bluuebunny/crossref_metadata_2025_split huggingface dataset:
Unveiling Clonostachys rosea bioactives: Investigating antifungal potential against Fusarium oxysporum through in vitro and in silico studies
Authors: Shravani Vyamasani , Iruthayasamy Johnson , Nallusamy Saranya , Govindasamy Jothi , Eswaran Kokiladevi , Annaiyan Shanthi 
Published: August 2024

Abstract

Fusarium spp. pose significant threats to agriculture by causing wilt in various crops like ridge gourd. This study identifies Fusarium isolates from wilted ridge gourd plants and evaluates Clonostachys rosea's biocontrol potential. Twelve isolates were characterized using molecular and morphological analyses, revealing nine Fusarium oxysporum, two Fusarium brachygibbosum, and one Fusarium equiseti. Pathogenicity tests confirmed that F. oxysporum isolates were highly virulent, while other two species were weakly pathogenic. Antagonistic assays demonstrated that C. rosea significantly inhibited the growth of Fusarium spp. up to 71.59%. Microscopic analysis revealed its mycoparasitic activity, involving hyphal encirclement and degradation of Fusarium hyphae. Metabolite profiling through GC-MS characterized 44 bioactive compounds, including fatty acids, alcohols, amines, thiols, triazoles, and hydrazines. Molecular docking analysis revealed high binding affinities of these metabolites with key fungal proteins, suggesting potential mechanisms of antifungal action. C. rosea demonstrates potential as a biocontrol agent, with its antifungal metabolites providing new insights and strategies for managing Fusarium wilt in ridge gourd.
Comparison of the red fox gut microbiota among different habitat types in southern Anatolia
Authors: Akbaba Burak , Küçükyıldırım Sibel , Ünal Hasan 
Published: August 2024

Abstract

Environmental conditions, especially diet, affect the diversity of gut microbiota (GM). This diversity within and between populations may influence the host’s health and fitness, therefore plays important roles in adaptation. Regarding this, we collected fecal samples from natural, rural, suburban, and urban habitats to reveal the interaction between diet and compositional and functional diversity of GM of a generalist carnivore, the red fox. The prokaryotic diversity of fecal microbiota was investigated by sequencing the 16S rRNA gene V3-V4 regions. 46 archaeal and bacterial phyla were identified, and Firmicutes was the most common phylum in most samples. The dominant genera in the GM of the red fox were Collinsella, Fusobacterium, Faecalibacterium, Escherichia-Shigella, and Blautia. Fusobacterium was significantly more abundant in suburban (16.0%), natural (11.0%), and rural habitats (10.8%) than in urban habitats (2.0%) indicating dietary differences of the red foxes that feed close to human settlements. However, PICRUSt (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States) showed that the host’s habitat did not significantly affect the functional diversity. Our study determined the compositional changes of the GM of a wild animal for the first time in the Anatolian peninsula and revealed the effects of dietary changes, especially urbanization, on the diversity of GM of red foxes.
Viral infection by CABMV-cowpea aphid-borne mosaic virus- reduces gas exchange in passion fruit leaves
Authors: Bezerra Luan Baritiello da Silva , Viana Alexandre Pio , Bernado Wallace de Paula , Mendes Débora Souza , Campostrini Eliemar , Silva Flavia Alves da 
Published: August 2024

Abstract

Passion fruit (Passiflora spp.) is a highly important crop with increasing yield levels in recent years. However, its expansion in Brazil faces challenges, including diseases affecting the crop. The main disease is passion fruit woodiness, caused by cowpea aphid-borne mosaic virus (CABMV), which leads to leaf and fruit symptoms, compromising both quality and production. Viral infections directly affect plant physiology and often disrupt gas exchange by impacting leaf function. In this study, our aim was to analyze gas exchange in view of a scale of foliar symptoms caused by CABMV and to estimate genetic parameters to aid in the selection of genotypes with superior physiological performance. Gas exchange measurements were performed on passion fruit leaves from full-sib families showing varying symptoms of infection, as well as on leaves from resistant (P. setacea) and susceptible (P. edulis) individuals. Disease severity was assessed on a rating scale associated with the SPAD index. The estimation of genetic parameters facilitated the determination of variances, heritability and accuracy for each physiological variable examined. Our results confirmed that the presence of CABMV in leaves reduced photosynthetic rates and stomatal conductance, especially in the face of moderate and severe symptoms. Furthermore, genotypic variation played a more significant role in photosynthetic rate, intercellular CO2 concentration and transpiration rate compared to phenotypic variation. Heritability values ranged from moderate to high, and accuracy values were high, validating the reliability of the analyses. In conclusion, the study demonstrates, for the first time, the negative impact of CABMV infection on gas exchange in passion fruit leaves. In addition, it highlights the potential use of physiological variables, such as photosynthesis, in the selection of individuals with superior physiological performance in passion fruit breeding programs.
Assessment of Single Photon Emission Computed Tomography 123I-IMP Brain Scan Parameters Using Low Energy High Resolution Collimator and 3D Iterative Image Reconstruction Algorithm (Flash 3D)
Authors: Zhao Xiaofei , Ichihara Takashi , Inui Yoshitaka , Toyama Hiroshi , Suzuki Motoshi , Kung Boom Ting , Tang Chung ting , Takenaka Akinori , Ota Seiichiro , Inoue Masanori , Ishiguro Masanobu 
Published: August 2024

Abstract

Objective Statistical parametric mapping of 123I-IMP brain SPECT images has been used for brain disorders such as Alzheimer’s disease (AD) and dementia with Lewy bodies (DLB) for several decade. The analysis results highly dependent on the way how to construct the normal database (NDB), due to validity of spatial resolutions recovery, scatter and attenuation correction methods for quantification of SPECT value. And also, there is no NDB available for 3D image reconstruction algorithm (Flash 3D) so far. Purpose of this study is to evaluate whether the Siemens Symbia T6 SPECT/CT (Siemens Healthineers, Germany) with LEHR collimator and Flash3D reconstruction combined with computed tomography-attenuation correction (CT-AC) and scatter correction (SC) can be applied for 123I-IMP brain perfusion SPECT for Statistical image analysis.Methods LSF phantom, Cerebral blood flow brain phantom with skull cover (male bone, female bone, acrylic), cold rods phantom with male bone cover, and six chambers phantom with male bone cover were used. The acquisition time was determined by the SPECT count, that would be the condition of using SMS LEHR with 6 mCi of 123I-IMP administration and counting equivalent to 30 minutes of collection. The phantom conditions and the rotation radius (14, 15, 16cm) were changed and collected. Finally, the evaluation was performed using visual judgement by two independent nuclear medicine physicians, validity of spatial resolutions recovery, linearity of the radioactivity and SPECT value, and the gray-to-white matter count ratio were evaluated.Results Visual inspection of image determined image reconstruction with Gaussian filter 10mm should be used. The spatial resolutions were constant while change the rotation radius. There is good linearity relation between SPECT values and activity concentration of phantom, and the gray-to-white matter count ratio were almost the same while using male bone cover, female bone cover, and acrylic cover.Conclusions Siemens Symbia T6 SPECT/CT with LEHR collimator and Flash3D reconstruction combined with computed tomography - attenuation correction(CT-AC) and scatter correction (SC) can be used for SPECT 123I-IMP brain perfusion scanning with a LEHR collimator.
Dominant control of temperature on (sub-)tropical soil carbon turnover
Authors: Meyer Vera Dorothee , Köhler Peter , Smit Nadine , Lipp Julius , Wei Bingbing , Mollenhauer Gesine , Schefuß Enno 
Published: August 2024

Abstract

Carbon storage in soils is important in regulating atmospheric carbon dioxide (CO2). However, the sensitivity of the soil-carbon turnover time (τsoil) to temperature and hydrology forcing is still not fully understood. Here, we use radiocarbon dating of plant-derived lipids in conjunction with reconstructions of temperature and rainfall from an eastern Mediterranean sediment core receiving terrigenous material from the Nile-River watershed to investigate τsoil in subtropical and tropical areas during the last 18,000 years. We find that the τsoil was reduced by an order of magnitude over the last deglaciation and infer that this reduction was caused from amplified soil respiration rates. Our data indicate that the deglacial warming was the major driver of these changes while the impact of hydroclimate was relatively small. We conclude that increased CO2 efflux from soils into the atmosphere constituted a positive feedback to global warming. However, simulated glacial-to-interglacial changes in a dynamic global vegetation model underestimate our data-based reconstructions of soil-carbon turnover times suggesting that this climate feedback might be underestimated.
Urban Noise Dynamics during COVID-19 Lockdown: Machine Learning Perspectives from Mashhad, Iran
Authors: Ardalan Raheleh Valizadeh , Mohammadi Mitra , Bahadori Mohammad Sadegh , Mohammadi Mandana , Moezzi Seyed Mohammad Mahdi , Saloglu Didem 
Published: August 2024

Abstract

This paper investigates the impact of human activities on noise pollution in the Mashhad metropolis, Iran, as well as the fluctuations that occurred during the COVID-19 pandemic. By leveraging a dual strategy, a comprehensive review was initiated. First, the noise level measurements collected before (March 21 to April 20, 2019) and during (March 20 to April 19, 2020) the COVID-19 quarantine period at four key intersections in Mashhad are compared. The non-parametric Wilcoxon signed test was employed to evaluate the statistical significance of the observed changes. The results showed a statistically significant reduction in the noise level during the quarantine period at every four intersections. Next, a predictive modeling algorithm named random forest (RF) was developed to predict noise pollution levels by considering time factors such as month, day, hour, and cumulative hour. The RF model achieved a high R-squared value (0.914), representing a strong correlation between predicted and actual noise levels. The predictive power of this model was demonstrated by the root mean square error (RMSE) of 0.967 and the mean absolute error (MAE) of 0.620, indicating reasonable accuracy. This study demonstrates evidence that human activities are the main cause of noise pollution in Mashhad. The findings highlight the potential benefits of urban planning strategies that reduce traffic and noise generation. Furthermore, the development of a noise prediction model using a random forest approach provides a valuable tool for future noise management efforts in urban environments.
Utility PET/CT for identifying Prosthetic valve endocarditis in pediatric patients and correlating with outcomes
Authors: Fletes Gladys M. Arguello , Trenbeath Zachary T. , Hayes Kari L. , Malone LaDonna J. 
Published: August 2024

Abstract

Pediatric patients with a history of vascular stents or prosthetic valve replacement face an increased risk of infective endocarditis. Echocardiography and cardiac CT can be limited in some cases for diagnosing prosthetic valve endocarditis. PET/CT has shown promise for diagnosis in difficult cases in adults. We reviewed our clinical experience over 13 years and compared surgical findings and clinical outcomes. Utilizing PET/CT as a diagnostic test for prosthetic valve endocarditis in our study resulted in a positive predictive value of 87.5%, a negative predictive value 100% and an accuracy of 92.3%.
Research on the Microscopic Pore- Throat Structure and Reservoir Quality of Tight Sandstone Using Fractal Dimensions
Authors: He Taping , Zhou Yaoqi , Li Yuanhao , Xie Huanyu , Shang Yuehan , Cen Tongtong , Zhang Zhenwei 
Published: August 2024

Abstract

The pore-throat structure is a crucial parameter for evaluating the characteristics of reservoirs and the potential oil and gas resources. Analyzing the relationship between reservoir pore-throat variations and oil-bearing properties is essential. Through experiments such as thin-section casting, scanning electron microscopy (SEM), micro-computed tomography (micro-CT), and high-pressure mercury injection (HPMI), we examined the tight sandstone reservoirs from the Chang 4+5 members of the Yanchang Formation in the study area. This analysis elucidates the relationship between the pore-throat structure and fractal characteristics of the samples and their oil-bearing properties. The results show that : (1) The tight sandstone reservoirs in the study area mainly develop three types of pores: dissolution pores, residual intergranular pores, and microfractures. Residual intergranular pores are primarily controlled by early compaction processes, while dissolution processes easily form secondary pores, increasing the porosity of the reservoir. Microfractures can significantly enhance both the permeability of the reservoir. (2) Using the characteristic parameters of HPMI, the reservoir is classified into four categories, labeled as type I to type IV. As the categories progress from type I to type IV, pore-throat size decreases, porosity and permeability decrease, and reservoir properties deteriorate. The overall fractal dimension of pores decreases, while the fractal dimensions of individual pore types increase. Pore connectivity becomes more complex, and heterogeneity strengthens. (3) The reservoir porosity is strongly positively correlated with permeability. As reservoir properties improve, the number of macropores increases, leading to a higher Reservoir Quality Index (RQI) and better oil-bearing characteristics.
Urban arbovirus underreporting in a hyperendemic area of ​​Brazil: a population-based survey and implications for public health surveillance
Authors: Nobre Tayane , Fenner Andre Luiz Dutra , Araújo Emerson Luiz Lima , de Araújo Wildo Navegantes , Roux Emmanuel , Handschumacher Pascal , Gurgel Helen , Dallago Brunno , Hecht Mariana , Hagström Luciana , Ramalho Walter Massa , Nitz Nadjar 
Published: August 2024

Abstract

Background
Urban arboviruses pose a significant global burden, particularly in tropical regions like Brazil. São Sebastião, a lower-middle-class urban area just 26 km from the Brazilian capital, is a hyperendemic area for dengue cases. However, asymptomatic cases may obscure the actual extent of the disease. In this study, we measured the seroprevalence of dengue, Zika virus, and chikungunya, and compared these findings with surveillance data.
Methods
A cross-sectional study was conducted involving 1,535 households. ELISA serological tests were performed to detect IgM and IgG antibodies against dengue, Zika virus, and chikungunya. History of previous exposure to arbovirus, data on age, gender, and education level were collected through a questionnaire. Participants testing positive for IgM and/or IgG were classified as positive. Statistical analyses included tests for normality, associations, mean comparisons, and correlations. Positive serological results were compared with cases captured by local epidemiological surveillance.
Results
The study included 1,405 individuals, divided into two groups related to pre-pandemic and pandemic COVID-19 phases. Among participants, 0,7% to 28,8% self-reported history of dengue, Zika, or chikungunya. However, the estimated overall seroprevalence was 64.3% (95% CI: 61.8–66.7) for dengue virus, 51.4% (95% CI: 48.8–53.9) for Zika virus, and 5.4% (95% CI: 4.4–6.7) for chikungunya virus. Multiple arboviruses were noted at 4.0% (95% CI: 3.1–5.1). Advancing age and lower education were associated with higher exposure to arboviruses (p < 0.05). The number of urban arboviral cases was 84 times higher than reported.
Conclusions
The underreporting of arbovirus cases in the evaluated area reveals a substantial deficiency in epidemiological surveillance. Addressing these gaps is crucial for effective resource allocation and implementation of public health interventions.
Causal relationship between body mass index and risk of pancreatitis: a Mendelian randomisation study
Authors: Liu Rongfei , Lu Jiamin , Shao Xupeng , Xie Na , Xing Shuai , Fan Kailiang 
Published: August 2024

Abstract

Objective
The aim of the study was to investigate whether body mass index (BMI) is causally related to pancreatitis, and to guide patients with potential pancreatitis to control their weight and prevent pancreatitis.
Methods
Weighted median, MR-Egger regression, and inverse variance weighting (IVW) were accessed using a two-sample Mendelian randomization (MR) analysis. In the Genome-Wide Association Study (GWAS) meta-analysis, we used the publicly available summary statistics set of BMI in individuals of European ancestry (n = 681,275) (GIANT Alliance) as the exposure, and as the outcome, we used the self-reported non-cancer disease codes: pancreatitis in individuals from the European Biobank (n = 462, 933).
Results
Selecting 220 single nucleotide polymorphisms (SNPs) for BMI was done using the GWAS instrumental variable (IV). The IVW method's results show that pancreatitis and BMI are causally related (beta = 0.0011, SE = 0.0004, p = 0.0137). Although orientational polyvalency was not expected to skew the data (intercept = 1.24E-05; p = 0.511), MR-Egger regression did not reveal a causal relationship between pancreatitis and BMI (beta = 0.0003, SE = 0.0013, p = 0.7941). Furthermore, there was no evidence of a link between pancreatitis and BMI using the weighted median approach (β = 0.0006, SE = 0.0008, p = 0.4296). There was no indication of heterogeneity or asymmetry in the funnel plot or the Cochran's Q test, indicating the absence of directed pleiotropy.
Conclusion
The hypothesis that a higher incidence of pancreatitis may be partially attributed to BMI is supported by the MR study.
Correcting Scale Distortion in RNA Sequencing Data
Authors: Thron Christopher , Jafari Farhad 
Published: August 2024

Abstract

RNA sequencing (RNA-seq) is the conventional genome-scale approach used to capture the expression levels of all detectable genes in a biological sample. This is now regularly used in the clinical diagnostic space for cancer patients. While the information gained is intended to impact treatment decisions, numerous technical and quality issues remain. This includes inaccuracies in the dissemination of gene-gene relationships. For such reasons, clinical decisions are still mostly driven by DNA biomarkers, such as gene mutations or fusions. In this study, we aimed to correct for systemic bias based on RNA-sequencing platforms in order to improve our understanding of the gene-gene relationships. To do so, we examined standard pre-processed RNA-seq datasets obtained from three studies conducted by two consortium efforts including The Cancer Genome Atlas (TCGA) and Stand Up 2 Cancer (SU2C). We particularly examined the TCGA Bladder Cancer (n = 408) and Prostate Cancer (n = 498) studies as well as the SU2C Prostate Cancer study (n = 208). Using various statistical tests, in all datasets we detected expression-level dependent biases that differ from sample to sample. Using simulations, we show that these biases corrupt gene-gene correlation estimations and t-tests between subpopulations. To mitigate these biases, we introduce two different nonlinear transforms based on statistical considerations that correct these observed biases. We demonstrate that that these transforms effectively remove the observed per-sample biases, reduce sample-to-sample variance, and improve the characteristics of gene-gene correlation distributions. Using a novel simulation methodology that creates controlled diffferences between subpopulations, we show that these transforms reduce variability and slightly increase sensitivity of two population tests. Altogether, these results improve our capacity to understand gene-gene relationships, and may lead to novel ways to utilize the information derived from clinical tests.
Demographic and Socio-economic Correlates of Nutrition Status of Adult Cancer Patients: A Case of Texas Cancer Center, Kenya
Authors: ODUOR ELIZABETH ACHIENG , ODONGO ALFRED OWINO , KIBOI WILLY 
Published: August 2024

Abstract

Background
Cancer has become a serious global health threat following its increasing incidence and prevalence rates. The study's objective was to establish any existing relationships between demographic and socio-economic characteristics and the nutrition status of adult cancer patients. This was aimed at gathering more data for evidence-based interventions to establish factors that influence nutrition status among cancer patients, given only the existence of scanty information on the same.
Methods
In this cross-sectional study, 384 patients were randomly selected. Data on demographic and socio-economic characteristics was collected through interviewer-administered questionnaires. Nutrition status data was determined through body mass index which was computed from the weight and height measurements. Chi-square and logistic regression were used to assess the correlates of nutrition status.
Results
The study revealed that 41% (n = 157) of participants had optimal nutrition. The mean BMI was 25.0kg/m2 ± 4.25SD, with 17% being underweight, 28% overweight, and 14% obese. The majority of the participants, 89% (n = 343), were above 36 years and 66% (n = 254) were female. Those with secondary education had the highest frequency 41% (n = 158). The monthly household income category with the highest number of respondents was less than 15,000 Kenya shillings (n = 196; 51%), while most of the study participants, 54% (n = 209), had household sizes of 4–6. Factors found to be associated with the participants' nutrition status included age (AOR = 6.73; 95% CI = 1.88–24.11; p-value = 0.003), occupation status (AOR = 2.57; 95% CI = 1.42–4.68; p-value = 0.002), sex (AOR = 2.64; 95% CI = 1.33–5.26; p-value = 0.006), household size (AOR = 1.79; 95% CI = 1.03–3.12; p-value = 0.039), and level of education (AOR = 10.81; 95% CI = 1.29–90.66; p-value = 0.028).
Conclusion
This study found that malnutrition was common among the study participants, and this could be a result of low income among the families and intake of low nutrients. Therefore, approaches such as increasing the availability, affordability, and accessibility of nutrient-dense foods are key when designing and prioritizing interventions.