PTPN11 Mutation Clonal Hierarchy in Acute Myeloid Leukemia.

Mutations in protein tyrosine phosphatase non-receptor type 11 ( PTPN11 ) have been considered late acquired mutations in acute myeloid leukemia (AML) development. To interrogate the ontogeny of PTPN11 mutations, we utilized single-cell DNA sequencing and identified that PTPN11 mutations can occur as initiating events in some AML patients when accompanied by strong oncogenic drivers, commonly NPM1 mutations. The co-driver role of PTPN11 mutations was confirmed in a novel murine model that exhibits an AML phenotype with early expansion of a diverse set of variably differentiated myeloid cells that engrafted into immunodeficient and immunocompetent mice. This immune diversity was reconstituted from early precursor cells when engrafted into immunodeficient mice. Moreover, immune diversity was also observed in the blast component of patient samples with NPM1 and PTPN11 mutations, providing novel antigen targets for immune based approaches in this subset of AML that is resistant to multiple targeted therapies.

Disparities in Clinical Trial Participation: A Cross-Sectional Survey of Cancer Patients at a Midwest Academic Medical Center.

Research conducted on homogenous populations can lead to biased and misleading findings, impeding the development of effective interventions and treatments for diverse populations. Low participation among minority groups further leads to disparities in access to innovative cancer care and treatment outcomes associated with trial participation. To better understand cancer patients' attitudes and willingness to participate in clinical trials, solid tumor patients attending their clinic visits were invited to complete a survey. The survey included questions on demographics, previous trial participation, and future trial interest. Responses were analyzed with frequency tables and chi-square tests. Of 300 participants, only 96 (32%) were asked to participate in a clinical trial. Of these, 81 (84%) chose to participate and 15 (16%) did not. There were notable differences by race but not gender or education level. Of the 204 who had never been asked to participate, 70% indicated that they would be willing to participate in future, and there was a strong sex-race interaction. Non-White males were the most hesitant group. Of 204, 99% indicated that they would participate to access new treatments, and 57% would participate to contribute to research overall. This study shows that many solid tumor patients undergoing treatment are not offered clinical trials. Racial differences in attitudes toward trial participation are evident. Nonetheless, many patients are willing to participate in trials to access innovative treatments and to support research. Culturally relevant outreach to build trust with minority groups is needed to increase overall participation in clinical trials.

Predicting the Effect of miRNA on Gene Regulation to Foster Translational Multi-Omics Research-A Review on the Role of Super-Enhancers.

Gene regulation is crucial for cellular function and homeostasis. It involves diverse mechanisms controlling the production of specific gene products and contributing to tissue-specific variations in gene expression. The dysregulation of genes leads to disease, emphasizing the need to understand these mechanisms. Computational methods have jointly studied transcription factors (TFs), microRNA (miRNA), and messenger RNA (mRNA) to investigate gene regulatory networks. However, there remains a knowledge gap in comprehending gene regulatory networks. On the other hand, super-enhancers (SEs) have been implicated in miRNA biogenesis and function in recent experimental studies, in addition to their pivotal roles in cell identity and disease progression. However, statistical/computational methodologies harnessing the potential of SEs in deciphering gene regulation networks remain notably absent. However, to understand the effect of miRNA on mRNA, existing statistical/computational methods could be updated, or novel methods could be developed by accounting for SEs in the model. In this review, we categorize existing computational methods that utilize TF and miRNA data to understand gene regulatory networks into three broad areas and explore the challenges of integrating enhancers/SEs. The three areas include unraveling indirect regulatory networks, identifying network motifs, and enriching pathway identification by dissecting gene regulators. We hypothesize that addressing these challenges will enhance our understanding of gene regulation, aiding in the identification of therapeutic targets and disease biomarkers. We believe that constructing statistical/computational models that dissect the role of SEs in predicting the effect of miRNA on gene regulation is crucial for tackling these challenges.

Evaluation of supplementary carnosine accumulation and distribution: an initial analysis of participants in the Nucleophilic Defense Against PM Toxicity (NEAT) clinical trial.

Carnosine is an endogenous dipeptide that buffers intracellular pH and quenches toxic products of lipid peroxidation. Used as a dietary supplement, it also supports exercise endurance. However, the accumulation and distribution of carnosine after supplementation has not been rigorously evaluated. To do this, we randomized a cohort to receive daily supplements of either placebo or carnosine (2 g/day). Blood and urine samples were collected twice over the subsequent 12 week supplementation period and we measured levels of red blood cell (RBC) carnosine, urinary carnosine, and urinary carnosine-propanol and carnosine-propanal conjugates by LC/MS-MS. We found that, when compared with placebo, supplementation with carnosine for 6 or 12 weeks led to an approximate twofold increase in RBC carnosine, while levels of urinary carnosine increased nearly sevenfold. Although there were no changes in the urinary levels of carnosine propanol, carnosine propanal increased nearly twofold. RBC carnosine levels were positively associated with urinary carnosine and carnosine propanal levels. No adverse reactions were reported by those in the carnosine or placebo arms, nor did carnosine supplementation have any effect on kidney, liver, and cardiac function or blood electrolytes. In conclusion, irrespective of age, sex, or BMI, oral carnosine supplementation in humans leads to its increase in RBC and urine, as well as an increase in urinary carnosine-propanal. RBC carnosine may be a readily accessible pool to estimate carnosine levels. Clinical trial registration: This study is registered with ClinicalTrials.gov (Nucleophilic Defense Against PM Toxicity (NEAT Trial)-Full Text View-ClinicalTrials.gov), under the registration: NCT03314987.

Estimating Transition Intensity Rate on Interval-censored Data Using Semi-parametric with EM Algorithm Approach.

Phase IV clinical trials are designed to monitor long-term side effects of medical treatment. For instance, childhood cancer survivors treated with chest radiation and/or anthracycline are often at risk of developing cardiotoxicity during their adulthood. Often the primary focus of a study could be on estimating the cumulative incidence of a particular outcome of interest such as cardiotoxicity. However, it is challenging to evaluate patients continuously and usually, this information is collected through cross-sectional surveys by following patients longitudinally. This leads to interval-censored data since the exact time of the onset of the toxicity is unknown. Rai et al. computed the transition intensity rate using a parametric model and estimated parameters using maximum likelihood approach in an illness-death model. However, such approach may not be suitable if the underlying parametric assumptions do not hold. This manuscript proposes a semi-parametric model, with a logit relationship for the treatment intensities in two groups, to estimate the transition intensity rates within the context of an illness-death model. The estimation of the parameters is done using an EM algorithm with profile likelihood. Results from the simulation studies suggest that the proposed approach is easy to implement and yields comparable results to the parametric model.

Associations between Per- and polyfluoroalkyl substance exposures and metabolic dysfunction associated steatotic liver disease (MASLD) in adult National Health and Nutrition Examination Survey 2017-2018.

Per- and polyfluoroalkyl substances (PFAS) are persistent organic pollutants previously associated with elevated liver enzymes in human cohorts and steatotic liver disease in animal models. We aimed to evaluate the associations between PFAS exposures, and liver enzymes and vibration controlled transient elastography (VCTE) biomarkers of metabolic dysfunction associated steatotic liver disease (MASLD) in adult National Health and Nutrition Examination Survey (NHANES) 2017-2018. VCTE was determined by FibroScan®. Serum PFAS (n = 14), measured by mass spectrometry, were analyzed individually and by principal component (PC). Univariate and multivariable associations were determined between PFAS exposures and liver disease outcome variables: Alanine aminotransferase (ALT), controlled attenuation parameter (CAP), liver stiffness measurement (LSM), FibroScan®-based Score (FAST), using R. 1400 participants including 50% women with a mean age of 48 ± 19 years and a mean BMI of 29 ± 7 kg/m2 were analyzed. Four PFAS clustered to PC1, while three PFAS clustered to PC2. PC1 was significantly associated with ALT (ß = 0.028), CAP (ß = 0.041), LSM (ß = 0.025) and FAST (ß = 0.198) in univariate analysis. Individual PFAS exposures were oftentimes inversely associated with these measurements in multivariate analysis. In adult NHANES 2017-2018, PFAS may not be a significant burden for MASLD, because of the inconsistent associations between the environmental PFAS exposures and biomarkers of liver steatosis, inflammation, and fibrosis. More data are required to better understand the relationships between PFAS exposures and liver disease.

Beyond mutations: Accounting for quantitative changes in the analysis of protein evolution.

Molecular phylogenetic research has relied on the analysis of the coding sequences by genes or of the amino acid sequences by the encoded proteins. Enumerating the numbers of mismatches, being indicators of mutation, has been central to pertinent algorithms. Specific amino acids possess quantifiable characteristics that enable the conversion from "words" (strings of letters denoting amino acids or bases) to "waves" (strings of quantitative values representing the physico-chemical properties) or to matrices (coordinates representing the positions in a comprehensive property space). The application of such numerical representations to evolutionary analysis takes into account not only the occurrence of mutations but also their properties as influences that drive speciation, because selective pressures favor certain mutations over others, and this predilection is represented in the characteristics of the incorporated amino acids (it is not born out solely by the mismatches). Besides being more discriminating sources for tree-generating algorithms than match/mismatch, the number strings can be examined for overall similarity with average mutual information, autocorrelation, and fractal dimension. Bivariate wavelet analysis aids in distinguishing hypermutable versus conserved domains of the protein. The matrix depiction is readily subjected to comparisons of distances, and it allows the generation of heat maps or graphs. This analysis preserves the accepted taxa order where tree construction with standard approaches yields conflicting results (for the protein S100A6). It also aids hypothesis generation about the origin of mitochondrial proteins. These analytical algorithms have been automated in R and are applicable to various processes that are describable in matrix format.

Refining Surveillance Guidelines after Stereotactic Body Radiation Therapy for Early-Stage Lung Cancer.

INTRODUCTION: Stereotactic body radiation therapy (SBRT) is a treatment for patients with early-stage non-small cell lung cancer (ES-NSCLC). Surveillance guidelines vary after treatment. While patients are more likely to locally recur within 2 years of treatment, there remains a paucity of data on the benefit of frequent and long-term surveillance. We evaluated a cohort of NSCLC patients to evaluate surveillance patterns and outcomes. MATERIALS AND METHODS: Patients with ES-NSCLC treated with SBRT were retrospectively evaluated. Imaging was reviewed after SBRT for evidence of recurrence or new malignancy. The median scan interval (MSI) was calculated as the median number of months between surveillance scans. The MSI between patients with or without new disease was compared by t-test. New disease development and survival between patients with =T2 disease and with or without prior malignancy was compared using χ², Kaplan-Meier analysis, and Gray's test. RESULTS: A cohort of 168 patients with median follow up of 23.4 months met criteria for review with 50% developing new disease. MSI did not differ between patients with or without new disease. Patients with >=cT2 tumors had worse overall survival and trended towards higher incidence of new disease. New disease continued to occur, even 5 years after treatment. CONCLUSION: Increased scan frequency did not increase detection of new disease. Patients continued to fail 5 years after treatment. Larger tumors trended toward more frequent failures and those patients experienced worse OS. Surveillance guidelines should be optimized to prevent over surveillance after treatment and to continue long-term surveillance.

Detection of COVID-19 by quantitative analysis of carbonyl compounds in exhaled breath.

COVID-19 has caused a worldwide pandemic, creating an urgent need for early detection methods. Breath analysis has shown great potential as a non-invasive and rapid means for COVID-19 detection. The objective of this study is to detect patients infected with SARS-CoV-2 and even the possibility to screen between different SARS-CoV-2 variants by analysis of carbonyl compounds in breath. Carbonyl compounds in exhaled breath are metabolites related to inflammation and oxidative stress induced by diseases. This study included a cohort of COVID-19 positive and negative subjects confirmed by reverse transcription polymerase chain reaction between March and December 2021. Carbonyl compounds in exhaled breath were captured using a microfabricated silicon microreactor and analyzed by ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS). A total of 321 subjects were enrolled in this study. Of these, 141 (85 males, 60.3%) (mean ± SD age: 52 ± 15 years) were COVID-19 (55 during the alpha wave and 86 during the delta wave) positive and 180 (90 males, 50%) (mean ± SD age: 45 ± 15 years) were negative. Panels of a total of 34 ketones and aldehydes in all breath samples were identified for detection of COVID-19 positive patients. Logistic regression models indicated high accuracy/sensitivity/specificity for alpha wave (98.4%/96.4%/100%), for delta wave (88.3%/93.0%/84.6%) and for all COVID-19 positive patients (94.7%/90.1%/98.3%). The results indicate that COVID-19 positive patients can be detected by analysis of carbonyl compounds in exhaled breath. The technology for analysis of carbonyl compounds in exhaled breath has great potential for rapid screening and detection of COVID-19 and for other infectious respiratory diseases in future pandemics.

Intra-neighborhood associations between residential greenness and blood pressure.

INTRODUCTION: Previous investigations have reported that individuals living in greener neighborhoods have better cardiovascular health. It is unclear whether the effects reported at large geographic scales persist when examined at an intra-neighborhood level. The effects of greenness have not been thoroughly examined using high-resolution metrics of greenness exposure, and how they vary with spatial scales of assessment or participant characteristics. METHODS: We conducted a cross-sectional assessment of associations between blood pressure and multiple high-resolution measures of residential area greenness in spatially concentrated HEAL Study cohort of the Green Heart Project. We employed generalized linear models, accounting for individual-level covariates, to examine associations between different high-resolution measures of greenness and blood pressure among 667 participants in a 4 sq. mile contiguous neighborhood area in Louisville, KY. RESULTS: In adjusted models, we observed significant inverse associations between residential greenness, measured by leaf area index (LAI), and systolic blood pressure (SBP) within 150-250 m and 500 m of homes, but not for Normalized Difference Vegetation Index (NDVI) or grass cover. Weaker associations were also found with diastolic blood pressure (DBP). Significant positive associations were observed between LAI and SBP among participants who reported being female, White, without obesity, non-exercisers, non-smokers, younger age, of lower income, and who had high nearby roadway traffic. We found few significant associations between grass cover and SBP, but an inverse association in those with obesity, but positive associations for those without obesity. CONCLUSIONS: We found that leaf surface area of trees around participants home is strongly associated with lower blood pressure, with little association with grass cover. These effects varied with participant characteristics and spatial scales. More research is needed to test causative links between greenspace types and cardiovascular health and to develop population-, typology-, and place-based evidence to inform greening interventions.

Disparities Associated with Decision to Undergo Oncologic Surgery: A Prospective Mixed-Methods Analysis.

BACKGROUND: Underrepresented minority patients with surgical malignancies experience disparities in outcomes. The impact of provider-based factors, including communication, trust, and cultural competency, on outcomes is not well understood. This study examines modifiable provider-based barriers to care experienced by patients with surgical malignancies. METHODS: A parallel, prospective, mixed-methods study enrolled patients with lung or gastrointestinal malignancies undergoing surgical consultation. Surveys assessed patients' social needs and patient-physician relationship. Semi-structured interviews ascertained patient experiences and were iteratively analyzed, identifying key themes. RESULTS: The cohort included 24 patients (age 62 years; 63% White and 38% Black/African American). The most common cancers were lung (n = 18, 75%) and gastroesophageal (n = 3, 13%). Survey results indicated that food insecurity (n = 5, 21%), lack of reliable transportation (n = 4, 17%), and housing instability (n = 2, 8%) were common. Lack of trust in their physician (n = 3, 13%) and their physician's treatment recommendation (n = 3, 13%) were identified. Patients reported a lack of empathy (n = 3, 13%), lack of cultural competence (n = 3, 13%), and inadequate communication (n = 2, 8%) from physicians. Qualitative analysis identified five major themes regarding the decision to undergo surgery: communication, trust, health literacy, patient fears, and decision-making strategies. Five patients (21%) declined the recommended surgery and were more likely Black (100% vs. 21%), lower income (100% vs. 16%), and reported poor patient-physician relationship (40% vs. 5%; all p < 0.05). CONCLUSIONS: Factors associated with declining recommended cancer surgery were underrepresented minority race and poor patient-physician relationships. Interventions are needed to improve these barriers to care and racial disparities.

The effect of treatment package time on locally advanced oral cavity cancer outcomes.

OBJECTIVE(S): To assess the influence of treatment package time (TPT) on overall survival (OS) and event free survival (EFS) in oral cavity cancer (OCC) patients treated with surgery and adjuvant radiation therapy (RT) with or without concurrent chemotherapy (CHT). MATERIALS/METHODS: 354 adult OCC patients treated at a single, high-volume center between 2012-2022 with various pathologic risk features were included. TPT was defined as days from surgery to RT completion. Kaplan-Meier estimates, log-rank p-values, univariable (UVA) and multivariable (MVA) Cox regression analyses were performed to determine the impact of TPT on OS and EFS, and the optimal TPT cutoff. RESULTS: The optimal TPT cutoff was 105 days. TPT < 105 days was significantly associated with improved OS and EFS (p = 0.002 and p = 0.027, respectively) compared to TPT ≥ 105 days. On UVA, factors significantly associated with OS were TPT < 105 days, former/current smoker status, pathologic stage IV, positive perineural invasion (PNI), and extranodal extension (ENE) (all p < 0.05). On MVA for OS, TPT < 105 days, former/current smoker status, pathologic stage IV, and positive PNI (all p < 0.05) remained significant. Factors significantly associated with EFS on UVA were TPT < 105 days, former/current smoker status, pathologic stage IV, positive PNI or ENE, and concurrent CHT (all p < 0.05). On MVA, TPT < 105 days, pathologic stage IV, and positive PNI (all p < 0.05) remained significant. CONCLUSIONS: In a large, homogenous cohort of OCCs, optimal TPT was <105 days, with TPT ≥ 105 days significantly associated with worse OS and EFS. Multidisciplinary coordination should analyze factors potentially contributing to treatment delay.

Pyrimidine depletion enhances targeted and immune therapy combinations in acute myeloid leukemia.

Acute myeloid leukemia (AML) is a fatal disease characterized by the accumulation of undifferentiated myeloblasts, and agents that promote differentiation have been effective in this disease but are not curative. Dihydroorotate dehydrogenase inhibitors (DHODHi) have the ability to promote AML differentiation and target aberrant malignant myelopoiesis. We introduce HOSU-53, a DHODHi with significant monotherapy activity, which is further enhanced when combined with other standard-of-care therapeutics. We further discovered that DHODHi modulated surface expression of CD38 and CD47, prompting the evaluation of HOSU-53 combined with anti-CD38 and anti-CD47 therapies, where we identified a compelling curative potential in an aggressive AML model with CD47 targeting. Finally, we explored using plasma dihydroorotate (DHO) levels to monitor HOSU-53 safety and found that the level of DHO accumulation could predict HOSU-53 intolerability, suggesting the clinical use of plasma DHO to determine safe DHODHi doses. Collectively, our data support the clinical translation of HOSU-53 in AML, particularly to augment immune therapies. Potent DHODHi to date have been limited by their therapeutic index; however, we introduce pharmacodynamic monitoring to predict tolerability while preserving antitumor activity. We additionally suggest that DHODHi is effective at lower doses with select immune therapies, widening the therapeutic index.

Chronic Aroclor 1260 exposure alters the mouse liver proteome, selenoproteins, and metals in steatotic liver disease.

The prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) continues to increase due in part to the obesity epidemic and to environmental exposures to metabolism disrupting chemicals. A single gavage exposure of male mice to Aroclor 1260 (Ar1260), an environmentally relevant mixture of non-dioxin-like polychlorinated biphenyls (PCBs), resulted in steatohepatitis and altered RNA modifications in selenocysteine tRNA 34 weeks post-exposure. Unbiased approaches identified the liver proteome, selenoproteins, and levels of 25 metals. Ar1260 altered the abundance of 128 proteins. Enrichment analysis of the liver Ar1260 proteome included glutathione metabolism and translation of selenoproteins. Hepatic glutathione peroxidase 4 (GPX4) and Selenoprotein O (SELENOO) were increased and Selenoprotein F (SELENOF), Selenoprotein S (SELENOS), Selenium binding protein 2 (SELENBP2) were decreased with Ar1260 exposure. Increased copper, selenium (Se), and zinc and reduced iron levels were detected. These data demonstrate that Ar1260 exposure alters the (seleno)proteome, Se, and metals in MASLD-associated pathways.

Inhibition of Enhancer of Zeste Homolog 2 Induces Blast Differentiation, Impairs Engraftment and Prolongs Survival in Murine Models of Acute Myeloid Leukemia.

BACKGROUND: Acute myeloid leukemia (AML) is the malignant proliferation of immature myeloid cells characterized by a block in differentiation. As such, novel therapeutic strategies to promote the differentiation of immature myeloid cells have been successful in AML, although these agents are targeted to a specific mutation that is only present in a subset of AML patients. In the current study, we show that targeting the epigenetic modifier enhancer of zeste homolog 2 (EZH2) can induce the differentiation of immature blast cells into a more mature myeloid phenotype and promote survival in AML murine models. METHODS: The EZH2 inhibitor EPZ011989 (EPZ) was studied in AML cell lines, primary in AML cells and normal CD34+ stem cells. A pharmacodynamic assessment of H3K27me3; studies of differentiation, cell growth, and colony formation; and in vivo therapeutic studies including the influence on primary AML cell engraftment were also conducted. RESULTS: EPZ inhibited H3K27me3 in AML cell lines and primary AML samples in vitro. EZH2 inhibition reduced colony formation in multiple AML cell lines and primary AML samples, while exhibiting no effect on colony formation in normal CD34+ stem cells. In AML cells, EPZ promoted phenotypic evidence of differentiation. Finally, the pretreatment of primary AML cells with EPZ significantly delayed engraftment and prolonged the overall survival when engrafted into immunodeficient mice. CONCLUSIONS: Despite evidence that EZH2 silencing in MDS/MPN can promote AML pathogenesis, our data demonstrate that the therapeutic inhibition of EZH2 in established AML has the potential to improve survival.

Chronic arsenic exposure induces malignant transformation of human HaCaT cells through both deterministic and stochastic changes in transcriptome expression.

Biological processes are inherently stochastic, i.e., are partially driven by hard to predict random probabilistic processes. Carcinogenesis is driven both by stochastic and deterministic (predictable non-random) changes. However, very few studies systematically examine the contribution of stochastic events leading to cancer development. In differential gene expression studies, the established data analysis paradigms incentivize expression changes that are uniformly different across the experimental versus control groups, introducing preferential inclusion of deterministic changes at the expense of stochastic processes that might also play a crucial role in the process of carcinogenesis. In this study, we applied simple computational techniques to quantify: (i) The impact of chronic arsenic (iAs) exposure as well as passaging time on stochastic gene expression and (ii) Which genes were expressed deterministically and which were expressed stochastically at each of the three stages of cancer development. Using biological coefficient of variation as an empirical measure of stochasticity we demonstrate that chronic iAs exposure consistently suppressed passaging related stochastic gene expression at multiple time points tested, selecting for a homogenous cell population that undergo transformation. Employing multiple balanced removal of outlier data, we show that chronic iAs exposure induced deterministic and stochastic changes in the expression of unique set of genes, that populate largely unique biological pathways. Together, our data unequivocally demonstrate that both deterministic and stochastic changes in transcriptome-wide expression are critical in driving biological processes, pathways and networks towards clonal selection, carcinogenesis, and tumor heterogeneity.

Type 3 secretion system induced leukotriene B4 synthesis by leukocytes is actively inhibited by Yersinia pestis to evade early immune recognition.

Subverting the host immune response to inhibit inflammation is a key virulence strategy of Yersinia pestis. The inflammatory cascade is tightly controlled via the sequential action of lipid and protein mediators of inflammation. Because delayed inflammation is essential for Y. pestis to cause lethal infection, defining the Y. pestis mechanisms to manipulate the inflammatory cascade is necessary to understand this pathogen's virulence. While previous studies have established that Y. pestis actively inhibits the expression of host proteins that mediate inflammation, there is currently a gap in our understanding of the inflammatory lipid mediator response during plague. Here we used the murine model to define the kinetics of the synthesis of leukotriene B4 (LTB4), a pro-inflammatory lipid chemoattractant and immune cell activator, within the lungs during pneumonic plague. Furthermore, we demonstrated that exogenous administration of LTB4 prior to infection limited bacterial proliferation, suggesting that the absence of LTB4 synthesis during plague contributes to Y. pestis immune evasion. Using primary leukocytes from mice and humans further revealed that Y. pestis actively inhibits the synthesis of LTB4. Finally, using Y. pestis mutants in the Ysc type 3 secretion system (T3SS) and Yersinia outer protein (Yop) effectors, we demonstrate that leukocytes recognize the T3SS to initiate the rapid synthesis of LTB4. However, several Yop effectors secreted through the T3SS effectively inhibit this host response. Together, these data demonstrate that Y. pestis actively inhibits the synthesis of the inflammatory lipid LTB4 contributing to the delay in the inflammatory cascade required for rapid recruitment of leukocytes to sites of infection.

Estimation of foot-and-mouth disease virus sero-prevalence rates using novel computational approach for the susceptible bovine population in India during the period 2008-2021.

Foot-and-mouth disease (FMD) is a severe contagious viral disease of cloven-hoofed animals. In India, a vaccination-based official FMD control programme was started, which got expanded progressively to cover entire country in 2019. The serological tests are used to determine non-structural protein based sero-prevalence rates for properly implementing and assessing the control programme. Since 2008, reporting of the FMD sero-surveillance was limited to the serum sample-based serological test results without going for population-level estimation due to lack of proper statistical methodology. Thus, we present a computational approach for estimating the sero-prevalence rates at the state and national levels. Based on the reported approach, a web-application ( https://nifmd-bbf.icar.gov.in/FMDSeroSurv ) and an R software package ( https://github.com/sam-dfmd/FMDSeroSurv ) have been developed. The presented computational techniques are applied to the FMD sero-surveillance data during 2008-2021 to get the status of virus circulation in India under a strict vaccination policy. Furthermore, through various structural equation models, we attempt to establish a link between India's estimated sero-prevalence rate and field FMD outbreaks. Our results indicate that the current sero-prevalence rates are significantly associated with previous field outbreaks up to 2 years. Besides, we observe downward trends in sero-prevalence and outbreaks over the years, specifically after 2013, which indicate the effectiveness of various measures implemented under the FMD control programme. The findings of the study may help researchers and policymakers to track virus infection and identification of potential disease-free zones through vaccination.