Search Results (448)

PSR B1259-63/LS 2883 is a well-studied gamma-ray binary hosting a pulsar in a 3.4-year eccentric orbit around a Be-type star. Its non-thermal emission spans from radio to TeV energies, exhibiting a significant increase near the periastron passage. This paper is dedicated to the analysis of INTEGRAL observations of the system following its last periastron passage in June 2024. We aim to study the spectral evolution of this gamma-ray binary in the soft (0.3–10 keV) and hard (30–300 keV) X-ray energy bands. We performed a joint analysis of the data taken by INTEGRAL/ISGRI in July–August 2024 and quasi-simultaneous Swift/XRT observations. The spectrum of the system in the 0.3–300 keV band is well described by an absorbed power law with a photon index of $\Gamma =1.42\pm 0.03$. We place constraints on potential spectral curvature, limiting the break energy $E_{\mathrm{b}}>30$ keV for $\Delta \Gamma >0.3$ and cutoff energy $E_{\mathrm{cutoff}}>150$ keV at a 95% confidence level. For one-zone leptonic emission models, these values correspond to electron distribution spectral parameters of $E_{\mathrm{b},\mathrm{e}}>0.8$ TeV and $E_{\mathrm{cutoff},\mathrm{e}}>1.7$ TeV, consistent with previous constraints derived by H.E.S.S. Full article

Background: Environmental exposures, such as per- and polyfluoroalkyl substances (PFAS), in conjunction with social and behavioral factors, can significantly impact liver health. This research investigates the combined effects of PFAS (perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS), alcohol consumption, smoking, income, and education on liver function among the U.S. population, utilizing data from the 2017–2018 National Health and Nutrition Examination Survey (NHANES). Methods: PFAS concentrations in blood samples were analyzed using online solid-phase extraction combined with liquid chromatography–tandem mass spectrometry (LC-MS/MS), a highly sensitive and specific method for detecting levels of PFAS. Liver function was evaluated using biomarkers such as alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), gamma-glutamyltransferase (GGT), total bilirubin, and the fatty liver index (FLI). Descriptive statistics and multivariable linear regression analyses were employed to assess the associations between exposures and liver outcomes. Bayesian Kernel Machine Regression (BKMR) was utilized to explore the nonlinear and interactive effects of these exposures. To determine the relative influence of each factor on liver health, Posterior Inclusion Probabilities (PIPs) were calculated. Results: Linear regression analyses indicated that income and education were inversely associated with several liver injury biomarkers, while alcohol use and smoking demonstrated stronger and more consistent associations. Bayesian Kernel Machine Regression (BKMR) further highlighted alcohol and smoking as the most influential predictors, particularly for GGT and total bilirubin, with posterior inclusion probabilities (PIPs) close to 1.0. In contrast, PFAS showed weaker associations. Regression coefficients were small and largely non-significant, and PIPs were comparatively lower across most liver outcomes. Notably, education had a higher PIP for ALT and GGT than PFAS, suggesting a more protective role in liver health. People with higher education levels tend to live healthier lifestyles, have better access to healthcare, and are generally more aware of health risks. These factors can all help reduce the risk of liver problems. Overall mixture effects demonstrated nonlinear trends, including U-shaped relationships for ALT and GGT, and inverse associations for AST, FLI, and ALP. Conclusion: These findings underscore the importance of considering both environmental and social–behavioral determinants in liver health. While PFAS exposures remain a long-term concern, modifiable lifestyle and structural factors, particularly alcohol, smoking, income, and education, exert more immediate and pronounced effects on hepatic biomarkers in the general population. Full article

Ecological restoration in the cold and high-altitude mining areas of the Qinghai–Tibet Plateau is faced with dual challenges of extreme environments and insufficient microbial adaptability. This study aimed to screen local microbial resources with both extreme environmental adaptability and plant-growth-promoting functions. Local fungi (DK; F18-3) and commercially available bacteria (B0) were used as materials to explore their regulatory mechanisms for plant growth, soil physicochemical factors, microbial communities, and metabolic profiles in the field. Compared to bacterial treatments, local fungi treatments exhibited stronger ecological restoration efficacy. In addition, the DK and F18-3 strains, respectively, increased shoot and root biomass by 23.43% and 195.58% and significantly enhanced soil nutrient content and enzyme activity. Microbiome analysis further implied that, compared with the CK, DK treatment could significantly improve the α-diversity of fungi in the rhizosphere soil (the Shannon index increased by 14.27%) and increased the amount of unique bacterial genera in the rhizosphere soil of plants, totaling fourteen genera. Meanwhile, this aggregated the most biomarkers and beneficial microorganisms and strengthened the interactions among beneficial microorganisms. After DK treatment, twenty of the positively accumulated differential metabolites (DMs) in the plant rhizosphere were highly positively associated with six plant traits such as shoot length and root length, as well as beneficial microorganisms (e.g., Apodus and Pseudogymnoascus), but two DMs were highly negatively related to plant pathogenic fungi (including Cistella and Alternaria). Specifically, DK mainly inhibited the growth of pathogenic fungi through regulating the accumulation of D-(+)-Malic acid and Gamma-Aminobutyric acid (Cistella and Alternaria decreased by 84.20% and 58.53%, respectively). In contrast, the F18-3 strain mainly exerted its antibacterial effect by enriching Acidovorax genus microorganisms. This study verified the core role of local fungi in the restoration of mining areas in the Qinghai–Tibet Plateau and provided a new direction for the development of microbial agents for ecological restoration in the Qinghai–Tibet Plateau. Full article

Background/Objectives: This study aimed to evaluate the effects of lung injury induced by insoluble uranium oxide particles on gut microbiota and related metabolites in rats. Methods: The rats were randomly divided into six UO₂ dose groups. A rat lung injury model was established through UO₂ aerosol. The levels of uranium in lung tissues were detected by ICP-MS. The expression levels of the inflammatory factors and fibrosis indexes were measured by enzyme-linked immunosorbent assay. Paraffin embedding-based hematoxylin & eosin staining for the lung tissue was performed to observe the histopathological imaging features. Metagenomic sequencing technology and HM700-targeted metabolomics were conducted in lung tissues. Results: Uranium levels in the lung tissues increased with dose increase. The expression levels of Tumor Necrosis Factor-α (TNF-α), Interleukin-1β (IL-1β), Collagen I, and Hydroxyproline (Hyp) in rat lung homogenate increased with dose increase. Inflammatory cell infiltration and the deposition of extracellular matrix were observed in rat lung tissue post-exposure. Compared to the control group, the ratio of Firmicutes and Bacteroides in the gut microbiota decreased, the relative abundance of Akkermansia_mucinphila decreased, and the relative abundance of Bacteroides increased. The important differential metabolites mainly include αlpha-linolenic acid, gamma-linolenic acid, 2-Hydroxybutyric acid, Beta-Alanine, Maleic acid, Hyocholic acid, L-Lysine, L-Methionine, L-Leucine, which were mainly concentrated in unsaturated fatty acid biosynthesis, propionic acid metabolism, aminoacyl-tRNA biosynthesis, phenylalanine metabolism, and other pathways in the UO₂ group compared to the control group. Conclusions: These findings suggest that uranium-induced lung injury can cause the disturbance of gut microbiota and its metabolites in rats, and these changes are mainly caused by Akkermansia_mucinphila and Bacteroides, focusing on unsaturated fatty acid biosynthesis and the propionic acid metabolism pathway. Full article

Background/Objectives: Biomarkers such as lens agglutinin-reactive alpha-fetoprotein and des-gamma-carboxy prothrombin, as well as biomarker- and/or clinical-parameter-derived composite models (GALAD, GAAP, ASAP, aMAP, Doylestown), may improve detection in addition to alpha-fetoprotein, yet comparative data across diverse populations remain limited. Methods: In this biobank-based case–control study, we evaluated 562 adults (120 healthy controls, 277 chronic liver disease, 165 hepatocellular carcinoma) from January 2019 to 2024. Diagnostic performance for any-stage and early-stage hepatocellular carcinoma was assessed across three thresholds: Youden-index-derived optimal cut-offs, research-established cut-offs, and cut-offs ensuring 90% specificity. Receiver operating characteristic analysis was performed. Subgroup analyses were stratified by etiology and alpha-fetoprotein status. Results: At optimal cut-offs, GALAD showed the highest sensitivity for any-stage (90.3%) and early-stage (89.1%) hepatocellular carcinoma, with 70–80% specificity. Using established cut-offs, GALAD retained the highest sensitivity for any-stage (75.8%) and early-stage (57.8%) hepatocellular carcinoma, with 93.5% specificity. GALAD demonstrated the best performance in non-viral hepatocellular carcinomas (area under the curve 0.872), whereas GAAP and ASAP showed similarly high area under the curve values in viral etiology (area under the curve 0.955–0.960). Conclusions: Our results demonstrate the consistent performance of the GALAD score across diverse populations and underscore its superiority over individual biomarkers and other composite models. Notably, the GAAP and ASAP scores—which use one less biomarker (AFP-L3)—exhibited comparable performance, particularly in viral etiology. These findings support the integration of the composite biomarker models into tailored hepatocellular carcinoma surveillance strategies. Full article

Accurate drought monitoring depends on selecting an appropriate cumulative distribution function (CDF) to model the original data, resulting in the standardized drought indices. In the numerous research studies, while rigorous validation was not made by scrutinizing the model assumptions and uncertainties in identifying theoretical drought CDF models, such oversights lead to biased representations of drought evaluation and characteristics. This research compares the parametric theoretical and empirical CDFs for a comprehensive evaluation of standardized Drought Indices. Additionally, it examines the advantages, disadvantages, and limitations of both empirical and theoretical distribution functions in drought assessment. Three drought indices, Standardized Precipitation Index (SPI), Streamflow Drought Index (SDI), and Standardized Precipitation Evapotranspiration Index (SPEI), cover meteorological and hydrological droughts. The assessment spans diverse applications, covering different climates and regions: Durham, United Kingdom (SPEI, 1868–2021); Konya, Türkiye (SPI, 1964–2022); and Lüleburgaz, Türkiye (SDI, 1957–2015). The findings reveal that theoretical and empirical CDFs demonstrated notable discrepancies, particularly in long-term hydrological drought assessments, where underestimations reached up to 50%, posing risks of misinformed conclusions that may impact critical drought-related decisions and policymaking. Root Mean Squared Error (RMSE) for SPI3 between empirical and best-fitted CDF was 0.087, and between empirical and Gamma it was 0.152. For SDI, it ranged between 0.09 and 0.143. The Mean Absolute Error (MAE) for SPEI was approximately 0.05 for all timescales. Additionally, it concludes that empirical CDFs provide more reliable and conservative drought assessments and are free from the constraints of model assumptions. Both approaches gave approximately the same drought duration with different intensities regarding drought characteristics. Due to the complex process of drought events and different definitions of drought events, each drought event must be studied separately, considering its effects on different sectors. Full article

Background/Objectives: Myopia is associated with peripapillary changes, namely, gamma peripapillary atrophy (γPPA) and optic disc ovalization, estimated by the ovality index (OI). These changes have been suggested to be promoted by adduction. Recent studies highlight that near reading significantly contributes to the development and progression of myopia and that the interpupillary distance (IPD) influences vergence amplitudes. While both adduction and convergence are involved during near reading, a potential link between IPD and myopic peripapillary changes has not yet been explored. We, therefore, sought to determine whether IPD is related to the OI or γPPA width. Methods: In this monocentric cross-sectional study, 100 eyes from 100 adults (mean age of 62.6 ± 13.7 years) were analyzed. Axial length (AL), refractive error, and IPD were recorded. The OI and γPPA width were assessed using spectral-domain Optical Coherence Tomography. Pearson correlations and multivariable linear regressions were performed, adjusting for age, gender, and myopia status. Results: IPD showed no significant correlation with the OI (r = 0.001; p = 0.989) or γPPA (r = −0.028; p = 0.789). A weak, non-significant correlation was found between IPD and AL (p = 0.059). In contrast, AL was strongly correlated with both a lower OI and wider γPPA (p < 0.001). Conclusions: These findings suggest that IPD-related biomechanical forces do not influence optic nerve head (ONH) shape or γPPA. Axial elongation remains the key driver of myopic ONH remodeling. Full article

Background: Administration of PARP inhibitors against breast and ovarian cancers with BRCA1 and BRCA2 mutations has shown clinical benefits in patients. However, these agents are also toxic and have a narrow therapeutic index. Objectives: In this work, we aimed to identify membrane proteins that are specifically upregulated in these cancers. Methods: We interrogated public datasets to analyze genes upregulated or downregulated when these mutations were present, compared with wild-type cancers. Surface protein expression and functional annotation analyses were also performed. Results: In breast cancer, we identified 11 upregulated and 44 downregulated transcripts in BRCA1-mut, while 10 upregulated and 57 downregulated transcripts were identified in BRCA2-mut cancers. In ovarian cancer, 79 transcripts were upregulated and 123 were downregulated in BRCA1-mut cancers, while five were upregulated and seven were downregulated in BRCA2-mut tumors. Regarding the biological function related to these genes, in BRCA1-mutated ovarian cancers, the main functions of upregulated genes included MHC assembly or regulation of the interferon gamma pathway; in BRCA2-mut ovarian cancers, regulation of phosphorylation and signaling; in BRCA1-mut breast cancers, cell damage repair and angiogenesis; and finally, in BRCA2-mut breast cancers, cytokine production and T-cell migration. Genes expressed in the surface membrane or extracellular matrix and related to patient outcomes included B3GNT7 and CTSV in BRCA2-mut breast cancers, exhibiting detrimental prognoses. CD6, CXCL9, and CXCL13 were associated with favorable outcomes in BRCA1-mutant ovarian cancers. The last three genes were also correlated with the infiltration of effector T cells and dendritic cells in ovarian tumors. Conclusions: In summary, we identified deregulated candidate genes that could be used as therapeutic targets. Full article

Background/Objectives: The prevalence of childhood obesity has recently increased, particularly during the COVID-19 pandemic, owing to lifestyle changes as a result of public health regulations and guidelines introduced by governments worldwide. The aim of our study was to evaluate the impact of novel e-Health applications in addressing childhood obesity prior to and during the COVID-19 pandemic. Methods: The study was conducted as part of the four-year European project BigO (Horizon2020, No.727688). A total of 86 children and adolescents with overweight and obesity (mean age ± standard error of the mean: 11.82 ± 0.25 years; 49 males, 37 females; 31 prepubertal, 55 pubertal) were studied prospectively for 1 year prior to the pandemic (non-COVID-19 group, n = 50) and during the pandemic (COVID-19 group, n = 36). Based on the body mass index (BMI), subjects were classified as having morbid obesity (n = 40, 46,51%) obesity (n = 21, 24.42%), overweight (n = 22, 25.58%), and normal ΒΜΙ (n = 3, 3.49%) according to the International Obesity Task Force cut-off points. The data collection system utilized the BigO technology platform, which connects to a smartphone and smartwatch to objectively record each patient’s diet, sleep, and physical activity. Participants used the BigO system continuously for 4 weeks and wore the smartwatch for specific periods during the week. Subsequently, they entered a personalized, multidisciplinary lifestyle intervention program for 4 months and used the system again for 4 weeks. Results: The key finding was a significantly higher improvement rate in BMI category among children and adolescents during the COVID-19 pandemic (58.3%) compared to before the pandemic (36%). Both groups showed significant reductions in BMI, BMI z-score, insulin resistance indices (homeostatic model assessment and quantitative insulin sensitivity check index), blood pressure, gamma-glutamyl transferase, and insulin concentrations, alongside increases in high-density lipoprotein cholesterol (p < 0.01). Notably, the COVID-19 group experienced a significantly greater reduction in BMI z-score at 12 months compared to the non-COVID-19 group (p < 0.05). Conclusions: Our results reveal that the COVID-19 group demonstrated better compliance with lifestyle interventions and experienced more significant improvements in cardiometabolic risk factors. This suggests that the innovative e-Health applications were successful in managing childhood obesity despite the challenges caused by the COVID-19 pandemic. Full article

Free space optics (FSO) aims to perform as one of the best optical wireless channels to design a reliable, flexible, and cost-effective communication system. In FSO systems, mode-division multiplexing (MDM) transmission is a proven technique to expand transmission capacity per communication link. Thus, a 16 × 10 Gbps MDM-FSO system using fiber Bragg grating (FBG) sensors for the coexistence of communication and sensing, exploiting FSO links to transmit distinct Laguerre-Gaussian (LG) beams at a 1000–1900 m range, is proposed. The results illustrate that the system can transmit higher-order LG beams with sensor temperatures of 20–120 °C over a 1500 m range under clear air, drizzle, and moderate haze weather. Also, an improved performance is achieved in gamma–gamma compared to the log-normal distribution model for 10⁻⁶–10^−2.5 index modulation under weak-to-strong turbulence. The proposed system is capable of offering a high optical signal-to-noise ratio (OSNR) and gain of 113.39 and 15.43 dB, respectively, at an aggregate data rate of 160 Gbps under different atmospheric scenarios. Moreover, the proposed system achieves better system performance compared to existing works. Full article

Introduction: The clinical implementation of noninvasive tests for liver fibrosis assessment has attracted increasing attention, particularly for diagnosing advanced fibrosis (≥F3). This observational study aimed to evaluate the stratification accuracy of nine direct and seven indirect biomarkers across four etiologies: chronic hepatitis B (CHB), chronic hepatitis C (CHC), alcoholic liver cirrhosis (ALC), and nonalcoholic liver cirrhosis (NALC). Materials and Methods: Our study was conducted on 116 participants, including 96 with chronic liver disease (16 CHB, 15 CHC, 49 ALC, and 16 NALC) and 20 healthy controls. The values of direct (aspartate aminotransferase, alanine aminotransferase, total bilirubin, serum albumin, platelet count, international normalized ratio, gamma-glutamyl transpeptidase, CD5 antigen-like, and transforming growth factor-beta 1) and indirect non-serological biomarkers (De Ritis ratio, albumin–bilirubin score, gamma-glutamyl transpeptidase-to-platelet ratio, aspartate aminotransferase-to-platelet-ratio index, fibrosis-4 index, INR-to-platelet ratio, and fibrosis quotient) were analyzed for their discriminative power in fibrosis stratification. Results: Statistical analyses revealed a significant correlation (0.05 level; two-tailed), and AUC 95% CI ranged within 0.50–1.00 between the direct and indirect biomarker values across all etiologies. Among the evaluated biomarkers, the recorded AUC was 0.998 in CHB for APRI, 0.981 in CHC for FIB-4, and 1.000 in ALC and NALC for APRI and AST, respectively, while CD5L consistently achieved an AUC of 1.000 across all etiologies. Conclusions: These findings suggest that applying a multifactorial approach in liver pathology may improve diagnosis accuracy compared to the use of individual biomarkers and can provide data that may inform the development of clinically applicable mathematical models. Full article

Hyperglycemia during fetal development disturbs extracellular matrix (ECM) synthesis and deposition patterns, which disrupts organogenesis and adult organ function. Although the ECM cooperates in pancreas development, little is known about the effects of hyperglycemia on the pancreatic ECM during development. This study investigates the effect of severe maternal hyperglycemia on ECM composition and endocrine pancreas development in E19.0 mouse fetuses. Deposition patterns of pan-laminin, laminin (alpha 1 and gamma 1 chains) and integrin alpha 3 were evaluated by immunostaining. The proliferative index of islet cells and alpha and beta cell distribution were evaluated by PCNA, glucagon and insulin immunostaining, respectively. Pdx1 and Pax4 expressions were analyzed by RT-qPCR. While for pan-laminin and laminin (alpha1 and gamma1 chains) deposition was weaker in the endocrine pancreas of hyperglycemic mothers’ fetuses, integrin alpha 3 deposition in the basement membrane was increased. The proliferative index of endocrine cells was lower in the hyperglycemic group, while the beta-cell area was increased. In addition, there was a tendency towards lower Pdx1 and increased Pdx4 expression. These data suggest that maternal hyperglycemia alters fetal endocrine pancreas morphogenesis by modifying peri-islet basement membrane molecule patterns, promoting a decrease in endocrine cell proliferation associated with changes in the expression of important growth factors for the beta cells differentiated and the proliferative state. Full article

The Activity Concentration Index (ACI), defined in Directive 2013/59/Euratom, serves as a criterion for the radiological significance of Naturally Occurring Radioactive Materials (NORMs) concentrated in building materials, considering related exposures due to the external gamma radiation field but not due to radon concentration levels. This study proposes a simple way of applying the ACI to interior spaces when concrete is the dominant construction material. Three calculation methods were examined, using four spaces within existing buildings, namely Method A, using the building elements’ mass proportions as a weighting factor; Method B, using only the geometrical characteristics of the internal space; and Method C, combining the mass proportions and inverse square distances. This methodology proposes a way of calculating the ACI based on data provided by existing studies about NORM concentrations in building materials and, thus, no sampling and subsequent NORM concentration measurements were required. The spatial data could be easily determined using either building plans or in situ measurements, using a handheld laser distance meter. The advantages and disadvantages of all three methods were analyzed, along with a comparison to in situ gamma radiation field measurements, performed with a portable Geiger–Müller detector. All the methods showed proportionality to the measured values. Method C was found to be the most suitable, especially for existing buildings, and Method A is recommended for early-stage design assessments. Full article

Objective: This study proposes a novel deep learning approach for enhancing low-dose bone scintigraphy images using an Enhanced Convolutional Autoencoder (ECAE), aiming to reduce patient radiation exposure while preserving diagnostic quality, as assessed by both expert-based quantitative image metrics and qualitative evaluation. Methods: A supervised learning framework was developed using real-world paired low- and full-dose images from 105 patients. Data were acquired using standard clinical gamma cameras at the Nuclear Medicine Department of the University General Hospital of Alexandroupolis. The ECAE architecture integrates multiscale feature extraction, channel attention mechanisms, and efficient residual blocks to reconstruct high-quality images from low-dose inputs. The model was trained and validated using quantitative metrics—Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM)—alongside qualitative assessments by nuclear medicine experts. Results: The model achieved significant improvements in both PSNR and SSIM across all tested dose levels, particularly between 30% and 70% of the full dose. Expert evaluation confirmed enhanced visibility of anatomical structures, noise reduction, and preservation of diagnostic detail in denoised images. In blinded evaluations, denoised images were preferred over the original full-dose scans in 66% of all cases, and in 61% of cases within the 30–70% dose range. Conclusion: The proposed ECAE model effectively reconstructs high-quality bone scintigraphy images from substantially reduced-dose acquisitions. This approach supports dose reduction in nuclear medicine imaging while maintaining—or even enhancing—diagnostic confidence, offering practical benefits in patient safety, workflow efficiency, and environmental impact. Full article

Background: Lumpy skin disease (LSD) is major transboundary disease affecting cattle and water buffaloes, indirectly causing huge socio-economic losses. Following its first outbreak in India in 2019, the heterologous Goatpox (Uttarkashi strain) vaccine mitigated LSD. Objective: Due to limited data on the spatiotemporal distribution of the disease, this study investigates its dynamics and presents findings from a field study conducted in Maharashtra, India. This study evaluates the safety, immunogenicity, and duration of immunity provided by a heterologous vaccine. Additionally, it examines post-vaccination responses in relation to factors such as age, gender, and breed. Methods: This study employed spatiotemporal analysis of lumpy skin disease (LSD) outbreaks from 2020 to 2024 using GeoDa (v1.22), incorporating Moran’s I and Getis-Ord Gi* statistics to identify spatial clustering patterns. A randomized field trial was conducted to evaluate vaccine safety and immunogenicity in 657 cattle across seven districts. Humoral immune responses were assessed using the serum neutralization test (SNT) and indirect enzyme-linked immunosorbent assay (ELISA), while cell-mediated immunity was evaluated via Interferon-gamma (IFN-γ) ELISA. For sero-monitoring, a total of 1925 serum samples from 22 districts were analyzed. Additionally, statistical analyses (n = 1925), including the Kappa Index, ANOVA, and logistic regression, were performed using SPSS v27 to investigate the influence of factors such as age, sex, and breed (significance level: p < 0.05). Results: LSD exhibited significant spatial clustering across Maharashtra. The Goatpox vaccine was 100% safe, with no adverse reactions. Protective antibody titers (≥1:8) were observed in 96.9% of vaccinated cattle by 14–21 days post-vaccination (dpv), peaking at 60 dpv before declining at 150 dpv. The cell-mediated immune response peaked at 28 dpv. Clinical monitoring for one year showed that only 2% of vaccinated cattle developed mild LSD symptoms after nine months, with no mortality. At six months post-vaccination, seroconversion was 69.7%, with breed significantly influencing seropositivity. Conclusions: This study confirms the Goatpox vaccine’s safety and strong immunogenicity in cattle, marking its first large-scale evaluation in the Indian subcontinent. Further research is needed to assess long-term immunity and protection against virulent LSD strains. Full article