Search Results (7,769)

Influence Maximization (IM) is a fundamental problem in social network analysis that aims to identify a set of k seed nodes that maximizes influence spread under a given propagation model. Despite its importance in applications such as viral marketing and epidemic control, the IM problem is NP-hard, making exact solutions computationally infeasible for large-scale networks. Existing approximation methods typically rely either on static centrality heuristics, which often ignore global network structure, or on metaheuristic algorithms, which may suffer from slow convergence due to random initialization. This paper proposes a novel approach, termed Advanced Centrality-Driven Discrete Particle Swarm Optimization (DPSO), which integrates a weighted hybrid centrality score combining Degree, PageRank, and Betweenness centrality to guide the stochastic search process. In addition, a systematic grid search methodology is employed to determine the optimal weight configuration of the hybrid score. Experiments conducted on three real-world datasets (Twitter, ego-Facebook, and ca-HepTh) demonstrate that the optimal seeding strategy is strongly dependent on network topology. The results show that dense social networks favor popularity-based metrics such as Degree and PageRank, whereas sparse collaboration networks benefit significantly from bridge-oriented metrics such as Betweenness centrality. Overall, the proposed method achieves consistent improvements in influence spread across different network types, with the largest gains (up to 70%) observed in sparse network settings. Full article

Surface plasmon resonance (SPR) is a label-free, real-time biosensing technology with high sensitivity for the detection of biomolecular interactions. This review highlights recent advances in SPR biosensors for the detection of SARS-CoV-2. First, we outline design strategies, especially advanced plasmonic nanostructures and precise surface functionalization, that improve the specificity and binding affinity to viral targets. Next, we cover signal amplification methods, such as nanoparticle conjugation and plasmonic photothermal effects, which enhance the sensitivity for low-abundance viral components. Subsequently, we conducted a comparative analysis of SPR biosensors alongside traditional and emerging detection approaches for SARS-CoV-2, elucidating their individual merits and drawbacks. We also discuss how machine learning improves data interpretation and diagnostic accuracy. Finally, we discuss the current challenges and future development directions, particularly for clinical diagnostics, epidemic monitoring, and public health security. These advances support faster, more reliable, and accessible diagnostics for current and future viral outbreaks. Full article

A suicide epidemic exists among young U.S. veterans, with risk especially elevated in the first year of transition for the 200,000 servicemembers exiting the military annually. The VA Veteran Sponsorship Initiative (VSI) is a public–private-partnership between federal and community partners that aims to decrease suicides by providing a VA-certified volunteer peer sponsor and connection to community services. Onward Ops is a key community-based national program that enrolls, matches and manages the relationship between servicemembers and sponsors. A prior randomized controlled trial showed that the effectiveness of community interventions can be enhanced when augmented by an Onward Ops sponsor. In preparation for national implementation, we conducted a quasi-experimental, matched-cohort pilot to evaluate the feasibility of an adapted VSI protocol and then assessed effectiveness. The adaptations were executed using the Framework for Reporting Adaptations and Modifications-Enhanced between April 2021 and April 2023. The formative results supported the feasibility of the adaptations to enable proactive enrollment on military installations and expand data infrastructure, partnerships, peer sponsors, and VA clinical services. We then assessed the effectiveness for outcomes not studied in the original VSI trial for active-duty soldiers who enrolled between April and December 2023. After nearest-neighbor matching, the sample included 551 VSI participants and 551 soldiers transitioning as usual. The point-probability contrast or risk differences from the conditional logistic regression model indicated that the VSI caused a statistically significant increase in VA primary care utilization of 0.198 and a statistically significant decrease in suicide attempts of −0.019, both assessed 10 months post-military discharge. The study demonstrated the utility of public–private-partnerships, peer-sponsorship programs and enhanced VA services to support servicemembers during transition. Full article

Cardiovascular diseases (CVDs) are a leading cause of morbidity and mortality globally, with low-resource settings, including Ethiopia facing challenges due to limited early diagnostic services. AI-powered electrocardiography (ECG) interpretation has the potential to improve diagnostic accuracy, decentralize care, and support timely clinical decisions, but evidence on healthcare providers’ perspectives and adoption determinants is limited. This exploratory descriptive qualitative study employed 31 in-depth interviews with healthcare providers. Healthcare providers (cardiologists, internists, cardiac and critical care nurses, critical care specialists, and general practitioners) were purposively selected through maximum variation sampling from ten hospitals in four regions of Ethiopia. Data were transcribed verbatim, coded inductively, and analyzed thematically. The data analysis identified six themes: perceived benefit of AI-powered ECG interpretation CDSS, trust development, workflow integration, ethical concerns, functionality, and adoption determinants. Participants emphasized AI’s potential to enhance accessibility, consistency, and diagnostic accuracy while reducing subjectivity and unnecessary referrals. Acceptance relied on high accuracy, reliable data, and rigorous validation, with the technology seen as supportive rather than replacing clinicians. Material resources, human resource readiness, and leadership engagement were key factors for adoption. Recommendations included phased implementation, continuous training, and model expansion to ensure sustainability and clinical utility. The AI-powered ECG interpretation CDSS was viewed as a valuable adjunct for strengthening cardiovascular care in Ethiopia, highlighting the need for context-sensitive strategies, ethical safeguards, and multi-level system readiness for successful adoption. Full article

Network dismantling—the targeted removal of nodes to degrade large-scale connectivity—plays a central role in resilience analysis, epidemic containment, and systemic-risk mitigation. Recent work shows that dismantling performance depends strongly on mesoscale modular structure, suggesting that community-aware strategies may offer advantages over classical centrality-based heuristics. In this work, we perform a large-scale, systematic evaluation of dismantling strategies and introduce gateways as a new mesoscale dismantling concept. While similar experiments exist using degree- and betweenness-based dismantling strategies, we check a new strategy based on gateways, which capture asymmetric entry points into communities and generalize the notion of inter-community connectors. Furthermore, we process a massive dataset of 568,584 LFR benchmark graphs, covering a wide range of degree distributions, community sizes, and mixing parameters. For evaluation, we use both extrinsic (ARI, NMI, FMI, VI) and intrinsic (Modularity, Coverage, Performance, Average Conductance, Average Internal Density) metrics. We find that across parameter regimes and evaluation metrics, classical strategies (degree, betweenness, community connections) and gateway-based dismantling exhibit broadly similar performance. Our results also corroborate recent findings that dismantling effectiveness is robust to the specific partitioning algorithm and that inter-community connectivity plays a dominant role in global fragmentation. The evaluation provides large-scale evidence that gateway-aware dismantling captures an operationally relevant mesoscale mechanism as good as previous approaches and motivates further empirical studies on real networks and cost-aware settings. Full article

Marek’s disease (MD), caused by pathogenic Marek’s disease virus serotype 1 (MDV-1), is one of the most important avian immunosuppressive and neoplastic diseases and has led to huge economic losses to the poultry industry worldwide. Rapid and accurate clinical diagnosis is of great significance for efficient control of the disease. Herein, we have established a multiplex PCR (mPCR) method to simply differentiate all of the three types of MDV, using five specific primers targeting to MDV-1 oncogene meq or MDV-2 and MDV-3/HVT gB genes. Simultaneously, it can detect any type of virulent or vaccine MDV strains in one PCR reaction, with amplicons of the short (S) and long (L)-meq of MDV-1 strains, and the gB of MDV-2 and HVT vaccine strains. Non-specific amplifications of avian leukosis virus (ALV), reticuloendotheliosis virus (REV), or fowl adenovirus virus 4 (FAdV-4) were not observed, indicating a good specificity of this method. A total of 522 clinical samples of tumor-bearing or suspected diseased birds collected from 30 poultry farms were detected. The results demonstrated that the newly developed mPCR method accurately detected and differentiated epidemic MDV-1 infections and vaccine strains, and provided nearly 100% consistency for detecting clinical wild-type infections compared with conventional PCR amplification of the meq gene. Collectively, our data has provided a highly efficient method for early differential diagnosis of MD clinical cases, virus identification and future evaluation of vaccination efficacy in healthy chicken flocks, which would be meaningful for efficient control of the disease. Full article

Background: Hepatitis B virus (HBV) infection continues to be a major public health concern, especially in sub-Saharan Africa, where widespread epidemics and restricted availability of long-term antiviral therapies result in higher mortality and morbidity rates. Drug repurposing represents a strategic approach to accelerate the discovery of effective therapies by leveraging agents with demonstrated antiviral and immunomodulatory activity. Product Nkabinde (PN) is a patented African polyherbal formulation initially developed for the treatment of HIV. Recent experimental studies demonstrate PN’s potent anti-HIV activity and significant immunomodulatory effects in human immune cells, implicating host-directed mechanisms relevant to chronic viral infections. This study combines an integrative application of network pharmacology and molecular docking to evaluate the repurposing potential of PN as a multi-target agent in HBV. Method: Bioactive components of PN were screened, and compound-associated targets were intersected with HBV-associated genes (proteins) to construct a protein–protein interaction (PPI) network. Topological analysis identified 10 hub targets (STAT1, STAT3, SRC, HCK, EGFR, SYK, PIK3CA, PIK3CB, PIK3R1, and PTPN11). Gene Ontology and KEGG pathway enrichment were performed with an FDR cut-off < 0.05. Significantly enriched pathways included JAK–STAT signaling, chemokine signaling, EGFR-TKI resistance, PI3K complex signaling, and viral infection pathways, particularly those related to Kaposi sarcoma virus and HSV-1, indicating immunoregulatory and antiviral roles. Molecular docking was performed using AutoDock Vina 1.1.2 to evaluate binding affinity and interaction mode of key PN phytochemicals against the hub proteins, and results were compared to their respective co-crystallized ligands. Results: Molecular docking indicated that major phytochemicals from PN exhibited significant binding affinities across all 10 hub host targets, typically outperforming or closely matching their respective co-crystallized ligands. The strongest contacts were observed for β-sitosterol–PIK3CB (−14.2 kcal/mol) and oleanolic acid–SYK (−14.0 kcal/mol), which were significantly stronger than the co-crystallized ligands (−7.9 and −8.3 kcal/mol, respectively), indicating robust stabilization within catalytic and regulatory pockets. Procyanidin B2 toward HCK (−10.5 vs. −7.9 kcal/mol) and PIK3CA (−9.5 vs. −7.3 kcal/mol), quercetin toward PIK3R1 (−10.6 vs. −8.2 kcal/mol) and PTPN11 (−9.2 vs. −7.5 kcal/mol), rutin toward SRC (−10.5 vs. 7.8 kcal/mol), and diosgenin toward EGFR (−9.4 vs. 8.4 kcal/mol). Procyanidin B2 maintained robust multi-hydrogen bonding networks, demonstrating significant binding, despite STAT1 and STAT3 docking showing identical affinities to co-crystals. Conserved hydrogen bonds, π–cation interactions, and significant hydrophobic packing at ATP-binding clefts and regulatory domains supported these interaction patterns, indicating competitive suppression of host signaling nodes taken over by HBV. Conclusions: Together, these results demonstrate that the components of PN possess strong multitarget binding capabilities across the PI3K/AKT, JAK–STAT, SRC-family kinase, EGFR, and SYK pathways, supporting their potential repurposing as host-directed HBV therapeutics with the ability to impede immune evasion, viral persistence, and HBV-associated oncogenic progression. Full article

The global obesity epidemic has emerged as a major driver of cancer incidence and mortality, with accumulating evidence highlighting the gut–adipose–tumor axis as a critical mediator of obesity-related carcinogenesis. The gut–adipose–tumor axis is a tripartite communication network, wherein the intestinal microbiome, adipose tissue, and tumor microenvironment engage in dynamic bidirectional crosstalk that alters cancer susceptibility and progression. This review synthesizes current understanding of the epidemiology, pathophysiology, therapeutic implications, and future directions of this axis. Obesity-induced gut dysbiosis leads to systemic dissemination of pro-inflammatory microbial products and metabolites. These gut-derived signals profoundly influence adipose tissue homeostasis, exacerbating chronic low-grade inflammation, promoting macrophage infiltration and polarization, and disrupting adipokine secretion patterns. Dysfunctional adipose tissue generates cancer-promoting mediators and metabolic perturbations. The convergence of gut-derived and adipose-derived signals creates a systemic pro-carcinogenic environment that reshapes the tumor microenvironment through multiple mechanisms. Understanding the gut–adipose–tumor axis as an integrated biological system offers opportunities for cancer prevention and treatment. This is of significant importance for exploring the mechanisms of obesity-related carcinogenesis and developing new therapeutic approaches for obesity-related cancers. Full article

Atrial septal defect (ASD) has become increasingly common in the USA and now affects 1 in 11.3 children in some places, but space–time analysis has not been applied to this emerging trend. ASD rate (ASDR) data were obtained from the National Birth Defects Prevention Network 2003–2020. Substance (cigarettes, alcohol, cannabis, analgesics, cocaine) use data were obtained from the National Survey of Drug Use and Health. Income data were obtained from the US Census. Analysis was limited to the Non-Hispanic White population by technical factors. Time-sequential univariate and bivariate maps were prepared for both covariates and outcomes and their combinations. Spatial regression of the ASDR was performed using the R package splm. A total of 7.6% of data was interpolated by linear regression. A total of 110,107 ASD cases were identified amongst 17,751,437 live births in 27 US states across 10 reporting periods. Time series maps showed that ASDR showed concordant patterns with indices of cannabis use rather than other substances. This was confirmed by multivariate spatial regression where cannabis and cannabinoids alone were found to significantly relate to ASDR, with p = 0.00002 for cannabidiol. Cannabis legal status similarly tracked with ASDR. Compared to states where cannabis was not legal, ASDR was more prevalent in cannabis-legal states (OR = 2.73 (2.66, 2.80); E-Value 4.90 (lower C.I. 4.76)). Twenty-seven of 34 (79.4%) E-values were >9 (high range) and 34/34 were > 1.25 (causal threshold). Data show that cannabis, including cannabis legalization, is driving the US ASD epidemic. While most high-ASDR states have high rates of cannabis use, Midwestern states where cannabis is farmed, such as Kentucky, Tennessee and Missouri, do not, suggesting other routes of exposure, potentially implicating environmental contamination. ASD is a bellwether marker for cannabinoid teratogenicity, indicating that communities should carefully control cannabinoid exposure and limit transgenerational cannabinoid genotoxicity more generally. Full article

Solving constrained multiobjective optimization problems (CMOPs) is highly challenging due to the presence of complicated feasible regions, intense conflicts among objectives, and unevenly distributed constraints. As a result, conventional methods relying on a single constraint-handling mechanism frequently fail to maintain a stable equilibrium among solution feasibility, diversity, and convergence. To overcome these bottlenecks, this article introduces AFFCMO, a novel adaptive feasibility-guided framework tailored for constrained multiobjective optimization. At its core, the proposed approach utilizes a coevolutionary dual-population architecture that divides the search process into two distinct tasks. Specifically, an auxiliary population is tasked with global exploration, while a primary population focuses on the intensive exploitation of discovered feasible areas. To achieve this, the primary population leverages a DE/current-to-pbest/1 differential evolution strategy to closely approximate the constrained Pareto front. Simultaneously, the auxiliary population expands the search space using a mutation operator that adapts to the current evolutionary stage. Furthermore, exploration is bolstered by a multicriterion environmental selection scheme designed for the auxiliary group. By combining Euclidean geometric distributions, constraint relaxation, and value modeling inspired by epidemic dynamics, this strategy successfully preserves valuable infeasible solutions that can guide the search. Additionally, a dynamic resource allocation strategy based on historical search feedback and Thompson sampling is incorporated. This mechanism continuously evaluates the recent search contributions of both populations and adaptively adjusts their offspring sizes, thereby reducing the bias introduced by static allocation schemes. This mechanism continuously assesses the actual search contributions of both populations, allowing for the adaptive resizing of offspring generations and thereby eliminating the inherent biases of static allocation methods. Comprehensive empirical evaluations are conducted on 47 benchmark problems from four distinct test suites. The results indicate that AFFCMO significantly outperforms seven contemporary multiobjective evolutionary algorithms in terms of exploring complex feasible regions, preserving solution diversity, and achieving high convergence accuracy. Full article

Background and Objectives: Diabetes is one of the most common chronic non-communicable diseases and represents a major public health problem. At the global level, the epidemic character of diabetes mellitus can be attributed to an extended life expectancy but also to lifestyle. The aim of this study was to examine the sociodemographic, health, and lifestyle characteristics of adults with type 2 diabetes mellitus in Serbia. Materials and Methods: The research is part of the Serbian Population Health Survey conducted in the period from October to December 2019 by the Republic Statistical Office, in cooperation with the Institute of Public Health of Serbia “Dr Milan Jovanović Batut” and the Ministry of Health of the Republic of Serbia. The research instrument was standardized questionnaires constructed in accordance with the European Health Interview Survey (EHIS—European Health Interview Survey, wave 3) questionnaire, which were adapted to the specifics of our area. The research was conducted as a cross-sectional study on a representative sample of the adult population of Serbia. Results: Among 1138 adults with type 2 diabetes in Serbia (52.8% female; mean age 66.0 ± 11.9 years), overweight and obesity were highly prevalent (40.1% and 34.4%, respectively), with Obesity I predominating. Significant gender differences were observed: female more often reported obesity, multimorbidity, and depressive symptoms, whereas men were more physically active and more frequently overweight. Most participants were physically inactive, consumed breakfast and bread daily, and had low engagement in cycling and sports. Alcohol consumption was significantly higher in men, while dietary habits differed by gender for bread intake. These findings highlight substantial gender- and lifestyle-related disparities among adults with type 2 diabetes in Serbia. Conclusions: Targeted interventions promoting healthy lifestyle, physical activity, psychosocial support, and chronic disease management are urgently needed to address gender- and lifestyle-related disparities in adults with type 2 diabetes in Serbia. Full article

Coronavirus infections pose a significant threat to both human and animal health, causing widespread morbidity, mortality, and substantial economic losses. While vaccines are crucial for prevention, their efficacy is often limited by the high mutation rate of these viruses. This underscores the urgent need for anti-coronavirus drugs, particularly broad-spectrum antiviral agents. In this study, we demonstrated for the first time that Biochanin A (BCA), a bioactive isoflavonoid found in legumes, exhibits broad-spectrum antiviral activity against coronaviruses. BCA potently inhibits porcine epidemic diarrhea virus (PEDV), as well as human coronaviruses HCoV-OC43 and HCoV-229E in vitro, with EC₅₀ values of 6.90, 2.80 and 15.4 μM, respectively. In a lethal mouse model of HCoV-OC43-induced encephalitis, oral administration of BCA (40–60 mg/kg) significantly improved animal survival and reduced cerebral viral loads. Mechanistic studies revealed that BCA upregulates the AMPK/Nrf2 signaling pathway, thereby increasing expression of the glutamate-cysteine ligase catalytic subunit (GCLC) and enhancing glutathione (GSH) biosynthesis. Our findings identify BCA as a promising host-directed antiviral agent and highlight its therapeutic potential against coronavirus infections. Full article

In recent years, fractional HIV models have received increasing attention. This study derives a fractional HIV model using the continuous-time random walk (CTRW) method, endowing the mathematical model with physical significance. Based on the transmission characteristics of HIV, the proposed model considers extrinsic infectivity, intrinsic infectivity, and drug control, specifically as follows: the extrinsic infectivity is a constant independent of the infection time; the intrinsic infectivity is a power-law function that depends on drug efficacy and infection time; the drug efficacy rate follows a Mittag–Leffler distribution with a long-term effect. Based on these considerations, a fractional HIV model with drug control is established in this paper. In addition, the global asymptotic stability of the equilibrium and the sensitivity analysis of the basic reproduction number $R_0$ are studied, and the theoretical results are verified by numerical simulations. The results show that reducing extrinsic infectivity, controlling intrinsic infectivity, and the drug efficacy rate are crucial in controlling the spread of HIV. Full article

Getah virus (GETV), a mosquito-borne virus capable of infecting multiple economically important animal species, poses a potential epidemic risk. In May 2024, one pig farm from Heyuan, Guangdong Province, China, suffered reproductive disorders in sows and diarrhea in newborn piglets. Out of the six blood samples that were collected, three tested strongly positive for GETV, yielding a positivity rate of 50%. Moreover, a GETV strain (designated GDHYLC2024) was successfully isolated and identified. The viral titer of GDHYLC2024 was 10^7.687 TCID₅₀/mL in Vero cells. Its genome was composed of 11,688 bases in length. Interestingly, compared with GDHYLC23, it had no unique 32-nucleotide repeat insertion in 3′ non-coding region. However, phylogenetic analysis showed that GDHYLC2024 and GDHYLC23 clustered in genotype III. Animal infection experiments demonstrated that the GDHYLC2024 strain was highly pathogenic to 4-day-old piglets, which caused obvious clinical symptoms including fever, depression, anorexia, periorbital edema, ataxia, and three deaths out of a total of five individuals in the infection group. This study reported re-emergence of GETV in the same region of Guangdong Province, China. The above findings suggest that GETV continuously poses a threat to farm pig’s health and has genetic diversity. Full article

The increasing burden of dengue represents a growing global public health concern. Among the factors associated with rising dengue incidence, climate change, particularly increasing temperatures, has been frequently highlighted, alongside other environmental, biological, and social determinants. The emergence of dengue in previously non-endemic areas and its sustained increase in incidence have become increasingly common in recent decades. Objective: The aim of this study was to describe national dengue case trends in Mexico from 1990 to 2023 and to assess their association with temperature over the same period using a descriptive, retrospective analysis of epidemiological surveillance and temperature data. Methods: Epidemiological data on confirmed dengue cases and incidence were obtained from the Morbidity Yearbook of the General Directorate of Epidemiology (DGE) of the Mexican Ministry of Health. These data were used to construct epidemic curves and to analyze the geographic distribution of incidence using quartiles. Temperature data were derived from the national annual mean calculated from monthly reports issued by the National Water Commission (CONAGUA). Associations between temperature and dengue cases and incidence were explored over the study period. Results: Temporal analysis revealed a significant increase in both dengue cases and incidence in Mexico, with a positive association with temperature during the same period. Quartile-based geographic analysis showed that state-level classifications remained relatively stable across periods, with several states clustering within or tending toward the group considered endemic. Conclusions: The results of this study show an increase in cases and incidence of dengue over time, as well as a positive association between cases/incidence of dengue in Mexico and the increase in the national average temperature during the study period; however, due to its descriptive and retrospective design, causal inference is not possible. Dengue transmission is inherently multifactorial, and the observed trends likely reflect the combined influence of climatic conditions, historical expansion of transmission cycles, vector establishment, and unmeasured socio-epidemiological factors. The absence of entomological indicators, additional climatic variables, and spatially or seasonally disaggregated analyses limits the ability to capture localized dynamics. Overall, temperature should be interpreted as a contributing factor within a complex system rather than as the sole driver of dengue trends, underscoring the need for integrated surveillance and control strategies in both endemic and non-endemic regions. Full article