Search Results (38)

Wastewater-based epidemiology is a robust, scalable, cost-effective, and high-performing tool to monitor and predict SARS-CoV-2 trends. We aimed to investigate whether this approach could be applied to influenza A/B viruses and respiratory syncytial virus (RSV) in Marseille, southern France. Wastewater concentrations of SARS-CoV-2, influenza A/B viruses, and RSV in Marseille were monitored by qPCR between January 2021 and October 2024. These concentrations were compared with the diagnosis numbers for the three viruses collected at public hospitals in Marseille, using cross-correlation analyses. The Granger causality test was used to determine whether wastewater concentrations can predict the number of clinical cases. SARS-CoV-2 and influenza virus concentrations in wastewater preceded the rise in the incidence of patient diagnoses by a lag of five days and nine/ten days, respectively. In contrast, for RSV, the rise in incidence of clinical cases preceded that of wastewater concentrations. We conclude that wastewater-based epidemiology is a powerful tool to monitor the level of circulation of these viruses independently of tests carried out on people. It enables earlier alerts than monitoring patients for SARS-CoV-2 and influenza symptoms. However, for RSV, it does not provide an early warning, and clinical data-based surveillance appears to be more suitable. Full article

Despite widespread adoption, traditional Agile project management practices often fail to ensure successful delivery of enterprise-scale software projects. One key limitation lies in the absence of a conceptually defined structure for the various types of Agile activities and their interactions. As a result, Agile methodologies typically lack formal indicators for evaluating the semantic content and progress status of project activities. Although widely used tools for Agile project management, such as Atlassian Jira, capture operational data, project status assessment interpretation remains largely subjective—relying on the experience and judgment of managers and team members rather than on a formal knowledge model or well-defined semantic attributes. As Agile project activities continue to grow in complexity, there is a pressing need for a modeling approach that captures their causal structure in order to describe the essential characteristics of the processes and ensure systematic monitoring and evaluation of the project. The complexity of the corresponding model must correlate with the causality of processes to avoid losing essential properties and to reveal the content of causal interactions. To address these gaps, this paper introduces a causal Agile process model that formalizes the internal structure and transformation pathways of Agile activity types. To our knowledge, it is the first framework to integrate a recursive, causally grounded structure into Agile management, enabling both semantic clarity and quantitative evaluation of project complexity and progress. The aim of the article is, first, to describe conceptually different Agile activity types from a causal modeling perspective, its internal structure and information transformations, and, second, to formally define the causal Agile management model and its characteristics. Each Agile activity type (e.g., theme, initiative, epic, user story) is modeled using the management transaction (MT) framework—an internal model of activity that comprises a closed-loop causal relationship among management function (F), process (P), state attribute (A), and control (V) informational flows. Using this framework, the internal structure of Agile activity types is normalized and the different roles of activities in internal MT interactions are defined. An important feature of this model is its recursive structure, formed through a hierarchy of MTs. Additionally, the paper presents classifications of vertical and horizontal causal interactions, uncovering theoretically grounded patterns of information exchange among Agile activities. These classifications support the derivation of quantitative indicators for assessing project complexity and progress at a given point in time, offering insights into activity specification completeness at hierarchical levels and overall project content completeness. Examples of complexity indicator calculations applied to real-world enterprise application system (EAS) projects are included. Finally, the paper describes enhancements to the Jira tool, including a causal Agile management repository and a prototype user interface. An experimental case study involving four Nordic EAS projects (using Scrum at the team level and SAFe at the program level) demonstrates that the Jira tool, when supplemented with causal analysis, can reveal missing links between themes and initiatives and align interdependencies between teams in real time. The causal Agile approach reduced the total number of requirements by an average of 13% and the number of change requests by 14%, indicating a significant improvement in project coordination and quality. Full article

Type 1 diabetes mellitus (T1DM) is a chronic autoimmune disorder characterized by the destruction of insulin-producing pancreatic beta cells, resulting in lifelong insulin dependence. While genetic susceptibility—particularly human leukocyte antigen (HLA) class II alleles—is a major risk factor, accumulating evidence implicates viral infections as potential environmental triggers in disease onset and progression. This narrative review synthesizes current findings on the role of viral pathogens in T1DM pathogenesis. Enteroviruses, especially Coxsackie B strains, are the most extensively studied and show strong epidemiological and mechanistic associations with beta-cell autoimmunity. Large prospective studies—including Diabetes Virus Detection (DiViD), The environmental determinans of diabetes in the young (TEDDY), Miljøfaktorer i utvikling av type 1 diabetes (MIDIA), and Diabetes Autoimmunity Study in the Young (DAISY)—consistently demonstrate correlations between enteroviral presence and the initiation or acceleration of islet autoimmunity. Other viruses—such as mumps, rubella, rotavirus, influenza A (H1N1), and SARS-CoV-2—have been investigated for their potential involvement through direct cytotoxic effects, immune activation, or molecular mimicry. Interestingly, certain viruses like varicella-zoster virus (VZV) and cytomegalovirus (CMV) may exert modulatory or even protective influences on disease progression. Proposed mechanisms include direct beta-cell infection, molecular mimicry, bystander immune activation, and dysregulation of innate and adaptive immunity. Although definitive causality remains unconfirmed, the complex interplay between genetic predisposition, immune responses, and viral exposure underscores the need for further mechanistic research. Elucidating these pathways may inform future strategies for targeted prevention, early detection, and vaccine or antiviral development in at-risk populations. Full article

This article aims to assess the conditions and prospects for biomass utilization in the Visegrad Group (V4) countries. Additionally, the relationship between biomass energy production and greenhouse gas emissions was examined. A key component of the analysis involved identifying potential directions for the development of biomass utilization in the pursuit of the sustainable development of agricultural enterprises. In relation to these research objectives, a hypothesis was formulated regarding the causal relationship between biomass energy consumption and economic growth, the abundance of natural resources, and income in reference to the European Union economies. Both static and dynamic panel studies were applied. The conducted research revealed the complex nature of the conditions influencing biomass utilization. The study period covered the years 2004–2022. A negative correlation was found between the use of biomass and greenhouse gas emissions. At the same time, factors favoring biomass utilization included economic growth, the level of natural resource consumption per capita, and government policies aimed at increasing the share of renewable resources in the economy. Full article

Background/Objectives: Diabetic kidney disease (DKD) is a common diabetic complication, driven by a multifactorial pathogenesis that includes various genetic components. However, the precise causative genes and their underlying biological pathways remain poorly understood. Methods: We performed a cross-tissue transcriptome-wide association study (TWAS) of DKD using expression quantitative trait loci (eQTL) data from 49 tissues in the Genotype—Tissue Expression (GTEx) version 8 (v8) resource. Five complementary analytical frameworks—sparse canonical correlation analysis (sCCA), functional summary-based imputation (FUSION), fine-mapping of causal gene sets (FOCUS), summary-data-based Mendelian randomization (SMR), and multi-marker analysis of genomic annotation (MAGMA)—were integrated to nominate candidate genes. Causal inference was refined using Mendelian randomization (MR), and biological significance was evaluated through pathway enrichment, protein interaction networks, and druggability profiling. Results: We identified 23 candidate genes associated with DKD risk, of which 13 were supported by MR analysis. Among these, 10 represent previously unreported susceptibility genes. Notably, four genes—HLA-DRB1, HLA-DRB5, NOTCH4, and CYP21A2—encode potentially druggable proteins, with HLA-DRB5 and CYP21A2 both qualifying as novel susceptibility genes and therapeutic targets. These genes converge on immune modulation, steroid biosynthesis, DNA repair, and transcriptional regulation—processes central to DKD pathogenesis. Conclusions: Our study represents the first systematic cross-tissue TWAS of DKD, revealing a prioritized set of genetically and functionally supported susceptibility genes. The identification of druggable targets among these genes provides critical insight into the mechanistic underpinnings of DKD and highlights their potential for future therapeutic development. These findings enhance our understanding of DKD pathophysiology and offer a foundation for precision medicine strategies in nephrology. Full article

(1) Background: Clinical evidence has raised concerns regarding a potential link between COVID-19 mRNA-based vaccines and the occurrence of thromboembolic events. So far, no research has explored the effects of this possible interaction in cancer patients undergoing active treatment. We leveraged prospective monitoring from the Vax-On-Third-Profile study to examine the development of venous thromboembolism (VTE) after the third dose of mRNA-BNT162b2 (tozinameran) and its association with antibody and lymphocyte responses. (2) Methods: Patients who had received a third dose of tozinameran and had not experienced any VTE in the previous 30 days were eligible. A serological evaluation was conducted before the booster vaccination (timepoint-1) and four weeks thereafter (timepoint-2) to measure antibody titers against the SARS-CoV-2 spike protein, as well as to determine the absolute counts of T-helper cells, T-cytotoxic cells, B cells, and NK cells. Data were acquired from November 2021 to October 2022 and analyzed from November 2022 to October 2023. (3) Results: The present study involved 429 patients who were given a third dose of tozinameran from 26 September to 30 October 2021. Among the active treatments of interest, 109 (25.4%) patients received targeted therapy, 111 (25.9%) received cytotoxic chemotherapy, 39 (9.1%) received immune checkpoint inhibitors, 21 (4.9%) received endocrine therapy, and 30 (7.0%) received a combination of chemotherapy and targeted agents in the eight weeks preceding the booster dosing. In addition, 119 (27.7%) patients who had discontinued any systemic therapy for at least 12 weeks accounted for the reference subgroup. After a median follow-up time of 10.6 (95% CI 8.1–11.7) months, we observed 31 venous thromboembolic events in the general population, for an overall incidence rate of 7.2% (95% CI 5.0–10.1). The median time to VTE development after booster immunization was 99 (95% CI 85–112) days. In a univariate comparison, patients exposed to targeted therapies (11.3% [95% CI 6.0–18.9]; p = 0.030) or immune checkpoint inhibitors (16.2% [95% CI 6.2–32.0]; p = 0.012) had a significantly higher incidence of VTE than the reference cohort (3.4% [95% CI 0.9–8.5]). Univariate analysis of immune responses showed that only dynamic changes pertaining to NK cell distributions correlated significantly with VTE occurrence. Multivariate regression analysis confirmed only a high-level NK cell response (OR 6.10 [9% CI 2.16–17.21]; p = 0.001), a history of thromboembolic events (OR 9.81 [3.99–24.13]; p < 0.001), and the presence of a central venous catheter (OR 5.02 [95% CI 1.84–13.67]; p = 0.002) as independently associated with an increased risk of VTE. (4) Conclusions: This prospective cohort study provides unprecedented evidence that cancer patients have no increased risk of developing VTE after the third dose of tozinameran, regardless of the type of active therapy. The specific pattern of lymphocyte response appears to increase thromboembolic risk, underlying immune dysregulation as a causal cofactor. These findings emphasize the need for additional monitoring after periodic COVID-19 vaccination in cancer patients. Full article

Clinical trials consistently demonstrate an inverse correlation between serum 25-hydroxyvitamin D [25(OH)D; calcifediol] levels and the risk of symptomatic SARS-CoV-2 disease, complications, and mortality. This systematic review (SR), guided by Bradford Hill’s causality criteria, analyzed 294 peer-reviewed manuscripts published between December 2019 and November 2024, focusing on plausibility, consistency, and biological gradient. Evidence confirms that cholecalciferol (D₃) and calcifediol significantly reduce symptomatic disease, complications, hospitalizations, and mortality, with optimal effects above 50 ng/mL. While vitamin D requires 3–4 days to act, calcifediol shows effects within 24 h. Among 329 trials, only 11 (3%) showed no benefit due to flawed designs. At USD 2/patient, D₃ supplementation is far cheaper than hospitalization costs and more effective than standard interventions. This SR establishes a strong inverse relationship between 25(OH)D levels and SARS-CoV-2 vulnerability, meeting Hill’s criteria. Vitamin D₃ and calcifediol reduce infections, complications, hospitalizations, and deaths by ~50%, outperforming all patented, FDA-approved COVID-19 therapies. With over 300 trials confirming these findings, waiting for further studies is unnecessary before incorporating them into clinical protocols. Health agencies and scientific societies must recognize the significance of these results and incorporate D₃ and calcifediol for prophylaxis and early treatment protocols of SARS-CoV-2 and similar viral infections. Promoting safe sun exposure and adequate vitamin D₃ supplementation within communities to maintain 25(OH)D levels above 40 ng/mL (therapeutic range: 40–80 ng/mL) strengthens immune systems, reduces hospitalizations and deaths, and significantly lowers healthcare costs. When serum 25(OH)D levels exceed 70 ng/mL, taking vitamin K₂ (100 µg/day or 800 µg/week) alongside vitamin D helps direct any excess calcium to bones. The recommended vitamin D dosage (approximately 70 IU/kg of body weight for a non-obese adult) to maintain 25(OH)D levels between 50–100 ng/mL is safe and cost-effective for disease prevention, ensuring optimal health outcomes. Full article

This study investigates the relationship between SARS-CoV-2 RT–PCR cycle threshold (Ct) values and key COVID-19 transmission and outcome metrics across five years of the pandemic in Jalisco, Mexico. Utilizing a comprehensive time-series analysis, we evaluated weekly median Ct values as proxies for viral load and their temporal associations with positivity rates, reproduction numbers (Rt), hospitalizations, and mortality. Cross-correlation and lagged regression analyses revealed significant lead–lag relationships, with declining Ct values consistently preceding surges in positivity rates and hospitalizations, particularly during the early phases of the pandemic. Granger causality tests and vector autoregressive modeling confirmed the predictive utility of Ct values, highlighting their potential as early warning indicators. The study further observed a weakening association in later pandemic stages, likely influenced by the emergence of new variants, hybrid immunity, changes in human behavior, and diagnostic shifts. These findings underscore the value of Ct values as scalable tools for public health surveillance and highlight the importance of contextualizing their analysis within specific epidemiological and temporal frameworks. Integrating Ct monitoring into surveillance systems could enhance pandemic preparedness, improve outbreak forecasting, and strengthen epidemiological modeling. Full article

Constant exposure to the atmospheric air polluted with particulate matter is considered to have a negative influence on human health, even if it is found at values that may not exceed the maximum allowable concentration. Starting from the correlation between atmospheric air polluted with PM and COVID-19 incidence/mortality, this research had as first objective to assess the exposure to an average concentration of PM₁₀ in Romania and, in particular, in Bucharest for a period of six years and the cumulative incidence of COVID-19 cases per 1000 inhabitants (continuing previous research, from 2020). Subsequently, we studied the cumulative incidence of COVID-19 cases per 1000 inhabitants until January 2022. Another research objective was to identify a possible association between the atmospheric air polluted with particulate matter, viruses (SARS-CoV-2) and aeroallergens (common ragweed). To achieve the first two proposed objectives, the research method used was a univariate statistical analysis, correlation and regression analysis, subsequently analyzing the data and comparing with the results obtained in the research conducted previously (2020). In the selection of data, which formed the basis of the last part of the research, we used the recommendations of the PRISMA-ScR Guidelines, which were useful and guided us in the proper conduct of the research and in obtaining results in line with the proposed purpose. The applied regression model showed that in Bucharest, 86.34% of the variation in the cases incidence is explained by the variation in the PM₁₀ concentration. In the second part of the research, we observed an exponential increase in the number of cases, without demonstrating a direct causal relationship with exposure to particulate matter air polluted. Otherwise, we additionally studied the data on the existence of a causal relationship between the increase of pollen in the atmospheric air over time and the incidence of SARS-CoV-2 infection, as well as the data that considered that there would be no causal relationship between these parameters. Full article

In viticulture, pathogens like the oomycete Plasmopara viticola, the causal agent of downy mildew, can cause severe yield loss and require extensive application of plant protection chemicals. Breeders are generating pathogen-resistant varieties exploiting American and Asian wild Vitis germplasm as sources of resistance. Several loci mediating resistance to P. viticola have been identified in the past but may be overcome by specifically adapted strains of the pathogen. Aiming to find and characterize novel loci, a cross population with Vitis amurensis ancestry was investigated searching for resistance-correlated quantitative trait loci (QTL). As a prerequisite, a genetic map was generated by analyzing the 244 F₁ individuals derived from a cross of the downy mildew susceptible Vitis vinifera cultivar ‘Tigvoasa’ and the resistant V. amurensis pBC1 breeding line We 90-06-12. This genetic map is based on the information from 627 molecular markers including 56 simple sequence repeats and 571 rhAmpSeq markers. A phenotypic characterization of the progeny showed a clear segregation of the resistance traits in the F₁ population after an experimental inoculation of leaf discs with downy mildew. Combining genetic and phenotypic data, an analysis for QTL revealed a major locus on linkage Group 9 that correlates strongly with the resistance to downy mildew. The locus was mapped to a region of about 80 kb on the PN40024 (12x.V2) grapevine reference genome. This genomic region co-localizes with the formerly identified locus Rpv10 from the grapevine cultivar ‘Solaris’. As we found different allele sizes of the locus-linked SSR markers than those characterizing the known Rpv10 locus and differences in the sequence of a candidate gene, it was regarded as a haplotype variant and named Rpv10.2. Full article

The aim of this research is to devise a continuous simulation model for predicting ship crane failures to increase their reliability and reduce unplanned downtime during cargo loading and unloading operations. To predict the condition of the hydraulic system, a database from the GALIOT software package was used for carrying out maintenance on cranes at m/v “O” over a period of 120,000 working hours. In the research, fault tree analysis (FTA) was used to identify causal relationships between system failures and basic events, while the Markov mathematical model was used to model the system state and predict transitions between different failure states. A system dynamics simulation model was developed to simulate the behavior of a system using POWERSIM PowerSim Constructor 2.5.d (4002), and regression analysis was performed to analyze the simulation results and understand the relationships between dependent and independent variables. The results show that a model for predicting failures in the hydraulic motors and pumps of ship cranes was developed, and the Markov model makes it possible to estimate the frequency of transitions between states under the condition that the sum of reliability equals one. The simulation model shows high reliability of the cranes and a constant frequency of failures throughout the 120,000 operating hours, while the regression analysis confirms the validity of the simulation model and shows a strong correlation between the analyzed variables. These models are used to improve the planning of ship crane maintenance, reduce unplanned downtime, and predict and promptly detect failures, which overall minimizes maintenance costs and failures. Full article

Causal discovery is central to human cognition, and learning directed acyclic graphs (DAGs) is its foundation. Recently, many nature-inspired meta-heuristic optimization algorithms have been proposed to serve as the basis for DAG learning. However, a single meta-heuristic algorithm requires specific domain knowledge and empirical parameter tuning and cannot guarantee good performance in all cases. Hyper-heuristics provide an alternative methodology to meta-heuristics, enabling multiple heuristic algorithms to be combined and optimized to achieve better generalization ability. In this paper, we propose a multi-population choice function hyper-heuristic to discover the causal relationships encoded in a DAG. This algorithm provides a reasonable solution for combining structural priors or possible expert knowledge with swarm intelligence. Under a linear structural equation model (SEM), we first identify the partial v-structures through partial correlation analysis as the structural priors of the next nature-inspired swarm intelligence approach. Then, through partial correlation analysis, we can limit the search space. Experimental results demonstrate the effectiveness of the proposed methods compared to the earlier state-of-the-art methods on six standard networks. Full article

Manufacturing enterprises face a strategic challenge in managing risks, as safety concerns can result in huge costs for employee wellbeing and business success. However, there is no clear link between using diverse instruments to assess and measure safety performance and the culture and climate of safety in the workplace, which is likely due to differing perspectives on the topic. This study explores the influence of safety culture and climate on safety performance and on the mediating role of employee engagement in the Ethiopian manufacturing sector. This study was conducted using a quantitative research methodology 368, where three hundred and sixty-eight respondents from five large-scale industrial manufacturing enterprises were selected through purposive sampling. A combination of techniques was used, including structural equation modeling, growth paths, and correlation matrix, and these were performed using the SPSS/AMOS v. 24 software suites. These methods established a causal relationship between safety culture, safety climate, and safety performance. The study’s main finding is that safety culture significantly impacts safety performance, which is followed by safety climate. Additionally, employee engagement played a significant mediating role between safety culture and safety performance, as well as between safety climate and safety performance. Based on these results, policymakers and practitioners in large-scale manufacturing enterprises in Ethiopia should prioritize improving the safety culture and climate of their workplaces to enhance safety performance and overall safety. Full article

SARS-CoV-2 is the causal agent of COVID-19; the first report of SARS-CoV-2 infection was in December 2019 in Wuhan, China. This virus has since caused the largest pandemic in history, and the number of deaths and infections has been significant. Nevertheless, the development of vaccines has helped to reduce both deaths and infections. Comorbidities such as diabetes, hypertension, heart and lung diseases, and obesity have been identified as additional risk factors for infection and the progression of COVID-19. Additionally, latent toxoplasmosis has been reported to be a risk factor for acquiring COVID-19 in some studies, but other studies have suggested a negative association between these two infections. Furthermore, in patients after vaccination or with COVID-19 and coinfection, an increase in the lethality and mortality of toxoplasmosis has been observed. Therefore, the objective of the current study is to determine the association of toxoplasmosis with COVID-19 in patients diagnosed with COVID-19. Serum samples from 384 patients previously diagnosed with COVID-19 using IgG antibodies against the S1/S2 antigens of SARS-CoV-2 were collected. Subsequently, anti-Toxoplasma IgG and IgM antibodies were analyzed with ELISA. Statistical analysis was performed using SPSS Version 20.0 frequencies, percentages, 2 × 2 tables, and the Pearson correlation coefficient. IgG and IgM anti-Toxoplasma antibodies were positive in 105/384 (27.34%) and (26/191) 13.6% of patients, respectively. The positivity for both infections was higher in patients aged >40 years old. Subjects who were overweight or obese were mainly positive for both IgG antibodies against S1/S2 SARS-CoV-2 and Toxoplasma antibodies. In conclusion, the coinfection rate was 21.7%. The prevalence of S1/S2 SARS-CoV-2 was 308/384 (80.2%), and the percentage of Toxoplasma antibodies was 27.34%. Full article

The coronavirus disease 2019 (COVID-19) pandemic is a universal emergency public health issue. A large proportion of the world’s population has had several spike antigen exposures to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and/or COVID-19 vaccinations in a relatively short-term period. Although sporadic hematopoietic adverse events after COVID-19 vaccine inoculation were reported, there is currently no sufficient evidence correlating anti-spike protein immune responses and hematopoietic adverse events of vaccinations. We reported the first case of Ph-positive B-cell acute lymphoblastic leukemia (ALL) occurring after a bivalent mRNA COVID-19 vaccine inoculation. The otherwise healthy 43-year-old female patient had a total of six spike antigen exposures in the past 1.5 years. Informative pre-vaccine tests and bone marrow study results were provided. Although the causal relationship between bivalent vaccinations and the subsequent development of Ph–positive B-cell ALL cannot be determined in the case report, we propose that anti-spike protein immune responses could be a trigger for leukemia. Clinicians must investigate the hematopoietic adverse events closely after COVID-19 vaccinations. Further pre-clinical studies to investigate the safety of bivalent mRNA COVID-19 vaccine are required. Full article