The critical role of groundwater in meeting diverse needs, including drinking, industrial, and agricultural, highlights the urgency of effective resource management. Excessive groundwater extraction, especially in coastal regions including Urmia Plain in NW Iran, disrupts the equilibrium between freshwater and saline boundaries within aquifers. Influential parameters governing seawater intrusion-groundwater occurrence (G), aquifer hydraulic conductivity (A), the height of groundwater level above the mean sea level (L), distance from the shore (D), impact of the existing status of seawater intrusion (I), and thickness of the saturated aquifer (T)-merge to shape the GALDIT vulnerability index for coastal aquifers. This study enriches the GALDIT framework by incorporating two additional hydrogeological variables: hydraulic gradient (i) and pumping rate (P). This expansion produces seven distinct vulnerability maps (GALDIT, GAiDIT, GAiDIT-P, GALDIT-i, GALDIT-iP, GALDIT-P, GAPDIT). In the Urmia Plain, the traditional GALDIT index reveals vulnerability values ranging from 2 to 8.1, categorized into six classes from negligible to very high vulnerability. However, the modified indices, GAiDIT and GAiDIT-P, yield a three-class categorization, ranging from low to high vulnerability. The introduction of the \"i\" and \"P\" parameters in GALDIT-i and GALDIT-iP enhances the precision of vulnerability mapping, altering class distribution and intensifying vulnerability ratings. The eastern, central, and coastal areas of the Urmia Plain demonstrate high to very high vulnerability levels, in contrast to the lower vulnerability observed in the western regions. Both the GALDIT-P (r = 0.82) and GALDIT-iP (r = 0.81) indices show strong correlations with Cl concentration, thereby improving mapping accuracy over the traditional GALDIT index (r = 0.72). A sensitivity analysis highlights the critical influence of the \"i\" parameter, suggesting its weighting should be revised. Parameter recalibration serves to amplify the significance of \"G,\" \"L,\" \"D,\" and \"i\" parameters, while diminishing others. The integration of multiple hydrogeological variables considerably enhances the precision of groundwater vulnerability assessments.

Tuberculosis (TB) remains a significant global health concern, necessitating effective control strategies. This article presents a mathematical model to evaluate the comparative effectiveness of medical mask usage and case detection in TB control. The model is constructed as a system of ordinary differential equations and incorporates crucial aspects of TB dynamics, including slow-fast progression, medical mask use, case detection, treatment interventions and differentiation between symptomatic and asymptomatic cases. A key objective of TB control is to ensure that the reproduction number, R c , remains below unity to achieve TB elimination or persistence if R c exceeds 1. Our mathematical analysis reveals the presence of a transcritical bifurcation when the R c = 1 signifies a critical juncture in TB control strategies. These results confirm that the effectiveness of case detection in diminishing the endemic population of symptomatic individuals within a TB-endemic equilibrium depends on exceeding a critical threshold value. Furthermore, our model is calibrated using TB yearly case incidence data per 100 000 population from Indonesia, India, Lesotho and Angola. We employed the bootstrap resampling residual approach to assess the uncertainty inherent in our parameter estimates which provides a comprehensive distribution of the parameter values. Despite a declining trend in new incidence, these four countries exhibit a reproduction number greater than 1, indicating persistent TB cases in the presence of ongoing TB control programmes. We employ the partial rank correlation coefficient in conjunction with the Latin hypercube sampling method to conduct a global sensitivity analysis of the R c parameter for each fitted parameter in every country. We find that the medical mask use is more sensitive to reduce R c compared with the case detection implementation. To further gain insight into the necessary control strategy, we formulated an optimal control and studied the cost-effectiveness analysis of our model to investigate the impact of case detection and medical mask use as control measures in TB spread. Cost-effectiveness analysis demonstrates that combining these interventions emerges as the most cost-effective strategy for TB control. Our findings highlight the critical importance of medical masks and their efficacy coupled with case detection in shaping TB control dynamics, elucidating the primary parameter of concern for managing the control reproduction number. We envisage our findings to have implications and be vital for TB control if implemented by policymakers and healthcare practitioners involved in TB control efforts.

UNASSIGNED: The causal associations between dietary intake and the risk and severity of Inflammatory Arthritis (IA) are currently unknown.
UNASSIGNED: In this study, we aimed to investigate the causal relationship between nine dietary categories (30 types of diet) and IA using Mendelian randomization (MR).
UNASSIGNED: We analyzed data from 30 diets and IA in a genome-wide association study (GWAS). Single nucleotide polymorphisms (SNPs) that could influence the results of MR analyses were screened out through the Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) test. SNPs were analyzed through two-sample bidirectional MR using inverse variance weighting, MR-Egger regression, and weighted median method. The multiplicity and heterogeneity of SNPs were assessed using MR-Egger intercept term tests and Cochran\'s Q tests. FDR correction was used to correct the p-values.
UNASSIGNED: IVW results showed that Beef intake [Odds ratio (OR) = 2.862; 95% confidence interval (CI), 1.360-6.021, p = 0.006, p_fdr < 0.05] was positively associated with rheumatoid arthritis(RA); Dried fruit intake (OR = 0.522; 95% CI, 0.349-0.781, p = 0.002, p_fdr < 0.05), and Iron intake (OR = 0.864; 95%CI, 0.777-0.960, p = 0.007, p_fdr < 0.05) were negatively associated with RA, all of which were evidence of significance. Fresh fruit intake (OR = 2.528. 95% CI, 1.063-6.011, p = 0.036, p_fdr > 0.05) was positively associated with psoriatic arthritis (PsA); Cheese intake (OR = 0.579; 95% CI, 0.367-0.914, p = 0.019, p_fdr > 0.05) was negatively associated with PsA; both were suggestive evidence. Processed meat intake (OR = 0.238; 95% CI, 0.100-0.565, p = 0.001, p_fdr < 0.05) was negatively associated with reactive arthritis (ReA), a protective factor, and significant evidence. All exposure data passed the heterogeneity check (Cochrane\'s Q test p > 0.05) and no directional pleiotropy was detected. Leave-one-out analyses demonstrated the robustness of the causal relationship in the positive results.
UNASSIGNED: Our study presents genetic evidence supporting a causal relationship between diet and an increased risk of IA. It also identifies a causal relationship between various dietary modalities and different types of IA. These findings have significant implications for the prevention and management of IA through dietary modifications.

The interaction between the immune system and the brain, crucial for blood-brain barrier integrity, is a potential factor in migraine development. Although there\'s evidence of a connection between immune dysregulation and migraine, a clear causal link has been lacking. To bridge this knowledge gap, we performed a two-sample Mendelian randomization (MR) analysis of 731 immune cell phenotypes to determine their causality with migraine, of which parameters included fluorescence, cell abundance, count, and morphology. Sensitivity and pleiotropy checks validated our findings. After applying a false discovery rate correction, our MR study identified 35 of 731 immune phenotypes with a significant causal link to migraine (p < 0.05). Of these, 24 showed a protective effect (inverse variance weighting : p < 0.05, odds ratio <1), and 11 were risk factors (inverse variance weighting : p < 0.05, odds ratio >1). Although limited by population sample size and potential population-specific genetic variations, our study uncovers a significant genetic link between certain immune cell markers and migraine, providing new insights into the disorder\'s pathophysiology. These discoveries are crucial for developing targeted biomarkers and personalized treatments. The research enhances our understanding of immune cells\' role in migraine and may substantially improve patient outcomes and lessen its socio-economic impact.

In developing countries, informal sector is the primary job provider for a significant portion of the workforce. This study aims to analyze how jobs in the informal sector affect the unemployment dynamics of developing nations. To achieve this goal, we formulate a nonlinear mathematical model by categorizing the considered workforce into three distinct classes: unemployed, employed, and self-employed, and include a separate dynamic variable to represent vacancies within the informal sector. The proposed model is analyzed using the qualitative theory of dynamical systems. A threshold quantity known as the reproduction number is derived and using this, one can compute the job generation rate necessary to stabilize the system. It is observed that variations in the reproduction number lead to qualitative changes, such as transcritical (forward or backward) and saddle-node bifurcations in the formulated system. Moreover, we propose an optimal control problem to determine an optimal strategy for government policy implementation in enhancing the employment rate of unemployed individuals and promoting the self-employment of informal employees inside the informal sector. Further, the analytical findings are validated numerically. The obtained results suggest that promoting the self-employment of informal employees for job generation effectively reduces unemployment.

The recent mpox outbreak (in 2022-2023) has different clinical and epidemiological features compared with previous outbreaks of the disease. During this outbreak, sexual contact was believed to be the primary transmission route of the disease. In addition, the community of men having sex with men (MSM) was disproportionately affected by the outbreak. This population is also disproportionately affected by HIV infection. Given that both diseases can be transmitted sexually, the endemicity of HIV, and the high sexual behavior associated with the MSM community, it is essential to understand the effect of the two diseases spreading simultaneously in an MSM population. Particularly, we aim to understand the potential effects of HIV on an mpox outbreak in the MSM population. We develop a mechanistic mathematical model of HIV and mpox co-infection. Our model incorporates the dynamics of both diseases and considers HIV treatment with anti-retroviral therapy (ART). In addition, we consider a potential scenario where HIV infection increases susceptibility to mpox, and investigate the potential impact of this mechanism on mpox dynamics. Our analysis shows that HIV can facilitate the spread of mpox in an MSM population, and that HIV treatment with ART may not be sufficient to control the spread of mpox in the population. However, we showed that a moderate use of condoms or reduction in sexual contact in the population combined with ART is beneficial in controlling mpox transmission. Based on our analysis, it is evident that effective control of HIV, specifically through substantial ART use, moderate condom compliance, and reduction in sexual contact, is imperative for curtailing the transmission of mpox in an MSM population and mitigating the compounding impact of these intertwined epidemics.

This study presents a significant contribution to the field of chemical kinetics by providing a detailed analysis of a multi-step chemical kinetic process using ordinary differential equations (ODEs). The aim is to describe complex chemical processes\' kinetics and the steady-state behavior of chemical species. The research employs reduction techniques to simplify the model by separating fast and slow processes based on their time scales, with a focus on a two-step reversible reaction mechanism. Special consideration is given to the phase flow of solution trajectories near equilibrium points, providing a clear depiction of system behavior. MATLAB simulations demonstrate the physical properties of observed data, while sensitivity analysis reveals parameters\' impact on species behavior. Overall, this study enhances our understanding of chemical kinetics and offers insights into modeling complex reaction processes, with implications for various applications in chemistry and related fields.

Introduction: Numerical modeling of the intervertebral disc (IVD) is challenging due to its complex and heterogeneous structure, requiring careful selection of constitutive models and material properties. A critical aspect of such modeling is the representation of annulus fibers, which significantly impact IVD biomechanics. This study presents a comparative analysis of different methods for fiber reinforcement in the annulus fibrosus of a finite element (FE) model of the human IVD. Methods: We utilized a reconstructed L4-L5 IVD geometry to compare three fiber modeling approaches: the anisotropic Holzapfel-Gasser-Ogden (HGO) model (HGO fiber model) and two sets of structural rebar elements with linear-elastic (linear rebar model) and hyperelastic (nonlinear rebar model) material definitions, respectively. Prior to calibration, we conducted a sensitivity analysis to identify the most important model parameters to be calibrated and improve the efficiency of the calibration. Calibration was performed using a genetic algorithm and in vitro range of motion (RoM) data from a published study with eight specimens tested under four loading scenarios. For validation, intradiscal pressure (IDP) measurements from the same study were used, along with additional RoM data from a separate publication involving five specimens subjected to four different loading conditions. Results: The sensitivity analysis revealed that most parameters, except for the Poisson ratio of the annulus fibers and C01 from the nucleus, significantly affected the RoM and IDP outcomes. Upon calibration, the HGO fiber model demonstrated the highest accuracy (R2 = 0.95), followed by the linear (R2 = 0.89) and nonlinear rebar models (R2 = 0.87). During the validation phase, the HGO fiber model maintained its high accuracy (RoM R2 = 0.85; IDP R2 = 0.87), while the linear and nonlinear rebar models had lower validation scores (RoM R2 = 0.71 and 0.69; IDP R2 = 0.86 and 0.8, respectively). Discussion: The results of the study demonstrate a successful calibration process that established good agreement with experimental data. Based on our findings, the HGO fiber model appears to be a more suitable option for accurate IVD FE modeling considering its higher fidelity in simulation results and computational efficiency.

BACKGROUND: The mucosal barrier\'s immune-brain interactions, pivotal for neural development and function, are increasingly recognized for their potential causal and therapeutic relevance to irritable bowel syndrome (IBS). Prior studies linking immune inflammation with IBS have been inconsistent. To further elucidate this relationship, we conducted a Mendelian randomization (MR) analysis of 731 immune cell markers to dissect the influence of various immune phenotypes on IBS. Our goal was to deepen our understanding of the disrupted brain-gut axis in IBS and to identify novel therapeutic targets.
OBJECTIVE: To leverage publicly available data to perform MR analysis on 731 immune cell markers and explore their impact on IBS. We aimed to uncover immunophenotypic associations with IBS that could inform future drug development and therapeutic strategies.
METHODS: We performed a comprehensive two-sample MR analysis to evaluate the causal relationship between immune cell markers and IBS. By utilizing genetic data from public databases, we examined the causal associations between 731 immune cell markers, encompassing median fluorescence intensity, relative cell abundance, absolute cell count, and morphological parameters, with IBS susceptibility. Sensitivity analyses were conducted to validate our findings and address potential heterogeneity and pleiotropy.
RESULTS: Bidirectional false discovery rate correction indicated no significant influence of IBS on immunophenotypes. However, our analysis revealed a causal impact of IBS on 30 out of 731 immune phenotypes (P < 0.05). Nine immune phenotypes demonstrated a protective effect against IBS [inverse variance weighting (IVW) < 0.05, odd ratio (OR) < 1], while 21 others were associated with an increased risk of IBS onset (IVW ≥ 0.05, OR ≥ 1).
CONCLUSIONS: Our findings underscore a substantial genetic correlation between immune cell phenotypes and IBS, providing valuable insights into the pathophysiology of the condition. These results pave the way for the development of more precise biomarkers and targeted therapies for IBS. Furthermore, this research enriches our comprehension of immune cell roles in IBS pathogenesis, offering a foundation for more effective, personalized treatment approaches. These advancements hold promise for improving IBS patient quality of life and reducing the disease burden on individuals and their families.

The temperature stratification in reservoirs post-construction carries substantial environmental implications. A MIKE11-2DV model was developed to simulate yearly water temperature changes in the newly established Qincun Reservoir. Sensitivity analysis was performed to assess the influence of eight key parameters on the model\'s performance. Linear and Boltzmann curves were employed to fit water temperature profiles and extract four features for quantitative sensitivity analyses. In addition, a comparative analysis was conducted considering two different withdrawal scenarios. The SSI were employed for the assessment of thermal stratification. The MIKE11-2DV model demonstrated a high accuracy in simulating hydrodynamics and water temperature in the monomictic reservoir. A sensitivity analysis showed varying levels of sensitivity among model parameters. Specifically, the hypolimnetic water temperature was highly sensitive to the vertical viscosity factor but almost insensitive to the horizontal factor. Additionally, the light attenuation coefficient and constant in Beer\'s law significantly influenced the thermocline. Radiation and evaporation parameters affected overall the water temperature, maintaining a stable \"shape\". Furthermore, the initial scenarios simulation results showed that initial water temperature significantly affected the hypolimnion. The analysis of the thermal structure based on two water intake scenarios revealed that multi-level withdrawal had a higher Schmidt\'s Stability Index (SSI) and a longer stratified period compared to single-level withdrawal. During the fish breeding season, using multi-level water intake resulted in higher outlet temperatures than single-level water intake. The SSI reflected both temporal and spatial heterogeneity. Hysteresis behavior was observed between SSI and air temperature, with the hysteresis loops\' direction being influenced by different water intake levels. Enhanced hysteresis was observed in deeper reservoir segments during multi-level water intake scenario. These findings provide novel insights for interpreting thermal stratification in reservoirs.