Search Results (7,509)

Viral and fungal diseases of greenhouse strawberries lead to significant crop losses, while traditional uniform spraying schemes do not account for the actual distribution of infection foci or changes in the microclimate. This paper proposes an integrated system for greenhouse farms that combines a stochastic SIRS model of the epidemic process with a microclimate-dependent infection coefficient β_eff(t), a computer vision module based on a lightweight YOLOv10n detector, and a mobile sprayer robot. For three sets of parameters corresponding to moderate infection, outbreak, and suppression scenarios, ensemble simulations are performed (100 realizations per scenario). The results show that the maximum number of infected plants reaches approximately 690 out of 1000 in the outbreak scenario and only about 28 out of 1000 in the suppression scenario, reflecting the effect of timely microclimate correction and local spraying. The YOLOv10n detector is used as a sensor to determine the proportion of affected plants I(0)/N and provides automatic formation of the initial conditions of the population model. The resulting forecasts then serve as the basis for selecting one of three operating modes for the spraying robot (observation, microclimate correction, local treatment). Unlike existing works that consider disease detection, epidemiological models, or robotic spraying separately, this paper proposes a unified closed-loop scheme of “computer vision—stochastic model—mobile robot,” linking detection quality with epidemic process forecasting and treatment strategy. In this study, the feasibility of the proposed system was examined through numerical simulations, detector-level performance evaluation, and offline image-based integrated validation of the detector-to-decision workflow. Full closed-loop experiments in a real greenhouse environment are planned for future work. Full article

Background: In recent years, the severity of COVID-19 has diminished. However, some patients progressed to respiratory failure, necessitating intubation and mechanical ventilation. This study investigated the impact of variants of concern and vaccination status on mortality in mechanically ventilated patients. Method: We conducted a retrospective analysis of the medical records of intubated COVID-19 patients from 1 January 2021, to 31 December 2023. Patients who received at least one dose of a vaccine were classified as vaccinated, and variant types were classified based on the dominant variant reported by the Taiwan Centers for Disease Control. The primary outcome measured was time from intubation to all-cause in-hospital death. Result: A total of 254 patients were analyzed, comprising 65 patients infected with the Alpha variant and 189 with the Omicron variant. Clinical data, including variant type, vaccination status, and SOFA score at the time of intubation, were meticulously recorded. The overall mortality rate was 40%, with two epidemic surges occurring in 2021 and 2022. Infection with the Alpha variant was associated with a significantly higher risk of mortality (adjusted hazard ratio = 5.42 (2.78–10.7); p < 0.01). Key prognostic factors identified included age, body mass index, SOFA score, and serum bicarbonate levels. Conclusions: The overall mortality rate remained notably high. The study identified several factors associated with increased mortality risk, including older age, higher SOFA scores, Alpha variant infection, decreased serum bicarbonate levels, and lower BMI. However, vaccination status was not a significant prognostic indicator. Full article

Vertical transmission of plant pathogenic viruses is an important component of viral persistence, survival, and spread in agricultural production systems. This type of transmission is of considerable economic significance as it can cause major crop losses by serving as the initial focus of infection for future epidemics. Vertical transmission occurs when a virus is passed on to offspring either by direct invasion of the developing seed embryo from infected mother plants or through infected pollen grains after fertilization. We have recently demonstrated via high-throughput sequencing that mature seeds of the agriculturally important forage crop alfalfa (Medicago sativa L.) are associated with a broad range of viruses, some of which could potentially spread over long distances via seed. With the exception of the alfalfa mosaic virus, little is currently known about viral transmission through alfalfa pollen and its subsequent impact on the disease epidemiology of the crop. The objective of this study was to screen pollen from diverse alfalfa genotypes for pathogenic viruses and assess their risk of transmission. The pollen was collected from alfalfa genotypes selected for fungal disease resistance and agronomic performance in the USDA ARS pre-breeding program in Prosser, WA. Full article

White mold caused by Sclerotinia sclerotiorum (Lib.) de Bary continues to threaten yield and quality and remains a stubborn, sometimes unpredictable constraint in many cropping systems. The pathogen’s broad host range and its capacity to persist for years as sclerotia mean that fields can carry risk long after visible symptoms fade. Disease development is often driven by short windows of favorable temperature and moisture that promote germination and ascospore release and dispersal, while myceliogenic infection from soil-borne sclerotia can also initiate disease directly. Yet dependable control is still undermined by durable inoculum, limited stable host resistance, variable biocontrol performance, and shrinking chemical options together with fungicide resistance risk. Here we consolidate current understanding and ongoing uncertainties around sclerotial formation and germination cues, the environmental drivers that shape epidemic onset, and the processes governing host colonization, including the roles of cell wall-degrading enzymes, oxalic acid, and redox regulation, as well as the continuing debate over necrotrophic versus hemibiotrophic phases. Management is considered from a practical perspective, covering cultural risk reduction, forecasting-guided fungicide programmes supported by resistance-management principles, and biological control strategies targeting sclerotia. Across systems, the evidence points to the same lesson: single tactics rarely remain reliable under field variability, whereas integrated packages that reduce soil inoculum and align interventions with risk are more durable. Future priorities include resolving early infection events, improving prediction of carpogenic germination under changing climates, increasing the consistency of biocontrol, and accelerating resistance breeding supported by genomic resources. Full article

Porcine epidemic diarrhea virus (PEDV) causes acute diarrhea, dehydration and death in piglets, resulting in significant economic losses in the pig industry. It is crucial to identify the pathogenesis and mechanism between host–PEDV interactions. In our study, we performed transcriptomic and metabolomic analyses in PEDV-infected Large White (LW) pigs. PEDV infection caused blunted and fused intestinal villi, necrosis of the intestinal mucosal epithelial cells and atrophy of intestinal glands. Transcriptomic and metabolomic analyses revealed 692 differentially expressed genes and 1485 differential metabolites, respectively. Among them, differentially expressed genes were enriched in virion assembly, lipoprotein metabolic process and PPAR signaling pathway. Differential metabolites were enriched in primary bile acid biosynthesis and lipoic acid metabolism. An integrated analysis of the transcriptome and metabolome revealed that differentially expressed genes and metabolites were co-enriched in steroid hormone biosynthesis and bile secretion. In addition, key metabolites Dehydroepiandrosterone (DHEA) and Estriol in steroid hormone biosynthesis both inhibited PEDV infection and alleviated the excessive inflammatory response in vitro. Collectively, our study constructed a multi-omics landscape of PEDV infection in LW pigs, providing potential targets for developing metabolic-targeted antiviral interventions. Full article

The porcine epidemic diarrhea virus (PEDV) causes a gastrointestinal disease generating mortality rates approaching 100% in piglets worldwide. The S glycoprotein of PEDV is the main target for the development of vaccines. Two vaccines approved by the Ministry of Agriculture and Rural Development are used in Mexico: the first vaccine is based on an inactivated virus isolated more than a decade ago, whereas the second vaccine is based on mRNA technology. The most important tool for controlling PEDV outbreaks is vaccination; however, coronaviruses are characterized by the accumulation of multiple mutations, which compromise the immune response elicited by outdated vaccines. In this work, we classified the Mexican strains of PEDV reported so far in GenBank, according to their genotypes. Subsequently, we searched for B and T cell epitopes conserved in Mexican PEDV strains using bioinformatic tools. In addition, we explored whether these epitopes can induce allergies, autoimmunity, and/or toxic effects. Next, we determined the localization of B cell epitopes in the S glycoprotein using the protein crystal and protein modeling of several S glycoproteins. Finally, we carried out molecular docking analysis to assess whether these T cell epitopes could interact with the peptide-binding groove of the Swine Leukocyte Antigens (SLAs). Five conserved B cell epitopes were found to be exposed on the surface of the S glycoprotein, whereas several promiscuous CTL and HTL epitopes were bound, with low free energy, to the peptide-binding grooves of SLA-I and SLA-II, respectively. The best epitopes were used to generate a plasmid carrying the sequence to produce a recombinant protein. This plasmid was used for transfection experiments in PK-15 cell culture. The B cell epitopes reported here were recognized by the sera from pigs infected with PEDV but not by the sera from uninfected animals. These results justify future evaluations of the ability of these epitopes to stimulate cytokine production by T cells, antibody generation, and their neutralizing activity. Full article

Prediabetes is a critical precursor to type 2 diabetes (T2DM) and cardiometabolic diseases, yet its burden in Oman remains understudied. Leveraging data from Oman’s 2023 National Screening Program, this study quantifies the prevalence of prediabetes and its risk profiles among adults in Muscat Governorate—providing urgent evidence to guide diabetes prevention strategies in the Gulf region. Objectives: To estimate the prevalence of prediabetes and identify associated risk factors among Omani adults screened at primary health centers in Muscat Governorate (2023), given its critical role in preventing type 2 diabetes mellitus (T2DM) progression. Methods: This cross-sectional study analyzed data from Oman’s national screening program. Socio-demographics, clinical parameters (blood pressure, body mass index [BMI]), and laboratory results (fasting glucose, lipids, renal function) were extracted from the Al-Shifa electronic health system and National Screening Register. Multivariable logistic regression was performed using SPSS 30.0 (IBM Corp., Armonk, NY, USA). Results: Among 4862 participants (mean age 43.2 ± 6.3 years; 61.7% female), prevalences were: prediabetes 29.0%, T2DM 5.5%, obesity (BMI 30–40 kg/m²) 35.7%, hypertension 42.0%, hypercholesterolemia 48.8%, and renal involvement 51.8%. Males had significantly higher prediabetes prevalence than females (35.4% vs. 24.7%; adjusted odds ratio [aOR] = 1.43; 95% confidence interval [CI]: 1.21–1.70). Independent risk factors included each 1-year age increase (aOR = 1.05; 95% CI: 1.03–1.08), each 1-unit BMI increase (aOR = 1.03; 95% CI: 1.01–1.05), and family history of diabetes (aOR = 1.28; 95% CI: 1.09–1.50). Conclusions: The high burden of prediabetes and comorbid non-communicable diseases in Oman necessitates urgent public health strategies, including enhanced screening, lifestyle interventions, and gender-specific approaches to curb the T2DM epidemic. Full article

Branching processes are stochastic models describing the evolution of populations in which individuals reproduce and die independently over time. In the classical setting, an individual’s reproductive capacity is fixed throughout its lifetime. However, in real-world situations, fertility typically rises during a juvenile phase, peaks at maturity, and subsequently declines. In order to capture this feature, we introduce a branching random walk with ageing, as an extension of the classical branching random walk, by assigning each individual an age-dependent reproductive rate. Our model differs from classical age-dependent processes such as the Bellman–Harris model, where the remaining lifespan depends on age, while the rate of reproduction is fixed within that lifetime. As in the classical case, branching random walks with ageing are parametrised by $\lambda >0$, which tunes the reproductive speed and may be seen as a characteristic of the population. The thresholds of $\lambda$ separating extinction and survival are the global and local critical parameters. We characterise the value of the local critical parameter and provide a lower bound for the global critical parameter. We identify a class of ageing branching random walks for which this lower bound coincides with the global critical parameter. We study how local modifications to the reproduction and ageing rates may change the critical parameters. This is of practical interest: in species preservation, one may want to lower the critical parameters, so that $\lambda$ exceeds them, and there is a positive probability of survival. On the other hand, in epidemic control, the goal is to increase the critical parameters, since if $\lambda$ is below them, then the epidemic is eventually going to disappear. We compute the expected number of individuals alive in a branching process with ageing and show that, contrary to the behaviour of classical branching processes, it may exhibit an initial growth even when the population is ultimately destined for extinction. Full article

To monitor the epidemiological situation of bluetongue virus (BTV) in Belgium, a national surveillance programme was conducted during the 2024–2025 winter season. The objective was to estimate the apparent seroprevalence of BTV-3 following the 2023–2024 epidemic and to prove the absence of active circulation of other BTV serotypes in mixed herds (cattle and sheep). A total of 2551 cattle and 1458 sheep were sampled across Belgium. Serological analyses were performed using ELISA, and molecular detection of BTV-3, BTV-8, and BTV-12 was conducted by RT-qPCR. The majority of cattle and sheep herds showed evidence of exposure to BTV-3, with a very high herd-level apparent seroprevalence (100%; 95% CI: 96.2–100% in cattle and 98.9%; 95% CI: 93.8–99.8% in sheep). Apparent within-herd seroprevalence was also high in cattle (94.6%; 95% CI: 91.8–96.5%) and sheep (85.5%; 95% CI: 80.4–89.5%). No evidence of active circulation of BTV-8 or BTV-12 was detected. A moderate significant positive correlation between Ct values and sampling date was observed both for bovine and ovine samples, consistent with a progressive decline in detectable BTV RNA during winter in the absence of vector activity. Full article

Recent reports have advocated the global resurgence of human metapneumovirus (hMPV) infections in the post-COVID-19 era. Considering the absence of relevant data from Greece, the present study aimed to explore the molecular epidemiology and possible resurgence of significant genotypic variants. Whole genome and F gene-specific sequencing were implemented in order to obtain complete information on the genotype and lineage distribution of circulating hMPV strains in Greece. The results showed a statistically significant increase in monthly positivity rates in 2025, especially from February to April, compared to the respective period in 2024. Overall, 21 strains were classified as genotype A2.2.2 (42.9%) and 27 as genotype B2 (55.1%), whereas only one strain belonged to genotype B1. The G gene of most completely sequenced A2.2.2 strains harbored a 111nt duplication sequence and a genotype-specific pattern of N-glycosylation sites. Maximum likelihood and time-scaled, Bayesian phylogenetic analyses demonstrated the dominance of specific sub-lineages at the regional level and international transmission events. This complex epidemic pattern in conjunction with the differential evolutionary pressure exerted on the hMPV genes, advocates continuous surveillance of hMPV epidemiology with multiple genes, or complete genome sequencing methodologies. Full article

Rift Valley fever virus (RVFV) and Crimean-Congo hemorrhagic fever virus (CCHFV) are designated by the World Health Organization as priority pathogens due to their epidemic potential, zoonotic transmission, and the absence of licensed therapeutics or vaccines. The development of effective antivirals critically relies on robust in vitro and in vivo models; however, progress is limited by the requirement for high-containment facilities. In this review, we provide a comprehensive overview of the experimental models currently available for RVFV and CCHFV, ranging from cell-based assays to animal models, and discuss their respective advantages, limitations, and translational relevance. We further highlight strategies allowing for BSL-2 experimentations, thereby expanding research accessibility, and accelerating the development of countermeasures against these high-priority pathogens. Full article

This paper proposes an impulsive SIRQ model for the analysis of computer network resilience against malware propagation and distributed denial-of-service (DDoS) attacks. The model extends classical epidemic frameworks by combining the continuous-time dynamics of malicious object spreading with discrete control actions corresponding to mass updates, node isolation, and access control policies. A qualitative analysis of the resulting system of impulsive differential equations is performed. The basic reproduction number ${\mathcal{R}}_0$, identified as a threshold parameter characterizing the intensity of attack propagation, and sufficient conditions for the global asymptotic stability of the infection-free state are established. It is shown that, under periodic impulsive control, the infection-free state can be stabilized with respect to the target population coordinates even when ${\mathcal{R}}_0>1$. An exponential decay estimate for the total active threat is derived, guaranteeing the asymptotic extinction of the infected and quarantined node populations. The proposed approach provides quantitative criteria for the effectiveness of impulsive cyber defense strategies and offers a theoretical foundation for the design of adaptive multi-layer protection systems for critical information infrastructures. Practical interpretation of the results illustrates the dependence of the critical impulsive control period on the model parameters and demonstrates the applicability of the approach to cybersecurity strategy design. Full article

Pertussis, caused by Bordetella pertussis, remains a public health concern despite long-standing vaccination programs. After a marked decline during the COVID-19 pandemic, a resurgence was observed in Europe and Italy, with a sharp increase in 2024. This study describes pertussis epidemiological trends in the Tuscany Region (Italy) from 2019 to 2024 to identify high-risk groups and inform prevention strategies. A retrospective population-based analysis was conducted using cases reported to the national surveillance system (PREMAL). Incidence rates were calculated using ISTAT population data, and demographic, temporal, and clinical characteristics were analyzed. Overall, 669 cases were reported (mean annual incidence rate: 3.03/100,000 (IC 95% 2.47–3.59; period incidence rate: 18.2/100,000 (IC 95% 16.81–19.56)), with 89% occurring in 2024 (16.34/100,000 (IC 95% 15.03–17.65)). No sex differences were observed, and most cases were reported in Central Tuscany (64%). Children under 15 years accounted for 87% of cases. The highest incidence was observed among 10–14-year-olds, while infants < 1 year, particularly those under 4 months, showed the highest burden in narrower age strata. Hospitalizations occurred in 12.6% of cases, decreasing substantially in 2024. The 2024 resurgence likely reflects waning immunity, disruptions to routine vaccinations during the pandemic, and reduced pathogen circulation in previous years due to containment and isolation measures related to the pandemic. Strengthening surveillance and improving booster and maternal vaccination coverage are essential to protect vulnerable populations. Full article

In the early stages of the COVID-19 pandemic, uncertainty around the extent of SARS-CoV-2 spread hampered policymakers’ understanding of the epidemic’s extent. Mathematical models, which proved vital for aiding decision-making, relied primarily on reported cases that were unreliable due to significant underdetection and underreporting. While serological data was used to improve understanding of the epidemiology, it can be costly and difficult to implement without bias. To counter these issues, we integrated serological data from 7229 remnant serum samples collected in 15 Maryland emergency departments (EDs) in Maryland between August and December 2020 into a Bayesian modeling approach to derive an estimate of the incidence of infection and the case fatality rate during the pandemic’s initial wave. We estimated that 5.2% (95% CI, 3.7–7.2%) of the population of Maryland had been infected by late fall 2020. The inferred reporting rate that was estimated started low (<10% in March 2020) and increased to 32% (95% HDI = 26–41%) by the fall, while the estimated infection fatality rate was likely initially higher but fell to 0.51% (95% HDI = 0.43–0.68%) after 1 September 2020. These results demonstrate how existing ED infrastructure can be leveraged to generate less biased, more accurate estimates of the true prevalence of a disease, improving the ability to make decisions and allocate resources under uncertainty. Full article

Energy thriftiness and metabolic adaptations have had a crucial role in the emergence and spreading of the Homo lineage in the world. A higher-energy demand was required not only for the growing body mass, encephalization and human proliferation, but also for the survival adaptations to the environmental stresses. Because lean body mass lacks the energy-storage capacity required to supply the body’s demands, dedicated fat-storing cells originated. To feed such fat stores, the hominid evolution developed “meat-adaptive” genes to detect, digest and metabolize higher fat diets, and body-fat stores can be affected by lifestyle through hormonal-controlled daily energy balance. In energy surplus conditions, hypertrophy and hyperplasia of adipocytes can occur, with hypertrophic adipocyte signaling both a neo-adipocyte differentiation (leading to hyperplasia) and a local macrophage density (resident + infiltrated macrophages) for fat surplus scavenging. Adiposity-induced inflammation is caused by fat-overstored (hypertrophied) adipocytes that may operate as an overactive endocrine organ secreting an array of pro-inflammatory adipokines that, in combination with resident-macrophage activity and infiltrated blood-recruited, monocyte-derived macrophages, amplify the inflammatory process by spurting pro-inflammatory cytokines into the bloodstream. From an evolutionary perspective, obese humans represent a natural selection overexpressing the “thrifty” genes evolved for efficient food collection and fat deposition intended to help in survival in prolonged periods of famine. However, genetically speaking, obesity is a polygenic multifactorial disorder. Considering the rapidity of obesity-epidemic growth worldwide, epigenetic sets forth the key assumption of the mismatch between our human genome molded over thousands of generations, coping with the unprecedented dietary and physical conditions. Consequently, obesity would be due to our evolutionary-adapted polygenic-charge expressed by a deteriorated lifestyle characterized by high energy-dense food intake coupled with a reduction in caloric expenditure stemming from new mobility-reducing technologies. As a model of lifestyle change (LiSM), our 28-year on-going longitudinal study (“Moving for Health”) has shown effectiveness in the reduction not only of obesity but especially of its comorbidities, in a (10 week to 3 year) length-dependent LiSM. However, a disappointing progressive decrease in compliance with the study has been observed and attributed to the resistance of people to change their actual “obesogenic” lifestyle, basically represented by the individuals’ demand for labor-saving technologies and convenient, affordable, palatable foods. Full article