENT AND RESEARCH IMPLICATIONS

Political commitment forms the backbone of effective One Health governance in China. The research reveals that while there is strong national support at the highest levels of government, the absence of a unified national strategy remains a critical gap. This creates challenges in translating political will into long-term institutionalized actions. Further research should examine how political priorities influence policy coherence and resource allocation across ministries. Understanding the political economy of One Health in China is essential for assessing sustainability and resilience in health security.

LEGISLATION AND REGULATORY FRAMEWORKS

Legislation plays a pivotal role in shaping One Health outcomes by providing the legal basis for prevention, surveillance, and response to health threats. China has made significant progress in drafting laws and regulations targeting zoonotic diseases, food safety, and environmental protection. However, fragmentation across different sectors results in limited enforcement and regulatory overlaps. Future research must evaluate the impact of fragmented legislation on disease control outcomes and propose models for harmonizing regulations within a cohesive One Health legal system.

LEADERSHIP BUILDING AND CRISIS MANAGEMENT

The role of leadership in One Health governance becomes particularly visible during health crises, as evidenced by China’s coordinated responses to outbreaks. Yet, leadership structures are often temporary and lack institutionalization. This research highlights the need for long-term leadership development programs that go beyond emergency response. Analyzing past outbreak responses provides insights into how adaptive leadership can transition from crisis-driven coordination to sustainable, institutionalized governance.

STRATEGIC PLANNING AND INTERSECTORAL COORDINATION

Strategic planning is a cornerstone for the success of One Health governance. While regional pilot programs and initiatives exist, China still requires a comprehensive national plan that integrates human, animal, and environmental health. Research should focus on evaluating existing strategic plans, identifying their limitations, and proposing scalable models that strengthen intersectoral coordination. Policy-driven planning linked with research evidence can help ensure better preparedness for emerging zoonotic and environmental threats.

STAKEHOLDER ENGAGEMENT AND PUBLIC PARTICIPATION

Stakeholder engagement remains an evolving yet underdeveloped area in China’s One Health governance. Public awareness, academic contributions, and professional participation have grown in recent years; however, local community involvement remains weak. Research should investigate barriers to community participation and explore inclusive models that empower grassroots stakeholders. Strengthening engagement across multiple levels of society is vital for ensuring sustainability, accountability, and shared responsibility in One Health governance.

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Hashtags

#OneHealth, #ChinaResearch, #HealthGovernance, #ZoonoticDiseases, #GlobalHealth, #PublicHealth, #EnvironmentalHealth, #AnimalHealth, #FoodSafety, #HealthPolicy, #HealthSecurity, #HealthStrategy, #CommunityHealth, #ResearchInnovation, #HealthSystems, #SustainableDevelopment, #InterdisciplinaryResearch, #HealthRegulation, #PandemicPreparedness, #OneHealthGovernance

Screening of Tuberculosis Suspected Cases 🧬 | Real-Time PCR (TaqMan) Insights | #Pencis

INTRODUCTION

Tuberculosis (TB) remains one of the world’s leading infectious diseases, posing significant health and socio-economic burdens globally. Despite advances in treatment, the effectiveness of TB control largely depends on rapid and accurate diagnosis. Conventional methods such as sputum smear microscopy and culture, while considered standard, often fail to detect early or extrapulmonary TB cases. This study was conducted in Northeastern Iran between 2020 and 2021 to evaluate how many presumptive TB patients may have been missed by these conventional techniques. By incorporating an in-house real-time PCR (qPCR) TaqMan method, the research aimed to assess the sensitivity and specificity of molecular diagnostics compared with traditional methods, ultimately providing insight into more effective strategies for TB detection and management.

METHODS AND STUDY DESIGN

The study followed a cross-sectional design, involving 307 TB-suspected patients who had previously tested negative by Ziehl-Neelsen (ZN) microscopy and culture. An additional control group comprised 21 confirmed TB-positive patients from a referral TB center in Northeastern Iran. All subjects were re-evaluated using an in-house qPCR assay with the TaqMan method. This molecular approach was selected due to its ability to detect Mycobacterium tuberculosis (M.tb) DNA rapidly, even in paucibacillary and extrapulmonary samples. The study emphasized the feasibility of using standardized reagents, making the assay applicable in various resource-limited settings.

RESULTS AND DIAGNOSTIC PERFORMANCE

The qPCR assay successfully detected all TB cases in the positive control group, establishing a sensitivity of 100%. Among the 307 individuals negative by conventional methods, 50 (13.55%) were positive by qPCR, highlighting the considerable diagnostic gap in routine smear and culture. Specificity was calculated at 83.7%, demonstrating reliable accuracy. Importantly, the findings suggested that a significant proportion of TB cases remain undetected when relying solely on conventional diagnostic approaches.

SAMPLE TYPE AND FAILURE RATES

The study further analyzed failure rates across different sample types. Notably, urine samples showed the highest failure rates in conventional methods, as none tested positive by smear or culture, while six of 20 (30%) were identified as positive by qPCR. In sputum samples, although smear and culture were more effective, qPCR still detected nine additional cases out of 53, proving its superior sensitivity. Interestingly, one of 61 unculturable samples also tested positive with qPCR, reinforcing the utility of molecular diagnostics in challenging sample conditions. These findings indicate that extrapulmonary TB diagnosis, particularly using urine and cerebrospinal fluid (CSF), could be significantly enhanced through qPCR.

CLINICAL AND PUBLIC HEALTH IMPLICATIONS

The results of this study highlight the importance of integrating molecular diagnostics into TB control programs, especially in high-burden regions. Since conventional smear and culture methods can miss a considerable number of cases, patients may go untreated, contributing to continued transmission. Early and accurate diagnosis using qPCR could substantially reduce diagnostic delays, improve treatment outcomes, and prevent disease spread. This approach is particularly valuable in extrapulmonary TB cases, where sample limitations often hinder diagnosis. Thus, molecular methods should complement, rather than replace, traditional diagnostics for a comprehensive TB detection strategy.

CONCLUSIONS AND FUTURE DIRECTIONS

In-house qPCR using the TaqMan method proved to be a practical, feasible, and time-saving diagnostic tool for TB-suspected patients, particularly when conventional methods fail. With 100% sensitivity and acceptable specificity, it offers strong potential for routine use in diagnostic laboratories. Future research should focus on expanding sample size, standardizing protocols, and conducting cost-effectiveness analyses to support broader implementation. Moreover, integrating molecular diagnostics into national TB programs could play a pivotal role in achieving global TB control targets and reducing missed diagnoses in resource-constrained regions.

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#TuberculosisResearch, #PCRDiagnostics, #MolecularBiology, #TaqManAssay, #qPCRMethod, #TBDetection, #ClinicalMicrobiology, #TBPrevention, #Epidemiology, #InfectiousDiseases, #GlobalHealth, #MedicalDiagnostics, #LaboratoryMedicine, #PublicHealthResearch, #SmearMicroscopy, #CultureMethod, #MolecularDiagnostics, #TBControl, #HealthcareInnovation, #IranResearch,

Differentiation-Associated ISG Expression of NK Cells in Chronic Viral Infection 🧬 | #Pencis

INTRODUCTION

Natural killer (NK) cells are central players in antiviral immunity, exerting cytotoxic effects on infected cells and secreting cytokines that shape adaptive responses. In the context of chronic viral infections such as hepatitis B virus (HBV) and hepatitis C virus (HCV), their activity is modulated by diverse molecular signals, most notably type-I interferons (IFNs). While robust IFN signatures are a hallmark of chronic HCV, similar NK cell functional alterations are observed in HBV, highlighting the complexity of immune regulation beyond IFN-driven mechanisms. Understanding these shared and distinct pathways offers a foundation for therapeutic innovation.

TYPE-I INTERFERONS AND NK CELL MODULATION

Type-I IFNs are potent regulators of innate immunity and critical modulators of NK cell function during viral infection. In HCV, persistent IFN signaling enhances NK cell cytotoxicity while impairing cytokine release, contributing to disease persistence and immune evasion. Interestingly, comparable NK cell behavior in HBV infection occurs without a pronounced IFN milieu, suggesting IFN-independent regulatory layers. Dissecting the dual role of IFNs—protective versus suppressive—remains a critical area of research with implications for antiviral therapy.

INTERFERON-STIMULATED GENES IN NK CELL FUNCTION

Conserved interferon-stimulated genes (ISGs) such as IFITM3, IRF1, IFIT2, and ISG20 exhibit strong expression in NK cells across healthy donors and patients with chronic HBV or HCV. Their consistent expression patterns, regardless of IFN levels, indicate that these ISGs are integral to NK cell biology rather than simply markers of viral persistence. Functional studies suggest these ISGs contribute not only to direct antiviral defense but also to regulatory mechanisms that balance NK cytotoxicity and cytokine production.

TRANSCRIPTION FACTORS GOVERNING NK CELL DIFFERENTIATION

The expression of NK cell ISGs is tightly linked to differentiation states and governed by transcription factors such as ETS1, FLI1, and Eomes. These fate-determining regulators ensure that NK cells adapt to environmental cues and maintain functional readiness against viral challenges. Deciphering their role in ISG regulation provides insight into how NK cells achieve both short-term effector responses and long-term adaptation during chronic infections.

NETWORK ANALYSIS OF NK CELL ISGs

Systems-level network analysis reveals that NK cell ISGs extend their function beyond antiviral defense to roles in cellular transport, metabolic regulation, and survival pathways. This broad repertoire highlights the integration of immune function with metabolic adaptation in the chronic infection setting. By identifying key ISG-driven hubs, researchers can better understand how NK cells maintain activity in resource-limited or suppressive environments such as chronic HBV and HCV infections.

IMPLICATIONS FOR IMMUNOTHERAPY

The constitutive expression of ISGs in NK cells, independent of persistent IFN signaling, underscores new therapeutic opportunities for modulating immune responses. Targeting transcription factors or metabolic pathways linked with ISG activity may restore balanced NK function, enabling effective viral control without promoting immune exhaustion. These findings provide a roadmap for developing immunotherapies aimed at enhancing NK cell responses in chronic viral infections and potentially in cancer immunology.

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 Hashtags

#NKcells, #TypeIIFN, #ChronicHCV, #ChronicHBV, #InterferonStimulatedGenes, #ISGExpression, #AntiviralImmunity, #InnateImmunity, #Cytotoxicity, #CytokineRegulation, #TranscriptionFactors, #ETS1, #Eomes, #FLI1, #Immunometabolism, #ViralPersistence, #Immunotherapy, #HBVResearch, #HCVResearch, #SystemsImmunology