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Phenome-wide association study and functional annotation of hemoglobin A1c-associated variants in African populations
Background Glycated hemoglobin (HbA1c) measures the average blood sugar level over the past three months. As a vital biomarker of blood glucose levels, it is used to diagnose Type-2 diabetes mellitus (T2D) and monitor glycemic control. A heritability estimate of 47% to 59% suggests that about half of the variation in HbA1c levels can be attributed to genetic factors. Despite African populations being the most genetically diverse and unique for fine-mapping, there is a paucity of data on the genetic drivers of HbA1c in African individuals. In this study, we performed functional annotation and a Phenome-Wide Association Study (PheWAS) of HbA1c-associated variants in two African populations. Method In this study, we utilized summary statistics of the HbA1c GWAS meta-analysis of 7,526 individuals from South Africa and Uganda to conduct a PheWAS using GWASATLAS. We also performed a functional analysis using the functional mapping and annotation (FUMA) tool. Single nucleotide polymorphisms (SNPs) were prioritized using the SNP2GENE function, while the gene expression patterns and shared molecular functions were explored in the GENE2FUNC. Result Three genome-wide significant loci were identified with the lead SNPs: rs6724428, rs148228241, and rs8045544 – mapped to GULP1, HBA1, and ITFG3 genes, respectively. The minor allele frequencies of rs148228241 (0.07) and rs8045544 (0.19) are rare or non-existent in non-African populations. Both rs8045544 and rs148228241 are significantly associated with the mean corpuscular hemoglobin concentration (MCHC). A lower MCHC is associated with alpha thalassaemia, resulting from deletions in HBA1 and HBA2 genes. Such deletions are prevalent in malaria-endemic regions of Africa due to their selective survival advantage. The rs6724428 variant is associated with skeletal functions, reflecting the link between glucose metabolism and bone mineral density. Discussion Our findings highlight the interplay between glucose metabolism, erythropoiesis, and skeletal health. The significant associations of HbA1c-variants with both skeletal function and MCHC underscore the potential of these variants to impact broader physiological processes. A large-scale study of African individuals will be essential to unravel genetic variants influencing HbA1c.
Gait assessment using a 2D video-based motion analysis app in healthy subjects and subjects with lower limb amputation – A pilot study
Introduction Although three-dimensional marker-based motion analysis is the gold standard for biomechanical investigations, it is time-consuming and cost-intensive. The conjunction of monocular video recordings with pose estimation algorithms addresses this gap. With the Orthelligent VISION app (OPED GmbH) a commercial and easy-to-use tool is now available for implementation in everyday clinical practice. The study investigates the accuracy of the 2D video-based system in measuring joint kinematics, expressed as range of motion, compared to an optoelectronic 3D motion analysis system as the gold standard. Materials and methods Its accuracy was determined by synchronously measuring ten healthy subjects with Orthelligent and the optoelectronic 3D motion analysis system Qualisys (Qualisys AB) during level walking and at different treadmill walking speeds (1 m/s; 1.4 m/s; 1.8 m/s). Range of motion (RoM) of lower limb joints and time-distance parameters were compared using Bland-Altman plots, t-tests, and correlations between systems. Kinematic outputs of two subjects with a lower limb amputation were also analyzed. Results The mean RoM deviation was smaller for the knee (3.8°) and hip joints (3.7°) than for the ankle joint (5.4°), but differed significantly between systems in most conditions. The correlation range was 0.36 ≤ r ≤ 0.83, with best results for 1 m/s treadmill walking (mean r = 0.71 across joints). While the accuracy was affected by high inter-subject variability, individual RoM changes from slow to fast walking did not differ between the systems. The kinematics of the prosthetic and sound leg of individuals with an amputation exhibited characteristic patterns in the video-based system, even though side differences were smaller compared to the optoelectronic measurement. Conclusions The rather high inter-subject variability would make future comparisons between individuals challenging. Nonetheless, the app shows potential for intra-subject progress monitoring.
Role of blood Krebs von Lungen-6 in predicting acute exacerbation in patients with idiopathic pulmonary fibrosis
Background This study evaluated the role of blood Krebs von den Lungen-6 (KL-6) in predicting acute exacerbation (AE) in patients with idiopathic pulmonary fibrosis (IPF). Methods From April 2018 to March 2023, clinical data of 233 IPF patients with baseline and follow-up KL-6 values at Haeundae Paik Hospital were retrospectively analyzed. AE was defined following the criteria proposed by Collard et al. in 2016. Results The mean age was 71.8 years; 79% were male. During follow-up (median: 18.7 months), 33 (14.2%) patients experienced AE. Throughout the entire period from baseline, KL-6 values were higher in the AE group compared to the non-AE group (P < 0.001), and the patterns of change over time also showed significant differences between both groups (P < 0.001). The KL-6 values in the post-exacerbation phase were higher than those in the pre-exacerbation phase among the AE group (P = 0.004). The AE group showed lower 1-year (86.4% vs. 95.9%) and 3-year (50.2% vs. 91.4%) survival rates compared to the non-AE group (P < 0.001). The occurrence of AE (hazard ratio (HR) 74.09, 95% confidence interval (CI) 31.97–171.7, P < 0.001) and higher lactate dehydrogenase (HR 1.02, 95% CI: 1.01–1.02, P < 0.001) were independently associated with mortality in patients with IPF Conclusions Our data suggest that the trend in changes in KL-6 values may be utilized as a tool for predicting AE-IPF. Further research is needed to establish the clinical significance of changes in KL-6 for predicting AE-IPF and to validate the cut-off values for prediction.
Optimization of non-smooth functions via differentiable surrogates
Mathematical optimization is fundamental across many scientific and engineering applications. While data-driven models like gradient boosting and random forests excel at prediction tasks, they often lack mathematical regularity, being non-differentiable or even discontinuous. These models are commonly used to predict outputs based on a combination of fixed parameters and adjustable variables. A key transition in optimization involves moving beyond simple prediction to determine optimal variable values. Specifically, the challenge lies in identifying values of adjustable variables that maximize the output quality according to the model’s predictions, given a set of fixed parameters. To address this challenge, we propose a method that combines XGBoost’s superior prediction accuracy with neural networks’ differentiability as optimization surrogates. The approach leverages gradient information from neural networks to guide SLSQP optimization while maintaining XGBoost’s prediction precision. Through extensive testing on classical optimization benchmarks including Rosenbrock, Levy, and Rastrigin functions with varying dimensions and constraint conditions, we demonstrate that our method achieves solutions up to 40% better than traditional methods while reducing computation time by orders of magnitude. The framework consistently maintains near-zero constraint violations across all test cases, even as problem complexity increases. This approach bridges the gap between model accuracy and optimization efficiency, offering a practical solution for optimizing non-differentiable machine learning models that can be extended to other tree-based ensemble algorithms. The method has been successfully applied to real-world steel alloy optimization, where it achieved superior performance while maintaining all metallurgical composition constraints.
GDFGAT: Graph attention network based on feature difference weight assignment for telecom fraud detection
In recent years, the number of telecom frauds has increased significantly, causing substantial losses to people’s daily lives. With technological advancements, telecom fraud methods have also become more sophisticated, making fraudsters harder to detect as they often imitate normal users and exhibit highly similar features. Traditional graph neural network (GNN) methods aggregate the features of neighboring nodes, which makes it difficult to distinguish between fraudsters and normal users when their features are highly similar. To address this issue, we proposed a spatio-temporal graph attention network (GDFGAT) with feature difference-based weight updates. We conducted comprehensive experiments on our method on a real telecom fraud dataset. Our method obtained an accuracy of 93.28%, f1 score of 92.08%, precision rate of 93.51%, recall rate of 90.97%, and AUC value of 94.53%. The results showed that our method (GDFGAT) is better than the classical method, the latest methods and the baseline model in many metrics; each metric improved by nearly 2%. In addition, we also conducted experiments on the imbalanced datasets: Amazon and YelpChi. The results showed that our model GDFGAT performed better than the baseline model in some metrics.
Antimicrobial-resistance of Escherichia coli in dogs and cats: A scoping review
Pathogenic Escherichia coli causes a range of clinical manifestations in dogs and cats, and the use of antimicrobials in pets is associated with the risk of antimicrobial resistance (AMR). Pets contribute to the dissemination of AMR both within their species and to humans. This study conducts a scoping review to assess the existing evidence on the AMR of E. coli in dogs and cats, noting the purpose of antimicrobial susceptibility testing (AST) and determining the knowledge gaps to inform future research. The search utilized specific and generic strings aligned with the research objectives, spanning databases such as MEDLINE®, Web of Science, Biological Science Collection, AGRICOLA, CAB Direct, and Google Scholar, from January 1990 to July 2023. The study selection included only articles published in English and related to primary research. Following deduplication, the initial search identified 1,205 studies. After a detailed full-text review, 108 independent studies were identified. Studies on the AMR of E. coli in companion animals are largely concentrated in North America and Western Europe. Most of the studies were observational and were conducted in veterinary clinics. AST was primarily conducted to guide the antimicrobial treatment of E. coli infections in pets. Although not all studies provided clinical histories, among those that did, multi-drug resistant (MDR) E. coli was reported in both healthy and ailing pets. The detection of MDR E. coli in healthy and sick pets serve as a clarion call for antimicrobial stewardship. However, the limited number of studies dedicated to AMR monitoring and surveillance programs for companion animals raises a substantial concern.
Identifying genes and traits associated with pre-eclampsia using summary statistics
The occurrence and development of pre-eclampsia (PE) is closely related to genetics. However, multi-omics analysis does not provide sufficient evidence to define significant genes. Therefore, we aimed to identify significant genes and pathways using summary statistics from genome-wide association studies (GWAS). Based on the summary statistics, we used linkage disequilibrium score regression (LDSC) to discover genetic correlation between PE and complex traits. Leveraging summary statistics of tissue-specific expression quantitative trait loci (eQTL), we used FUSION to define significant genes, Bayesian colocalization analysis to identify pleiotropic genes, and Multi-marker Analysis of GenoMic Annotation (MAGMA) to determine the associated pathways. Specifically, considering the potential relationship between PE and tissues, we included 11 tissues, such as kidney cortex. Our integrative analysis revealed that the observed heritability of PE was 0.0179 (standard error [SE] = 0.0021, P-value < 0.001). Also, based on the Bonferroni correction, we defined 238 traits genetically correlated to PE, such as the other cardiovascular diseases (r = −0.55) and furosemide (r = 0.79). Integrating eQTL summary statistics across eleven tissues, we identified 30 significant genes, such as EIF2S1 in the uterus (TWAS. Z = 4.44, TWAS. P = 8.95 × 10−6), and PAWRP2 in ovary (TWAS. Z = 4.34, TWAS. P = 1.45 × 10−5). Based on colocalization, we identified 26 pleiotropic genes. We found that three genes, including RPS26, SULT1A2, OBSCN-AS1, and SUOX, were simultaneously defined by FUSION and colocalization. Moreover, we found that the significant enrichment was in the FOXG1_TARGET_GENES pathway regulated by the transcription factor FOXG1 (PFDR = 0.049). The findings of post-GWAS analysis for PE indicate that there are 30 significant genes and 26 pleiotropic genes. Future studies are required to investigate the efficacy of targeting pleiotropic genes to reduce the risk of PE.
Numerical simulation study on optimization of key technical parameters of unpowered dust removal system in a gas-solid two-phase flow field
Based on the engineering background of the Huaibei Coal Preparation Plant in Anhui Province, China, this study aims to effectively mitigate dust pollution during the blanking process at coal transfer points. Given the limitations of conventional dust control measures, a numerical simulation was conducted using the Euler model and discrete element method (DEM) for simulating particulate matter. The simulation incorporated the two-way coupling effect between gas-solid two-phase flow and the collision-adhesion dynamics among particles. We examined the migration behavior of dust within an unpowered dust removal system under various technical parameters. Results indicate that installing a return pipe significantly reduces dust overflow caused by impact airflow during blanking. Specifically, when the return pipe diameter is 500 mm, and the horizontal distance between the drainage port of the return pipe and the bottom of the blanking pipe is 2000 mm, the dust removal efficiency reaches its optimal level. Field tests confirmed that after implementing the improved dust removal system, the ambient air dust concentration decreased to less than 2 mg/m³, representing a reduction of approximately 92.02% compared to pre-transformation levels. This approach overcomes the limitations of traditional dust prevention technologies, inhibits dust generation at its source within the coal conveying system, effectively reduces working space dust concentrations, and ensures occupational health and safety for workers.
Schistosoma mansoni infection causes consistent changes to the fecal bacterial microbiota of mice across and within sites
Eggs of Schistosoma mansoni are produced by adult female worms in mesenteries of infected hosts. Eggs can cross the intestinal barrier and form granulomas in the tissue or breach and exit the host through fecal excretion. These interactions may affect the host microbiome assemblages. Given the potential for schistosomal alteration of host gut microbiome and subsequent effects on the fecal bacterial composition, it is important to conduct controlled microbiome studies on model animals. While pursuing these studies, it is important to take into account the different conditions in which microbiome studies are conducted and their consequent impacts on variability and reproducibility of results. In particular, we are interested in inter-institutional effects on controlled microbiome studies, in which the study location itself may impact study outcomes. In this work, we report global changes caused by acute and chronic schistosomiasis on the fecal microbiome of mice at two different institutions and three timepoints.
T7 RNA polymerase-based gene expression from a transcriptionally silent rDNA spacer in the endosymbiont-harboring trypanosomatid Angomonas deanei
Eukaryotic life has been shaped fundamentally by the integration of bacterial endosymbionts. The trypanosomatid Angomonas deanei that contains a β-proteobacterial endosymbiont, represents an emerging model to elucidate initial steps in symbiont integration. Although the repertoire of genetic tools for A. deanei is growing, no conditional gene expression system is available yet, which would be key for the functional characterization of essential or expression of toxic proteins. Development of a conditional expression system based on endogenous RNA polymerase II (POLII) is hampered by the absence of information on transcription signals in A. deanei as well as the unusual genetic system used in the Trypanosomatidae that relies on read-through transcription. This mode of transcription can result in polar effects when manipulating expression of genes in their endogenous loci. Finally, only a few resistance markers are available for A. deanei yet, restricting the number of genetic modifications that can be introduced into one strain. To increase the range of possible genetic manipulations in A. deanei , and in particular, build the base for a conditional expression system that does not interfere with the endogenous gene expression machinery, here we (i) implemented two new drug resistance markers, (ii) identified the spacer upstream of the rDNA array on chromosome 13 as transcriptionally silent genomic locus, and (iii) used this locus for engineering an ectopic expression system that depends on the T7 RNA polymerase expressed from the δ-amastin locus. We show that transgene expression in this system is independent of the activity of endogenous RNA polymerases, reaches expression levels similar to the previously described POLII-dependent expression from the γ-amastin locus, and can be applied for studying endosymbiosis. In sum, the new tools expand the possibilities for genetic manipulations of A. deanei and provide a solid base for the development of an ectopic conditional expression system.
Deep learning reconstruction of free-breathing, diffusion-weighted imaging of the liver: A comparison with conventional free-breathing acquisition
This study aimed to compare image quality and solid focal liver lesion (FLL) assessments between free-breathing, diffusion-weighted imaging using deep learning reconstruction (FB-DL-DWI) and conventional DWI (FB-C-DWI) in patients undergoing clinically indicated liver MRIs. Our retrospective study included 199 patients who underwent 3 T-liver MRIs with FB-DL-DWI and FB-C-DWI. DWI was performed using a single-shot, spin-echo, echo-planar, fat suppression technique during free-breathing with matching parameters. Three radiologists independently evaluated subjective image quality across two sequences. The apparent diffusion coefficient (ADC) was measured in 15 liver regions. Four radiologists analyzed 138 solid FLLs from 60 patients for the presence of diffusion restriction, lesion conspicuity, and sharpness. Among the 199 patients, 110 (55.3%) had underlying chronic liver disease (CLD). FB-DL-DWI was found to be 43.0% faster than FB-C-DWI (119.4 ± 2.2 sec vs. 209.6 ± 3.7 sec). Furthermore, FB-DL-DWI scored higher than FB-C-DWI for all subjective image quality parameters (all, P < 0.001); however, FB-DL-DWI exhibited greater artificial sensation than FB-C-DWI (P < 0.001). In patients with CLD, FB-DL-DWI exhibited a better subjective image quality (all, P < 0.001) than FB-C-DWI. ADC values ranged from 1.06–1.12 × 10-3 mm2/sec in FB-DL-DWI and 1.06–1.20 × 10-3 mm2/sec in FB-C-DWI. Among the 138 lesions analyzed, 116 malignancies (61 hepatocellular carcinomas, 3 cholangiocarcinomas, 52 metastases) and 22 benignities were included. Four readers identified 88, 93, 93, and 105 diffusion-restricted FLLs in FB-DL-DWI and 84, 80, 98, and 95 in FB-C-DWI. FB-DL-DWI (75.9–90.5%) demonstrated comparable or superior diffusion restriction rates for malignant FLLs compared to FB-C-DWI (68.1–82.8%). Furthermore, FB-DL-DWI presented higher lesion-edge sharpness and lesion-conspicuity compared to FB-C-DWI. Overall, FB-DL-DWI provided better image quality, lesion sharpness, and conspicuity for solid FLLs, with a shorter acquisition time than FB-C-DWI. Therefore, FB-DL-DWI may replace FB-C-DWI as the preferred imaging method for liver evaluations.
A framework for identifying calcium accumulation problem in cropland: Integrating field surveys, legacy soil map, and machine learning models
The calcium accumulation problem (CAP) in cinnamon soil regions of northern China significantly impacts crop yields. Identifying and mitigating CAP is crucial for improving soil quality and agricultural productivity. This study, based on field research in Aohan Banner, Chifeng City, utilizes legacy soil maps to construct a CAP dataset and evaluates the predictive performance of several machine learning models. The influence of topography on CAP is also analyzed. Key findings include: (1) In the study area, CAP predominantly manifests as block formations in dry land. Of the surveyed farmers, 58% report CAP in their cropland, with 84% noting reduced yields, though 76% have not implemented any specific mitigation measures. (2) Evaluation of machine learning models shows that tree-based models (BRT and XGBoost) outperform others in predicting CAP, with BRT demonstrating superior mapping capabilities. (3) Spatial analysis reveals that CAP is more common in the eastern and central regions of Aohan Banner, particularly in terrains such as slopes, ridges, and peaks. Additionally, the cold-to-hot zone ratio increases significantly as terrain transitions from dry to humid. (4) Regression analysis shows a strong negative correlation between terrain variables (e.g., MRVBF and GEO) and the likelihood of CAP. A further analysis indicates that CAP is more likely to occur in areas with higher soil erosion risk. These findings provide valuable insights for identifying CAP in regional soil mapping and for guiding future research in this area.
Educational video combined with augmented clinical support to improve CPAP use in patients with obstructive sleep apnea-hypopnea syndrome: A randomized controlled trial protocol
Background Poor patient adherence to continuous positive airway pressure (CPAP) remains a common challenging issue and a major cause of treatment failure in patients with obstructive sleep apnea-hypopnea syndrome (OSAHS). Our study aims to test the hypothesis that therapeutic patient education (TPE) combined with augmented clinical support (ACS) at CPAP initiation would improve CPAP adherence and treatment outcomes compared to usual care. Patients and methods We will perform a prospective, randomized, controlled, parallel-group trial including 60 adult patients newly diagnosed with severe OSAHS. Each patient will be randomly assigned to either the TPE group or the usual care group and then scheduled to start CPAP therapy within 1–2 weeks after the nocturnal polygraph recording. For the TPE group, CPAP initiation will be performed at the hospital during a 3-hour educational session that will include 4 workshops entitled: “What’s OSAHS”, “CPAP machine: what is it? How does it work? And what does it serve for?”, “How to use your CPAP and fit your mask” and “How to deal with CPAP side effects”. The educational team will include a sleep disorders specialist, a sleep nurse, and a CPAP technician. As educational tools, we will use a short storytelling video in the local language, live demonstrations and a daily desk calendar with 60 removable sheets and 1 tip on CPAP therapy on each sheet. Patients assigned to the usual care group will undergo CPAP initiation at home under the guidance of a CPAP technician and will not receive additional educational support beyond the documents provided by the manufacturers. Our primary outcome is unadjusted CPAP adherence measured in hours/night at 1, 3, and 6 months after CPAP initiation. Our secondary outcome is functional status at the 6-month follow-up, which included snoring, nasal obstruction symptoms, subjective quality of life, fatigue, emotional status, cognitive function, insomnia and excessive daytime sleepiness (EDS). Conclusion We designed this original protocol by combining TPE with ACS. We hope that our findings will help us improve CPAP adherence among Tunisian patients with OSAHS.
Thymoquinone loaded on chitosan nanoparticles alleviated the consequences of cryptosporidiosis infection in a murine model: Evidence from parasitological, histopathological, immunohistochemical, and immunological studies
Background Cryptosporidiosis, a parasitic zoonosis caused by the genus Cryptosporidium (C.), currently lacks a vaccine or fully effective treatment. Nitazoxanide (NTZ), the only medication approved by the US Food and Drug Administration for treating cryptosporidiosis, exhibits limited efficacy in immunosuppressed hosts. Thymoquinone (THQ), the active component of Nigella sativa, possesses immunomodulatory, antitumor, hepatoprotective, antioxidant, antimicrobial, and antiprotozoal properties. This study evaluated the therapeutic effects of THQ alone or loaded onto chitosan nanoparticles (CsNPs) against Cryptosporidium parvum infection compared to NTZ. Methods Chitosan nanoparticles were synthesized and characterized using X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), zeta potential analysis, and scanning electron microscopy. The cytotoxicity of CsNPs, THQ/CsNPs, and NTZ/CsNPs was evaluated on HT-29 cells. Mice were divided into seven groups to assess treatment efficacy through parasitological analysis of oocyst shedding, histopathological examination of intestinal, hepatic, and splenic tissues, immunohistochemical analysis using cyclin D1 staining of intestinal tissue, and immunological analysis measuring IFN-γ and IL-10 cytokine levels. Additionally, pharmacokinetic profiles of THQ and NTZ in free and nanoparticle-loaded forms were analyzed. Results XRD confirmed changes in peak position, shape, and intensity following the loading of THQ and NTZ into CsNPs. FTIR spectra demonstrated distinct differences in peak patterns between loaded nanoparticles and individual components, confirming successful drug encapsulation. Moreover, cytotoxicity studies showed dose-dependent effects on cell viability, with NTZ/CsNPs exhibiting the highest cytotoxicity. Regarding oocyst shedding reduction, THQ demonstrated greater efficacy than NTZ (77% vs. 54%), which was further enhanced when loaded onto CsNPs (89% for THQ/CsNPs vs. 78% for NTZ/CsNPs). Histopathological analysis revealed the restoration of structural alterations in intestinal, hepatic, and splenic tissues in treated groups. Cyclin D1 immunohistochemical staining showed a significant reduction in immunoreactivity in the THQ/CsNP-treated group compared to other treatments. Furthermore, immune responses were modulated by nanoparticle therapies, with significantly lower IFN-γ levels and higher IL-10 levels in treated groups. Pharmacokinetic analysis demonstrated that CsNP formulations significantly improved drug bioavailability by achieving higher peak plasma concentrations (Cmax), earlier time to peak concentration (Tmax), and prolonged half-life (t1/2) compared to free drugs. Conclusion Thymoquinone demonstrated significant potential as an anti-cryptosporidiosis therapeutic agent, with enhanced efficacy when loaded onto chitosan nanoparticles. Chitosan-based nanoparticle formulations improved the pharmacokinetic profiles of both THQ and NTZ, offering a promising strategy for enhancing drug bioavailability and retention while reducing parasitic burden and modulating immune responses effectively.
EODA: A three-stage efficient outlier detection approach using Boruta-RF feature selection and enhanced KNN-based clustering algorithm
Outlier detection is essential for identifying unusual patterns or observations that significantly deviate from the normal behavior of a dataset. With the rapid growth of data science, the prevalence of anomalies and outliers has increased, which can disrupt system modeling and parameter estimation, leading to inaccurate results. Recently, deep learning-based outlier detection methods have gained significant attention, but their performance is often limited by challenges in parameter selection and the nearest neighbor search. To overcome these limitations, we propose a three-stage Efficient Outlier Detection Approach (named EODA), that not only detects outliers with high accuracy but also emphasizes dataset characteristics. In the first stage, we apply a feature selection algorithm based on the Boruta method and Random Forest to reduce the data size by selecting the most relevant attributes and calculating the highest Z-score of shadow features. In the second stage, we improve the K-nearest neighbors algorithm to enhance the accuracy of nearest neighbor identification in the clustering phase. Finally, the third stage efficiently identifies the most significant outliers within clustered datasets. We evaluate the proposed EODA algorithm across eight UCI machine-learning repository datasets. The results demonstrate the effectiveness of our EODA approach, achieving a Precision of 63.07%, Recall of 82.49%, and an F1-Score of 64.53%, outperforming the existing techniques in the field.
Constraining the population size estimates of the pre-Columbian Casarabe Culture of Amazonian Bolivia
The capacity of Amazonian environments to support large indigenous societies prior to European Contact has long been a contentious area of debate, particularly in regions where pre-Columbian cultures are known to have constructed large, spatially complex earthworks. Here, we provide the first range of supported population estimates for the Casarabe Culture of the Bolivian Llanos de Moxos – one of the most complex pre-Columbian societies yet documented in Amazonia. Between 400 and 1400 CE, the Casarabe Culture inhabited this forest-savanna mosaic landscape, where they constructed hundreds of monumental habitation mounds, integrated by a dense network of causeways and canals, suggesting the former presence of a large, sedentary society. To estimate the population size of this culture, we employed a multifaceted modelling approach – including architectural energetics, maximum carrying capacity, and agent-based modelling – which considers: (i) the number of people needed to build these earthworks; (ii) how many people the local environment could support; and (iii) how their population grew and spread over time. Our results indicate that the Casarabe Culture likely grew to a maximum population of between 10,000 and 100,000 people within a 5020 km2 quadrant of their former territory, representing a density of between 2 and 20 people km-2. These values are considerably larger than both the modern rural population density and the indigenous carrying capacity estimates made for Amazonia more widely, and they support previous interpretations that this culture practiced a form of low-density urbanism.
Identifying functional roles and pathways of shared mutations in canine solid tumors by whole-genome sequencing
Identifying genetic mutations contributing to solid tumors by altering the biological pathways related to tumor formation and development is essential for the development of targeted therapies. This study aimed to identify commonly mutated genes and altered pathways in canine solid tumors. Four dogs with different types of naturally occurring neoplasias (urothelial carcinoma, adenocarcinoma, rhabdomyosarcoma, and chondrosarcoma) were randomly selected and classified into carcinoma and sarcoma groups based on histopathological findings. Tumor tissues were analyzed using whole-genome sequencing, and significant variants shared within each tumor group were identified. Gene set enrichment analyses were conducted to compare the biological and functional pathways altered by the mutations in each carcinoma and sarcoma group. Forty-three and fifty-eight genes were identified in the carcinoma and sarcoma groups, respectively. Distinctions between the two tumor groups were noted for mutations related to tumor metastatic function. Mutations were identified in genes encoding cell adhesion molecules in the carcinoma group, whereas significant variations in extracellular matrix-related molecules were evident in the sarcoma group. This study revealed mutations and modified pathways associated with immune and tumor metastatic functions in canine carcinoma and sarcoma, indicating their significant relevance to the development and progression of each tumor group. Additionally, the distinctions indicated that different therapeutic approaches were required for each tumor group.
Pre-exercise health screening in the UAE: A necessity or barrier to engage in physical activity?
Background Sedentary lifestyles contribute to the rise of non-communicable diseases, making physical activity (PA) crucial for public health. Pre-exercise screening is an important tool for ensuring safety, but its utilization and the factors influencing its adoption need further exploration. Objective This study assesses the utilization of pre-exercise screening among physical activity facility users in the UAE, identifying sociodemographic and health-related factors associated with screening practices. Methods A cross-sectional study was conducted among adults aged 18 and above in the UAE. Data were collected through a self-administered questionnaire from 630 adults using PA facilities, covering socio-demographic characteristics, PA engagement, knowledge of PA benefits, and pre-exercise screening practices. Data analysis was performed using SPSS version 28 for descriptive and inferential statistics. Results Of the participants, 496 (78.7%) were unemployed, 554 (87.6%) were aged 18–34, 294 (46.7%) had bachelor’s degrees, and 522 (82.9%) were single. Females made up 52% of the respondents. Only 186 (29.5%) underwent pre-exercise screening, with 377 (59.8%) not screened and 67 (10.6%) uncertain. Associations were found between higher screening utilization and factors such as being over 30 years old (44.9%), male (33.9%), having higher education (33.5%), and being employed (40.3%). Participants with chronic health conditions, including heart disease (52.4%), chest pain (48%), and mental health problems (50%), were significantly more likely to utilize pre-exercise screening (P < 0.001). The purpose of pre-exercise screening as risk stratification was recognized by 214 (34.1%), while 257 (40.7%) understood its preventive role. Using the 2023 PARQ + , 401 (63.7%) were cleared for PA, and 229 (36.3%) required further evaluation due to medical or mental health issues. Most participants (83.4%) did not receive guidance from exercise professionals, but 74.3% favoured mandatory pre-exercise screening. Conclusions The study highlights a gap in pre-exercise screening utilization in the UAE, with significant associations to sociodemographic factors and health conditions. The findings highlight the need for increased awareness and adoption of pre-exercise screening in the UAE. Addressing knowledge gaps and implementing mandatory screening protocols could improve health literacy and safety in PA facilities.
Biocontrol of Cercospora leaf spot in sugar beet by a novel Bacillus velezensis KT27 strain: Enhanced antifungal activity and growth promotion in laboratory and field conditions
Diseases in crops are a major contributor to yield reduction and economic losses. Cercospora leaf spot (CLS), caused by Cercospora beticola, is among the most severe diseases affecting sugar beet and other crops. The increasing resistance of C. beticola to conventional chemical fungicides, along with their excessive application, exacerbates environmental pollution. This study investigates the antagonistic activity of a newly isolated strain, Bacillus velezensis KT27, against Cercospora beticola, Rhizoctonia cerealis, and Fusarium oxysporum under laboratory conditions. The bacterium’s ability to produce lipopeptides (surfactin, iturin, and fengycin) and solubilize phosphorus, potassium, and zinc was also assessed. In vitro assays revealed that B. velezensis KT27 effectively inhibited C. beticola growth (60.2%), though it exhibited lower antagonistic activity against R. cerealis (22.5%) and F. oxysporum (15.5%). The elimination of bacterial biomass by centrifugation and the use of sterile supernatant reduced antifungal activity by more than 3.5-fold for all tested fungi, highlighting the importance of direct bacterial interactions. Notably, the antagonistic effect of B. velezensis KT27 against C. beticola significantly increased when bacterial cultures were supplemented with thermally inactivated fungal biomass of C. beticola especially R. cerealis. Field experiments demonstrated the high efficacy of B. velezensis KT27 biological control agent, particularly when induced by R. cerealis. The level of CLS protection achieved with the bacterial treatment was only 9.1% lower than that obtained using a combination of three chemical fungicides. Additionally, the biocontrol agent positively influenced sugar beet growth, leading to a root yield increase of up to 15.2% compared to the untreated control. These findings highlight the potential of B. velezensis KT27 as an effective and environmentally sustainable biocontrol agent against CLS in sugar beet cultivation.
Hematological and biochemical alterations in preeclampsia: Readings from cord blood analysis
Background Preeclampsia is a serious complication of pregnancy characterized by hypertension and proteinuria that adversely affects both maternal and fetal health. This study aimed to investigate hematological and biochemical alterations in cord blood associated with preeclampsia, with a focus on hemoglobin variants and blood gas parameters. Methods A case‒control study involving 54 participants, including 24 women diagnosed with preeclampsia and 30 normotensive controls, was conducted. Cord blood samples were analyzed for total hemoglobin (Hb), blood gas, and complete blood count (CBC) indices. Statistical analyses included independent t tests for parametric data and Mann‒Whitney U tests for nonparametric data, with significance set at p < 0.05. Results The results revealed significant differences in hemoglobin concentrations, with cord blood collected from preeclamptic women exhibiting lower levels of adult hemoglobin (HbA) (64.0% ± 32.0% vs. 76.2% ± 25.7%, p = 0.004) and higher fetal hemoglobin (HbF) concentrations (35.9% ± 32.1% vs. 23.7% ± 25.6%, p = 0.004) than controls. Blood gas parameters, including pH and bicarbonate and carbon dioxide levels, were not significantly different between the groups. However, CBC results revealed a lower platelet count in the cord blood of the preeclamptic group than in the cord blood of the preeclampsia group, (213.7*103/µL ± 112*103/µL vs. 314.6*103/µL ± 70.8*103/µL, p = 0.0005). Conclusions While our study reveals significant alterations in fetal hemoglobin variants and CBC indices in the cord blood of preeclamptic pregnancies, the clinical applicability of these markers for early detection is currently limited by the inaccessibility of fetal blood before delivery. Nevertheless, these findings offer important insights into the hematological changes linked to preeclampsia. Future studies should explore the potential of detecting similar alterations in maternal blood as a more feasible and non-invasive approach for early diagnosis and risk assessment of preeclampsia.