Functional Approach Research Articles

Credit default swap spreads modeling and forecasting with a stochastic square-root three-factor model

In this study, we consider the CIR3 model, a three-factor stochastic model with correlated trends and volatilities for modeling and forecasting credit default swap (CDS) spreads. After recalling existence and uniqueness results, together with a generalized Feller condition to ensure positivity, we use a Lamperti-type transform to rewrite our SDEs system in a form in which the stochastic part of the leading process is uncorrelated with those of its mean and volatility processes. Finally, we calibrate the model through the estimating function approach for ergodic diffusions and simulate the CDS prices by discretizing our (transformed) system. These findings contribute to a deeper understanding of stochastic models with correlated trends and volatilities, with applications in pricing, trading and risk assessment.

Unplugging lateral fenestrations of NALCN reveals a hidden drug binding site within the pore region

The sodium (Na+) leak channel (NALCN) is a member of the four-domain voltage-gated cation channel family that includes the prototypical voltage-gated sodium and calcium channels (NaVs and CaVs, respectively). Unlike NaVs and CaVs, which have four lateral fenestrations that serve as routes for lipophilic compounds to enter the central cavity to modulate channel function, NALCN has bulky residues (W311, L588, M1145, and Y1436) that block these openings. Structural data suggest that occluded fenestrations underlie the pharmacological resistance of NALCN, but functional evidence is lacking. To test this hypothesis, we unplugged the fenestrations of NALCN by substituting the four aforementioned residues with alanine (AAAA) and compared the effects of NaV, CaV, and NALCN blockers on both wild-type (WT) and AAAA channels. Most compounds behaved in a similar manner on both channels, but phenytoin and 2-aminoethoxydiphenyl borate (2-APB) elicited additional, distinct responses on AAAA channels. Further experiments using single alanine mutants revealed that phenytoin and 2-APB enter the inner cavity through distinct fenestrations, implying structural specificity to their modes of access. Using a combination of computational and functional approaches, we identified amino acid residues critical for 2-APB activity, supporting the existence of drug binding site(s) within the pore region. Intrigued by the activity of 2-APB and its analogues, we tested compounds containing the diphenylmethane/amine moiety on WT channels. We identified clinically used drugs that exhibited diverse activity, thus expanding the pharmacological toolbox for NALCN. While the low potencies of active compounds reiterate the pharmacological resistance of NALCN, our findings lay the foundation for rational drug design to develop NALCN modulators with refined properties.

Comparison of the predatory impacts of indigenous and adventive ladybeetle species (Coleoptera: Coccinellidae) using a functional response approach

Comparison of the predatory impacts of indigenous and adventive ladybeetle species (Coleoptera: Coccinellidae) using a functional response approach

Significant impact of urban tree biogenic emissions on air quality estimated by a bottom-up inventory and chemistry transport modeling

Abstract. Biogenic volatile organic compounds (BVOCs) are emitted by vegetation and react with other compounds to form ozone and secondary organic matter (OM). In regional air quality models, biogenic emissions are often calculated using a plant functional type approach, which depends on the land use category. However, over cities, the land use is urban, so trees and their emissions are not represented. Here, we develop a bottom-up inventory of urban tree biogenic emissions in which the location of trees and their characteristics are derived from the tree database of the Paris city combined with allometric equations. Biogenic emissions are then computed for each tree based on their leaf dry biomass, tree-species-dependent emission factors, and activity factors representing the effects of light and temperature. Emissions are integrated in WRF-CHIMERE air quality simulations performed over June–July 2022. Over Paris city, the urban tree emissions have a significant impact on OM, inducing an average increase in the OM of about 5 %, reaching 14 % locally during the heatwaves. Ozone concentrations increase by 1.0 % on average and by 2.4 % during heatwaves, with a local increase of up to 6 %. The concentration increase remains spatially localized over Paris, extending to the Paris suburbs in the case of ozone during heatwaves. The inclusion of urban tree emissions improves the estimation of OM concentrations compared to in situ measurements, but they are still underestimated as trees are still missing from the inventory. OM concentrations are sensitive to terpene emissions, highlighting the importance of favoring urban tree species with low-terpene emissions.

Understanding Graphic Design Process in Visual Communication

From a chocolate wrapper design to a huge advertising hoarding, graphic design play a significant role in our daily life, which takes into consideration three important aspect of acceptance of a design - an aesthetic appeal, functional and semiotic approach. Graphic design encompasses the diverse set of design solution in visual form -from designing a logo, poster, signage to advertising design, web based design and many more that utilizes various visual elements, combining art and technology to communicate a message visually. Since it a coherent creative process of visual communication, the content of communication need to be streamed between the clients and the end user that takes into consideration certain aspect of structural stages or design process in order to get the best service and design solution to a problem. The paper highlights on the structure of the design process involve in a graphic design in bringing about a solution to a design problem within the practice of visual communication.

Colloidal carbon soot templated TiO2/Ag surface functionalized 3D printed metal brushes as new generation surface enhanced Raman scattering substrates

This present work demonstrated the functional transformation of 3D printed metal substrates into a new family of Surface-enhanced Raman Scattering substrates, a promising approach in developing SERS-based Point-of-care (PoC) analytical platforms. l-Powder Bed Fusion (l-PBF, Additive manufacturing or 3D printing technique) printed metal substrates have rough surfaces, and exhibit high thermal stability and intrinsic chemical inertness, necessitating a suitable surface functionalization approach. This present work demonstrated a unique multi-stage approach to transform l-PBF printed metal structures as recyclable SERS substrates by colloidal carbon templating, chemical vapor deposition, and electroless plating methods sequentially. The surface of the printed metal structures was functionalized using the colloidal carbon soot particles, that were formed by the eucalyptus oil flame deposition method. These carbon particles were shown to interact with the metals present in the printed structures by forming metal carbides and function as an adlayer on the surface. Subsequent deposition of TiO2 onto these templates led to strong grafting of TiO2 and retaining the fractal structure of the soot template onto the metal surface. Electroless deposition of silver nanoparticles resulted in the formation of fractally structured TiO2/Ag nanostructures and these functionalized printed metal structures were shown as excellent SERS substrates in enhancing the vibrational spectral features of Rhodamine B (RhB). The presence of TiO2 photocatalyst on the surface was shown to remove the RhB analyte from the surface under photochemical conditions, which enables the regeneration of SERS activity, and the substrate can be recycled. The migration of metals from the printed metal structures into the fractally ordered TiO2/Ag nanostructures was found to enhance the photocatalytic activity and increase the recyclability of these substrates. This study demonstrates the potential of 3D-printed Inconel metal substrates as next-generation recyclable SERS platforms, offering a substantial advancement over traditional colloidal, thin-film, flexible, and hard SERS substrates.

The Effect of Foreign Direct Investment and Economic Growth on Health: An Empirical Investigation for Türkiye

This study aims to investigate the effect of foreign direct investment (FDI) on health for the period of 1975-2018 in Türkiye by using a health production function approach. Life expectancy at birth which is the dependent variable in the study is used as a proxy for the average health status of Turkish citizens. FDI is defined as the ratio of foreign direct investment to GDP. In order to provide optimal estimates of cointegrating relationship, the Fully Modified OLS (FMOLS) developed by Phillips & Hansen (1990) is preferred as the main estimation method, as it allows for endogeneity of explanatory variables. The findings of the study point out that foreign direct investment inflows reduce life expectancy in Türkiye.

Time‐Resolved Optical Response of the Dicke's Model via the Nonequilibrium Green's Function Approach

Due to their conceptual appeal and computational convenience, two‐level systems (TLSs) and generalizations are used to investigate nonlinear behavior in quantum optics and assess the applicability of theoretical methods. Herein, the focus is on second‐harmonic generation (SHG) and, as system of interest, on the Dicke model, which consists of several TLSs inside an optical cavity. The main aspect addressed is the scope of nonequilibrium Green's function (NEGF) to describe the effect of inhomogeneities and electron–electron (e–e) interactions on the SHG signal. For benchmarking purposes, exact diagonalization (ED) results are also presented and discussed. SHG spectra obtained with NEGF and ED are found to be in very good mutual agreement in most situations. Furthermore, inhomogeneity in the TLS and e–e interactions reduce the SHG signal, and the reduction is stronger with inhomogeneity than with interactions. This trend is consistently noted across different (small to large) system sizes. Finally, a modified NEGF approach is proposed to account for cavity leakage, where the quantum photon fields are coupled to a bath of classical oscillators. As expected, within this mixed quantum‐classical scheme, a decrease in the intensity of the fluorescent spectra takes place depending on the entity of leakage.

Modeling oxygen transport in the brain: An efficient coarse-grid approach to capture perivascular gradients in the parenchyma.

Recent progresses in intravital imaging have enabled highly-resolved measurements of periarteriolar oxygen gradients (POGs) within the brain parenchyma. POGs are increasingly used as proxies to estimate the local baseline oxygen consumption, which is a hallmark of cell activity. However, the oxygen profile around a given arteriole arises from an interplay between oxygen consumption and delivery, not only by this arteriole but also by distant capillaries. Integrating such interactions across scales while accounting for the complex architecture of the microvascular network remains a challenge from a modelling perspective. This limits our ability to interpret the experimental oxygen maps and constitutes a key bottleneck toward the inverse determination of metabolic rates of oxygen. We revisit the problem of parenchymal oxygen transport and metabolism and introduce a simple, conservative, accurate and scalable direct numerical method going beyond canonical Krogh-type models and their associated geometrical simplifications. We focus on a two-dimensional formulation, and introduce the concepts needed to combine an operator-splitting and a Green's function approach. Oxygen concentration is decomposed into a slowly-varying contribution, discretized by Finite Volumes over a coarse cartesian grid, and a rapidly-varying contribution, approximated analytically in grid-cells surrounding each vessel. Starting with simple test cases, we thoroughly analyze the resulting errors by comparison with highly-resolved simulations of the original transport problem, showing considerable improvement of the computational-cost/accuracy balance compared to previous work. We then demonstrate the model ability to flexibly generate synthetic data reproducing the spatial dynamics of oxygen in the brain parenchyma, with sub-grid resolution. Based on these synthetic data, we show that capillaries distant from the arteriole cannot be overlooked when interpreting POGs, thus reconciling recent measurements of POGs across cortical layers with the fundamental idea that variations of vascular density within the depth of the cortex may reveal underlying differences in neuronal organization and metabolic load.

Tuning the potentials of aluminum phosphide nanotube photocatalyst for wastewater treatment through band gap engineering: a DFT study

The photocatalytic properties of semiconductor materials, which are controllable through the design of the bandgap structure, make them a promising catalyst for wastewater treatment. This work investigated the photocatalytic properties of single-walled aluminum phosphide nanotube (SWAlPNT) doped with different concentrations of boron (B) atoms for wastewater treatment. Analysis of the structural, electronic and optical properties of the SWAlPNT photocatalyst was performed using the density functional theory approach in terms of plane wave basis set and pseudopotential. SWAlPNT was found to be stable to B doping with 3.6% and 7.1% concentrations. The obtained formation energy values of 12.33 eV, 12.00 eV and 11.98 eV and also cohesive energies of −0.82, eV, −0.75 eV and 0.79 eV for pristine, 3.6% and 7.1% B-doped SWAlPNTs, revealed the systems’ well mechanical and thermodynamic stabilities. Results also revealed that cohesive energy decreases with an increase in concentration of B dopant, which significantly enhances efficient thermal stability. Electronic band gap calculations revealed that pristine SWAlPNT demonstrated a direct band gap value of 0.2 eV. Due to B doping, an indirect band gap value of 1.4 eV was obtained with 3.6% B-doped SWAlPNT, which agreed well with band gaps of other photocatalysts used for wastewater purification. Analysis using optical absorption spectra revealed that 3.6% B-doped system absorbs visible light while 7.1% doped system absorbs both visible and ultraviolet light. This study found both 3.6% and 7.1% B-doped SWAlPNT as suitable photocatalysts for wastewater treatment under solar irradiation, with the 3.6% B-doped system demonstrating relatively better performance for wastewater treatment.

Multidrug-Resistant Profiles in Non-Small Cell Lung Carcinoma Patient-Derived Cells: Implications for Personalized Approaches with Tyrosine Kinase Inhibitors.

The impact of tyrosine kinase inhibitors (TKIs) on multidrug resistance (MDR) in non-small cell lung carcinoma (NSCLC) is a critical aspect of cancer therapy. While TKIs effectively target specific signaling pathways of cancer cells, they can also act as substrates for ABC transporters, potentially triggering MDR. The aim of our study was to evaluate the response of 17 patient-derived NSCLC cultures to 10 commonly prescribed TKIs and to correlate these responses with patient mutational profiles. Using an ex vivo immunofluorescence assay, we analyzed the expression of the MDR markers ABCB1, ABCC1, and ABCG2, and correlated these data with the genetic profiles of patients for a functional diagnostic approach. NSCLC cultures responded differently to TKIs, with erlotinib showing good efficacy regardless of mutation burden or EGFR status. However, the modulation of MDR mechanisms by erlotinib, such as increased ABCG2 expression, highlights the challenges associated with erlotinib treatment. Other TKIs showed limited efficacy, highlighting the variability of response in NSCLC. Genetic alterations in signaling pathways associated with drug resistance and sensitivity, including TP53 mutations, likely contributed to the variable responses to TKIs. The relationships between ABC transporter expression, gene alterations, and response to TKIs did not show consistent patterns. Our results suggest that in addition to mutational status, performing functional sensitivity screening is critical for identifying appropriate treatment strategies with TKIs. These results underscore the importance of considering drug sensitivity, off-target effects, MDR risks, and patient-specific genetic profiles when optimizing NSCLC treatment and highlight the potential for personalized approaches, especially in early stages.

Complementary technology adoption and smallholder commercialization: Panel data evidence from Ethiopia

AbstractAgricultural transformation involves the transition from subsistence agriculture marked by cultivating crops for auto‐consumption to cultivating crops for output markets. This transition from subsistence agriculture to market‐oriented agriculture can be a key policy boost to economic development, but evidence on the key entry points to increasing smallholder commercialization remains scarce. We examine the relationship between the adoption of improved maize varieties (IMVs), inorganic fertilizers, and smallholder commercialization. We model commercialization as a two‐step decision process involving market participation and the extent of participation (sales quantity) conditional on participation. Given these two related steps, we estimate a double‐hurdle model in both linear and non‐linear forms. Employing a three‐wave panel dataset from Ethiopia, we use the household fixed effects and correlated random effects model with the control function approach. We find the adoption of IMVs to be significantly associated with both market participation and the extent of participation. This relationship is also true for fertilizers, where we show a positive association between fertilizer use and commercialization. Given the seeming complementarity in the use of both IMVs and fertilizers, we further estimate their joint adoption. We use the multinomial endogenous switching regression model where we show greater commercialization gains under joint adoption. These findings are in line with a growing literature supporting the bundling of agricultural technologies. Given these insights, we provide empirical and policy support to the scaling of agricultural technologies as they have the potential to induce agricultural transformation by unlocking market opportunities.

#2639 Unraveling complement activation profiles on endothelial cells in healthy donors using an ex vivo model

Abstract Background and Aims Complement is involved in numerous kidney diseases. However, functional approaches to properly examine individual's susceptibility to complement dysregulation are limited. Method We assessed ex vivo complement activation induced by sera from 38 healthy donors on resting microvascular endothelial cells (HMEC-1) with or without complement dysregulation by an anti-FH monoclonal antibody (OX-24 mAb). Following incubation, immunofluorescence was used to reveal and quantify membrane-bound C3c (evaluating C3b/iC3b) and C5b-9 with a computer-assisted method (H-score). Additionally, complement anaphylatoxins (C3a and C5a) were quantified in cell supernatants by ELISA. Further exploration of ex vivo complement activation profiles were conducted by next generation sequencing of a panel of alternative pathway genes in 32 donors. Results Increase in complement deposition on HMEC-1 surface was defined for a H-scoreC3c > 50 and/or a H-scoreC5b-9 > 30. Combined analysis of C3b/iC3b and C5b-9 deposition in 35 donors showed that one donor (2.8%) had an isolated increase in C3b/iC3b deposits, 3 (8.6%) had an isolated increase in C5b-9 deposits and one other (2.8%) had both increased C3b/iC3b and C5b-9 deposition. Genetic analysis of 32/38 donors revealed 3 heterozygous rare or low frequency missense variants in CFH (p.N1050Y and p.R1210C) and CFI (p.A76G) in 3/5 donors (60%) with increased complement deposition. Conclusion Our ex vivo model for measuring complement activation allowed the identification of distinct complement activation profiles among healthy donors, revealing genetic susceptibility in 3 donors. This new dynamic and functional model provides an exciting avenue for exploring the mechanisms governing complement dysregulation in various kidney diseases in research.

Deep lakes support higher zooplankton functional diversity than shallow lakes: A case study in lacustrine environments affected by mining tailings (lower Doce River basin, Brazil)

Abstract Tragic incidents involving mine tailings spills have impacted many aquatic ecosystems around the world. The massive mine tailings dam collapse of Fundão, which occurred in Brazil in 2015, affected several aquatic ecosystems, including shallow and deep lakes in the lower Doce River basin. Until now, the effects of mine tailings on the functional diversity of zooplankton remain poorly understood. We investigated the functional diversity of zooplankton (functional groups, functional richness [FRic] and functional evenness [FEve]) in shallow and deep lakes, exploring the influence of environmental variables and metals. In addition, trends in functional redundancy and functional vulnerability were also assessed to understand patterns of resilience in mining‐impacted ecosystems. Surveys were performed monthly on three deep and three shallow lakes affected by the dam failure, from October 2018 to September 2019. In the deep lakes, the zooplankton community was dominated by smaller filter‐feeders and omnivorous species, associated with cyanobacteria density and chlorophyll‐a. Medium‐sized filters were associated to iron, suspended particulate organic matter and total organic carbon in shallow lakes. The smaller filter‐feeders and omnivorous trophic groups had a higher contribution to increasing the functional diversity of zooplankton than medium‐sized filter‐feeders in both deep and shallow lakes. FRic and FEve were higher in deep lakes than in shallow lakes. Shallow lakes were highly vulnerable to species loss and functional diversity was modulated by environmental changes and metal pollution. Tropical shallow lakes impacted by mining tailings should receive particular attention in conservation plans, as a consequence of their high level of pollutant retention in comparison with deep lakes. In addition, we highlight the importance of using a functional approach to better understand the ecosystem changes resulting from the impacts of mine tailings on aquatic environments.

A functional autoregressive approach for modeling and forecasting short-term air temperature

A precise forecast of atmospheric temperatures is essential for various applications such as agriculture, energy, public health, and transportation. Modern advancements in technology have led to the development of sensors and other tools to collect high-frequency air temperature data. However, accurate forecasts are challenging due to their specific features including high dimensionality, non-linearity, seasonal dependency, etc. To address these forecasting challenges, this study proposes a functional modeling framework based on the components estimation technique by partitioning the air temperature time series into deterministic and stochastic components. The deterministic component that comprises daily and yearly seasonalities is modeled and forecasted using generalized additive modeling techniques. Similarly, the stochastic component that accounts for the short-term dynamics of the process is modeled and forecasted by a functional autoregressive model, autoregressive integrated moving average, and vector autoregressive models. To evaluate the performance of models, hourly air temperature data are collected from Islamabad, Pakistan, and one-day-ahead out-of-sample forecasts are obtained for a complete year. The forecasting results from all models are compared using the root mean squared error, mean absolute error, and mean absolute percentage error. The results suggest that the proposed FAR model performs relatively well compared to ARIMA and VAR models, resulting in lower out-of-sample forecasting errors. The findings of this research can facilitate informed decision-making across sectors, optimize resource allocation, enhance public safety, and promote socio-economic resilience.

Advancing statistical treatment of photolocomotor behavioral response study data.

Fish photolocomotor behavioral response (PBR) studies have become increasingly prevalent in pharmacological and toxicological research to assess the environmental impact of various chemicals. There is a need for a standard, reliable statistical method to analyze PBR data. The most common method currently used, univariate analysis of variance (ANOVA), does not account for temporal dependence in observations and leads to incomplete or unreliable conclusions. Repeated measures ANOVA, another commonly used method, has drawbacks in its interpretability for PBR study data. Because each observation is collected continuously over time, we instead consider each observation to be a function and apply functional ANOVA (FANOVA) to PBR data. Using the functional approach not only accounts for temporal dependency but also retains the full structure of the data and allows for straightforward interpretation in any subregion of the domain. Unlike the traditional univariate and repeated measures ANOVA, the FANOVA that we propose is nonparametric, requiring minimal assumptions. We demonstrate the disadvantages of univariate and repeated measures ANOVA using simulated data and show how they are overcome by applying FANOVA. We then apply one-way FANOVA to zebrafish data from a PBR study and discuss how those results can be reproduced for future PBR studies.

On a localization-in-frequency approach for a class of elliptic problems with singular boundary data

We consider a class of nonhomogeneous elliptic equations in the half-space with critical singular boundary potentials and nonlinear fractional derivative terms. The forcing terms are considered on the boundary and can be taken as singular measure. Employing a functional setting and approach based on localization-in-frequency and Littlewood–Paley decomposition, we obtain results on solvability, regularity, and symmetry of solutions.

First-principles study of hydrogen sulfide decomposition on Sc-Ti3C2O2 single-atom catalyst.

Hydrogen sulfide gas poses significant risks to both human health and the environment, with the potential to induce respiratory and neurological effects, and a heightened fatality risk at elevated concentrations. This article investigates the catalytic decomposition of H2S on a Sc-Ti3C2O2 single-atom catalyst(SAC) using the density functional theory-based first-principles calculation approach. Initially, the adsorption behavior of H2S on Ti3C2O2-MXene was examined, revealing weak physical adsorption between them. Subsequently, the transition metal atom Sc was introduced to the Ti3C2O2 surface, and its stability was studied, demonstrating high stability. Further exploration of H2S adsorption on Sc-Ti3C2O2 revealed direct dissociation of H2S gas molecules into HS* and H*, with HS* binding to Sc and H* binding to O on the Ti3C2O2 surface, resulting in OH groups. Using the transition state search method, the dissociation of H2S molecules on the SAC's surface was investigated, revealing a potential barrier of 2.45eV for HS* dissociation. This indicates that the H2S molecule can be dissociated into H2 and S with the action of the Sc-Ti3C2O2 SAC. Moreover, the S atom left on the catalyst surface can aggregate to produce elemental S8, desorbing on the catalyst surface, completing the catalytic cycle. Consequently, the Sc-Ti3C2O2 SAC is poised to be an efficient catalyst for the catalytic decomposition of H2S. The Dmol3 module in Materials Studio software based on density functional theory is used in this study. The generalized gradient approximation method GGA-PBE is used for the exchange-correlation function. The complete LST/QST and the NEB methods in the Dmol3 module were used to study the minimum energy path of the dissociation of hydrogen sulfide molecules on the catalyst surface.

Income inequality and household debt: A U.S. state-level spatial analysis

While most agree that the 2007–2008 financial bust stemmed from an excessive credit boom, researchers disagree about the causes of the boom amid income inequality, monetary excesses, and an unregulated credit market. Empirical findings on inequality's impact on credit booms are contradictory. This paper examines the impact of income inequality on household debt, utilizing U.S. state-level data from 1999 to 2015 within macroeconomic and credit market contexts. Diverging from prior research, it provides consistent and robust estimates by using the control function approach to identify exogenous variations in inequality and employing a spatial error panel model to remove significant cross-sectional dependence. The results indicate that inequality indices have a negative or insignificant effect on household debt, while monetary policy and credit market uncertainty also affect household debt. Thus, higher inequality is linked with credit contraction rather than expansion; rising inequality does not trigger a credit boom.

A combined metagenome and disease enrichment analysis of nitrosamines present in smokeless tobacco, wiz using molecular docking and functional annotation approach

Smokeless tobacco products (SLTs) are a major concern due to the associated health risks of the carcinogens, toxins, dynamic microbial system and other harmful chemicals present in them. Procured tobacco leaves are sweetened, flavored and processed to yield the various noncombustible forms of SLTs. These SLTs contain a discrete microbial ecosystem which may contribute to the formation of tobacco specific nitrosamines (TSNAs), endotoxins and other pro inflammatory components. In the present study Whole Metagenome Sequencing was carried out for the exploration of microbial communities followed by their functional profiling. In addition to this, novel targets for TSNAs were predicted using the Swiss Target Prediction tool. Further, disease enrichment analysis of various TSNAs present in Wiz was done using Molecular Docking and functional annotation approach using David database. Bacterial, fungal and viral species were found in the sample where more than 50 % of total bacterial species were Proteobacteria followed by Actinobacteria, Firmicutes, Apicomplexa, Bacteroidetes, Basidiomycota and Cyanobacteria phyla. Total 22,766 genes with 64.9 % GC content were found, which were associated with nitrogen metabolism, antibiotic resistance, multidrug transportation, multitoxins, and pro-inflammation. The presence of phages in wiz showed the possibility of horizontal gene transfer. The pathway enrichment analysis of various TSNAs of wiz were found to be associated with numerous diseases, such as Parkinson's disease, schizophrenia, mental depression, Hypertension, male infertility, Acute Kidney disease and various kinds of cancers.This study will help to understand the possible role of microbiota, TSNAs and their genetic contribution to the overall product's effect on human health. The raw data was submitted to NCBI Short Read Archive (SRA) under Bio Project accession number PRJNA837388.