Browse Articles
Discover research articles across all indexed journals
Determining farm surface porcine reproductive and respiratory syndrome virus (PRRSV) contamination through viability RT-qPCR
Porcine reproductive and respiratory syndrome (PRRS) continues to be a major threat to U.S. swine industry, as a substantial number of herds become positive and can pose a risk to other nearby farms, especially in post weaning farms as multiple of them may be overseen by one worker. Personnel moving between farms without adequate biosecurity measures, may play a role in viral spread acting as a fomite. The ability to detect and distinguish between the free PRRS virus (PRRSV) genomic RNA vs its genome found in a viable virus form on frequently touched surfaces in growing pig farms was assess in this study. Ten PRRSV positive growing pig farms in the Midwestern U.S. were visited to collect 20 environmental surface samples and eight oral fluids from each one. Environmental samples were analyzed using standard RT-qPCR and viability RT-qPCR, while oral fluids were assessed using the VetMAX™ PRRSV EU & NA v3.0 kit. The virus’ RNA was commonly detected on metal and plastic (non-porous) surfaces (e.g., pig pen top rail, mortality handling equipment’s handle) from all farms, with 80 out of 200 environmental samples testing positive. Viable virus was detected in 48 samples across six farms, with non-porous materials testing positive more frequently. A generalized linear mixed effect model suggested a negative association (OR = 0.005; 95% CI 0.00, 6.82; p-value = 0.18) between the proportion of positive oral fluids and detecting viable virus from sampled surfaces. Agreement between the detection of RNA and viable PRRSV from surface samples using Cohen’s kappa yielded perfect agreement (κ = 1.00) from doorknobs of different locations, to low agreement (κ = 0.29) in the floor of a specific area, among others. These results indicate the presence of viable virus on surfaces that are frequently touched by the farm’s personnel. This study highlights the importance of biosecurity measures applied to the personnel and their potential role of environmental contamination and PRRSV dissemination. The use of viability RT-qPCR to detect viable PRRSV offers a practical tool in field settings to improve biosecurity protocols to reduce indirect transmission of PRRSV in swine production systems.
Platform-visible sentiment and topics in Ningbo’s community revitalization: evidence from short videos
Development of a monoclonal antibody-based competitive ELISA as a surrogate assay for detecting neutralizing anti-interferon gamma autoantibodies in adult-onset immunodeficiency
Neutralizing anti-interferon gamma autoantibodies (nAIGAs) play a pivotal role in the pathogenesis of adult-onset immunodeficiency (AOID), predisposing affected individuals to severe opportunistic infections. Current detection of nAIGAs relies on cell-based assays requiring flow cytometric analysis, which limits routine clinical settings. Notably, nAIGAs recognizing the B27 epitope of interferon gamma (IFN-γ) exhibit strong neutralizing activity, underscoring the need for practical, epitope-specific detection methods for routine diagnostic. This study aimed to develop and validate a competitive enzyme-linked immunosorbent assay (cELISA) as a surrogate assay for detecting B27 epitope-targeting nAIGAs in plasma samples from patients with AOID. Plasma samples from patients with AOID (n = 40) and healthy controls (n = 40) were initially screened for AIGAs using an indirect ELISA. Neutralizing activity was confirmed using a cell-based assay measuring MHC class II expression on IFN-γ-stimulated THP-1 cells. The cELISA was subsequently developed and optimized to detect nAIGAs specific to the B27 epitope. ROC curve analysis was performed to assess the diagnostic performance of the assay. All AOID samples with detectable levels of AIGAs showed percentage inhibition above the cut-off in the cell-based assay, confirming the neutralizing activity of AIGAs. The developed cELISA detected nAIGAs in 36 of 40 AOID samples, with no false-positive results observed among healthy controls. ROC curve analysis indicated excellent diagnostic performance, yielding an area under curves (AUC) of 0.9684. Taken together, our findings indicate that the developed cELISA serves as a surrogate assay for detecting nAIGAs targeting the B27 epitope of IFN-γ. This assay represents a practical and scalable tool for AOID screening and may facilitate broader applications in clinical diagnostics.
Drivers and influence of social conformity on decision making in human-AI teams
Abstract Advances in AI are transforming decision making teams. A fundamental open question is whether AI agents elicit social conformity effects comparable to human peers. If so, a critical challenge is determining whether the established drivers of social conformity in human teams—informational influence (the need to gain information from others) and normative influence (the need to gain approval or avoid punishment from others)—also transfer to AI teammates. In two studies, we investigated informational and normative influence in mixed human–AI teams using a medical information cascade paradigm. Participants received private evidence about a medical case and public advice from one or more AI or human advisors. Study 1 explored how participants weighted this public advice compared to their private information in scenarios where private and public information were equally accurate. Study 2 varied the accuracy of the private and public information. Results showed a distinct contrast between the two mechanisms. Humans and AI exerted a similar level of informational influence in both Study 1 and Study 2, and participants systematically under-weighted advice from both human and AI advisors relative to a Bayesian computational benchmark when source accuracies varied in Study 2. However, normative influence differed by advisor identity. In Study 1, participants placed significantly more weight on human advice than on equally reliable AI advice, indicating that AI lacks the normative pull inherent to human peers. Crucially, Study 2 revealed that this preference is fragile. We found that participants did not rely on a single heuristic, but instead attempted to integrate majority consensus with variable advisor accuracy. This complex processing eliminated the normative bias toward humans, and participants systematically under-weighted advice from both humans and AIs relative to the Bayesian computational reference. In addition, we also found an egocentric bias in both studies: participants in both studies weighed their private information significantly more than public advice. Theoretically, these findings suggest that differential reliance on AI versus human advice stems from the absence of normative influence rather than a lack of informational trust. Practically, the results highlight a design risk: presenting heterogeneous accuracy cues may increase cognitive load, leading to suboptimal advice integration.
DNA metabarcoding on roadkill stomach contents reveals the breadth of species present in bobcat diets
Trophic dynamics can be altered in complex ways as a result of urbanization. Understanding predator diets in these contexts may not only provide insight into these changes, but also in sources of mortality for vulnerable prey species like the New England cottontail ( Sylvilagus transitionalis ). However, studying the diets of mammalian predators such as bobcats ( Lynx rufus ) can be challenging because of their elusive behavior. DNA metabarcoding of stomach contents from roadkill is a method which provides a new opportunity to study predator diets when mortality events occur. We used this technique to examine variation in bobcat diet across a range of urbanized environments in Connecticut, USA, as well as determine whether bobcats consume the declining New England cottontail. DNA metabarcoding identified between two and five species in the majority of bobcat stomachs. Cottontail ( Sylvilagus spp. ) and eastern gray squirrel ( Sciurus carolinensis ) were each found in over 80% of samples, and most remaining taxa were other small mammals. Nearly a third of the bobcats had consumed white-tailed deer ( Odocoileus virginianus ). Stomach contents containing cottontail remains were sequenced at an additional species-specific marker, but no samples containing the New England cottontail were identified. Bobcats in Connecticut consumed a wide variety of natural prey species including a relatively high proportion of semi-aquatic mammals, and we found no evidence of domestic dog or cat consumption. DNA metabarcoding of stomach contents is an effective approach for opportunistically examining predator diet, and our use of this tool may provide a more complete picture of bobcat diet where other techniques have failed to do so.
Dream content and slow waves benefit prey against predator in a video game confrontation
Abstract Every studied animal species exhibits some form of sleep, a state evolved under the sustained influence of prey and predator behaviors. Dreams have been proposed to have evolved as offline mental simulations able to warn against impending threats from the environment, such as predators. To assess how the ecological roles of prey and predator interact with sleep and dreaming, we used a first-person shooter game as a proxy for predator-prey confrontations. Electroencephalographic (EEG) and electrocardiographic (ECG) signals were simultaneously recorded from 30 human adults paired while (1) playing a video game round against each other, (2) taking a nap, (3) reporting dreams and/or thoughts, and (4) playing another round. We found that the participants in the prey role were highly affected by sleep and dreaming. Their score gains were positively correlated with slow wave activity during the nap, with how much the dreams were related to the game, and with heart rate variability during the first round. In contrast, no significant correlations were found for participants in the predator role. The results suggest that slow wave activity and task-related dream content predict the post-sleep performance of individuals under stressful, low-agency, prey-like situations.
Genotype by environment interaction and yield stability analysis of durum wheat (Triticum turgidum var. durum) varieties using AMMI and GGE biplot analysis in Amahara Region, Northwest Ethiopia
Durum wheat is a staple crop for over one- third of the global population; however, its production in Ethiopia, particularly in the Amhara Region, faces major challenges due to limited adaptable varieties, poor management practices, and environmental constraints. Newly released wheat varieties often fail in unfamiliar environments, leading to yield losses. To address this issue, a study was conducted to evaluate the adaptability, performance, and yield stability of recently released high-performing durum wheat cultivars in the Amahara region. The field trials were conducted over two consecutive years (2022/2023 and 2023/2024) at three districts; Simada, Bichena, and Dabat, using a Randomized Complete Block Design with three replications. Data were collected on main agronomic traits, including growth, phenological, and yield traits such as grain yield. Statistical analyses included SAS 9.4 and R software were used, showing significant differences in crop phenological stages, growth, and yield parameters across years and locations for tested traits. Additive Main Effect and Multiplicative Interaction(AMMI) and Genotype and Genotype × Environment (GGE) biplot analysis were used to study genotype by environmental interaction(GEI). Genotype, location, and year interactions significantly influenced all durum wheat genotypes. The combined analysis of variance for all tested traits including grain yield, showed highly significant effects (p < 0.001). Grain yield ranged from 4.5 t ha -1 in Dabat to 2.29 t ha -1 in Simada. Among the genotypes, Tesfaye had the highest mean yield (3.74 t ha -1 ), while Wehabit had the lowest (2.75 t ha -1 ). The AMMI analysis revealed that most of the variation was due to environment (45%), followed by genotype (16%) and genotype × environment interaction (16%), showing strong environmental influence on yield performance. The GGE biplot and AMMI analysis identified Tesfaye and Don metteo as stable genotypes, while Simada and Bichena as representative environments. This study identifies Tesfaye as the most productive and stable wheat variety in the study area and suggests farmers should adopt it to increase wheat yield per unit area of land.
Association between TNF-α polymorphisms and responsiveness to TNF-α blockers in ankylosing spondylitis and psoriatic arthritis: a meta-analysis
Best reference genes for unbiased normalized transcript expression in normal and dystrophic human cell models of myogenesis
Patient-derived cell models of dystrophic myogenesis and differentiation are valuable preclinical tools for early and mutation-based assessment of candidate therapeutic approaches. Quantitative measurement of gene expression within such models plays a key role in these studies, but normalisation of RT-qPCR data requires a panel of validated stably expressed reference genes. This study aims to identify stable reference genes for RT-qPCR assays in three human derived muscle immortalized cell lines: one healthy WT (from a 16-year-old donor), and two dystrophic lines, DMD1 (from a 11-year-old patient carrying a stop codon mutation on exon 59) and DMD2, from a 14-year-old patient carrying an exon 48–50 deletion. We screened a pool of 14 candidate genes ( ACTB, HPRT1, RPL13A, RPS18, GAPDH, ALAS1, UBC, YWHAZ, IPO8, PSMC4, HSP90AB1, NONO, CSNK2A2, AP3D1 ), investigating stability of expression from proliferation through to 11 days of myogenic differentiation. Data were analysed using four complementary approaches (Bestkeeper, geNorm, Normfinder and DeltaCt) to determine the most appropriate references both within and between cell lines. Our study shows that RPS18, UBC, YWHAZ scored highly across all comparisons, and we therefore suggest that these three genes represent an appropriate reference panel for these human myogenic cell lines, regardless of genotype or differentiation stage.
Exploring the hereditary genetic mutational landscape of breast and ovarian cancer in Estonia
The influence of paternal preconception health on infant birth weight: A scoping review
Birth weight is an important determinant of infant growth and development associated with neonatal morbidity (e.g., respiratory distress, hypoglycemia) and mortality, as well as long-term health risks such as developmental delays and chronic conditions (e.g., asthma, type 2 diabetes) in later life. These adverse health outcomes are particularly concerning when infants are born small or large for their gestational age. A potential strategy to improve optimal birth weight is preconception care, with consistent evidence demonstrating a relationship between maternal preconception health and infant birth weight. However, little attention has been given to the influence of paternal preconception health on pregnancy outcomes. This scoping review aimed to capture the existing literature and highlight evidence gaps regarding associations between paternal preconception health and infant birth weight. We followed the Joanna Briggs Institute methodology and the Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for Scoping Reviews. The review considered studies that included men in the preconception period who identified as the parent of a child for whom infant birth weight outcomes were reported. Medline, PsycINFO, Embase, Scopus and CINAHL databases were searched to June 30, 2024. Two independent reviewers screened the titles/abstracts and full-text articles. Data extraction was performed independently by two researchers using a standardized form in Covidence. The data were synthesized narratively according to the paternal preconception health factors identified within the included studies (e.g., physical well-being, health behaviors, substance use, environmental exposures, mental health, and treatment effects). From 7,690 citations, 57 published studies were included in the review. Most studies were conducted in China (n = 18, 31.6%) or the United States (US) (n = 17, 29.8%) and used a cohort design (n = 54, 94.7%). Our review identified growing evidence that specific paternal preconception factors, such as physical well-being (e.g., BMI, physical health), certain medications (e.g., recreational drugs, sulfonylureas, diazepam), and environmental chemical exposure, may adversely influence infant birth weight. There are mixed findings related to other paternal health factors, including some health behaviors (e.g., nutrition, sleep, physical activity), substance use, and mental health. Consideration should be given to expanding preconception counseling and public health initiatives to include fathers, to improve paternal health and potentially reduce risks to offspring (e.g., birth weight). We also identified key areas where further research is required to advance knowledge in this field.
NMR characterisation of biopolymers and lipids from hemp pomace treated with Thermomyces lanuginosus
Abstract The influence of Thermomyces lanuginosus on the chemical structure of biopolymers and lipids from hemp pomace during solid-state fermentation (SSF) was studied using Nuclear Magnetic Resonance (NMR) spectroscopy. The samples of hemp pomace before, during and after SSF were used for the isolation of biopolymers (lignin, cellulose, hemicellulose) and lipids, which were subsequently analyzed using solution and solid-state NMR spectroscopy. It was observed that SSF significantly alters the composition and quality of individual biopolymers. An increase in the carbonyl group content in lignin was noted. In lipid samples, a significant reduction in mono-, di-, and triglycerides occurred accompanied by an increase in glycerol and unsaturated fatty acids. SSF also notably impacted phosphorus-containing compounds in the hemp pomace. These results demonstrate that SSF enables targeted modification of key chemical components in hemp pomace. By altering the structure of lignin, breaking down complex lipids, and affecting phosphorus-containing compounds, SSF improves the chemical quality and functionality of the biomass. This highlights its potential as an effective method for upgrading agricultural residues into more valuable and versatile materials supporting sustainable biorefinery applications.
Quantifying the impact of great coaches on Olympic medal predictions: A CPD-D3 model analysis
The step-up effect of great coaches on Olympic performance has been widely recognized, but its dynamic influence mechanism and quantitative evaluation remain methodological challenges. This study proposes a Change-Point Driven Difference-in-Differences with Decay Model ( CPD-D 3 ), which integrates the CUSUM algorithm, dynamic difference method (DID), and exponential decay function. The Great Coach effect’s nonlinear characteristics and time attenuation rule were analyzed systematically. First, based on the improved CUSUM algorithm to detect the abrupt points of performance, the dual test mechanism of medal continuity and competition size stability was introduced to filter the pseudo-abrupt signals (such as the host effect and short-term strategic interference). Secondly, a hierarchical DID model was used to quantify the net effect of heterogeneous coach turnover events to solve the problem of traditional methods ignoring the dynamic confounding bias and run-in period. Finally, the sustainability difference of the coaching effects is revealed by the half-life model. Empirical studies show that the effect half-life of a systematic coaching system (such as Zhou Jihong coaching the Chinese diving team) is more than 20 years, while the technology-driven intervention (such as the AI tactical optimization for Japanese judo) has a half-life of only 5.3 years. The model predicts that in the 2028 Los Angeles Olympics, the introduction of great coaches will enable the Brazilian swimming team to achieve a breakthrough from 0 to 5 medals (95% CI: 4.7–6.3). This study provides an explainable and predictive framework for the allocation of coaching resources in Olympic strategy, and its methodology can be extended to dynamic causal inference in policy evaluation and organizational management.
Post-COVID-19 surge in Guillain-Barré syndrome during the Omicron wave in China with clinical characteristics and potential immune-mediated pathways
Abstract This multicenter study investigated the epidemiological and clinical characteristics of Guillain-Barré syndrome (GBS) during China’s Omicron wave (December 2022–February 2023), and compared the number of GBS hospitalizations with the historical data for the same period from 2018 to 2022. A retrospective analysis was conducted at two tertiary hospitals, categorizing patients into COVID-GBS (case group) and Non-COVID-GBS (control group). During the Omicron wave, the number of GBS hospitalizations was 1.5 times higher compared to the period of 2018–2019 (99 cases vs. 66 cases). Poisson regression analysis confirmed a significant increase in GBS incidence during the Omicron wave (December 2022–February 2023) compared to the 2018–2019 baseline period, with an IRR of 1.541 (95% CI: 1.123–2.129, p = 0.0079). COVID-19-associated GBS patients were significantly older (54.04 vs. 42.06 years, p = 0.002) and exhibited higher rates of cranial nerve involvement ( p = 0.014), particularly bulbar involvement ( p = 0.009). Acute severity was greater in COVID-19-associated cases, evidenced by elevated ICU admissions, higher peak GBS disability scores ( p = 0.048), increased mechanical ventilation needs, and one fatality. The median latency from COVID-19 infection to neurological onset was 9.5 days (IQR: 8–14). Despite these acute differences, 6-month disability outcomes showed no significant divergence between groups, suggesting similar long-term prognoses. The surge in GBS incidence aligns with broader reports of elevated GBS rates during COVID-19 surges, though mechanistic links may involve immune-mediated pathways rather than direct viral causation.
The 5G COVID-19 Digital Wildfire: An evolving network of Twitter contacts to explore phase transition metaphors in viral misinformation
Shortly after the first COVID-19 cases became apparent in December 2019, rumors spread on social media suggesting a connection between the virus and the 5G radiation emanating from the recently deployed telecommunications network. In the course of the following weeks, this idea gained increasing popularity, and various alleged explanations for how such a connection manifests emerged. Ultimately, after being amplified by prominent conspiracy theorists, a series of arson attacks on telecommunication equipment followed, concluding with the kidnapping of telecommunication technicians in Peru. In this paper, we study the spread of content related to a conspiracy theory with harmful consequences, a so-called Digital Wildfire (DW). In particular, we investigate the 5G and COVID-19 DW on Twitter before, during, and after its peak in April and May 2020. For this purpose, we examine the community dynamics in complex temporal interaction networks underlying Twitter user activity. We assess the evolution of this particular DW by appropriately defining the temporal dynamics of communication in communities within social networks. We observe that, for this specific DW, the number of interactions of the users participating in the DW, as well as the size of the engaged communities, both exhibit visual patterns suggestive of power-law distributions, consistent with other social networks, though based on exploratory inspection rather than formal statistical tests. Moreover, our exploratory analysis elucidates the possibility of conceptualizing the phases of a DW, as per established literature. We identify one such phase as a potential critical shift, marked by a shift from sporadic tweets to a global spreading event, highlighting patterns suggestive of dramatic scaling in misinformation propagation, used heuristically without quantitative physical parameters. Additionally, we argue that patterns suggest the observed shift is associated with influential users, who appear to amplify the spread of misinformation, though causality is exploratory. Lastly, our data suggest that the characteristics of such events could contribute to prediction models, at least in some instances. From this data, we hypothesize that monitoring minor peaks in user interactions, which precede the critical phase culminating in real-world consequences, could serve as an early warning system, aiding in the anticipation and potentially the mitigation of DWs.
Alkaloids from Evodia rutaecarpa inhibit the occurrence and development of gallbladder cancer in vivo and in vitro
Preparation and luminescent properties of color-adjustable La1-x-ySiBO5: xTb3+, yEu3+ phosphor for NUV-LEDs
A series of La 1-x-y SiBO 5 :xTb 3+ , yEu 3+ phosphors was synthesized through high-temperature solid-state reaction. The crystal structure, morphology, and luminescence properties of the phosphors were characterized by employing X-ray diffraction, scanning electron microscopy, photoluminescence, photoluminescence excitation and fluorescence lifetime measurements. Results show that the excitation spectra of La 1-x SiBO 5 :xTb 3+ and La 1-y SiBO 5 :yEu 3+ overlap at 300–400 nm, and the La 1-x-y SiBO 5 :xTb 3+ , yEu 3+ phosphors emit yellowish green (530–560 nm) and red (580–650 nm) light under 377 nm excitation. When x = 0.05 and y increases from 0.005 to 0.05, the emission intensity of Tb 3+ decreases gradually, whereas that of Eu 3+ increases gradually. This trend indicates energy transfer from Tb 3+ to Eu 3+ and color change from green to yellow and then red. The fluorescence lifetime test further confirms energy transfer from Tb 3+ to Eu 3+ . The prepared LaSiBO 5 :Tb 3+ , Eu 3+ phosphors exhibit effective tunable emission and near ultraviolet excitation and thus have potential applications in White-LEDs.
Crack propagation mechanism and life prediction of liner under thermal fatigue loads
Respiratory syncytial virus burden among Ugandan adults aged ≥65 years: A 15-year sentinel surveillance study of prevalence, coinfections, and comorbidities (2010–2025)
Background Respiratory syncytial virus is an important cause of acute respiratory illness in older adults, yet data from sub-Saharan Africa remain scarce. Better understanding of its prevalence, coinfections, seasonal patterns, and risk factors in older populations is essential for strengthening surveillance systems and informing prevention strategies in low-resource settings. Methods We conducted a retrospective cross-sectional study using Uganda’s national influenza-like illness and severe acute respiratory infection sentinel surveillance data from December 2010 to January 2025. Adults aged ≥65 years with real-time-PCR results for respiratory syncytial virus, influenza A and B, and SARS-CoV-2 were included. Descriptive analyses summarized prevalence, clinical characteristics, and temporal trends. Poisson regression with robust variance estimated adjusted prevalence ratios for factors associated with infection and hospitalization. Results Among 545 illness episodes (mean age 73.2 years; 54.1% female), the period prevalence of respiratory syncytial virus across 2010–2025 was 4.8% (95% CI 3.3–6.9), comparable to influenza A (4.2%) and lower than SARS-CoV-2 (6.4%). Most RSV cases were mono-infections (92.3%), with rare respiratory syncytial virus–influenza coinfections (0.4%) and no respiratory syncytial virus–SARS-CoV-2 coinfections. Asthma and pneumonia were independent predictors of infection. Hospitalization was strongly associated with asthma, pneumonia, and heart disease. Activity showed seasonal peaks in March and June, with a marked decline during 2020–2021 and resurgence thereafter. Conclusions RSV is a consistent contributor to medically attended respiratory illness among older Ugandan adults, with prevalence similar to influenza A. Although strong associations with asthma and pneumonia were observed, asthma-related findings are based on few cases and should be considered hypothesis-generating. Seasonal clustering and post-pandemic resurgence support integrating respiratory syncytial virus into routine respiratory surveillance and inform the targeted introduction of preventive interventions, including vaccination, in low- and middle-income settings.